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Whole-genome mapping of quantitative trait loci and accuracy of genomic predictions for resistance to columnaris disease in two rainbow trout breeding populations
Columnaris disease (CD) is an emerging problem for the rainbow trout aquaculture industry in the US. The objectives of this study were to: (1) identify common genomic regions that explain a large proportion of the additive genetic variance for resistance to CD in two rainbow trout (Oncorhynchus myki...
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Published in: | Genetics selection evolution (Paris) 2019-08, Vol.51 (1), p.42-42, Article 42 |
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description | Columnaris disease (CD) is an emerging problem for the rainbow trout aquaculture industry in the US. The objectives of this study were to: (1) identify common genomic regions that explain a large proportion of the additive genetic variance for resistance to CD in two rainbow trout (Oncorhynchus mykiss) populations; and (2) estimate the gains in prediction accuracy when genomic information is used to evaluate the genetic potential of survival to columnaris infection in each population.
Two aquaculture populations were investigated: the National Center for Cool and Cold Water Aquaculture (NCCCWA) odd-year line and the Troutlodge, Inc., May odd-year (TLUM) nucleus breeding population. Fish that survived to 21 days post-immersion challenge were recorded as resistant. Single nucleotide polymorphism (SNP) genotypes were available for 1185 and 1137 fish from NCCCWA and TLUM, respectively. SNP effects and variances were estimated using the weighted single-step genomic best linear unbiased prediction (BLUP) for genome-wide association. Genomic regions that explained more than 1% of the additive genetic variance were considered to be associated with resistance to CD. Predictive ability was calculated in a fivefold cross-validation scheme and using a linear regression method.
Validation on adjusted phenotypes provided a prediction accuracy close to zero, due to the binary nature of the trait. Using breeding values computed from the complete data as benchmark improved prediction accuracy of genomic models by about 40% compared to the pedigree-based BLUP. Fourteen windows located on six chromosomes were associated with resistance to CD in the NCCCWA population, of which two windows on chromosome Omy 17 jointly explained more than 10% of the additive genetic variance. Twenty-six windows located on 13 chromosomes were associated with resistance to CD in the TLUM population. Only four associated genomic regions overlapped with quantitative trait loci (QTL) between both populations.
Our results suggest that genome-wide selection for resistance to CD in rainbow trout has greater potential than selection for a few target genomic regions that were found to be associated to resistance to CD due to the polygenic architecture of this trait, and because the QTL associated with resistance to CD are not sufficiently informative for selection decisions across populations. |
doi_str_mv | 10.1186/s12711-019-0484-4 |
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Two aquaculture populations were investigated: the National Center for Cool and Cold Water Aquaculture (NCCCWA) odd-year line and the Troutlodge, Inc., May odd-year (TLUM) nucleus breeding population. Fish that survived to 21 days post-immersion challenge were recorded as resistant. Single nucleotide polymorphism (SNP) genotypes were available for 1185 and 1137 fish from NCCCWA and TLUM, respectively. SNP effects and variances were estimated using the weighted single-step genomic best linear unbiased prediction (BLUP) for genome-wide association. Genomic regions that explained more than 1% of the additive genetic variance were considered to be associated with resistance to CD. Predictive ability was calculated in a fivefold cross-validation scheme and using a linear regression method.
Validation on adjusted phenotypes provided a prediction accuracy close to zero, due to the binary nature of the trait. Using breeding values computed from the complete data as benchmark improved prediction accuracy of genomic models by about 40% compared to the pedigree-based BLUP. Fourteen windows located on six chromosomes were associated with resistance to CD in the NCCCWA population, of which two windows on chromosome Omy 17 jointly explained more than 10% of the additive genetic variance. Twenty-six windows located on 13 chromosomes were associated with resistance to CD in the TLUM population. Only four associated genomic regions overlapped with quantitative trait loci (QTL) between both populations.
Our results suggest that genome-wide selection for resistance to CD in rainbow trout has greater potential than selection for a few target genomic regions that were found to be associated to resistance to CD due to the polygenic architecture of this trait, and because the QTL associated with resistance to CD are not sufficiently informative for selection decisions across populations.</description><identifier>ISSN: 1297-9686</identifier><identifier>ISSN: 0999-193X</identifier><identifier>EISSN: 1297-9686</identifier><identifier>DOI: 10.1186/s12711-019-0484-4</identifier><identifier>PMID: 31387519</identifier><language>eng</language><publisher>France: BioMed Central Ltd</publisher><subject>Agriculture ; Animal diseases ; Aquaculture ; Aquaculture industry ; BASIC BIOLOGICAL SCIENCES ; Benchmarking ; Breeding ; Care and treatment ; Chromosomes ; Cold ; Cold water ; Columnaris disease ; Disease ; Disease resistance ; Fish diseases ; Fish populations ; Fishes ; Gene mapping ; Gene polymorphism ; Genetic aspects ; Genetic diversity ; Genetic polymorphisms ; Genetic variance ; Genetics & Heredity ; Genomes ; Genomics ; Genotype & phenotype ; Genotypes ; Infection ; Life Sciences ; Model accuracy ; Nucleotides ; Oncorhynchus mykiss ; Pathogens ; Phenotypes ; Polygenic inheritance ; Polymorphism ; Population ; Populations ; Predictions ; Quantitative genetics ; Quantitative trait loci ; Rainbow trout ; Regression analysis ; Risk factors ; Salmon ; Seafood industry ; Single nucleotide polymorphisms ; Single-nucleotide polymorphism ; Trout</subject><ispartof>Genetics selection evolution (Paris), 2019-08, Vol.51 (1), p.42-42, Article 42</ispartof><rights>COPYRIGHT 2019 BioMed Central Ltd.</rights><rights>2019. This work is licensed under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.</rights><rights>Distributed under a Creative Commons Attribution 4.0 International License</rights><rights>The Author(s) 2019</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c655t-82e3dbbc3dd3f5f1315e19f848f6e3886e7dba9dcbe00548da4c32855150a1f03</citedby><cites>FETCH-LOGICAL-c655t-82e3dbbc3dd3f5f1315e19f848f6e3886e7dba9dcbe00548da4c32855150a1f03</cites><orcidid>0000-0002-4953-8878 ; 0000000249538878</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC6683352/pdf/$$EPDF$$P50$$Gpubmedcentral$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.proquest.com/docview/2546776842?pq-origsite=primo$$EHTML$$P50$$Gproquest$$Hfree_for_read</linktohtml><link.rule.ids>230,314,727,780,784,885,25753,27924,27925,37012,37013,44590,53791,53793</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/31387519$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink><backlink>$$Uhttps://hal.science/hal-02265710$$DView record in HAL$$Hfree_for_read</backlink><backlink>$$Uhttps://www.osti.gov/biblio/1618934$$D View this record in Osti.gov$$Hfree_for_read</backlink></links><search><creatorcontrib>Silva, Rafael M O</creatorcontrib><creatorcontrib>Evenhuis, Jason P</creatorcontrib><creatorcontrib>Vallejo, Roger L</creatorcontrib><creatorcontrib>Gao, Guangtu</creatorcontrib><creatorcontrib>Martin, Kyle E</creatorcontrib><creatorcontrib>Leeds, Tim D</creatorcontrib><creatorcontrib>Palti, Yniv</creatorcontrib><creatorcontrib>Lourenco, Daniela A L</creatorcontrib><creatorcontrib>Oak Ridge Associated Univ., Oak Ridge, TN (United States)</creatorcontrib><title>Whole-genome mapping of quantitative trait loci and accuracy of genomic predictions for resistance to columnaris disease in two rainbow trout breeding populations</title><title>Genetics selection evolution (Paris)</title><addtitle>Genet Sel Evol</addtitle><description>Columnaris disease (CD) is an emerging problem for the rainbow trout aquaculture industry in the US. The objectives of this study were to: (1) identify common genomic regions that explain a large proportion of the additive genetic variance for resistance to CD in two rainbow trout (Oncorhynchus mykiss) populations; and (2) estimate the gains in prediction accuracy when genomic information is used to evaluate the genetic potential of survival to columnaris infection in each population.
Two aquaculture populations were investigated: the National Center for Cool and Cold Water Aquaculture (NCCCWA) odd-year line and the Troutlodge, Inc., May odd-year (TLUM) nucleus breeding population. Fish that survived to 21 days post-immersion challenge were recorded as resistant. Single nucleotide polymorphism (SNP) genotypes were available for 1185 and 1137 fish from NCCCWA and TLUM, respectively. SNP effects and variances were estimated using the weighted single-step genomic best linear unbiased prediction (BLUP) for genome-wide association. Genomic regions that explained more than 1% of the additive genetic variance were considered to be associated with resistance to CD. Predictive ability was calculated in a fivefold cross-validation scheme and using a linear regression method.
Validation on adjusted phenotypes provided a prediction accuracy close to zero, due to the binary nature of the trait. Using breeding values computed from the complete data as benchmark improved prediction accuracy of genomic models by about 40% compared to the pedigree-based BLUP. Fourteen windows located on six chromosomes were associated with resistance to CD in the NCCCWA population, of which two windows on chromosome Omy 17 jointly explained more than 10% of the additive genetic variance. Twenty-six windows located on 13 chromosomes were associated with resistance to CD in the TLUM population. Only four associated genomic regions overlapped with quantitative trait loci (QTL) between both populations.
Our results suggest that genome-wide selection for resistance to CD in rainbow trout has greater potential than selection for a few target genomic regions that were found to be associated to resistance to CD due to the polygenic architecture of this trait, and because the QTL associated with resistance to CD are not sufficiently informative for selection decisions across populations.</description><subject>Agriculture</subject><subject>Animal diseases</subject><subject>Aquaculture</subject><subject>Aquaculture industry</subject><subject>BASIC BIOLOGICAL SCIENCES</subject><subject>Benchmarking</subject><subject>Breeding</subject><subject>Care and treatment</subject><subject>Chromosomes</subject><subject>Cold</subject><subject>Cold water</subject><subject>Columnaris disease</subject><subject>Disease</subject><subject>Disease resistance</subject><subject>Fish diseases</subject><subject>Fish populations</subject><subject>Fishes</subject><subject>Gene mapping</subject><subject>Gene polymorphism</subject><subject>Genetic aspects</subject><subject>Genetic diversity</subject><subject>Genetic polymorphisms</subject><subject>Genetic variance</subject><subject>Genetics & Heredity</subject><subject>Genomes</subject><subject>Genomics</subject><subject>Genotype & phenotype</subject><subject>Genotypes</subject><subject>Infection</subject><subject>Life Sciences</subject><subject>Model accuracy</subject><subject>Nucleotides</subject><subject>Oncorhynchus mykiss</subject><subject>Pathogens</subject><subject>Phenotypes</subject><subject>Polygenic inheritance</subject><subject>Polymorphism</subject><subject>Population</subject><subject>Populations</subject><subject>Predictions</subject><subject>Quantitative genetics</subject><subject>Quantitative trait loci</subject><subject>Rainbow trout</subject><subject>Regression analysis</subject><subject>Risk factors</subject><subject>Salmon</subject><subject>Seafood industry</subject><subject>Single nucleotide 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mapping of quantitative trait loci and accuracy of genomic predictions for resistance to columnaris disease in two rainbow trout breeding populations</title><author>Silva, Rafael M O ; Evenhuis, Jason P ; Vallejo, Roger L ; Gao, Guangtu ; Martin, Kyle E ; Leeds, Tim D ; Palti, Yniv ; Lourenco, Daniela A L</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c655t-82e3dbbc3dd3f5f1315e19f848f6e3886e7dba9dcbe00548da4c32855150a1f03</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2019</creationdate><topic>Agriculture</topic><topic>Animal diseases</topic><topic>Aquaculture</topic><topic>Aquaculture industry</topic><topic>BASIC BIOLOGICAL SCIENCES</topic><topic>Benchmarking</topic><topic>Breeding</topic><topic>Care and treatment</topic><topic>Chromosomes</topic><topic>Cold</topic><topic>Cold water</topic><topic>Columnaris disease</topic><topic>Disease</topic><topic>Disease resistance</topic><topic>Fish diseases</topic><topic>Fish populations</topic><topic>Fishes</topic><topic>Gene mapping</topic><topic>Gene polymorphism</topic><topic>Genetic aspects</topic><topic>Genetic diversity</topic><topic>Genetic polymorphisms</topic><topic>Genetic variance</topic><topic>Genetics & Heredity</topic><topic>Genomes</topic><topic>Genomics</topic><topic>Genotype & phenotype</topic><topic>Genotypes</topic><topic>Infection</topic><topic>Life Sciences</topic><topic>Model accuracy</topic><topic>Nucleotides</topic><topic>Oncorhynchus mykiss</topic><topic>Pathogens</topic><topic>Phenotypes</topic><topic>Polygenic inheritance</topic><topic>Polymorphism</topic><topic>Population</topic><topic>Populations</topic><topic>Predictions</topic><topic>Quantitative genetics</topic><topic>Quantitative trait loci</topic><topic>Rainbow trout</topic><topic>Regression analysis</topic><topic>Risk factors</topic><topic>Salmon</topic><topic>Seafood industry</topic><topic>Single nucleotide 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Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Silva, Rafael M O</au><au>Evenhuis, Jason P</au><au>Vallejo, Roger L</au><au>Gao, Guangtu</au><au>Martin, Kyle E</au><au>Leeds, Tim D</au><au>Palti, Yniv</au><au>Lourenco, Daniela A L</au><aucorp>Oak Ridge Associated Univ., Oak Ridge, TN (United States)</aucorp><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Whole-genome mapping of quantitative trait loci and accuracy of genomic predictions for resistance to columnaris disease in two rainbow trout breeding populations</atitle><jtitle>Genetics selection evolution (Paris)</jtitle><addtitle>Genet Sel Evol</addtitle><date>2019-08-06</date><risdate>2019</risdate><volume>51</volume><issue>1</issue><spage>42</spage><epage>42</epage><pages>42-42</pages><artnum>42</artnum><issn>1297-9686</issn><issn>0999-193X</issn><eissn>1297-9686</eissn><abstract>Columnaris disease (CD) is an emerging problem for the rainbow trout aquaculture industry in the US. The objectives of this study were to: (1) identify common genomic regions that explain a large proportion of the additive genetic variance for resistance to CD in two rainbow trout (Oncorhynchus mykiss) populations; and (2) estimate the gains in prediction accuracy when genomic information is used to evaluate the genetic potential of survival to columnaris infection in each population.
Two aquaculture populations were investigated: the National Center for Cool and Cold Water Aquaculture (NCCCWA) odd-year line and the Troutlodge, Inc., May odd-year (TLUM) nucleus breeding population. Fish that survived to 21 days post-immersion challenge were recorded as resistant. Single nucleotide polymorphism (SNP) genotypes were available for 1185 and 1137 fish from NCCCWA and TLUM, respectively. SNP effects and variances were estimated using the weighted single-step genomic best linear unbiased prediction (BLUP) for genome-wide association. Genomic regions that explained more than 1% of the additive genetic variance were considered to be associated with resistance to CD. Predictive ability was calculated in a fivefold cross-validation scheme and using a linear regression method.
Validation on adjusted phenotypes provided a prediction accuracy close to zero, due to the binary nature of the trait. Using breeding values computed from the complete data as benchmark improved prediction accuracy of genomic models by about 40% compared to the pedigree-based BLUP. Fourteen windows located on six chromosomes were associated with resistance to CD in the NCCCWA population, of which two windows on chromosome Omy 17 jointly explained more than 10% of the additive genetic variance. Twenty-six windows located on 13 chromosomes were associated with resistance to CD in the TLUM population. Only four associated genomic regions overlapped with quantitative trait loci (QTL) between both populations.
Our results suggest that genome-wide selection for resistance to CD in rainbow trout has greater potential than selection for a few target genomic regions that were found to be associated to resistance to CD due to the polygenic architecture of this trait, and because the QTL associated with resistance to CD are not sufficiently informative for selection decisions across populations.</abstract><cop>France</cop><pub>BioMed Central Ltd</pub><pmid>31387519</pmid><doi>10.1186/s12711-019-0484-4</doi><tpages>1</tpages><orcidid>https://orcid.org/0000-0002-4953-8878</orcidid><orcidid>https://orcid.org/0000000249538878</orcidid><oa>free_for_read</oa></addata></record> |
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identifier | ISSN: 1297-9686 |
ispartof | Genetics selection evolution (Paris), 2019-08, Vol.51 (1), p.42-42, Article 42 |
issn | 1297-9686 0999-193X 1297-9686 |
language | eng |
recordid | cdi_doaj_primary_oai_doaj_org_article_82e7a760e2954bb1a28c899119df20e7 |
source | Publicly Available Content (ProQuest); PubMed Central |
subjects | Agriculture Animal diseases Aquaculture Aquaculture industry BASIC BIOLOGICAL SCIENCES Benchmarking Breeding Care and treatment Chromosomes Cold Cold water Columnaris disease Disease Disease resistance Fish diseases Fish populations Fishes Gene mapping Gene polymorphism Genetic aspects Genetic diversity Genetic polymorphisms Genetic variance Genetics & Heredity Genomes Genomics Genotype & phenotype Genotypes Infection Life Sciences Model accuracy Nucleotides Oncorhynchus mykiss Pathogens Phenotypes Polygenic inheritance Polymorphism Population Populations Predictions Quantitative genetics Quantitative trait loci Rainbow trout Regression analysis Risk factors Salmon Seafood industry Single nucleotide polymorphisms Single-nucleotide polymorphism Trout |
title | Whole-genome mapping of quantitative trait loci and accuracy of genomic predictions for resistance to columnaris disease in two rainbow trout breeding populations |
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