Meta-analysis for milk fat and protein percentage using imputed sequence variant genotypes in 94,321 cattle from eight cattle breeds
Abstract Background Sequence-based genome-wide association studies (GWAS) provide high statistical power to identify candidate causal mutations when a large number of individuals with both sequence variant genotypes and phenotypes is available. A meta-analysis combines summary statistics from multip...
| Main Authors: | , , , , , , , , , , , |
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| Format: | Article |
| Language: | deu |
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BMC
2020-07-01
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| Series: | Genetics Selection Evolution |
| Online Access: | http://link.springer.com/article/10.1186/s12711-020-00556-4 |
| _version_ | 1819039293559013376 |
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| author | Irene van den Berg Ruidong Xiang Janez Jenko Hubert Pausch Mekki Boussaha Chris Schrooten Thierry Tribout Arne B. Gjuvsland Didier Boichard Øyvind Nordbø Marie-Pierre Sanchez Mike E. Goddard |
| author_facet | Irene van den Berg Ruidong Xiang Janez Jenko Hubert Pausch Mekki Boussaha Chris Schrooten Thierry Tribout Arne B. Gjuvsland Didier Boichard Øyvind Nordbø Marie-Pierre Sanchez Mike E. Goddard |
| author_sort | Irene van den Berg |
| collection | DOAJ |
| description | Abstract Background Sequence-based genome-wide association studies (GWAS) provide high statistical power to identify candidate causal mutations when a large number of individuals with both sequence variant genotypes and phenotypes is available. A meta-analysis combines summary statistics from multiple GWAS and increases the power to detect trait-associated variants without requiring access to data at the individual level of the GWAS mapping cohorts. Because linkage disequilibrium between adjacent markers is conserved only over short distances across breeds, a multi-breed meta-analysis can improve mapping precision. Results To maximise the power to identify quantitative trait loci (QTL), we combined the results of nine within-population GWAS that used imputed sequence variant genotypes of 94,321 cattle from eight breeds, to perform a large-scale meta-analysis for fat and protein percentage in cattle. The meta-analysis detected (p ≤ 10−8) 138 QTL for fat percentage and 176 QTL for protein percentage. This was more than the number of QTL detected in all within-population GWAS together (124 QTL for fat percentage and 104 QTL for protein percentage). Among all the lead variants, 100 QTL for fat percentage and 114 QTL for protein percentage had the same direction of effect in all within-population GWAS. This indicates either persistence of the linkage phase between the causal variant and the lead variant across breeds or that some of the lead variants might indeed be causal or tightly linked with causal variants. The percentage of intergenic variants was substantially lower for significant variants than for non-significant variants, and significant variants had mostly moderate to high minor allele frequencies. Significant variants were also clustered in genes that are known to be relevant for fat and protein percentages in milk. Conclusions Our study identified a large number of QTL associated with fat and protein percentage in dairy cattle. We demonstrated that large-scale multi-breed meta-analysis reveals more QTL at the nucleotide resolution than within-population GWAS. Significant variants were more often located in genic regions than non-significant variants and a large part of them was located in potentially regulatory regions. |
| first_indexed | 2024-12-21T08:50:54Z |
| format | Article |
| id | doaj.art-8fc569f86b0e419b804acf71d07792d8 |
| institution | Directory Open Access Journal |
| issn | 1297-9686 |
| language | deu |
| last_indexed | 2024-12-21T08:50:54Z |
| publishDate | 2020-07-01 |
| publisher | BMC |
| record_format | Article |
| series | Genetics Selection Evolution |
| spelling | doaj.art-8fc569f86b0e419b804acf71d07792d82022-12-21T19:09:42ZdeuBMCGenetics Selection Evolution1297-96862020-07-0152111610.1186/s12711-020-00556-4Meta-analysis for milk fat and protein percentage using imputed sequence variant genotypes in 94,321 cattle from eight cattle breedsIrene van den Berg0Ruidong Xiang1Janez Jenko2Hubert Pausch3Mekki Boussaha4Chris Schrooten5Thierry Tribout6Arne B. Gjuvsland7Didier Boichard8Øyvind Nordbø9Marie-Pierre Sanchez10Mike E. Goddard11Agriculture Victoria Research, AgriBioAgriculture Victoria Research, AgriBioGENO SAAnimal Genomics, ETH ZurichUniversité Paris-Saclay, INRAE, AgroParisTech, GABICRVUniversité Paris-Saclay, INRAE, AgroParisTech, GABIGENO SAUniversité Paris-Saclay, INRAE, AgroParisTech, GABIGENO SAUniversité Paris-Saclay, INRAE, AgroParisTech, GABIAgriculture Victoria Research, AgriBioAbstract Background Sequence-based genome-wide association studies (GWAS) provide high statistical power to identify candidate causal mutations when a large number of individuals with both sequence variant genotypes and phenotypes is available. A meta-analysis combines summary statistics from multiple GWAS and increases the power to detect trait-associated variants without requiring access to data at the individual level of the GWAS mapping cohorts. Because linkage disequilibrium between adjacent markers is conserved only over short distances across breeds, a multi-breed meta-analysis can improve mapping precision. Results To maximise the power to identify quantitative trait loci (QTL), we combined the results of nine within-population GWAS that used imputed sequence variant genotypes of 94,321 cattle from eight breeds, to perform a large-scale meta-analysis for fat and protein percentage in cattle. The meta-analysis detected (p ≤ 10−8) 138 QTL for fat percentage and 176 QTL for protein percentage. This was more than the number of QTL detected in all within-population GWAS together (124 QTL for fat percentage and 104 QTL for protein percentage). Among all the lead variants, 100 QTL for fat percentage and 114 QTL for protein percentage had the same direction of effect in all within-population GWAS. This indicates either persistence of the linkage phase between the causal variant and the lead variant across breeds or that some of the lead variants might indeed be causal or tightly linked with causal variants. The percentage of intergenic variants was substantially lower for significant variants than for non-significant variants, and significant variants had mostly moderate to high minor allele frequencies. Significant variants were also clustered in genes that are known to be relevant for fat and protein percentages in milk. Conclusions Our study identified a large number of QTL associated with fat and protein percentage in dairy cattle. We demonstrated that large-scale multi-breed meta-analysis reveals more QTL at the nucleotide resolution than within-population GWAS. Significant variants were more often located in genic regions than non-significant variants and a large part of them was located in potentially regulatory regions.http://link.springer.com/article/10.1186/s12711-020-00556-4 |
| spellingShingle | Irene van den Berg Ruidong Xiang Janez Jenko Hubert Pausch Mekki Boussaha Chris Schrooten Thierry Tribout Arne B. Gjuvsland Didier Boichard Øyvind Nordbø Marie-Pierre Sanchez Mike E. Goddard Meta-analysis for milk fat and protein percentage using imputed sequence variant genotypes in 94,321 cattle from eight cattle breeds Genetics Selection Evolution |
| title | Meta-analysis for milk fat and protein percentage using imputed sequence variant genotypes in 94,321 cattle from eight cattle breeds |
| title_full | Meta-analysis for milk fat and protein percentage using imputed sequence variant genotypes in 94,321 cattle from eight cattle breeds |
| title_fullStr | Meta-analysis for milk fat and protein percentage using imputed sequence variant genotypes in 94,321 cattle from eight cattle breeds |
| title_full_unstemmed | Meta-analysis for milk fat and protein percentage using imputed sequence variant genotypes in 94,321 cattle from eight cattle breeds |
| title_short | Meta-analysis for milk fat and protein percentage using imputed sequence variant genotypes in 94,321 cattle from eight cattle breeds |
| title_sort | meta analysis for milk fat and protein percentage using imputed sequence variant genotypes in 94 321 cattle from eight cattle breeds |
| url | http://link.springer.com/article/10.1186/s12711-020-00556-4 |
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