Genomic dissection of the correlation between milk yield and various health traits using functional and evolutionary information about imputed sequence variants of 34,497 German Holstein cows
Abstract Background Over the last decades, it was subject of many studies to investigate the genomic connection of milk production and health traits in dairy cattle. Thereby, incorporating functional information in genomic analyses has been shown to improve the understanding of biological and molecu...
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| Format: | Article |
| Language: | English |
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BMC
2024-03-01
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| Series: | BMC Genomics |
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| Online Access: | https://doi.org/10.1186/s12864-024-10115-6 |
| _version_ | 1827114852084088832 |
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| author | Helen Schneider Ana-Marija Krizanac Clemens Falker-Gieske Johannes Heise Jens Tetens Georg Thaller Jörn Bennewitz |
| author_facet | Helen Schneider Ana-Marija Krizanac Clemens Falker-Gieske Johannes Heise Jens Tetens Georg Thaller Jörn Bennewitz |
| author_sort | Helen Schneider |
| collection | DOAJ |
| description | Abstract Background Over the last decades, it was subject of many studies to investigate the genomic connection of milk production and health traits in dairy cattle. Thereby, incorporating functional information in genomic analyses has been shown to improve the understanding of biological and molecular mechanisms shaping complex traits and the accuracies of genomic prediction, especially in small populations and across-breed settings. Still, little is known about the contribution of different functional and evolutionary genome partitioning subsets to milk production and dairy health. Thus, we performed a uni- and a bivariate analysis of milk yield (MY) and eight health traits using a set of ~34,497 German Holstein cows with 50K chip genotypes and ~17 million imputed sequence variants divided into 27 subsets depending on their functional and evolutionary annotation. In the bivariate analysis, eight trait-combinations were observed that contrasted MY with each health trait. Two genomic relationship matrices (GRM) were included, one consisting of the 50K chip variants and one consisting of each set of subset variants, to obtain subset heritabilities and genetic correlations. In addition, 50K chip heritabilities and genetic correlations were estimated applying merely the 50K GRM. Results In general, 50K chip heritabilities were larger than the subset heritabilities. The largest heritabilities were found for MY, which was 0.4358 for the 50K and 0.2757 for the subset heritabilities. Whereas all 50K genetic correlations were negative, subset genetic correlations were both, positive and negative (ranging from -0.9324 between MY and mastitis to 0.6662 between MY and digital dermatitis). The subsets containing variants which were annotated as noncoding related, splice sites, untranslated regions, metabolic quantitative trait loci, and young variants ranked highest in terms of their contribution to the traits’ genetic variance. We were able to show that linkage disequilibrium between subset variants and adjacent variants did not cause these subsets’ high effect. Conclusion Our results confirm the connection of milk production and health traits in dairy cattle via the animals’ metabolic state. In addition, they highlight the potential of including functional information in genomic analyses, which helps to dissect the extent and direction of the observed traits’ connection in more detail. |
| first_indexed | 2024-04-24T09:57:12Z |
| format | Article |
| id | doaj.art-fc91620e4f15462b92ef552461f05daf |
| institution | Directory Open Access Journal |
| issn | 1471-2164 |
| language | English |
| last_indexed | 2025-03-20T12:08:27Z |
| publishDate | 2024-03-01 |
| publisher | BMC |
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| series | BMC Genomics |
| spelling | doaj.art-fc91620e4f15462b92ef552461f05daf2024-09-15T11:08:31ZengBMCBMC Genomics1471-21642024-03-0125111610.1186/s12864-024-10115-6Genomic dissection of the correlation between milk yield and various health traits using functional and evolutionary information about imputed sequence variants of 34,497 German Holstein cowsHelen Schneider0Ana-Marija Krizanac1Clemens Falker-Gieske2Johannes Heise3Jens Tetens4Georg Thaller5Jörn Bennewitz6Institute of Animal Science, University of HohenheimDepartment of Animal Sciences, University of GöttingenDepartment of Animal Sciences, University of GöttingenVereinigte Informationssysteme Tierhaltung w.V. (VIT)Department of Animal Sciences, University of GöttingenInstitute of Animal Breeding and Husbandry, Christian-Albrechts University of KielInstitute of Animal Science, University of HohenheimAbstract Background Over the last decades, it was subject of many studies to investigate the genomic connection of milk production and health traits in dairy cattle. Thereby, incorporating functional information in genomic analyses has been shown to improve the understanding of biological and molecular mechanisms shaping complex traits and the accuracies of genomic prediction, especially in small populations and across-breed settings. Still, little is known about the contribution of different functional and evolutionary genome partitioning subsets to milk production and dairy health. Thus, we performed a uni- and a bivariate analysis of milk yield (MY) and eight health traits using a set of ~34,497 German Holstein cows with 50K chip genotypes and ~17 million imputed sequence variants divided into 27 subsets depending on their functional and evolutionary annotation. In the bivariate analysis, eight trait-combinations were observed that contrasted MY with each health trait. Two genomic relationship matrices (GRM) were included, one consisting of the 50K chip variants and one consisting of each set of subset variants, to obtain subset heritabilities and genetic correlations. In addition, 50K chip heritabilities and genetic correlations were estimated applying merely the 50K GRM. Results In general, 50K chip heritabilities were larger than the subset heritabilities. The largest heritabilities were found for MY, which was 0.4358 for the 50K and 0.2757 for the subset heritabilities. Whereas all 50K genetic correlations were negative, subset genetic correlations were both, positive and negative (ranging from -0.9324 between MY and mastitis to 0.6662 between MY and digital dermatitis). The subsets containing variants which were annotated as noncoding related, splice sites, untranslated regions, metabolic quantitative trait loci, and young variants ranked highest in terms of their contribution to the traits’ genetic variance. We were able to show that linkage disequilibrium between subset variants and adjacent variants did not cause these subsets’ high effect. Conclusion Our results confirm the connection of milk production and health traits in dairy cattle via the animals’ metabolic state. In addition, they highlight the potential of including functional information in genomic analyses, which helps to dissect the extent and direction of the observed traits’ connection in more detail.https://doi.org/10.1186/s12864-024-10115-6Dairy cattleHealth traitsMilk productionGenomic predictionGenome annotationFunctional information |
| spellingShingle | Helen Schneider Ana-Marija Krizanac Clemens Falker-Gieske Johannes Heise Jens Tetens Georg Thaller Jörn Bennewitz Genomic dissection of the correlation between milk yield and various health traits using functional and evolutionary information about imputed sequence variants of 34,497 German Holstein cows BMC Genomics Dairy cattle Health traits Milk production Genomic prediction Genome annotation Functional information |
| title | Genomic dissection of the correlation between milk yield and various health traits using functional and evolutionary information about imputed sequence variants of 34,497 German Holstein cows |
| title_full | Genomic dissection of the correlation between milk yield and various health traits using functional and evolutionary information about imputed sequence variants of 34,497 German Holstein cows |
| title_fullStr | Genomic dissection of the correlation between milk yield and various health traits using functional and evolutionary information about imputed sequence variants of 34,497 German Holstein cows |
| title_full_unstemmed | Genomic dissection of the correlation between milk yield and various health traits using functional and evolutionary information about imputed sequence variants of 34,497 German Holstein cows |
| title_short | Genomic dissection of the correlation between milk yield and various health traits using functional and evolutionary information about imputed sequence variants of 34,497 German Holstein cows |
| title_sort | genomic dissection of the correlation between milk yield and various health traits using functional and evolutionary information about imputed sequence variants of 34 497 german holstein cows |
| topic | Dairy cattle Health traits Milk production Genomic prediction Genome annotation Functional information |
| url | https://doi.org/10.1186/s12864-024-10115-6 |
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