Identification of Genomic Variants Causing Variation in Quantitative Traits: A Review

Theo Meuwissen, Ben Hayes, Iona MacLeod and Michael Goddard ()
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Theo Meuwissen: Faculty of Biosciences, Norwegian University of Life Sciences, P.O. Box 5003, 1432 As, Norway
Ben Hayes: Queensland Alliance for Agriculture and Food Innovation, The University of Queensland, St Lucia, QLD 4072, Australia
Iona MacLeod: Agriculture Victoria Research, Agribio, Bundoora, VIC 3083, Australia
Michael Goddard: Agriculture Victoria Research, Agribio, Bundoora, VIC 3083, Australia

Agriculture, 2022, vol. 12, issue 10, 1-11

Abstract: Many of the important traits of livestock are complex or quantitative traits controlled by thousands of variants in the DNA sequence of individual animals and environmental factors. Identification of these causal variants would be advantageous for genomic prediction, to understand the physiology and evolution of important traits and for genome editing. However, it is difficult to identify these causal variants because their effects are small and they are in linkage disequilibrium with other DNA variants. Nevertheless, it should be possible to identify probable causal variants for complex traits just as we do for simple traits provided we compensate for the small effect size with larger sample size. In this review we consider eight types of evidence needed to identify causal variants. Large and diverse samples of animals, accurate genotypes, multiple phenotypes, annotation of genomic sites, comparisons across species, comparisons across the genome, the physiological role of candidate genes and experimental mutation of the candidate genomic site.

Keywords: genomic prediction; causal variants; linkage disequilibrium; quantitative trait loci (search for similar items in EconPapers)
JEL-codes: Q1 Q10 Q11 Q12 Q13 Q14 Q15 Q16 Q17 Q18 (search for similar items in EconPapers)
Date: 2022
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