美国再生元基因中心Timothy A. Thornton等研究人员合作实现英国生物银行中基因组、外显子组和归因的遗传关联信号产出。相关论文于2024年9月25日在线发表在《自然—遗传学》杂志上。

研究人员表示，全基因组测序（WGS）、全外显子测序（WES）和基于阵列的基因分型与填补分析（IMP）是评估遗传变异及其与医学相关表型关联的常见策略。迄今为止，尚未对这些方法在数十万样本中的产出进行系统的实证评估，以促进复杂性状遗传信号的发现。

利用来自英国生物银行的149195名个体的100个复杂性状数据，研究人员系统比较了这些策略在遗传关联研究中的相对产出。研究人员发现，结合阵列和填补分析的WGS和WES（WES+IMP）具有最大的关联产出。尽管WGS使得检测的变异总数相比WES+IMP增加了约五倍，但在单变异和基因基础关联分析中检测到的信号仅相差1%。

考虑到WES+IMP通常能节省每个样本的实验和计算时间及资源，研究人员评估了将WES+IMP应用于更大样本的潜在收益。当研究人员将WES+IMP分析扩展到468169名英国生物银行个体时，观察到关联信号约增加四倍，而样本量增加三倍。

研究人员得出结论，优先考虑WES+IMP和大样本量，而不是当代短读长WGS替代方案，将最大化遗传关联研究中的发现数量。

附：英文原文

Title: Yield of genetic association signals from genomes, exomes and imputation in the UK Biobank

Author: Gaynor, Sheila M., Joseph, Tyler, Bai, Xiaodong, Zou, Yuxin, Boutkov, Boris, Maxwell, Evan K., Delaneau, Olivier, Hofmeister, Robin J., Krasheninina, Olga, Balasubramanian, Suganthi, Marcketta, Anthony, Backman, Joshua, Reid, Jeffrey G., Overton, John D., Lotta, Luca A., Marchini, Jonathan, Salerno, William J., Baras, Aris, Abecasis, Goncalo R., Thornton, Timothy A.

Issue&Volume: 2024-09-25

Abstract: Whole-genome sequencing (WGS), whole-exome sequencing (WES) and array genotyping with imputation (IMP) are common strategies for assessing genetic variation and its association with medically relevant phenotypes. To date, there has been no systematic empirical assessment of the yield of these approaches when applied to hundreds of thousands of samples to enable the discovery of complex trait genetic signals. Using data for 100 complex traits from 149,195 individuals in the UK Biobank, we systematically compare the relative yield of these strategies in genetic association studies. We find that WGS and WES combined with arrays and imputation (WES+IMP) have the largest association yield. Although WGS results in an approximately fivefold increase in the total number of assayed variants over WES+IMP, the number of detected signals differed by only 1% for both single-variant and gene-based association analyses. Given that WES+IMP typically results in savings of lab and computational time and resources expended per sample, we evaluate the potential benefits of applying WES+IMP to larger samples. When we extend our WES+IMP analyses to 468,169 UK Biobank individuals, we observe an approximately fourfold increase in association signals with the threefold increase in sample size. We conclude that prioritizing WES+IMP and large sample sizes rather than contemporary short-read WGS alternatives will maximize the number of discoveries in genetic association studies.

DOI: 10.1038/s41588-024-01930-4

Source: https://www.nature.com/articles/s41588-024-01930-4