The impact of SNP density on quantitative genetic analyses of body size traits in a wild population of Soay sheep.
GWAS
SNP density
animal model
heritability
wild population
Journal
Ecology and evolution
ISSN: 2045-7758
Titre abrégé: Ecol Evol
Pays: England
ID NLM: 101566408
Informations de publication
Date de publication:
Dec 2022
Dec 2022
Historique:
received:
07
07
2022
revised:
01
11
2022
accepted:
29
11
2022
entrez:
19
12
2022
pubmed:
20
12
2022
medline:
20
12
2022
Statut:
epublish
Résumé
Understanding the genetic architecture underpinning quantitative traits in wild populations is pivotal to understanding the processes behind trait evolution. The 'animal model' is a popular method for estimating quantitative genetic parameters such as heritability and genetic correlation and involves fitting an estimate of relatedness between individuals in the study population. Genotypes at genome-wide markers can be used to estimate relatedness; however, relatedness estimates vary with marker density, potentially affecting results. Increasing density of markers is also expected to increase the power to detect quantitative trait loci (QTL). In order to understand how the density of genetic markers affects the results of quantitative genetic analyses, we estimated heritability and performed genome-wide association studies (GWAS) on five body size traits in an unmanaged population of Soay sheep using two different SNP densities: a dataset of 37,037 genotyped SNPs and an imputed dataset of 417,373 SNPs. Heritability estimates did not differ between the two SNP densities, but the high-density imputed SNP dataset revealed four new SNP-trait associations that were not found with the lower density dataset, as well as confirming all previously-found QTL. We also demonstrated that fitting fixed and random effects in the same step as performing GWAS is a more powerful approach than pre-correcting for covariates in a separate model.
Identifiants
pubmed: 36532132
doi: 10.1002/ece3.9639
pii: ECE39639
pmc: PMC9750819
doi:
Types de publication
Journal Article
Langues
eng
Pagination
e9639Subventions
Organisme : Cancer Research UK
ID : 18927
Pays : United Kingdom
Organisme : Medical Research Council
ID : MC_PC_U127527198
Pays : United Kingdom
Organisme : Medical Research Council
ID : MC_UU_00007/1
Pays : United Kingdom
Organisme : Medical Research Council
ID : MC_UU_00007/10
Pays : United Kingdom
Informations de copyright
© 2022 The Authors. Ecology and Evolution published by John Wiley & Sons Ltd.
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