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Using Microarrays to Measure Sequence Preferences of Berenil Binding to the DNA Minor Groove

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

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Using Microarrays to Measure Sequence Preferences of Berenil Binding to the DNA Minor Groove

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  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 • Biological Activity • Berenil

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

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

  5. Indirect Labeling – 3DNA • Includes Two Hybridizations • Reverse Transcription occurs without labeling • 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 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 Phosphate metabolism, rRNA processing

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

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

  15. Direct versus Indirect Effects • Upstream sequences of 54 affected genes were A+T rich, heteropolymeric • But, the method cannot distinguish: • Genes directly affected by berenil • Genes indirectly affected by the product of a directly affected gene • Are the stress-related genes indirectly affected? • 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 • 100% are at least 80% A+T • Difference and ratio measures yield 75% shared sequences • 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 • 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 • Gene functions suggested direct and indirect effects • Direct category had expected sequence features • Indirect category did not display sequence features • Results contribute to • an understanding of in vivo sequence requirements for Berenil binding • a new approach to analysis of microarray data sets

  23. References S. Neidle. Nat Prod Rep18, 291 (2001) P.G. Baraldi et al., Med Res Rev24, 475 (2004) L.J. Heyer et al., Bioinformatics. 21, 2114 (2005) A. Abu-Daya et al., Nucleic Acids Res23, 3385 (1995) D.L. Boger et al., J Am Chem Soc123, 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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