ArticleGenetics2015
The Nature of Genetic Variation for Complex Traits Revealed by GWAS and Regional Heritability Mapping Analyses.
Article in Genetics, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 42 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
42 citing papers in PubMed, 71 citations in OpenAlex.
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- Cost-effective non-additive GWAS across 2329 diseases in 500,349 individuals.Nature communications · 2025Article
- The Genetics of Host Plant Acceptance in Pea Aphids.Molecular ecology · 2025Article
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- Leveraging Whole-Genome Resequencing to Uncover Genetic Diversity and Promote Conservation Strategies for Ruminants in Asia.Animals : an open access journal from MDPI · 2025Review
- Genome-wide association study and haplotype analyses reveal the genetic architecture of agronomic traits and sugars in sweet sorghum.Frontiers in genetics · 2025Article
- Conditional frequency spectra as a tool for studying selection on complex traits in biobanks.bioRxiv : the preprint server for biology · 2024Article
- Tree-based QTL mapping with expected local genetic relatedness matrices.American journal of human genetics · 2023Article
- Assessing efficiency of fine-mapping obesity-associated variants through leveraging ancestry architecture and functional annotation using PAGE and UKBB cohorts.Human genetics · 2023Article
- Performance Comparison of Computational Methods for the Prediction of the Function and Pathogenicity of Non-coding Variants.Genomics, proteomics & bioinformatics · 2023Article
- Genetic variation in chromatin state across multiple tissues in Drosophila melanogaster.PLoS genetics · 2023Article
- Tree-based QTL mapping with expected local genetic relatedness matrices.bioRxiv : the preprint server for biology · 2023Article
- Partitioning gene-level contributions to complex-trait heritability by allele frequency identifies disease-relevant genes.American journal of human genetics · 2022Article
- Genomic architecture of phenotypic extremes in a wild cervid.BMC genomics · 2022Article
- SNP characteristics and validation success in genome wide association studies.Human genetics · 2022Article
- Genetic characterization of carrot root shape and size using genome-wide association analysis and genomic-estimated breeding values.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2022Article
- Genome-Wide Association Study of Healthful Flavonoids among Diverse Mandarin Accessions.Plants (Basel, Switzerland) · 2022Article
- Association Studies and Genomic Prediction for Genetic Improvements in Agriculture.Frontiers in plant science · 2022Review
- Regional Heritability Mapping of Quantitative Trait Loci Controlling Traits Related to Growth and Productivity in Popcorn (Plants (Basel, Switzerland) · 2021Article
- Highly pleiotropic variants of human traits are enriched in genomic regions with strong background selection.Human genetics · 2021Article
Corrections and comments
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Authors and funding
3 authors at 2 institutions in 2 countries.
Funding
Abstract
We use computer simulations to investigate the amount of genetic variation for complex traits that can be revealed by single-SNP genome-wide association studies (GWAS) or regional heritability mapping (RHM) analyses based on full genome sequence data or SNP chips. We model a large population subject to mutation, recombination, selection, and drift, assuming a pleiotropic model of mutations sampled from a bivariate distribution of effects of mutations on a quantitative trait and fitness. The pleiotropic model investigated, in contrast to previous models, implies that common mutations of large effect are responsible for most of the genetic variation for quantitative traits, except when the trait is fitness itself. We show that GWAS applied to the full sequence increases the number of QTL detected by as much as 50% compared to the number found with SNP chips but only modestly increases the amount of additive genetic variance explained. Even with full sequence data, the total amount of additive variance explained is generally below 50%. Using RHM on the full sequence data, a slightly larger number of QTL are detected than by GWAS if the same probability threshold is assumed, but these QTL explain a slightly smaller amount of genetic variance. Our results also suggest that most of the missing heritability is due to the inability to detect variants of moderate effect (∼0.03-0.3 phenotypic SDs) segregating at substantial frequencies. Very rare variants, which are more difficult to detect by GWAS, are expected to contribute little genetic variation, so their eventual detection is less relevant for resolving the missing heritability problem.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.