The correlation of substitution effects across populations and generations in the presence of nonadditive functional gene action

Author:

Legarra Andres1ORCID,Garcia-Baccino Carolina A.123,Wientjes Yvonne C. J.4ORCID,Vitezica Zulma G.1

Affiliation:

1. INRAE/INP, UMR 1388 GenPhySE, Castanet-Tolosan 31326, France

2. Departamento de Producción Animal, Facultad de Agronomía, Universidad de Buenos Aires, Buenos Aires C1417DSQ, Argentina

3. SAS NUCLEUS, Le Rheu 35650, France

4. Wageningen University & Research, Animal Breeding and Genomics, Wageningen 6700 AH, the Netherlands

Abstract

Abstract Allele substitution effects at quantitative trait loci (QTL) are part of the basis of quantitative genetics theory and applications such as association analysis and genomic prediction. In the presence of nonadditive functional gene action, substitution effects are not constant across populations. We develop an original approach to model the difference in substitution effects across populations as a first order Taylor series expansion from a “focal” population. This expansion involves the difference in allele frequencies and second-order statistical effects (additive by additive and dominance). The change in allele frequencies is a function of relationships (or genetic distances) across populations. As a result, it is possible to estimate the correlation of substitution effects across two populations using three elements: magnitudes of additive, dominance, and additive by additive variances; relationships (Nei’s minimum distances or Fst indexes); and assumed heterozygosities. Similarly, the theory applies as well to distinct generations in a population, in which case the distance across generations is a function of increase of inbreeding. Simulation results confirmed our derivations. Slight biases were observed, depending on the nonadditive mechanism and the reference allele. Our derivations are useful to understand and forecast the possibility of prediction across populations and the similarity of GWAS effects.

Funder

GenPhySE

INRAE

Netherlands Organisation of Scientific Research

European Unions’ Horizon 2020 Research & Innovation programme

Publisher

Oxford University Press (OUP)

Subject

Genetics

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