Estimation of (co)variances for genomic regions of flexible sizes: application to complex infectious udder diseases in dairy cattle.
BACKGROUND
Multi-trait genomic models in a Bayesian context can be used to estimate genomic (co)variances, either for a complete genome or for genomic regions (e.g. per chromosome) for the purpose of multi-trait genomic selection or to gain further insight into the genomic architecture of related traits such as mammary disease traits in dairy cattle.


METHODS
Data on progeny means of six traits related to mastitis resistance in dairy cattle (general mastitis resistance and five pathogen-specific mastitis resistance traits) were analyzed using a bivariate Bayesian SNP-based genomic model with a common prior distribution for the marker allele substitution effects and estimation of the hyperparameters in this prior distribution from the progeny means data. From the Markov chain Monte Carlo samples of the allele substitution effects, genomic (co)variances were calculated on a whole-genome level, per chromosome, and in regions of 100 SNP on a chromosome.


RESULTS
Genomic proportions of the total variance differed between traits. Genomic correlations were lower than pedigree-based genetic correlations and they were highest between general mastitis and pathogen-specific traits because of the part-whole relationship between these traits. The chromosome-wise genomic proportions of the total variance differed between traits, with some chromosomes explaining higher or lower values than expected in relation to chromosome size. Few chromosomes showed pleiotropic effects and only chromosome 19 had a clear effect on all traits, indicating the presence of QTL with a general effect on mastitis resistance. The region-wise patterns of genomic variances differed between traits. Peaks indicating QTL were identified but were not very distinctive because a common prior for the marker effects was used. There was a clear difference in the region-wise patterns of genomic correlation among combinations of traits, with distinctive peaks indicating the presence of pleiotropic QTL.


CONCLUSIONS
The results show that it is possible to estimate, genome-wide and region-wise genomic (co)variances of mastitis resistance traits in dairy cattle using multivariate genomic models.
University of Aarhus, Faculty of Science and Technology, Department of Molecular Biology and Genetics, DK-8830, Tjele, Denmark. LarsPeter.Sorensen@agrsci.dk
Lars P
LP
Sørensen
Luc
L
Janss
Per
P
Madsen
Thomas
T
Mark
Mogens S
MS
Lund
D000483:Alleles; D000818:Animals; D001499:Bayes Theorem; D002417:Cattle / Q000235:genetics*; D033481:Chromosomes, Mammalian / Q000235:genetics; D004926:Escherichia coli / Q000472:pathogenicity; D005260:Female; D056726:Genetic Association Studies / Q000379:methods; D058685:Genetic Pleiotropy; D020022:Genetic Predisposition to Disease; D059646:Genome Size; D008321:Mammary Glands, Animal / Q000382:microbiology*; D008390:Markov Chains; D008414:Mastitis, Bovine / Q000382:microbiology*; D008957:Models, Genetic; D009010:Monte Carlo Method; D015999:Multivariate Analysis; D010375:Pedigree; D020641:Polymorphism, Single Nucleotide; D040641:Quantitative Trait Loci; D019655:Quantitative Trait, Heritable; D015203:Reproducibility of Results; D013211:Staphylococcus aureus / Q000302:isolation & purification / Q000472:pathogenicity; D013291:Streptococcus / Q000472:pathogenicity