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Weighting sequence variants based on their annotation increases the power of genome-wide association studies in dairy cattle.

ABSTRACT: BACKGROUND:Genome-wide association studies (GWAS) are widely used to identify regions of the genome that harbor genetic determinants of quantitative traits. However, the multiple-testing burden from scanning tens of millions of whole-genome sequence variants reduces the power to identify associated variants, especially if sample size is limited. In addition, factors such as inaccuracy of imputation, complex linkage disequilibrium structures, and multiple closely-located causal variants may result in an identified causative mutation not being the most significant single nucleotide polymorphism in a particular genomic region. Therefore, the use of information from different sources, particularly variant annotations, was proposed to enhance the fine-mapping of causal variants. Here, we tested whether applying significance thresholds based on variant annotation categories increases the power of GWAS compared with a flat Bonferroni multiple-testing correction. RESULTS:Whole-genome sequence variants in dairy cattle were categorized according to type and predicted impact. Then, GWAS between markers and 17 quantitative traits were analyzed for enrichment for association of each annotation category. By using annotation categories that were determined with the variants effect predictor software and datasets indicating regions of open chromatin, "low impact" variants were found to be highly enriched. Moreover, when the variants annotated as "modifier" and not located at open chromatin regions were further classified into different types of potential regulatory elements, the high impact variants, moderate impact variants, variants located in the 3' and 5' untranslated regions, and variants located in potential non-coding RNA regions exhibited relatively more enrichment. In contrast, a similar study on human GWAS data reported that enrichment of association signals was highest with high impact variants. We observed an increase in power when these variant category-based significance thresholds were applied for GWAS results on stature in Nordic Holstein cattle, as more candidate genes from previous large GWAS meta-analysis for cattle stature were confirmed. CONCLUSIONS:Use of variant category-based genome-wide significance thresholds can marginally increase the power to detect the candidate genes in cattle. With the continued improvements in annotation of the bovine genome, we anticipate that the growing usefulness of variant category-based significance thresholds will be demonstrated.

SUBMITTER: Cai Z

PROVIDER: S-EPMC6511139 | biostudies-literature | 2019 May

REPOSITORIES: biostudies-literature

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Weighting sequence variants based on their annotation increases the power of genome-wide association studies in dairy cattle.

Cai Zexi Z Guldbrandtsen Bernt B Lund Mogens Sandø MS Sahana Goutam G

Genetics, selection, evolution : GSE 20190510 1

<h4>Background</h4>Genome-wide association studies (GWAS) are widely used to identify regions of the genome that harbor genetic determinants of quantitative traits. However, the multiple-testing burden from scanning tens of millions of whole-genome sequence variants reduces the power to identify associated variants, especially if sample size is limited. In addition, factors such as inaccuracy of imputation, complex linkage disequilibrium structures, and multiple closely-located causal variants m ...[more]

PMID: 31077144

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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.

Dataset Information

Weighting sequence variants based on their annotation increases the power of genome-wide association studies in dairy cattle.

Publications

Weighting sequence variants based on their annotation increases the power of genome-wide association studies in dairy cattle.

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