Quantitatively assessing the effects of regulatory factors on nucleosome dynamics by multiple kernel learning
Nucleosome, a nucleoprotein structure formed by coiling 147bp of DNA around an octamer of histone proteins, is the fundamental repeating unit of eukaryotic chromatin. By regulating the access of biological machineries to underlying cis-regulatory elements, its mobility has been implicated in many important cellular processes. Although it has been known that various factors, such as DNA sequences, histone modifications, etc., cooperatively affect nucleosome mobility, the contribution of each factor in the common impact remains unclear. We propose, in this work, a novel computational approach based on multiple kernel learning for quantitatively assessing the effects of two important factors, i.e., genomic sequence and post-translational histone modifications (PTMs), on nucleosome dynamics. Our result on Saccharomyces cerevisiae shows that, epigenetic feature, such as histone modifications, plays more important role than genomic sequence in regulating nucleosome dynamics. Based on that, we carried further analysis on each PTM to reveal their combinatory effects on nucleosome dynamics and found out that some pairs of PTMs such as H3K9AcH4H14Ac, H4K5AcH4K12Ac and H4K5AcH3K14Ac might co-operate in altering nucleosome stability in gene regulation.
nucleosome dynamics multiple kernel learning genomic sequence post-translational histone modification