Tuyển tập các báo cáo nghiên cứu về y học được đăng trên tạp chí y học Wertheim cung cấp cho các bạn kiến thức về ngành y đề tài: A statistical framework for modeling gene expression using chromatin features and application to modENCODE datasets. | Cheng et al. Genome Biology 2011 12 R15 http 2011 12 2 R15 Genome Biology METHOD Open Access A statistical framework for modeling gene expression using chromatin features and application to modENCODE datasets 1 1 I X X - 1 1 1 Chao Cheng Koon-Kiu Yan Kevin Y Yip Joel Rozowsky Roger Alexander Chong Shou and Mark Gerstein Abstract We develop a statistical framework to study the relationship between chromatin features and gene expression. This can be used to predict gene expression of protein coding genes as well as microRNAs. We demonstrate the prediction in a variety of contexts focusing particularly on the modENCODE worm datasets. Moreover our framework reveals the positional contribution around genes upstream or downstream of distinct chromatin features to the overall prediction of expression levels. Background In eukaryotes nuclear chromosomes are organized into chains of nucleosomes which are in turn composed of octamers of four types of histones wrapped around 147 bp of DNA. Modifications of these core histones are central to many biological processes including transcriptional regulation 1 replication 2 alternative splicing 3 DNA repair 4 apoptosis 5 6 gene silencing 7 X-chromosome inactivation 8 and carcinogenesis 9 10 . Among them transcriptional regulation is one of the most important and thereby intensively investigated processes 1 11 12 . Histone modifications have been demonstrated to regulate gene transcription in positive or negative manners depending on the modification site and type 13-18 . For example a genome-wide map of 18 histone acetylation and 19 histone methylation sites in human T cells indic ates that H3K9me2 H3K9me3 H3K27me2 H3K27me3 and H4K20me3 are negatively correlated with gene expression whereas most other modifications including all the acetylations are correlated with gene activation 18 19 . As an extreme case histone modifications play critical roles in X-chromo-some inactivation in females to equalize the
