Detection of candidate genes associated with mastitis resistance in dairy cattle

Mastitis is the most frequent and costly disease that dairy producers all over the world face. Due to the etiology of this complex disease, conventional ways of prevention have yielded limited progress. Beside management strategies, a promising approach to control mastitis in dairy farms is the genetic improvement of the population. Due to low heritability of clinical mastitis and its indicator somatic cell score (SCS), traditional ways of selection have limited success. Alternatively, selective breeding based on genomic information is more accurate and could become sustainable practice. To effectively apply genomic information in selection decisions, reliable knowledge of genetic effects associated with clinical mastitis or SCS in breeding populations is desirable.
The availability of high-throughput genotyping technology has opened the field for animal genetics to perform genome wide association studies (GWAS) using single nucleotide polymorphism (SNP) markers. After estimating SNP effects, these effects can be used to calculate genomic breeding values. Albeit GWAS are powerful to identify genomic loci with high precision, false positive associations due to confounding effects and missing associations due to low level of linkage disequilibrium (LD) have been considered as limiting factors. The most important confounding effect is the population sub-structure, which can cause misleading results. Although GWAS based on single markers lead to significant findings, analyses based on haplotypes could shed new light on genetic determinants of mastitis and may identify loci that are not captured by single marker approach or that reveal the combinatory effect of loci. Because some false results might still remain, even after correction for population stratification, validation studies are important to verify associations.