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Using Microarrays to Measure Sequence Preferences of Berenil Binding to the DNA Minor Groove Adam Brown Missouri Western State University Coauthors: Steven.

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Presentation on theme: "Using Microarrays to Measure Sequence Preferences of Berenil Binding to the DNA Minor Groove Adam Brown Missouri Western State University Coauthors: Steven."— Presentation transcript:

1 Using Microarrays to Measure Sequence Preferences of Berenil Binding to the DNA Minor Groove Adam Brown Missouri Western State University Coauthors: Steven N. Hart, Kelly J. Malloy, Todd T. Eckdahl, Laurie J. Heyer, Martha Shott, Laura L. Mays Hoopes, Gloria Yiu Missouri Western State University Biology Department, Genome Consortium for Active Teaching, Davidson College Biology Department, Pomona College Biology Department

2 Introduction Minor Groove Binding Drugs Minor Groove Binding Drugs Biological Activity Biological Activity Berenil Berenil

3 Berenil Sequence Preferences Binding sites 5-6 bp Binding sites 5-6 bp A+T rich A+T rich Heteropolymeric Heteropolymeric ATAT > AATT > AAAA ATAT > AATT > AAAA ATATT > AATAT > AATTT > AAAA ATATT > AATAT > AATTT > AAAA

4 Experimental Plan Yeast model Yeast model Expose yeast to berenil Expose yeast to berenil RNA Isolation RNA Isolation Microarray Chips Microarray Chips MAGIC Tool MAGIC Tool Real Time PCR Real Time PCR Data Analysis Data Analysis

5 Indirect Labeling – 3DNA Includes Two Hybridizations Includes Two Hybridizations Reverse Transcription occurs without labeling Reverse Transcription occurs without labeling Requires only 2.0 ug of RNA Requires only 2.0 ug of RNA

6 Microarray Images

7 MAGIC Tool

8 Microarray Data

9 Genes Affected by Berenil 50 Genes Turned off 50 Genes Turned off 15 carbohydrate metabolism, cell division, proteolysis, response to metals, vacuole fusion 5 mitochondrial or respiration 16 unassigned function 14 stress-related 2 Genes Turned on 2 Genes Turned on Phosphate metabolism, rRNA processing

10 Validation by RT PCR Expression ratios for selected genes validated by Real Time RT-PCR Expression ratios for selected genes validated by Real Time RT-PCR

11 Sequence Analysis 54 affected genes compared to 56 unaffected genes 54 affected genes compared to 56 unaffected genes 200 nt upstream regions of translation start sites 200 nt upstream regions of translation start sites Occurrence of all 5-mer and 6-mer sequences measured Occurrence of all 5-mer and 6-mer sequences measured Ranking criteria Ranking criteria Diff between percentage of affected and unaffected regions having a sequence Diff between percentage of affected and unaffected regions having a sequence Ratio of occurrence of sequence in affected compared to unaffected regions Ratio of occurrence of sequence in affected compared to unaffected regions

12 Difference Criterion Sequences

13 Ratio Criterion Sequences

14 Sequence Features The average A+T content of the sequences is 90% (65% for all yeast genes) The average A+T content of the sequences is 90% (65% for all yeast genes) Of the 8 possible completely heteropolymeric sequences, 4 appear Of the 8 possible completely heteropolymeric sequences, 4 appear 51% of the dinucleotides are AT or TA. Only 18% of dinucleotides in the 200 bp upstream of all yeast genes are AT or TA. 51% of the dinucleotides are AT or TA. Only 18% of dinucleotides in the 200 bp upstream of all yeast genes are AT or TA.

15 Direct versus Indirect Effects Upstream sequences of 54 affected genes were A+T rich, heteropolymeric Upstream sequences of 54 affected genes were A+T rich, heteropolymeric But, the method cannot distinguish: But, the method cannot distinguish: Genes directly affected by berenil Genes directly affected by berenil Genes indirectly affected by the product of a directly affected gene Genes indirectly affected by the product of a directly affected gene Are the stress-related genes indirectly affected? Are the stress-related genes indirectly affected? Are their upstream sequences different from the rest of the affected genes? Are their upstream sequences different from the rest of the affected genes?

16 Difference Criterion - Direct

17 Ratio Criterion - Direct

18 Difference Criterion - Indirect

19 Ratio Criterion - Indirect

20 Features Found Upstream Directly Affected Genes Average of 92% A+T Average of 92% A+T 100% are at least 80% A+T 100% are at least 80% A+T Difference and ratio measures yield 75% shared sequences Difference and ratio measures yield 75% shared sequences 52% of dinucleotides are AT and TA, compared to 18% for all yeast genes 52% of dinucleotides are AT and TA, compared to 18% for all yeast genes Completely A/T heteropolymeric 5- and 6-mers occur at 4.4 times the expected rate Completely A/T heteropolymeric 5- and 6-mers occur at 4.4 times the expected rate The high rate of heteropolymeric tracts of 3-6 nt is statistically significant The high rate of heteropolymeric tracts of 3-6 nt is statistically significant

21 Chi-squared Analysis

22 Conclusions Microarray analysis yielded list of yeast genes affected by Berenil Microarray analysis yielded list of yeast genes affected by Berenil Gene functions suggested direct and indirect effects Gene functions suggested direct and indirect effects Direct category had expected sequence features Direct category had expected sequence features Indirect category did not display sequence features Indirect category did not display sequence features Results contribute to Results contribute to an understanding of in vivo sequence requirements for Berenil binding an understanding of in vivo sequence requirements for Berenil binding a new approach to analysis of microarray data sets a new approach to analysis of microarray data sets

23 References S. Neidle. Nat Prod Rep 18, 291 (2001) P.G. Baraldi et al., Med Res Rev 24, 475 (2004) L.J. Heyer et al., Bioinformatics. 21, 2114 (2005) A. Abu-Daya et al., Nucleic Acids Res 23, 3385 (1995) D.L. Boger et al., J Am Chem Soc 123, 5878 (2001) F. Rosu et al., Nucleic Acids Res. 30, e82 (2002) Acknowledgements Thanks to the Genome Consortium for Active Teaching (GCAT) and Dr. John N. Anderson (Purdue) for advice and discussions. This work was supported by the Missouri Western Summer Research Institute, and NIH AREA grant 1R15CA096723-01.


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