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Estimating indirect parental genetic effects on offspring phenotypes using virtual parental genotypes derived from sibling and half sibling pairs
Indirect parental genetic effects may be defined as the influence of parental genotypes on offspring phenotypes over and above that which results from the transmission of genes from parents to their children. However, given the relative paucity of large-scale family-based cohorts around the world, i...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7646364/ https://www.ncbi.nlm.nih.gov/pubmed/33104719 http://dx.doi.org/10.1371/journal.pgen.1009154 |
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author | Hwang, Liang-Dar Tubbs, Justin D. Luong, Justin Lundberg, Mischa Moen, Gunn-Helen Wang, Geng Warrington, Nicole M. Sham, Pak C. Cuellar-Partida, Gabriel Evans, David M. |
author_facet | Hwang, Liang-Dar Tubbs, Justin D. Luong, Justin Lundberg, Mischa Moen, Gunn-Helen Wang, Geng Warrington, Nicole M. Sham, Pak C. Cuellar-Partida, Gabriel Evans, David M. |
author_sort | Hwang, Liang-Dar |
collection | PubMed |
description | Indirect parental genetic effects may be defined as the influence of parental genotypes on offspring phenotypes over and above that which results from the transmission of genes from parents to their children. However, given the relative paucity of large-scale family-based cohorts around the world, it is difficult to demonstrate parental genetic effects on human traits, particularly at individual loci. In this manuscript, we illustrate how parental genetic effects on offspring phenotypes, including late onset conditions, can be estimated at individual loci in principle using large-scale genome-wide association study (GWAS) data, even in the absence of parental genotypes. Our strategy involves creating “virtual” mothers and fathers by estimating the genotypic dosages of parental genotypes using physically genotyped data from relative pairs. We then utilize the expected dosages of the parents, and the actual genotypes of the offspring relative pairs, to perform conditional genetic association analyses to obtain asymptotically unbiased estimates of maternal, paternal and offspring genetic effects. We apply our approach to 19066 sibling pairs from the UK Biobank and show that a polygenic score consisting of imputed parental educational attainment SNP dosages is strongly related to offspring educational attainment even after correcting for offspring genotype at the same loci. We develop a freely available web application that quantifies the power of our approach using closed form asymptotic solutions. We implement our methods in a user-friendly software package IMPISH (IMputing Parental genotypes In Siblings and Half Siblings) which allows users to quickly and efficiently impute parental genotypes across the genome in large genome-wide datasets, and then use these estimated dosages in downstream linear mixed model association analyses. We conclude that imputing parental genotypes from relative pairs may provide a useful adjunct to existing large-scale genetic studies of parents and their offspring. |
format | Online Article Text |
id | pubmed-7646364 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-76463642020-11-16 Estimating indirect parental genetic effects on offspring phenotypes using virtual parental genotypes derived from sibling and half sibling pairs Hwang, Liang-Dar Tubbs, Justin D. Luong, Justin Lundberg, Mischa Moen, Gunn-Helen Wang, Geng Warrington, Nicole M. Sham, Pak C. Cuellar-Partida, Gabriel Evans, David M. PLoS Genet Research Article Indirect parental genetic effects may be defined as the influence of parental genotypes on offspring phenotypes over and above that which results from the transmission of genes from parents to their children. However, given the relative paucity of large-scale family-based cohorts around the world, it is difficult to demonstrate parental genetic effects on human traits, particularly at individual loci. In this manuscript, we illustrate how parental genetic effects on offspring phenotypes, including late onset conditions, can be estimated at individual loci in principle using large-scale genome-wide association study (GWAS) data, even in the absence of parental genotypes. Our strategy involves creating “virtual” mothers and fathers by estimating the genotypic dosages of parental genotypes using physically genotyped data from relative pairs. We then utilize the expected dosages of the parents, and the actual genotypes of the offspring relative pairs, to perform conditional genetic association analyses to obtain asymptotically unbiased estimates of maternal, paternal and offspring genetic effects. We apply our approach to 19066 sibling pairs from the UK Biobank and show that a polygenic score consisting of imputed parental educational attainment SNP dosages is strongly related to offspring educational attainment even after correcting for offspring genotype at the same loci. We develop a freely available web application that quantifies the power of our approach using closed form asymptotic solutions. We implement our methods in a user-friendly software package IMPISH (IMputing Parental genotypes In Siblings and Half Siblings) which allows users to quickly and efficiently impute parental genotypes across the genome in large genome-wide datasets, and then use these estimated dosages in downstream linear mixed model association analyses. We conclude that imputing parental genotypes from relative pairs may provide a useful adjunct to existing large-scale genetic studies of parents and their offspring. Public Library of Science 2020-10-26 /pmc/articles/PMC7646364/ /pubmed/33104719 http://dx.doi.org/10.1371/journal.pgen.1009154 Text en © 2020 Hwang et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Article Hwang, Liang-Dar Tubbs, Justin D. Luong, Justin Lundberg, Mischa Moen, Gunn-Helen Wang, Geng Warrington, Nicole M. Sham, Pak C. Cuellar-Partida, Gabriel Evans, David M. Estimating indirect parental genetic effects on offspring phenotypes using virtual parental genotypes derived from sibling and half sibling pairs |
title | Estimating indirect parental genetic effects on offspring phenotypes
using virtual parental genotypes derived from sibling and half sibling
pairs |
title_full | Estimating indirect parental genetic effects on offspring phenotypes
using virtual parental genotypes derived from sibling and half sibling
pairs |
title_fullStr | Estimating indirect parental genetic effects on offspring phenotypes
using virtual parental genotypes derived from sibling and half sibling
pairs |
title_full_unstemmed | Estimating indirect parental genetic effects on offspring phenotypes
using virtual parental genotypes derived from sibling and half sibling
pairs |
title_short | Estimating indirect parental genetic effects on offspring phenotypes
using virtual parental genotypes derived from sibling and half sibling
pairs |
title_sort | estimating indirect parental genetic effects on offspring phenotypes
using virtual parental genotypes derived from sibling and half sibling
pairs |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7646364/ https://www.ncbi.nlm.nih.gov/pubmed/33104719 http://dx.doi.org/10.1371/journal.pgen.1009154 |
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