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Javier ELR, Gabriel MMJ, Candelario SCJ, Manuel PBG. Maternal effects and its importance in the genetic evaluations of preweaning live weight traits of beef cattle. A review. Trop Anim Health Prod 2024; 56:260. [PMID: 39292374 DOI: 10.1007/s11250-024-04142-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/14/2024] [Accepted: 09/11/2024] [Indexed: 09/19/2024]
Abstract
Maternal effects in cattle genetics are defined as the causal influence of the phenotype or maternal genotype on the offspring's phenotype by effects occurring when the genetic and environmental characteristics of the mother influence the phenotype of the offspring beyond the direct inheritance of genes. Its relevance has been strongly described in genetic models focused on the genetic improvement of preweaning traits in cow-calf beef cattle production systems. Here, basic concepts and the importance of maternal effects when using linear and animal model procedures for genetic evaluations of growth and live-weight traits in beef cattle are reviewed and discussed. A brief history of estimation methods from classical studies to recent studies used for the development of animal models for studying maternal effects is also provided. Some important biometric concepts for maternal effect estimation are described, and the antagonism between direct genetic effects and maternal effects, its biological basis, and sources of error in the estimation of direct genetic and maternal covariance are discussed. Finally, some genomic perspectives are presented.
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Affiliation(s)
- Estrada-León Raciel Javier
- Tecnológico Nacional de México, Instituto Tecnológico Superior de Calkiní. 24900, Calkiní, Campeche, México
| | - Magaña-Monforte Juan Gabriel
- Facultad de Medicina Veterinaria y Zootecnia, Universidad Autónoma de Yucatán, Campus de Ciencias Biológicas y Agropecuarias. 97100, Mérida, Yucatán, México
| | - Segura-Correa José Candelario
- Facultad de Medicina Veterinaria y Zootecnia, Universidad Autónoma de Yucatán, Campus de Ciencias Biológicas y Agropecuarias. 97100, Mérida, Yucatán, México
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Cardona-Cifuentes D, Neira JDR, Albuquerque LG, Espigolan R, Gonzalez-Herrera LG, Amorim ST, López-Correa RD, Aguilar I, Baldi F. Influence of variance component estimates on genomic predictions for growth and reproductive-related traits in Nellore cattle. J Anim Breed Genet 2024. [PMID: 39291375 DOI: 10.1111/jbg.12900] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/29/2024] [Revised: 07/23/2024] [Accepted: 08/20/2024] [Indexed: 09/19/2024]
Abstract
This study aimed to estimate variance components (VCs) for growth and reproductive traits in Nellore cattle using two relationship matrices (pedigree relationship A matrix and pedigree plus genomic relationship H matrix), and records collected before and after genomic selection (GS) implementation. The study also evaluated how genomic breeding values (GEBV) are affected by variance components and discarding old records. The analysed traits were weight at 120 days (W120), weight and scrotal circumference at 450 days (W450 and SC450, respectively). Three datasets were used to estimate VCs, including all phenotypic information (All) or records for animals born before or after GS implementation (Before or After datasets, respectively). Both relationship matrices were considered for VC estimation, the A matrix was used in all three datasets and VC from each combination were named as A_Before, A_After, and A_All). The H was used in two datasets: H_All and H_After. Different VCs were used for GEBV prediction through ssGBLUP. This step used two possible Datasets, using all available phenotypic data (Dataset 1) or just records collected since GS implementation (Dataset 2). Validation was conducted using accuracy, bias and dispersion according to the LR method and prediction accuracy from corrected phenotypes. The heritability of all traits increased from A_Before to A_After, while estimates for A_All were intermediary. In the previous order, the estimates were 0.16, 0.17, and 0.15 for W120; 0.31, 0.39, and 0.35 for W450; 0.35, 0.47, and 0.41 for SC. For W450 and SC, using the H matrix reduced the heritability (0.33 and 0.32 for W450; 0.41 and 0.38 for SC for H_After and H_All, respectively). For W120, Dataset1 and VCs from A_After showed the highest accuracy for direct and maternal GEBV (0.953 and 0.868). For W450, Dataset 1 and VC from H_After allowed the highest accuracy (0.854) but use Dataset 2 and same VC source yield similar value (0.846). For SC, Dataset 2 with VC from H_After showed the highest accuracy (0.925). To use Dataset 2 does not cause important changes in bias or dispersion with respect to Dataset 1. The VC and genetic parameters changed for W120, W450, and SC450, using records before or after the GS implementation. For W450 and SC450, genetic variance and heritability estimates increased with the use of GS. For W120, genomic predictions were more accurate using A for VC estimation. Accuracy gains were observed for W450 and SC450 using H in VC estimation and/or discarding records before GS. It is possible to discard phenotypic records before GS implementation without generating bias or dispersion in the GEBV of young candidates.
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Affiliation(s)
- Daniel Cardona-Cifuentes
- Departamento de Zootecnia, Faculdade de Ciências Agrarias e Veterinárias, Universidade Estadual Paulista (UNESP), Jaboticabal, SP, Brazil
- Facultad de Ciencias Agrarias, Fundación Universitaria Agraria de Colombia-UNIAGRARIA, Bogotá, Colombia
| | | | - Lucia G Albuquerque
- Departamento de Zootecnia, Faculdade de Ciências Agrarias e Veterinárias, Universidade Estadual Paulista (UNESP), Jaboticabal, SP, Brazil
- Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq), Brasilia, Brazil
| | - Rafael Espigolan
- Departamento de Zootecnia e Ciências Biológicas, Universidade Federal de Santa Maria, Palmeira das Missões, RS, Brazil
| | - Luis Gabriel Gonzalez-Herrera
- Grupo de Investigación Biodiversidad y Genética Molecular (BIOGEM), Universidad Nacional de Colombia Sede Medellín, Medellín, Colombia
| | - Sabrina Thaise Amorim
- Department of Animal and Food Sciences, Oklahoma State University, Stillwater, Oklahoma, USA
| | | | - Ignacio Aguilar
- Instituto Nacional de Investigación Agropecuaria (INIA), Montevideo, Uruguay
| | - Fernando Baldi
- Departamento de Zootecnia, Faculdade de Ciências Agrarias e Veterinárias, Universidade Estadual Paulista (UNESP), Jaboticabal, SP, Brazil
- Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq), Brasilia, Brazil
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Carrara ER, Peixoto MGCD, da Silva AA, Bruneli FAT, Ventura HT, Zadra LEF, Josahkian LA, Veroneze R, Lopes PS. Genomic prediction in Brazilian Guzerá cattle: application of a single-step approach to productive and reproductive traits. Trop Anim Health Prod 2023; 55:48. [PMID: 36705782 DOI: 10.1007/s11250-023-03484-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/13/2022] [Accepted: 01/23/2023] [Indexed: 01/28/2023]
Abstract
This study aimed to investigate the feasibility of genomic prediction for productive and reproductive traits in Guzerá cattle using single-step genomic best linear unbiased prediction (ssGBLUP). Evaluations included the 305-day cumulative yields (first lactation, in kg) of milk, lactose, protein, fat, and total solids; adjusted body weight (kg) at the ages of 450, 365, and 210 days; and age at first calving (in days), from a database containing 197,283 measurements from Guzerá males and females born between 1954 and 2018. The pedigree included 433,823 animals spanning up to 14 overlapping generations. A total of 1618 animals were genotyped. The analyses were performed using ssGBLUP and traditional BLUP methods. Predictive ability and bias were accessed using cross-validation: predictive ability was similar between the methods and ranged from 0.27 to 0.47 for the genomic-based model and from 0.30 to 0.45 for the pedigree-based model; the bias was also similar between the methods, ranging from 0.88 to 1.35 in the genomic-based model and from 0.96 to 1.41 in the pedigree-based model. The individual accuracies of breeding values were evidently increased in the genomic evaluation, with values ranging from 0.41 to 0.56 in the genomic-based model and from 0.26 to 0.54 in the pedigree-based model. Even based on a small number of genotyped animals and a small database for some traits, the results suggest that ssGBLUP is feasible and may be applied to national genetic evaluation of the breed to increase the accuracy of breeding values without greatly impacting predictive ability and bias.
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Affiliation(s)
- Eula Regina Carrara
- Department of Animal Science, Federal University of Viçosa, Viçosa, Minas Gerais, Brazil.
| | | | - Alessandra Alves da Silva
- Department of Agricultural Sciences, School of Agricultural and Veterinarian Sciences, São Paulo State University, Jaboticabal, São Paulo, Brazil
| | | | | | - Lenira El Faro Zadra
- Brazilian Center for the Genetic Improvement of Guzerá, Belo Horizonte, Minas Gerais, Brazil
| | | | - Renata Veroneze
- Department of Animal Science, Federal University of Viçosa, Viçosa, Minas Gerais, Brazil
| | - Paulo Sávio Lopes
- Department of Animal Science, Federal University of Viçosa, Viçosa, Minas Gerais, Brazil
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Bonifazi R, Calus MPL, Ten Napel J, Veerkamp RF, Michenet A, Savoia S, Cromie A, Vandenplas J. International single-step SNPBLUP beef cattle evaluations for Limousin weaning weight. Genet Sel Evol 2022; 54:57. [PMID: 36057564 PMCID: PMC9441073 DOI: 10.1186/s12711-022-00748-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/11/2021] [Accepted: 07/22/2022] [Indexed: 11/30/2022] Open
Abstract
Background Compared to national evaluations, international collaboration projects further improve accuracies of estimated breeding values (EBV) by building larger reference populations or performing a joint evaluation using data (or proxy of them) from different countries. Genomic selection is increasingly adopted in beef cattle, but, to date, the benefits of including genomic information in international evaluations have not been explored. Our objective was to develop an international beef cattle single-step genomic evaluation and investigate its impact on the accuracy and bias of genomic evaluations compared to current pedigree-based evaluations. Methods Weaning weight records were available for 331,593 animals from seven European countries. The pedigree included 519,740 animals. After imputation and quality control, 17,607 genotypes at a density of 57,899 single nucleotide polymorphisms (SNPs) from four countries were available. We implemented two international scenarios where countries were modelled as different correlated traits: an international genomic single-step SNP best linear unbiased prediction (SNPBLUP) evaluation (ssSNPBLUPINT) and an international pedigree-based BLUP evaluation (PBLUPINT). Two national scenarios were implemented for pedigree and genomic evaluations using only nationally submitted phenotypes and genotypes. Accuracies, level and dispersion bias of EBV of animals born from 2014 onwards, and increases in population accuracies were estimated using the linear regression method. Results On average across countries, 39 and 17% of sires and maternal-grand-sires with recorded (grand-)offspring across two countries were genotyped. ssSNPBLUPINT showed the highest accuracies of EBV and, compared to PBLUPINT, led to increases in population accuracy of 13.7% for direct EBV, and 25.8% for maternal EBV, on average across countries. Increases in population accuracies when moving from national scenarios to ssSNPBLUPINT were observed for all countries. Overall, ssSNPBLUPINT level and dispersion bias remained similar or slightly reduced compared to PBLUPINT and national scenarios. Conclusions International single-step SNPBLUP evaluations are feasible and lead to higher population accuracies for both large and small countries compared to current international pedigree-based evaluations and national evaluations. These results are likely related to the larger multi-country reference population and the inclusion of phenotypes from relatives recorded in other countries via single-step international evaluations. The proposed international single-step approach can be applied to other traits and breeds. Supplementary Information The online version contains supplementary material available at 10.1186/s12711-022-00748-0.
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Affiliation(s)
- Renzo Bonifazi
- Animal Breeding and Genomics, Wageningen University & Research, P.O. Box 338, 6700 AH, Wageningen, The Netherlands.
| | - Mario P L Calus
- Animal Breeding and Genomics, Wageningen University & Research, P.O. Box 338, 6700 AH, Wageningen, The Netherlands
| | - Jan Ten Napel
- Animal Breeding and Genomics, Wageningen University & Research, P.O. Box 338, 6700 AH, Wageningen, The Netherlands
| | - Roel F Veerkamp
- Animal Breeding and Genomics, Wageningen University & Research, P.O. Box 338, 6700 AH, Wageningen, The Netherlands
| | - Alexis Michenet
- Interbull Centre-Department of Animal Breeding and Genetics, SLU-Box 7023, S-75007, Uppsala, Sweden
| | - Simone Savoia
- Interbull Centre-Department of Animal Breeding and Genetics, SLU-Box 7023, S-75007, Uppsala, Sweden
| | - Andrew Cromie
- Irish Cattle Breeding Federation, Link Road, Ballincollig, P31 D452, Co Cork, Ireland
| | - Jérémie Vandenplas
- Animal Breeding and Genomics, Wageningen University & Research, P.O. Box 338, 6700 AH, Wageningen, The Netherlands
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