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Genetic Architecture of Milk, Fat, Protein, Mastitis and Fertility Studied Using NGS Data in Holstein Cattle

Thursday, August 21, 2014: 10:45 AM
Bayshore Grand Ballroom E-F (The Westin Bayshore)
Goutam Sahana , Center for Quantitative Genetics and Genomics, Department of Molecular Biology and Genetics, Aarhus University, Tjele, Denmark
Luc Janss , Center for Quantitative Genetics and Genomics, Department of Molecular Biology and Genetics, Aarhus University, Tjele, Denmark
Bernt Guldbrandtsen , Center for Quantitative Genetics and Genomics, Department of Molecular Biology and Genetics, Aarhus University, Tjele, Denmark
Mogens Sandø Lund , Center for Quantitative Genetics and Genomics, Department of Molecular Biology and Genetics, Aarhus University, Tjele, Denmark
Recorded Presentation (mp4)
Abstract Text: The use of genomic information in genetic evaluation has revolutionized dairy cattle breeding. It remains a major challenge to understand the genetic basis of variation for quantitative traits. Here, we study the genetic architecture for milk, fat, protein, mastitis and fertility indices in dairy cattle using NGS variants. The analysis was done using a linear mixed model (LMM) and a Bayesian mixture model (BMM). The top 10 QTL identified by LMM analyses explained 22.61, 23.86, 10.88, 18.58 and 14.83% of the total genetic variance for these traits respectively. Trait-specific sets of 4,964 SNPs from NGS variants (most ‘associated’ SNP for each 0.5 Mbp bin) explained 81.0, 81.6, 85.0, 60.4 and 70.9% of total genetic variance for milk, fat, protein, mastitis and fertility indices when analyzed simultaneously by BMM.

Keywords:

dairy cattle
genetic architecture
QTL effect

See more of: Statistical and Genomic Tools for Mapping QTL and Genes (Dairy and Beef)
See more of: Methods and Tools: Statistical and genomic tools for mapping QTL and genes
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