Genetic Selection for Mastitis Resistance.

Mastitis is a prevalent and costly disease on dairy farms. Improved management and hygiene can reduce the risk of infection by contagious or environmental pathogens, and genetic selection can confer permanent improvement in mastitis resistance. National veterinary recording systems in the Nordic countries have allowed direct selection for sire families with low incidence of clinical mastitis for 3 decades, whereas other countries have practiced indirect selection for lower somatic cell count. Recently, pooling of producer-recorded data from on-farm herd management software programs has enabled selection for reduced incidence of clinical mastitis in the United States and other leading dairy countries.

An across-breed genome wide association analysis of susceptibility to paratuberculosis in dairy cattle.

Paratuberculosis is a chronic disease of ruminants caused by Mycobacterium avium subspecies paratuberculosis (MAP). It occurs worldwide and causes a significant loss in the animal production industry. There is no cure for MAP infection and vaccination is problematic. Identification of genetics of susceptibility could be a useful adjunct for programs that focus on management, testing and culling of diseased animals. A case-control, genome-wide association study (GWAS) was conducted using Holstein and Jersey cattle in a combined analysis in order to identify markers and chromosomal regions associated with susceptibility to MAP infection across-breed. A mixed-model method (GRAMMAR-GC) implemented in the GenABEL R package and a Bayes C analysis implemented in GenSel software were used as alternative approaches to conduct GWAS analysis focused on single SNPs and chromosomal segments, respectively. After conducting quality control, 22 406 SNPs from 2157 individuals were available for the GRAMMAR-GC (Bayes C) analysis and 45 640 SNPs from 2199 individuals were available for the Bayes C analysis. One SNP located on BTA27 (8·6 Mb) was identified as moderately associated (P < 5 × 10-5, FDR = 0·44) in the GRAMMAR-GC analysis of the combined breed data. Nine 1 Mb windows located on BTA 2, 3 (3 windows), 6, 8, 25, 27 and 29 each explained ≥1% of the total proportion of genetic variance in the Bayes C analysis. In an analysis ignoring differences in linkage phase, two moderately significantly associated SNPs were identified; ARS-BFGL-NGS-19381 on BTA23 (32 Mb) and Hapmap40994-BTA-46361 on BTA19 (61 Mb). New common genomic regions and candidate genes have been identified from the across-breed analysis that might be involved in the immune response and susceptibility to MAP infection.

Genome-wide association study of susceptibility to infection by Mycobacterium avium subspecies paratuberculosis in Holstein cattle.

Paratuberculosis, or Johne's disease, is a chronic, granulomatous, gastrointestinal tract disease of cattle and other ruminants caused by the bacterium Mycobacterium avium, subspecies paratuberculosis (MAP). Control of Johne's disease is based on programs of testing and culling animals positive for infection with MAP while concurrently modifying management to reduce the likelihood of infection. The current study is motivated by the hypothesis that genetic variation in host susceptibility to MAP infection can be dissected and quantifiable associations with genetic markers identified. For this purpose, a case-control, genome-wide association study was conducted using US Holstein cattle phenotyped for MAP infection using a serum ELISA and/or fecal culture test. Cases included cows positive for either serum ELISA, fecal culture or both. Controls consisted of animals negative for the serum ELISA test or both serum ELISA and fecal culture when both were available. Controls were matched by herd and proximal birth date with cases. A total of 856 cows (451 cases and 405 controls) were used in initial discovery analyses, and an additional 263 cows (159 cases and 104 controls) from the same herds were used as a validation data set. Data were analyzed in a single marker analysis controlling for relatedness of individuals (GRAMMAR-GC) and also in a Bayesian analysis in which multiple marker effects were estimated simultaneously (GenSel). For the latter, effects of non-overlapping 1 Mb marker windows across the genome were estimated. Results from the two discovery analyses were generally concordant; however, discovery results were generally not well supported in analysis of the validation data set. A combined analysis of discovery and validation data sets provided strongest support for SNPs and 1 Mb windows on chromosomes 1, 2, 6, 7, 17 and 29.

Genome-wide association analysis and genomic prediction of Mycobacterium avium subspecies paratuberculosis infection in US Jersey cattle.

Paratuberculosis (Johne's disease), an enteric disorder in ruminants caused by Mycobacterium avium subspecies paratuberculosis (MAP), causes economic losses in excess of $200 million annually to the US dairy industry. To identify genomic regions underlying susceptibility to MAP infection in Jersey cattle, a case-control genome-wide association study (GWAS) was performed. Blood and fecal samples were collected from ∼ 5,000 mature cows in 30 commercial Jersey herds from across the US. Discovery data consisted of 450 cases and 439 controls genotyped with the Illumina BovineSNP50 BeadChip. Cases were animals with positive ELISA and fecal culture (FC) results. Controls were animals negative to both ELISA and FC tests that matched cases on birth date and herd. Validation data consisted of 180 animals including 90 cases (positive to FC) and 90 controls (negative to ELISA and FC), selected from discovery herds and genotyped by Illumina BovineLD BeadChip (∼ 7K SNPs). Two analytical approaches were used: single-marker GWAS using the GRAMMAR-GC method and Bayesian variable selection (Bayes C) using GenSel software. GRAMMAR-GC identified one SNP on BTA7 at 68 megabases (Mb) surpassing a significance threshold of 5 × 10(-5). ARS-BFGL-NGS-11887 on BTA23 (27.7 Mb) accounted for the highest percentage of genetic variance (3.3%) in the Bayes C analysis. SNPs identified in common by GRAMMAR-GC and Bayes C in both discovery and combined data were mapped to BTA23 (27, 29 and 44 Mb), 3 (100, 101, 106 and 107 Mb) and 17 (57 Mb). Correspondence between results of GRAMMAR-GC and Bayes C was high (70-80% of most significant SNPs in common). These SNPs could potentially be associated with causal variants underlying susceptibility to MAP infection in Jersey cattle. Predictive performance of the model developed by Bayes C for prediction of infection status of animals in validation set was low (55% probability of correct ranking of paired case and control samples).

Genetic susceptibility to paratuberculosis.

Multiple studies indicate that host animal genetics play a role in susceptibility to Mycobacterium avium subsp. paratuberculosis (MAP) infection. However, due to differences in methods used to define MAP-infected animals and controls and differences in methods of genetic analysis, there is as yet no clear consensus on the genes or markers to reliably define the MAP infection susceptibility of any animal species. Meta-analysis of combined studies and larger studies will help resolve the situation in the coming years.