Quantifying the effects of the mitochondrial genome on milk production traits in dairy cows: empirical results and modelling challenges.

Significant advances in livestock traits have been achieved primarily through selection strategies targeting variation in the nuclear genome, with little attention given to mitogenome variation. We analyzed the influence of the mitogenome on milk production traits of Holstein cattle in Croatia based on strategically generated next-generation sequencing data for 109 cows pedigree-linked to 7115 milk production records (milk, fat and protein yield) from 3006 cows (first 5 lactations). Since little is known about the biology of the relationship between mitogenome variation and production traits, our quantitative genetic modeling was complex. Thus, the proportion of total variance explained by mitogenome inheritance was estimated using 5 different models: (1) cytoplasmic model with maternal lineages (CYTO), (2) haplotypic model with mitogenome sequences (HAPLO), (3) amino acid model with unique amino acid sequences (AMINO), (4) evolutionary model based on a phylogenetic analysis using Bayesian Evolutionary Analysis Sampling Trees phylogenetic analysis (EVOL), and (5) mitogenome SNP model (SNPmt). The polygenic autosomal and X chromosome additive genetic effects based on pedigree were modeled, together with the effects of herd-year-season interaction, permanent environment, location, and age at first calving. The estimated proportions of phenotypic variance explained by mitogenome in 4 different models (CYTO, HAPLO, AMINO, and SNPmt) were found to be substantial given the size of mitogenome, ranging from 5% to 7% for all 3 milk traits. At the same time, a negligible proportion of the phenotypic variance was explained by mitogenome with the EVOL model. Similarly, in all models, no proportion of phenotypic variance was explained by the X chromosome. Although our results should be confirmed in other dairy cattle populations, including a large number of sequenced mitogenomes and nuclear genomes, the potential of utilizing mitogenome information in animal breeding is promising, especially as the acquisition of complete genome sequences becomes cost-effective.