The genetic and mechanistic basis for variation in gene regulation.
The genetic and mechanistic basis for variation in gene regulation.
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DOI：
10.1371/journal.pgen.1004857
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发表时间：
2015-01
期刊：
影响因子：
4.5
通讯作者：
Gilad Y
中科院分区：
文献类型：
--
作者：
Pai AA;Pritchard JK;Gilad Y
现在已经确定，非编码调节变体在常见疾病的遗传学和进化中起着核心作用。然而，直到最近，我们对大多数调节变体的作用机制知之甚少。例如，DNA、RNA或蛋白质中哪些类型的功能元件最常受到调控变体的影响？基因调控的哪些阶段通常会发生改变？我们如何预测哪些变体最有可能影响给定细胞类型的调节？最近的研究，在许多情况下，使用数量性状基因座（QTL）定位方法在细胞系或组织样本，为我们提供了相当深入的了解具有调节作用的遗传基因座的属性。这些研究发现了新的生化调节相互作用，并导致以前未被识别的调节机制的鉴定。我们已经了解到，遗传变异通常与调控活动的变异直接相关（即，我们可以定位调控QTL，而不仅仅是表达QTL [eQTL]），我们已经迈出了理解调控事件因果顺序的第一步（例如，先驱转录因子的作用）。然而，在大多数情况下，我们仍然不知道如何解释重叠的调控相互作用的组合，我们仍然远远不能预测调控机制的变化是如何通过一系列的相互作用传播，最终导致基因表达谱的变化。
It is now well established that noncoding regulatory variants play a central role in the genetics of common diseases and in evolution. However, until recently, we have known little about the mechanisms by which most regulatory variants act. For instance, what types of functional elements in DNA, RNA, or proteins are most often affected by regulatory variants? Which stages of gene regulation are typically altered? How can we predict which variants are most likely to impact regulation in a given cell type? Recent studies, in many cases using quantitative trait loci (QTL)-mapping approaches in cell lines or tissue samples, have provided us with considerable insight into the properties of genetic loci that have regulatory roles. Such studies have uncovered novel biochemical regulatory interactions and led to the identification of previously unrecognized regulatory mechanisms. We have learned that genetic variation is often directly associated with variation in regulatory activities (namely, we can map regulatory QTLs, not just expression QTLs [eQTLs]), and we have taken the first steps towards understanding the causal order of regulatory events (for example, the role of pioneer transcription factors). Yet, in most cases, we still do not know how to interpret overlapping combinations of regulatory interactions, and we are still far from being able to predict how variation in regulatory mechanisms is propagated through a chain of interactions to eventually result in changes in gene expression profiles.
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影响因子：
64.8
作者：
通讯作者：
--
影响因子：
4.5
作者：
Cusanovich DA;Pavlovic B;Pritchard JK;Gilad Y
通讯作者：
Gilad Y
DOI：
10.1126/science.1183621
发表时间：
2010-04-09
期刊：
Science (New York, N.Y.)
影响因子：
--
作者：
Kasowski M;Grubert F;Heffelfinger C;Hariharan M;Asabere A;Waszak SM;Habegger L;Rozowsky J;Shi M;Urban AE;Hong MY;Karczewski KJ;Huber W;Weissman SM;Gerstein MB;Korbel JO;Snyder M
通讯作者：
Snyder M
DOI：
10.1126/science.1242379
发表时间：
2013-11-29
期刊：
Science (New York, N.Y.)
影响因子：
--
作者：
Khan Z;Ford MJ;Cusanovich DA;Mitrano A;Pritchard JK;Gilad Y
通讯作者：
Gilad Y
影响因子：
7
作者：
Battle A;Mostafavi S;Zhu X;Potash JB;Weissman MM;McCormick C;Haudenschild CD;Beckman KB;Shi J;Mei R;Urban AE;Montgomery SB;Levinson DF;Koller D
通讯作者：
Koller D