Quantifying the mapping precision of genome-wide association studies using whole-genome sequencing data
Open accessAbstract
BACKGROUND: Understanding the mapping precision of genome-wide association studies (GWAS), that is the physical distances between the top associated single-nucleotide polymorphisms (SNPs) and the causal variants, is essential to design fine-mapping experiments for complex traits and diseases. RESULTS: Using simulations based on whole-genome sequencing (WGS) data from 3642 unrelated individuals of European descent, we show that the association signals at rare causal variants (minor allele frequency ≤ 0.01) are very unlikely to be mapped to common variants in GWAS using either WGS data or imputed data and vice versa. We predict that at least 80% of the common variants identified from published GWAS using imputed data are within 33.5 Kbp of the causal variants, a resolution that is comparable with that using WGS data. Mapping precision at these loci will improve with increasing sample sizes of GWAS in the future. For rare variants, the mapping precision of GWAS using WGS data is extremely high, suggesting WGS is an efficient strategy to detect and fine-map rare variants simultaneously. We further assess the mapping precision by linkage disequilibrium between GWAS hits and causal variants and develop an online tool (gwasMP) to query our results with different thresholds of physical distance and/or linkage disequilibrium ( http://cnsgenomics.com/shiny/gwasMP ). CONCLUSIONS: Our findings provide a benchmark to inform future design and development of fine-mapping experiments and technologies to pinpoint the causal variants at GWAS loci.
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At a stricter threshold of P < 1×10−8, the number of lead SNPs declines to 3,277.
“At the stricter threshold9 of P < 1×10−8, the number declines to 3,277”
From Polygenic prediction of educational attainment within and between families from genome-wide association analyses in 3 million individuals (2022) · cites this paper as [9]
Simulations have suggested that without replication, variants with P values between 5E-08 and 5E-9 should be interpreted with greater caution.
“Simulations have suggested that without replication variants with P values between 5E-08 and 5E-9 should be interpreted with greater caution (46,47).”
From Identification of novel risk loci, causal insights, and heritable risk for Parkinson's disease: a meta-analysis of genome-wide association studies (2019) · cites this paper as [46]
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- Authors
- Wu, Y., Zheng, Z., Visscher, P. M., & Yang, J.
- Affiliations
- The University of Queensland (AU)
- Corresponding author
- Yang, Jian
- Venue
- Genome biology
- Published
- 2017-05-16
- Volume
- 18
- Issue
- 1
- Pages
- 86-86
- ISSN
- 1465-6906 (ISSN-L)
- 1474-760X
- PMC
- PMC5432979
- OpenAlex
- W2612591211
- Cited by
- 100
- References
- 26
- Citations by year
- 2026: 4 · 2025: 8 · 2024: 11 · 2023: 7 · 2022: 15 · 2021: 10 · 2020: 16 · 2019: 14 · 2018: 13 · 2017: 2
- FWCI
- 8.17
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Locations
- Genome biology (publishedVersion, cc-by)
- Europe PMC (PubMed Central) (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Funders
- Australian Research Council (DP160101343)
- Australian National Health and Medical Research Council (1078037 and 1113400)
- Sylvia and Charles Viertel Charitable Foundation (Senior Medical Research Fellowship)
- National Health and Medical Research Council (1107258)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Associations and Epidemiology
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Mapping and Diversity in Plants and Animals
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic and phenotypic traits in livestock
- Keywords
- genome-wide association study, fine mapping, causal variants, rare variants, common genetic variants, linkage disequilibrium, whole genome sequencing, imputation, physical distance, sample size, European ancestry
- MeSH terms
- Alleles, Gene Frequency, Genotype, Humans, Phenotype, Linkage Disequilibrium, Genome, Human, Sample Size, Physical Chromosome Mapping, Polymorphism, Single Nucleotide, Quantitative Trait Loci, White People, Genome-Wide Association Study, High-Throughput Nucleotide Sequencing
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