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Phenotypic covariance across the entire spectrum of relatedness for 86 billion pairs of individuals
Attributing the similarity between individuals to genetic and non-genetic factors is central to genetic analyses. In this paper we use the genomic relationship ([Formula: see text] ) among 417,060 individuals to investigate the phenotypic covariance between pairs of individuals for 32 traits across...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7886899/ https://www.ncbi.nlm.nih.gov/pubmed/33594080 http://dx.doi.org/10.1038/s41467-021-21283-4 |
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author | Kemper, Kathryn E. Yengo, Loic Zheng, Zhili Abdellaoui, Abdel Keller, Matthew C. Goddard, Michael E. Wray, Naomi R. Yang, Jian Visscher, Peter M. |
author_facet | Kemper, Kathryn E. Yengo, Loic Zheng, Zhili Abdellaoui, Abdel Keller, Matthew C. Goddard, Michael E. Wray, Naomi R. Yang, Jian Visscher, Peter M. |
author_sort | Kemper, Kathryn E. |
collection | PubMed |
description | Attributing the similarity between individuals to genetic and non-genetic factors is central to genetic analyses. In this paper we use the genomic relationship ([Formula: see text] ) among 417,060 individuals to investigate the phenotypic covariance between pairs of individuals for 32 traits across the spectrum of relatedness, from unrelated pairs through to identical twins. We find linear relationships between phenotypic covariance and [Formula: see text] that agree with the SNP-based heritability ([Formula: see text] ) in unrelated pairs ([Formula: see text] ), and with pedigree-estimated heritability in close relatives ([Formula: see text] ). The covariance increases faster than [Formula: see text] in distant relatives ([Formula: see text] ), and we attribute this to imperfect linkage disequilibrium between causal variants and the common variants used to construct [Formula: see text] . We also examine the effect of assortative mating on heritability estimates from different experimental designs. We find that full-sib identity-by-descent regression estimates for height (0.66 s.e. 0.07) are consistent with estimates from close relatives (0.82 s.e. 0.04) after accounting for the effect of assortative mating. |
format | Online Article Text |
id | pubmed-7886899 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-78868992021-03-03 Phenotypic covariance across the entire spectrum of relatedness for 86 billion pairs of individuals Kemper, Kathryn E. Yengo, Loic Zheng, Zhili Abdellaoui, Abdel Keller, Matthew C. Goddard, Michael E. Wray, Naomi R. Yang, Jian Visscher, Peter M. Nat Commun Article Attributing the similarity between individuals to genetic and non-genetic factors is central to genetic analyses. In this paper we use the genomic relationship ([Formula: see text] ) among 417,060 individuals to investigate the phenotypic covariance between pairs of individuals for 32 traits across the spectrum of relatedness, from unrelated pairs through to identical twins. We find linear relationships between phenotypic covariance and [Formula: see text] that agree with the SNP-based heritability ([Formula: see text] ) in unrelated pairs ([Formula: see text] ), and with pedigree-estimated heritability in close relatives ([Formula: see text] ). The covariance increases faster than [Formula: see text] in distant relatives ([Formula: see text] ), and we attribute this to imperfect linkage disequilibrium between causal variants and the common variants used to construct [Formula: see text] . We also examine the effect of assortative mating on heritability estimates from different experimental designs. We find that full-sib identity-by-descent regression estimates for height (0.66 s.e. 0.07) are consistent with estimates from close relatives (0.82 s.e. 0.04) after accounting for the effect of assortative mating. Nature Publishing Group UK 2021-02-16 /pmc/articles/PMC7886899/ /pubmed/33594080 http://dx.doi.org/10.1038/s41467-021-21283-4 Text en © The Author(s) 2021 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/. |
spellingShingle | Article Kemper, Kathryn E. Yengo, Loic Zheng, Zhili Abdellaoui, Abdel Keller, Matthew C. Goddard, Michael E. Wray, Naomi R. Yang, Jian Visscher, Peter M. Phenotypic covariance across the entire spectrum of relatedness for 86 billion pairs of individuals |
title | Phenotypic covariance across the entire spectrum of relatedness for 86 billion pairs of individuals |
title_full | Phenotypic covariance across the entire spectrum of relatedness for 86 billion pairs of individuals |
title_fullStr | Phenotypic covariance across the entire spectrum of relatedness for 86 billion pairs of individuals |
title_full_unstemmed | Phenotypic covariance across the entire spectrum of relatedness for 86 billion pairs of individuals |
title_short | Phenotypic covariance across the entire spectrum of relatedness for 86 billion pairs of individuals |
title_sort | phenotypic covariance across the entire spectrum of relatedness for 86 billion pairs of individuals |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7886899/ https://www.ncbi.nlm.nih.gov/pubmed/33594080 http://dx.doi.org/10.1038/s41467-021-21283-4 |
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