IMPACT ON GENOMIC PREDICTION OF MIXING BETWEEN PARALLEL YEARS GROUPS IN ATLANTIC SALMON BREEDING PROGRAMS

Panagiotis Kokkinias

Research output: Contribution to conferenceAbstractpeer-review

Abstract

Because of the reproductive biology of Atlantic salmon, farmed populations typically follow a breeding program characterised by discrete generations with interval of four years. This results in the formation of four independent parallel lines within a breeding program. Genomic selection (GS) allows simultaneously using the information from parallel lines and, thereby, increasing the size of the reference population. However, despite all lines having a common selection objective, their relative isolation could have resulted in genetic differentiation, reducing the genetic relatedness between them. This could affect selection accuracy, as the candidates would be only distantly related to a large part of the reference population. GS might need to be implemented within each parallel line, leading to smaller reference populations and, eventually, a lower selection accuracy. Bringing in candidates from one line to another (‘mixing’) to connect the lines could improve GS accuracy. The aim of this study was to investigate the impact of various mixing strategies on the accuracy of prediction from genomic evaluation across lines.

The effect of mixing between lines was tested by simulation. A salmon population was simulated assuming four parallel lines (500 fish/line) derived from a common ancestral population (lines were genetically related but drift started to differentiate them). One line reproduced each year in a rotational manner, so each line produced offspring every four years. In a given year, the next generation for a given line was created by randomly selecting four year old candidate parents from that line plus a proportion of three year old candidate parents from a parallel line. Each selected candidate has two randomly assigned mates to produce two full sib families of equal size. Ten discrete generations were created by line. Genetic distance between individuals (within and across lines) was calculated at each generation to study the impact of the mixing rate on genetic differentiation between lines. The accuracy of the breeding values from genomic evaluation achieved within and across population was compared. The relationship between the accuracy and degree of genetic distance between lines was quantified to determine the optimum mixing strategy to improve genetic prediction in farmed salmon.
Original languageEnglish
Publication statusPublished - Jul 2018
Event'Empowering aquaculture through the application of modern genetics' - Cairns, Queensland Australia, Queensland, Australia
Duration: 15 Jul 201820 Jul 2018

Conference

Conference'Empowering aquaculture through the application of modern genetics'
Country/TerritoryAustralia
CityQueensland
Period15/07/1820/07/18

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