Exploring genetics of trotting using a Nordic horse model

Last changed: 15 May 2019

Horses have been strongly selected for speed, strength, and endurance-exercise traits since the onset of domestication. As a result, highly specialized horse breeds have developed with many modern horse breeds often representing closed populations with high phenotypic and genetic uniformity. However, a great deal of variation still exists between breeds, making the horse particularly well suited for genetic studies of athleticism.

To identify genomic regions associated with athleticism as it pertains to trotting racing ability in the horse, the current study applies a pooled sequence analysis approach using a unique Nordic horse model.

Results

Pooled sequence data from three Nordic horse populations were used for FST analysis. After strict filtering, FST analysis yielded 580 differentiated regions for trotting racing ability. Candidate regions on equine chromosomes 7 and 11 contained the largest number of SNPs (n = 214 and 147, respectively). GO analyses identified multiple genes related to intelligence, energy metabolism, and skeletal development as potential candidate genes. However, only one candidate region for trotting racing ability overlapped a known racing ability QTL.

Conclusions

Not unexpected for genomic investigations of complex traits, the current study identified hundreds of candidate regions contributing to trotting racing ability in the horse. Likely resulting from the cumulative effects of many variants across the genome, racing ability continues to demonstrate its polygenic nature with candidate regions implicating genes influencing both musculature and neurological development.

Link to the publication

https://doi.org/10.1186/s12864-019-5484-9

Reference

Brandon D Velie, Mette Lillie, Kim Jäderkvist Fegraeus, Maria K Rosengren, Marina Solé, Maja Wiklund, Carl-Fredrik Ihler, Eric Strand & Gabriella Lindgren (2019). Exploring the genetics of trotting racing ability in horses using a unique Nordic horse model. BMC Genomics 2019; 20:104.