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Effects of alleles in crossbred pigs estimated for genomic prediction depend on their breed-of-origin

BACKGROUND: This study investigated if the allele effect of a given single nucleotide polymorphism (SNP) for crossbred performance in pigs estimated in a genomic prediction model differs depending on its breed-of-origin, and how these are related to estimated effects for purebred performance. RESULT...

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Autores principales: Sevillano, Claudia A, ten Napel, Jan, Guimarães, Simone E F, Silva, Fabyano F, Calus, Mario P L
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6180412/
https://www.ncbi.nlm.nih.gov/pubmed/30305017
http://dx.doi.org/10.1186/s12864-018-5126-7
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author Sevillano, Claudia A
ten Napel, Jan
Guimarães, Simone E F
Silva, Fabyano F
Calus, Mario P L
author_facet Sevillano, Claudia A
ten Napel, Jan
Guimarães, Simone E F
Silva, Fabyano F
Calus, Mario P L
author_sort Sevillano, Claudia A
collection PubMed
description BACKGROUND: This study investigated if the allele effect of a given single nucleotide polymorphism (SNP) for crossbred performance in pigs estimated in a genomic prediction model differs depending on its breed-of-origin, and how these are related to estimated effects for purebred performance. RESULTS: SNP-allele substitution effects were estimated for a commonly used SNP panel using a genomic best linear unbiased prediction model with breed-specific partial relationship matrices. Estimated breeding values for purebred and crossbred performance were converted to SNP-allele effects by breed-of-origin. Differences between purebred and crossbred, and between breeds-of-origin were evaluated by comparing percentage of variance explained by genomic regions for back fat thickness (BF), average daily gain (ADG), and residual feed intake (RFI). From ten regions explaining most additive genetic variance for crossbred performance, 1 to 5 regions also appeared in the top ten for purebred performance. The proportion of genetic variance explained by a genomic region and the estimated effect of a haplotype in such a region were different depending upon the breed-of-origin. To illustrate underlying mechanisms, we evaluated the estimated effects across breeds-of-origin for haplotypes associated to the melanocortin 4 receptor (MC4R) gene, and for the MC4Rsnp itself which is a missense mutation with a known effect on BF and ADG. Although estimated allele substitution effects of the MC4Rsnp mutation were very similar across breeds, explained genetic variance of haplotypes associated to the MC4R gene using a SNP panel that does not include the mutation, was considerably lower in one of the breeds where the allele frequency of the mutation was the lowest. CONCLUSIONS: Similar regions explaining similar additive genetic variance were observed across purebred and crossbred performance. Moreover, there was some overlap across breeds-of-origin between regions that explained relatively large proportions of genetic variance for crossbred performance; albeit that the actual proportion of variance deviated across breeds-of-origin. Results based on a missense mutation in MC4R confirmed that even if a causal locus has similar effects across breeds-of-origin, estimated effects and explained variance in its region using a commonly used SNP panel can strongly depend on the allele frequency of the underlying causal mutation. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12864-018-5126-7) contains supplementary material, which is available to authorized users.
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spelling pubmed-61804122018-10-18 Effects of alleles in crossbred pigs estimated for genomic prediction depend on their breed-of-origin Sevillano, Claudia A ten Napel, Jan Guimarães, Simone E F Silva, Fabyano F Calus, Mario P L BMC Genomics Research Article BACKGROUND: This study investigated if the allele effect of a given single nucleotide polymorphism (SNP) for crossbred performance in pigs estimated in a genomic prediction model differs depending on its breed-of-origin, and how these are related to estimated effects for purebred performance. RESULTS: SNP-allele substitution effects were estimated for a commonly used SNP panel using a genomic best linear unbiased prediction model with breed-specific partial relationship matrices. Estimated breeding values for purebred and crossbred performance were converted to SNP-allele effects by breed-of-origin. Differences between purebred and crossbred, and between breeds-of-origin were evaluated by comparing percentage of variance explained by genomic regions for back fat thickness (BF), average daily gain (ADG), and residual feed intake (RFI). From ten regions explaining most additive genetic variance for crossbred performance, 1 to 5 regions also appeared in the top ten for purebred performance. The proportion of genetic variance explained by a genomic region and the estimated effect of a haplotype in such a region were different depending upon the breed-of-origin. To illustrate underlying mechanisms, we evaluated the estimated effects across breeds-of-origin for haplotypes associated to the melanocortin 4 receptor (MC4R) gene, and for the MC4Rsnp itself which is a missense mutation with a known effect on BF and ADG. Although estimated allele substitution effects of the MC4Rsnp mutation were very similar across breeds, explained genetic variance of haplotypes associated to the MC4R gene using a SNP panel that does not include the mutation, was considerably lower in one of the breeds where the allele frequency of the mutation was the lowest. CONCLUSIONS: Similar regions explaining similar additive genetic variance were observed across purebred and crossbred performance. Moreover, there was some overlap across breeds-of-origin between regions that explained relatively large proportions of genetic variance for crossbred performance; albeit that the actual proportion of variance deviated across breeds-of-origin. Results based on a missense mutation in MC4R confirmed that even if a causal locus has similar effects across breeds-of-origin, estimated effects and explained variance in its region using a commonly used SNP panel can strongly depend on the allele frequency of the underlying causal mutation. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12864-018-5126-7) contains supplementary material, which is available to authorized users. BioMed Central 2018-10-11 /pmc/articles/PMC6180412/ /pubmed/30305017 http://dx.doi.org/10.1186/s12864-018-5126-7 Text en © The Author(s). 2018 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided 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 Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research Article
Sevillano, Claudia A
ten Napel, Jan
Guimarães, Simone E F
Silva, Fabyano F
Calus, Mario P L
Effects of alleles in crossbred pigs estimated for genomic prediction depend on their breed-of-origin
title Effects of alleles in crossbred pigs estimated for genomic prediction depend on their breed-of-origin
title_full Effects of alleles in crossbred pigs estimated for genomic prediction depend on their breed-of-origin
title_fullStr Effects of alleles in crossbred pigs estimated for genomic prediction depend on their breed-of-origin
title_full_unstemmed Effects of alleles in crossbred pigs estimated for genomic prediction depend on their breed-of-origin
title_short Effects of alleles in crossbred pigs estimated for genomic prediction depend on their breed-of-origin
title_sort effects of alleles in crossbred pigs estimated for genomic prediction depend on their breed-of-origin
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6180412/
https://www.ncbi.nlm.nih.gov/pubmed/30305017
http://dx.doi.org/10.1186/s12864-018-5126-7
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