Assessing Hardy-Weinberg equilibrium in T2T-aligned 1000 genomes project
4 affiliations
- 1Genetics and Genome Biology Program, The Hospital for Sick Children, Toronto, Ontario, Canada
- 2Division of Biostatistics and 4 Division of Epidemiology, Dalla Lana School of Public Health, University of Toronto, Toronto, Ontario, Canada
- 3Department of Statistical Sciences, University of Toronto, Toronto, Ontario, Canada
- 4Epidemiology, Dalla Lana School of Public Health, University of Toronto, Toronto, Ontario, Canada
Abstract
Quality control of markers in genome-wide association studies often includes testing for Hardy-Weinberg equilibrium (HWE). However, this is usually implemented in a homogeneous population without stratifying by sex. Previous work indicates sex-based selection at numerous autosomal loci in cohorts with active recruitment. Sex chromosome sequences can also interfere with autosomal SNPs. These motivate a re-examination of HWE in sex-aware analyses. Using the telomere-to-telomere (T2Tv2)-aligned high-coverage whole genome sequencing data from 2,490 individuals in the 1000 Genomes Project, we examined genome-wide sex-specific deviations from HWE across five super-populations. Our analyses were restricted to bi-allelic SNPs with non-missing genotypes and minor allele frequency (MAF) ≥5% in both sexes of the five super-populations. We applied an allele-based framework to quantify both the magnitude and direction of Hardy–Weinberg disequilibrium (HWD), followed by a second-order omnibus meta-analysis that combined HWD results across populations and sexes. At a genome-wide significance threshold of p < 5e-8, 0.9% of autosomal SNPs exhibited significant deviations from HWE. The majority of these deviations were associated with genomic features indicative of poor sequence quality. Restricting the analysis to reliable genomic regions substantially reduced the number of signals, yielding 255 autosomal SNPs and one non-pseudoautosomal chromosome X SNP. Among these, 140 autosomal SNPs displayed significant heterogeneity across populations but not across sexes. Notably, eight SNPs within a 15-bp region on chromosome 14q31.3 showed excess heterozygosity in both sexes of the African super-population (AFR). Finally, we developed a multivariate predictor of HWD based on sequence features, providing a practical tool that can be integrated into existing quality control pipelines for whole genome sequencing studies. Author summary: We conducted a specific quality control test, which compares the observed and expected genotype counts, on an updated version of the 1000 Genomes Project whole genome sequence data generated on ~2500 individuals. We first performed this analysis by grouping the data by ancestry and sex. We then combined and contrasted the group results. We found that most regions that differed between observed and expected counts overlapped regions of the genome that are difficult to sequence using current short-read technology. In the remaining regions, we found an interesting cluster of SNPs in a single ancestry group, where there is a large excess of heterozygous genotypes. GWASes typically use a standard strict threshold for this quality control test for genotyping arrays to remove SNPs. Here, we suggest a more nuanced approach that is applicable to whole genome sequence data.
Related
- The 100 Diatom Genomes Project
- Project Psyche: reference genomes for all Lepidoptera in Europe
- The Vertebrate Genomes Project Phase I: A global reference genome resource
- Active centromeres share a conserved array-architecture signature across great ape genomes
- Unbiased and scalable reduction of diverse bacterial genomes
BibTeX
@article{garg2026assessing,
title = {{Assessing Hardy-Weinberg equilibrium in T2T-aligned 1000 genomes project}},
author = {Elika Garg and Jaffa Romain and Lei Sun and Andrew D. Paterson},
journal = {PLOS Genetics},
year = {2026},
month = sep,
doi = {10.1371/journal.pgen.1012280},
url = {https://journals.plos.org/plosgenetics/article?id=10.1371/journal.pgen.1012280},
note = {CC BY 4.0},
}
RIS
TY - JOUR
TI - Assessing Hardy-Weinberg equilibrium in T2T-aligned 1000 genomes project
AU - Elika Garg
AU - Jaffa Romain
AU - Lei Sun
AU - Andrew D. Paterson
PY - 2026
DA - 2026/09/15
JO - PLOS Genetics
DO - 10.1371/journal.pgen.1012280
UR - https://journals.plos.org/plosgenetics/article?id=10.1371/journal.pgen.1012280
AB - Quality control of markers in genome-wide association studies often includes testing for Hardy-Weinberg equilibrium (HWE). However, this is usually implemented in a homogeneous population without stratifying by sex. Previous work indicates sex-based selection at numerous autosomal loci in cohorts with active recruitment. Sex chromosome sequences can also interfere with autosomal SNPs. These motivate a re-examination of HWE in sex-aware analyses. Using the telomere-to-telomere (T2Tv2)-aligned high-coverage whole genome sequencing data from 2,490 individuals in the 1000 Genomes Project, we examined genome-wide sex-specific deviations from HWE across five super-populations. Our analyses were restricted to bi-allelic SNPs with non-missing genotypes and minor allele frequency (MAF) ≥5% in both sexes of the five super-populations. We applied an allele-based framework to quantify both the magnitude and direction of Hardy–Weinberg disequilibrium (HWD), followed by a second-order omnibus meta-analysis that combined HWD results across populations and sexes. At a genome-wide significance threshold of p < 5e-8, 0.9% of autosomal SNPs exhibited significant deviations from HWE. The majority of these deviations were associated with genomic features indicative of poor sequence quality. Restricting the analysis to reliable genomic regions substantially reduced the number of signals, yielding 255 autosomal SNPs and one non-pseudoautosomal chromosome X SNP. Among these, 140 autosomal SNPs displayed significant heterogeneity across populations but not across sexes. Notably, eight SNPs within a 15-bp region on chromosome 14q31.3 showed excess heterozygosity in both sexes of the African super-population (AFR). Finally, we developed a multivariate predictor of HWD based on sequence features, providing a practical tool that can be integrated into existing quality control pipelines for whole genome sequencing studies. Author summary: We conducted a specific quality control test, which compares the observed and expected genotype counts, on an updated version of the 1000 Genomes Project whole genome sequence data generated on ~2500 individuals. We first performed this analysis by grouping the data by ancestry and sex. We then combined and contrasted the group results. We found that most regions that differed between observed and expected counts overlapped regions of the genome that are difficult to sequence using current short-read technology. In the remaining regions, we found an interesting cluster of SNPs in a single ancestry group, where there is a large excess of heterozygous genotypes. GWASes typically use a standard strict threshold for this quality control test for genotyping arrays to remove SNPs. Here, we suggest a more nuanced approach that is applicable to whole genome sequence data.
SN - 1553-7404
ER -