A TWO-COLOUR REPORTER SCREEN AND APPLICATION TO CELL CYCLE

TRANSCRIPTION

By

Parminder Kainth

A thesis submitted in conformity with the requirements

for the degree of Doctor of Philosophy

Graduate Department of Molecular Genetics

University of Toronto

© Copyright by Parminder Kainth (November 2009)

 

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A two-colour reporter screen and application to cell cycle transcription

Parminder Kainth

Doctor of Philosophy (November 2009)

Department of Molecular Genetics

University of Toronto

Abstract

Development of genome-wide reagents has allowed systematic analysis of gene function.

The experimental accessibility of budding yeast makes it a test-bed for technology

development and application of new functional genomic tools and resources that pave the

way for comparable efforts in higher eukaryotes. In this Thesis, I describe a two-color GFP-

RFP reporter system I developed to assess the consequences of genetic perturbations on a

promoter of interest. The dual-reporter system is compatible with the synthetic genetic array

methodology, an approach that enables marked genetic elements to be introduced into arrays

of yeast mutants via an automated procedure. I use this approach to probe cell cycle-

regulation of histone gene transcription by introducing an HTA1 promoter-GFP reporter gene

construct into an ordered array of ~4500 yeast deletion mutants. I scored defects in reporter

gene expression for each mutant, generating a quantitative analysis of histone promoter

activity. The results of my screen motivated a number of follow-up experiments, including

chromatin immunoprecipitation, transcript profiling and genome-wide analysis of

nucleosome positions, which revealed a previously unappreciated pathway that specifies

regions of repressed chromatin in a cell cycle-sensitive manner. A novel aspect of this

 

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pathway is that it involves histone chaperones and a chromatin boundary element.

Specifically, we discovered that the histone chaperone Rtt106 works with two other

chaperones, Asf1 and the HIR complex, to create a repressive chromatin structure at histone

promoters which is bound by the protein Yta7. It was clear from previous work that Asf1

and HIR repress transcription at HTA1 and that HIR localizes to and functions through a

specific element in histone promoters. However, there was no previous data demonstrating a

role for Rtt106 in cell cycle-dependent gene transcription. In sum, I describe a new genomic

screen that I used to discover a novel pathway regulating cell cycle-dependent transcription.

While I examined histone gene expression as proof-of-principle, my screening system could

be applied to virtually any pathway for which a suitable reporter can be devised. I anticipate

this methodology will enable yeast researchers to collect quantitative data on hundreds of

gene expression pathways.

 

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Acknowledgements

I would like to take this opportunity to thank my supervisor, Dr. Brenda Andrews, for

all of her help and support with all aspects of my graduate experience. Without Brenda’s

guidance and patience, this work would not be possible. In addition to guiding me daily with

my project, Brenda gave me the opportunity to work with and meet other researchers, which

has enriched my learning experience over the past four years. I also benefitted from advice

and guidance provided by my committee members Dr. Timothy Hughes and Dr. Frank

Sicheri. I have been lucky to collaborate daily with Tim and members of his laboratory

which has been indispensible for progress with my work.

I spent the first two years of graduate school working with Holly Sassi, a Research

Associate in our laboratory who provided help and guidance during the early years of

graduate school. I would also like to acknowledge Dr. Jeffrey Fillingham, a former

postdoctoral fellow in Dr. Jack Greenblatt’s laboratory. Working with Jeff over the past two

years has been a great experience and all of his advice and instruction will not be forgotten.

The support from friends I have made in the program has enriched my experience in

the PhD program and their help along the way is greatly appreciated. Finally, I must

acknowledge the support from my family throughout my entire education.

 

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Table of Contents

Abstract……………………………………………………………………….ii-iii Acknowledgements…………………………………………………………...iv List of Tables………………………………………………………………….viii List of Figures…………………………………………………………………ix-x List of Abbreviations………………………………………………………….xi-xiii Chapter 1: Introduction……………………………………………………..1-46 1.1 Gene expression microarrays……………………………………...2-8 1.2 Chromatin immunoprecipitation followed by microarray

hybridization (ChIP-chip)………………………………………….8-16

1.3 Protein binding microarrays………………………………………..17-20 1.4 Genome-wide nucleosome occupancy……………………………..20-26 1.5 The yeast deletion array and the synthetic genetic array

(SGA) approach…………………………………………………….27-33 1.6 Reporter-based screens……………………………………………..33-39 1.7 Global cell cycle transcription……………………………………...39-45 1.8 Summary and overall significance………………………………….45-46 Chapter 2: Comprehensive genetic analysis of transcription factor pathways using a dual reporter gene system in budding yeast……………..47-69 Abstract………………………………………………………………………….48 2.1 Introduction…………………………………………………………49-52 2.2 Description of methods……………………………………………..52-60

2.2.1 Reporter system…………………………………………...52-53

 

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2.2.2 Generating an output array of GFP and RFP reporter genes in yeast deletion mutants………………………….54-57

2.2.3 Digital imaging of yeast plates…………………………..57

2.2.4 Assaying GFP and RFP fluorescence intensities from colonies arrayed on agar plates………………………….58-59 2.2.5 Quantifying fluorescence intensities from output scans….59-60

2.3 Analysis of data from a genome-wide promoter-reporter screen…..60-69

2.3.1 Using colony size data to filter dead/sick colonies from further analysis………………………………………62-63 2.3.2 Normalization of GFP and RFP intensities……………….64

2.3.3 Correlation between replicate screens and display of genome-wide data………………………………………….64-69

2.4 Concluding remarks………………………………………………….69

Chapter 3: A two-colour cell array screen reveals interdependent roles for histone chaperones and a chromatin boundary regulator in histone gene repression………………………………………………………70-114 Abstract…………………………………………………………………………...71

3.1 Introduction…………………………………………………………..72-76

3.2 Experimental Procedures……………………………………………..76-80

3.2.1 Yeast strains and plasmids………………………………….76-77

3.2.2 SGA-based Functional Genomic Screen for Regulators of HTA1 expression……………………………..78 3.2.3 qPCR Analysis of Histone Gene Expression………………..78-79

3.2.4 Chromatin Immunoprecipitation (ChIP)……………………79

3.2.5 Purification and Analysis of Rtt106-associated proteins…...80

3.2.6 Genome-wide nucleosome occupancy……………………….80

 

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3.3 Results………………………………………………………………….80-106

3.3.1 A dual-reporter functional genomic screen to discover new regulators of gene expression…………...………………80-81

3.3.2 Identification of regulators of HTA1 expression……………..81-87 3.3.3 Rtt106 represses HIR-regulated histone genes……………....88-93

3.3.4 The HTA1-HTB1 promoter region is nucleosome-free in asf1, hir1, rtt106 mutants……………………….........94-98 3.3.5 HIR/RTT106 repression at HTA1-HTB1 creates a requirement for RTT109……………………………………98-100 3.3.6 Yta7 is a boundary element within the HTA1-HTB1 locus......101-106

3.4 Discussion………………………………………………………………107-114

Summary and Future Directions………………………………………………….115-130 4.1 Summary………………………………………………………………..116-119

4.2 Future directions………………………………………………………...119-130

4.2.1 Characterizing the Rtt106/Asf1/HIR/Yta7 pathway genome-wide…………………………………………………..119-121

4.2.2 Characterizing protein domains in Rtt106 required for function with HIR……………………………………….....121-122

4.2.3 Screening overexpression arrays……………………………...123-125 4.2.4 Increasing throughput of reporter-gene analysis using pooled screens in yeast and higher eukaryotes………………..125-129

4.3 Overall significance……………………………………………………...129-130

References……………………………………………………………………………131-152

 

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List of Tables

Table 1-1: Key regulators of cell cycle transcription.  Table 2-1: Query strains and plasmids used in the two-colour promoter-reporter screening

system. Table 3-1: Strains used in this Chapter.

 

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List of Figures

Figure 1-1: A two-colour microarray experiment to identify differentially expressed genes.

Figure 1-2: Schematic of the chromatin immunoprecipitation (ChIP) approach.

Figure 1-3: Regulator-gene motifs identified from ChIP-chip analysis of transcription factors.

Figure 1-4: Schematic of a protein binding microarray experiment.

Figure 1-5: Schematic representation of genome-wide nucleosome occupancy experiment.

Figure 1-6: Gene-deletion strategy for replacing each yeast ORF with a kanamycin resistant cassette (KanMX).

Figure 1-7: The synthetic genetic array approach used for high-throughput double mutant

strain construction. Figure 1-8: A forward genetic reporter screen to identify regulators of a promoter of

interest. Figure 2-1: Overview of the dual reporter SGA methodology.

Figure 2-2: Representative fluorescence scan of a single output array plate.

Figure 2-3: Colony size distribution of yeast deletion mutants.

Figure 2-4: Pearson correlation between replicate CLN2pr-GFP screens.

Figure 2-5: Screening deletion mutants to identify regulators of the CLN2 promoter.

Figure 3-1: Reporter-Synthetic Genetic Array (R-SGA) functional genomic screen for regulators of HTA1 expression.

Figure 3-2: Rtt106, Rtt109 and Yta7 regulate histone gene expression.

Figure 3-3: Rtt106 and HIR localize to the promoter region of HTA1-HTB1.

Figure 3-4: HIR and Asf1 are required for Rtt106 localization to HTA1-HTB1.

Figure 3-5: Asf1, HIR and Rtt106 collaborate to assemble chromatin at the HTA1-HTB1 promoter.

Figure 3-6: Constitutive repression at HTA1-HTB1 creates a requirement for RTT109.

 

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Figure 3-7: Spt4, Spt5, Spt6 and FACT cross-link to the transcribed regions of HTA1 but not to the promoter region.

Figure 3-8: Yta7 localizes to the HTA1-HTB1 locus.

Figure 3-9: Yta7 creates a boundary within the HTA1-HTB1 locus.

Figure 3-10: A model describing histone chaperone mediated repression at the HTA1 locus in yeast.

Figure 4-1: Overexpression screen to identify regulators of a promoter of interest.

Figure 4-2: Reporter screening using barcoded gene disruption libraries and FACS.

 

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List of Abbreviations

α……………………….alpha

Δ…………………….....gene deletion

µg……………………...microgram

~……………………….approximately

Arg……………………..arginine

CDK……………………cyclin-dependent kinase

cDNA…………………..complementary DNA

ChIP…………………….chromatin immunoprecipitation

ChIP-chip……………….chromatin immunoprecipitation followed by microarray hybridization

ChIP-seq………………...chromatin immunoprecipitation followed by sequencing DaMP…………………...decreased abundance of messenger RNA by perturbation

DN……………………....down

DNA…………………….deoxyribonucleic acid

dSLAM………………….diploid-based synthetic lethality analysis on microarrays

FACS……………………fluorescence activated cell sorting

FAIRE…………………..formaldehyde assisted isolation of regulatory elements

GFP……………………..green fluorescent protein

H3 K56Ac………………histone H3 lysine 56 acetylation

H3 K9Ac………………..histone H3 lysine 9 acetylation

HAT…………………….histone acetyltransferase

HDAC…………………..histone deacetylase

HphMX…………………hygromycin B resistance cassette

 

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HU………………………hydroxyurea

His………………………histidine

KanMX……………........kanamycin resistance cassette

Leu………………………leucine

Lys………………………lysine

MBF…………………….Mlu1 cell cycle box binding factor

mRNA………………….messenger RNA

NAT…………………….nourseothricin

NDR…………………….nucleosome-depleted region

NEG…………………….negative

ORF…………………….open reading frame

PAC…………………….polymerase A and C

PBM……………………protein binding microarray

PCR…………………….polymerase chain reaction

PMT…………………….photomultiplier tube

Pol II……………………RNA polymerase II

pr………………………..promoter

qPCR……………………quantitative polymerase chain reaction

RFP……………………..red fluorescent protein

RNA…………………….ribonucleic acid

RNAi……………………ribonucleic acid interference

R-SGA…………………..reporter-synthetic genetic array

SBF……………………...SCB binding factor

SCB……………………...Swi4,6-dependent cell cycle box

SDS-PAGE………………sodium dodecyl sulphate polyacrylamide gel electrophoresis

 

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SGA………………….......synthetic genetic array

STAGE…………………...sequence tag analysis of genomic enrichment

TAP……………………….tandem affinity purification

TBP……………………….TATA binding protein

tdTomato………………….tandem dimer tomato

TSS………………………..transcriptional start site

UAS……………………....upstream activating sequence

URS……………………….upstream regulatory sequence

UTR……………………….untranslated region

WT…………………….......wild type

 

 

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Chapter 1

Introduction

 

 

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Proper control of gene expression is vital for virtually all aspects of cellular function.

In many cases, aberrant gene expression is apparent in various diseased states, including

many types of cancers (Weeraratna, 2005). Exploration of mechanisms of transcriptional

control in Saccharomyces cerevisiae has led to major discoveries on how gene expression is

regulated, which are generally applicable in higher organisms because of the high degree of

conservation of the transcriptional machinery (Woychik and Hampsey, 2002). Furthermore,

the relatively straightforward genetics that can be employed in yeast make it an excellent

model organism for testing and validating new technologies (Bader et al., 2003).

The development of functional genomic tools over the last decade or so has made

large-scale systematic analysis of gene function possible. Perhaps one of the most

groundbreaking advances was the development of DNA microarrays, which revolutionized

the gene expression field. Below I summarize applications and discoveries pertinent to gene

regulation that stem from DNA microarray technology, mainly in terms of key studies

carried out in yeast. I then discuss gene expression reporter screens and their application to

cell cycle transcription, a theme that forms the basis of the work carried out in this Thesis.

1.1 Gene expression microarrays

DNA chip technology has enabled transcriptional profiling of the entire complement

of cellular mRNA in parallel. The DNA probes on the microarray are covalently attached to

the support material, and can include DNA fragments (e.g cDNA microarrays) or

oligonucleotides, which can be spotted onto specific sites on the array or synthesized in situ

(Hughes et al., 2001; Ramsay, 1998 and reviewed in Hughes and Shoemaker, 2001). To

interrogate the array, sample RNA is prepared, reverse transcribed to cDNA with fluorescent

 

 

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labels and hybridized to the microarray. Because DNA probes are arranged in known

positions on the microarray, fluorescent signal captured from hybridization of labelled

sample cDNA is indicative of the presence of that particular transcript (Schena et al., 1995;

Shalon et al., 1996). An important attribute of DNA chips is that multiple fluorescent-

labelled samples can be simultaneously hybridized to the array (Schena et al., 1995; Shalon

et al., 1996). This allows, for example, differently labelled samples from a mutant strain and

a wild type strain to be hybridized to the same gene chip (Figure 1-1). In this type of two-

colour experiment, the ratio of signal intensity from the mutant strain compared to the wild

type strain can be directly compared to determine genes that are differentially expressed in a

particular mutant.

 

 

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Figure 1-1: A two-colour microarray experiment to identify differentially expressed genes. RNA is prepared from a wild type strain and a strain deleted for a particular gene of interest. The RNA is reverse transcribed to cDNA and labelled with different fluorescent dyes. The resulting cDNA from both wild type and mutant strains are hybridized to a microarray that contains oligonucleotide sequences complementary to all genes. After scanning fluorescence intensities, differentially expressed genes are identified. Yellow spots indicate equal expression of that particular gene in the mutant and wild type strain. Green indicates lower transcript levels of that gene in the mutant strain compared to wild type while red indicates higher expression of that particular gene in the mutant compared to wild type.

 

 

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Spotted cDNA or oligonucleotide arrays are advantageous because they can be

printed in-house and customized arrays can be produced that are tailored to the particular

experiment being carried out. However, these types of spotted arrays are not printed with the

same probe density as commercial arrays, which are generally made by synthesizing short

oligonucleotide probes directly on the array surface (see Lipshutz et al., 1999 for a review on

manufacturing high density arrays). In addition, arrays synthesized in situ have been shown

to generate the most reproducible results between different laboratories (Bammler et al.,

2005). Commercial arrays are available from various companies including Affymetrix and

Agilent Technologies. The Affymetrix platform requires hybridization of the labelled

experimental and control sample to different microarrays while the Agilent arrays allow two-

colour hybridization on the same array similar to the scheme shown in Figure 1-1. In tests to

determine reproducibility of microarray results between various technologies, single-colour

platforms produced data with greatest precision and Affymetrix arrays in particular were

slightly more sensitive in detecting small changes in gene expression (de Reynies et al.,

2006). However, Agilent arrays have the advantage that half as many microarrays are

required for an experiment since test and control samples are hybridized to the same array.

In pioneering work, Schena et al. (1995) showed the utility of a two-colour cDNA

microarray experiment to identify differentially expressed genes in Arabidopsis thaliana.

They showed that small amounts of initial RNA (2 µg) were required to identify 45

differentially expressed transcripts and also demonstrated the specificity of the array

hybridization by including yeast TRP4 and rat glucocorticoid receptor cDNA, which showed

no hybridization signal (Schena et al., 1995). Later, genome-scale microarrays were

produced for yeast by spotting PCR products corresponding to each ORF on glass slides and

 

 

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allowed characterization of gene expression programs in different conditions (Lashkari et al.,

1997).

Since this initial work, genome-wide expression profiling has become a common

practice in the study of gene regulation. Numerous publications catalogue genome-wide

transcriptional responses to mutations, environmental changes and drug treatment across the

spectrum of model organisms. These types of experiments generate enormous data sets that

are rich in biological information. An important publication by Hughes et al. (2000a)

highlighted the use of genome-wide expression profiling as a phenotypic readout that can be

used to assign gene function. They assembled a compendium of 300 yeast expression

profiles derived from either treatment of cells with chemicals or from assaying an array of

strains with mutations in known and uncharacterized genes (Hughes et al., 2000a). This

reference compendium of expression profiles was used to assign functions to genes based on

similarity of transcriptional responses which was determined by cluster analysis. For

example, strains with gene mutations in components of the ergosterol biosynthesis pathway

(erg2Δ, erg3Δ and tetracycline repressible-ERG11) had similar transcriptional profiles

causing the mutant strains to cluster together in the reference set, consistent with the known

role for the ERG genes in the same cellular process. Deleting the uncharacterized ORF

YER044c resulted in a transcriptional output similar to the ERG mutants, indicating that

YER044c might also participate in ergosterol biosynthesis (Hughes et al., 2000a). Follow-up

experiments revealed that YER044c (now named ERG28) mutants were defective in

ergosterol accumulation compared to wild type cells, supporting the hypothesis derived from

comparative transcriptional profiling (Hughes et al., 2000a).

 

 

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The compendium approach was also successful in identifying drug targets (Hughes et

al., 2000a). In principle, deleting a drug target should have the same phenotypic

consequence as inhibition of the target by drug treatment. Also, drugs that affect similar

cellular processes should result in similar expression profiles and thus co-cluster in a

compendium matrix. In the compendium of expression profiles, clustering was observed

among the erg2Δ mutant and cells treated with dyclonine, an anaesthetic commonly used in

throat lozenges. Dyclonine-treated cells accumulated fecosterol, indicating Erg2 function

was comprised in the presence of dyclonine, thus identifying Erg2 as the target of dyclonine

(Hughes et al., 2000a). These findings show the power of gene expression profiling for

functional discovery and highlight the utility of the compendium approach for studying gene

function.

Gene expression microarrays have also been used in clinical applications, particularly

in the study of cancers. In one study, expression profiles were generated for 13 dissected

human breast tumours (Perou et al., 1999). Variation in gene expression programs among

these different samples, compared to human mammary epithelial cells, revealed that different

breast tumours could be classified and identified based on the observed expression profiles

(Perou et al., 1999). This type of gene expression profiling has been carried out in hundreds

of different tumours and mining these data has been used to generate hypotheses about

cancer biology. For example, computational analysis of hundreds of tumour gene expression

profiles revealed a role for the transcription factor C/EBPβ in regulating genes with aberrant

expression profiles upon cyclin D1 overexpression, a common signature of many tumours

(Lamb et al., 2003).

 

 

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A general concern with data obtained from expression profiling when testing for

regulators is whether or not target genes are directly controlled by the regulator or if the

observed expression response is indirect. For example, suppose a gene expression

microarray carried out on a strain deleted for gene A reveals altered expression of gene X.

The microarray result alone cannot distinguish between direct regulation of gene X by

binding of gene product A to its promoter or an indirect mechanism that involves gene

product A binding to the promoter of another gene whose product directly regulates gene X.

To differentiate direct versus indirect regulation, it is useful to examine the location of

regulatory proteins on DNA. In the next section, I summarize assays for genome-wide

assessment of the localization of regulatory proteins.

1.2 Chromatin immunoprecipitation followed by microarray hybridization (ChIP-

chip)

Control of gene expression requires proper localization of trans-acting regulatory

factors to their cognate cis-elements in promoters of genes. Thus, an important question in

gene regulation is: what regions of DNA are occupied by transcription factors and other

proteins that regulate transcription? A biochemical approach called chromatin

immunoprecipitation (ChIP) has been applied productively to address this question (Orlando,

2000). This approach relies on immunoprecipitation of a tagged protein of interest along

with its associated proteins and DNA (Figure 1-2). Briefly, tagged proteins are cross-linked

to interacting proteins and DNA in vivo by treatment with formaldehyde, chromatin is

prepared, sheared by sonication, protein-protein and protein-DNA complexes are

immunoprecipitated, cross-linking is reversed, DNA is purified and potential target genes of

 

 

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interest are examined by PCR amplification (Orlando, 2000). Shearing of DNA to usually

less than 500 base pairs followed by immunoprecipitation with an antibody directed towards

the tagged protein allows enrichment of only those genomic regions occupied by the protein.

The advantage of this approach is that tagged proteins do not necessarily need to contact the

DNA but can be bridged by other proteins.

 

 

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Figure 1-2: Schematic of the chromatin immunoprecipitation (ChIP) approach. A tagged ORF is expressed and formaldehyde treatment cross-links protein-DNA interactions. Chromatin is prepared, sheared and the tagged protein is immunoprecipitated using an antibody that recognizes the protein tag. In parallel a control input DNA sample is prepared. The cross-link is reversed, DNA is purified and the population of DNA immunoprecipitated with the protein of interest is characterized by PCR analysis of specific regions of the DNA or the entire complement of immunoprecipitated DNA could be determined by comparing the microarray hybridization signal to the control input DNA signal (ChIP-chip).

 

 

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In early work, formaldehyde-mediated cross-linking of proteins to DNA followed by

immunoprecipitation led to insights into the chromatin structure of highly transcribed genes.

Studies in Drosophila melanogaster revealed that perturbed chromatin structure underlies

heat shock-mediated induction of the HSP70 gene (Solomon et al., 1988). Upon heat shock,

fewer proteins were found to cross-link to the transcribed region. This was consistent with

the notion that actively transcribed genes are devoid of histones, likely to allow RNA

polymerase passage and transcriptional elongation. However, the rate of transcription did

not influence histone H4 cross-linking efficiency to the region providing evidence that not all

transcribed genes are depleted of histones, which contested the general view at the time

(Solomon et al., 1988).

The development of DNA chip technology (discussed above), combined with the

ChIP approach, provides the tools to carry out genome-wide protein-promoter localization

studies. In early experiments, DNA chips were produced with probes complementary to

known intergenic or promoter regions, in contrast to the cDNA chips used to characterize the

complement of mRNA transcripts. The immunoprecipitated DNA from a ChIP experiment

is then hybridized to intergenic DNA chips to identify all of the promoter regions a particular

protein cross-links to genome-wide, an approach known as ChIP-chip (Figure 1-2). ChIP-

chip experiments were reported in Saccharomyces cerevisiae, whereby the genomic

localization of the DNA binding proteins Gal4 and Ste12 (Ren et al., 2000), as well as MBF

and SBF (Iyer et al., 2001) (see Section 1.7) was determined. These studies described the

ChIP-chip methodology and showed that target genes of DNA-associated proteins could be

identified. The Gal4 transcriptional activator, which activates genes involved in galactose

metabolism when cells are grown in galactose, bound 10 genes (Ren et al., 2000). Seven of

 

 

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these genes were previously characterized targets of Gal4 while 3 were new (Ren et al.,

2000). The localization of Ste12, a protein that is required for induction of >200 genes upon

activation of the pheromone response pathway, revealed that 29 of these genes are bound by

Ste12 (Ren et al., 2000). In future work, Ste12 localization was revisited using advanced

sequencing technologies or microarrays and identified hundreds of Ste12 binding sites

(Borneman et al., 2007; Harbison et al., 2004; Lefrancois et al., 2009) that were altered in

different conditions tested in a study by Harbison et al. (2004).

In the past 10 years or so, a huge effort has been made to characterize the

transcriptional regulatory network in yeast by charting genome-wide localization of all

known DNA binding proteins using the ChIP-chip methodology (Harbison et al., 2004; Lee

et al., 2002). In the first study, genes encoding 106 yeast transcription factors were tagged

with the myc epitope to create a library of strains suitable for ChIP experiments aimed at

identifying their localization on promoters genome-wide (Lee et al., 2002). Approximately

4000 regulator-promoter interactions were discovered (P<0.001), where 37% of yeast genes

bound at least one of the 106 regulators tested (Lee et al., 2002). A general feature of yeast

promoters discovered here is that many promoters bound multiple regulators suggesting that,

as in higher eukaryotes, combinations of transcription factors control gene expression.

Dissecting data produced from this study revealed six network motifs in yeast cells that

describe general principles of regulation that underlie the transcriptional regulatory network

(Figure 1-3). These are: (1) autoregulation where the regulator controls its own promoter;

(2) multi-component loop where the regulator controls a gene and that gene product controls

the promoter of the initial regulator; (3) feedforward loop where a regulator activates another

regulator and both of these regulators control a common downstream gene; (4) single input

 

 

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motif where a regulator controls expression of a set of genes whose protein products

coordinate the same cellular process; (5) multi-input motif where a group of regulators bind

together to a group of promoters and; (6) regulator chain consisting of a regulator that

activates another regulator which in turn regulates another gene (Lee et al., 2002).

 

 

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Figure 1-3: Regulator-gene motifs identified from ChIP-chip analysis of transcription factors. Circles represent proteins while rectangles represent genes. See text for details. Figure adapted from Lee et al., 2002.

 

 

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In 2004, another study was published where 204 tagged transcription factors were

analyzed for their genome-wide localization (Harbison et al., 2004). ChIP of all 204

transcription factors was performed in rich media, but because environmental conditions

influence gene expression programs, 84 regulators were also tested in a minimum of 1 out of

12 other conditions (Harbison et al., 2004). This project produced an enormous data set

cataloguing 11 000 regulator-promoter interactions which led to the discovery of sequence

motifs in promoters of target genes for 116 regulators. Testing localization of regulators in

different conditions revealed important behavioural patterns of regulator-gene interactions

that are applied broadly across the genome. These patterns are: (1) condition invariant, in

which the regulator binds the same promoters in two different conditions; (2) condition

enabled, in which the regulator does not bind promoters in one condition but in a second

condition the regulator binds many promoters; (3) condition expanded, in which the regulator

binds a set of promoters in one environment and in another environment the regulator binds

that same set and additional promoters; and (4) condition altered, in which the regulator has

preference for a different set of promoters in two different conditions (Harbison et al., 2004).

Histone modifications such as acetylation and methylation of specific lysine residues

also influence transcriptional output. Antibodies with specificity for these modifications

have allowed ChIP-chip experiments to be carried out to determine the regions of DNA

where these various modifications exist (Pokholok et al., 2005). For example, antibodies that

specifically recognize histone H3 lysine 9 and lysine 14 acetylation were used in ChIP-chip

experiments which revealed that these chromatin marks are found particularly at

transcriptional start sites of active genes and the presence of these acetyl lysines correlates

with transcriptional output (Pokholok et al., 2005). In human cells, antibodies specific for

 

 

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methylation marks on histone H3 lysine 4 revealed that enhancer regions are generally

mono-methylated while promoter regions are tri-methylated, providing a powerful means to

identify regulatory regions in more complex genomes (Heintzman et al., 2007).

Technological advances have allowed production of extremely dense DNA

microarrays that allow analysis of whole genomes such as yeast with high resolution (see

David et al., 2006 and Section 1.4). For larger genomes, approaches that utilize sequencing

to characterize ChIP-enriched DNA were developed. For example, an approach called

sequence tag analysis of genomic enrichment (STAGE) was applied to characterize locations

of regulatory proteins along the genome (Kim et al., 2005). Briefly, this approach allowed a

library to be created where each ChIP-enriched DNA molecule is ligated to a sequencing tag.

Many of these molecules are then ligated to form concatemers of ChIP DNA that can be

sequenced in order to identify genomic regions bound by regulatory proteins (Kim et al.,

2005).

Cost-effective next generation sequencing platforms like the Illumina Genome

Analyzer II are becoming the method of choice for characterizing immunoprecipitated DNA

from ChIP experiments, a method referred to as ChIP-seq. ChIP-seq experiments allow

greater resolution of protein localization on DNA, sequencing can be carried out on a small

amount of ChIP DNA and this approach requires less handling than ChIP-chip.

Additionally, for small genomes like yeast, different experiments can be multiplexed into a

single sequencing run for cost effective generation of high quality data (Lefrancois et al.,

2009). Applications of ChIP-seq in the context of work carried out in this Thesis are

discussed further in the Future Directions section of Chapter 4.

 

 

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1.3 Protein binding microarrays

A key to understanding gene regulation is determination of the cis-regulatory

sequences recognized by DNA binding transcription factors. One method to determine

binding sites of transcription factors in promoters is to search for conserved sequence motifs

present in promoters that are occupied by regulatory proteins in ChIP-chip experiments

(Harbison et al., 2004) or to search for common sequence elements in promoters of genes

that share similar expression profiles (Spellman et al., 1998). As noted above, in yeast, most

known transcription factors have been tested for their genome-wide localization using ChiP-

chip under a variety of conditions (Harbison et al., 2004). However, this in vivo approach

has not created a complete map of sequence motifs bound by transcription factors, likely

because transcription factor binding is not occurring under the conditions tested.

Additionally, in ChIP experiments, proteins do not necessarily need to contact DNA but their

association with DNA can be bridged by other regulatory proteins.

Proteome-level approaches have been developed and applied productively to identify

consensus sites that are bound by regulatory proteins. Protein binding microarray (PBM)

experiments have been carried out to test for DNA sequences that are bound by transcription

factors in vitro (Figure 1-4). Briefly, a tagged transcription factor of choice is purified,

applied to a double stranded DNA microarray, probed with a labelled antibody that

recognizes the protein tag and DNA sequences bound by the protein identified based on

positions on the array that are illuminated (Berger and Bulyk, 2006; Berger et al., 2006). For

these experiments, DNA microarrays have been produced that represent all possible DNA

sequence variants of 10 base pair binding sites (Berger et al., 2006).

 

 

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Figure 1-4: Schematic of a protein binding microarray experiment. Tagged proteins are purified and applied to a microarray with all combinations of 10-mer binding sites. Transcription factor-DNA sequence interactions are identified by treating the microarray with an antibody conjugated to a fluorophore.

 

 

19

 

The universal design of this microarray allows protein binding experiments to be

carried out across different organisms and proof-of-principle of this approach was shown by

identifying consensus binding sites for five transcription factors from yeast (Cbf1 and Rap1),

worm (Ceh-22), mouse (Zif268) and human (Oct-1) (Berger et al., 2006).

Prior to 2008, a catalogue of DNA binding specificities of transcription factors in an

organism was lacking. Even in yeast, sequence motifs for only about half of the ~200

transcription factors were known. To better characterize sequence motifs bound by

transcription factors, one study reported sequence specificities for 112 yeast DNA binding

proteins (Badis et al., 2008). The majority of these binding specificities were derived from

carrying out protein binding microarray experiments on purified DNA binding domains for

transcription factors. Of the 112 sequence specificities identified, 63 motifs were previously

known and match the specificities known for these proteins (Badis et al., 2008). These

results validated the PBM approach and also defined a number of sequence motifs for

transcription factors that were previously unknown. Lending further support to this, many

sequence motifs identified from this study are found upstream of functionally related genes,

suggesting transcription factors co-ordinately control expression of these genes for specific

processes (Badis et al., 2008).

Shortly after this publication, another paper was published using the same PBM

approach to identify direct binding sequences of 89 transcription factors (where 157 proteins

did not yield binding profiles), revealing 50 new DNA binding site motifs in yeast (Zhu et

al., 2009). Both studies identified 2 proteins (called Pbf1 or Ybl054w and Pbf2 or Dot6) that

bind to the PAC and RRPE motifs (Badis et al., 2008; Zhu et al., 2009), which are binding

sites found in promoters of ribosomal RNA genes (Hughes et al., 2000b). Zhu et al. used

 

 

20

 

expression microarrays in a pbf1Δpbf2Δ double mutant to show that ribosomal target genes

of Pbf1 and Pbf2 are no longer repressed under heat shock conditions indicating Pbf1 and

Pbf2 are in fact regulators of these genes (Zhu et al., 2009). Additionally, both Pbf1 and

Pbf2 localized to a subset of PAC-containing ribosomal processing regulatory regions by

ChIP (Zhu et al., 2009). Together the studies by Badis et al. and Zhu et al. significantly

advance our knowledge of cis-binding sequences that are bound by yeast transcription factors

and will guide future studies to examine transcription factor localization at promoters

containing specific binding sites under a series of conditions in vivo.

1.4 Genome-wide nucleosome occupancy

To pack the large genomes of eukaryotic organisms into the nucleus of the cell, DNA

is organized into repeating units called nucleosomes that form chromatin. Histones are the

protein components of nucleosomes that form the histone octamer, which is built from two

histone H2A-H2B dimers and a histone H3-H4 tetramer. 147 base pairs of DNA are

wrapped around the histone octamer to form a nucleosome, which are present in ordered

arrays along the DNA and are separated by linker DNA.

In S. cerevisiae, the PHO5 promoter has been studied as a model to understand the

influence nucleosome occupancy has on transcriptional output. The PHO5 gene encodes an

acid phosphatase and is actively transcribed when intracellular phosphate levels are low and

repressed when phosphate levels are high (Tait-Kamradt et al., 1986). The PHO5 promoter

contains two upstream activating sequences (UAS) that are bound by the transcriptional

activators Pho2 and Pho4 (Barbaric et al., 1996). An important aspect underlying activation

of PHO5 transcription is that nucleosome disassembly must occur to allow activation and

 

 

21

 

this disassembly is mediated by the histone H3/H4 chaperone protein Asf1 (Adkins et al.,

2004; Boeger et al., 2003; Reinke and Horz, 2003). Interestingly, genetic evidence suggests

Asf1-mediated nucleosome disassembly is not required for binding of Pho2 or Pho4 to the

UAS sites in the PHO5 promoter (Adkins et al., 2007). Instead, ChIP analysis of TATA

binding protein (TBP) and RNA polymerase II (Pol II) under activating conditions at the

PHO5 promoter revealed that in the absence of Asf1, TBP and Pol II no longer localize to

the promoter (Adkins et al., 2007). These data indicate that chromatin disassembly at the

PHO5 promoter is required to recruit the general transcriptional machinery to allow activated

transcription. In addition, Asf1 and thus chromatin disassembly is also required for

recruitment of SWI/SNF and SAGA (Adkins et al., 2007), two protein complexes that

modify chromatin and also play a role in activation of PHO5 transcription. Interestingly,

Asf1 appears to be present at many locations throughout the genome (Adkins et al., 2007;

Schwabish and Struhl, 2006), indicating it may be poised on chromatin waiting for specific

transcriptional activators to bind their respective cis-regulatory sites to activate transcription

(Adkins et al., 2007). These PHO5 studies exemplify the role nucleosome assembly and

disassembly play in proper gene regulation, indicating that knowledge of the positions of all

nucleosomes in wild type cells would be informative for better understanding of global

transcriptional control.

Identifying the positions of nucleosomes on DNA involves carrying out a protection

assay where DNA wrapped around the histone octamer is protected from micrococcal

nuclease digestion so that linker DNA separating nucleosomes is preferentially digested

(Figure 1-5) (Yuan et al., 2005). After microccocal nuclease digestion, DNA is purified

from nucleosomes and analyzed to determine specific regions of DNA that were wrapped

 

 

22

 

around the histone octamer. For large-scale assessment of genomic regions occupied by

nucleosomes, high-resolution tiling microarrays are utilized. One study used a microarray

with 50-mer DNA probes tiled every 20 base pairs spanning chromosome III in S. cerevisiae,

allowing positions of nucleosomes to be determined with 20 base pair resolution (Yuan et al.,

2005).

 

 

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Figure 1-5: Schematic representation of a genome-wide nucleosome occupancy experiment. Nucleosomes are cross-linked to DNA with formaldehyde, and nucleosomal DNA is prepared. Micrococcal nuclease treatment preferentially digests linker DNA compared to protected nucleosomal DNA. Cross-linking is reversed and DNA is treated with DNase I to digest DNA to ~50 base pair fragments. To identify genomic regions protected from micrococcal nuclease digestion, DNA is hybridized to a high resolution DNA tiling array and signal is normalized to the hybridization signal from genomic DNA hybridization. Green spots represent genomic regions occupied by nucleosomes while white spots are regions devoid of nucleosomes, as long as genomic DNA is present.

 

 

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The first complete genome map of nucleosome positions was published in 2007

where an even higher density tiling array was used (Lee et al., 2007). This array contains the

S. cerevisiae genome tiled at 4 base pair resolution (David et al., 2006). This study defined

positions of ~71,000 nucleosomes spanning 81% of the genome (Lee et al., 2007) and

revealed that 87% of transcribed genes are occupied by nucleosomes. Intergenic regions

tend to be depleted where only 53% encompass nucleosomes, a trend that is consistent with

ChIP-chip experiments assaying histone levels across the genome (Pokholok et al., 2005).

The general trend of nucleosome-depleted promoters compared to occupied transcribed

regions has been reported by other groups using approaches with different degrees of

resolution, adding to the validity of the data presented by Lee et al. (2007) (Bernstein et al.,

2004; Lee et al., 2004; Yuan et al., 2005). Nucleosome-depleted regions (NDRs) are

generally found 50 base pairs upstream of the transcriptional start site (TSS). Interestingly,

this finding is also supported using a different technique called formaldehyde assisted

isolation of regulatory elements (FAIRE) to positively select regulatory elements (Giresi and

Lieb, 2009; Nagy et al., 2003). Briefly, in FAIRE, protein-DNA interactions are cross-linked

with formaldehyde, sonicated to shear chromatin and treated with phenol-chloroform (Nagy

et al., 2003). DNA devoid of histones separates into the aqueous phase which can be

detected by hybridization of this DNA to a microarray or by sequencing. FAIRE DNA was

found to contain promoter regions upstream of genes, suggesting that these regions are in

fact devoid of histones (Nagy et al., 2003), the most abundant proteins on DNA with the

highest cross-linking efficiency (Brutlag et al., 1969; Polach and Widom, 1995; Solomon and

Varshavsky, 1985).

 

 

25

 

Promoters of actively transcribed genes tend to contain characteristic NDRs

compared to promoters of genes expressed at lower levels which have higher nucleosome

occupancy. Interestingly, open reading frames show an opposite relationship where highly

transcribed genes are occupied with nucleosomes compared to ORFs expressed at low levels

(Lee et al., 2007), possibly because transcriptional initiation and elongation requires ordered

nucleosomes (Lee et al., 2007). Nucleosome depleted regions at promoters correlate with

transcriptional output. For instance, promoters of genes likely not expressed under standard

growth conditions, such as stress-responsive genes, lack nucleosome free regions upstream

of the TSS (Lee et al., 2007). However, promoters of genes that are actively transcribed, like

genes required for protein translation and ribosome production, have characteristic

nucleosome depleted regions upstream of the TSS (Lee et al., 2007). The nucleosome

depleted regions often contain transcription factor binding sequences that in many cases are

80-100 base pairs upstream of the TSS. Examples of transcription factors that have binding

sites at many promoters at the NDRs are Abf1, Reb1 and Mbp1 (Lee et al., 2007).

Many factors contribute to the proper positioning and occupancy of nucleosomes on

DNA including chromatin remodelers, transcription factor binding and the DNA sequence

itself. Because in vivo studies in wild type cells report on the contribution of all these

factors, in vitro studies were carried out to understand the sole contribution of DNA

sequence on nucleosome occupancy. Briefly, genomic DNA was purified from yeast,

incubated with purified chicken erythrocyte histone octamers and then subject to micrococcal

nuclease digestion (Kaplan et al., 2009). The protected nucleosomal DNA was identified by

sequencing to determine the positions on DNA where nucleosomes assembled and relative

occupancy at each base. This experiment defined the DNA sequence preference of

 

 

26

 

nucleosomes and, upon comparison to in vivo maps, was used to determine the contribution

of DNA sequence to nucleosome positions in living cells (Kaplan et al., 2009). A high

correspondence between in vitro and in vivo maps was discovered (correlation of 0.74)

indicating that DNA sequence preferences of nucleosomes play a dominant role in their

occupancy (Kaplan et al., 2009). Higher correlation between in vivo and in vitro maps was

found at non-promoter intergenic regions compared to promoters and open reading frames,

also indicating that DNA sequence is not the sole determinant of nucleosome organization

(Kaplan et al., 2009). To derive a general set of rules governing sequence-determined

nucleosome occupancy, a computational model trained from the in vitro nucleosome data

was developed (Kaplan et al., 2009). The model could predict in vivo nucleosome

occupancy in yeast and in C. elegans (albeit to a lesser degree), indicating the usefulness of

the in vitro yeast data in predicting DNA features that mediate nucleosome organization in

other organisms.

Nucleosome positions were also monitored in living cells in different growth

conditions that are known to change global transcription patterns. When comparing

nucleosome positions from cells grown in glucose (standard growth conditions), galactose or

ethanol, global nucleosome occupancy was found to correlate well amongst the three maps

and these maps also showed a high correlation with the in vitro map (although gene-specific

differences were also observed) (Kaplan et al., 2009). These results indicate that

nucleosomes have an intrinsic preference for DNA sequences and that this preference plays a

central role in establishing nucleosome organization.

 

 

27

 

1.5 The yeast deletion array and the synthetic genetic array (SGA) approach

Assigning functions to genes classically involves cataloguing phenotypic outcomes of

gene perturbations. Typically, forward genetic approaches have been employed where

random mutagenesis of cells to perturb genes has been coupled with follow-up genetic

approaches to characterize mutant phenotypes. Although this approach has proven extremely

useful, random mutagenesis does not provide a saturating survey of all genes and

identification of mutant genes often involves considerable work.

Since genomes of a variety of organisms are fully sequenced, researchers have

knowledge of all predicted open reading frames (ORFs). These gene models have allowed

the creation of genome-wide resources where all genes are deleted or can be systematically

perturbed. RNA interference (RNAi) is typically used to knockdown gene function by

reducing levels of messenger RNA (mRNA). In Caenorhabitis elegans, Drosophila

melanogaster, human and mouse, genome-wide RNAi libraries exist to reduce expression of

each gene (Boutros et al., 2004; Kamath et al., 2003; Moffat et al., 2006). For example, in

human HT29 colon cancer cells, RNAi-mediated knockdown of gene expression was

combined with high-content imaging to identify genes required for proper regulation of

mitosis (Moffat et al., 2006). Measurements of histone H3 phosphorylation on serine 10

(which marks mitotic cells), DNA content by Hoechst staining and actin organization by

phalloidin staining, were combined with RNAi suppression of gene expression to reveal

several known genes and ~100 novel genes associated with mitotic progression (Moffat et

al., 2006).

In C. elegans, RNAi has been used to examine the phenotypic consequences of

perturbation of single genes (Kamath et al., 2003) and to explore genetic interactions. In C.

 

 

28

 

elegans, systematic RNAi screens can be performed very simply by feeding worms bacteria

expressing constructs that produce double-stranded RNA designed to target every worm gene

(Timmons and Fire, 1998). This astounding feature of the C. elegans model means that the

phenotypic consequence of combining an RNAi library with any query mutation can be

assessed. In one study, 37 query mutations of genes involved in cellular signalling pathways

were combined with an RNAi library targeting ~1750 genes involved in signal transduction,

transcriptional regulation and chromatin remodeling producing pairwise combinations of

~65,000 genes (Lehner et al., 2006). This study identified 350 genetic interactions amongst

signalling genes and library genes, many of which are perturbed in human diseases (Lehner

et al., 2006). A more recent genetic interaction study using RNAi identified more genetic

interactions in C. elegans than the Lehner et al. study, even though fewer pairwise

combinations of gene mutations were tested (Byrne et al., 2007). These results suggests that

the spectrum of genetic interactions in the worm may be much larger than initially expected.

In budding yeast, more directed approaches have been used to generate strain

collections where each full length gene is deleted. Here, researchers take advantage of the

high intrinsic rate of recombination to replace each gene with a dominant antibiotic resistant

cassette. The first construction of a complete gene-deletion library was reported in budding

yeast, Saccharomyces cerevisiae, where a kanamycin resistance cassette (KanMX) with

flanking regions homologous to each yeast ORF was targeted to replace each yeast coding

sequence (Figure 1-6) (Giaever et al., 2002). Gene-replacement strategies have been used to

create deletion libraries in other organisms like Schizosaccharomyes pombe (available from

BiONEER), E. coli (Baba et al., 2006) and Cryptococcus sp (Idnurm et al., 2009).

 

 

29

 

Figure 1-6: Gene-deletion strategy for replacing each yeast ORF with a kanamycin resistant cassette (KanMX). The gene knockout cassette is transformed into yeast cells and is precisely integrated in the genome by homologous recombination. Each deletion cassette has up and down (DN) tags which contain unique DNA sequences or barcodes that can be used for strain identification (Giaever et al., 2002; Winzeler et al., 1999).

 

 

30

 

Characterizing the library of yeast deletion strains revealed that approximately 20%

of all 6000 yeast genes are essential for haploid viability, only about half of which were

previously known (Giaever et al., 2002). This remarkable result revealed that extensive

redundancy exists in the genome that buffers the consequence of single gene-deletions. This

observation fuelled development of a high-throughput method for genetic manipulation of

the yeast deletion library termed the synthetic genetic array (SGA) approach (Figure 1-7)

(Tong et al., 2001; Tong et al., 2004). Initially, this approach was used to combine a query

mutation of choice with each yeast deletion strain to create an output array of double mutants

where arrayed colonies could be scored for a growth defect that is more severe than each

single gene deletion (so called synthetic lethal or synthetic sick interactions). Key features of

the SGA approach are: (1) it is automated by use of robotics to replicate arrays of yeast

colonies onto different selection media; (2) since yeast deletion mutants are arrayed, the

position of each yeast mutant is known; (3) yeast of MATα mating type with a mutation in

gene ‘A’ can be mated to the array of MATa yeast deletion mutants to produce diploid yeast

strains; (4) the arrayed diploid strains can be sporulated, and (5) MATa meiotic progeny with

both marked gene deletions can be preferentially selected because they contain a STE2

promoter driving expression of an auxotrophic marker gene that is only expressed in MATa

cells, allowing them to grow on media lacking that particular amino acid (Tong et al., 2001;

Tong et al., 2004).

 

 

31

 

Figure 1-7: The synthetic genetic array approach used for high-throughput double mutant strain construction. A query mutation in a particular ORF (orfAΔ) marked with a nourseothricin resistant cassette (Nat) is mated to the array of viable haploid deletion mutants using a robotic replica pinning procedure. Diploid yeast strains are selected and sporulated and mieotic haploid progeny with the query mutation combined with each yeast deletion mutant is selected. Genetic interactions are identified by observing double mutants that have a growth defect that is more severe than the product of each single mutant. See Tong et al., 2001.

 

 

32

 

The SGA protocol produces an output array of haploid strains where the query

deletion in gene ‘A’ is combined with each deletion mutant which can subsequently be

assayed for double mutant strains that show a synthetic lethal or synthetic sick phenotype.

This approach was applied to probe the yeast genome for genes that were inviable when

combined with 8 query mutations which revealed 291 interactions among 204 genes (Tong et

al., 2001). In a follow-up study, 132 query mutations were screened against the array of

deletion mutants to generate a larger network charting ~4000 synthetic lethal relationships

among ~1000 genes (Tong et al., 2004). This screening approach revealed previously

unappreciated relationships among genes and pathways that span the spectrum of cellular

processes and provides a powerful means to assign gene function.

The SGA-based strain construction strategy provided the tools for another high-

throughput strategy to produce double mutant strains for profiling genetic interactions called

diploid-based synthetic lethality analysis on microarrays or dSLAM (Pan et al., 2004). This

approach involves introduction of a query mutation of choice by transformation into a pooled

collection of the heterozygous MATα/a deletion collection (Giaever et al., 2002) and

conversion of this collection into MATa haploid double mutants that now have the query

mutation combined with each deletion mutant (Pan et al., 2004). As noted earlier, the yeast

deletion collection contains unique strain identifiers or molecular barcodes that flank the

KanMX knockout cassette (Giaever et al., 2002 and Figure 1-6). The barcodes can be PCR

amplified from a pool of mutants and the resulting DNA hybridized to a DNA microarray

with probes complementary to each barcode as a means to identify deletion strains present in

the pool. In dSLAM, double mutants that cause a growth defect or lethality compared to

each single mutant will drop out of the pooled population and those barcodes will be under-

 

 

33

 

represented on the microarray compared to the single mutant, thus identifying genetic

interactions among genes (Pan et al., 2004). This approach was recently used to identify

genetic interactions among genes involved in histone acetylation and deacetylation, revealing

new functional roles for histone acetyltransferases (HATs) and histone deacetylases

(HDACs) (Lin et al., 2008).

Although the SGA approach was initially described to genetically manipulate the

array of viable haploid deletion strains, other genetic arrays can also be screened. For

instance, the functions of essential genes can be probed using SGA by screening arrays of

tetracycline-repressible alleles (Davierwala et al., 2005; Mnaimneh et al., 2004), temperature

sensitive strains and alleles which contain a disruption in the 3’ untranslated region (UTR) of

essential genes to knockdown gene expression (called the decreased abundance of mRNA by

perturbation or DAmP strains) (Schuldiner et al., 2005). Other types of genome-wide arrays

are available that allow overexpression of each yeast ORF, which again often impinges on

cellular growth, particularly when combined with sensitized genetic backgrounds (Sopko et

al., 2006). In addition to screening other arrays in S. cerevisiae, high-throughput strain

construction methodologies have been extended to other organisms including

Schizosaccharomyces pombe (Dixon et al., 2008; Roguev et al., 2007) and E. coli (Butland et

al., 2008; Typas et al., 2008).

1.6 Reporter-based screens

Above, I describe a number of genome-wide approaches largely based on DNA

microarray technology that have been employed to make major discoveries on global gene

regulation. Other major insights have derived from a variety of genetic screening approaches

 

 

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designed to discover regulators of a particular gene of interest. Reporter genes have been

particularly useful in this regard, and I provide an overview of reporter gene screens in yeast

below, since they form the basis of the functional genomic approach that I developed

(Chapter 2).

Reporter genes are constructed by fusing a promoter or any cis-regulatory element of

interest to a gene that provides an easily assayable readout of the activity of that particular

promoter (or cis element). One such reporter gene that has been widely employed is the lacZ

gene from E. coli that encodes the enzyme β-galactosidase. When a promoter-lacZ reporter

gene is introduced into a particular cell, the activity of the promoter can be assayed by

plating cells on media containing X-gal. When β-galactosidase is produced, the substrate X-

gal is cleaved which results in the formation of blue colonies. If the promoter is inactive in

that particular cell, lacZ expression is turned off and colonies appear white.

Reporter technology can be combined with forward genetic screens to isolate mutants

that cause differential expression of the reporter gene, which elucidates candidate regulators

of the promoter being analyzed (Figure 1-8). Randomly mutagenized cells that result in

increased or decreased reporter activity are isolated and the gene mutation characterized to

discover the gene responsible for controlling the promoter driving lacZ expression.

 

 

35

 

Figure 1-8: A forward genetic reporter screen to identify regulators of a promoter of interest. A strain that harbours a promoter-lacZ reporter gene is mutagenized. Mutants are screened for a defect in lacZ production on media containing X-gal. Higher lacZ levels produce dark blue colonies and mapping of the mutation reveals a repressor of the promoter driving lacZ expression. Lower lacZ levels produce white colonies and mapping of the mutation reveals an activator of the promoter driving lacZ expression.

 

 

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An excellent example of early applications of this approach is the effort to learn how

the HO gene in S. cerevisiae is regulated. The HO gene encodes an endonuclease that is

involved in mating type switching. HO transcription occurs only in haploid MATa or MATα

cells but not in a/α diploid cells (Jensen et al., 1983). Furthermore, HO expression is cell

cycle-regulated with transcripts peaking in late G1 and HO expression is restricted to the

mother cell and is not seen in the newly formed daughter cell (Nasmyth, 1983). A forward

genetic screen was employed to identify trans-acting factors that control expression of a HO

promoter-lacZ reporter gene (Breeden and Nasmyth, 1987). Five new SWI genes were

identified that caused a defect in HO promoter-lacZ transcription (Breeden and Nasmyth,

1987), adding to the five already known (Stern et al., 1984). Further dissection of the HO

upstream regulatory sequence (URS) revealed that a short motif repeated throughout the

URS, now called the Swi4-6-dependent cell cycle box (SCB) element [CACGA]4 is

sufficient to confer cell cycle regulation of the HO gene (Breeden and Nasmyth, 1987). To

characterize which SWI mutants specifically act through the [CACGA]4 motif in the HO

promoter, a [CACGA]4-lacZ reporter gene was introduced into the 10 SWI mutants. Only

SWI3, SWI4 and SWI6 deletion strains caused a defect in [CACGA]4-lacZ expression,

suggesting these genes are acting specifically through this cis-regulatory sequence while

other activators like SWI1, 2 and 5 regulate the promoter independently of [CACGA]4

(Breeden and Nasmyth, 1987). Further work revealed that Swi4 and Swi6 directly interact

through their C-terminal regions to form a heterodimeric transcription factor called SBF and

that Swi4 is responsible for directly binding DNA (Andrews and Herskowitz, 1989; Andrews

and Moore, 1992). It was also discovered that chromatin remodelers such as SWI/SNF and

 

 

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SAGA are required for proper regulation of HO transcription and that the protein Ash1

represses HO transcription in daughter cells.

Many of the factors that affect HO were initially discovered using reporter gene

technology but the order of events that lead to HO activation remained unclear. Chromatin

immunoprecipitation studies were carried out to clarify the timing and order of these

transcriptional regulators at the HO promoter. These experiments revealed the following

series of events: (1) Swi5 arrives at the promoter in late anaphase, (2) Swi5 localization to

the HO promoter then recruits SWI/SNF, (3) SWI/SNF recruits the SAGA complex and (4)

recruitment of SWI/SNF and SAGA is required for recruitment of SBF (Cosma et al., 1999).

These events allow HO transcription to occur in the mother cell while the Ash1 protein

represses HO transcription specifically in the daughter cell. These results, largely motivated

by applications of reporter genes, demonstrated complex regulation of a promoter that is

under combinatorial control and shows lineage-specific transcription.

Reporter gene screens have become a standard tool in transcriptional analysis.

Normally, forward genetic screening approaches are employed by randomly mutagenizing

strains harbouring the reporter gene of interest but limitations to this approach exist. First,

random mutagenesis is normally not saturating for the genome nor is it truly random.

Second, a large mutant library must be constructed to ensure high coverage of the genome.

Third, a large amount of follow-up work is required to characterize mutants. Fourth, these

types of reporter screens provide only qualitative measures of gene expression.

To combat many of these problems, we recently described methods for carrying out

systematic reverse genetic screens to identify regulators of a promoter of interest using

functional genomic tools and resources in yeast (Sassi et al., 2009). We describe a system

 

 

38

 

where a wild type yeast strain carrying a reporter gene of interest can be introduced into an

ordered array of ~4500 yeast deletion mutants using the SGA procedure described above.

The use of two types of reporter genes are described, which are based on a colourimetric

assay or auxotrophy. In one case, the activity of a promoter fused to lacZ could be assayed

in each yeast deletion mutant by replica plating the entire array onto medium containing the

substrate X-gal (see above). On this medium, deletion mutants that are required for

repression of the promoter driving lacZ expression will result in higher levels of lacZ

transcription and thus greater β-galactosidase activity leading to very blue colonies. If the

deletion mutant is an activator of the promoter, lacZ transcription will be reduced leading to

a white colony colour.

A second reporter gene is based on HIS3 auxotrophy. Cells that cannot produce

histidine because they lack the HIS3 gene must be grown on media supplemented with

histidine. In this case, a reporter gene harbouring a promoter fused to HIS3 is introduced into

the yeast deletion array using the SGA methodology and deletion of genes that allow growth

on medium lacking histidine are scored as repressors of that promoter (Sassi et al., 2009).

This type of screen is useful only if the promoter driving HIS3 is weak enough so that a

growth defect is seen when cells are grown on medium lacking histidine or a mutation is

made so that the promoter driving HIS3 is inactivated.

The HIS3 reporter gene approach was used to screen for new regulators of the SCB

element, which is bound by the transcription factor SBF (see above). In this case, an SCB-

HIS3 reporter gene was introduced into a strain with a CLN3 deletion (Costanzo et al., 2004).

The absence of the cyclin CLN3 prevents activation of SCB-dependent transcription, thus

cells cannot grow in the absence of histidine because of the failure of the SCB element to

 

 

39

 

drive transcription of the HIS3 gene. The SGA methodology was used to combine the

reporter gene and CLN3 deletion with each yeast deletion mutant. The resulting array of

yeast mutants was screened on media lacking histidine, and it was found that deletion of

WHI5 resulted in growth of colonies because the absence of Whi5 relieved repression of the

SCB element (caused by the CLN3 mutation) and allowed HIS3 transcription (Costanzo et

al., 2004). Follow up experiments revealed that Whi5 association with SBF represses

transcription but upon CDK phosphorylation, Whi5 dissociates from SBF to allow

expression of late G1 genes (Costanzo et al., 2004). This study defined a pathway in yeast

analogous to the Rb-E2F pathway in mammalian cells, which is often targeted in many types

of tumours.

1.7 Global cell cycle transcription

My thesis work has involved the systematic analysis of pathways leading to

activation of cell cycle transcription in yeast. In eukaryotic organisms, the mitotic cell cycle

is an ordered series of events where one cell gives rise to a daughter cell with identical DNA

content. The daughter cell undergoes a gap phase (G1) then upon reaching a critical cell

size, commits to another round of cell division at a point called START in yeast or the

restriction point in mammalian cells. After G1, cells synthesize their DNA (S-phase),

undergo a second gap phase (G2) then ultimately produce a daughter cell after completing

mitosis (M phase). Many input signals underlie cell cycle progression like nutrient

availability, cell size, transcription and protein production and degradation. Proteins called

cyclins are the regulatory components of cyclin dependent kinases (CDKs) that are critical

for the proper control of cell cycle events. Cyclins were so named because their transcript

 

 

40

 

and protein levels peak at particular cell cycle phases and are rapidly degraded when cells

transit outside of that phase (Evans et al., 1983). This oscillation of cyclin levels ensures that

bursts of CDK activity occur at critical points of the cell cycle. For example, in yeast the

CDK Cdc28 associates with G1 cyclins (Cln1, 2 and 3) to promote progression through G1

of the cell cycle. Alternatively, Cdc28 associates with B type cyclins (Clb5 and 6) to

promote replication of DNA while association with Clb1, 2, 3 and 4 is required for proper

progression through G2 and M phases of the cell cycle (reviewed in Mendenhall and Hodge,

1998).

In addition to cyclins, many other gene transcripts fluctuate throughout the cell cycle.

For example, histone genes are among the earliest discovered cell cycle-regulated transcripts

(Hereford et al., 1981). Histone gene expression is tightly regulated so that the genes are

transcribed at high levels during S-phase of the cell cycle when histones are needed to meet

the demands of DNA replication. In the late 1990’s, gene expression microarrays were

utilized to discover the complement of genes whose transcripts are cell cycle-regulated.

Briefly, synchronized yeast cultures were grown so that samples could be taken at fixed time

points to cover each phase of the cell cycle and RNA from cells taken at these time points

was analyzed with gene expression microarrays (Cho et al., 1998; Spellman et al., 1998).

These studies revealed that ~400 to 800 yeast genes are cell cycle-regulated, equating to

~10% of the genome (Cho et al., 1998; Spellman et al., 1998). A more recent study was

carried out to probe cell cycle transcription and the combination of these data with previous

studies revealed that upwards of 1000 yeast genes are cell cycle-regulated (Pramila et al.,

2006). Comparable experiments have been carried out in other eukaryotes including three

studies in S. pombe which individually identified 407 periodically expressed transcripts

 

 

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(Rustici et al., 2004), 747 cell cycle transcripts (Peng et al., 2005) and 750 genes with

significant cell cycle oscillations but suggesting as many as 2000 genes might be cell cycle-

regulated (Oliva et al., 2005). In human cell lines similar experiments revealed >1000 cell

cycle-regulated genes (Cho et al., 2001; Whitfield et al., 2002). In comparing cell cycle-

regulated transcription between S. cerevisiae and S. pombe, one study reported 142

transcripts that were cycle-regulated in both organisms (Peng et al., 2005). Overlapping cell

cycle-regulated genes in both organisms tended to be involved in core cell cycle functions

like DNA replication, chromosome maintenance and mitosis defining a core group of cell

cycle genes that seem to be conserved throughout evolution (Oliva et al., 2005; Peng et al.,

2005; Rustici et al., 2004). Differences in cell cycle-regulated transcripts were often seen

with genes involved in cell metabolism and growth or cell wall biogenesis, likely reflecting

differences in the cell cycle biology of S. pombe and S. cerevisiae (Oliva et al., 2005; Peng et

al., 2005). These studies have collectively defined massive waves of gene expression that

underlie cell cycle progression and imply the existence of a transcriptional regulatory

network that controls proper expression of these genes.

Often times, regulators of cell cycle transcription control genes that perform functions

specific to that phase of the cell cycle. For instance, SBF and MBF are sequence-specific

heterodimeric transcription factors that generally regulate genes transcribed at the G1-S

transition (Koch et al., 1993). ChIP-chip studies carried out to identify all regulatory regions

occupied by these transcription factors showed that SBF generally controls genes involved in

budding and membrane and cell wall biosynthesis while MBF for the most part controls

genes that function in DNA replication and repair (Iyer et al., 2001). Additionally, a number

of target genes defined by ChIP-chip are cell cycle-regulated and these were enriched for

 

 

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genes expressed during G1 and S-phase (Iyer et al., 2001). Some target genes showed peak

expression outside of G1 and S-phase. For example, the G2/M cyclins CLB1 and CLB2 were

bound by Swi4, suggesting SBF plays a more complex role than previously thought (Iyer et

al., 2001).

Waves of gene expression at one cell cycle phase are important for proper timing and

expression of genes at the adjacent phase. Also, key regulators of the cell cycle are usually

themselves cell cycle regulated and ChIP-chip studies on 9 of these transcriptional activators

(Mbp1, Swi4, Swi6, Mcm1, Fkh1, Fkh2, Ndd1, Swi5 and Ace2) described a cyclic model

whereby transcriptional regulators drive expression of each other (Simon et al., 2001).

Additionally, multiple activators function at each cell cycle phase, indicating that extensive

buffering exists so that cell cycle progression is not severely impaired by single mutations in

transcription factors. This study set the stage for future work to decipher the complete group

of regulators that control cell cycle transcription. ChIP-chip experiments and analysis of

transcription factor binding sites of co-expressed genes from microarray data, identified the

transcription factor Hcm1 as an important regulator of S-phase specific transcription, filling a

key gap in our knowledge of cell cycle transcriptional regulation in yeast (Horak et al., 2002;

Pramila et al., 2006).

These and other studies led to the general model that cell cycle transcriptional control

is a closed circuit where activators at one phase control expression of transcription factors at

the next phase. In late G1, SBF (Swi4-Swi6) is responsible for activation of Hcm1 which is

active at late S-phase (Horak et al., 2002; Iyer et al., 2001; Pramila et al., 2006). Hcm1, SBF

and MBF account for activation of Ndd1, Fkh1 and Fkh2, transcription factors that together

with Mcm1 regulate G2/M transcription and in turn regulate Swi5 and Ace2 (Horak et al.,

 

 

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2002; Iyer et al., 2001; Pramila et al., 2006; Simon et al., 2001). Swi5-Ace2-Mcm1 controls

M/G1 transcription (Simon et al., 2001). Mcm1 is then responsible for activation of Swi4,

closing the transcriptional circuit and allowing another burst of G1 transcription during the

next cell cycle (Simon et al., 2001). These results set the framework for understanding cell

cycle transcriptional control (key regulators are summarized in Table 1-1), but does not

account for the cell cycle periodicity of hundreds of transcripts indicating many more

discoveries are required to fully understand cell cycle transcription.

 

 

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Table 1-1: Key regulators of cell cycle transcription

Cell Cycle Regulator Activator or Repressor Cell Cycle Phase Regulated SBF (Swi4-Swi6) Activator G1 MBF (Mbp1-Swi6) Activator G1 Hir1 Repressor S Hir2 Repressor S Hir3 Repressor S Hpc2 Repressor S Hcm1 Activator S Fkh1 Activator G2/M Fkh2 Activator G2/M Ndd1 Activator G2/M Mcm1 Activator G2/M, M/G1 Swi5 Activator M/G1 Ace2 Activator M/G1 Yox1 Repressor M/G1 Yhp1 Repressor M/G1

 

 

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A major void in understanding cell cycle transcription is a clear understanding of the

factors and mechanisms that underlie histone transcription that occurs in S-phase. Most of

histone gene regulation has been characterized in terms of repression by the Hir proteins

(Osley and Lycan, 1987). Histone gene expression is a main focus of this Thesis and is

discussed extensively in Chapter 3.

1.8 Summary and overall significance

Above I describe a number of genome-wide approaches that have been broadly

applied to study transcriptional control. Many of these approaches utilize DNA chip

technology, which has revolutionized the field of gene regulation. Parallel analysis of all

transcripts being expressed in a particular cell, locations of regulatory proteins on DNA,

genome-wide positions of nucleosomes, computational prediction and experimental

identification of transcription factor binding sites have led to enormous discoveries on how

the genome is transcribed.

These approaches provide information on how all promoters are being regulated in

the genome and have been combined to identify target genes of particular proteins.

However, some of these approaches require prior knowledge of protein function. For

example in ChIP-chip studies, knowledge of protein function in transcriptional control is

required in order to choose proteins to tag for analysis. By carrying out reporter screens and

using a single promoter as bait, the genome can be analyzed to discover proteins that affect

transcription of that particular promoter. Although extremely useful, advanced techniques

for reporter screening are lacking. Limitations to traditional forward genetic screening

approaches are discussed above. We have recently described a functional genomics

 

 

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methodology by combining lacZ and HIS3 reporter genes with array-based approaches in

yeast to counter some of these problems (Sassi et al., 2009). However, these types of screens

are generally not quantifiable making them difficult to employ in large-scale studies.

In this Thesis, I describe the development and complete methodology of a large-scale

reporter screen which combines available functional genomic tools and resources in yeast

that is unbiased, quantifiable and internally controlled (Kainth et al., 2009 and Chapter 2). I

applied this screening procedure to discover novel regulators of histone gene expression, an

important group of genes that are tightly cell cycle-regulated with peak transcription

occurring during S-phase. I show the utility of this screening approach by identifying a

number of well established regulators of histone gene expression including the Asf1, Hir1, 2

and 3 histone chaperone proteins and the histone periodic control 2 (Hpc2) protein.

Additionally, my screen revealed a novel role for Rtt106, another histone chaperone, in

repression of histone genes as well as a role for the HAT, Rtt109, and the bromodomain

containing protein, Yta7, in activation of histone gene expression. A series of follow-up

experiments are described utilizing ChIP, transcript profiling, genome-wide nucleosome

occupancy and protein-protein interaction studies to show that Rtt106 is a member of the

Hir-Asf1 complex, which is responsible for repression and cell cycle control of histone

genes. This repression is countered in part by Rtt109, likely by acetylating histone H3 lysine

56 (H3 K56Ac). We discovered that this Rtt106 is correctly localized at the promoter

because Yta7 is also present, which restricts Rtt106 from spreading into the coding region of

histone genes. Thus, the work described here represents biological discovery as well as

technology development, which should form the basis of future studies employing reporter

gene screens.

 

 

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Chapter 2

Comprehensive genetic analysis of transcription factor pathways using a dual reporter gene system in budding yeast

The work described in this chapter is published as: Pinay Kainth, Holly Elizabeth Sassi, Lourdes Peña-Castillo, Gordon Chua, Timothy R. Hughes and Brenda Andrews. Comprehensive genetic analysis of transcription factor pathways using a dual reporter gene system in budding yeast. Methods. 48, 2009, 258-264. Permission to reprint this work was obtained from Elsevier. Author contributions:

PK developed the method, analyzed the data, carried out the screening, wrote the manuscript and produced Figures 2-2 through 2-5.

HES helped with development of the method, screening, editing the manuscript and produced Figure 2-1.

LP carried out the data normalization and statistical analysis for data shown in Figures 2-3, 2-4 and 2-5.

GC assisted with developing the method.

TRH assisted with development of the method and editing the manuscript.

BA directed the project and writing of the manuscript.

 

 

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Abstract

The development and application of genomic reagents and techniques has fuelled progress in

our understanding of regulatory networks that control gene expression in eukaryotic cells.

However, a full description of the network of regulator-gene interactions that determine

global gene expression programs remains elusive and will require systematic genetic as well

as biochemical assays. Here, I describe a functional genomics approach that combines

reporter technology, genome-wide array-based reagents and high-throughput imaging to

discover new regulators controlling gene expression patterns in Saccharomyces cerevisiae.

Our strategy utilizes the SGA method to systematically introduce promoter-GFP (Green

Fluorescent Protein) reporter constructs along with a control promoter-RFP (Red Fluorescent

Protein) gene into the array of ~4500 viable yeast deletion mutants. Fluorescence intensities

from each reporter are assayed from individual colonies arrayed on solid agar plates using a

scanning fluorimager and the ratio of GFP to RFP intensity reveals deletion mutants that

cause differential GFP expression. I describe analysis of data from a CLN2 promoter-GFP

screen and show that our method identifies deletion of SWI4, the known activator of CLN2

expression, as causing the greatest defect in CLN2 promoter-GFP fluorescence. The method

is extensible to any transcription factor or signalling pathway for which an appropriate

reporter gene can be devised.

 

 

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2.1 Introduction

With its sophisticated yet straightforward genetic tools, the budding yeast

Saccharomyces cerevisiae has long been a premier model organism for exploring eukaryotic

biology. The utility of yeast for studying conserved processes and biological pathways has

been aided in the past decade or so by access to remarkable genetic resources including a

complete gene deletion collection (Giaever et al., 2002; Winzeler et al., 1999) and

comprehensive arrays of yeast strains carrying tagged alleles of all genes (Huh et al., 2003;

Krogan et al., 2006; Sopko et al., 2006). These resources have allowed yeast to serve as a

test-bed for the development of many functional genomic techniques that are now broadly

applied. Recent advances in our global understanding of transcription factors and their target

genes have relied heavily on gene expression microarrays, genome-wide chromatin-

immunoprecipitation (ChIP-chip) experiments, and computational prediction of transcription

factor binding sites based on these data.

As discussed in Chapter 1, approaches such as ChIP-chip demand prior knowledge of

gene function to choose proteins to tag with the purpose of understanding their roles in

transcriptional regulation at all promoters. Complementary genetic approaches have also

been productively used for many years to discover genes that regulate a promoter of interest.

In particular, the development and use of sensitive reporter genes has enabled many

landmark discoveries about transcriptional regulation over the past two decades. Typically

these types of screens involve fusing a specific promoter to an appropriate reporter gene (pr-

reporter) and assessing the effect of perturbing cis-elements or trans-acting factors on

reporter gene expression. Reporter genes based on the CYC1 promoter and the bacterial lacZ

gene enabled the early definition of the UAS as a key promoter element in yeast (Guarente et

 

 

50

 

al., 1982). Here, promoter activity was assessed by measuring levels of lacZ-encoded β-

galactosidase using simple colourimetric assays. Other types of reporters are based on

nutritional requirements and are detected using a growth readout. For example, a histidine

auxotroph containing a promoter of interest fused to the histidine biosynthetic gene HIS3 can

be screened to identify mutants defective in driving HIS3 expression, which will result in a

growth defect.

As noted above, reporter genes have been extensively used in genetic screens to

discover trans-acting factors that influence expression from a specific promoter leading to

new paradigms of transcriptional regulation. For example, early screens for mutants that

affected expression of an HOpr-lacZ reporter gene led to 1) the discovery of the founding

member of the Swi/Snf family of chromatin remodelers; 2) elucidation of a pathway of

lineage-specific gene expression involving localized mRNA and 3) the description of

transcription factors that induce gene expression during G1 phase, a conserved and important

feature of eukaryotic cell cycles (Andrews and Herskowitz, 1989; Breeden and Nasmyth,

1987; Jansen et al., 1996; Sternberg et al., 1987). These examples illustrate the capacity of

reporter gene screens to uncover both proteins that directly regulate gene expression by

binding to promoters or their regulatory regions as well as upstream factors that influence

their activity.

Although classical genetic screens employing reporter genes have been extremely

useful, they are generally not saturating. Recently, we described an approach that makes use

of the yeast deletion array to analyze expression of lacZ and HIS3 promoter reporter genes

that provides a saturating survey of the effect of loss-of-function mutations in yeast genes on

a promoter of interest (Sassi et al., 2009), the latter of which was used to identify regulators

 

 

51

 

of G1 transcription (Costanzo et al., 2004). However, the readout of these reporters is

difficult to reliably and rapidly quantify. I therefore sought to devise a completely

quantitative and unbiased approach to study transcription factor pathways.

The recent engineering of fluorescent proteins in a variety of different colours across

non-overlapping spectral classes has made multi-colour cell biological experiments feasible

(Shaner et al., 2007; Shaner et al., 2005). Additionally, fluorescent proteins are easy to

detect with the correct optics and fluorescent signals can be rapidly quantified, making them

useful markers of a variety of cellular events.

In this Chapter, I describe a system that combines dual colour promoter-reporter

genes with the SGA methodology (Tong et al., 2001; Tong et al., 2004) to assess the effect of

deleting each yeast gene on a promoter of interest. The system includes a query strain that

harbours any promoter of interest fused to GFP on a plasmid as well as an integrated control

promoter fused to the dsRed variant tdTomato (Shaner et al., 2004) (which we refer to as

RFP). The query strain is crossed to the collection of ~4500 viable haploid yeast deletion

mutants using a simple replica-pinning procedure, resulting in an output array in which each

deletion mutant contains both reporters. By constructing such an output colony array, we can

easily assess the effect of each yeast deletion mutant on reporter gene activity by scanning

both GFP and RFP fluorescence intensities directly from colonies arrayed on agar plates.

After quantifying these data, the GFP intensity captured from each colony can be

standardized to the RFP signal from that same colony to identify deletion mutants causing

differential GFP expression. We expect deletion of a putative activator to result in a

decreased GFP:RFP ratio while deletion of a putative repressor will result in an increased

 

 

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GFP:RFP ratio. This methodology allows a survey of the genome to identify both direct

regulators and upstream signals and pathways that impinge upon a promoter of interest.

2.2 Description of methods

2.2.1 Reporter system

Promoters are PCR amplified from yeast genomic DNA and cloned into the plasmid

BA1926 upstream of a cassette consisting of a GFP reporter followed by the terminator

sequence of the ADH1 gene (Wach et al., 1997) (Table 2-1). BA1926 is a CEN-based and

LEU2-marked plasmid that was derived from the plasmid pRS315 (Sikorski and Hieter,

1989).

In my work, I define a promoter as the intergenic region upstream of a given open

reading frame (ORF) up to 1000 base pairs. The resulting reporter constructs are

transformed into an appropriate SGA query strain harbouring an integrated copy of a control

promoter fused to RFP, marked with the hygromycin resistance gene (HphMX) (Goldstein

and McCusker, 1999) (see below and Table 2-1). Users should be careful to select a control

promoter that is regulated independently of the promoter of interest. Because of my interest

in cell cycle-regulated transcription, I constructed control reporter constructs containing the

promoter of the actin gene, ACT1, or the promoter of the RPL39 gene which encodes a

ribosomal protein. Both of these promoters are constitutively expressed and independent of

cell cycle regulation (Spellman et al., 1998).

 

 

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Table 2-1: Query strains and plasmids used in the two-colour promoter-reporter screening system.

Strain Genotype Source Y7092* MATα can1Δ::STE2pr-his5 lyp1Δ his3Δ1 leu2Δ0 ura3Δ0 met15Δ0 Tong et al.,

2007 BY4256 MATα HO::RPL39pr-tdTomato::hphMX integrated in Y7092 Andrews lab BY4347 MATα HO::ACT1pr-tdTomato::hphMX integrated in Y7092 Andrews lab

Plasmids Description Source pRS315 CEN-based LEU2-marked low copy plasmid Sikorski and

Hieter, 1989 BA1926 GFP followed by ADH1 terminator cloned into pRS315 Andrews lab BA1927 CLN2 promoter cloned upstream of GFP in BA1926 Andrews lab *pr-tdTomato::hphMX reporters were integrated in the SGA compatible query strain Y7092. If other control reporter genes are desired, they should be integrated into the strain Y7092. his5 refers to the gene from Schizosaccharomyces pombe (Tong, 2007).

 

 

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2.2.2 Generating an output array of GFP and RFP reporter genes in yeast deletion mutants

We are using the SGA technique to simultaneously introduce GFP and RFP reporter

genes into an array of ~4500 yeast deletion mutants. The yeast deletion collection (Giaever

et al., 2002) is comprised of strains in which each of the known or predicted ORFs is deleted

and replaced with the KanMX antibiotic-resistance marker (available from OpenBioSystems:

http://www.openbiosystems.com) or EuroScarf: http://web.uni-

frankfurt.de/fb15/mikro/euroscarf).

In Figure 2-1, I summarize the strategy for producing an output array of both reporter

genes in each deletion mutant. The SGA technique automates yeast genetics and has been

described elsewhere, including detailed descriptions of drug selections (Tong, 2005; Tong,

2007). My approach follows the basic SGA protocol, and pertinent features for my method

include: 1) omission of leucine from the media to select growth of yeast carrying the GFP

reporter plasmid and hygromycin B and G418 addition to allow for selective growth of yeast

carrying the RFP reporter gene and gene deletion respectively; 2) omission of histidine to

allow selective growth of MATa meiotic progeny, since only these cells express the STE2pr-

his5 reporter. Other drug additions and amino acid omissions are used to specifically enrich

for haploid yeast after sporulation which is described in detail in (Tong, 2007).

 

 

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Figure 2-1: Overview of the dual reporter SGA methodology. A lawn of the MATα query strain BY4256 or BY4347 containing the LEU2-marked pr-GFP plasmid and control pr-RFP gene is crossed to an array of MATa haploid gene-deletion mutants on YEPD. can1Δ and lyp1Δ markers and canavanine and thialysine selections are described in Tong et al., 2007. The result of the SGA-based cross is an array of yeast deletion mutants, each containing the pr-GFP reporter and RPL39pr-RFP control gene. Fluorescence intensities are measured directly from the colonies arrayed on the final agar plates using a scanning fluorimager and the resulting scans are quantified using GenePix Pro version 3.0 software. Yellow circles represent colonies in which GFP and RFP fluorescence intensities are relatively equal, as is expected for deletion mutants that do not affect GFP expression. Green circles represent yeast strains containing deletions in candidate repressors. Red circles represent yeast strains containing deletions in candidate activators. Digital images of the final selection plates are taken after scanning and colony sizes are scored to exclude strains that are sick, dead, or mis-pinned from the analysis. XXX: wild-type allele, xxxΔ: gene-deletion allele, black oval: LEU2-marked plasmid, blue box: promoter, green box: GFP, SGA methodology adapted from (Tong, 2007).

 

 

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The following serves as a guide to generate haploid yeast strains harbouring LEU2-

marked GFP reporter plasmids and an integrated HphMX marked RFP reporter combined

with a KanMX gene deletion. All manipulations of yeast arrays can be performed using

hand pinning tools or robotics (specialized robots for manipulating yeast arrays are available

from BioRad, Singer Instruments or S&P Robotics). The general protocol summarized

below can be completed in less than three weeks and effectively substitutes for many

thousands of individual yeast transformations.

Day 1: Create a lawn of the strain BY4256 or BY4347 (Table 2-1) harbouring a pr-GFP

reporter gene of interest on a CEN-based plasmid on SC -Leu solid media (prepared in Nunc

brand single well OmniTrays). Grow for 2 days at 30 °C.

Day 3: Mate the lawn to 14 plates of arrayed yeast deletion mutants, in 768-colonies per

plate density on YEPD solid media. Incubate for 1 day at 30 °C.

Day 4: Replicate onto SC -Leu +200 µg/ml G418 (G418 Sulfate/Geneticin, Gibco,

Invitrogen Corp.) diploid selection plates. Incubate at 30 °C for 2 days.

Day 6: Repeat selection on SC -Leu +200 µg/ml G418 plates to further enrich for

heterozygous mutant strains carrying the pr-GFP reporter. Incubate at 30 °C for 1 day.

Day 7: Replicate the array of diploids onto enriched sporulation media. Incubate for 5 days

at 22 °C.

Day 12: Select MATa haploids on SC -Leu -Arg -His -Lys +50 µg/ml canavanine +50 µg/ml

thialysine +200 µg/ml G418 plates. Incubate at 30 °C for 3 days. Canavanine (L-

Canavanine Sulfate Salt) and thialysine [(S-(2-Aminoethyl)-L-cysteine hydrochloride/L-4-

Thialysine hydrochloride)] are available from Sigma Aldrich Co.

 

 

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Day 15: Select MATa haploids on SC -Leu -Arg -His -Lys +50 µg/ml canavanine +50 µg/ml

thialysine +200 µg/ml G418 +300 µg/ml hygromycin B (MP Biomedicals) plates. Grow for

2 days at 30 °C. Addition of hygromycin B allows selection of the control RFP reporter gene

in haploid strains carrying the GFP reporter and deletion mutation. Omitting hygromycin B

from the media on Day 12 conserves use of this drug.

Day 17: Select MATa haploids on final selection SC –Leu –Arg -His -Lys +50 µg/ml

canavanine +50 µg/ml thialysine +200 µg/ml G418 +300 µg/ml hygromycin B solid media.

Grow for 2 days at 30 °C. This step facilitates further enrichment of the final haploid strains.

The Day 17 plates are poured to a volume of 60 ml per OmniTray, generating plates of

optimal thickness for colony fluorescence imaging (see section 2.2.4).

Day 19: Digital imaging of plates (section 2.2.3) and colony fluorescence detection (section

2.2.4).

2.2.3 Digital imaging of yeast plates

The 14 plates representing the output array are individually photographed with a

Canon powershot G2 4.0 megapixel digital camera operated by Remote Capture software

version 2.7.5.27. These images are uploaded into Qt ColonyImager software version 1.01

(Boone and Andrews labs, unpublished software) to derive colony diameter values for each

array position measured in number of pixels. Automated systems for imaging yeast and

bacterial arrays are also available [http://www.sprobotics.com/spImager_Desc.html].

 

 

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2.2.4 Assaying GFP and RFP fluorescence intensities from colonies arrayed on agar plates

GFP and RFP fluorescence intensities are assayed directly from colonies arrayed on 14

agar plates using a fluorescence scanner (Typhoon Trio Variable Mode Imager, GE

Healthcare). The surface of the scanner is large enough to detect fluorescence from 7 plates

in a single run meaning two output scans are required to assay fluorescence signals from the

complete array of 14 plates. To collect colony fluorescence data, lids are removed from the

OmniTrays and the plates are inverted so that colonies are facing the glass surface of the

scanner. Plates are affixed to the scanner surface using clear tape to prevent movement

during the scan. To excite and measure fluorescence intensities from the GFP and RFP

fluorophores, Typhoon Scanner Control version 5.0 software is used with the following

settings:

1. Acquisition mode - fluorescence

2. Laser 1: 488 nm, emission filter: 520 BP40

Laser 2: 532 nm, emission filter: 580 BP30

3. Adjust photomultiplier tube (PMT) voltage so that GFP and RFP intensities measured

from colonies are below saturation. To detect RFP intensity from strains BY4256 and

BY4347, a PMT value of 615 volts is optimal. Users should generate a test plate of

colonies to determine the optimal PMT setting for GFP detection (Laser 1) which will

depend on the strength of the promoter driving GFP expression.

4. Pixel size: 100 microns

5. Focal plane: +3 mm

6. Start scan and save file

 

 

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GFP intensities are acquired first followed by RFP intensities. The duration of each scan is

~25 minutes. Thus, genome-wide scanning of 14 output array plates takes ~50 minutes. We

have taken care to pour final selection plates to a volume of 60 ml using a Wheaton

Unispense media pump so that colonies arrayed on these plates are 3 mm above the surface

of the scanner. Therefore, it is important that a focal plane setting of +3 mm is selected so

that the laser is focused directly on the colonies to allow maximal excitation of fluorescent

proteins in each colony.

2.2.5 Quantifying fluorescence intensities from output scans

The scanned output file (.gel) can be uploaded directly into GenePix Pro version 3.0

software for automated feature detection and quantification of both GFP and RFP intensities.

The median colony fluorescence intensity for each fluorophore corrected for local

background fluorescence is obtained from GenePix and is used for further data normalization

and analysis.

Additional notes:

The yeast deletion array we use is a collection of 14 plates where each deletion

mutant is represented twice. Each plate has 384 deletion mutants arrayed in duplicate in two

separate 16 x 24 grids producing an array with 768 colonies per plate (Tong, 2005). Note

that each plate is bordered by his3Δ deletion strains which benefit from a growth advantage

due to availability of additional nutrients compared to other colonies (Tong, 2007). These

border colonies are removed from further analysis to limit gene expression measurements

 

 

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derived from colonies with favourable growth advantages as a result of their arrayed

position.

2.3 Analysis of data from a genome-wide promoter-reporter screen

I carried out a screen to identify novel regulators of the CLN2 promoter, which drives G1

specific expression of the CLN2 gene, a key cyclin involved in promoting the G1 to S phase

transition (Hadwiger, 1989). CLN2 transcription is activated in late G1 of the cell cycle by

the transcription factor Swi4 (Nasmyth and Dirick, 1991; Ogas et al., 1991). Thus, I expect

deletion of SWI4 to result in decreased CLN2pr-GFP expression compared to its effect on the

control RPL39pr-RFP gene. By visual inspection of an output fluorescence scan, shown in

Figure 2-2, I find that SWI4 deletion does in fact cause a defect in CLN2 transcription.

 

 

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Figure 2-2: Representative fluorescence scan of a single output array plate. The output array consists of yeast deletion mutants carrying the CLN2pr-GFP construct and an integrated RPL39pr-RFP control gene arrayed in duplicate in a 768-colony per plate format. The left panel depicts the GFP fluorescence intensities, the centre panel depicts the RFP fluorescence intensities and the image overlay of both scans is shown in the right panel. Deletion of SWI4, the known hallmark transcriptional activator of CLN2 expression (Nasmyth and Dirick, 1991; Ogas et al., 1991), results in decreased GFP intensity by visual inspection.

 

 

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To identify regulators in an unbiased manner, I use a quantitative approach to generate a

high-confidence list of potential regulators controlling expression from a particular promoter.

This approach is described below in the context of CLN2 transcriptional regulation.

2.3.1 Using colony size data to filter dead/sick colonies from further analysis.

Colony size varies depending on the growth rate of individual mutant strains, which can

confound analysis of colony fluorescence. The data set obtained from each promoter screen

is filtered for dead/sick colonies using colony size values obtained from digital images of the

output array (section 2.2.3). Using a data set of 27 genome-wide pr-GFP reporter screens

(Andrews lab, unpublished data), we determined a threshold of minimal colony diameter

based on the observed distribution of colony size values. Colonies with diameters that

measure less than 345 pixel units (P-value < 0.01, normal distribution) are removed from the

data set. An example of this analysis and colony size distributions for the CLN2pr-GFP

screen is displayed in Figure 2-3.

 

 

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Figure 2-3: Colony size distribution of yeast deletion mutants. Arrays of colonies were imaged after final selection of haploid mutant strains harbouring the CLN2pr-GFP reporter plasmid and the RPL39pr-RFP control gene. Qt ColonyImager version 1.01 software was used to measure colony diameter in pixel units. The x-axis represents colony size measurements from four individual colony replicates of each deletion mutant binned in groups of 10 pixel units. The y-axis represents the frequency with which colony sizes fall into each bin. Based on the observed normal distribution of 27 pr-GFP screens (Andrews lab, unpublished data), we set a minimal colony size threshold of 345 pixel units. Each colony that is below this threshold should be removed from further analysis of fluorescence intensities.

 

 

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2.3.2 Normalization of GFP and RFP intensities

For each screen, the GFP and RFP intensities from both replicate mutant strains are

averaged and GFP:RFP log2 ratios of intensity measurements are obtained. The

normalization algorithm LOESS (Cleveland, 1979) is applied to the log2 ratios. LOESS

seeks to eliminate intensity-dependent artefacts in the data. In addition, since LOESS-

normalized log2 ratios are centered at zero, we can directly compare ratios from different

screens and jointly visualize data collected from multiple screens by clustering and other

computational approaches. We find that the LOESS-normalized log2 ratios of GFP to RFP

are reproducible in replicate screens on different plates and are unaffected by spatial artefacts

and small variations in colony size above the pre-determined threshold described above (data

not shown).

2.3.3 Correlation between replicate screens and display of genome-wide data

I screened the CLN2pr-GFP reporter in duplicate to assess the reproducibility of our

results and found that GFP:RFP log2 ratios of replicate experiments correlated with R=0.90

(Figure 2-4).

 

 

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Figure 2-4: Scatter plot of replicate CLN2pr-GFP screens. We carried out each screen in duplicate to assay the reproducibility of our system and found that log2 GFP:RFP measurements from individual screens correlate with Pearson R=0.90. Correlation was determined by comparing the average log2 GFP:RFP ratio from two replicate colonies from individual screens.

 

 

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Quantified, normalized log2 GFP:RFP fluorescence intensity ratios are sorted in

ascending order to identify deletion mutants with decreased GFP:RFP (putative activators)

and those with increased GFP:RFP (putative repressors) ratios. Figure 2-5 shows the data

obtained from the genome-wide CLN2pr-GFP screen. Points on the curve represent

normalized fluorescent protein intensities averaged from four replicate deletion mutant

colonies. As expected, most deletion mutants do not affect transcription and are represented

on the flat portion of the curve in Figure 2-5A. The sigmoidal nature of the curve suggests

putative activators will be discovered in the tail of mutants with log2 GFP:RFP ratios below

zero and putative repressors identified in the tail of mutants with log2 GFP:RFP ratios above

zero. My survey of the genome reveals that deletion of SWI4, which is the known

transcriptional activator of CLN2 gene expression (Nasmyth and Dirick, 1991; Ogas et al.,

1991), results in the greatest defect in CLN2pr-GFP expression when normalized to the

RPL39pr-RFP measurement (Figure 2-5A). Note that quantitative measurements from a

single reporter screen using only GFP would fail to detect Swi4 as the major activator of

CLN2 gene expression (Figure 2-5B). Instead, Tps2, which is a phosphatase involved in the

synthesis of the carbohydrate trehalose (De Virgilio et al., 1993), would have erroneously

appeared as the top transcriptional activator. This is likely due to the reduced colony size of

the tps2∆ strain on the output array from which the GFP measurement was taken.

In Figure 2-5A, a 2–fold increase and decrease in reporter expression is marked to orient

the reader. To define thresholds for establishing regulators, the data represented here can be

transformed to Z-scores, and P-values can be assigned based on a normal distribution. Users

can set P-value cut-offs for individual screens depending on the stringency desired.

 

 

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Figure 2-5: Screening deletion mutants to identify regulators of the CLN2 promoter. (A) Distribution of log2

GFP:RFP ratios from genome-wide analysis of the CLN2 promoter. The y-axis represents log2 GFP:RFP ratios measured from each deletion mutant displayed on the x-axis. When CLN2pr-GFP fluorescence intensities are standardized to the control RPL39pr-RFP intensities, we find deletion of the known activator SWI4 results in the greatest defect in CLN2 reporter transcription. (B) Quantitative measurements of a single reporter screen. The y-axis represents GFP intensities measured from each deletion mutant displayed on the x-axis. If only CLN2pr-GFP intensities are considered, our quantitative analysis fails to detect Swi4 as the major transcription factor that activates CLN2 gene expression. Instead, we falsely detect Tps2 as the top activator.

 

 

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Additional notes

The majority of our pr-GFP screens were carried out using a CEN-based low copy

plasmid. In cases where GFP expression from a given promoter is weak, the reporter

construct can be moved to a high copy plasmid to sufficiently amplify the GFP signal for

robust detection. Cell-to-cell variation in plasmid copy number should be considered when

designing single-cell imaging experiments. However, our system involves detection of

fluorescence intensities from whole colonies comprised of many cells, making plasmid copy

number of little concern. If desired, it is possible to integrate the GFP reporter gene into the

genome.

It should also be noted that since our reporter constructs contain the entire intergenic

region (up to 1000 base pairs upstream of each ORF), the 5’ UTR corresponding to each

gene being studied will be included in the transcript. Thus, mutants required for post-

transcriptional regulation through interaction with the 5’ UTR could potentially be

indentified in our screen. For example, the 5’ UTR of the Yap2 transcript has been

implicated in decay of YAP2 mRNA (Vilela et al., 1999).

Since our approach relies on the SGA methodology to construct output arrays of

reporter genes in deletion mutant backgrounds, users should be aware that KanMX gene

deletions linked to markers used in the MATα query strain cannot be screened. For example,

screening KanMX deletion strains linked to the HO gene requires integration of the control

promoter-RFP::hphMX gene at a locus other than HO in the MATα query strain. I also note

that because this approach relies on reporter proteins driven by specific promoters, it does

not provide a direct measure of transcript levels of the endogenous gene controlled by the

 

 

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promoter studied. An independent verification assaying endogenous transcript levels in

identified deletion strains should be carried out.

2.4 Concluding remarks

I developed a two-colour promoter-reporter system that makes use of high-throughput

genetics and the array of viable haploid deletion mutants to understand transcription factor

pathways in yeast. This method could also be used to screen any appropriately marked yeast

array, so that additional types of genetic perturbations as well as the roles of essential genes

can be assessed. Relevant strain collections include arrays where each yeast ORF is

overexpressed (Sopko et al., 2006), tetracycline-repressible alleles (Mnaimneh et al., 2004)

and the decreased abundance of messenger RNA by perturbation (DAmP) alleles (Schuldiner

et al., 2005). Additionally, the dual-reporter system can be used to screen promoters in

various experimental conditions by pinning the output reporter gene arrays on the appropriate

medium or growing them under specific environmental conditions. Such an approach should

prove useful in revealing how cells integrate external environmental signals into their gene

expression program. Finally, this two-colour promoter-reporter system can be applied to

virtually any pathway for which a fluorescent reporter can be designed, representing a

powerful and general approach for analysis of biological pathways.

 

 

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Chapter 3

A two-color cell array screen reveals interdependent roles for histone chaperones and a

chromatin boundary regulator in histone gene repression

The work described in this Chapter is published as:

Jeffrey Fillingham*, Pinay Kainth*, Jean-Philippe Lambert, Harm van Bakel, Kyle Tsui, Lourdes Peña-Castillo, Corey Nislow, Daniel Figeys, Timothy R. Hughes, Jack Greenblatt, and Brenda Andrews. Two-colour cell array screen reveals interdependent roles for histone chaperones and a chromatin boundary regulator in histone gene repression. Molecular Cell. 35, 2009, 340-351.

* These authors contributed equally to this work. Permission to reprint this work was obtained from Elsevier. Author contributions: PK developed and carried out the HTA1 promoter-GFP screen, analyzed the reporter data, carried out all of the qPCR experiments, initiated collaborations with JF, JG, KT, CN and HvB, and assisted JF with writing the manuscript. JF carried out all of the ChIP experiments in this study, initiated the collaboration with JL and DF and wrote the initial draft of the manuscript. JL did the co-purification experiment in Figure 3-4D under supervision from DF. KT and CN carried out the nucleosome positioning experiments in Figures 3-5C and D. HvB normalized the nucleosome positioning data and assisted PK with analysis. LP normalized the data from the HTA1 promoter-GFP screen. TRH and JG assisted with editing the manuscript. BA directed the entire project and assisted with writing and editing the manuscript.

 

 

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Abstract

In this Chapter, I describe application of a fluorescent reporter system that I developed to

systematically assess consequences of genetic perturbations on gene expression (Chapter 2).

I used the so-called Reporter-Synthetic Genetic Array (R-SGA) method to screen for

regulators of core histone gene expression. I discovered that the histone chaperone Rtt106

functions in a pathway with two other chaperones, Asf1 and the HIR complex, to create a

repressive chromatin structure at core histone promoters. Activation of histone (HTA1) gene

expression involves both relief of Rtt106-mediated repression by the activity of the histone

acetyltransferase Rtt109 and restriction of Rtt106 to the promoter region by the

bromodomain-containing protein Yta7. I propose that the maintenance of Asf1/HIR/Rtt106-

mediated repressive chromatin domains is the primary mechanism of cell cycle regulation of

histone promoters. These data suggest that the HIR/Rtt106 pathway may represent a

chromatin regulatory mechanism that is broadly used across the genome.

 

 

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3.1 Introduction

Waves of cell cycle-regulated transcription are a universal feature of eukaryotic cell

cycles, yet our understanding of mechanisms linking gene expression to the cell cycle

remains incomplete. Conventional genetic screens in yeast, and complementary experiments

in many systems, have provided considerable insight but it is clear that many regulators

remain to be discovered. One important group of cell cycle-regulated genes encode histones

which form the nucleosome. Transcription of core histone genes is coordinated with the cell

cycle to ensure large amounts of new histones are available during DNA replication (Gunjan

et al., 2005). The restriction of histone gene expression to S phase (DNA synthesis) is

required not only to produce adequate histone pools but also to prevent toxicity that is

associated with their inappropriate overexpression at other stages of the cell cycle (Gunjan

and Verreault, 2003; Sopko et al., 2006). The yeast S. cerevisiae has proven a useful model

to understand the mechanism of regulation of core histone transcription. S. cerevisiae

contains two copies of each core histone gene, each of which is arranged in opposite

orientation to a gene encoding its dimer partner within the nucleosome: HHT1-HHF1 and

HHT2-HHF2, the two gene pairs that encode H3/H4, and HTA1-HTB1 and HTA2-HTB2, the

two gene pairs that encode H2A/H2B.

Four genes were identified in yeast genetic screens that encode transcriptional

repressors of three of the four histone gene pairs, HTA1-HTB1, HHT1-HHF1 and HHT2-

HHF2, both outside of S-phase and in response to hydroxyurea (HU), a chemical that causes

stalling of DNA replication forks (Osley and Lycan, 1987; Xu et al., 1992). These four

proteins, Hir1, Hir2, Hir3, and Hpc2, were subsequently demonstrated to co-purify as the

HIR protein complex (HIR) (Green et al., 2005; Prochasson et al., 2005). A fifth protein,

 

 

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Asf1, also co-purifies with HIR (Green et al., 2005) and is similarly required to repress

transcription of HTA1-HTB1, HHT1-HHF1, and HHT2-HHF2 (Sutton et al., 2001). Asf1

and HIR are both histone chaperones, proteins that bind to histones and assemble or

disassemble chromatin (reviewed in De Koning et al., 2007). Asf1 and HIR are H3/H4-

specific chaperones that together are able to deposit histones onto DNA in a replication-

independent manner in vitro (Green et al., 2005).

Two members of the HIR protein complex, Hir1 and Hir2, share homology to the

HIRA protein in human cells (Lamour et al., 1995). Deletion of one copy of HIRA is

thought to underlie the human disease DiGeorge syndrome (Lamour et al., 1995). The N-

terminal region of HIRA shares homology to the yeast Hir1 protein, which contains a WD40

domain (Lamour et al., 1995). The C-terminal region of HIRA shares homology with the

yeast Hir2 protein suggesting that the human HIRA protein may be the result of a Hir1/Hir2

fusion (Lamour et al., 1995). The HIR protein complex in yeast has been largely

characterized in terms of its role in repressing transcription of histone genes to allow proper

S-phase specific expression of these genes.

The HIR proteins are also involved in heterochromatin silencing along with the CAF-

1 (chromatin assembly factor 1) complex, another H3-H4 histone chaperone. CAF-1 is a

complex of three proteins (Cac1, Cac2 and Msi1). Strains that harbour a mutation in both

HIR1 and members of CAF-1 show synergistic defects in heterochromatin silencing,

suggesting that HIR and CAF-1 may function in two separate pathways to create silenced

regions of chromatin (Sutton et al., 2001). Rtt106, another H3-H4 histone chaperone protein,

was found to interact physically with Cac1 and participate in heterochromatin silencing

(Huang et al., 2005). Subsequent studies revealed that the histone chaperones CAF-1 and

 

 

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Rtt106 are required to recruit Sir1 and Sir3 to the silent mating type locus HMR in yeast

(Huang et al., 2007).

In addition to their role in heterochromatin silencing, Rtt106 and CAF-1 play a

distinct role from the HIR complex in replication-coupled nucleosome assembly where

Rtt106 and CAF-1 assemble nucleosomes onto newly replicated DNA during S-phase of the

cell cycle. Lysine 56 on histone H3 is acetylated (H3 K56Ac) by action of the histone

acetyltransferase Rtt109 and the associated histone chaperone Asf1, a chromatin mark that is

involved in genome stability and is also incorporated into the promoter regions of genes

(Collins et al., 2007; Driscoll et al., 2007; Han et al., 2007a; Masumoto et al., 2005; Recht et

al., 2006; Rufiange et al., 2007). Recent studies have shown that this acetylation mark

increases the affinity for Rtt106 and CAF-1 binding to histone H3 (Li et al., 2008). Although

Rtt106 and CAF-1 do not contain an acetyl lysine binding bromodomain, the only domain

previously known to bind acetylated histones (Kouzarides, 2007), Rtt106 was found to have

a PH domain similar to that in Pob3 (Li et al., 2008). Pob3 is a member of the FACT

complex and is involved in remodeling nucleosomes to allow RNA polymerase II elongation.

This PH domain in Rtt106 from residues 195 to 301 is necessary for binding K56Ac histone

H3 (Li et al., 2008). Further work showed that both Rtt106 and CAF-1 are required to

deposit H3 K56Ac histones onto newly replicated DNA (Li et al., 2008).

As noted above, repression of histone gene transcription has been characterized in

terms of the histone chaperone pathway that involves Asf1 and HIR. Asf1/HIR-mediated

repression of histone transcription relies on a specific DNA sequence, the negative regulatory

element (NEG), found in the promoters of the three HIR-regulated gene pairs but absent

from that of HTA2-HTB2 (Osley et al., 1986; Osley and Lycan, 1987). The NEG sequence is

 

 

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required for proper cell cycle regulation of histone genes and when deleted, constitutive

histone transcription is observed (Osley, 1991; Osley et al., 1986). The only proteins known

to regulate HTA2-HTB2 are Spt10 and Spt21 (Dollard et al., 1994). Deletion of SPT10

reduces levels of all core histone gene transcripts to some degree (Hess et al., 2004; Xu et al.,

2005) possibly by acetylating histone H3 K56, although histone acetyltransferase activity for

Spt10 has not been shown. Additionally, the promoters of histone genes contain DNA

binding sites that are bound by Spt10 (Eriksson et al., 2005).

Although several regulators of histone gene expression are known, underlying

molecular mechanisms remain unclear. To address this void, I sought to exploit the

functional genomic tools available in yeast for performing rapid, saturating genetic screens.

Specifically, as described in Chapter 2, I devised a two-color GFP-RFP reporter system

called Reporter-Synthetic Genetic Array (R-SGA) to systematically assess the consequences

of gene deletions on a promoter of interest. I used R-SGA to screen an HTA1 reporter gene

and discovered a previously unappreciated role for the H3/H4 histone chaperone Rtt106 in

repression of histone gene expression. We demonstrate that Rtt106 functions downstream of

Asf1 and the HIR complex to create a repressive chromatin structure at the HTA1-HTB1

regulatory region. My genomic screen also revealed an activating role for Yta7, an

evolutionarily conserved protein containing both a bromodomain and an AAA ATPase

domain. Our molecular analysis indicates that Yta7 acts as a boundary element within the

HTA1 locus, preventing the spread of Rtt106 and associated repressive chromatin into the

histone gene coding regions. I also discovered that the HAT, Rtt109, functions as an HTA1

activator and genetic tests suggest that it counters HIR/Rtt106 repressive chromatin to permit

transcription in a cell cycle-regulated manner. Finally, our genome-wide analysis of

 

 

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nucleosome positioning suggests that comparable HIR/Rtt106-Yta7 domains may dictate

regions of repressive chromatin throughout the genome.

3.2 Experimental Procedures

3.2.1 Yeast Strains and Plasmids

Yeast strains are listed in Table 3-1. Strains were constructed using standard yeast media

and genetic approaches. To generate the promoter-reporter construct, GFP (S65T) followed

by the ADH1 terminator sequence was amplified from the plasmid pFA6a-GFP S65T-ADH1

HIS3MX6 (Wach et al., 1997) and cloned into the SacI-PstI sites of plasmid pRS315

(Sikorski and Hieter, 1989), giving rise to the plasmid BA1926. The entire HTA1-HTB1

intergenic region was PCR amplified and cloned into plasmid BA1926 adjacent to GFP

leading to the reporter plasmid BA1930, which was subsequently transformed into the strain

BY4256 (Kainth et al., 2009).

 

 

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Table 3-1: Strains used in this Chapter.

Strain Genotype Source BY4741 MATa, ura30, leu20, his31, met150 Winzeler et al., 1999 SC217 BY4741, asf1::KANMX Winzeler et al., 1999 SC218 BY4741, rtt109::KANMX Winzeler et al., 1999 JF08-405 BY4741, rtt106∆::KANMX Winzeler et al., 1999 JF08-406 BY4741, hir1∆::KANMX Winzeler et al., 1999 JF08-407 BY4741, yta7∆::KANMX Winzeler et al., 1999 6109 BY4741, swi4∆::KANMX EUROSCARF 1298 BY4741, spt10∆::KANMX EUROSCARF BY4742 MATα, his3Δ1, leu2Δ0, lys2Δ0 ura3Δ Winzeler et al., 1999 Y7092 MATα , can1Δ::STE2pr-his5, lyp1Δ Tong et al., 2007 BY4256 Y7092, HO::RPL39pr-tdTomato::hphMX Kainth et al., 2009 SN1601 Y7092, MATα, hir1∆::NAT Boone lab SN1483 Y7092, MATα, rtt106∆::NAT Boone lab BY4594 MATα, hir1∆::NAT, rtt109∆::KAN This work BY4595 MATα, rtt106∆::NAT, rtt109∆::KAN This work BY4596 MATα, rtt106∆::NAT, hir1∆::KAN This work JF08-32 BY4741, SPT10-TAP::HIS3 TAP fusion library JF08-25 BY4741, HIR1-TAP::HIS3 TAP fusion library JF08-402 BY4741, HIR2-TAP::HIS3 TAP fusion library JF08-403 BY4741, HIR3-TAP::HIS3 TAP fusion library JF08-404 BY4741, HPC2-TAP::HIS3 TAP fusion library JF08-21 BY4741, RTT106-TAP::HIS3 TAP fusion library JF08-000 BY4741, CAC1-TAP::HIS3 TAP fusion library JF08-26 BY4741, HIR1-TAP::HIS3, asf1∆::NAT This work JF08-294 BY4741, HIR1-TAP::HIS3, rtt106∆::KANMX This work JF08-293 BY4741, HIR1-TAP::HIS3, hpc2∆::KANMX This work JF08-22 BY4741, RTT106-TAP::HIS3, asf1∆::NAT This work JF08-23 BY4741, RTT106-TAP::HIS3, hir1∆::KANMX This work JF08-24 BY4741, RTT106-TAP::HIS3, rtt109∆::NAT This work JF08-256 BY4741, RTT106-TAP::HIS3, hir2∆::KANMX This work JF08-257 BY4741, RTT106-TAP::HIS3, hir3∆::KANMX This work JF08-258 BY4741, RTT106-TAP::HIS3, hpc2∆::KANMX This work JF08-255 BY4741, RTT106-TAP::HIS3, cac2∆::KANMX This work JF08-306 BY4741, SPT5-HA::KANMX This work JF08-278 BY4741, SPT4-TAP::HIS3 TAP fusion library JF08-282 BY4741, SPT6-TAP::HIS3 TAP fusion library JF08-270 BY4741, SPT16-TAP::HIS3 TAP fusion library JF08-285 BY4741, POB3-TAP::HIS3 TAP fusion library JF08-275 BY4741, YTA7-TAP::HIS3 TAP fusion library JF08-276 BY4741, YTA7-TAP::HIS3, hir1∆::KANMX This work JF08-277 BY4741, YTA7-TAP::HIS3, rtt109∆::KANMX This work JF08-295 BY4741, HIR1-TAP::HIS3, yta7∆::KANMX This work JF08-253 BY4741, RTT106-TAP::HIS3, yta7∆::KANMX This work BY4597 MATα, rtt106∆::KAN, yta7∆::NAT This work

 

 

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3.2.2 SGA-based Functional Genomic Screen for Regulators of HTA1 expression

A detailed description of this method is described in Kainth et al., 2009 and in

Chapter 2. By using the SGA methodology (Tong, 2007), the HTA1pr-GFP reporter plasmid

(BA1930) along with the control RFP reporter gene was combined with each yeast deletion

mutant. Colony size for each arrayed mutant was derived using Qt ColonyImager software

version 1.01 (Boone and Andrews labs, unpublished) and positions on the array with no or

slow colony growth were removed from further analysis. Colony fluorescence was assayed

using the Typhoon Trio variable mode imager (GE Healthcare) and quantification was

carried out with GenePix Pro 3.0 software. Each screen was carried out in duplicate where

deletion mutants are represented twice on the array. GFP and RFP intensities were averaged

from replicate deletion mutant colonies on the array and log2 GFP:RFP ratios computed.

LOESS-normalized (Cleveland, 1979) log2 GFP:RFP ratios from duplicate screens were

averaged, giving rise to a single gene expression measurement for each deletion strain

derived from a total of 4 independent colonies. These log2 ratios were transformed to robust

Z-scores using median and median absolute deviation and P-values were assigned to these Z-

scores using the normal distribution. From a diverse dataset of 27 promoter-GFP reporter

screens, I obtained a list of 260 deletion mutants that usually appear as hits in these screens

(Andrews lab, unpublished data), which were removed from further analysis of specific

HTA1 promoter regulators.

3.2.3 qPCR Analysis of Histone Gene Expression

RNA was prepared using the RNeasy mini kit (Qiagen). The QuantiTect Reverse

Transcription Kit (Qiagen) was used to eliminate contaminating genomic DNA and to

 

 

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synthesize cDNA from ~1 µg of RNA. qPCR reactions were set up using manufacturers

conditions with the TaqMan Core Reagents PCR kit (Applied Biosystems) containing

AmpliTaq Gold polymerase (Roche Molecular Systems Inc.) on a 7500 Real-Time PCR

block (Applied Biosystems). Primer annealing/extension for all qPCR reactions was 60 °C.

TaqMan gene specific probes were purchased from Applied Biosystems. To distinguish

between similar copies of histone genes, reverse primers annealing to the 3’ UTR of histone

transcripts were used.

3.2.4 Chromatin Immunoprecipitation (ChIP)

Soluble chromatin was prepared from cells treated with formaldehyde and

immunoprecipitated using standard procedures (Kim et al., 2004). Chromatin prepared from

TAP-tagged strains was incubated with IgG-Sepharose (Amersham). Antibodies against

histones H3 and H2B were obtained from Lake Placid Biologicals and used at a

concentration of 1:200. Immunoprecipitated DNA was analyzed by semi-quantitative,

multiplex PCR, always including an internal control (either a region of ACT1 or a non-

transcribed region of chromosome V, as indicated) for background. PCR reactions were

separated on 6% PAGE, imaged, and in some cases quantified by using a Typhoon

phosphoimager. For ChIP reactions that required quantification, the ratio of the experimental

to the control signal for the precipitated DNA was divided by the ratio of the experimental to

the control signal for the input DNA.

 

 

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3.2.5 Purification and Analysis of Rtt106-associated proteins

Proteins associated with Rtt106-TAP were purified utilizing a modified TAP

purification procedure and subsequently identified by mass spectrometry. The mChIP

protocol consists of a single affinity purification step, whereby chromatin-bound protein

networks are isolated from mildly sonicated and gently clarified cellular extracts using

magnetic beads coated with antibodies (Lambert et al., 2009). This procedure reduces

sample loss due to poor

solubility of chromatin-associated protein complexes by shearing DNA through sonication to

maximize the protein complex solubility, and by reducing to a minimum the need for sample

centrifugation. The mChIP procedure was previously shown to be successful at purifying

proteins associated with both histone and non-histone chromatin-bound baits (Lambert et al.,

2009). Mass spectrometry analysis of gel slices was performed using LC-MS/MS as

described (Lambert et al., 2009).

3.2.6 Genome-wide nucleosome occupancy

Isolation of nucleosome bound DNA and hybridization onto the yeast tiling array

(Affymetrix) was carried out according to Lee et al., 2007.

3.3 Results

3.3.1 A dual-reporter functional genomic screen to discover new regulators of gene

expression

As described in Chapter 2, I devised a two-colour GFP-RFP reporter system called

Reporter-Synthetic Genetic Array (R-SGA) to systematically assess the consequences of

 

 

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gene deletions on a promoter of interest (Figure 3-1A). The system involves creation of a

wild type yeast strain with the promoter sequence of a particular gene of interest fused to

GFP along with a control reporter construct with the constitutively expressed RPL39

promoter driving tdTomato (Shaner et al., 2004) (RFP) expression. The dual-reporter strain

is compatible with SGA methodology which enables marked genetic elements to be

combined in a single haploid cell through standard yeast mating and meiotic recombination

via an automated procedure (Tong et al., 2001; Tong et al., 2004). My goal was to survey

the yeast deletion collection (Giaever et al., 2002), which contains the set of ~4500 viable

KanMX-marked deletion mutants, for defects in gene expression. To do so, I apply the SGA

approach to introduce both the test and control fluorescent reporters into the deletion

collection. The resulting panel of yeast deletion mutants is then assayed for enhanced or

diminished promoter-GFP expression by scanning both fluorescence intensities directly from

colonies arrayed on agar plates using a scanning fluorimager. The ratio of GFP to RFP

fluorescence intensity for each yeast deletion mutant provides a genome-wide survey of the

effect of viable deletion mutants on the promoter of interest. I expect decreased GFP:RFP

when the deleted gene is a specific activator of the reporter gene, while deletion of a

repressor will result in higher GFP:RFP.

3.3.2 Identification of regulators of HTA1 expression

To uncover new regulators of S-phase specific expression of histone genes, I fused

the HTA1 promoter to GFP (HTA1pr-GFP) and used the R-SGA-based screening approach

described above (Figure 3-1A) to explore the genome for potential regulators of HTA1

expression. I carried out this screen in duplicate using a yeast deletion array where each

 

 

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mutant is represented twice, providing an average GFP:RFP intensity from 2 deletion mutant

colonies for each replicate screen. Thus, log2 GFP:RFP ratios are averaged from 4 replicate

deletion mutants. As a test of significance of mutants causing differential GFP:RFP

expression, we assigned P-values to these log2 ratios based on the normal distribution of Z-

scores transformed from average log2 ratios from each screen. From replicate experiments,

we observed a Pearson correlation of 0.81.

 

 

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Figure 3-1: Reporter-Synthetic Genetic Array (R-SGA) functional genomic screen for regulators of HTA1 expression. (A) Outline of R-SGA screening procedure describing construction of the output array having each deletion mutant combined with GFP and RFP reporter genes. Fluorescence is assayed directly from colonies arrayed on agar plates using a scanning fluorimager, and GFP:RFP ratios are calculated to assess specific effects of gene deletions on the GFP reporter of interest (see Methods). (B) Results of R-SGA screen for identification of regulators of the histone H2A gene HTA1. A reporter plasmid with the promoter normally driving HTA1 expression fused to GFP was screened as described in (A). Gene expression measurements taken from 3907 yeast deletion mutants are displayed, and mutants causing differential GFP expression with P-value < 10-4 are highlighted. (C) The fold change in GFP:RFP for each mutant is described along with corresponding P-values for each gene expression measurement.

 

 

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Since the screen relies on GFP under the control of the HTA1 promoter, I expect

candidate regulators to reflect bona-fide promoter regulation rather than regulation of histone

mRNA stability, unless deletion mutants regulate the 5’ UTR of the transcript. As proof of

the utility of the approach, I identified a number of previously characterized HTA1 gene

regulators in my screen including HPC2, HIR1, HIR2, HIR3, ASF1 and SWI4 (Figure 3-1B)

(Green et al., 2005; Hess and Winston, 2005; Osley and Lycan, 1987; Prochasson et al.,

2005; Simon et al., 2001; Xu et al., 1992). Specifically, deletion of HPC2, HIR1, HIR3,

HIR2 or ASF1 caused HTA1pr-GFP expression to increase between 2 to 3.9-fold (Figure 3-

1C). Deletion of the known HTA1 transcriptional activator SWI4 caused a reduction in GFP

levels by 1.8-fold (Figure 3-1C). These results validate the utility of my approach and led

me to explore regulatory roles of other genes uncovered from my screen. These include the

histone H3-H4 chaperone, RTT106, which upon deletion caused a 2.5-fold increase in

HTA1pr-GFP expression, suggesting Rtt106 has a repressive role in HTA1 transcription. In

contrast, deletion of the H3-specific histone acetyltransferase, RTT109, caused a 2.5 fold

reduction in HTA1 expression (Figure 3-1C), which links Rtt109 to HTA1 activation. Other

genes uncovered by my screen that potentially encode activators of HTA1 expression include

YTA7, VPS75, and RRM3 (Figure 3-1C). Vps75 is a histone chaperone that copurifies with

the HAT Rtt109 and associates with Rtt109 to acetylate histone H3 K9 (H3 K9Ac)

(Fillingham et al., 2008). Rrm3 is a DNA helicase that helps replication forks pass protein-

DNA complexes (Ivessa et al., 2003). Yta7 encodes a bromodomain-containing protein that

was recently suggested to repress histone transcription (Gradolatto et al., 2008). However, in

my R-SGA screen, deletion of YTA7 resulted in decreased HTA1pr-GFP levels, indicating

Yta7 may have a more complex role at HTA1 than previously appreciated (see below).

 

 

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To confirm my screen results, I used quantitative real time-PCR (qPCR) to assess

endogenous HTA1 transcript levels in deletion mutants of potential HTA1 regulators.

Consistent with the results of my genomic screen, deletion of RTT106 resulted in increased

HTA1 transcript levels (Figure 3-2A). The de-repression observed in an RTT106 deletion

strain was clear but slightly less pronounced than that observed in a strain lacking HIR1. In

my R-SGA screen, deletion of ASF1 caused de-repression of the promoter (Figure 3-1C) but

endogenous HTA1 transcript levels appear similar to wild type (Figure 3-2A) which was

observed previously and suggests a dual role in repression and activation of histone genes by

Asf1 (Sutton et al., 2001). One possibility is that Asf1 is behaving as an activating factor at

the HTA1 coding region which would be missed in my screen since the promoter is fused to

GFP. In terms of confirming activators uncovered from my R-SGA screen, deletion of YTA7

and RTT109 caused decreased HTA1 transcript levels relative to wild type, similar to the

deletion of the previously described histone activators SPT10 and SWI4 (Hess and Winston,

2005) (Figure 3-2A). Because deletion of SPT10 causes a significant growth defect, it is

absent on the deletion array and thus was not tested in my R-SGA screen.

The HIR proteins and Asf1 repress HTA1 expression outside of S-phase. To

determine if Rtt106 represses HTA1 in a manner similar to that of the HIR proteins, I

assessed HTA1 expression during the cell cycle in cells deleted for RTT106 and HIR1, which

have no obvious cell cycle defect by FACS analysis (data not shown). Wild-type, rtt106∆

and hir1∆ strains were arrested in late G1 phase with alpha factor and HTA1 transcripts were

profiled every 15 minutes using qPCR after release as a synchronized culture into fresh

medium. In wild type cells, HTA1 transcription fluctuated throughout the cell cycle, peaking

in S-phase before being repressed as cells progress past S-phase into G2/M (Figure 3-2B).

 

 

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Consistent with previous results, deletion of HIR1 caused a significant defect in HTA1

expression, with obvious de-repression of gene expression throughout the cell cycle (Figure

3-2B). Similarly, the absence of RTT106 also caused constitutive HTA1 expression through

the cell cycle (Figure 3-2B). The HTA1 transcription peak occurred at 15-30 minutes after

alpha-factor release and was not completely repressed past S-phase of the cell cycle (45 and

60 minutes post release (Figure 3-2B)). Cell cycle regulation of CLB2 transcripts, which

peak at G2/M, was monitored to mark proper progression through the cell cycle. These

results indicate that the observed increase in HTA1 transcript levels in rtt106∆ log phase cells

is due to a failure to repress transcription outside of S-phase rather than over-activation

during S-phase of the cell cycle. It is important to note that cellular toxicity due to

inappropriate histone expression was not observed in these mutants, likely because

expression levels are not as high as those observed in other studies where constitutive histone

overexpression from GAL inducible histone genes affected cellular fitness (Gunjan and

Verreault, 2003; Sopko et al., 2006).

 

 

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Figure 3-2: Rtt106, Rtt109 and Yta7 regulate histone gene expression. (A) cDNA was prepared from the indicated strains. The ratio of the indicated transcript to that of ACT1 was determined using qPCR. (B) Rtt106 represses HTA1 through the cell cycle. Each strain was blocked with 5µM -factor, released and samples taken at the indicated times. For each time point, cDNA was prepared and analyzed using qPCR. CLB2 transcription was assayed in addition to show proper progression through the cell cycle. (C) HIR-regulated histone genes are also regulated by Rtt106. Error bars represent standard deviations from the mean from at least 3 replicate qPCR reactions.

 

 

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3.3.3 Rtt106 represses HIR-regulated histone genes

I next asked if Rtt106, like HIR, represses expression of other histone genes. First, I

tested the effect of RTT106 deletion on transcription of HTA1’s partner locus, HTB1. I did

not detect a significant effect of RTT106 deletion on transcription of HTB1 (Figure 3-2C),

possibly reflecting its demonstrated complex regulation by both transcriptional and post-

transcriptional mechanisms (Lycan et al., 1987; Xu et al., 1992). Both Asf1 and HIR repress

HHT1, HHF1, HHT2 and HHF2 gene expression. Likewise, I saw that deletion of RTT106

resulted in higher levels of HHT1, HHF1, HHT2 and HHF2 transcripts (Figure 3-2C),

indicating that the HHT1-HHF1 and HHT2-HHF2 loci are also regulated by Rtt106. Unlike

the other histone loci, HTA2-HTB2 is not subject to Asf1/HIR repression. Similarly, I found

that Rtt106 did not repress transcription of HTA2 and HTB2 (Figure 3-2C). I conclude that

Rtt106, like HIR and Asf1, represses transcription at three of the four histone gene pairs.

Rtt106 localizes to HTA1-HTB1 in a manner dependent on Asf1 and the HIR complex

My data link the histone chaperone Rtt106 to repression of HTA1-HTB1 expression.

To ask if Rtt106 acts directly on the HTA1-HTB1 promoter, we used chromatin

immunoprecipitation (ChIP) to assess whether Rtt106 and the four members of the HIR

complex localize to the HTA1-HTB1 region. Figure 3-3A shows the HTA1-HTB1 locus with

approximate locations of primer sets used in our ChIP analysis. As a control, we found that

Spt10-TAP cross-linked most effectively to the promoter region containing the NEG site as

well as several upstream activating sequences (primer set ‘C’, Figure 3-3B), consistent with

previous results (Eriksson et al., 2005; Xu et al., 2005).

 

 

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We next used ChIP to assay the cross-linking pattern of Rtt106 and the four members

of the HIR complex at HTA1-HTB1. Hir2 is known to cross-link at the promoter region of

HTA1-HTB1 (Green et al., 2005). Consistent with this result, we found that all four members

of the HIR complex, Hir1-TAP, Hir2-TAP, Hir3-TAP and Hpc2-TAP, specifically localized

to this region (Figure 3-3B and data not shown). HIR binding was restricted to only

background levels outside of region ‘C’ and at the ORFs (Figure 3B and data not shown).

Importantly, like the HIR proteins, Rtt106-TAP specifically localized to the HTA1-HTB1

promoter region and did not localize to the ORFs (Figure 3-3B).

 

 

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Figure 3-3: Rtt106 and HIR localize to the promoter region of HTA1-HTB1. (A) Schematic representation of the PCR products (A-E) used in ChIP to cover the HTA1-HTB1 locus. (B) Rtt106 and members of the HIR complex (but not Cac1) cross-link to the promoter region of HTA1-HTB1. PCR results from IgG-sepharose ChIP of an untagged negative control (WT) or positive control (Spt10-TAP) show that PCR products A-E effectively cover the locus. Precipitated chromatin was used for PCR amplification (upper panels). The top band is specific to the HTA1-HTB1 locus, while the common lower band (marked by an asterisk) is an internal background control from a nontranscribed region on chromosome V. The bottom panels show the input control. (C) Rtt106 and members of HIR cross-link to the promoters of the same set of histone genes. A similar analysis was performed as in Figure 3-3A with primers directed against the promoters of the indicated histone genes. ChIP analysis was performed exactly as in Figure 3-3B.

 

 

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Since HIR and Rtt106 repress three of the four histone loci (Figure 3-2C), we tested

whether they also localize to other histone promoters to further correlate transcriptional

effects with promoter binding. We used ChIP of Spt10-TAP to the promoter regions of the

four core histone promoters as a control for the performance of our primers. We also

assessed binding to the promoter region of the HTZ1 gene, which encodes an H2A variant

and serves here as a negative control since its transcription is not under cell cycle control. As

expected (Eriksson et al., 2005), Spt10-TAP effectively localized to the promoter regions of

the four core histone promoters, but not to that of HTZ1 (Figure 3-3C). Hir1-TAP also

cross-linked to the promoters of HTA1-HTB1, HHT1-HHF1 and HHT2-HHF2 but not HTA2-

HTB2 (Figure 3-3C), consistent with the failure of the HIR complex to regulate HTA2-

HTB2. Like Hir1, Rtt106-TAP also localized to the promoter region of HTA1-HTB1 and was

enriched at HHT1-HHF1 and HHT2-HHF2, although not to the same degree as at HTA1-

HTB1 (Figure 3-3C). Like Hir1, Rtt106 did not cross-link above background levels to

HTA2-HTB2. Thus, promoter localization of Hir1 and Rtt106 correlates with their ability to

specifically repress transcription of HTA1-HTB1, HHT1-HHF1 and HHT2-HHF2 but not

HTA2-HTB2.

So far, our experiments place HIR and Rtt106 in a common pathway that functions to

repress histone transcription. To further explore the relationship between Rtt106 and other

histone gene regulators, we used our ChIP assay to test the genetic requirements for specific

cross-linking of Hir1 and Rtt106 to the promoter of HTA1-HTB1. Consistent with previous

results (Green et al., 2005), deletion of HPC2 but not ASF1 prevented recruitment of Hir1-

TAP to the HTA1-HTB1 promoter (Figure 3-4A). Similar to ASF1, deletion of RTT106 did

not affect Hir1-TAP recruitment to HTA1-HTB1 (Figure 3-4A). However, when we deleted

 

 

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either HIR1 or ASF1, recruitment of Rtt106 to HTA1-HTB1 was undetectable (Figure 3-4B).

Rtt106-TAP recruitment to the HTA1-HTB1 promoter was also prevented by deletion of

HIR2, HIR3, or HPC2 (Figure 3-4C).

Asf1 and HIR form a protein complex in yeast (Green et al., 2005) and the interaction

of Asf1 with the HIR complex is abolished when any of the four HIR subunits are deleted.

These results suggest that an intact Asf1-HIR complex functions upstream of Rtt106

recruitment to HTA1-HTB1. By contrast, although Rtt106 physically interacts with the CAF-

1 protein complex (Huang et al., 2005), localization of Rtt106 to HTA1-HTB1 occurred

independently of Cac2, a subunit of the CAF-1 complex (Figure 3-4C) indicating that

Rtt106 is functioning in a CAF-1 independent pathway with the Asf1/HIR complex. This

result is consistent with the failure of Cac1-TAP to cross-link to the region (Figure 3-3B).

In order to determine the molecular basis of the HIR requirement for Rtt106 recruitment, we

co-purified its associated proteins and identified them using mass spectrometry (Lambert et

al., 2009). We co-purified two of the three members of the CAF-1 complex (Figure 3-4D)

along with Pol30/PCNA (which interacts with CAF-1), consistent with previous results

(Huang et al., 2005). In addition, we co-purified three of the four members of the HIR

complex (Figure 3-4D). Our genetic experiments demonstrating Asf1/HIR-dependent

localization of Rtt106 to HTA1-HTB1, coupled with these biochemical data, suggest a direct

physical interaction between these proteins at a core histone promoter.

 

 

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Figure 3-4: HIR and Asf1 are required for Rtt106 localization to HTA1-HTB1. (A) Hir1 localization to the HTA1-HTB1 promoter is independent of Asf1 and Rtt106. The analysis is the same as in Figure 3-3 with the exception that the top band represents PCR product ‘C’ from HTA1-HTB1. (B) Rtt106 localization to the HTA1-HTB1 promoter requires Asf1 and Hir1. The analysis is the same as above except that the internal background control (indicated by an asterisk) is from the ACT1 gene. Below the ChIP analysis, a western blot indicates that RTT106 expression is not dependent on Asf1 or Hir1. (C) Rtt106 localization to the HTA1-HTB1 promoter requires all members of HIR but not CAF-1. ChIP analysis is the same as in Figure 3-4A. Below the ChIP analysis, a western blot indicates that RTT106 expression is not dependent on expression of HIR members. (D) Affinity purification and identification of Rtt106-TAP associated proteins. A silver-stained SDS-PAGE is shown with affinity purified proteins from an untagged strain (-) and from Rtt106-TAP (+). Co-purifying proteins were identified by LC-MS/MS as described in Lambert et al., 2009. The percent sequence coverage is indicated in the table, with the number of unique peptides shown in parentheses.

 

 

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3.3.4 The HTA1-HTB1 promoter region is nucleosome-free in asf1, hir1, rtt106 mutants

As described in the Introduction, Asf1, the HIR complex and Rtt106 are histone

chaperones/chromatin assembly factors. To ask if their effects on HTA1-HTB1 transcription

are related to this function, we used an antibody generated against unmodified histone H3 to

assess H3 levels at the HTA1-HTB1 promoter in WT and several deletion strains (Figure 3-

5A). Compared to a WT strain, or a strain deleted for RTT109 which we also identified in

our screen (see below), the amount of H3 that cross-linked to the HTA1-HTB1 promoter in

asf1, hir1, and rtt106 was low relative to a control locus (Figure 3-5A). A similar

experiment with an antibody against unmodified histone H2B (Figure 3-5B) revealed that

histone H2B levels were significantly lower again in asf1, hir1, and rtt106 mutants

relative to a WT strain (Figure 3-5B).

 

 

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Figure 3-5: Asf1, HIR and Rtt106 collaborate to assemble chromatin at the HTA1-HTB1 promoter. (A, B) Chromatin was prepared from the indicated strains and immunoprecipitated with an antibody against histone H3 (A) or H2B (B). The top band in the ChIP analysis represents PCR product ‘C’ from HTA1-HTB1 and the internal background control (indicated by an asterisk) is from the ACT1 gene. (C, D) A genome-wide nucleosome positioning assay was used to identify regions of depleted nucleosomes in rtt106Δ and hir1Δ strains. The HTA1-HTB1 intergenic region is nucleosome free when RTT106 or HIR1 is deleted but has regions of higher and lower intrinsic occupancy in the in vitro experiments (C). In Panel (D) nucleosome profiles at promoter regions genome-wide are sorted in ascending order (most depleted in blue colour to most occupied in yellow colour) based on the average nucleosome occupancy up to 500 base pairs upstream of the transcriptional start site (TSS) for each ORF. The 50 top ranking nucleosome depleted promoter regions are shown. Histone genes are highlighted in red while other nucleosome depleted regions overlapping in rtt106Δ and hir1Δ strains are highlighted in cyan.

 

 

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To further explore the molecular defect in histone chaperone mutants, we assessed

genome-wide nucleosome occupancy of promoter regions in wild type cells as well as hir1∆

and rtt106∆ strains using a previously described method (Lee et al., 2007). Consistent with

our ChIP results, we found that most of the HTA1-HTB1 intergenic region was nucleosome-

free when either HIR1 or RTT106 was deleted while nucleosome positions at HTA1-HTB1

coding regions remained unchanged (Figure 3-5C). Similarly, we found that along with

HTA1-HTB1, promoter regions of HHT1-HHF1 and HHT2-HHF2 were amongst the most

nucleosome-depleted intergenic regions genome-wide in strains deleted for either HIR1 or

RTT106 (Figure 3-5D, red). These results suggest that cell-cycle repression of HTA1-HTB1,

HHT1-HHF1 and HHT2-HHF2 is dependent on a nucleosome assembly pathway that relies

on the coordinated actions of Asf1, the HIR complex, and Rtt106. A number of other

promoters in the genome are also nucleosome-free in the HIR1 and RTT106 deletion strains,

including several common to both (Figure 3-5D, cyan), suggesting HIR and Rtt106 may

function together at other loci.

Since the HTA1-HTB1 promoter region is nucleosome-free in the rtt106Δ and hir1Δ

mutants, we wondered whether this promoters intrinsic DNA sequence preference favours

nucleosome depletion. This would indicate that the action of HIR and Rtt106 are required

for proper nucleosome occupancy at this promoter. To investigate this, we assessed the

DNA-encoded nucleosome occupancy at the HTA1-HTB1 promoter using two separate in

vitro nucleosome occupancy experiments generated by Kaplan et al. (2009) and Zhang et al.

(2009). In these experiments, histone octamers were incubated with yeast genomic DNA and

the nucleosome occupancy, determined solely by DNA sequence, was determined as

described in Section 1.4 (Kaplan et al., 2009; Zhang et al., 2009). In Figure 3-5C, the in

 

 

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vitro occupancy data is shown at the HTA1-HTB1 promoter and reveals that in the central

region (which encompasses the NEG site) of the promoter, there appears to be higher

intrinsic nucleosome occupancy relative to the TSS. This indicates that in wild type cells,

nucleosome occupancy is determined by the action of HIR, Rtt106 and to some degree the

DNA sequence in the region of the NEG site. When HIR1 or RTT106 are deleted, another

factor may be disassembling nucleosomes at the promoter that form because of preference

for the DNA sequence itself, which means there may be constant assembly/disassembly

occurring at the HTA1-HTB1 intergenic region. It should be noted that discrepancies exist in

the in vitro nucleosome occupancy data at the HTA1-HTB1 locus in these two data sets

(particularly at the HTB1 TSS), possibly due to differences in experimental and analysis

methods (Kaplan et al., 2009; Zhang et al., 2009).

3.3.5 HIR/RTT106 repression at HTA1-HTB1 creates a requirement for RTT109

Our analysis of HIR and RTT106 requirements for histone gene expression and

promoter binding suggest that activation of HTA1 may reflect relief of repression, rather than

the function of specific activators, as seen at other cell cycle-regulated promoters (reviewed

in Wittenberg and Reed, 2005). To test this idea further, we first used a synchronized cell

culture and our ChIP assay to assess Rtt106 localization at the promoter of HTA1-HTB1

throughout the cell cycle. We found that the proportion of HTA1-HTB1 promoter that bound

Rtt106 did not change significantly during the cell cycle (Figure 3-6A). In addition,

consistent with our previous results, Rtt106 did not cross-link to the ORF region of HTA1 at

any time in the cell cycle (Figure 3-6A). qPCR analysis of HTA1 expression confirmed that

the cells progressed synchronously through the cell cycle in our experiment (Figure 3-6A).

 

 

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Thus, temporal changes in Rtt106 localization to the promoter cannot account for repression

of cell cycle transcription of the histone genes. Rather, we reasoned that an activating factor

may serve to relieve Rtt106-mediated repression during S-phase. As noted earlier, our

functional genomic screen uncovered RTT109 as an activator of HTA1 expression (Figure 3-

1B and 3-2A). The Rtt109 histone acetyltransferase has specificity for K56 on Histone H3

(H3 K56ac) (Collins et al., 2007; Driscoll et al., 2007; Han et al., 2007a) and acetylation of

H3K56 is required for the cell-cycle dependent transcription of the histone genes (Xu et al.,

2005). I therefore examined HTA1 expression in a series of double mutants by qPCR. As

expected, HTA1 expression was de-repressed in hir1 and rtt106 single mutants (Figure 3-

6B). HTA1 expression was not considerably different in a hir1 rtt106 double mutant than

the respective single mutants (Figure 3-6B), consistent with them functioning together in the

same pathway. As I showed previously, rtt109∆ caused a reduction in HTA1 transcript levels

(Figures 3-2A and 3-6B). However when either hir1 or rtt106 was combined with

rtt109, the inhibitory effect of rtt109 on HTA1 expression was significantly reduced

(Figure 3-6B). These genetic results suggest that Rtt109 functions to activate histone gene

expression by antagonizing the repressive effect of Rtt106 and the HIR complex.

 

 

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Figure 3-6: Constitutive repression at HTA1-HTB1 creates a requirement for RTT109. (A) A Rtt106-TAP strain was blocked with -factor, released and samples taken for ChIP and qPCR at the indicated times. The top band of the ChIP analysis represents PCR product ‘C’ from HTA1-HTB1 while the common lower one (marked by an asterisk) is an internal background control from a nontranscribed region on chromosome V. The top left panel represents PCR products from Rtt106-TAP ChIP DNA at region “C” of the HTA1-HTB1 locus while the top right panel represents PCR products from Rtt106-TAP ChIP DNA at region “E” of the HTA1-HTB1 locus. qPCR shows normal kinetics of HTA1 expression throughout the cell cycle. (B) The cDNA was prepared from the indicated strains. The ratio of the indicated transcript to that of ACT1 was determined using qPCR. Error bars represent standard deviations from the mean from at least 3 replicate qPCR reactions.

 

 

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3.3.6 Yta7 is a boundary element within the HTA1-HTB1 locus

Because Rtt106 and members of the HIR complex have recently been identified as

transcriptional elongation factors (Imbeault et al., 2008; Nourani et al., 2006), we compared

their localization pattern at HTA1-HTB1 to that of several other elongation factors implicated

in chromatin assembly. We used ChIP to assess the localization of the functionally related

proteins Spt4-TAP, Spt5-TAP and Spt6-TAP, as well as the two subunits of FACT, Pob3-

TAP and Spt16-TAP, at the HTA1 portion of the HTA1-HTB1 region. All five factors cross-

linked at HTA1 in a pattern distinct from HIR/Rtt106. While HIR/Rtt106 cross-linked

primarily to the promoter region of HTA1 (Figure 3-3B and data not shown), Spt4, Spt5,

Spt6, Spt16 and Pob3 associated mainly with the coding regions of HTA1 (Figure 3-7) and

HTB1 (data not shown). Thus, consistent with our other experiments, HIR-Rtt106 likely has

a role at the HTA1 locus distinct from the elongation factors that we tested.

 

 

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Figure 3-7: Spt4, Spt5, Spt6 and FACT cross-link to the transcribed regions of HTA1 but not to the promoter region. The top band of the ChIP analysis represents the indicated PCR product from HTA1-HTB1 while the common lower band (marked by an asterisk) is an internal background control from a nontranscribed region on chromosome V.

 

 

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We next assayed the relationship between YTA7 and the various chromatin assembly

factors and chaperones that are present at histone core promoters. As noted earlier, YTA7

encodes a bromodomain-containing protein and was identified as an HTA1 activator in our

R-SGA screen (Figure 3-1B). Yta7 is known to function as a boundary element within

chromatin at HMR, a locus that is typically transcriptionally silent (Tackett et al., 2005). To

ask if Yta7 might perform a similar function at a transcribed locus, we assayed cross-linking

of Yta7 at HTA1-HTB1. We observed strong enrichment of Yta7 at regions occupied by

HIR/Rtt106 (region “C”), Spt4/5/6 and FACT (region “E”) and also to the region between

them (region “D”) (Figure 3-8A). Similar to the Hir1 and Rtt106 proteins, we found Yta7

cross-linked to the promoter region of HHT1-HHF1 and HHT2-HHF2 but not HTA2-HTB2

(Figure 3-8B). Localization of Yta7 was dependent on HIR1 but not RTT109 (Figure 3-8A)

at all three histone promoter regions (Figure 3-8B). Because Yta7 localized efficiently to

the region bounded by HIR/Rtt106 and Spt4, Spt5, Spt6, and FACT, we asked whether HIR

or Rtt106 localization to HTA1-HTB1 was affected by deletion of YTA7. We did not observe

a difference in the cross-linking pattern of Hir1-TAP at HTA1-HTB1 in a yta7∆ strain

(Figure 3-8C).

 

 

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Figure 3-8: Yta7 localizes to the HTA1-HTB1 locus. (A) Hir1 is required for Yta7 localization to HTA1-HTB1. The top band of the ChIP analysis represents the indicated PCR product from HTA1-HTB1 while the common lower band (marked by an asterisk) is an internal background control from a nontranscribed region on chromosome V. A western blot shows that YTA7 expression is not dependent on expression of Hir1. (B) Yta7 localization to other histone promoters is dependent on HIR1. A similar analysis was performed as in Figure 3-8A with primers directed against the promoters of the indicated histone genes. (C) Yta7 is not required for proper Hir1 localization at HTA1-HTB1. ChIP analysis was performed as in Figure 3-8A.

 

 

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Instead, we found that Rtt106 cross-linked throughout the entire HTA1-HTB1 region in the

absence of YTA7, including the transcribed regions where it is normally not present (Figure

3-9A). Thus Yta7 influences Rtt106 but not Hir1 localization at HTA1-HTB1. We propose

that the inhibitory affect that deletion of YTA7 causes on HTA1 transcript levels (Figure 3-

9B) is the result of Rtt106 mislocalization at the HTA1 coding region, likely by creating

repressed chromatin or inhibiting transcription initiation by RNA polymerase II. When the

YTA7 deletion is combined with deletion of RTT106, the inhibitory effect on HTA1

transcription is partially relieved (Figure 3-9B), suggesting Rtt106 mislocalization in the

absence of Yta7 causes a defect in HTA1 expression. We also saw increased Rtt106 cross-

linking to the HHT1-HHF1 and HHT2-HHF2 promoters in the absence of YTA7, indicating

the same relationships among Hir1, Rtt106 and Yta7 at three of the four histone gene pairs

(Figure 3-9C). We conclude that Yta7 may contribute to the proper activation of histone

gene expression by preventing Rtt106 from spreading from the HTA1-HTB1 regulatory

region into the transcribed regions (Figure 3-10).

 

 

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Figure 3-9: Yta7 creates a boundary within the HTA1-HTB1 locus. (A) Yta7 is required for proper Rtt106 localization at HTA1-HTB1. The top band of the ChIP analysis represents the indicated PCR product from HTA1-HTB1 while the common lower band (marked by an asterisk) is an internal background control from a nontranscribed region on chromosome V. (B) qPCR analysis of HTA1 transcript levels reveals that the inhibitory affect caused by deletion of YTA7 can be partially relieved in the yta7Δ rtt106Δ strain. (C) Deletion of YTA7 affects localization of Rtt106-TAP to other histone promoters. Rtt106-Tap localizes to other histone promoters with the exception of HTA2 and in the absence of YTA7, more Rtt106-TAP cross links to these promoters indicating that Yta7 functions as a boundary element at HIR/Asf1/Rtt106 regulated histone promoters. ChIP analysis was performed as described in Figure 3-9A with primers directed against the promoters of the indicated histone genes.

 

 

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3.4 Discussion

Cell cycle-dependent regulation of histone gene expression is a universal feature of

eukaryotic cell cycles, yet the mechanisms of activation and repression of histone genes have

remained obscure. I developed a reporter-based functional genomic screen using SGA

technology in S. cerevisiae and identified several regulators of HTA1 expression,

demonstrating that the H3-H4 histone chaperone Rtt106 functions along with known HTA1

regulators, Asf1 and the HIR complex, to repress HTA1 transcription. We found that the

HTA1-HTB1 promoter region is mostly nucleosome-free in the absence of ASF1, HIR1 or

RTT106. Whether or not Asf1/HIR/Rtt106-mediated nucleosome formation is associated

with a specific histone post-translational modification pattern remains unknown. We also

discovered that Yta7 bound the HTA1-HTB1 promoter region and that loss of Yta7 results in

a defect in activation of HTA1 transcription. Yta7 appears to mediate histone gene activation

by restraining repressive chromatin formed by Asf1/HIR/Rtt106 at the HTA1-HTB1

promoter.

Our genetic and biochemical experiments suggest that a primary role of the HIR

complex and Asf1 in histone gene regulation is to recruit the histone H3/H4 chaperone

Rtt106 to promoter regions. We found that Rtt106 is present at the HTA1-HTB1 regulatory

region throughout the cell cycle (Figure 3-6A), suggesting that repression is the default state

at HTA1-HTB1. I propose that, unlike other well characterized cell cycle-sensitive

promoters, activation of histone gene expression does not require the action of specific

activating transcription factors, although they may play some role. Rather, the key to

activating histone gene expression resides with overcoming the repressive chromatin

structure established by Rtt106 and its partners. My functional genomic screen and follow-

 

 

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up experiments suggest that Rtt109 may relieve repression by Asf1/HIR/Rtt106 at HTA1-

HTB1 (Figure 3-10).

 

 

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Figure 3-10: A model describing histone chaperone mediated repression at the HTA1 locus in yeast. See text for details.

 

 

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The defect in HTA1 activation caused by mutation of RTT109 is partially overcome by

deletion of hir1∆ or rtt106∆. The remaining repressive effect of the RTT109 deletion when

combined with hir1 or rtt106 could be a consequence of its requirement to remove any

remaining nucleosomes in those double mutants. Thus, the activity of Rtt109 may not be

required when the HTA1-HTB1 promoter region is nucleosome-free. This phenomenon

mirrors that of the HIR-dependent recruitment of the yeast SWI/SNF complex that also

activates transcription at HTA1-HTB1 (Dimova et al., 1999) since mutation of components of

the HIR complex abolishes the requirement for SWI/SNF in transcriptional activation.

Rtt109 acetylates H3 K56, a modification that is enriched at the yeast histone gene

promoters (Xu et al., 2005) in a cell cycle-dependent manner. The acetylation of H3 K56 is

required for the recruitment of the SWI/SNF complex member Snf5 (Xu et al., 2005). Thus

SWI/SNF could act directly downstream of Rtt109 in a cell cycle-dependent manner to

overcome HIR/Rtt106-mediated repression and activate transcription of HTA1. Rtt109 and

H3 K56Ac have been implicated in the process of nucleosome disassembly leading to

transcriptional activation at the PHO5 locus (Williams et al., 2008). Based on these

observations, a plausible model for Rtt109 action at the HTA1-HTB1 promoter involves the

coordinated action of Rtt109 and SWI/SNF to disassemble nucleosomes leading to

transcriptional activation (Figure 3-10). SWI/SNF functions in nucleosome eviction

pathways [for example, at SUC2 where it binds to the UAS and mediates nucleosome

eviction (Schwabish and Struhl, 2007)].

It is likely that Rtt109 is not itself recruited to the histone promoters since it only

acetylates non-nucleosomal histones (Han et al., 2007b) and we were unable to detect

Rtt109-TAP at the HTA1-HTB1 locus using ChIP (data not shown). One possibility is that

 

 

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during S-phase, Rtt109 acetylates H3 K56 on free histone H3 which is then incorporated into

the HTA1-HTB1 intergenic region because of the presence of Asf1/HIR/Rtt106 since Rtt106

has been shown to have a higher affinity for K56 acetylated histone H3 (Li et al., 2008).

HIR is directed to the histone promoter because of the presence of the NEG cis-regulatory

site which is required for HIR localization (Osley, 1991). Deletion of the NEG sequence or

HIR results in constitutive histone transcription (Osley, 1991; Osley et al., 1986; Osley and

Lycan, 1987) consistent with our results showing that deletion of Rtt106 also causes de-

repression of HTA1 transcription and that localization of Rtt106 to the NEG region is

dependent on HIR. Outside of S-phase, removal of H3 K56Ac by the Hst3/4 deacetylase

(Celic et al., 2006; Maas et al., 2006) would result in incorporation of unacetylated H3 K56

histones by the Asf1/HIR/Rtt106 complex [which is likely constitutively present at the

promoter (Figure 3-6A)] leading to repression of histone gene expression. The presence of

Yta7 at the promoter may be dependent on other histone marks in the histone N-terminal

domain since previous work has shown that Yta7 does not associate with K56Ac histone H3

(Gradolatto et al., 2008). However, it is likely that Yta7 localization specifically at the

HTA1-HTB1 region is dependent on the presence of NEG, since this site is required for HIR

recruitment (Osley, 1991) which is in turn required for Yta7 localization (Figure 3-8A and

B). An important caveat to these models is the unclear relationship of Rtt109 to Spt10, a

protein initially suggested to be the H3 K56-specific HAT at the histone genes in S.

cerevisiae (Xu et al., 2005). My results indicate that both Rtt109 and Spt10 function to

activate HTA1 (Figure 3-2). Clearly more work will be required to discover whether Spt10

directly acetylates H3 K56, or if it stabilizes H3 K56Ac-containing nucleosomes, as well as

what (if any) relationship exists between Spt10 and Rtt109 at HTA1-HTB1. Additionally, we

 

 

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also detected another histone chaperone, Vps75, as a potential activator of HTA1

transcription (Figure 3-1B). Vps75 physically interacts with Rtt109 which acetylates H3 K9

(Fillingham et al., 2008). However, we have not observed a significant change in HTA1

transcription in a point mutant where H3 K9 cannot be acetylated (H3 K9R mutant), nor have

we seen Vps75 localization at the HTA1-HTB1 locus, indicating that H3 K9 acetylation is

likely not required for HTA1 activation (data not shown). Vps75 is required for stability of

Rtt109 (Fillingham et al., 2008) meaning that Vps75 may result in lower Rtt109 levels and

thus a slight reduction in HTA1 transcription, consistent with our screening results.

We also identified the DNA helicase RRM3 as a potential activator of HTA1

transcription (Figure 3-1B). Interestingly, a screen for proteins required to localize

telomeres to the nuclear periphery revealed a role for Rtt109, Asf1, Vps75, H3 K56Ac and

Rrm3 (Hiraga et al., 2008), indicating these proteins along with K56Ac might function

together in a common pathway that might also be applicable to transcription of the HTA1

gene. Clearly future work will be required to determine what role, if any, RRM3 plays in

histone gene transcription. In follow-up work, ChIP analysis will be carried out to determine

if RRM3 localizes to the HTA1-HTB1 locus.

Rtt106 interacts physically with CAF-1 (Huang et al., 2005) to function in

replication-coupled chromatin assembly (Li et al., 2008). In contrast, both the yeast

Asf1/HIR complex and higher organism versions of HIR function in the replication-

independent assembly of chromatin (Green et al., 2005 and reviewed in De Koning et al.,

2007). We found that the CAF-1 subunit Cac2 is not necessary for Rtt106 localization to

HTA1-HTB1 (Figure 3-4), suggesting that Asf1/HIR/Rtt106-mediated nucleosome assembly

at HTA1-HTB1 likely occurs in a replication-independent manner. Although our results

 

 

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suggest that the major function of the three histone chaperones at the HTA1-HTB1 promoter

is the assembly of nucleosomes, the precise nature of Asf1/HIR/Rtt106-mediated repression

remains to be determined.

A striking feature of the spectrum of regulatory proteins at the HTA1-HTB1 locus is

the physical separation of HIR/Rtt106 from Spt4, Spt5, Spt6 and FACT (Figures 3-3B and

3-7). Rtt106 was recently found to cross-link to the coding region of PMA1 (Imbeault et al.,

2008), as do Spt4, Spt5, Spt6 and FACT (Kim et al., 2004). Spt6 and Rtt106 are also known

to function in parallel to suppress cryptic initiation at an internal promoter within the FLO8

gene (Imbeault et al., 2008). Since Rtt106 has a defined role in transcriptional elongation, a

mechanism may exist to restrict Rtt106 to the promoter region of HTA1-HTB1. Yta7 was

originally identified as a protein whose absence led to the spreading of the silent state of

chromatin at HMR to surrounding genes, consistent with its proposed function as a barrier

between regions of heterochromatin and euchromatin at HMR (Tackett et al., 2005). We

found that Rtt106, but not Hir1, cross-links throughout HTA1-HTB1 in the absence of YTA7,

including the transcribed regions (Figure 3-8C and Figure 3-9A). Thus, the loss of a barrier

protein (Yta7) at HTA1-HTB1 appears to cause the lateral spread of Rtt106 from the

promoter through the ORFs. Since Rtt106 is a histone chaperone specifically associated with

the formation of repressive chromatin, its lateral spreading across the coding region of HTA1

could repress transcription by propagating a repressive chromatin structure. The regulation

of Rtt106 localization could represent a more general mechanism underlying

heterochromatin spreading. For example Yta7 may influence Rtt106 at heterochromatin

boundaries at HMR, a region where both proteins have been functionally implicated (Huang

et al., 2007; Jambunathan et al., 2005; Tackett et al., 2005). More generally, Yta7 could

 

 

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function together with Asf1/HIR/Rtt106 to create short domains of repressed chromatin

throughout the genome. Our nucleosome occupancy data hints that the promoter regions of

other genes are indeed subject to HIR/Rtt106 regulation and Yta7 may also be involved in

their regulation. Global approaches such as ChIP-chip combined with nucleosome

occupancy studies will address this question and are currently in progress.

In this chapter, I present a detailed analysis of histone gene regulation based on the

use of a dual-reporter screen to discover new regulators. I have elucidated mechanisms of

histone gene control for both well-studied regulators like HIR and previously unknown

proteins like the histone chaperone Rtt106 and the Yta7 boundary element. I also note that

the functional genomics approach presented here can be applied to study virtually any

pathway for which an appropriate fluorescent reporter gene can be devised, providing a

powerful means to link gene function to transcriptional control.

 

 

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Chapter 4

Summary and Future Directions

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

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4.1 Summary

Reporter gene screens are used as a fundamental tool to identify regulatory proteins

that control gene expression from promoters of interest. In the past, forward genetic screens

were carried out to randomly mutagenize cells harbouring reporter constructs with the aim of

mapping mutant genes causing differential reporter expression. This general approach has

identified many transcriptional regulators but has several limitations. Screens involving

random mutagenesis can be quite time consuming, since they require generating a large

library of mutants to attempt an effective survey of the genome, and follow-up mapping of

mutations causing differential reporter expression requires considerable work. Also, these

screens are generally not quantitative and are rarely saturating.

Systematic, genome-wide analysis of mutants for an effect on reporter gene

expression in a quantitative, rapid and unbiased manner was not possible, and my thesis work

aimed to address this. I describe the development and application of a screening system that

combines fluorescent proteins with functional genomic tools and resources already available

in budding yeast. Specifically, I developed a two-colour reporter system where a wild type

yeast strain that harbours a promoter of interest fused to GFP along with a control promoter

fused to RFP can be introduced into an ordered array of yeast deletion mutants using the

SGA methodology. GFP and RFP fluorescence are easily assayed by directly scanning the

intensities from the colonies arrayed on solid agar plates and all of these intensities can be

quantified using appropriate software. Deletion mutants that cause decreased GFP:RFP

ratios are indicative of genes that are required for activation of the promoter of interest while

deletion mutants causing increased GFP:RFP ratios reveal genes that repress the promoter of

interest.

 

 

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In Chapter 2, I described the complete methodology for carrying out this type of

screen including particular details we discovered to generate high quality data. I describe the

SGA-selection media required and timeline for generating the output array as well as general

guidelines to consider when screening. I show step-by-step how we carry out the screen

using a CLN2 promoter-GFP reporter gene as an example, revealing that this screen can

distinguish the known transcriptional activator, Swi4, as the principal activator of CLN2

expression. Further, I show that normalization of GFP to the control RFP signal is

imperative to reliably detect Swi4 as the top activator of CLN2 expression compared to

considering the GFP signal alone. This information shows the utility of the approach and

will guide other researchers in adapting this type of screening to applications of their choice.

In Chapter 3, I describe the application of the above screening approach to probe the

yeast genome for new regulators of histone gene transcription, an important group of genes

whose expression is tightly regulated during S-phase of the cell cycle (Hereford et al., 1981).

In S. cerevisiae, each of the four histones are encoded by two different genes and histone

pairs are divergently transcribed from the same intergenic region so that the HTA1-HTB1 and

HTA2-HTB2 gene pairs encode histone H2A and H2B expression while HHT1-HHF1 and

HHT2-HHF2 encode H3 and H4 expression respectively. The promoter regions of three of

the four gene pairs (excluding HTA2-HTB2) contain a cis-acting negative regulatory DNA

sequence called NEG which is required for cell cycle regulation of histone transcripts and

repression through this site is mediated by the Asf1/HIR protein complex (Green et al., 2005;

Osley et al., 1986; Osley and Lycan, 1987; Prochasson et al., 2005; Xu et al., 1992). To

probe for new repressors and better characterize Asf1/HIR mediated repression of these

genes, as well as identify potential activators, I carried out a R-SGA screen with the HTA1

 

 

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promoter fused to GFP. I discovered that the histone H3-H4 chaperone protein Rtt106 is a

novel repressor of HTA1 transcription while other proteins like Rtt109 and Yta7 play an

activating role.

To characterize the roles these proteins play, I worked with my collaborators to

perform a series of experiments including chromatin immunoprecipitation, transcript

profiling, genome-wide nucleosome positioning and co-purification. These experiments

revealed that Rtt106 is a novel member of the Asf1/HIR pathway that regulates histone

transcription through the NEG site. Like HIR and Asf1, Rtt106 is required for proper cell

cycle regulation of histone transcripts. Our genome-wide nucleosome positioning analysis

revealed that the absence of Rtt106 or Hir1 renders histone promoters containing the NEG

sequence nucleosome free, indicating that cell cycle regulation of histone transcription is

controlled by proper nucleosome occupancy at the promoter. Because Rtt106 is

constitutively localized at the promoter throughout the cell cycle, we propose an activating

factor is required to overcome Asf1/HIR/Rtt106 mediated repression of histone genes. One

gene that is required for activation of histone genes encodes the histone H3 K56 specific

HAT, Rtt109, which seems to play some role in countering Rtt106 and Hir1 mediated

repression. We also show that the bromodomain containing protein Yta7 acts as a boundary

element at histone gene promoters by restricting the localization of Rtt106 specifically to the

NEG-containing region of the promoter and excluding it from the coding regions. These

findings illustrate the power of an unbiased, functional genomics approach for identifying

new transcriptional regulators. We identified and characterized novel members of the

Asf1/HIR pathway and our genome-wide nucleosome positioning experiments suggest that

 

 

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the Rtt106/Asf1/HIR/Yta7 pathway we characterized is acting at promoters broadly in the

genome.

4.2 Future directions

4.2.1 Characterizing the Rtt106/Asf1/HIR/Yta7 pathway genome-wide

Our efforts so far have uncovered a novel pathway where the Rtt106/Asf1/HIR

proteins repress transcription at histone promoters and Rtt106 localization is restricted to the

promoter regions and excluded from the coding regions by the presence of Yta7. Because

we carried out nucleosome positioning experiments genome-wide in the absence of Rtt106

and Hir1, we were able to identify hundreds of promoters that appear to be nucleosome-free

when these genes are deleted, suggesting that the Rtt106/Asf1/HIR/Yta7 pathway defines a

previously unappreciated transcriptional regulatory mechanism that is broadly applied across

the genome. To test this idea, I propose ChIP-seq experiments to determine the localization

patterns of these proteins on DNA. Until recently, this type of experiment has been carried

out by hybridizing ChIP-enriched DNA to a microarray to identify regions occupied by a

protein of interest. However, the advent of next generation sequencing technologies has

made ChIP-seq experiments feasible. Sequencing allows greater resolution for mapping

protein-DNA interactions and for small genomes like yeast, multiplexing experiments in

single sequencing runs allows cost-effective generation of large data sets (Lefrancois et al.,

2009).

We have shown efficient cross-linking of TAP-tagged versions of Rtt106, Hir1 and

Yta7 to the regulatory regions of histone genes and these strains can be used for the ChIP-seq

experiments. If Rtt106, HIR and Yta7 are collaborating to create regions of repressed

 

 

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chromatin in promoters of genes, which is suggested from our previous nucleosome

positioning data, I expect to find these proteins localizing to the same promoters across the

genome. Our previous work also revealed that Yta7 is a boundary protein at the cell cycle-

regulated histone genes. When YTA7 is deleted, Rtt106 spreads laterally from the NEG-site

in the promoter and into the ORF. Thus, to determine whether Yta7 is acting as a boundary

element at other active promoters, ChIP-seq on the Rtt106-TAP yta7Δ strain could be

performed. I expect that many promoters will be occupied by Rtt106 and Hir1 and that these

promoters will also be targeted by Yta7. In the absence of Yta7, I expect to see spreading of

Rtt106, similar to what we observed at the HTA1 locus.

Interestingly, localization of Rtt106 and Yta7 to the NEG site of histone promoters is

dependent on HIR and this NEG sequence is only present in histone gene promoters. It is

possible that at other promoters, Rtt106 is recruited by other factors independently of HIR in

which case ChIP-seq experiments would reveal HIR-dependent and HIR-independent

pathways of Rtt106 transcriptional regulation at promoters. This might particularly be true

for promoters that are independent of cell cycle regulation, since the NEG site is required to

confer proper S-phase specific expression of histone genes (Osley, 1991; Osley et al., 1986).

To determine experimentally if this is the case, I will carry out ChIP-seq experiments on the

Rtt106-TAP hir1Δ strain. The results of this experiment will reveal whether Rtt106 can

localize to promoters in the genome in the absence of HIR1. Because a single sequencing

run generates many more sequence reads than is required, four different ChIP-enriched DNA

samples can be multiplexed and sequenced in a single reaction using an Illumina Genome

Analyzer II sequencing platform (Lefrancois et al., 2009). To further characterize HIR-

independent Rtt106-regulated promoters, I propose to fuse those promoters that I discover in

 

 

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my ChIP-seq experiments to GFP and carry out an R-SGA screen to identify other regulators

of those promoters that might be responsible for recruiting Rtt106.

Since our results show a role for Rtt106 in regulating transcription, gene expression

microarray experiments will be carried out in rtt106Δ, hir1Δ and yta7Δ mutants to correlate

promoter localization of these proteins with transcriptional output. These data will also be

compared to our nucleosome positioning data already generated. Thus, I plan to characterize

the Rtt106-Hir-Yta7 pathway by overlapping data from ChIP-seq, gene expression

microarrays and nucleosome occupancy experiments.

4.2.2 Characterizing protein domains in Rtt106 required for function with HIR

Our analysis of Rtt106 revealed a role for this protein in repressing transcription of

the cell cycle-histone genes. As noted in Chapter 3, Rtt106 has higher affinity for K56Ac

histone H3 (Li et al., 2008), a chromatin mark that is abundant in S-phase of the cell cycle by

action of the HAT Rtt109 (Collins et al., 2007; Driscoll et al., 2007; Han et al., 2007a;

Ozdemir et al., 2005; Xu et al., 2005). A PH-like domain was discovered in Rtt106 from

residues 195 to 301 that mediates binding to H3 K56Ac (Li et al., 2008). Because K56Ac is

known to be important for activation of histone gene transcription (Xu et al., 2005), it is of

interest to understand if the PH-like domain in Rtt106 plays a role in regulation of histone

genes. It is possible that Rtt109 acetylates H3 K56 and this mark is incorporated into the

histone promoter region by Rtt106 to allow activation of transcription transiently during S-

phase which is rapidly repressed by incorporation of non-acetylated H3 K56 histones during

other phases of the cell cycle by Rtt106.

 

 

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To test this hypothesis, I propose to carry out experiments with a strain where the PH-

like domain of Rtt106 is deleted (RTT106Δ196-301) (Li et al., 2008). First, I will test

endogenous HTA1 transcript levels in the RTT106Δ196-301 strain using qPCR (see Chapter

3) to determine if there remains derepression of HTA1 transcripts similar to the rtt106Δ

strain. If the above hypothesis is correct, transcript levels may be reduced in the rtt106Δ196-

301 strain (possibly similar to the rtt109Δ strain) compared to the rtt106Δ strain because of a

failure to incorporate K56Ac histone H3 into the promoter. Next, I will test H3 K56Ac

levels specifically at the HTA1 promoter using ChIP with an antibody that recognizes H3

K56Ac in both the rtt106Δ and rtt106Δ196-301 strains and compare these levels to histone

H3 levels using an antibody specific for histone H3. In both strains, K56Ac maybe be

reduced because of the absence of the PH domain of Rtt106 at the promoter but H3 levels

may not be completely reduced in the rtt106Δ196-301 relative to rtt106Δ, which causes the

promoter to become nucleosome free. In the rtt106Δ196-301 strain, there may be other

protein domains that still allow proper nucleosome assembly of unacetylated H3 K56

histones to still allow repression outside of S-phase so that the promoter does not become

nucleosome-free and constitutively active like in the rtt106Δ strain. An important control is

to test whether a TAP-tagged version of the Rtt106-PH domain mutant protein still localizes

to the NEG-containing region of the histone promoter using the ChIP assay described in

Chapter 3. Furthermore, it will be important to test whether its localization is still dependent

on HIR, as for Rtt106-TAP.

 

 

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4.2.3 Screening overexpression arrays

The screening approach I described here makes use of a collection of yeast deletion

mutants. However, because ~1000 genes are essential (Giaever et al., 2002), the effect that

mutation of these genes causes on reporter genes cannot be scored in the present screening

format. One way to identify regulatory pathways controlled by essential genes is to examine

the consequence of gene overexpression on a reporter gene of interest. In this case, an array

of yeast strains where each yeast colony represents overexpression of a yeast protein is useful

(Sopko et al., 2006). Each colony on this array harbours a high-copy plasmid where the

GAL1/10 promoter, which is induced in the presence of galactose, drives expression of a

different ORF (Sopko et al., 2006). This array can be manipulated using the SGA

methodology to combine GFP and RFP reporter genes with overexpression of each ORF

when grown in the presence of galactose. Opposite effects to gene-deletions are likely to

result such that increased GFP:RFP would indicate the overexpressed gene is an activator of

the promoter while decreased GFP:RFP would indicate the overexpressed gene is a repressor

of the promoter (Figure 4-1).

 

 

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Figure 4-1: Overexpression screen to identify regulators of a promoter of interest. The SGA methodology is used to combine a promoter-GFP and a control promoter-RFP gene into an ordered array of galactose inducible overexpression strains. The output array is replicated on media containing galactose to induce overexpression of each ORF and colonies arrayed on agar plates are assayed using the typhoon fluorescence scanner. Since overexpression of most ORFs will not affect gene expression, the combination of GFP and RFP in those strains will result in a yellow colour. Increased GFP compared to RFP will indicate the overexpressed gene is an activator of the promoter of interest while decreased GFP compared to RFP will indicate the overexpressed gene is a repressor of the promoter of interest.

 

 

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Previous work has shown that deletion of many transcription factors results in little

effect on target genes examined by gene expression microarrays, likely because the

transcription factor is inactive under the conditions tested (Chua et al., 2006). However,

overexpression in many cases resulted in a gene expression pattern above noise indicating

that artificially activating expression of these proteins bypasses the need for specific

activating conditions and can be used to identify target genes of transcription factors (Chua et

al., 2006). Similarly, by overexpressing genes it would be possible to identify activating

pathways of a promoter that may not normally be active in the conditions tested. Thus,

overexpression screens are advantageous because they allow analysis of essential genes,

regulatory proteins that are only expressed under specific conditions can be assayed for an

activating role on promoters of interest and they can provide complementary data to deletion

screens.

4.2.4 Increasing throughput of reporter-gene analysis using pooled screens in yeast and

higher eukaryotes

I developed a novel approach to study gene regulation by combining fluorescent

reporter genes, the SGA approach and a simple assay for detecting fluorescence from yeast

colonies arrayed on agar plates. Although this approach has proven useful for studying gene

regulatory pathways, the plate-based colony assay is generally not adaptable to higher

eukaryotes. I propose to develop and validate a methodology to identify trans-acting factors

of promoter-reporter constructs using pooled cultures that could be adapted to any organism

for which an appropriate gene disruption library exists. Because of the potential for

 

 

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exploring the possibility of new methodologies in S. cerevisiae, I propose to first test this

approach in yeast.

As I described in Chapter 1, the yeast deletion library contains each yeast ORF

knocked out with a kanamycin resistance cassette. In addition, each knockout cassette is

flanked by unique sequences that are used as strain identifiers or molecular barcodes and all

mutants contain a universal sequence that allows a single primer set to amplify each unique

barcode (Giaever et al., 2002 and Figure 1-6). If the entire collection is pooled into a single

culture and treated with a particular condition (for example drug treatment), deletion strains

that are sensitive to treatment are under-represented in the population. DNA is prepared

from the pooled culture, PCR-amplified with the universal primer set and hybridized to a

microarray that contains oligonucleotide probes homologous to each molecular barcode.

Positions on the microarray that no longer show signal after hybridization are indicative of

mutants sensitive to the particular treatment. This type of strategy has been used to

quantitatively monitor the deletion collection for strains that show a fitness defect when

grown in rich-media or under various conditions (Giaever et al., 2002).

Since these barcodes allows identification of deletion mutants in a mixed population,

the potential for combining this pooled strategy with fluorescent reporter genes and

fluorescence activated cell sorting (FACS) exists. In this case, a promoter-GFP reporter gene

can be introduced into the collection of deletion mutants using the SGA approach or by

directly transforming the reporter plasmid into a pooled culture of all viable deletion strains.

The population of cells is pooled and grown in appropriate selection media and subject to

FACS so that the brightest cells in the population are sorted into one sub-population and the

dimmest cells are sorted into a different sub-population (Figure 4-2). Flow cytometry has

 

 

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been used to make precise measurements of GFP-tagged proteins from single cells, which

indicates the feasibility of the approach described here for detecting fine cell-to-cell changes

in GFP expression (Newman et al., 2006). The brightest cells expressing high levels of GFP

likely contain deletion mutants that are required to repress the promoter of interest while the

dimmest cells likely contain activators of the promoter. To identify which mutants are in

each population, DNA prepared from each pool is hybridized to a barcode microarray and

compared to hybridization signal from an unsorted population (Figure 4-2). This type of

approach could be used to determine how the promoter-reporter gene responds to different

environmental conditions or drug treatments (particularly when drugs are scarce) in each

mutant background and should aid in discovery of new pathways of gene regulation.

 

 

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Figure 4-2: Reporter screening using barcoded gene disruption libraries and FACS. A pooled culture of cells with a promoter-GFP reporter gene combined with each yeast deletion mutant is subject to FACS to physically sort cells based on the intensity of GFP signal. Mutants present in the brightest and dimmest sub-populations after sorting are identified by hybridization to a barcode microarray and normalized to the hybridization signal from the unsorted population, which defines the mutants present in the initial pooled culture.

 

 

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In human cells and other eukaryotes, barcoded RNAi libraries exist to perturb

expression of each gene (Moffat et al., 2006). Reporter genes of interest could be stably

expressed in cell lines of choice and combined with the RNAi library. Similar to the above

experiment, FACS cell sorting could be used to physically sort bright and dim cells from the

population and RNAi molecular barcodes detected to determine which gene is targeted.

Pooled RNAi barcode screens have been carried out previously on a genome-scale and

identified a number of genes required for cell proliferation in different tumour types

(Schlabach et al., 2008; Silva et al., 2008). These types of screens should prove useful for

studying transcriptional regulatory pathways that are perturbed in cancer cell types.

4.3 Overall significance

The advent of DNA microarrays has revolutionized the gene expression field and has

led to major discoveries on regulator-gene interactions. From parallel transcript profiling,

genome-wide localization of proteins and histone modifications on chromatin, maps of

nucleosome positions and DNA sequences bound by regulatory proteins, array-based

approaches have allowed detailed analysis of mechanisms that control how the genome is

regulated. Now that next generation sequencing applications are becoming commonplace,

gene expression regulatory pathways are being examined with unprecedented resolution.

With the work presented in this Thesis, it is now possible to carry out systematic and

quantitative gene expression reporter screens using array-based reagents in yeast, a

methodology that was previously lacking. Based on this work, I propose a new approach

that is based on sorting cells with fluorescent reporter genes that should be adaptable to

 

 

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higher organisms and aid in the discovery of new transcription factor pathways that have

previously been unappreciated.

It is clear that even though an enormous amount of gene expression data has been

generated, there remain many more regulatory pathways to be discovered, even in well

studied organisms like S. cerevisiae. My work has shown the power of systematic reporter

screens for linking protein function to transcriptional regulation that would otherwise remain

mysterious. However, for complete elucidation and characterization of transcription factor

pathways, no one approach should be considered superior. Instead a combined approach

utilizing various functional genomic techniques and tools should be carried out to fully

realize the goal of defining all pathways that control gene expression.

 

 

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References Adkins, M. W., Howar, S. R., and Tyler, J. K. (2004). Chromatin disassembly mediated by

the histone chaperone Asf1 is essential for transcriptional activation of the yeast

PHO5 and PHO8 genes. Mol Cell 14, 657-666.

Adkins, M. W., Williams, S. K., Linger, J., and Tyler, J. K. (2007). Chromatin disassembly

from the PHO5 promoter is essential for the recruitment of the general transcription

machinery and coactivators. Mol Cell Biol 27, 6372-6382.

Andrews, B. J., and Herskowitz, I. (1989). Identification of a DNA binding factor involved

in cell-cycle control of the yeast HO gene. Cell 57, 21-29.

Andrews, B. J., and Moore, L. A. (1992). Interaction of the yeast Swi4 and Swi6 cell cycle

regulatory proteins in vitro. Proc Natl Acad Sci U S A 89, 11852-11856.

Baba, T., Ara, T., Hasegawa, M., Takai, Y., Okumura, Y., Baba, M., Datsenko, K. A.,

Tomita, M., Wanner, B. L., and Mori, H. (2006). Construction of Escherichia coli K-

12 in-frame, single-gene knockout mutants: the Keio collection. Mol Syst Biol 2,

2006 0008.

Bader, G. D., Heilbut, A., Andrews, B., Tyers, M., Hughes, T., and Boone, C. (2003).

Functional genomics and proteomics: charting a multidimensional map of the yeast

cell. Trends Cell Biol 13, 344-356.

Badis, G., Chan, E. T., van Bakel, H., Pena-Castillo, L., Tillo, D., Tsui, K., Carlson, C. D.,

Gossett, A. J., Hasinoff, M. J., Warren, C. L., et al. (2008). A library of yeast

transcription factor motifs reveals a widespread function for Rsc3 in targeting

nucleosome exclusion at promoters. Mol Cell 32, 878-887.

Bammler, T., Beyer, R. P., Bhattacharya, S., Boorman, G. A., Boyles, A., Bradford, B. U.,

 

 

132

 

Bumgarner, R. E., Bushel, P. R., Chaturvedi, K., Choi, D., et al. (2005).

Standardizing global gene expression analysis between laboratories and across

platforms. Nat Methods 2, 351-356.

Barbaric, S., Munsterkotter, M., Svaren, J., and Horz, W. (1996). The homeodomain protein

Pho2 and the basic-helix-loop-helix protein Pho4 bind DNA cooperatively at the

yeast PHO5 promoter. Nucleic Acids Res 24, 4479-4486.

Berger, M. F., and Bulyk, M. L. (2006). Protein binding microarrays (PBMs) for rapid, high-

throughput characterization of the sequence specificities of DNA binding proteins.

Methods Mol Biol 338, 245-260.

Berger, M. F., Philippakis, A. A., Qureshi, A. M., He, F. S., Estep, P. W., 3rd, and Bulyk, M.

L. (2006). Compact, universal DNA microarrays to comprehensively determine

transcription-factor binding site specificities. Nat Biotechnol 24, 1429-1435.

Bernstein, B. E., Liu, C. L., Humphrey, E. L., Perlstein, E. O., and Schreiber, S. L. (2004).

Global nucleosome occupancy in yeast. Genome Biol 5, R62.

Boeger, H., Griesenbeck, J., Strattan, J. S., and Kornberg, R. D. (2003). Nucleosomes unfold

completely at a transcriptionally active promoter. Mol Cell 11, 1587-1598.

Borneman, A. R., Gianoulis, T. A., Zhang, Z. D., Yu, H., Rozowsky, J., Seringhaus, M. R.,

Wang, L. Y., Gerstein, M., and Snyder, M. (2007). Divergence of transcription factor

binding sites across related yeast species. Science 317, 815-819.

Boutros, M., Kiger, A. A., Armknecht, S., Kerr, K., Hild, M., Koch, B., Haas, S. A., Paro, R.,

and Perrimon, N. (2004). Genome-wide RNAi analysis of growth and viability in

Drosophila cells. Science 303, 832-835.

Breeden, L., and Nasmyth, K. (1987). Cell cycle control of the yeast HO gene: cis- and trans-

 

 

133

 

acting regulators. Cell 48, 389-397.

Brutlag, D., Schlehuber, C., and Bonner, J. (1969). Properties of formaldehyde-treated

nucleohistone. Biochemistry 8, 3214-3218.

Butland, G., Babu, M., Diaz-Mejia, J. J., Bohdana, F., Phanse, S., Gold, B., Yang, W., Li, J.,

Gagarinova, A. G., Pogoutse, O., et al. (2008). eSGA: E. coli synthetic genetic array

analysis. Nat Methods 5, 789-795.

Byrne, A. B., Weirauch, M. T., Wong, V., Koeva, M., Dixon, S. J., Stuart, J. M., and Roy, P.

J. (2007). A global analysis of genetic interactions in Caenorhabditis elegans. J Biol

6, 8.

Celic, I., Masumoto, H., Griffith, W. P., Meluh, P., Cotter, R. J., Boeke, J. D., and Verreault,

A. (2006). The sirtuins hst3 and Hst4p preserve genome integrity by controlling

histone h3 lysine 56 deacetylation. Curr Biol 16, 1280-1289.

Cho, R. J., Campbell, M. J., Winzeler, E. A., Steinmetz, L., Conway, A., Wodicka, L.,

Wolfsberg, T. G., Gabrielian, A. E., Landsman, D., Lockhart, D. J., and Davis, R. W.

(1998). A genome-wide transcriptional analysis of the mitotic cell cycle. Mol Cell 2,

65-73.

Cho, R. J., Huang, M., Campbell, M. J., Dong, H., Steinmetz, L., Sapinoso, L., Hampton, G.,

Elledge, S. J., Davis, R. W., and Lockhart, D. J. (2001). Transcriptional regulation

and function during the human cell cycle. Nat Genet 27, 48-54.

Chua, G., Morris, Q. D., Sopko, R., Robinson, M. D., Ryan, O., Chan, E. T., Frey, B. J.,

Andrews, B. J., Boone, C., and Hughes, T. R. (2006). Identifying transcription factor

functions and targets by phenotypic activation. Proc Natl Acad Sci U S A 103,

12045-12050.

 

 

134

 

Cleveland, W. S. (1979). Robust locally weighted regression and smoothing scatterplots.

Journal of the American Statistical Association 74, 829-836.

Collins, S. R., Miller, K. M., Maas, N. L., Roguev, A., Fillingham, J., Chu, C. S., Schuldiner,

M., Gebbia, M., Recht, J., Shales, M., et al. (2007). Functional dissection of protein

complexes involved in yeast chromosome biology using a genetic interaction map.

Nature 446, 806-810.

Cosma, M. P., Tanaka, T., and Nasmyth, K. (1999). Ordered recruitment of transcription and

chromatin remodeling factors to a cell cycle- and developmentally regulated

promoter. Cell 97, 299-311.

Costanzo, M., Nishikawa, J. L., Tang, X., Millman, J. S., Schub, O., Breitkreuz, K., Dewar,

D., Rupes, I., Andrews, B., and Tyers, M. (2004). CDK activity antagonizes Whi5, an

inhibitor of G1/S transcription in yeast. Cell 117, 899-913.

David, L., Huber, W., Granovskaia, M., Toedling, J., Palm, C. J., Bofkin, L., Jones, T.,

Davis, R. W., and Steinmetz, L. M. (2006). A high-resolution map of transcription in

the yeast genome. Proc Natl Acad Sci U S A 103, 5320-5325.

Davierwala, A. P., Haynes, J., Li, Z., Brost, R. L., Robinson, M. D., Yu, L., Mnaimneh, S.,

Ding, H., Zhu, H., Chen, Y., et al. (2005). The synthetic genetic interaction spectrum

of essential genes. Nat Genet 37, 1147-1152.

De Koning, L., Corpet, A., Haber, J. E., and Almouzni, G. (2007). Histone chaperones: an

escort network regulating histone traffic. Nat Struct Mol Biol 14, 997-1007.

de Reynies, A., Geromin, D., Cayuela, J. M., Petel, F., Dessen, P., Sigaux, F., and

Rickman, D. S. (2006). Comparison of the latest commercial short and long

oligonucleotide microarray technologies. BMC Genomics 7, 51.

 

 

135

 

De Virgilio, C., Burckert, N., Bell, W., Jeno, P., Boller, T., and Wiemken, A. (1993).

Disruption of TPS2, the gene encoding the 100-kDa subunit of the trehalose-6-

phosphate synthase/phosphatase complex in Saccharomyces cerevisiae, causes

accumulation of trehalose-6-phosphate and loss of trehalose-6-phosphate phosphatase

activity. Eur J Biochem 212, 315-323.

Dimova, D., Nackerdien, Z., Furgeson, S., Eguchi, S., and Osley, M. A. (1999). A role for

transcriptional repressors in targeting the yeast Swi/Snf complex. Mol Cell 4, 75-83.

Dixon, S. J., Fedyshyn, Y., Koh, J. L., Prasad, T. S., Chahwan, C., Chua, G., Toufighi, K.,

Baryshnikova, A., Hayles, J., Hoe, K. L., et al. (2008). Significant conservation of

synthetic lethal genetic interaction networks between distantly related eukaryotes.

Proc Natl Acad Sci U S A 105, 16653-16658.

Dollard, C., Ricupero-Hovasse, S. L., Natsoulis, G., Boeke, J. D., and Winston, F. (1994).

SPT10 and SPT21 are required for transcription of particular histone genes in

Saccharomyces cerevisiae. Mol Cell Biol 14, 5223-5228.

Driscoll, R., Hudson, A., and Jackson, S. P. (2007). Yeast Rtt109 promotes genome stability

by acetylating histone H3 on lysine 56. Science 315, 649-652.

Eriksson, P. R., Mendiratta, G., McLaughlin, N. B., Wolfsberg, T. G., Marino- Ramirez,

L., Pompa, T. A., Jainerin, M., Landsman, D., Shen, C. H., and Clark, D. J.

(2005). Global regulation by the yeast Spt10 protein is mediated through chromatin

structure and the histone upstream activating sequence elements. Mol Cell Biol 25,

9127-9137.

Evans, T., Rosenthal, E. T., Youngblom, J., Distel, D., and Hunt, T. (1983). Cyclin: a protein

specified by maternal mRNA in sea urchin eggs that is destroyed at each cleavage

 

 

136

 

division. Cell 33, 389-396.

Fillingham, J., Recht, J., Silva, A. C., Suter, B., Emili, A., Stagljar, I., Krogan, N. J., Allis, C.

D., Keogh, M. C., and Greenblatt, J. F. (2008). Chaperone control of the activity and

specificity of the histone H3 acetyltransferase Rtt109. Mol Cell Biol 28, 4342-4353.

Giaever, G., Chu, A. M., Ni, L., Connelly, C., Riles, L., Veronneau, S., Dow, S., Lucau-

Danila, A., Anderson, K., Andre, B., et al. (2002). Functional profiling of the

Saccharomyces cerevisiae genome. Nature 418, 387-391.

Giresi, P. G., and Lieb, J. D. (2009). Isolation of active regulatory elements from eukaryotic

chromatin using FAIRE (Formaldehyde Assisted Isolation of Regulatory Elements).

Methods.

Goldstein, A. L., and McCusker, J. H. (1999). Three new dominant drug resistance cassettes

for gene disruption in Saccharomyces cerevisiae. Yeast 15, 1541-1553.

Gradolatto, A., Rogers, R. S., Lavender, H., Taverna, S. D., Allis, C. D., Aitchison, J. D., and

Tackett, A. J. (2008). Saccharomyces cerevisiae Yta7 regulates histone gene

expression. Genetics 179, 291-304.

Green, E. M., Antczak, A. J., Bailey, A. O., Franco, A. A., Wu, K. J., Yates, J. R., 3rd, and

Kaufman, P. D. (2005). Replication-independent histone deposition by the HIR

complex and Asf1. Curr Biol 15, 2044-2049.

Guarente, L., Yocum, R. R., and Gifford, P. (1982). A GAL10-CYC1 hybrid yeast promoter

identifies the GAL4 regulatory region as an upstream site. Proc Natl Acad Sci U S A

79, 7410-7414.

Gunjan, A., Paik, J., and Verreault, A. (2005). Regulation of histone synthesis and

nucleosome assembly. Biochimie 87, 625-635.

 

 

137

 

Gunjan, A., and Verreault, A. (2003). A Rad53 kinase-dependent surveillance mechanism

that regulates histone protein levels in S. cerevisiae. Cell 115, 537-549.

Hadwiger, J. A., Wittenberg, C., Richardson, H. E., de Barros Lopes, M., Reed, S. I. (1989).

A family of cyclin homologs that control the G1 phase in yeast. Proc Natl Acad Sci U

S A 86, 6255-6259.

Han, J., Zhou, H., Horazdovsky, B., Zhang, K., Xu, R. M., and Zhang, Z. (2007a). Rtt109

acetylates histone H3 lysine 56 and functions in DNA replication. Science 315, 653-

655.

Han, J., Zhou, H., Li, Z., Xu, R. M., and Zhang, Z. (2007b). The Rtt109-Vps75 histone

acetyltransferase complex acetylates non-nucleosomal histone H3. J Biol Chem 282,

14158-14164.

Harbison, C. T., Gordon, D. B., Lee, T. I., Rinaldi, N. J., Macisaac, K. D., Danford, T. W.,

Hannett, N. M., Tagne, J. B., Reynolds, D. B., Yoo, J., et al. (2004). Transcriptional

regulatory code of a eukaryotic genome. Nature 431, 99-104.

Heintzman, N. D., Stuart, R. K., Hon, G., Fu, Y., Ching, C. W., Hawkins, R. D., Barrera, L.

O., Van Calcar, S., Qu, C., Ching, K. A., et al. (2007). Distinct and predictive

chromatin signatures of transcriptional promoters and enhancers in the human

genome. Nat Genet 39, 311-318.

Hereford, L. M., Osley, M. A., Ludwig, T. R., 2nd, and McLaughlin, C. S. (1981). Cell-cycle

regulation of yeast histone mRNA. Cell 24, 367-375.

Hess, D., Liu, B., Roan, N. R., Sternglanz, R., and Winston, F. (2004). Spt10-dependent

transcriptional activation in Saccharomyces cerevisiae requires both the Spt10

acetyltransferase domain and Spt21. Mol Cell Biol 24, 135-143.

 

 

138

 

Hess, D., and Winston, F. (2005). Evidence that Spt10 and Spt21 of Saccharomyces

cerevisiae play distinct roles in vivo and functionally interact with MCB-binding

factor, SCB-binding factor and Snf1. Genetics 170, 87-94.

Hiraga, S., Botsios, S., and Donaldson, A. D. (2008). Histone H3 lysine 56 acetylation by

Rtt109 is crucial for chromosome positioning. J Cell Biol 183, 641-651.

Horak, C. E., Luscombe, N. M., Qian, J., Bertone, P., Piccirrillo, S., Gerstein, M., and

Snyder, M. (2002). Complex transcriptional circuitry at the G1/S transition in

Saccharomyces cerevisiae. Genes Dev 16, 3017-3033.

Huang, S., Zhou, H., Katzmann, D., Hochstrasser, M., Atanasova, E., and Zhang, Z. (2005).

Rtt106p is a histone chaperone involved in heterochromatin-mediated silencing. Proc

Natl Acad Sci U S A 102, 13410-13415.

Huang, S., Zhou, H., Tarara, J., and Zhang, Z. (2007). A novel role for histone chaperones

CAF-1 and Rtt106p in heterochromatin silencing. Embo J 26, 2274-2283.

Hughes, J. D., Estep, P. W., Tavazoie, S., and Church, G. M. (2000a). Computational

identification of cis-regulatory elements associated with groups of functionally

related genes in Saccharomyces cerevisiae. J Mol Biol 296, 1205-1214.

Hughes, T. R., Mao, M., Jones, A. R., Burchard, J., Marton, M. J., Shannon, K. W.,

Lefkowitz, S. M., Ziman, M., Schelter, J. M., Meyer, M. R., et al. (2001). Expression

profiling using microarrays fabricated by an ink-jet oligonucleotide synthesizer. Nat

Biotechnol 19, 342-347.

Hughes, T. R., Marton, M. J., Jones, A. R., Roberts, C. J., Stoughton, R., Armour, C. D.,

Bennett, H. A., Coffey, E., Dai, H., He, Y. D., et al. (2000b). Functional discovery

via a compendium of expression profiles. Cell 102, 109-126.

 

 

139

 

Hughes, T. R., and Shoemaker, D. D. (2001). DNA microarrays for expression profiling.

Curr Opin Chem Biol 5, 21-25.

Huh, W. K., Falvo, J. V., Gerke, L. C., Carroll, A. S., Howson, R. W., Weissman, J. S., and

O'Shea, E. K. (2003). Global analysis of protein localization in budding yeast. Nature

425, 686-691.

Idnurm, A., Walton, F. J., Floyd, A., Reedy, J. L., and Heitman, J. (2009). Identification of

ENA1 as a virulence gene of the human pathogenic fungus Cryptococcus neoformans

through signature-tagged insertional mutagenesis. Eukaryot Cell 8, 315-326.

Imbeault, D., Gamar, L., Rufiange, A., Paquet, E., and Nourani, A. (2008). The Rtt106

histone chaperone is functionally linked to transcription elongation and is involved in

the regulation of spurious transcription from cryptic promoters in yeast. J Biol Chem

283, 27350-27354.

Ivessa, A. S., Lenzmeier, B. A., Bessler, J. B., Goudsouzian, L. K., Schnakenberg, S. L., and

Zakian, V. A. (2003). The Saccharomyces cerevisiae helicase Rrm3p facilitates

replication past nonhistone protein-DNA complexes. Mol Cell 12, 1525-1536.

Iyer, V. R., Horak, C. E., Scafe, C. S., Botstein, D., Snyder, M., and Brown, P. O. (2001).

Genomic binding sites of the yeast cell-cycle transcription factors SBF and MBF.

Nature 409, 533-538.

Jambunathan, N., Martinez, A. W., Robert, E. C., Agochukwu, N. B., Ibos, M. E., Dugas, S.

L., and Donze, D. (2005). Multiple bromodomain genes are involved in restricting the

spread of heterochromatic silencing at the Saccharomyces cerevisiae HMR-tRNA

boundary. Genetics 171, 913-922.

 

 

140

 

Jansen, R. P., Dowzer, C., Michaelis, C., Galova, M., and Nasmyth, K. (1996). Mother cell-

specific HO expression in budding yeast depends on the unconventional myosin

myo4p and other cytoplasmic proteins. Cell 84, 687-697.

Jensen, R., Sprague, G. F., Jr., and Herskowitz, I. (1983). Regulation of yeast mating-type

interconversion: feedback control of HO gene expression by the mating-type locus.

Proc Natl Acad Sci U S A 80, 3035-3039.

Kainth, P., Sassi, H. E., Pena-Castillo, L., Chua, G., Hughes, T. R., and Andrews, B. (2009).

Comprehensive genetic analysis of transcription factor pathways using a dual reporter

gene system in budding yeast. Methods.

Kamath, R. S., Fraser, A. G., Dong, Y., Poulin, G., Durbin, R., Gotta, M., Kanapin, A., Le

Bot, N., Moreno, S., Sohrmann, M., et al. (2003). Systematic functional analysis of

the Caenorhabditis elegans genome using RNAi. Nature 421, 231-237.

Kaplan, N., Moore, I. K., Fondufe-Mittendorf, Y., Gossett, A. J., Tillo, D., Field, Y.,

LeProust, E. M., Hughes, T. R., Lieb, J. D., Widom, J., and Segal, E. (2009). The

DNA-encoded nucleosome organization of a eukaryotic genome. Nature 458, 362-

366.

Kim, J., Bhinge, A. A., Morgan, X. C., and Iyer, V. R. (2005). Mapping DNA-protein

interactions in large genomes by sequence tag analysis of genomic enrichment. Nat

Methods 2, 47-53.

Kim, M., Ahn, S. H., Krogan, N. J., Greenblatt, J. F., and Buratowski, S. (2004). Transitions

in RNA polymerase II elongation complexes at the 3' ends of genes. Embo J 23, 354-

364.

 

 

141

 

Koch, C., Moll, T., Neuberg, M., Ahorn, H., and Nasmyth, K. (1993). A role for the

transcription factors Mbp1 and Swi4 in progression from G1 to S phase. Science 261,

1551-1557.

Kouzarides, T. (2007). Chromatin modifications and their function. Cell 128, 693-705.

Krogan, N. J., Cagney, G., Yu, H., Zhong, G., Guo, X., Ignatchenko, A., Li, J., Pu, S., Datta,

N., Tikuisis, A. P., et al. (2006). Global landscape of protein complexes in the yeast

Saccharomyces cerevisiae. Nature 440, 637-643.

Lamb, J., Ramaswamy, S., Ford, H. L., Contreras, B., Martinez, R. V., Kittrell, F. S.,

Zahnow, C. A., Patterson, N., Golub, T. R., and Ewen, M. E. (2003). A mechanism of

cyclin D1 action encoded in the patterns of gene expression in human cancer. Cell

114, 323-334.

Lambert, J. P., Mitchell, L., Rudner, A., Baetz, K., and Figeys, D. (2009). A novel

proteomics approach for the discovery of chromatin-associated protein networks. Mol

Cell Proteomics 8, 870-882.

Lamour, V., Lecluse, Y., Desmaze, C., Spector, M., Bodescot, M., Aurias, A., Osley, M. A.,

and Lipinski, M. (1995). A human homolog of the S. cerevisiae HIR1 and HIR2

transcriptional repressors cloned from the DiGeorge syndrome critical region. Hum

Mol Genet 4, 791-799.

Lashkari, D. A., DeRisi, J. L., McCusker, J. H., Namath, A. F., Gentile, C., Hwang, S. Y.,

Brown, P. O., and Davis, R. W. (1997). Yeast microarrays for genome wide parallel

genetic and gene expression analysis. Proc Natl Acad Sci U S A 94, 13057-13062.

 

 

142

 

Lee, C. K., Shibata, Y., Rao, B., Strahl, B. D., and Lieb, J. D. (2004). Evidence for

nucleosome depletion at active regulatory regions genome-wide. Nat Genet 36, 900-

905.

Lee, T. I., Rinaldi, N. J., Robert, F., Odom, D. T., Bar-Joseph, Z., Gerber, G. K., Hannett, N.

M., Harbison, C. T., Thompson, C. M., Simon, I., et al. (2002). Transcriptional

regulatory networks in Saccharomyces cerevisiae. Science 298, 799-804.

Lee, W., Tillo, D., Bray, N., Morse, R. H., Davis, R. W., Hughes, T. R., and Nislow, C.

(2007). A high-resolution atlas of nucleosome occupancy in yeast. Nat Genet 39,

1235-1244.

Lefrancois, P., Euskirchen, G. M., Auerbach, R. K., Rozowsky, J., Gibson, T., Yellman, C.

M., Gerstein, M., and Snyder, M. (2009). Efficient yeast ChIP-Seq using multiplex

short-read DNA sequencing. BMC Genomics 10, 37.

Lehner, B., Crombie, C., Tischler, J., Fortunato, A., and Fraser, A. G. (2006). Systematic

mapping of genetic interactions in Caenorhabditis elegans identifies common

modifiers of diverse signaling pathways. Nat Genet 38, 896-903.

Li, Q., Zhou, H., Wurtele, H., Davies, B., Horazdovsky, B., Verreault, A., and Zhang, Z.

(2008). Acetylation of histone H3 lysine 56 regulates replication-coupled nucleosome

assembly. Cell 134, 244-255.

Lin, Y. Y., Qi, Y., Lu, J. Y., Pan, X., Yuan, D. S., Zhao, Y., Bader, J. S., and Boeke, J. D.

(2008). A comprehensive synthetic genetic interaction network governing yeast

histone acetylation and deacetylation. Genes Dev 22, 2062-2074.

Lipshutz, R. J., Fodor, S. P., Gingeras, T. R., and Lockhart, D. J. (1999). High density

synthetic oligonucleotide arrays. Nat Genet 21, 20-24.

 

 

143

 

Lycan, D. E., Osley, M. A., and Hereford, L. M. (1987). Role of transcriptional and

posttranscriptional regulation in expression of histone genes in Saccharomyces

cerevisiae. Mol Cell Biol 7, 614-621.

Maas, N. L., Miller, K. M., DeFazio, L. G., and Toczyski, D. P. (2006). Cell cycle and

checkpoint regulation of histone H3 K56 acetylation by Hst3 and Hst4. Mol Cell 23,

109-119.

Masumoto, H., Hawke, D., Kobayashi, R., and Verreault, A. (2005). A role for cell-cycle-

regulated histone H3 lysine 56 acetylation in the DNA damage response. Nature 436,

294-298.

Mendenhall, M. D., and Hodge, A. E. (1998). Regulation of Cdc28 cyclin-dependent protein

kinase activity during the cell cycle of the yeast Saccharomyces cerevisiae. Microbiol

Mol Biol Rev 62, 1191-1243.

Mnaimneh, S., Davierwala, A. P., Haynes, J., Moffat, J., Peng, W. T., Zhang, W., Yang, X.,

Pootoolal, J., Chua, G., Lopez, A., et al. (2004). Exploration of essential gene

functions via titratable promoter alleles. Cell 118, 31-44.

Moffat, J., Grueneberg, D. A., Yang, X., Kim, S. Y., Kloepfer, A. M., Hinkle, G., Piqani, B.,

Eisenhaure, T. M., Luo, B., Grenier, J. K., et al. (2006). A lentiviral RNAi library for

human and mouse genes applied to an arrayed viral high-content screen. Cell 124,

1283-1298.

Nagy, P. L., Cleary, M. L., Brown, P. O., and Lieb, J. D. (2003). Genomewide demarcation

of RNA polymerase II transcription units revealed by physical fractionation of

chromatin. Proc Natl Acad Sci U S A 100, 6364-6369.

Nasmyth, K. (1983). Molecular analysis of a cell lineage. Nature 302, 670-676.

 

 

144

 

Nasmyth, K., and Dirick, L. (1991). The role of SWI4 and SWI6 in the activity of G1 cyclins

in yeast. Cell 66, 995-1013.

Newman, J. R., Ghaemmaghami, S., Ihmels, J., Breslow, D. K., Noble, M., DeRisi, J. L., and

Weissman, J. S. (2006). Single-cell proteomic analysis of S. cerevisiae reveals the

architecture of biological noise. Nature 441, 840-846.

Nourani, A., Robert, F., and Winston, F. (2006). Evidence that Spt2/Sin1, an HMG-like

factor, plays roles in transcription elongation, chromatin structure, and genome

stability in Saccharomyces cerevisiae. Mol Cell Biol 26, 1496-1509.

Ogas, J., Andrews, B. J., and Herskowitz, I. (1991). Transcriptional activation of CLN1,

CLN2, and a putative new G1 cyclin (HCS26) by SWI4, a positive regulator of G1-

specific transcription. Cell 66, 1015-1026.

Oliva, A., Rosebrock, A., Ferrezuelo, F., Pyne, S., Chen, H., Skiena, S., Futcher, B., and

Leatherwood, J. (2005). The cell cycle-regulated genes of Schizosaccharomyces

pombe. PLoS Biol 3, e225.

Orlando, V. (2000). Mapping chromosomal proteins in vivo by formaldehyde-crosslinked-

chromatin immunoprecipitation. Trends Biochem Sci 25, 99-104.

Osley, M. A. (1991). The regulation of histone synthesis in the cell cycle. Annu Rev

Biochem 60, 827-861.

Osley, M. A., Gould, J., Kim, S., Kane, M. Y., and Hereford, L. (1986). Identification of

sequences in a yeast histone promoter involved in periodic transcription. Cell 45,

537-544.

Osley, M. A., and Lycan, D. (1987). Trans-acting regulatory mutations that alter

transcription of Saccharomyces cerevisiae histone genes. Mol Cell Biol 7, 4204-4210.

 

 

145

 

Ozdemir, A., Spicuglia, S., Lasonder, E., Vermeulen, M., Campsteijn, C., Stunnenberg, H.

G., and Logie, C. (2005). Characterization of lysine 56 of histone H3 as an

acetylation site in Saccharomyces cerevisiae. J Biol Chem 280, 25949-25952.

Pan, X., Yuan, D. S., Xiang, D., Wang, X., Sookhai-Mahadeo, S., Bader, J. S., Hieter, P.,

Spencer, F., and Boeke, J. D. (2004). A robust toolkit for functional profiling of the

yeast genome. Mol Cell 16, 487-496.

Peng, X., Karuturi, R. K., Miller, L. D., Lin, K., Jia, Y., Kondu, P., Wang, L., Wong, L. S.,

Liu, E. T., Balasubramanian, M. K., and Liu, J. (2005). Identification of cell cycle-

regulated genes in fission yeast. Mol Biol Cell 16, 1026-1042.

Perou, C. M., Jeffrey, S. S., van de Rijn, M., Rees, C. A., Eisen, M. B., Ross, D. T.,

Pergamenschikov, A., Williams, C. F., Zhu, S. X., Lee, J. C., et al. (1999).

Distinctive gene expression patterns in human mammary epithelial cells and breast

cancers. Proc Natl Acad Sci U S A 96, 9212-9217.

Pokholok, D. K., Harbison, C. T., Levine, S., Cole, M., Hannett, N. M., Lee, T. I., Bell, G.

W., Walker, K., Rolfe, P. A., Herbolsheimer, E., et al. (2005). Genome-wide map of

nucleosome acetylation and methylation in yeast. Cell 122, 517-527.

Polach, K. J., and Widom, J. (1995). Mechanism of protein access to specific DNA

sequences in chromatin: a dynamic equilibrium model for gene regulation. J Mol Biol

254, 130-149.

Pramila, T., Wu, W., Miles, S., Noble, W. S., and Breeden, L. L. (2006). The Forkhead

transcription factor Hcm1 regulates chromosome segregation genes and fills the S-

phase gap in the transcriptional circuitry of the cell cycle. Genes Dev 20, 2266-2278.

 

 

146

 

Prochasson, P., Florens, L., Swanson, S. K., Washburn, M. P., and Workman, J. L. (2005).

The HIR corepressor complex binds to nucleosomes generating a distinct

protein/DNA complex resistant to remodeling by SWI/SNF. Genes Dev 19, 2534-

2539.

Ramsay, G. (1998). DNA chips: state-of-the art. Nat Biotechnol 16, 40-44.

Recht, J., Tsubota, T., Tanny, J. C., Diaz, R. L., Berger, J. M., Zhang, X., Garcia, B. A.,

Shabanowitz, J., Burlingame, A. L., Hunt, D. F., et al. (2006). Histone chaperone

Asf1 is required for histone H3 lysine 56 acetylation, a modification associated with

S phase in mitosis and meiosis. Proc Natl Acad Sci U S A 103, 6988-6993.

Reinke, H., and Horz, W. (2003). Histones are first hyperacetylated and then lose contact

with the activated PHO5 promoter. Mol Cell 11, 1599-1607.

Ren, B., Robert, F., Wyrick, J. J., Aparicio, O., Jennings, E. G., Simon, I., Zeitlinger, J.,

Schreiber, J., Hannett, N., Kanin, E., et al. (2000). Genome-wide location and

function of DNA binding proteins. Science 290, 2306-2309.

Roguev, A., Wiren, M., Weissman, J. S., and Krogan, N. J. (2007). High-throughput genetic

interaction mapping in the fission yeast Schizosaccharomyces pombe. Nat Methods 4,

861-866.

Rufiange, A., Jacques, P. E., Bhat, W., Robert, F., and Nourani, A. (2007). Genome-wide

replication-independent histone H3 exchange occurs predominantly at promoters and

implicates H3 K56 acetylation and Asf1. Mol Cell 27, 393-405.

Rustici, G., Mata, J., Kivinen, K., Lio, P., Penkett, C. J., Burns, G., Hayles, J., Brazma, A.,

Nurse, P., and Bahler, J. (2004). Periodic gene expression program of the fission

yeast cell cycle. Nat Genet 36, 809-817.

 

 

147

 

Sassi, H. E., Bastajian, N., Kainth, P., and Andrews, B. J. (2009). Reporter-based synthetic

genetic array analysis: a functional genomics approach for investigating the cell cycle

in Saccharomyces cerevisiae. Methods Mol Biol 548, 55-73.

Schena, M., Shalon, D., Davis, R. W., and Brown, P. O. (1995). Quantitative monitoring of

gene expression patterns with a complementary DNA microarray. Science 270, 467-

470.

Schlabach, M. R., Luo, J., Solimini, N. L., Hu, G., Xu, Q., Li, M. Z., Zhao, Z.,

Smogorzewska, A., Sowa, M. E., Ang, X. L., et al. (2008). Cancer proliferation gene

discovery through functional genomics. Science 319, 620-624.

Schuldiner, M., Collins, S. R., Thompson, N. J., Denic, V., Bhamidipati, A., Punna, T.,

Ihmels, J., Andrews, B., Boone, C., Greenblatt, J. F., et al. (2005). Exploration of the

function and organization of the yeast early secretory pathway through an epistatic

miniarray profile. Cell 123, 507-519.

Schwabish, M. A., and Struhl, K. (2006). Asf1 mediates histone eviction and deposition

during elongation by RNA polymerase II. Mol Cell 22, 415-422.

Schwabish, M. A., and Struhl, K. (2007). The Swi/Snf complex is important for histone

eviction during transcriptional activation and RNA polymerase II elongation in vivo.

Mol Cell Biol 27, 6987-6995.

Shalon, D., Smith, S. J., and Brown, P. O. (1996). A DNA microarray system for analyzing

complex DNA samples using two-color fluorescent probe hybridization. Genome Res

6, 639-645.

 

 

148

 

Shaner, N. C., Campbell, R. E., Steinbach, P. A., Giepmans, B. N., Palmer, A. E., and Tsien,

R. Y. (2004). Improved monomeric red, orange and yellow fluorescent proteins

derived from Discosoma sp. red fluorescent protein. Nat Biotechnol 22, 1567-1572.

Shaner, N. C., Patterson, G. H., and Davidson, M. W. (2007). Advances in fluorescent

protein technology. J Cell Sci 120, 4247-4260.

Shaner, N. C., Steinbach, P. A., and Tsien, R. Y. (2005). A guide to choosing

fluorescent proteins. Nat Methods 2, 905-909.

Sikorski, R. S., and Hieter, P. (1989). A system of shuttle vectors and yeast host strains

designed for efficient manipulation of DNA in Saccharomyces cerevisiae. Genetics

122, 19-27.

Silva, J. M., Marran, K., Parker, J. S., Silva, J., Golding, M., Schlabach, M. R., Elledge, S. J.,

Hannon, G. J., and Chang, K. (2008). Profiling essential genes in human mammary

cells by multiplex RNAi screening. Science 319, 617-620.

Simon, I., Barnett, J., Hannett, N., Harbison, C. T., Rinaldi, N. J., Volkert, T. L., Wyrick, J.

J., Zeitlinger, J., Gifford, D. K., Jaakkola, T. S., and Young, R. A. (2001). Serial

regulation of transcriptional regulators in the yeast cell cycle. Cell 106, 697-708.

Solomon, M. J., Larsen, P. L., and Varshavsky, A. (1988). Mapping protein-DNA

interactions in vivo with formaldehyde: evidence that histone H4 is retained on a

highly transcribed gene. Cell 53, 937-947.

Solomon, M. J., and Varshavsky, A. (1985). Formaldehyde-mediated DNA-protein

crosslinking: a probe for in vivo chromatin structures. Proc Natl Acad Sci U S A 82,

6470-6474.

 

 

149

 

Sopko, R., Huang, D., Preston, N., Chua, G., Papp, B., Kafadar, K., Snyder, M., Oliver, S.

G., Cyert, M., Hughes, T. R., et al. (2006). Mapping pathways and phenotypes by

systematic gene overexpression. Mol Cell 21, 319-330.

Spellman, P. T., Sherlock, G., Zhang, M. Q., Iyer, V. R., Anders, K., Eisen, M. B., Brown, P.

O., Botstein, D., and Futcher, B. (1998). Comprehensive identification of cell cycle-

regulated genes of the yeast Saccharomyces cerevisiae by microarray hybridization.

Mol Biol Cell 9, 3273-3297.

Stern, M., Jensen, R., and Herskowitz, I. (1984). Five SWI genes are required for expression

of the HO gene in yeast. J Mol Biol 178, 853-868.

Sternberg, P. W., Stern, M. J., Clark, I., and Herskowitz, I. (1987). Activation of the yeast

HO gene by release from multiple negative controls. Cell 48, 567-577.

Sutton, A., Bucaria, J., Osley, M. A., and Sternglanz, R. (2001). Yeast ASF1 protein is

required for cell cycle regulation of histone gene transcription. Genetics 158, 587-

596.

Tackett, A. J., Dilworth, D. J., Davey, M. J., O'Donnell, M., Aitchison, J. D., Rout, M. P.,

and Chait, B. T. (2005). Proteomic and genomic characterization of chromatin

complexes at a boundary. J Cell Biol 169, 35-47.

Tait-Kamradt, A. G., Turner, K. J., Kramer, R. A., Elliott, Q. D., Bostian, S. J., Thill, G. P.,

Rogers, D. T., and Bostian, K. A. (1986). Reciprocal regulation of the tandemly

duplicated PHO5/PHO3 gene cluster within the acid phosphatase multigene family of

Saccharomyces cerevisiae. Mol Cell Biol 6, 1855-1865.

Timmons, L., and Fire, A. (1998). Specific interference by ingested dsRNA. Nature 395,

854.

 

 

150

 

Tong, A. H., Boone, C. (2005). Synthetic genetic array (SGA) analysis in Saccharomyces

cerevisiae. In Yeast Protocols (Totowa NJ, The Humana Press Inc.), pp. 171-192.

Tong, A. H., Boone, C. (2007). High-throughput strain construction and systematic synthetic

lethal screening in Saccharomyces cerevisiae. In Yeast gene analysis - methods in

microbiology (Elsevier Ltd.), pp. 369-386, 706-707.

Tong, A. H., Evangelista, M., Parsons, A. B., Xu, H., Bader, G. D., Page, N., Robinson, M.,

Raghibizadeh, S., Hogue, C. W., Bussey, H., et al. (2001). Systematic genetic

analysis with ordered arrays of yeast deletion mutants. Science 294, 2364-2368.

Tong, A. H., Lesage, G., Bader, G. D., Ding, H., Xu, H., Xin, X., Young, J., Berriz, G. F.,

Brost, R. L., Chang, M., et al. (2004). Global mapping of the yeast genetic interaction

network. Science 303, 808-813.

Typas, A., Nichols, R. J., Siegele, D. A., Shales, M., Collins, S. R., Lim, B., Braberg, H.,

Yamamoto, N., Takeuchi, R., Wanner, B. L., et al. (2008). High-throughput,

quantitative analyses of genetic interactions in E. coli. Nat Methods 5, 781-787.

Vilela, C., Ramirez, C. V., Linz, B., Rodrigues-Pousada, C., and McCarthy, J. E. (1999).

Post-termination ribosome interactions with the 5'UTR modulate yeast mRNA

stability. Embo J 18, 3139-3152.

Wach, A., Brachat, A., Alberti-Segui, C., Rebischung, C., and Philippsen, P. (1997).

Heterologous HIS3 marker and GFP reporter modules for PCR-targeting in

Saccharomyces cerevisiae. Yeast 13, 1065-1075.

Weeraratna, A. T. (2005). Discovering causes and cures for cancer from gene expression

analysis. Ageing Res Rev 4, 548-563.

 

 

151

 

Whitfield, M. L., Sherlock, G., Saldanha, A. J., Murray, J. I., Ball, C. A., Alexander, K. E.,

Matese, J. C., Perou, C. M., Hurt, M. M., Brown, P. O., and Botstein, D. (2002).

Identification of genes periodically expressed in the human cell cycle and their

expression in tumors. Mol Biol Cell 13, 1977-2000.

Williams, S. K., Truong, D., and Tyler, J. K. (2008). Acetylation in the globular core of

histone H3 on lysine-56 promotes chromatin disassembly during transcriptional

activation. Proc Natl Acad Sci U S A 105, 9000-9005.

Winzeler, E. A., Shoemaker, D. D., Astromoff, A., Liang, H., Anderson, K., Andre, B.,

Bangham, R., Benito, R., Boeke, J. D., Bussey, H., et al. (1999). Functional

characterization of the S. cerevisiae genome by gene deletion and parallel analysis.

Science 285, 901-906.

Wittenberg, C., and Reed, S. I. (2005). Cell cycle-dependent transcription in yeast:

promoters, transcription factors, and transcriptomes. Oncogene 24, 2746-2755.

Woychik, N. A., and Hampsey, M. (2002). The RNA polymerase II machinery: structure

illuminates function. Cell 108, 453-463.

Xu, F., Zhang, K., and Grunstein, M. (2005). Acetylation in histone H3 globular domain

regulates gene expression in yeast. Cell 121, 375-385.

Xu, H., Kim, U. J., Schuster, T., and Grunstein, M. (1992). Identification of a new set of cell

cycle-regulatory genes that regulate S-phase transcription of histone genes in

Saccharomyces cerevisiae. Mol Cell Biol 12, 5249-5259.

Yuan, G. C., Liu, Y. J., Dion, M. F., Slack, M. D., Wu, L. F., Altschuler, S. J., and Rando, O.

J. (2005). Genome-scale identification of nucleosome positions in S. cerevisiae.

Science 309, 626-630.

 

 

152

 

Zhang, Y., Moqtaderi, Z., Rattner, B. P., Euskirchen, G., Snyder, M., Kadonaga, J. T., Liu,

X. S., and Struhl, K. (2009). Intrinsic histone-DNA interactions are not the major

determinant of nucleosome positions in vivo. Nat Struct Mol Biol 16, 847-852.

Zhu, C., Byers, K. J., McCord, R. P., Shi, Z., Berger, M. F., Newburger, D. E., Saulrieta, K.,

Smith, Z., Shah, M. V., Radhakrishnan, M., et al. (2009). High-resolution DNA-

binding specificity analysis of yeast transcription factors. Genome Res 19, 556-566.