Inferring regulatory element landscapes and transcription factor networks from cancer methylomes.
Inferring regulatory element landscapes and transcription factor networks from cancer methylomes.
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DOI：
10.1186/s13059-015-0668-3
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发表时间：
2015-05-21
期刊：
影响因子：
12.3
通讯作者：
Berman BP
中科院分区：
文献类型：
--
作者：
Yao L;Shen H;Laird PW;Farnham PJ;Berman BP
Recent studies indicate that DNA methylation can be used to identify transcriptional enhancers, but no systematic approach has been developed for genome-wide identification and analysis of enhancers based on DNA methylation. We describe ELMER (Enhancer Linking by Methylation/Expression Relationships), an R-based tool that uses DNA methylation to identify enhancers and correlates enhancer state with expression of nearby genes to identify transcriptional targets.增强子的转录因子基序分析与转录因子的表达分析相结合，以推断上游调节因子。我们使用 ELMER 研究了来自癌症基因组图谱的 2,000 多个肿瘤样本。 We identified networks regulated by known cancer drivers such as GATA3 and FOXA1 (breast cancer), SOX17 and FOXA2 (endometrial cancer), and NFE2L2, SOX2, and TP63 (squamous cell lung cancer).我们还发现了与预后相关的新网络，包括肾癌中的 RUNX1。 We propose ELMER as a powerful new paradigm for understanding the cis-regulatory interface between cancer-associated transcription factors and their functional target genes.本文的在线版本 (doi:10.1186/s13059-015-0668-3) 包含补充材料，可供授权用户使用。
Recent studies indicate that DNA methylation can be used to identify transcriptional enhancers, but no systematic approach has been developed for genome-wide identification and analysis of enhancers based on DNA methylation. We describe ELMER (Enhancer Linking by Methylation/Expression Relationships), an R-based tool that uses DNA methylation to identify enhancers and correlates enhancer state with expression of nearby genes to identify transcriptional targets. Transcription factor motif analysis of enhancers is coupled with expression analysis of transcription factors to infer upstream regulators. Using ELMER, we investigated more than 2,000 tumor samples from The Cancer Genome Atlas. We identified networks regulated by known cancer drivers such as GATA3 and FOXA1 (breast cancer), SOX17 and FOXA2 (endometrial cancer), and NFE2L2, SOX2, and TP63 (squamous cell lung cancer). We also identified novel networks with prognostic associations, including RUNX1 in kidney cancer. We propose ELMER as a powerful new paradigm for understanding the cis-regulatory interface between cancer-associated transcription factors and their functional target genes. The online version of this article (doi:10.1186/s13059-015-0668-3) contains supplementary material, which is available to authorized users.
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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：
10.1093/bioinformatics/btr064
发表时间：
2011-04-01
期刊：
Bioinformatics (Oxford, England)
影响因子：
--
作者：
Grant CE;Bailey TL;Noble WS
通讯作者：
Noble WS
影响因子：
5.6
作者：
Chou, Jonathan;Provot, Sylvain;Werb, Zena
通讯作者：
Werb, Zena
影响因子：
30.8
作者：
通讯作者：
--
影响因子：
16
作者：
Fujiwara T;O'Geen H;Keles S;Blahnik K;Linnemann AK;Kang YA;Choi K;Farnham PJ;Bresnick EH
通讯作者：
Bresnick EH