Recurrent Laryngeal Neuropathy (RLN) is a distal axonopathy of unknown etiology that results in the partial or total collapse of the left side of the larynx in up to 11 percent of Thoroughbreds (TBs). The consequent obstruction to air movement results in diminished racing performance and necessitates surgical correction. Although it has an inherited tendency, RLN does not follow a Mendelian pattern, and inheritance is likely multigenic. In fact, so little is known of the pathogenesis of RLN that it is impossible to develop a list of potential candidate genes. Under such conditions, a genome-wide association study (GWAS) can be used to identify genes that contribute to RLN pathogenesis. We propose to use a GWAS in a population-based study to test the hypothesis that there are genetic variants that contribute significantly to the pathogenesis of clinically expressed RLN. The study will use a 300 case/300 control cohort of samples from TBs (over 500 samples are already collected) under development by the Co-PI (Robinson). Objective 1 (Year 1) is to complete sample collection and archiving that have been ongoing since 2008. Blood samples from cases (grade 3 or 4 RLN-affected horses undergoing corrective surgery) will continue to be submitted by co-operating equine surgeons highly experienced in diagnosis and grading of the condition. Controls are endoscopically-examined older TBs with grade 1 (normal) laryngeal function. This selection of horses includes only the most informative horses for genotyping (no grade 2 category). In Objective 2, the EquineSNP50 Infinium BeadChip from Illumina, which carries 54,000 single nucleotide polymorphisms (SNPs), will be used to perform a genome-wide association study. Genotyping will be conducted at the Cornell Life Sciences Core Facility. Association analysis will be performed by the geneticists (Swinburne – AHT; Todhunter, Zhang – CU) using PLINK and custom software. Population stratification will be investigated and accounted for if necessary. Basic association tests will initially be performed and permutation procedures used to correct for multiple testing. Tests that investigate both single SNPs and haplotype blocks of several SNPs will also be performed. Disease associated haplotypes will be investigated using HAPLOVIEW software. All genetic analyses will be conducted on anonymized data. The identification of genes that confer risk of RLN will contribute substantially to the understanding of the disease etiology. It is also important to discover genes that cause such a career-threatening condition for equine athletes. If genes associated with RLN can be identified, selection towards reducing the prevalence of this disease in the equine population can begin.