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本文引用的文献

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Nucleosome-mediated cooperativity between transcription factors.核小体介导的转录因子之间的协同作用。
Proc Natl Acad Sci U S A. 2010 Dec 28;107(52):22534-9. doi: 10.1073/pnas.0913805107. Epub 2010 Dec 13.
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Independent component analysis: mining microarray data for fundamental human gene expression modules.独立成分分析:从微阵列数据中挖掘基本的人类基因表达模块。
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ChIP-Seq: a method for global identification of regulatory elements in the genome.染色质免疫沉淀测序(ChIP-Seq):一种用于全基因组范围内鉴定调控元件的方法。
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Identifying components of protein complexes in C. elegans using co-immunoprecipitation and mass spectrometry.使用免疫共沉淀和质谱技术鉴定秀丽隐杆线虫中的蛋白质复合物组分。
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GREAT improves functional interpretation of cis-regulatory regions.GREAT 提高了顺式调控区域的功能解释。
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Variation in transcription factor binding among humans.人类转录因子结合的变异性。
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Genetic analysis of variation in transcription factor binding in yeast.酵母中转录因子结合变化的遗传分析。
Nature. 2010 Apr 22;464(7292):1187-91. doi: 10.1038/nature08934. Epub 2010 Mar 17.
8
An atlas of combinatorial transcriptional regulation in mouse and man.《小鼠和人类组合转录调控图谱》
Cell. 2010 Mar 5;140(5):744-52. doi: 10.1016/j.cell.2010.01.044.
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Combinatorial binding predicts spatio-temporal cis-regulatory activity.组合结合预测时空顺式调控活性。
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10
Developmental roles of 21 Drosophila transcription factors are determined by quantitative differences in binding to an overlapping set of thousands of genomic regions.21 种果蝇转录因子的发育作用是由其与数千个重叠基因组区域的结合的定量差异决定的。
Genome Biol. 2009;10(7):R80. doi: 10.1186/gb-2009-10-7-r80. Epub 2009 Jul 23.

利用调控变异发现协同转录因子关联。

Cooperative transcription factor associations discovered using regulatory variation.

机构信息

Department of Genetics, Stanford University School of Medicine, Stanford, CA 94305, USA.

出版信息

Proc Natl Acad Sci U S A. 2011 Aug 9;108(32):13353-8. doi: 10.1073/pnas.1103105108. Epub 2011 Jul 26.

DOI:10.1073/pnas.1103105108
PMID:21828005
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC3156166/
Abstract

Regulation of gene expression at the transcriptional level is achieved by complex interactions of transcription factors operating at their target genes. Dissecting the specific combination of factors that bind each target is a significant challenge. Here, we describe in detail the Allele Binding Cooperativity test, which uses variation in transcription factor binding among individuals to discover combinations of factors and their targets. We developed the ALPHABIT (a large-scale process to hunt for allele binding interacting transcription factors) pipeline, which includes statistical analysis of binding sites followed by experimental validation, and demonstrate that this method predicts transcription factors that associate with NFκB. Our method successfully identifies factors that have been known to work with NFκB (E2A, STAT1, IRF2), but whose global coassociation and sites of cooperative action were not known. In addition, we identify a unique coassociation (EBF1) that had not been reported previously. We present a general approach for discovering combinatorial models of regulation and advance our understanding of the genetic basis of variation in transcription factor binding.

摘要

转录水平的基因表达调控是通过在靶基因上发挥作用的转录因子的复杂相互作用来实现的。解析与每个靶标结合的特定因子组合是一项重大挑战。在这里,我们详细描述了等位基因结合协同性测试,该测试利用个体之间转录因子结合的变化来发现因子及其靶标的组合。我们开发了 ALPHABIT(大规模搜索等位基因结合相互作用转录因子的过程)管道,该管道包括结合位点的统计分析,随后进行实验验证,并证明该方法可预测与 NFκB 相关的转录因子。我们的方法成功地鉴定了已知与 NFκB (E2A、STAT1、IRF2)一起工作的因子,但它们的全局共关联和协同作用的位点尚不清楚。此外,我们还鉴定了一个以前没有报道过的独特共关联(EBF1)。我们提出了一种发现调控组合模型的通用方法,推进了我们对转录因子结合变异的遗传基础的理解。