Widespread site-dependent buffering of human regulatory polymorphism.
Widespread site-dependent buffering of human regulatory polymorphism.
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DOI：
10.1371/journal.pgen.1002599
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发表时间：
2012
期刊：
影响因子：
4.5
通讯作者：
Stamatoyannopoulos JA
中科院分区：
文献类型：
--
作者：
Maurano MT;Wang H;Kutyavin T;Stamatoyannopoulos JA
预计普通个体在参与基因调控的非编码基因组区域内含有数千种变异。然而，目前尚无法可靠地解读任何给定转录因子识别序列内遗传变异的功能影响。为解决这一问题，我们全面分析了一种主要的序列特异性调节因子（CTCF）在多代家系中结合位点序列遗传变异性相关的全基因组可遗传结合模式。我们通过染色质免疫沉淀测序（ChIP - seq）对跨越三代的12名有亲缘关系和无亲缘关系的个体进行CTCF结合定位和定量，随后对所有个体的整个CTCF结合区域进行全面的靶向重测序。我们鉴定出数百种对CTCF结合具有可重复定量影响（正向和负向）的变异。虽然这些影响在平均水平上与蛋白质 - DNA识别能量学相符，但它们受到显著的局部环境依赖性的广泛缓冲。在绝大多数情况下，缓冲是完全的，导致在DNA识别界面的每个位置都存在沉默变异，无论结合能水平或进化约束如何。复杂的部分或完全缓冲效应的普遍存在严重限制了可靠预测任何给定结合位点实例中变异影响的能力。令人惊讶的是，40%增加CTCF结合的变异发生在人与黑猩猩分化的位置，这对绝大多数功能性调控变异应该是有害的这一预期提出了挑战。我们的结果表明，即使在有多个相关个体的重测序和平行研究提供的“完美”遗传信息的情况下，对调控DNA中个体变异后果的基因组位点特异性预测也需要与经验性功能基因组测量系统地结合。
全面理解个体基因组序列对疾病和数量性状的贡献，需要具备预测非蛋白质编码区域（特别是参与基因调控的区域）遗传变异后果的一般能力。在这里，我们测试了在拥有“完整”信息（包括一个经过充分研究的调节蛋白在多个相关个体中的基因组DNA结合位点模式，以及结合位置的所有个体基因组序列）的情况下预测此类后果的能力。我们发现，虽然有合理的能力预测转录调节因子共有识别序列内变异的平均影响，但无法可靠地确定任何给定基因组实例中变异的后果。这表明对个体基因组序列的解读将需要与功能基因组研究全面互补。
The average individual is expected to harbor thousands of variants within non-coding genomic regions involved in gene regulation. However, it is currently not possible to interpret reliably the functional consequences of genetic variation within any given transcription factor recognition sequence. To address this, we comprehensively analyzed heritable genome-wide binding patterns of a major sequence-specific regulator (CTCF) in relation to genetic variability in binding site sequences across a multi-generational pedigree. We localized and quantified CTCF occupancy by ChIP-seq in 12 related and unrelated individuals spanning three generations, followed by comprehensive targeted resequencing of the entire CTCF–binding landscape across all individuals. We identified hundreds of variants with reproducible quantitative effects on CTCF occupancy (both positive and negative). While these effects paralleled protein–DNA recognition energetics when averaged, they were extensively buffered by striking local context dependencies. In the significant majority of cases buffering was complete, resulting in silent variants spanning every position within the DNA recognition interface irrespective of level of binding energy or evolutionary constraint. The prevalence of complex partial or complete buffering effects severely constrained the ability to predict reliably the impact of variation within any given binding site instance. Surprisingly, 40% of variants that increased CTCF occupancy occurred at positions of human–chimp divergence, challenging the expectation that the vast majority of functional regulatory variants should be deleterious. Our results suggest that, even in the presence of “perfect” genetic information afforded by resequencing and parallel studies in multiple related individuals, genomic site-specific prediction of the consequences of individual variation in regulatory DNA will require systematic coupling with empirical functional genomic measurements. A comprehensive understanding of the contribution of individual genome sequences to disease and quantitative traits will require the general ability to predict consequences of genetic variation in non-protein-coding regions, particularly those involved in gene regulation. Here we tested the power to predict such consequences when presented with “complete” information encompassing the genomic DNA binding site patterns of a well-studied regulatory protein across multiple related individuals, coupled with all individual genome sequences at the binding positions. We find that, while there is reasonable ability to predict the average effects of variation within the consensus recognition sequence of a transcriptional regulator, it is not possible to determine reliably the consequences of variation at any given genomic instance. This suggests that the interpretation of individual genome sequences will require comprehensive complementation with functional genomic studies.
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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
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
影响因子：
9.8
作者：
Eddy, SR
通讯作者：
Eddy, SR
影响因子：
30.8
作者：
John S;Sabo PJ;Thurman RE;Sung MH;Biddie SC;Johnson TA;Hager GL;Stamatoyannopoulos JA
通讯作者：
Stamatoyannopoulos JA
影响因子：
64.8
作者：
Kellis, M;Patterson, N;Lander, ES
通讯作者：
Lander, ES