Yuan Guo-Cheng
Department of Biostatistics, Harvard School of Public Health, Cambridge, MA 02466, USA.
J Comput Biol. 2009 Feb;16(2):341-55. doi: 10.1089/cmb.2008.18TT.
Histone modifications are important epigenetic regulators and play a critical role in development. The targeting mechanism for histone modifications is complex and still incompletely understood. Here we applied a computational approach to predict genome-scale histone modification targets in humans by the genomic DNA sequences using a set of recent ChIP-seq data. We found that a number of histone modification marks could be predicted with high accuracy. On the other hand, the impact of DNA sequences for each mark is intrinsically different dependent upon the target- and tissue-specificity. Diverse patterns are associated with different repetitive elements. Unexpectedly, we found that non-overlapping, functionally opposite histone modification marks could share similar sequence features. We propose that these marks may target a common set of loci but are mutually exclusive and that the competition may be important for developmental control. Taken together, we show that our computational approach has provided new insights into the targeting mechanism of histone modifications.
组蛋白修饰是重要的表观遗传调控因子，在发育过程中发挥关键作用。组蛋白修饰的靶向机制复杂，目前仍未完全了解。在此，我们应用一种计算方法，利用一组最新的染色质免疫沉淀测序（ChIP-seq）数据，通过基因组DNA序列预测人类基因组规模的组蛋白修饰靶点。我们发现许多组蛋白修饰标记能够被高精度预测。另一方面，每个标记的DNA序列影响因靶点和组织特异性而本质上有所不同。不同的模式与不同的重复元件相关。出乎意料的是，我们发现非重叠、功能相反的组蛋白修饰标记可能共享相似的序列特征。我们提出，这些标记可能靶向一组共同的基因座，但相互排斥，这种竞争可能对发育控制很重要。综上所述，我们表明我们的计算方法为组蛋白修饰的靶向机制提供了新的见解。
