小柯机器人

美国Regeneron遗传学中心Manuel A. Ferreira、Gonçalo R. Abecasis等研究人员合作完成对454,787名英国生物库参与者的外显子组测序和分析。该项研究成果于2021年10月18日在线发表在《自然》杂志上。

研究人员使用外显子测序来探索了454,787名英国生物库研究参与者的蛋白质改变变体及其后果。研究人员确定了1200万个编码变体，包括约100万个功能丧失变体和约180万个缺失变体。当这些基因与3994个健康相关的性状进行检测时，研究人员发现有564个基因与性状的关联度为P≤2.18x10^-11。罕见的变异体关联在GWAS位点中被富集，但大多数（91%）是独立于普通变异体信号的。研究人员发现与肝病、眼病和癌症等相关的几个风险增加的关联，以及与高血压（SLC9A3R2）、糖尿病（MAP3K15、FAM234A）和哮喘（SLC27A3）的风险降低的新关联。

六个基因与大脑成像表型有关，包括两个参与神经发育的基因（GBE1、PLD1）。81%的可用信号和用于复制的信号在一个独立的队列中得到了证实；此外，关联信号在欧洲、亚洲和非洲血统的个体中普遍一致。研究人员证明能够用外显子测序来确定新的基因-性状关联，阐明基因功能，并在规模上确定GWAS信号的效应基因。

据介绍，人类遗传学的一个主要目标是利用自然变异来了解改变基因组中每个蛋白质编码基因的表型后果。

附：英文原文

Title: Exome sequencing and analysis of 454,787 UK Biobank participants

Author: Backman, Joshua D., Li, Alexander H., Marcketta, Anthony, Sun, Dylan, Mbatchou, Joelle, Kessler, Michael D., Benner, Christian, Liu, Daren, Locke, Adam E., Balasubramanian, Suganthi, Yadav, Ashish, Banerjee, Nilanjana, Gillies, Christopher, Damask, Amy, Liu, Simon, Bai, Xiaodong, Hawes, Alicia, Maxwell, Evan, Gurski, Lauren, Watanabe, Kyoko, Kosmicki, Jack A., Rajagopal, Veera, Mighty, Jason, Jones, Marcus, Mitnaul, Lyndon, Stahl, Eli, Coppola, Giovanni, Jorgenson, Eric, Habegger, Lukas, Salerno, William J., Shuldiner, Alan R., Lotta, Luca A., Overton, John D., Cantor, Michael N., Reid, Jeffrey G., Yancopoulos, George, Kang, Hyun M., Marchini, Jonathan, Baras, Aris, Abecasis, Gonalo R., Ferreira, Manuel A.

Issue&Volume: 2021-10-18

Abstract: A major goal in human genetics is to use natural variation to understand the phenotypic consequences of altering each protein-coding gene in the genome. Here we used exome sequencing1 to explore protein altering variants and their consequences in 454,787 UK Biobank study participants2. We identified 12 million coding variants, including ~1 million loss-of-function and ~1.8 million deleterious missense variants. When these were tested for association with 3,994 health-related traits, we found 564 genes with trait associations at P≤2.18x10-11. Rare variant associations were enriched in GWAS loci, but most (91%) were independent of common variant signals. We discover several risk-increasing associations with traits related to liver disease, eye disease and cancer, among others, as well as novel risk-lowering associations for hypertension (SLC9A3R2), diabetes (MAP3K15, FAM234A) and asthma (SLC27A3). Six genes were associated with brain imaging phenotypes, including two involved in neural development (GBE1, PLD1). 81% of signals available and powered for replication were confirmed in an independent cohort; furthermore, association signals were generally consistent across European, Asian and African ancestry individuals. We illustrate the ability of exome sequencing to identify novel gene-trait associations, elucidate gene function, and pinpoint effector genes underlying GWAS signals at scale.

DOI: 10.1038/s41586-021-04103-z

Source: https://www.nature.com/articles/s41586-021-04103-z

Nature：《自然》，创刊于1869年。隶属于施普林格·自然出版集团，最新IF：69.504
官方网址：http://www.nature.com/
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