High-resolution population structure and runs of homozygosity reveal the genetic architecture of complex traits in the Lipizzan horse

BACKGROUND

The sample ascertainment bias due to complex population structures remains a major challenge in genome-wide investigations of complex traits. In this study we derived the high-resolution population structure and levels of autozygosity of 377 Lipizzan horses originating from five different European stud farms utilizing the SNP genotype information of the high density 700 k Affymetrix Axiom™ Equine genotyping array. Scanning the genome for overlapping runs of homozygosity (ROH) shared by more than 50% of horses, we identified homozygous regions (ROH islands) in order to investigate the gene content of those candidate regions by gene ontology and enrichment analyses.

RESULTS

The high-resolution population network approach revealed well-defined substructures according to the origin of the horses (Austria, Slovakia, Croatia and Hungary). The highest mean genome coverage of ROH (SROH) was identified in the Austrian (SROH = 342.9), followed by Croatian (SROH = 214.7), Slovakian (SROH = 205.1) and Hungarian (SROH = 171.5) subpopulations. ROH island analysis revealed five common islands on ECA11 and ECA14, hereby confirming a closer genetic relationship between the Hungarian and Croatian as well as between the Austrian and Slovakian samples. Private islands were detected for the Hungarian and the Austrian Lipizzan subpopulations. All subpopulations shared a homozygous region on ECA11, nearly identical in position and length containing among other genes the homeobox-B cluster, which was also significantly (p < 0.001) highlighted by enrichment analysis. Gene ontology terms were mostly related to biological processes involved in embryonic morphogenesis and anterior/posterior specification. Around the STX17 gene (causative for greying), we identified a ROH island harbouring the genes NR4A3, STX17, ERP44 and INVS. Within further islands on ECA14, ECA16 and ECA20 we detected the genes SPRY4, NDFIP1, IMPDH2, HSP90AB1, whereas SPRY4 and HSP90AB1 are involved in melanoma metastasis and survival rate of melanoma patients in humans.

CONCLUSIONS

We demonstrated that the assessment of high-resolution population structures within one single breed supports the downstream genetic analyses (e.g. the identification of ROH islands). By means of ROH island analyses, we identified the genes SPRY4, NDFIP1, IMPDH2, HSP90AB1, which might play an important role for further studies on equine melanoma. Furthermore, our results highlighted the impact of the homeobox-A and B cluster involved in morphogenesis of Lipizzan horses.