ImmuneDEX: updated genomic estimates of genetic parameters and breeding values for Australian Angus cattle
Antonio Reverter
A D , Brad C. Hine B , Laercio Porto-Neto A , Pamela A. Alexandre A , Yutao Li A , Christian J. Duff C , Sonja Dominik B and Aaron B. Ingham A
A CSIRO Agriculture & Food, Queensland Bioscience Precinct, 306 Carmody Road, St Lucia, Brisbane, Qld 4067, Australia.
B CSIRO Agriculture & Food, F.D. McMaster Laboratory, Chiswick, New England Highway, Armidale, NSW 2350, Australia.
C Angus Australia, 86 Glen Innes Road, Armidale, NSW 2350, Australia.
D Corresponding author. Email: tony.reverter-gomez@csiro.au
Animal Production Science - https://doi.org/10.1071/AN21054
Submitted: 5 February 2021 Accepted: 11 June 2021 Published online: 17 August 2021
Journal Compilation © CSIRO 2021 Open Access CC BY-NC-ND
Abstract
Context: Immune competence is a proxy trait for general disease resistance and is based on combined measures of an animal’s ability to mount both a cell-mediated immune response (Cell-IR) and an antibody-mediated immune response (Ab-IR). On the basis of previously described arithmetic, we combined these measures into a single proxy trait for immune competence, named ImmuneDEX (IDEX).
Aims: Using a population of 3715 Australian Angus steers (n = 2395) and heifers (n = 1320) with genotypes for 45 364 single-nucleotide polymorphisms, we provide the latest genomic estimates of heritability and genetic correlations for IDEX and the components Cell-IR and Ab-IR immune competence phenotypes. Accuracy and bias of genomic predictions of breeding values are also presented and discussed.
Methods: Measures of Cell-IR, Ab-IR and IDEX were analysed jointly in a tri-variate genomic restricted maximum-likelihood model that contained the fixed effects of contemporary group with 80 levels, the linear covariates of age at measurement and change in skin thickness at control site, and the random polygenic (genomic estimated breeding value, GEBV) and residual effects. Following Method LR procedures, we estimate accuracy, bias and dispersion of genomic predictions using a cross-validation scheme based on five year-of-birth cohorts.
Key results: We report genomic restricted maximum-likelihood model estimates of heritability of 0.247 ± 0.040 for Cell-IR, 0.326 ± 0.059 for Ab-IR, 0.275 ± 0.046 for IDEX. While a small positive genetic correlation (rg) was estimated between Cell-IR and Ab-IR (rg = 0.138 ± 0.095), strongly positive estimates were obtained between IDEX and Cell-IR (rg = 0.740 ± 0.044) and between IDEX and Ab-IR (rg = 0.741 ± 0.036). Averaged across the five validation sets, the accuracy of GEBV for Cell-IR, Ab-IR and IDEX was 0.405, 0.443 and 0.411 respectively. Also, some significant bias or dispersion can be expected depending on the cohort used as the validation population.
Conclusions: Consistent with previous findings, immune competence phenotypes are moderately heritable and accurate GEBV can be generated to allow the selection of cattle with an improved ability to mount a general immune response.
Implications: Our analyses suggest that ImmuneDEX will provide a tool to underpin long-term genetic strategies aimed at improving the immune competence of Australian Angus cattle in production systems, which, in turn, is expected to reduce the incidence of disease and our reliance on antibiotics to treat disease.
Keywords: beef cattle, heritability, immune competence, genomic predictions, accuracy.
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