Stefan Bekiranov

Genomic Maps and Comparative Analysis of Histone Modifications in Human and Mouse

We mapped histone H3 lysine 4 di- and trimethylation and lysine 9/14 acetylation across the nonrepetitive portions of human chromosomes 21 and 22 and compared patterns of lysine 4 dimethylation for several orthologous human and mouse loci. Both chromosomes show punctate sites enriched for modified histones. Sites showing trimethylation correlate with transcription starts, while those showing mainly dimethylation occur elsewhere in the vicinity of active genes. Punctate methylation patterns are also evident at the cytokine and IL-4 receptor loci. The Hox clusters present a strikingly different picture, with broad lysine 4-methylated regions that overlay multiple active genes. We suggest these regions represent active chromatin domains required for the maintenance of Hox gene expression. Methylation patterns at orthologous loci are strongly conserved between human and mouse even though many methylated sites do not show sequence conservation notably higher than background. This suggests that the DNA elements that direct the methylation represent only a small fraction of the region or lie at some distance from the site.

Probe selection for high-density oligonucleotide arrays

High-density oligonucleotide microarrays enable simultaneous monitoring of expression levels of tens of thousands of transcripts. For accurate detection and quantitation of transcripts in the presence of cellular mRNA, it is essential to design microarrays whose oligonucleotide probes produce hybridization intensities that accurately reflect the concentration of original mRNA. We present a model-based approach that predicts optimal probes by using sequence and empirical information. We constructed a thermodynamic model for hybridization behavior and determined the influence of empirical factors on the effective fitting parameters. We designed Affymetrix GeneChip probe arrays that contained all 25-mer probes for hundreds of human and yeast transcripts and collected data over a 4,000-fold concentration range. Multiple linear regression models were built to predict hybridization intensities of each probe at given target concentrations, and each intensity profile is summarized by a probe response metric. We selected probe sets to represent each transcript that were optimized with respect to responsiveness, independence (degree to which probe sequences are nonoverlapping), and uniqueness (lack of similarity to sequences in the expressed genomic background). We show that this approach is capable of selecting probes with high sensitivity and specificity for high-density oligonucleotide arrays.