Whole-genome sequencing analysis identifies rare, large-effect noncoding variants and regulatory regions associated with circulating protein levels

IF 31.7 1区 生物学 Q1 GENETICS & HEREDITY
Gareth Hawkes, Kartik Chundru, Leigh Jackson, Kashyap A. Patel, Anna Murray, Andrew R. Wood, Caroline F. Wright, Michael N. Weedon, Timothy M. Frayling, Robin N. Beaumont
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Abstract

The contribution of rare noncoding genetic variation to common phenotypes is largely unknown, as a result of a historical lack of population-scale whole-genome sequencing data and the difficulty of categorizing noncoding variants into functionally similar groups. To begin addressing these challenges, we performed a cis association analysis using whole-genome sequencing data, consisting of 1.1 billion variants, 123 million noncoding aggregate-based tests and 2,907 circulating protein levels in ~50,000 UK Biobank participants. We identified 604 independent rare noncoding single-variant associations with circulating protein levels. Unlike protein-coding variation, rare noncoding genetic variation was almost as likely to increase or decrease protein levels. Rare noncoding aggregate testing identified 357 conditionally independent associated regions. Of these, 74 (21%) were not detectable by single-variant testing alone. Our findings have important implications for the identification, and role, of rare noncoding genetic variation associated with common human phenotypes, including the importance of testing aggregates of noncoding variants.

Abstract Image

由于历来缺乏人群规模的全基因组测序数据,而且很难将非编码变异归类到功能相似的群体中,因此罕见的非编码基因变异对常见表型的贡献在很大程度上是未知的。为了着手解决这些难题,我们利用全基因组测序数据进行了顺式关联分析,这些数据包括约 5 万名英国生物库参与者的 11 亿个变异、1.23 亿个基于聚合体的非编码检测和 2907 个循环蛋白水平。我们发现了 604 个独立的罕见非编码单变异与循环蛋白水平的关联。与蛋白质编码变异不同,罕见非编码基因变异几乎同样可能增加或减少蛋白质水平。稀有非编码集合测试确定了 357 个条件独立的相关区域。其中有 74 个(21%)是单个变异检测无法检测到的。我们的研究结果对识别与人类常见表型相关的罕见非编码基因变异及其作用具有重要意义,包括检测非编码变异聚合体的重要性。
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来源期刊
Nature genetics
Nature genetics 生物-遗传学
CiteScore
43.00
自引率
2.60%
发文量
241
审稿时长
3 months
期刊介绍: Nature Genetics publishes the very highest quality research in genetics. It encompasses genetic and functional genomic studies on human and plant traits and on other model organisms. Current emphasis is on the genetic basis for common and complex diseases and on the functional mechanism, architecture and evolution of gene networks, studied by experimental perturbation. Integrative genetic topics comprise, but are not limited to: -Genes in the pathology of human disease -Molecular analysis of simple and complex genetic traits -Cancer genetics -Agricultural genomics -Developmental genetics -Regulatory variation in gene expression -Strategies and technologies for extracting function from genomic data -Pharmacological genomics -Genome evolution
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