Detection of Genomic Regions with Pleiotropic Effects for Growth and Carcass Quality Traits in the Rubia Gallega Cattle Breed

The breeding scheme in the Rubia Gallega cattle population is based upon traits measured in farms and slaughterhouses. In recent years, genomic evaluation has been implemented by using a ssGBLUP (single-step Genomic Best Linear Unbiased Prediction). This procedure can reparameterized to perform ssGW...

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Main Authors: Maria Martinez-Castillero, Carlos Then, Juan Altarriba, Houssemeddine Srihi, David López-Carbonell, Clara Díaz, Paulino Martinez, Miguel Hermida, Luis Varona
Format: Article
Language:English
Published: MDPI AG 2021-06-01
Series:Animals
Subjects:
SNP
Online Access:https://www.mdpi.com/2076-2615/11/6/1682
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spelling doaj-f2467d5fdb1f4959acf1ab3fc01f98992021-06-30T23:22:11ZengMDPI AGAnimals2076-26152021-06-01111682168210.3390/ani11061682Detection of Genomic Regions with Pleiotropic Effects for Growth and Carcass Quality Traits in the Rubia Gallega Cattle BreedMaria Martinez-Castillero0Carlos Then1Juan Altarriba2Houssemeddine Srihi3David López-Carbonell4Clara Díaz5Paulino Martinez6Miguel Hermida7Luis Varona8Instituto Agroalimentario de Aragón (IA2), Universidad de Zaragoza, 50013 Zaragoza, SpainInstituto Agroalimentario de Aragón (IA2), Universidad de Zaragoza, 50013 Zaragoza, SpainInstituto Agroalimentario de Aragón (IA2), Universidad de Zaragoza, 50013 Zaragoza, SpainInstituto Agroalimentario de Aragón (IA2), Universidad de Zaragoza, 50013 Zaragoza, SpainInstituto Agroalimentario de Aragón (IA2), Universidad de Zaragoza, 50013 Zaragoza, SpainInstituto Nacional de Investigación y Tecnología Agraria (INIA), 28040 Madrid, SpainFacultad de Veterinaria, Universidad de Santiago de Compostela, 27002 Lugo, SpainFacultad de Veterinaria, Universidad de Santiago de Compostela, 27002 Lugo, SpainInstituto Agroalimentario de Aragón (IA2), Universidad de Zaragoza, 50013 Zaragoza, SpainThe breeding scheme in the Rubia Gallega cattle population is based upon traits measured in farms and slaughterhouses. In recent years, genomic evaluation has been implemented by using a ssGBLUP (single-step Genomic Best Linear Unbiased Prediction). This procedure can reparameterized to perform ssGWAS (single-step Genome Wide Association Studies) by backsolving the SNP (single nucleotide polymorphisms) effects. Therefore, the objective of this study was to identify genomic regions associated with the genetic variability in growth and carcass quality traits. We implemented a ssGBLUP by using a database that included records for Birth Weight (BW-327,350 records-), Weaning Weight (WW-83,818-), Cold Carcass Weight (CCW-91,621-), Fatness (FAT-91,475-) and Conformation (CON-91,609-). The pedigree included 464,373 individuals, 2449 of which were genotyped. After a process of filtering, we ended up using 43,211 SNP markers. We used the GBLUP and SNPBLUP model equivalences to obtain the effects of the SNPs and then calculated the percentage of variance explained by the regions of the genome between 1 Mb. We identified 7 regions of the genome for CCW; 8 regions for BW, WW, FAT and 9 regions for CON, which explained the percentage of variance above 0.5%. Furthermore, a number of the genome regions had pleiotropic effects, located at: BTA1 (131–132 Mb), BTA2 (1–11 Mb), BTA3 (32–33 Mb), BTA6 (36–38 Mb), BTA16 (24–26 Mb), and BTA 21 (56–57 Mb). These regions contain, amongst others, the following candidate genes: <i>NCK1</i>, <i>MSTN</i>, <i>KCNA3</i>, <i>LCORL</i>, <i>NCAPG</i>, and <i>RIN3</i>.https://www.mdpi.com/2076-2615/11/6/1682beef cattlesingle-step GBLUPSNPcandidate genesGWASpleiotropy
collection DOAJ
language English
format Article
sources DOAJ
author Maria Martinez-Castillero
Carlos Then
Juan Altarriba
Houssemeddine Srihi
David López-Carbonell
Clara Díaz
Paulino Martinez
Miguel Hermida
Luis Varona
spellingShingle Maria Martinez-Castillero
Carlos Then
Juan Altarriba
Houssemeddine Srihi
David López-Carbonell
Clara Díaz
Paulino Martinez
Miguel Hermida
Luis Varona
Detection of Genomic Regions with Pleiotropic Effects for Growth and Carcass Quality Traits in the Rubia Gallega Cattle Breed
Animals
beef cattle
single-step GBLUP
SNP
candidate genes
GWAS
pleiotropy
author_facet Maria Martinez-Castillero
Carlos Then
Juan Altarriba
Houssemeddine Srihi
David López-Carbonell
Clara Díaz
Paulino Martinez
Miguel Hermida
Luis Varona
author_sort Maria Martinez-Castillero
title Detection of Genomic Regions with Pleiotropic Effects for Growth and Carcass Quality Traits in the Rubia Gallega Cattle Breed
title_short Detection of Genomic Regions with Pleiotropic Effects for Growth and Carcass Quality Traits in the Rubia Gallega Cattle Breed
title_full Detection of Genomic Regions with Pleiotropic Effects for Growth and Carcass Quality Traits in the Rubia Gallega Cattle Breed
title_fullStr Detection of Genomic Regions with Pleiotropic Effects for Growth and Carcass Quality Traits in the Rubia Gallega Cattle Breed
title_full_unstemmed Detection of Genomic Regions with Pleiotropic Effects for Growth and Carcass Quality Traits in the Rubia Gallega Cattle Breed
title_sort detection of genomic regions with pleiotropic effects for growth and carcass quality traits in the rubia gallega cattle breed
publisher MDPI AG
series Animals
issn 2076-2615
publishDate 2021-06-01
description The breeding scheme in the Rubia Gallega cattle population is based upon traits measured in farms and slaughterhouses. In recent years, genomic evaluation has been implemented by using a ssGBLUP (single-step Genomic Best Linear Unbiased Prediction). This procedure can reparameterized to perform ssGWAS (single-step Genome Wide Association Studies) by backsolving the SNP (single nucleotide polymorphisms) effects. Therefore, the objective of this study was to identify genomic regions associated with the genetic variability in growth and carcass quality traits. We implemented a ssGBLUP by using a database that included records for Birth Weight (BW-327,350 records-), Weaning Weight (WW-83,818-), Cold Carcass Weight (CCW-91,621-), Fatness (FAT-91,475-) and Conformation (CON-91,609-). The pedigree included 464,373 individuals, 2449 of which were genotyped. After a process of filtering, we ended up using 43,211 SNP markers. We used the GBLUP and SNPBLUP model equivalences to obtain the effects of the SNPs and then calculated the percentage of variance explained by the regions of the genome between 1 Mb. We identified 7 regions of the genome for CCW; 8 regions for BW, WW, FAT and 9 regions for CON, which explained the percentage of variance above 0.5%. Furthermore, a number of the genome regions had pleiotropic effects, located at: BTA1 (131–132 Mb), BTA2 (1–11 Mb), BTA3 (32–33 Mb), BTA6 (36–38 Mb), BTA16 (24–26 Mb), and BTA 21 (56–57 Mb). These regions contain, amongst others, the following candidate genes: <i>NCK1</i>, <i>MSTN</i>, <i>KCNA3</i>, <i>LCORL</i>, <i>NCAPG</i>, and <i>RIN3</i>.
topic beef cattle
single-step GBLUP
SNP
candidate genes
GWAS
pleiotropy
url https://www.mdpi.com/2076-2615/11/6/1682
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