Literature DB >> 24492557

Sire evaluation for total number born in pigs using a genomic reaction norms approach.

F F Silva1, H A Mulder2, E F Knol3, M S Lopes3, S E F Guimarães4, P S Lopes4, P K Mathur3, J M S Viana5, J W M Bastiaansen2.   

Abstract

In the era of genome-wide selection (GWS), genotype-by-environment (G×E) interactions can be studied using genomic information, thus enabling the estimation of SNP marker effects and the prediction of genomic estimated breeding values (GEBV) for young candidates for selection in different environments. Although G×E studies in pigs are scarce, the use of artificial insemination has enabled the distribution of genetic material from sires across multiple environments. Given the relevance of reproductive traits, such as the total number born (TNB) and the variation in environmental conditions encountered by commercial dams, understanding G×E interactions can be essential for choosing the best sires for different environments. The present work proposes a two-step reaction norm approach for G×E analysis using genomic information. The first step provided estimates of environmental effects (herd-year-season, HYS), and the second step provided estimates of the intercept and slope for the TNB across different HYS levels, obtained from the first step, using a random regression model. In both steps, pedigree ( A: ) and genomic ( G: ) relationship matrices were considered. The genetic parameters (variance components, h(2) and genetic correlations) were very similar when estimated using the A: and G: relationship matrices. The reaction norm graphs showed considerable differences in environmental sensitivity between sires, indicating a reranking of sires in terms of genetic merit across the HYS levels. Based on the G: matrix analysis, SNP by environment interactions were observed. For some SNP, the effects increased at increasing HYS levels, while for others, the effects decreased at increasing HYS levels or showed no changes between HYS levels. Cross-validation analysis demonstrated better performance of the genomic approach with respect to traditional pedigrees for both the G×E and standard models. The genomic reaction norm model resulted in an accuracy of GEBV for "juvenile" boars varying from 0.14 to 0.44 across different HYS levels, while the accuracy of the standard genomic prediction model, without reaction norms, varied from 0.09 to 0.28. These results show that it is important and feasible to consider G×E interactions in evaluations of sires using genomic prediction models and that genomic information can increase the accuracy of selection across environments.

Entities:  

Keywords:  SNP markers; genotype by environment interaction; random regression

Mesh:

Year:  2014        PMID: 24492557     DOI: 10.2527/jas.2013-6486

Source DB:  PubMed          Journal:  J Anim Sci        ISSN: 0021-8812            Impact factor:   3.159


  16 in total

1.  Gene networks for total number born in pigs across divergent environments.

Authors:  Lucas L Verardo; Marcos S Lopes; Pramod Mathur; Ole Madsen; Fabyano F Silva; Martien A M Groenen; Egbert F Knol; Paulo S Lopes; Simone E F Guimarães
Journal:  Mamm Genome       Date:  2017-06-02       Impact factor: 2.957

2.  Reaction norm for yearling weight in beef cattle using single-step genomic evaluation.

Authors:  D P Oliveira; D A L Lourenco; S Tsuruta; I Misztal; D J A Santos; F R de Araújo Neto; R R Aspilcueta-Borquis; F Baldi; R Carvalheiro; G M F de Camargo; L G Albuquerque; H Tonhati
Journal:  J Anim Sci       Date:  2018-02-15       Impact factor: 3.159

3.  Genomic Selection Improves Response to Selection in Resilience by Exploiting Genotype by Environment Interactions.

Authors:  Han A Mulder
Journal:  Front Genet       Date:  2016-10-13       Impact factor: 4.599

4.  Environment-Dependent Genotype-Phenotype Associations in Avian Breeding Time.

Authors:  Phillip Gienapp; Veronika N Laine; A C Mateman; Kees van Oers; Marcel E Visser
Journal:  Front Genet       Date:  2017-08-04       Impact factor: 4.599

5.  Genomic selection for crossbred performance accounting for breed-specific effects.

Authors:  Marcos S Lopes; Henk Bovenhuis; André M Hidalgo; Johan A M van Arendonk; Egbert F Knol; John W M Bastiaansen
Journal:  Genet Sel Evol       Date:  2017-06-26       Impact factor: 4.297

6.  Genotype-by-environment interaction of fertility traits in Danish Holstein cattle using a single-step genomic reaction norm model.

Authors:  Zhe Zhang; Morten Kargo; Aoxing Liu; Jørn Rind Thomasen; Yuchun Pan; Guosheng Su
Journal:  Heredity (Edinb)       Date:  2019-02-13       Impact factor: 3.821

7.  Genotype-by-environment interaction in Holstein heifer fertility traits using single-step genomic reaction norm models.

Authors:  Rui Shi; Luiz Fernando Brito; Aoxing Liu; Hanpeng Luo; Ziwei Chen; Lin Liu; Gang Guo; Herman Mulder; Bart Ducro; Aart van der Linden; Yachun Wang
Journal:  BMC Genomics       Date:  2021-03-17       Impact factor: 3.969

8.  Genotype-by-environment interactions for reproduction, body composition, and growth traits in maternal-line pigs based on single-step genomic reaction norms.

Authors:  Shi-Yi Chen; Pedro H F Freitas; Hinayah R Oliveira; Sirlene F Lázaro; Yi Jian Huang; Jeremy T Howard; Youping Gu; Allan P Schinckel; Luiz F Brito
Journal:  Genet Sel Evol       Date:  2021-06-17       Impact factor: 4.297

9.  Utilization of farm animal genetic resources in a changing agro-ecological environment in the Nordic countries.

Authors:  Juha Kantanen; Peter Løvendahl; Erling Strandberg; Emma Eythorsdottir; Meng-Hua Li; Anne Kettunen-Præbel; Peer Berg; Theo Meuwissen
Journal:  Front Genet       Date:  2015-02-25       Impact factor: 4.599

10.  Genome-wide scan highlights the role of candidate genes on phenotypic plasticity for age at first calving in Nellore heifers.

Authors:  Lucio F M Mota; Fernando B Lopes; Gerardo A Fernandes Júnior; Guilherme J M Rosa; Ana F B Magalhães; Roberto Carvalheiro; Lucia G Albuquerque
Journal:  Sci Rep       Date:  2020-04-15       Impact factor: 4.379

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