Implementing meta - analysis from genome - wide association studies for pork quality traits

Pork quality plays an important role in the meat processing industry. Thus, different methodologies have been implemented to elucidate the genetic architecture of traits affecting meat quality. One of the most common and widely used approaches is to perform genome-wide association (GWA) studies. However, a limitation of many GWA in animal breeding is the limited power due to small sample sizes in animal populations. One alternative is to implement a metaanalysis of GWA (MA-GWA) combining results from independent association studies. The objective of this study was to identify significant genomic regions associated with meat quality traits by performing MA-GWA for 8 different traits in 3 independent pig populations. Results from MA-GWA were used to search for genes possibly associated with the set of evaluated traits. Data from 3 pig data sets (U.S. Meat Animal Research Center, commercial, and Michigan State University Pig Resource Population) were used. A MA was implemented by combining z-scores derived for each SNP in every population and then weighting them using the inverse of estimated variance of SNP effects. A search for annotated genes retrieved genes previously reported as candidates for shear force (calpain-1 catalytic subunit [CAPN1] and calpastatin [CAST]), as well as for ultimate pH, purge loss, and cook loss (protein kinase, AMP-activated, γ 3 noncatalytic subunit [PRKAG3]). In addition, novel candidate genes were identified for intramuscular fat and cook loss (acyl-CoA synthetase family member 3 mitochondrial [ACSF3]) and for the objective measure of muscle redness, CIE a* (glycogen synthase 1, muscle [GYS1] and ferritin, light polypeptide [FTL]). Thus, implementation of MA GWA allowed integration of results for economically relevant traits and identified novel genes to be tested as candidates for meat quality traits in pig populations.

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Main Authors: Bernal Rubio, Yeni Liliana, Gualdrón Duarte, José Luis, Bates, R. O., Ernst, C. W., Nonneman, D., Rohrer, G. A., King, D. A., Shackelford, S. D., Wheeler, T. L., Cantet, Rodolfo Juan Carlos, Steibel, Juan Pedro
Format: Texto biblioteca
Language:eng
Subjects:CANDIDATE GENES, GENOME - WIDE ASSOCIATION, MEAT QUALITY, META - ANALYSIS, PIGS, ,
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id KOHA-OAI-AGRO:46307
record_format koha
institution UBA FA
collection Koha
country Argentina
countrycode AR
component Bibliográfico
access En linea
En linea
databasecode cat-ceiba
tag biblioteca
region America del Sur
libraryname Biblioteca Central FAUBA
language eng
topic CANDIDATE GENES
GENOME - WIDE ASSOCIATION
MEAT QUALITY
META - ANALYSIS
PIGS

CANDIDATE GENES
GENOME - WIDE ASSOCIATION
MEAT QUALITY
META - ANALYSIS
PIGS
spellingShingle CANDIDATE GENES
GENOME - WIDE ASSOCIATION
MEAT QUALITY
META - ANALYSIS
PIGS

CANDIDATE GENES
GENOME - WIDE ASSOCIATION
MEAT QUALITY
META - ANALYSIS
PIGS
Bernal Rubio, Yeni Liliana
Gualdrón Duarte, José Luis
Bates, R. O.
Ernst, C. W.
Nonneman, D.
Rohrer, G. A.
King, D. A.
Shackelford, S. D.
Wheeler, T. L.
Cantet, Rodolfo Juan Carlos
Steibel, Juan Pedro
Implementing meta - analysis from genome - wide association studies for pork quality traits
description Pork quality plays an important role in the meat processing industry. Thus, different methodologies have been implemented to elucidate the genetic architecture of traits affecting meat quality. One of the most common and widely used approaches is to perform genome-wide association (GWA) studies. However, a limitation of many GWA in animal breeding is the limited power due to small sample sizes in animal populations. One alternative is to implement a metaanalysis of GWA (MA-GWA) combining results from independent association studies. The objective of this study was to identify significant genomic regions associated with meat quality traits by performing MA-GWA for 8 different traits in 3 independent pig populations. Results from MA-GWA were used to search for genes possibly associated with the set of evaluated traits. Data from 3 pig data sets (U.S. Meat Animal Research Center, commercial, and Michigan State University Pig Resource Population) were used. A MA was implemented by combining z-scores derived for each SNP in every population and then weighting them using the inverse of estimated variance of SNP effects. A search for annotated genes retrieved genes previously reported as candidates for shear force (calpain-1 catalytic subunit [CAPN1] and calpastatin [CAST]), as well as for ultimate pH, purge loss, and cook loss (protein kinase, AMP-activated, γ 3 noncatalytic subunit [PRKAG3]). In addition, novel candidate genes were identified for intramuscular fat and cook loss (acyl-CoA synthetase family member 3 mitochondrial [ACSF3]) and for the objective measure of muscle redness, CIE a* (glycogen synthase 1, muscle [GYS1] and ferritin, light polypeptide [FTL]). Thus, implementation of MA GWA allowed integration of results for economically relevant traits and identified novel genes to be tested as candidates for meat quality traits in pig populations.
format Texto
topic_facet
CANDIDATE GENES
GENOME - WIDE ASSOCIATION
MEAT QUALITY
META - ANALYSIS
PIGS
author Bernal Rubio, Yeni Liliana
Gualdrón Duarte, José Luis
Bates, R. O.
Ernst, C. W.
Nonneman, D.
Rohrer, G. A.
King, D. A.
Shackelford, S. D.
Wheeler, T. L.
Cantet, Rodolfo Juan Carlos
Steibel, Juan Pedro
author_facet Bernal Rubio, Yeni Liliana
Gualdrón Duarte, José Luis
Bates, R. O.
Ernst, C. W.
Nonneman, D.
Rohrer, G. A.
King, D. A.
Shackelford, S. D.
Wheeler, T. L.
Cantet, Rodolfo Juan Carlos
Steibel, Juan Pedro
author_sort Bernal Rubio, Yeni Liliana
title Implementing meta - analysis from genome - wide association studies for pork quality traits
title_short Implementing meta - analysis from genome - wide association studies for pork quality traits
title_full Implementing meta - analysis from genome - wide association studies for pork quality traits
title_fullStr Implementing meta - analysis from genome - wide association studies for pork quality traits
title_full_unstemmed Implementing meta - analysis from genome - wide association studies for pork quality traits
title_sort implementing meta - analysis from genome - wide association studies for pork quality traits
url http://ceiba.agro.uba.ar/cgi-bin/koha/opac-detail.pl?biblionumber=46307
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spelling KOHA-OAI-AGRO:463072022-04-13T10:00:01Zhttp://ceiba.agro.uba.ar/cgi-bin/koha/opac-detail.pl?biblionumber=46307http://ceiba.agro.uba.ar/cgi-bin/koha/opac-detail.pl?biblionumber=http://ceiba.agro.uba.ar/cgi-bin/koha/opac-detail.pl?biblionumber=http://ceiba.agro.uba.ar/cgi-bin/koha/opac-detail.pl?biblionumber=http://ceiba.agro.uba.ar/cgi-bin/koha/opac-detail.pl?biblionumber=http://ceiba.agro.uba.ar/cgi-bin/koha/opac-detail.pl?biblionumber=http://ceiba.agro.uba.ar/cgi-bin/koha/opac-detail.pl?biblionumber=http://ceiba.agro.uba.ar/cgi-bin/koha/opac-detail.pl?biblionumber=http://ceiba.agro.uba.ar/cgi-bin/koha/opac-detail.pl?biblionumber=AAGImplementing meta - analysis from genome - wide association studies for pork quality traitsBernal Rubio, Yeni LilianaGualdrón Duarte, José LuisBates, R. O.Ernst, C. W.Nonneman, D.Rohrer, G. A.King, D. A.Shackelford, S. D.Wheeler, T. L.Cantet, Rodolfo Juan CarlosSteibel, Juan Pedrotextengapplication/pdfPork quality plays an important role in the meat processing industry. Thus, different methodologies have been implemented to elucidate the genetic architecture of traits affecting meat quality. One of the most common and widely used approaches is to perform genome-wide association (GWA) studies. However, a limitation of many GWA in animal breeding is the limited power due to small sample sizes in animal populations. One alternative is to implement a metaanalysis of GWA (MA-GWA) combining results from independent association studies. The objective of this study was to identify significant genomic regions associated with meat quality traits by performing MA-GWA for 8 different traits in 3 independent pig populations. Results from MA-GWA were used to search for genes possibly associated with the set of evaluated traits. Data from 3 pig data sets (U.S. Meat Animal Research Center, commercial, and Michigan State University Pig Resource Population) were used. A MA was implemented by combining z-scores derived for each SNP in every population and then weighting them using the inverse of estimated variance of SNP effects. A search for annotated genes retrieved genes previously reported as candidates for shear force (calpain-1 catalytic subunit [CAPN1] and calpastatin [CAST]), as well as for ultimate pH, purge loss, and cook loss (protein kinase, AMP-activated, γ 3 noncatalytic subunit [PRKAG3]). In addition, novel candidate genes were identified for intramuscular fat and cook loss (acyl-CoA synthetase family member 3 mitochondrial [ACSF3]) and for the objective measure of muscle redness, CIE a* (glycogen synthase 1, muscle [GYS1] and ferritin, light polypeptide [FTL]). Thus, implementation of MA GWA allowed integration of results for economically relevant traits and identified novel genes to be tested as candidates for meat quality traits in pig populations.Pork quality plays an important role in the meat processing industry. Thus, different methodologies have been implemented to elucidate the genetic architecture of traits affecting meat quality. One of the most common and widely used approaches is to perform genome-wide association (GWA) studies. However, a limitation of many GWA in animal breeding is the limited power due to small sample sizes in animal populations. One alternative is to implement a metaanalysis of GWA (MA-GWA) combining results from independent association studies. The objective of this study was to identify significant genomic regions associated with meat quality traits by performing MA-GWA for 8 different traits in 3 independent pig populations. Results from MA-GWA were used to search for genes possibly associated with the set of evaluated traits. Data from 3 pig data sets (U.S. Meat Animal Research Center, commercial, and Michigan State University Pig Resource Population) were used. A MA was implemented by combining z-scores derived for each SNP in every population and then weighting them using the inverse of estimated variance of SNP effects. A search for annotated genes retrieved genes previously reported as candidates for shear force (calpain-1 catalytic subunit [CAPN1] and calpastatin [CAST]), as well as for ultimate pH, purge loss, and cook loss (protein kinase, AMP-activated, γ 3 noncatalytic subunit [PRKAG3]). In addition, novel candidate genes were identified for intramuscular fat and cook loss (acyl-CoA synthetase family member 3 mitochondrial [ACSF3]) and for the objective measure of muscle redness, CIE a* (glycogen synthase 1, muscle [GYS1] and ferritin, light polypeptide [FTL]). Thus, implementation of MA GWA allowed integration of results for economically relevant traits and identified novel genes to be tested as candidates for meat quality traits in pig populations.CANDIDATE GENESGENOME - WIDE ASSOCIATIONMEAT QUALITYMETA - ANALYSISPIGSJournal of animal science