小柯机器人

动态整合多个计算功能注释可实现大规模全基因组测序研究中稀有变异（RVs）的关联分析，这一成果由哈佛大学陈曾熙公共卫生学院Pradeep Natarajan课题组经过不懈努力而取得。2020年8月24日出版的《自然-遗传学》杂志发表了这一研究成果。

研究人员设计了STAAR（使用注释信息进行关联的变量集测试），这是一种可扩展且功能强大的RV关联测试方法，可使用动态加权有效地合并变体类别和多个互补注释。对于后者，研究人员研发了“注释主要组件”，即计算机模拟变体注释的多维摘要。STAAR解决了人口结构和相关性问题，可扩展用于分析连续和二分性状的超大型队列和生物库全基因组测序研究。

研究人员利用STAAR在Trans-Omics for Precision Medicine计划包含的12,316个发现样本和17,822个复制样本中鉴别了与四个脂质性状相关的RV。研究发现并复制了新的RV关联，包括NPC1L1的破坏性错义RV和APOC1P1附近一个与低密度脂蛋白胆固醇相关的基因间区域。

据了解，大规模全基因组测序研究能够分析与复杂表型相关的稀有变异。常用的RV关联测试范围有限，无法利用各种功能。

附：英文原文

Title: Dynamic incorporation of multiple in silico functional annotations empowers rare variant association analysis of large whole-genome sequencing studies at scale

Author: Xihao Li, Zilin Li, Hufeng Zhou, Sheila M. Gaynor, Yaowu Liu, Han Chen, Ryan Sun, Rounak Dey, Donna K. Arnett, Stella Aslibekyan, Christie M. Ballantyne, Lawrence F. Bielak, John Blangero, Eric Boerwinkle, Donald W. Bowden, Jai G. Broome, Matthew P. Conomos, Adolfo Correa, L. Adrienne Cupples, Joanne E. Curran, Barry I. Freedman, Xiuqing Guo, George Hindy, Marguerite R. Irvin, Sharon L. R. Kardia, Sekar Kathiresan, Alyna T. Khan, Charles L. Kooperberg, Cathy C. Laurie, X. Shirley Liu, Michael C. Mahaney, Ani W. Manichaikul, Lisa W. Martin, Rasika A. Mathias, Stephen T. McGarvey, Braxton D. Mitchell, May E. Montasser, Jill E. Moore, Alanna C. Morrison, Jeffrey R. OConnell, Nicholette D. Palmer, Akhil Pampana, Juan M. Peralta, Patricia A. Peyser, Bruce M. Psaty, Susan Redline, Kenneth M. Rice, Stephen S. Rich, Jennifer A. Smith, Hemant K. Tiwari, Michael Y. Tsai, Ramachandran S. Vasan, Fei Fei Wang, Daniel E. Weeks, Zhiping Weng, James G. Wilson, Lisa R. Yanek, Benjamin M. Neale, Shamil R. Sunyaev, Gonalo R. Abecasis, Jerome I. Rotter, Cristen J. Willer, Gina M. Peloso, Pradeep Natarajan

Issue&Volume: 2020-08-24

Abstract: Large-scale whole-genome sequencing studies have enabled the analysis of rare variants (RVs) associated with complex phenotypes. Commonly used RV association tests have limited scope to leverage variant functions. We propose STAAR (variant-set test for association using annotation information), a scalable and powerful RV association test method that effectively incorporates both variant categories and multiple complementary annotations using a dynamic weighting scheme. For the latter, we introduce ‘annotation principal components’, multidimensional summaries of in silico variant annotations. STAAR accounts for population structure and relatedness and is scalable for analyzing very large cohort and biobank whole-genome sequencing studies of continuous and dichotomous traits. We applied STAAR to identify RVs associated with four lipid traits in 12,316 discovery and 17,822 replication samples from the Trans-Omics for Precision Medicine Program. We discovered and replicated new RV associations, including disruptive missense RVs of NPC1L1 and an intergenic region near APOC1P1 associated with low-density lipoprotein cholesterol.

DOI: 10.1038/s41588-020-0676-4

Source: https://www.nature.com/articles/s41588-020-0676-4

Nature Genetics：《自然—遗传学》，创刊于1992年。隶属于施普林格·自然出版集团，最新IF：41.307
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投稿链接：https://mts-ng.nature.com/cgi-bin/main.plex