Dataset Information

Genome-Wide Association Studies Reveal Susceptibility Loci for Digital Dermatitis in Holstein Cattle.

ABSTRACT: Digital dermatitis (DD) causes lameness in dairy cattle. To detect the quantitative trait loci (QTL) associated with DD, genome-wide association studies (GWAS) were performed using high-density single nucleotide polymorphism (SNP) genotypes and binary case/control, quantitative (average number of FW per hoof trimming record) and recurrent (cases with ?2 DD episodes vs. controls) phenotypes from cows across four dairies (controls n = 129 vs. FW n = 85). Linear mixed model (LMM) and random forest (RF) approaches identified the top SNPs, which were used as predictors in Bayesian regression models to assess the SNP predictive value. The LMM and RF analyses identified QTL regions containing candidate genes on Bos taurus autosome (BTA) 2 for the binary and recurrent phenotypes and BTA7 and 20 for the quantitative phenotype that related to epidermal integrity, immune function, and wound healing. Although larger sample sizes are necessary to reaffirm these small effect loci amidst a strong environmental effect, the sample cohort used in this study was sufficient for estimating SNP effects with a high predictive value.

SUBMITTER: Lai E

PROVIDER: S-EPMC7693332 | biostudies-literature | 2020 Oct

REPOSITORIES: biostudies-literature

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Genome-Wide Association Studies Reveal Susceptibility Loci for Digital Dermatitis in Holstein Cattle.

Lai Ellen E Danner Alexa L AL Famula Thomas R TR Oberbauer Anita M AM

Animals : an open access journal from MDPI 20201031 11

Digital dermatitis (DD) causes lameness in dairy cattle. To detect the quantitative trait loci (QTL) associated with DD, genome-wide association studies (GWAS) were performed using high-density single nucleotide polymorphism (SNP) genotypes and binary case/control, quantitative (average number of FW per hoof trimming record) and recurrent (cases with ≥2 DD episodes vs. controls) phenotypes from cows across four dairies (controls <i>n</i> = 129 vs. FW <i>n</i> = 85). Linear mixed model (LMM) and ...[more]

PMID: 33142934

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Project description:Sole ulcers (SUs) and white line disease (WLD) are two common noninfectious claw lesions (NICL) that arise due to a compromised horn production and are frequent causes of lameness in dairy cattle, imposing welfare and profitability concerns. Low to moderate heritability estimates of SU and WLD susceptibility indicate that genetic selection could reduce their prevalence. To identify the susceptibility loci for SU, WLD, SU and/or WLD, and any type of noninfectious claw lesion, genome-wide association studies (GWAS) were performed using generalized linear mixed model (GLMM) regression, chunk-based association testing (CBAT), and a random forest (RF) approach. Cows from five commercial dairies in California were classified as controls having no lameness records and ≥6 years old (n = 102) or cases having SU (n = 152), WLD (n = 117), SU and/or WLD (SU + WLD, n = 198), or any type of noninfectious claw lesion (n = 217). The top single nucleotide polymorphisms (SNPs) were defined as those passing the Bonferroni-corrected suggestive and significance thresholds in the GLMM analysis or those that a validated RF model considered important. Effects of the top SNPs were quantified using Bayesian estimation. Linkage disequilibrium (LD) blocks defined by the top SNPs were explored for candidate genes and previously identified, functionally relevant quantitative trait loci. The GLMM and CBAT approaches revealed the same regions of association on BTA8 for SU and BTA13 common to WLD, SU + WLD, and NICL. These SNPs had effects significantly different from zero, and the LD blocks they defined explained a significant amount of phenotypic variance for each dataset (6.1-8.1%, p < 0.05), indicating the small but notable contribution of these regions to susceptibility. These regions contained candidate genes involved in wound healing, skin lesions, bone growth and mineralization, adipose tissue, and keratinization. The LD block defined by the most significant SNP on BTA8 for SU included a SNP previously associated with SU. The RF models were overfitted, indicating that the SNP effects were very small, thereby preventing meaningful interpretation of SNPs and any downstream analyses. These findings suggested that variants associated with various physiological systems may contribute to susceptibility for NICL, demonstrating the complexity of genetic predisposition.

Project description:Sole ulcers (SU) and white line disease (WLD) are noninfectious claw lesions that arise due to compromised horn production and are common causes of lameness in dairy cattle, imposing welfare and profitability concerns. The low to moderate heritability estimates of SU and WLD susceptibility indicate that genetic selection could reduce their prevalence. To identify loci associated with SU and WLD susceptibility, generalized linear mixed model (GLMM) regression and random forest (RF) genome-wide association studies (GWAS) were performed. Cows from five commercial dairies in California were classified as sound controls having no instances of lameness and above six years of age (n = 102) or cases having SU (n = 152), WLD (n = 117), SU and/or WLD (SU+WLD, n = 198), or any type of noninfectious claw lesion (n = 217). Top SNPs were defined as those passing Bonferroni-corrected suggestive and significance thresholds in the GLMM analysis or those that a validated RF model considered important. Effects of top SNPs were quantified using Bayesian estimation. Linkage disequilibrium (LD) blocks defined by top SNPs were explored for candidate genes and previously identified, functionally relevant quantitative trait loci. The GLMM GWAS revealed regions of association on BTA8 for SU and BTA13 common to WLD, SU+WLD, and noninfectious claw lesions. Bayesian estimation of effect sizes indicated that these SNPs had effects significantly different from zero, indicating their small but notable contribution to susceptibility. Promising candidate genes identified in these regions were involved in wound healing, skin lesions, bone growth and mineralization, adipose tissue, and keratinization. The LD block defined by the most significant SNP on BTA8 for SU included a SNP previously reported to be associated with SU. The RF models were overfitted, indicating that SNP effects were very small and thereby preventing meaningful interpretation of SNPs with the highest importance values and downstream analyses. These findings suggested that variants associated with a variety of physiological systems may contribute to susceptibility for noninfectious claw lesions, demonstrating the complexity of genetic predisposition.

Project description:BackgroundFor infectious diseases, the probability that an animal gets infected depends on its own susceptibility, and on the number of infectious herd mates and their infectivity. Together with the duration of the infectious period, susceptibility and infectivity determine the basic reproduction ratio of the disease ([Formula: see text]). [Formula: see text] is the average number of secondary cases caused by a typical infectious individual in an otherwise uninfected population. An infectious disease dies out when [Formula: see text] is lower than 1. Thus, breeding strategies that aim at reducing disease prevalence should focus on reducing [Formula: see text], preferably to a value lower than 1. In animal breeding, however, [Formula: see text] has received little attention. Here, we estimate the additive genetic variance in host susceptibility, host infectivity, and [Formula: see text] for the endemic claw disease digital dermatitis (DD) in Holstein Friesian dairy cattle, and estimate genomic breeding values (GEBV) for these traits. We recorded DD disease status of both hind claws of 1513 cows from 12 Dutch dairy farms, every 2 weeks, 11 times. The genotype data consisted of 75,904 single nucleotide polymorphisms (SNPs) for 1401 of the cows. We modelled the probability that a cow got infected between recordings, and compared four generalized linear mixed models. All models included a genetic effect for susceptibility; Models 2 and 4 also included a genetic effect for infectivity, while Models 1 and 2 included a farm*period interaction. We corrected for variation in exposure to infectious herd mates via an offset.ResultsGEBV for [Formula: see text] from the model that included genetic effects for susceptibility only had an accuracy of ~ 0.39 based on cross-validation between farms, which is very high given the limited amount of data and the complexity of the trait. Models with a genetic effect for infectivity showed a larger bias, but also a slightly higher accuracy of GEBV. Additive genetic standard deviation for [Formula: see text] was large, i.e. ~ 1.17, while the mean [Formula: see text] was 2.36.ConclusionsGEBV for [Formula: see text] showed substantial variation. The mean [Formula: see text] was only about one genetic standard deviation greater than 1. These results suggest that lowering DD prevalence by selective breeding is promising.

Dataset Information

Genome-Wide Association Studies Reveal Susceptibility Loci for Digital Dermatitis in Holstein Cattle.

Publications

Genome-Wide Association Studies Reveal Susceptibility Loci for Digital Dermatitis in Holstein Cattle.

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