Spatial modelling improves genetic evaluation in smallholder breeding programs.

Genetics, Selection, Evolution : GSE
Maria L SelleGregor Gorjanc

Abstract

Breeders and geneticists use statistical models to separate genetic and environmental effects on phenotype. A common way to separate these effects is to model a descriptor of an environment, a contemporary group or herd, and account for genetic relationship between animals across environments. However, separating the genetic and environmental effects in smallholder systems is challenging due to small herd sizes and weak genetic connectedness across herds. We hypothesised that accounting for spatial relationships between nearby herds can improve genetic evaluation in smallholder systems. Furthermore, geographically referenced environmental covariates are increasingly available and could model underlying sources of spatial relationships. The objective of this study was therefore, to evaluate the potential of spatial modelling to improve genetic evaluation in dairy cattle smallholder systems. We performed simulations and real dairy cattle data analysis to test our hypothesis. We modelled environmental variation by estimating herd and spatial effects. Herd effects were considered independent, whereas spatial effects had distance-based covariance between herds. We compared these models using pedigree or genomic data. The results sho...Continue Reading

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Citations

Aug 8, 2021·Animals : an Open Access Journal From MDPI·Beatriz Castro Dias CuyabanoCedric Gondro
Sep 12, 2021·Genetics, Selection, Evolution : GSE·Mohammad Al KalaldehJohn P Gibson

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Software Mentioned

AlphaSimR
INLA
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