小柯机器人

美国麻省总医院Konrad J. Karczewski、Daniel G. MacArthur等研究人员合作绘制了14万人的遗传变异图谱。这一研究成果于2020年5月27日在线发表在《自然》上。

研究人员将来自人类测序研究的125,748个外显子组和15,708个基因组合并描述到 Genome Aggregation Database（gnomAD）中。在筛选出由测序和注释错误引起的假象后，研究人员在该队列中确定了443,769个高可信度预测的功能丧失变异。使用改良的人类突变率模型，研究人员根据代表灭活耐受性分布对人类蛋白质编码基因进行分类，使用来自模式生物和工程化人类细胞的数据验证该分类，并证明其可用于提高常见和罕见疾病的基因发现。

据介绍，使蛋白质编码基因失活的遗传变体是有关基因破坏表型后果的来源。其中，对生物体功能至关重要的基因将在自然种群中被耗尽，而非必需基因将耐受它们积累。但是，预测的功能丧失变体会因注解错误而变得更加丰富，并且往往在极低的频率下被发现，因此要进行分析，需要仔细的变体注解和非常大的样本量。

附：英文原文

Title: The mutational constraint spectrum quantified from variation in 141,456 humans

Author: Konrad J. Karczewski, Laurent C. Francioli, Grace Tiao, Beryl B. Cummings, Jessica Alfldi, Qingbo Wang, Ryan L. Collins, Kristen M. Laricchia, Andrea Ganna, Daniel P. Birnbaum, Laura D. Gauthier, Harrison Brand, Matthew Solomonson, Nicholas A. Watts, Daniel Rhodes, Moriel Singer-Berk, Eleina M. England, Eleanor G. Seaby, Jack A. Kosmicki, Raymond K. Walters, Katherine Tashman, Yossi Farjoun, Eric Banks, Timothy Poterba, Arcturus Wang, Cotton Seed, Nicola Whiffin, Jessica X. Chong, Kaitlin E. Samocha, Emma Pierce-Hoffman, Zachary Zappala, Anne H. ODonnell-Luria, Eric Vallabh Minikel, Ben Weisburd, Monkol Lek, James S. Ware, Christopher Vittal, Irina M. Armean, Louis Bergelson, Kristian Cibulskis, Kristen M. Connolly, Miguel Covarrubias, Stacey Donnelly, Steven Ferriera, Stacey Gabriel, Jeff Gentry, Namrata Gupta, Thibault Jeandet, Diane Kaplan, Christopher Llanwarne, Ruchi Munshi, Sam Novod

Issue&Volume: 2020-05-27

Abstract: Genetic variants that inactivate protein-coding genes are a powerful source of information about the phenotypic consequences of gene disruption: genes that are crucial for the function of an organism will be depleted of such variants in natural populations, whereas non-essential genes will tolerate their accumulation. However, predicted loss-of-function variants are enriched for annotation errors, and tend to be found at extremely low frequencies, so their analysis requires careful variant annotation and very large sample sizes1. Here we describe the aggregation of 125,748 exomes and 15,708 genomes from human sequencing studies into the Genome Aggregation Database (gnomAD). We identify 443,769 high-confidence predicted loss-of-function variants in this cohort after filtering for artefacts caused by sequencing and annotation errors. Using an improved model of human mutation rates, we classify human protein-coding genes along a spectrum that represents tolerance to inactivation, validate this classification using data from model organisms and engineered human cells, and show that it can be used to improve the power of gene discovery for both common and rare diseases.

DOI: 10.1038/s41586-020-2308-7

Source: https://www.nature.com/articles/s41586-020-2308-7

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/
投稿链接：http://www.nature.com/authors/submit_manuscript.html