The bovine foot skin microbiota is associated with host genotype and the development of infectious digital dermatitis lesions.

BACKGROUND: Bovine Digital Dermatitis (BDD) is a prevalent infectious disease, causing painful foot skin lesions and lameness in cattle. We describe herein the bovine foot skin microbiota and its associations with BDD using 16S rRNA gene amplicon and shotgun metagenomic sequencing on samples from 259 dairy cows from three UK dairy farms. RESULTS: We show evidence of dysbiosis, and differences in taxonomy and functional profiles in the bovine foot skin microbiome of clinically healthy animals that subsequently develop BDD lesions, compared to those that do not. Our results suggest that taxonomical and functional differences together with alterations in ecological interactions between bacteria in the normal foot skin microbiome may predispose an animal to develop BDD lesions. Using genome-wide association and regional heritability mapping approaches, we provide first evidence for interactions between host genotype and certain members of the foot skin microbiota. We show the existence of significant genetic variation in the relative abundance of Treponema spp. and Peptoclostridium spp. and identify regions in the bovine genome that explain a significant proportion of this variation. CONCLUSIONS: Collectively this work shows early changes in taxonomic and functional profiles of the bovine foot-skin microbiota in clinically healthy animals which are associated with subsequent development of BDD and could be relevant to prevention of disease. The description of host genetic control of members of the foot skin microbiota, combined with the association of the latter with BDD development offer new insights into a complex relationship that can be exploited in selective breeding programmes. Video Abstract.

Genetic dissection of complex behaviour traits in German Shepherd dogs.

A favourable genetic structure and diversity of behavioural features highlights the potential of dogs for studying the genetic architecture of behaviour traits. However, behaviours are complex traits, which have been shown to be influenced by numerous genetic and non-genetic factors, complicating their analysis. In this study, the genetic contribution to behaviour variation in German Shepherd dogs (GSDs) was analysed using genomic approaches. GSDs were phenotyped for behaviour traits using the established Canine Behavioural Assessment and Research Questionnaire (C-BARQ). Genome-wide association study (GWAS) and regional heritability mapping (RHM) approaches were employed to identify associations between behaviour traits and genetic variants, while accounting for relevant non-genetic factors. By combining these complementary methods we endeavoured to increase the power to detect loci with small effects. Several behavioural traits exhibited moderate heritabilities, with the highest identified for Human-directed playfulness, a trait characterised by positive interactions with humans. We identified several genomic regions associated with one or more of the analysed behaviour traits. Some candidate genes located in these regions were previously linked to behavioural disorders in humans, suggesting a new context for their influence on behaviour characteristics. Overall, the results support dogs as a valuable resource to dissect the genetic architecture of behaviour traits and also highlight the value of focusing on a single breed in order to control for background genetic effects and thus avoid limitations of between-breed analyses.

Accuracy of genotype imputation in Labrador Retrievers.

The dog is a valuable model species for the genetic analysis of complex traits, and the use of genotype imputation in dogs will be an important tool for future studies. It is of particular interest to analyse the effect of factors like single nucleotide polymorphism (SNP) density of genotyping arrays and relatedness between dogs on imputation accuracy due to the acknowledged genetic and pedigree structure of dog breeds. In this study, we simulated different genotyping strategies based on data from 1179 Labrador Retriever dogs. The study involved 5826 SNPs on chromosome 1 representing the high density (HighD) array; the low-density (LowD) array was simulated by masking different proportions of SNPs on the HighD array. The correlations between true and imputed genotypes for a realistic masking level of 87.5% ranged from 0.92 to 0.97, depending on the scenario used. A correlation of 0.92 was found for a likely scenario (10% of dogs genotyped using HighD, 87.5% of HighD SNPs masked in the LowD array), which indicates that genotype imputation in Labrador Retrievers can be a valuable tool to reduce experimental costs while increasing sample size. Furthermore, we show that genotype imputation can be performed successfully even without pedigree information and with low relatedness between dogs in the reference and validation sets. Based on these results, the impact of genotype imputation was evaluated in a genome-wide association analysis and genomic prediction in Labrador Retrievers.

Assessing the impact of genomic selection against hip dysplasia in the Labrador Retriever dog.

Many purebred dogs exhibit a higher prevalence of inherited diseases compared with non-purebred dogs. One of the most popular breeds in the UK is the Labrador Retriever, which has a high prevalence of hip dysplasia resulting in high costs for surgical operations and impaired animal welfare. Considering the many complications of highly managed populations, mainly due to breeder's conventions and the resulting population structure, is of great importance for the proper development of a strategy against the disease. In this study, we have compared the utilities and performances of both genomic and phenotypic selection against hip dysplasia in a simulated population with the characteristics of the British Veterinary Association and Kennel Club (BV /KC) hip dysplasia scheme. The results confirm the potential benefits of genomic selection by showing a moderate increase of 1.15-fold (assuming a realistic accuracy of r(2) = 0.5) in response to selection due to the higher accuracy (between 0.96- and 1.32-fold, considering 0.35 ≤ r(2) ≤ 0.7) and more than a threefold increase when all the offspring in each litter are tested (between 3.25- and 4.55-fold, again considering 0.35 ≤ r(2) ≤ 0.7).