Discovery of rare variants for complex phenotypes.
Discovery of rare variants for complex phenotypes.
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DOI：
10.1007/s00439-016-1679-1
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发表时间：
2016-06
期刊：
影响因子：
5.3
通讯作者：
Neale BM
中科院分区：
文献类型：
--
作者：
Kosmicki JA;Churchhouse CL;Rivas MA;Neale BM
随着测序技术的兴起，现在可以评估罕见变异在复杂性状变异的遗传贡献中所起的作用。虽然一些早期的靶向测序研究成功地识别了具有大效应的罕见变异，但使用外显子组测序进行无偏见基因发现对于复杂性状的成功有限。尽管如此，罕见变异关联研究（RVAS）已经证明，罕见变异确实会导致表型变异，但样本量可能必须比常见变异关联研究（CVAS）更大，才能为基因和基因座的检测提供动力。数以万计的个体的大规模测序工作（例如 UK10K 项目）和聚合工作（例如外显子组聚合联盟）在增进我们对稀有变异景观的认识方面取得了巨大进步，但在复杂性状背景下研究稀有变异时，仍然存在许多考虑因素。我们在这篇综述中讨论了这些考虑因素，在高层次上提出了广泛的主题，作为对复杂性状的罕见变异分析的介绍，包括功效问题、研究设计、样本确定、从头变异和统计测试方法。最终，随着测序成本持续下降，更大规模的测序研究将对罕见突变的生物学后果产生更清晰的见解，并可能揭示哪些基因在复杂性状的病因学中发挥作用。
With the rise of sequencing technologies, it is now feasible to assess the role rare variants play in the genetic contribution to complex trait variation. While some of the earlier targeted sequencing studies successfully identified rare variants of large effect, unbiased gene discovery using exome sequencing has experienced limited success for complex traits. Nevertheless, rare variant association studies (RVAS) have demonstrated that rare variants do contribute to phenotypic variability, but sample sizes will likely have to be even larger than those of common variant association studies (CVAS) to be powered for the detection of genes and loci. Large-scale sequencing efforts of tens of thousands of individuals, such as the UK10K Project and aggregation efforts such as the Exome Aggregation Consortium, have made great strides in advancing our knowledge of the landscape of rare variation, but there remain many considerations when studying rare variation in the context of complex traits. We discuss these considerations in this review, presenting a broad range of topics at a high-level as an introduction to rare variant analysis in complex traits including the issues of power, study design, sample ascertainment, de novo variation, and statistical testing approaches. Ultimately, as sequencing costs continue to decline, larger sequencing studies will yield clearer insights into the biological consequence of rare mutations and may reveal which genes play a role in the etiology of complex traits.
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影响因子：
2.4
作者：
Elansary, Mahmoud;Stinckens, Anneleen;Georges, Michel
通讯作者：
Georges, Michel
影响因子：
30.8
作者：
Flannick, Jason;Thorleifsson, Gudmar;Beer, Nicola L.;Jacobs, Suzanne B. R.;Grarup, Niels;Burtt, Noel P.;Mahajan, Anubha;Fuchsberger, Christian;Atzmon, Gil;Benediktsson, Rafn;Blangero, John;Bowden, Don W.;Brandslund, Ivan;Brosnan, Julia;Burslem, Frank;Chambers, John;Cho, Yoon Shin;Christensen, Cramer;Douglas, Desiree A.;Duggirala, Ravindranath;Dymek, Zachary;Farjoun, Yossi;Fennell, Timothy;Fontanillas, Pierre;Forsen, Tom;Gabriel, Stacey;Glaser, Benjamin;Gudbjartsson, Daniel F.;Hanis, Craig;Hansen, Torben;Hreidarsson, Astradur B.;Hveem, Kristian;Ingelsson, Erik;Isomaa, Bo;Johansson, Stefan;Jorgensen, Torben;Jorgensen, Marit Eika;Kathiresan, Sekar;Kong, Augustine;Kooner, Jaspal;Kravic, Jasmina;Laakso, Markku;Lee, Jong-Young;Lind, Lars;Lindgren, Cecilia M.;Linneberg, Allan;Masson, Gisli;Meitinger, Thomas;Mohlke, Karen L.;Molven, Anders;Morris, Andrew P.;Potluri, Shobha;Rauramaa, Rainer;Ribel-Madsen, Rasmus;Richard, Ann-Marie;Rolph, Tim;Salomaa, Veikko;Segre, Ayellet V.;Skaerstrand, Hanna;Steinthorsdottir, Valgerdur;Stringham, Heather M.;Sulem, Patrick;Tai, E. Shyong;Teo, Yik Ying;Teslovich, Tanya;Thorsteinsdottir, Unnur;Trimmer, Jeff K.;Tuomi, Tiinamaija;Tuomilehto, Jaakko;Vaziri-Sani, Fariba;Voight, Benjamin F.;Wilson, James G.;Boehnke, Michael;McCarthy, Mark I.;Njolstad, Pal R.;Pedersen, Oluf;Groop, Leif;Cox, David R.;Stefansson, Kari;Altshuler, David
通讯作者：
Altshuler, David
影响因子：
4
作者：
Ellegren, H;Smith, NGC;Webster, MT
通讯作者：
Webster, MT
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7
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Hardison, RC;Roskin, KM;Haussler, D
通讯作者：
Haussler, D
影响因子：
64.8
作者：
COULONDRE, C;MILLER, JH;GILBERT, W
通讯作者：
GILBERT, W