Optimising genomic breeding of farmed salmon
The relatively recent domestication of aquaculture species, such as Atlantic salmon, produces both significant challenges and substantial opportunities for the use of genomic tools in animal breeding which could improve both production and welfare. The recent development of single-nucleotide polymor...
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The University of Edinburgh
2022
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ftunivedinburgh:oai:era.ed.ac.uk:1842/38810 2023-07-30T04:02:24+02:00 Optimising genomic breeding of farmed salmon Kokkinias, Panagiotis Navarro, Pau Pong-Wong, Ricardo Houston, Ross Hamilton, Alastair Haley, Chris 2022-03-25 application/pdf https://hdl.handle.net/1842/38810 https://doi.org/10.7488/era/2064 en eng The University of Edinburgh https://hdl.handle.net/1842/38810 http://dx.doi.org/10.7488/era/2064 Thesis or Dissertation Doctoral PhD Doctor of Philosophy 2022 ftunivedinburgh https://doi.org/10.7488/era/2064 2023-07-09T20:30:56Z The relatively recent domestication of aquaculture species, such as Atlantic salmon, produces both significant challenges and substantial opportunities for the use of genomic tools in animal breeding which could improve both production and welfare. The recent development of single-nucleotide polymorphism (SNP) genotyping arrays raises the possibility of substantially increasing rates of genetic improvement using genomic selection approaches. Genomic selection utilises computational analysis to combine genome-wide SNP data with trait information to identify individuals carrying the best of the naturally occurring genetic variation for desirable characteristics and hence select the best fish to breed future generations. The project is a collaboration with Landcatch (Hendrix Genetics), a salmon breeding company in Scotland with an extensive experience in genetic breeding programmes, which provide data from several different populations of salmon that have been recorded for traits such as body weight per year, growth and sex. This thesis aimed to investigate the efficiency of genomic prediction within and between populations, by 1) exploring the structure of farmed salmon populations and their genetic diversity, 2) simulating a similar breeding scheme and investigating the impact of various mixing strategies on the accuracy of prediction from genomic evaluation across populations under random and directional selection, 3) estimating the heritability, based on both closely and distantly related individuals, by estimating pedigree-like and SNP-based heritability simultaneously in a single model and 4) investigating the genetic basis of sexual determination and differentiation of farmed Atlantic salmon populations in order to increase the efficiency of breeding programmes. In Atlantic salmon, the broodstock populations follow a breeding programme characterised by discrete generations with a four-year generation interval. This results in the formation of up to four separate parallel lines (‘year groups’) with only ... Doctoral or Postdoctoral Thesis Atlantic salmon Edinburgh Research Archive (ERA - University of Edinburgh) |
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Edinburgh Research Archive (ERA - University of Edinburgh) |
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ftunivedinburgh |
language |
English |
description |
The relatively recent domestication of aquaculture species, such as Atlantic salmon, produces both significant challenges and substantial opportunities for the use of genomic tools in animal breeding which could improve both production and welfare. The recent development of single-nucleotide polymorphism (SNP) genotyping arrays raises the possibility of substantially increasing rates of genetic improvement using genomic selection approaches. Genomic selection utilises computational analysis to combine genome-wide SNP data with trait information to identify individuals carrying the best of the naturally occurring genetic variation for desirable characteristics and hence select the best fish to breed future generations. The project is a collaboration with Landcatch (Hendrix Genetics), a salmon breeding company in Scotland with an extensive experience in genetic breeding programmes, which provide data from several different populations of salmon that have been recorded for traits such as body weight per year, growth and sex. This thesis aimed to investigate the efficiency of genomic prediction within and between populations, by 1) exploring the structure of farmed salmon populations and their genetic diversity, 2) simulating a similar breeding scheme and investigating the impact of various mixing strategies on the accuracy of prediction from genomic evaluation across populations under random and directional selection, 3) estimating the heritability, based on both closely and distantly related individuals, by estimating pedigree-like and SNP-based heritability simultaneously in a single model and 4) investigating the genetic basis of sexual determination and differentiation of farmed Atlantic salmon populations in order to increase the efficiency of breeding programmes. In Atlantic salmon, the broodstock populations follow a breeding programme characterised by discrete generations with a four-year generation interval. This results in the formation of up to four separate parallel lines (‘year groups’) with only ... |
author2 |
Navarro, Pau Pong-Wong, Ricardo Houston, Ross Hamilton, Alastair Haley, Chris |
format |
Doctoral or Postdoctoral Thesis |
author |
Kokkinias, Panagiotis |
spellingShingle |
Kokkinias, Panagiotis Optimising genomic breeding of farmed salmon |
author_facet |
Kokkinias, Panagiotis |
author_sort |
Kokkinias, Panagiotis |
title |
Optimising genomic breeding of farmed salmon |
title_short |
Optimising genomic breeding of farmed salmon |
title_full |
Optimising genomic breeding of farmed salmon |
title_fullStr |
Optimising genomic breeding of farmed salmon |
title_full_unstemmed |
Optimising genomic breeding of farmed salmon |
title_sort |
optimising genomic breeding of farmed salmon |
publisher |
The University of Edinburgh |
publishDate |
2022 |
url |
https://hdl.handle.net/1842/38810 https://doi.org/10.7488/era/2064 |
genre |
Atlantic salmon |
genre_facet |
Atlantic salmon |
op_relation |
https://hdl.handle.net/1842/38810 http://dx.doi.org/10.7488/era/2064 |
op_doi |
https://doi.org/10.7488/era/2064 |
_version_ |
1772813194230759424 |