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Finding the Sources of Missing Heritability within Rare Variants Through Simulation
Thousands of genome-wide association studies (GWAS) have been conducted to identify the genetic variants associated with complex disorders. However, only a small proportion of phenotypic variances can be explained by the reported variants. Moreover, many GWAS failed to identify genetic variants asso...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
SAGE Publications
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5638154/ https://www.ncbi.nlm.nih.gov/pubmed/29051702 http://dx.doi.org/10.1177/1177932217735096 |
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author | Bandyopadhyay, Baishali Chanda, Veda Wang, Yupeng |
author_facet | Bandyopadhyay, Baishali Chanda, Veda Wang, Yupeng |
author_sort | Bandyopadhyay, Baishali |
collection | PubMed |
description | Thousands of genome-wide association studies (GWAS) have been conducted to identify the genetic variants associated with complex disorders. However, only a small proportion of phenotypic variances can be explained by the reported variants. Moreover, many GWAS failed to identify genetic variants associated with disorders displaying hereditary features. The “missing heritability” problem can be partly explained by rare variants. We simulated a causality scenario that gestational ages, a quantitative trait that can distinguish preterm (<37 weeks) and term births, were significantly correlated with the rare variant aggregations at 1000 single-nucleotide polymorphism loci. These 1000 simulated causal rare variants were embedded into randomly selected subsets of 9642 promoter regions from the 1000 Genomes Project genotypic data according to different proportions of causal rare variants within the embedded promoters. Through analysis of the correlations between rare variant aggregations and gestational ages, we found that the embedded promoters as a whole showed weaker genetic association when the proportion of causal rare variants decreased, and no individual embedded promoters showed genetic association when the proportion of causal rare variants was smaller than 0.4. Our analyses indicate that association signals can be greatly diluted when causal rare variants are dispersedly and sparsely distributed in the genome, accounting for an important source of missing heritability. |
format | Online Article Text |
id | pubmed-5638154 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | SAGE Publications |
record_format | MEDLINE/PubMed |
spelling | pubmed-56381542017-10-19 Finding the Sources of Missing Heritability within Rare Variants Through Simulation Bandyopadhyay, Baishali Chanda, Veda Wang, Yupeng Bioinform Biol Insights Short Report Thousands of genome-wide association studies (GWAS) have been conducted to identify the genetic variants associated with complex disorders. However, only a small proportion of phenotypic variances can be explained by the reported variants. Moreover, many GWAS failed to identify genetic variants associated with disorders displaying hereditary features. The “missing heritability” problem can be partly explained by rare variants. We simulated a causality scenario that gestational ages, a quantitative trait that can distinguish preterm (<37 weeks) and term births, were significantly correlated with the rare variant aggregations at 1000 single-nucleotide polymorphism loci. These 1000 simulated causal rare variants were embedded into randomly selected subsets of 9642 promoter regions from the 1000 Genomes Project genotypic data according to different proportions of causal rare variants within the embedded promoters. Through analysis of the correlations between rare variant aggregations and gestational ages, we found that the embedded promoters as a whole showed weaker genetic association when the proportion of causal rare variants decreased, and no individual embedded promoters showed genetic association when the proportion of causal rare variants was smaller than 0.4. Our analyses indicate that association signals can be greatly diluted when causal rare variants are dispersedly and sparsely distributed in the genome, accounting for an important source of missing heritability. SAGE Publications 2017-10-04 /pmc/articles/PMC5638154/ /pubmed/29051702 http://dx.doi.org/10.1177/1177932217735096 Text en © The Author(s) 2017 http://creativecommons.org/licenses/by-nc/4.0/ This article is distributed under the terms of the Creative Commons Attribution-NonCommercial 4.0 License (http://www.creativecommons.org/licenses/by-nc/4.0/) which permits non-commercial use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access pages (https://us.sagepub.com/en-us/nam/open-access-at-sage). |
spellingShingle | Short Report Bandyopadhyay, Baishali Chanda, Veda Wang, Yupeng Finding the Sources of Missing Heritability within Rare Variants Through Simulation |
title | Finding the Sources of Missing Heritability within Rare Variants Through Simulation |
title_full | Finding the Sources of Missing Heritability within Rare Variants Through Simulation |
title_fullStr | Finding the Sources of Missing Heritability within Rare Variants Through Simulation |
title_full_unstemmed | Finding the Sources of Missing Heritability within Rare Variants Through Simulation |
title_short | Finding the Sources of Missing Heritability within Rare Variants Through Simulation |
title_sort | finding the sources of missing heritability within rare variants through simulation |
topic | Short Report |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5638154/ https://www.ncbi.nlm.nih.gov/pubmed/29051702 http://dx.doi.org/10.1177/1177932217735096 |
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