Creating and validating cis-regulatory maps of tissue-specific gene expression regulation.
Creating and validating cis-regulatory maps of tissue-specific gene expression regulation.
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DOI：
10.1093/nar/gku801
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发表时间：
2014
影响因子：
14.9
通讯作者：
Bailey TL
中科院分区：
文献类型：
--
作者：
O'Connor TR;Bailey TL
预测哪些基因组区域控制给定基因的转录是一个挑战。我们提出了一种新颖的计算方法，用于创建和验证将基因组区域（顺式调控模块 - CRM）与基因相关联的图谱。该方法使用广泛可用的“其他”组织基因组数据来推断调节关系，解释在测试组织中观察到的基因表达。为了预测 CRM 的调控目标，我们使用 CRM 上存在的组蛋白修饰与其 1 Mbp 范围内的基因表达之间的跨组织相关性。为了验证顺式调控图谱，我们表明它们比精心构建的对照图谱产生更准确的基因表达模型。这些基因表达模型通过与该基因相连的 CRM 中的转录因子结合来预测观察到的基因表达。我们表明，我们的图谱能够识别远程调控相互作用，并且比基于控制图谱或“最近邻居”启发式的连接基因和 CRM 的图谱有了显着改进。我们的结果还表明，在图谱构建过程中包括在多个组织中预测的 CRM 至关重要，H3K27ac 是信息最丰富的组蛋白修饰，而 CAGE 是创建顺式调控图谱的基因表达信息最丰富的测量方法。
Predicting which genomic regions control the transcription of a given gene is a challenge. We present a novel computational approach for creating and validating maps that associate genomic regions (cis-regulatory modules–CRMs) with genes. The method infers regulatory relationships that explain gene expression observed in a test tissue using widely available genomic data for ‘other’ tissues. To predict the regulatory targets of a CRM, we use cross-tissue correlation between histone modifications present at the CRM and expression at genes within 1 Mbp of it. To validate cis-regulatory maps, we show that they yield more accurate models of gene expression than carefully constructed control maps. These gene expression models predict observed gene expression from transcription factor binding in the CRMs linked to that gene. We show that our maps are able to identify long-range regulatory interactions and improve substantially over maps linking genes and CRMs based on either the control maps or a ‘nearest neighbor’ heuristic. Our results also show that it is essential to include CRMs predicted in multiple tissues during map-building, that H3K27ac is the most informative histone modification, and that CAGE is the most informative measure of gene expression for creating cis-regulatory maps.
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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.
影响因子：
64.5
作者：
Hnisz D;Abraham BJ;Lee TI;Lau A;Saint-André V;Sigova AA;Hoke HA;Young RA
通讯作者：
Young RA
影响因子：
7
作者：
Kikuta, Hiroshi;Laplante, Mary;Becker, Thomas S.
通讯作者：
Becker, Thomas S.
影响因子：
7
作者：
Sinha, Saurabh;Adler, Adam S.;Segal, Eran
通讯作者：
Segal, Eran
影响因子：
64.5
作者：
Whyte WA;Orlando DA;Hnisz D;Abraham BJ;Lin CY;Kagey MH;Rahl PB;Lee TI;Young RA
通讯作者：
Young RA