New insights into the human genome by ENCODE

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ENCODE

• Union of genomic sequences encoding a coherent set of potentially overlapping functional products.

(Gerstein et al., 2007)

Its been ten years since scientists sequenced the human genome

But What do all these letters????????

21,000 genes

ENCODE- the Encyclopedia of DNA Elements has ANSWERS

Aiming to delineate all of the functional elements encoded in the human genome sequence

ENCODE Consortium

(The ENCODE Project Consortium, 2011)

Pilot Phase • 2003-2007

Technology development

phase

• 2007-2012• 30 papers

Production phase

ENCODE

Major methods

Data production and initial analysis

Accessing ENCODE data

Working with ENCODE data

Data analysis

Limitations

Threads – Nature explorer

Major Methods

(The ENCODE Project Consortium, 2004)

Overall data flow

(The ENCODE Project Consortium, 2011)

(The ENCODE Project Consortium, 2011)

RNA-seq – Isolation of RNA sequences followed by high-throughput

sequencing

CAGE – Capture of the methylated cap at the 5’end of RNA, followed

by high-throughput sequencing

RNA-PET – Simultaneous capture of RNAs with both a 5’methyl cap

and a poly(A) tail

ChIP-seq - Chromatin immunoprecipitation followed by sequencing

FAIRE-seq - Formaldehyde assisted isolation of regulatory elements.

Crosslinking, phenol extraction, and sequencing the DNA fragments

in the aqueous phase

(The ENCODE Project Consortium, 2011)

ENCODE cell types

(The ENCODE Project Consortium, 2011)

ENCODE data production and initial analyses

• Since 2007, ENCODE has developed methods and performed a

large number of sequence-based studies to map functional

elements across the human genome.

• The elements mapped (and approaches used) include

RNA transcribed regions (RNA-seq, CAGE, RNA-PET and

manual annotation),

Protein-coding regions (mass spectrometry),

Transcription-factor-binding sites (ChIP-seq and DNase-seq),

Chromatin structure (DNase-seq, FAIRE-seq, histone ChIP-seq),

DNA methylation sites (RRBS assay)

(The ENCODE Project Consortium, 2012)

Transcribed and protein-coding regions

• In total, GENCODE-annotated exons of protein-coding genes cover 2.94% of the

genome or 1.22% for protein-coding exons.

• Protein-coding genes span 33.45% from the outermost start to stop codons, or

39.54% from promoter to poly(A) site.

• Additional protein-coding genes remain to be found.

• In addition, they annotated 8,801 automatically derived small RNAs and 9,640

manually curated long non-coding RNA (lncRNA) loci

• The GENCODE annotated 11,224 pseudogenes

(The ENCODE Project Consortium, 2012)

Process flow of experimental evaluation of pseudogene transcription

Experimental validation results showing the transcription of pseudogenes in different tissues

(Pei et al., 2012)

ENCODE gene and transcript annotations.

(The ENCODE Project Consortium, 2011)

RNA

• They sequenced RNA from different cell lines and multiple

subcellular fractions to develop an extensive RNA expression

catalogue.

• They used CAGE-seq (5’cap-targeted RNA isolation and

sequencing) to identify 62,403 (TSSs) in tier 1 and2 cell types

(The ENCODE Project Consortium, 2012)

A large majority of GENCODE elements are detected by RNA-seq data

(Djebali et al., 2012)

Protein bound regions

• 119 different DNA-binding proteins and a number of RNA

polymerase components in 72 cell types using ChIP-seq

• Overall, 636,336 binding regions covering 231 mega bases (8.1%)

of the genome are enriched for regions bound by DNA-binding

proteins across all cell types.

(The ENCODE Project Consortium, 2012)

Occupancy of transcription factors and RNA polymerase 2 on human chromosome 6p as

determined by ChIP-seq

(The ENCODE Project Consortium, 2011)

DNase I hypersensitive sites and footprinting

• Chromatin accessibility characterized by DNase I hypersensitivity

is the hallmark of regulatory DNA regions.

• 2.89 million unique, non-overlapping (DHSs) by DNase-seq in 125

cell types – lie distal to TSSs

• In tier 1 and tier 2 cell types - 205,109 DHSs per cell type,

encompassing an average of 1.0% of the genomic sequence in

each cell type, and 3.9% in aggregate.

(The ENCODE Project Consortium, 2012)

Density of DNase I cleavage sites for selected cell types

(Thurman et al., 2012)

• On average, 98.5% of the occupancy sites of transcription factors

mapped by ENCODE ChIP-seq

• Using genomic DNase I footprinting on 41 cell types they identified

8.4million distinct DNase I footprints

(The ENCODE Project Consortium, 2012)

Regions of histone modification

• They assayed chromosomal locations for up to 12 histone

modifications and variants in 46 cell types, across tier 1 and 2.

(The ENCODE Project Consortium, 2012)(http://www.factorbook.org)

DNA methylation

• They used reduced representation bisulphite sequencing (RRBS) to

profile DNA methylation quantitatively for an average of 1.2

million CpGs in each of 82 cell lines and tissues (8.6% of non-

repetitive genomic CpGs), including CpGs in intergenic regions,

proximal promoters and intragenic regions.

(The ENCODE Project Consortium, 2012)

Proteomics

To assess putative protein products generated from novel RNA

transcripts and isoforms, proteins are sequenced and quantified by

mass spectrometry and mapped back to their encoding

transcripts.

K562 and GM12878 – protein study begun

(The ENCODE Project Consortium, 2011)

ENCODE chromatin annotations in the HLA locus

(The ENCODE Project Consortium, 2011)

Accessing ENCODE Data

ENCODE Data Release and Use Policy

• The ENCODE Data Release and Use Policy is described at http://

www.encodeproject.org/ENCODE/terms.html.

• ENCODE data are released for viewing in a publicly accessible

browser (initially at http://genome-preview.ucsc.edu/ENCODE and,

after additional quality checks, at http://encodeproject.org)

Public Repositories

• UCSC Genome Browser database (http://genome.ucsc.edu).

(The ENCODE Project Consortium, 2011)

UCSC Portal

Working with ENCODE Data

Using ENCODE Data in the UCSC Browser

• Many users will want to view and interpret the ENCODE data for

particular genes of interest. At the online ENCODE portal (http://

encodeproject.org), users should follow a ‘‘Genome Browser’’ link

to visualize the data in the context of other genome annotations.

(The ENCODE Project Consortium, 2011)

ENCODE Data Analysis

• Development and implementation of algorithms and pipelines for

processing and analyzing data - major activity of the ENCODE

Project.

• Short sequences are aligned to the reference genome

1st Phase

• Identifying the enriched regions

2nd Phase • Integrating the identified regions of enriched signal with each other and with other data types

3rd Phase

(The ENCODE Project Consortium, 2011)

Analysis tools applied by the ENCODE consortium

(The ENCODE Project Consortium, 2011)

Integrating ENCODE with other projects and the

Scientific Community

1. defining promoter and enhancer regions by combining transcript

mapping and biochemical marks,

2. delineating distinct classes of regions within the genomic

landscape by their specific combinations of biochemical and

functional characteristics, and

3. defining transcription factor co-associations and regulatory

networks.

(The ENCODE Project Consortium, 2011)

• ENCODE Project - interpretation of human genome variation that is

associated with disease or quantitative phenotypes

• Integrate with 1,000 Genomes Project - how SNPs and structural

variation may affect transcript, regulatory and DNA methylation

data

• ENCODE - GWAS and other sequence variation driven studies of

human phenotypes

Major contributor not only of data but also novel technologies for

deciphering the human genome

(The ENCODE Project Consortium, 2011)

Limitations of ENCODE Annotations

• Cell types - physiologically and genetically inhomogeneous.

• Local micro-environments in culture may also vary

• Use of DNA sequencing to annotate functional genomic features is

also constrained.

• Considerable quantitative variation in the signal strength along

the genome

(The ENCODE Project Consortium, 2011)

Challenges

• Adult human body contains several hundred distinct cell types

• Each of which expresses a unique subset of the 1,800 TFs encoded

in the human genome

• Brain alone contains thousands of types of neurons that are likely

to express not only different sets of TFs but also a larger variety of

non-coding RNAs

• A truly comprehensive atlas of human functional elements is not

practical with current technologies

(The ENCODE Project Consortium, 2011)

Outcome

• Understanding of the human genome

• The broad coverage of ENCODE annotations enhances our

understanding of common diseases with a genetic component,

rare genetic diseases

• 119 of 1,800 known transcription factors and 13 of more than 60

currently known histone or DNA modifications across 147 cell

types

• Overall these data reflect a minor fraction of the potential

functional information encoded in the human genome

(The ENCODE Project Consortium, 2012)

http://www.nature.com/encode/#/threads

13 Threads

1. Transcription factor motifs

2. Chromatin patterns at transcription factor binding sites

3. Characterization of intergenic regions and gene definition

4. RNA and chromatin modification patterns around promoters

5. Epigenetic regulation of RNA processing

6. Non-coding RNA characterization

7. DNA methylation

8. Enhancer discovery and characterization

9. Three-dimensional connections across the genome

10. Characterization of network topology

11. Machine learning approaches to genomics

12. Impact of functional information on understanding variation

13. Impact of evolutionary selection on functional regions

Schematic overview of the functional SNP approach

(Schaub et al., 2012)

Comparison of GWAS identified loci with ENCODE data

(Boyle et al., 2012)

Future goal

• Mechanistic processes that generate these elements and how and

where they function

• Enlarge the data set to additional factors, modifications and cell

types, complementing the other related projects

• Constitute foundational resources for human genomics, allowing a

deeper interpretation of the organization of gene and regulatory

information and the mechanisms of regulation, and thereby

provide important insights into human health and disease

(The ENCODE Project Consortium, 2012)

Project is still far from complete

Conclusion

For update: https://www.facebook.com/ENCODEProject

Encode – assign word to letter

Thank you:)