Characterizing selection on complex traits through conditional frequency spectra

Natural selection on complex traits is difficult to study in part due to the ascertainment inherent to genome-wide association studies (GWAS). The power to detect a trait-associated variant in GWAS is a function of its frequency and effect size - but for traits under selection, the effect size of a variant determines the strength of selection against it, constraining its frequency. Recognizing the biases inherent to GWAS ascertainment, we propose studying the joint distribution of allele frequencies across populations, conditional on the frequencies in the GWAS cohort. Before considering these conditional frequency spectra, we first characterized the impact of selection and non-equilibrium demography on allele frequency dynamics forwards and backwards in time. We then used these results to understand conditional frequency spectra under realistic human demography. Finally, we investigated empirical conditional frequency spectra for GWAS variants associated with 106 complex traits, finding compelling evidence for either stabilizing or purifying selection. Our results provide insights into polygenic score portability and other properties of variants ascertained with GWAS, highlighting the utility of conditional frequency spectra.

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Publication Details

Journal
Genetics
Published
2024-12-18
DOI
https://doi.org/10.1093/genetics/iyae210
Citations
12
Primary Topic
Genetic Associations and Epidemiology
Type
article
Field-Weighted Citation Impact
6.05

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article

Characterizing selection on complex traits through conditional frequency spectra

Huisheng Zhu, Yuval B. Simons, Hakhamanesh Mostafavi, Roshni Patel et al.
12 citations
Genetics
Genetic Associations and Epidemiology
6.05
article

Characterizing selection on complex traits through conditional frequency spectra

Huisheng Zhu, Yuval B. Simons, Hakhamanesh Mostafavi, Roshni Patel, Jonathan K. Pritchard, Clemens L. Weiß, Jeffrey P. Spence
article en
12 citations

Abstract

Natural selection on complex traits is difficult to study in part due to the ascertainment inherent to genome-wide association studies (GWAS). The power to detect a trait-associated variant in GWAS is a function of its frequency and effect size - but for traits under selection, the effect size of a variant determines the strength of selection against it, constraining its frequency. Recognizing the biases inherent to GWAS ascertainment, we propose studying the joint distribution of allele frequencies across populations, conditional on the frequencies in the GWAS cohort. Before considering these conditional frequency spectra, we first characterized the impact of selection and non-equilibrium demography on allele frequency dynamics forwards and backwards in time. We then used these results to understand conditional frequency spectra under realistic human demography. Finally, we investigated empirical conditional frequency spectra for GWAS variants associated with 106 complex traits, finding compelling evidence for either stabilizing or purifying selection. Our results provide insights into polygenic score portability and other properties of variants ascertained with GWAS, highlighting the utility of conditional frequency spectra.

GeneticsVol. 229(4)
University of Southern California (US), Cardiovascular Institute of the South (US), University of Chicago (US), Center for Human Genetics (US), New York University (US), Stanford University (US)
National Institutes of Health
Openalex Percentile: Top 3%
Genetic Associations and Epidemiology
6.05
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