STRING data mining of GWAS data in canine hereditary pigment-associated deafness
Document Type
Article
Publication Date
6-1-2020
Abstract
Most canine deafness is linked to white pigmentation caused by the piebald locus, shown to be the gene (), but studies have failed to identify a deafness cause. The coding regions of have not been shown to be mutated in deaf dogs, leading us to pursue genes acting on or controlled by . We have genotyped DNA from 502 deaf and hearing Australian cattle dogs, Dalmatians, and English setters, breeds with a high deafness prevalence. Genome-wide significance was not attained in any of our analyses, but we did identify several suggestive associations. Genome-wide association studies (GWAS) in complex hereditary disorders frequently fail to identify causative gene variants, so advanced bioinformatics data mining techniques are needed to extract information to guide future studies. STRING diagrams are graphical representations of known and predicted networks of protein-protein interactions, identifying documented relationships between gene proteins based on the scientific literature, to identify functional gene groupings to pursue for further scrutiny. The STRING program predicts associations at a preset confidence level and suggests biological functions based on the identified genes. Starting with (1) genes within 500 kb of GWAS-suggested SNPs, (2) known pigmentation genes, (3) known human deafness genes, and (4) genes identified from proteomic analysis of the cochlea, we generated STRING diagrams that included these genes. We then reduced the number of genes by excluding genes with no relationship to auditory function, pigmentation, or relevant structures, and identified clusters of genes that warrant further investigation.
Publication Source (Journal or Book title)
Veterinary and animal science
First Page
100118
Recommended Citation
Kelly-Smith, M., & Strain, G. M. (2020). STRING data mining of GWAS data in canine hereditary pigment-associated deafness. Veterinary and animal science, 9, 100118. https://doi.org/10.1016/j.vas.2020.100118