Study design and the sampling of deleterious rare variants in biobank-scale datasets

• 成果类型: Article
• 署名作者: Steiner, Margaret C.; Rice, Daniel P.; Biddanda, Arjun; Ianni-Ravn, Mariadaria K.; Porras, Christian; Novembre, John
• 署名单位: University of Chicago; Massachusetts Institute of Technology (MIT); Johns Hopkins University; Icahn School of Medicine at Mount Sinai; University of Chicago
• 刊物名称: PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA
• ISSN/ISSBN: 0027-11013
• DOI: 10.1073/pnas.2425196122
• 发表日期: 2025-06-10
• 关键词: linkage disequilibrium; demographic inference; population-structure; natural-populations; spatial structure; gene-frequencies; selection; allelism; migration; accuracy

摘要

One key component of study design in population genetics is the geographic breadth of a sample (i.e., how broad a region across which individuals are sampled). How the geographic breadth of a sample impacts observations of rare, deleterious variants is unclear, even though such variants are of particular interest for biomedical and evolutionary applications. Here, in order to gain insight into the effects of sample design on ascertained genetic variants, we formulate a stochastic model of dispersal, genetic drift, selection, mutation, and geographically concentrated sampling. We use this model to understand the effects of the geographic breadth of sampling effort on the discovery of negatively selected variants. We find that samples which are more geographically broad will discover a greater number of variants as compared to geographically narrow samples (an effect we label discovery); though the variants will be detected at lower average frequency than in narrow samples (e.g., as singletons, an effect we label dilution). Importantly, these effects are amplified for larger sample sizes and fitness effects. We validate these results using both population genetic simulations and empirical analyses in the UK Biobank. Our results are particularly important in two contexts: the association of large-effect rare variants with particular phenotypes and the inference of negative selection from allele frequency data. Overall, our findings emphasize the importance of considering geographic breadth when designing and carrying out genetic studies, especially at biobank scale.