Please use this identifier to cite or link to this item: https://hdl.handle.net/1959.11/51598
Title: Determination of optimum weighting factors for single-step genetic evaluation via genetic variance partitioning
Contributor(s): Torres-Vázquez, J A  (author)orcid ; Samaraweera, A M  (author)orcid ; Jeyaruban, M G  (author)orcid ; Johnston, D J  (author)orcid ; Boerner, V  (author)
Publication Date: 2021
Open Access: Yes
Handle Link: https://hdl.handle.net/1959.11/51598
Open Access Link: http://www.aaabg.org/aaabghome/proceedings24.phpOpen Access Link
Abstract: 

It is important in single-step genetic evaluations to use appropriate lambdas (λ) for calculating weighted average of NRM (numerator relationship matrix) and GRM (genomic relationship matrix) in joint relationship matrix. λ is usually estimated using a single-trait cross-validation procedure. However, it can be shown that a univariate single-step model applying a scalar λ is simply a condensed form of an extended model containing two genetic factors, factor H~N(0, H) and factor A~N(0, A), where the partitioning of the total genetic variance reflects λ. For multivariate single-step genetic evaluation, this model condensation implies that all involved genetic variances may yield the same λ, which is highly unlikely. Hence, it is required to estimate λ by accounting for its heterogeneity using the extended model for variance component estimation. This study used an extended single-step model to estimate variances and λs for calving difficulty (CD), gestation length (GL), and birth weight (BW) using Australian Angus data. A total of 129,851 animals with 45,575 genotypes were analysed. Initial variances obtained from a pedigree-only model were then used as starting values for the extended single-step model assigning 90% of the genetic variance to factor A and 10% to factor H. Since CD is a categorical trait with three categories, a threshold model-Gibbs sampling method was used to estimate variances. Heritability estimates for the extended single-step model were very similar to those from the pedigree only model implying that the single-step model was not explaining more variation in the data than the pedigree only model. For CD, GL, and BW, the total heritability estimates were 0.39 ± 0.04, 0.68 ± 0.02, and 0.44 ± 0.01, respectively. For the same traits, the total maternal heritability estimates were 0.17 ± 0.02, 0.11 ± 0.01, and 0.09 ± 0.01, respectively. In contrast, to the Gibbs sampling starting values, the genetic variance was partitioned between A and H such that direct genetic λ estimates for CD, GL, and BW were 0.36 ± 0.05, 0.62 ± 0.03, 0.75 ± 0.03, respectively. Maternal genetic λ estimates ranged from 0.01 ± 0.01 (for BW) to 0.05 ± 0.01 (for CD). The results imply that λ values are heterogeneous in multivariate single-step genomic evaluation. Further studies are needed to investigate the consequences of using heterogenous λ values for direct genetic and maternal genetic components in multivariate single-step evaluation in terms of model dimensions, solver convergence rate, and model forward predictive ability.

Publication Type: Conference Publication
Conference Details: AAABG 2021: 24th Conference of the Association for the Advancement of Animal Breeding and Genetics, Online Event, 2nd - 4th November, 2028
Source of Publication: Proceedings of the Association for the Advancement of Animal Breeding and Genetics, v.24, p. 402-405
Publisher: Association for the Advancement of Animal Breeding and Genetics (AAABG)
Place of Publication: Armidale, Australia
ISSN: 1328-3227
Fields of Research (FoR) 2020: 300301 Animal growth and development
Socio-Economic Objective (SEO) 2020: 100401 Beef cattle
Peer Reviewed: Yes
HERDC Category Description: E1 Refereed Scholarly Conference Publication
Publisher/associated links: http://www.aaabg.org/aaabghome/
Description: Paper presented by Gilbert Jeyaruban
Appears in Collections:Animal Genetics and Breeding Unit (AGBU)
Conference Publication

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