Quantitative integration of epigenomic variation and transcription factor binding using MAmotif toolkit identifies an important role of IRF2 as transcription activator at gene promoters.
Quantitative integration of epigenomic variation and transcription factor binding using MAmotif toolkit identifies an important role of IRF2 as transcription activator at gene promoters.
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使用 MAmotif 工具包对表观基因组变异和转录因子结合进行定量整合，确定了 IRF2 作为基因启动子转录激活剂的重要作用
DOI：
10.1038/s41421-018-0045-y
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发表时间：
2018
期刊：
影响因子：
33.5
通讯作者：
Shao Z
中科院分区：
文献类型：
--
作者：
Sun H;Wang J;Gong Z;Yao J;Wang Y;Xu J;Yuan GC;Zhang Y;Shao Z
Dear Editor, Eukaryotic gene transcription is controlled by a large cohort of chromatin-associated proteins including transcription factors (TFs) and epigenetic regulators 1, 2. ChIP-seq experiments are now widely used to characterize the genome-wide binding of these proteins, and comparing ChIP-seq data from different cell types can provide valuable insight into understanding how cell type-specific transcriptional programs are established 3. Specifically, epigenetic regulators often show dynamic chromatin binding during development and disease progressions 2. However, most of them are broadly expressed across tissues, and their chromatin binding is thought to be mainly modulated by crosstalk with TFs, which could be considered as their cell type-specific co-factors 4. Thus, identifying TFs that preferentially bind at the genomic regions differentially bound by a chromatin-associated protein between different cell types has become an important step toward deciphering the molecular mechanism modulating its chromatin binding 4. Moreover, applying this analysis to histone modifications marking active regulatory elements such as H3K4me1-3 and H3K27ac is frequently used for discovering cell type-specific regulators 5. A traditional way of this analysis is to first detect the cell type-specific ChIP-seq peaks of the protein of interest, which are typically defined as those that do not overlap with peaks identified from other cell types, and then search for TFs whose binding sites are significantly overrepresented in these peaks 6. But, the cell type-specific peaks defined in this way often suffer from high falsepositive rates, which can severely affect the accuracy of downstream analysis 6, 7. Recently, it has been demonstrated that quantitative comparison of ChIP-seq data using MAnorm or other statistical models can more precisely characterize the differential binding of proteins than arbitrarily classifying their peaks into cell typespecific and non-specific ones based on peak overlap, and thus can provide a better basis for the following analysis 6–8. This is particularly important for identifying the cell type-specific co-factors of the protein under study, which highly relies on both the sensitivity and specificity of the detection of differential binding 6. Therefore, developing computational tools that systematically incorporate quantitative comparison of ChIP-seq data based on appropriate statistical models into the identification of cell-type specific regulators can effectively facilitate the application of these models. Here, we present a practical toolkit, MAmotif, for this purpose. It can automatically perform quantitative comparison between ChIP-seq samples of the same protein© The Author (s) 2018
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影响因子：
64.8
作者：
Ernst, Jason;Kheradpour, Pouya;Mikkelsen, Tarjei S.;Shoresh, Noam;Ward, Lucas D.;Epstein, Charles B.;Zhang, Xiaolan;Wang, Li;Issner, Robbyn;Coyne, Michael;Ku, Manching;Durham, Timothy;Kellis, Manolis;Bernstein, Bradley E.
通讯作者：
Bernstein, Bradley E.
DOI：
10.1038/nrm3949
发表时间：
2015-03
期刊：
Nature reviews. Molecular cell biology
影响因子：
--
作者：
Heinz S;Romanoski CE;Benner C;Glass CK
通讯作者：
Glass CK
影响因子：
4.3
作者：
Bailey T;Krajewski P;Ladunga I;Lefebvre C;Li Q;Liu T;Madrigal P;Taslim C;Zhang J
通讯作者：
Zhang J
影响因子：
9.5
作者：
Steinhauser S;Kurzawa N;Eils R;Herrmann C
通讯作者：
Herrmann C
影响因子：
11.8
作者：
Xu, Jian;Shao, Zhen;Glass, Kimberly;Bauer, Daniel E.;Pinello, Luca;Van Handel, Ben;Hou, Serena;Stamatoyannopoulos, John A.;Mikkola, Hanna K. A.;Yuan, Guo-Cheng;Orkin, Stuart H.
通讯作者：
Orkin, Stuart H.