Using Microarrays to Measure Sequence Preferences of Berenil Binding to the DNA Minor Groove
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Transcript of Using Microarrays to Measure Sequence Preferences of Berenil Binding to the DNA Minor Groove
Using Microarrays to Measure Using Microarrays to Measure Sequence Preferences of Sequence Preferences of
Berenil Binding to the DNA Berenil Binding to the DNA Minor GrooveMinor Groove
Adam BrownAdam BrownMissouri Western State UniversityMissouri Western State University
Coauthors: Steven N. Hart, Kelly J. Malloy, Todd T. Eckdahl, Laurie J. Coauthors: Steven N. Hart, Kelly J. Malloy, Todd T. Eckdahl, Laurie J. Heyer, Martha Shott, Laura L. Mays Hoopes, Gloria YiuHeyer, Martha Shott, Laura L. Mays Hoopes, Gloria Yiu
Missouri Western State University Biology Department, Genome Missouri Western State University Biology Department, Genome Consortium for Active Teaching, Davidson College Biology Consortium for Active Teaching, Davidson College Biology
Department, Pomona College Biology Department Department, Pomona College Biology Department
IntroductionIntroduction
Minor Groove Binding Minor Groove Binding DrugsDrugs
Biological ActivityBiological Activity BerenilBerenil
Berenil Sequence PreferencesBerenil Sequence Preferences
Binding sites 5-6 bpBinding sites 5-6 bpA+T rich A+T rich HeteropolymericHeteropolymeric
ATAT > AATT > AAAA ATAT > AATT > AAAA ATATT > AATAT > AATTT > AAAAATATT > AATAT > AATTT > AAAA
Experimental PlanExperimental Plan
Yeast modelYeast model Expose yeast to Expose yeast to
berenilberenil RNA IsolationRNA Isolation Microarray ChipsMicroarray Chips MAGIC ToolMAGIC Tool Real Time PCRReal Time PCR Data AnalysisData Analysis
Indirect Labeling – 3DNAIndirect Labeling – 3DNA
Includes Two Includes Two HybridizationsHybridizations
Reverse Reverse Transcription Transcription occurs without occurs without labelinglabeling
Requires only Requires only 2.0 ug of RNA2.0 ug of RNA
Microarray ImagesMicroarray Images
MAGIC ToolMAGIC Tool
Microarray DataMicroarray Data
Genes Affected by BerenilGenes Affected by Berenil
50 Genes Turned off50 Genes Turned off15 carbohydrate metabolism, cell division, 15 carbohydrate metabolism, cell division,
proteolysis, response to metals, vacuole proteolysis, response to metals, vacuole fusionfusion
5 mitochondrial or respiration5 mitochondrial or respiration16 unassigned function16 unassigned function14 stress-related14 stress-related
2 Genes Turned on2 Genes Turned onPhosphate metabolism, rRNA processingPhosphate metabolism, rRNA processing
Validation by RT PCRValidation by RT PCR
Expression ratios for selected genes Expression ratios for selected genes validated by Real Time RT-PCRvalidated by Real Time RT-PCR
Sequence AnalysisSequence Analysis
54 affected genes compared to 56 unaffected 54 affected genes compared to 56 unaffected genesgenes
200 nt upstream regions of translation start sites200 nt upstream regions of translation start sites Occurrence of all 5-mer and 6-mer sequences Occurrence of all 5-mer and 6-mer sequences
measuredmeasured Ranking criteriaRanking criteria
Diff between percentage of affected and unaffected Diff between percentage of affected and unaffected regions having a sequenceregions having a sequence
Ratio of occurrence of sequence in affected Ratio of occurrence of sequence in affected compared to unaffected regionscompared to unaffected regions
Difference Criterion SequencesDifference Criterion Sequences
Ratio Criterion SequencesRatio Criterion Sequences
Sequence FeaturesSequence Features
The average A+T content of the The average A+T content of the sequences is 90% (65% for all yeast sequences is 90% (65% for all yeast genes)genes)
Of the 8 possible completely Of the 8 possible completely heteropolymeric sequences, 4 appearheteropolymeric sequences, 4 appear
51% of the dinucleotides are AT or TA. 51% of the dinucleotides are AT or TA. Only 18% of dinucleotides in the 200 bp Only 18% of dinucleotides in the 200 bp upstream of all yeast genes are AT or TA. upstream of all yeast genes are AT or TA.
Direct versus Indirect EffectsDirect versus Indirect Effects
Upstream sequences of 54 affected genes Upstream sequences of 54 affected genes were A+T rich, heteropolymeric were A+T rich, heteropolymeric
But, the method cannot distinguish:But, the method cannot distinguish:Genes directly affected by berenilGenes directly affected by berenilGenes indirectly affected by the product of a Genes indirectly affected by the product of a
directly affected genedirectly affected geneAre the stress-related genes indirectly Are the stress-related genes indirectly
affected?affected?Are their upstream sequences different Are their upstream sequences different
from the rest of the affected genes?from the rest of the affected genes?
Difference Criterion - DirectDifference Criterion - Direct
Ratio Criterion - DirectRatio Criterion - Direct
Difference Criterion - IndirectDifference Criterion - Indirect
Ratio Criterion - IndirectRatio Criterion - Indirect
Features Found Upstream Features Found Upstream Directly Affected GenesDirectly Affected Genes
Average of 92% A+TAverage of 92% A+T 100% are at least 80% A+T100% are at least 80% A+T Difference and ratio measures yield 75% Difference and ratio measures yield 75%
shared sequencesshared sequences 52% of dinucleotides are AT and TA, 52% of dinucleotides are AT and TA,
compared to 18% for all yeast genescompared to 18% for all yeast genes Completely A/T heteropolymeric 5- and 6-mers Completely A/T heteropolymeric 5- and 6-mers
occur at 4.4 times the expected rateoccur at 4.4 times the expected rate The high rate of heteropolymeric tracts of 3-6 The high rate of heteropolymeric tracts of 3-6
nt is statistically significantnt is statistically significant
Chi-squared AnalysisChi-squared Analysis
ConclusionsConclusions
Microarray analysis yielded list of yeast genes Microarray analysis yielded list of yeast genes affected by Berenilaffected by Berenil
Gene functions suggested direct and indirect Gene functions suggested direct and indirect effectseffects Direct category had expected sequence featuresDirect category had expected sequence features Indirect category did not display sequence featuresIndirect category did not display sequence features
Results contribute to Results contribute to an understanding of an understanding of in vivo in vivo sequence requirements sequence requirements
for Berenil bindingfor Berenil binding a new approach to analysis of microarray data setsa new approach to analysis of microarray data sets
ReferencesReferencesS. Neidle. S. Neidle. Nat Prod RepNat Prod Rep 1818, 291 (2001), 291 (2001)P.G. Baraldi P.G. Baraldi et al., Med Res Revet al., Med Res Rev 2424, 475 (2004), 475 (2004)L.J. Heyer L.J. Heyer et al., Bioinformaticset al., Bioinformatics. . 2121, 2114 (2005), 2114 (2005)A. Abu-Daya A. Abu-Daya et al., Nucleic Acids Reset al., Nucleic Acids Res 2323, 3385 (1995), 3385 (1995)D.L. Boger D.L. Boger et al., J Am Chem Socet al., J Am Chem Soc 123123, 5878 (2001), 5878 (2001)F. Rosu F. Rosu et al., Nucleic Acids Reset al., Nucleic Acids Res. . 3030, e82 (2002), e82 (2002)
AcknowledgementsAcknowledgementsThanks to the Genome Consortium for Active Teaching (GCAT) Thanks to the Genome Consortium for Active Teaching (GCAT)
and Dr. John N. Anderson (Purdue) for advice and discussions. and Dr. John N. Anderson (Purdue) for advice and discussions. This work was supported by the Missouri Western Summer This work was supported by the Missouri Western Summer Research Institute, and NIH AREA grant 1R15CA096723-01.Research Institute, and NIH AREA grant 1R15CA096723-01.