Obtaining unbiased estimates of the direct-maternal genetic correlation proves far from straightforward for several reasons. Consequently, the use of such over- or underestimated correlations may introduce errors in genetic evaluation models. The objective of our study was to evaluate how the value of the direct-maternal genetic correlation affects EBV. Direct, maternal, and total breeding values were predicted for the ADG or weight at weaning for 3 different species (sheep, rabbits, and pigs) using models that differ depending on the fixed value of the direct-maternal genetic correlation (ranging from -0.9 to 0.9) as well as a model in which the correlation was estimated. The results were consistent between species. The direct-maternal genetic correlation had a greater impact on the estimated maternal genetic effects than on direct effects. The lowest correlations between maternal breeding values obtained with different models were -0.20, -0.01, and -0.72 in pigs, sheep, and rabbits, respectively, whereas for the direct breeding value, the lowest correlations were 0.45, 0.90, and 0.95 in pigs, sheep, and rabbits, respectively. The total EBV, calculated as the unweighted sum of direct and maternal genetic effects, did not differ greatly between the models, the lowest correlations between total breeding values being 0.93, 0.98, and 0.97 for pigs, sheep, and rabbits, respectively. Given the uncertainty associated with estimating the direct-maternal genetic correlation, setting its value to 0 in genetic evaluation models appears to be a good compromise.
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http://dx.doi.org/10.2527/jas.2015-9548 | DOI Listing |
Animals (Basel)
December 2024
Department of Physiology & Cell Biology, University of Arkansas for Medical Sciences, 4301 West Markham Street, Little Rock, AR 72205, USA.
This study investigated the genetic parameters for serum IGF-I concentrations and growth traits in beef cattle. A divergent selection experiment for serum IGF-I concentration was initiated in 1989. One hundred spring-calving (50 high line and 50 low line) and 100 fall-calving (50 high line and 50 low line) black Angus cows with unknown IGF-I concentrations were randomly assigned to the two divergent selection lines.
View Article and Find Full Text PDFJ Anim Sci
January 2024
Department of Animal and Dairy Science, University of Georgia, Athens, GA 30602, USA.
Threshold models are often used in genetic analysis of categorical data, such as calving ease. Solutions in the liability scale are easily transformed into probabilities; therefore, estimated breeding values are published as the probability of expressing the category of main interest and are the industry's gold standard because they are easy to interpret and use for selection. However, because threshold models involve nonlinear equations and probability functions, implementing such a method is complex.
View Article and Find Full Text PDFTrop Anim Health Prod
September 2024
Centro de Biotecnología Genómica, Instituto Politécnico Nacional, 88710, Reynosa, Tamaulipas, México.
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.
View Article and Find Full Text PDFJ Evol Biol
May 2024
Centre for Ecology and Conservation, Biosciences, University of Exeter, Cornwall TR10 9FE, United Kingdom.
Animals (Basel)
September 2023
Institute for Animal Science and Technology, Universitat Politècnica de València, 46022 Valencia, Spain.
Maternal genetic effects (MGE) could affect meat quality traits such as intramuscular fat (IMF) and its fatty acid composition. However, it has been scarcely studied, especially in rabbits. The objectives of the present study were, first, to assess the importance of MGE on intramuscular fat and fatty acid composition by applying a Bayesian maternal animal model in two rabbit lines divergently selected for IMF.
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