Identification of Human Lineage-Specific Transcriptional Coregulators Enabled by a Glossary of Binding Modules and Tunable Genomic Backgrounds.
Identification of Human Lineage-Specific Transcriptional Coregulators Enabled by a Glossary of Binding Modules and Tunable Genomic Backgrounds.
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DOI：
10.1016/j.cels.2017.06.015
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发表时间：
2017-09-27
期刊：
影响因子：
9.3
通讯作者：
Bulyk ML
中科院分区：
文献类型：
--
作者：
Mariani L;Weinand K;Vedenko A;Barrera LA;Bulyk ML
转录因子通过结合特定的DNA基序来调节基因的表达，从而控制细胞的过程。基序富集区分析可以确定直接和间接的TF结合位点。在这里，我们从公开可用的和新的通用蛋白质结合微阵列(PBM)数据中为671个后生动物TF创建了108个非冗余的TF-8mer“模块”的词汇表，这些模块具有共同的特异性。对239个ENCODE TF CHIP-SEQ数据集和相关的RNA-SEQ图谱的分析表明，8mer模块在识别间接结合基序及其相关的系链TF方面比位置权重矩阵(PWMS)更准确。我们还开发了Genre(基因组等价负区)，这是一种可调的工具，用于构建匹配的基因组背景序列，用于分析调节区。流派的表现超过了四种最先进的背景序列构建方法。我们使用我们的TF-8mer词汇表和体裁来分析锚定因子的间接结合基序，提出了新的TF-TF相互作用。我们预计这些工具将有助于阐明组织特异性基因调控程序。
Transcription factors (TFs) control cellular processes by binding specific DNA motifs to modulate gene expression. Motif enrichment analysis of regulatory regions can identify direct and indirect TF binding sites. Here, we created a glossary of 108 non-redundant TF-8mer “modules” of shared specificity for 671 metazoan TFs from publicly available and new universal Protein Binding Microarray (PBM) data. Analysis of 239 ENCODE TF ChIP-seq datasets and associated RNA-seq profiles suggest the 8mer modules are more precise than position weight matrices (PWMs) in identifying indirect binding motifs and their associated tethering TFs. We also developed GENRE (Genomically Equivalent Negative REgions), a tunable tool for construction of matched genomic background sequences for analysis of regulatory regions. GENRE outperformed four state-of-the-art approaches to background sequence construction. We used our TF-8mer glossary and GENRE in the analysis of the indirect binding motifs for the co-occurrence of tethering factors, suggesting novel TF-TF interactions. We anticipate that these tools will aid in elucidating tissue-specific gene regulatory programs.
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DOI：
10.1126/science.1162327
发表时间：
2009-06-26
期刊：
Science (New York, N.Y.)
影响因子：
--
作者：
Badis G;Berger MF;Philippakis AA;Talukder S;Gehrke AR;Jaeger SA;Chan ET;Metzler G;Vedenko A;Chen X;Kuznetsov H;Wang CF;Coburn D;Newburger DE;Morris Q;Hughes TR;Bulyk ML
通讯作者：
Bulyk ML
影响因子：
14.8
作者：
Berger, Michael F.;Bulyk, Martha L.
通讯作者：
Bulyk, Martha L.
影响因子：
14.9
作者：
Bresnick EH;Katsumura KR;Lee HY;Johnson KD;Perkins AS
通讯作者：
Perkins AS
影响因子：
14.9
作者：
Bhasin, Jeffrey M.;Ting, Angela H.
通讯作者：
Ting, Angela H.
影响因子：
46.9
作者：
Berger, Michael F.;Philippakis, Anthony A.;Bulyk, Martha L.
通讯作者：
Bulyk, Martha L.