The Markhoz goat provides an opportunity to study the genetics underlying coat color and mohair traits of an Angora type goat using genome-wide association studies (GWAS). This indigenous Iranian breed is valued for its quality mohair used in ceremonial garments and has the distinction of exhibiting an array of coat colors including black, brown, and white. Here, we performed 16 GWAS for different fleece (mohair) traits and coat color in 228 Markhoz goats sampled from the Markhoz Goat Research Station in Sanandaj, Kurdistan province, located in western Iran using the Illumina Caprine 50K beadchip. The Efficient Mixed Model Linear analysis was used to identify genomic regions with potential candidate genes contributing to coat color and mohair characteristics while correcting for population structure. Significant associations to coat color were found within or near the ASIP, ITCH, AHCY, and RALY genes on chromosome 13 for black and brown coat color and the KIT and PDGFRA genes on chromosome 6 for white coat color. Individual mohair traits were analyzed for genetic association along with principal components that allowed for a broader perspective of combined traits reflecting overall mohair quality and volume. A multitude of markers demonstrated significant association to mohair traits highlighting potential candidate genes of POU1F1 on chromosome 1 for mohair quality, MREG on chromosome 2 for mohair volume, DUOX1 on chromosome 10 for yearling fleece weight, and ADGRV1 on chromosome 7 for grease percentage. Variation in allele frequencies and haplotypes were identified for coat color and differentiated common markers associated with both brown and black coat color. This demonstrates the potential for genetic markers to be used in future breeding programs to improve selection for coat color and mohair traits. Putative candidate genes, both novel and previously identified in other species or breeds, require further investigation to confirm phenotypic causality and potential epistatic relationships.

The effect of prolactin (PRL), beta-lactoglobulin (beta-LG), and kappa-casein (CSN3) on milk yield was estimated in an East Friesian dairy sheep population from Old Chatham Sheepherding Company, New York. Genotypes were determined by PCR amplification followed by digestion with HaeIII and RsaI for PRL and beta-LG, respectively, and by PCR amplification for CSN3. Monthly milking records and pedigree information were used to evaluate the effect of each polymorphism on milk yield. Results indicated that PRL genotype had a significant effect on milk yield. Ewes carrying one A allele produced 110.6g more milk per day than ewes with no A alleles. There was no statistical difference between ewes with only one A allele and ewes with 2 A alleles. No association among polymorphisms at the beta-LG and CSN3 loci and milk yield was found. The results presented in this study indicate that the PRL gene is a potential marker that could be used in selection programs for improving milk yield in dairy sheep.

SummaryA previous study revealed a strong association between the DMRT3:Ser301STOP mutation in horses and alternate gaits as well as performance in harness racing. Several follow-up studies have confirmed a high frequency of the mutation in gaited horse breeds and an effect on gait quality. The aim of this study was to determine when and where the mutation arose, to identify additional potential causal mutations and to determine the coalescence time for contemporary haplotypes carrying the stop mutation. We utilized sequences from 89 horses representing 26 breeds to identify 102 SNPs encompassing the DMRT3 gene that are in strong linkage disequilibrium with the stop mutation. These 102 SNPs were genotyped in an additional 382 horses representing 72 breeds, and we identified 14 unique haplotypes. The results provided conclusive evidence that DMRT3:Ser301STOP is causal, as no other sequence polymorphisms showed an equally strong association to locomotion traits. The low sequence diversity among mutant chromosomes demonstrated that they must have diverged from a common ancestral sequence within the last 10 000 years. Thus, the mutation occurred either just before domestication or more likely some time after domestication and then spread across the world as a result of selection on locomotion traits.

Conformation has long been a driving force in horse selection and breed creation as a predictor for performance. The Tennessee Walking Horse (TWH) ranges in size from 1.5 to 1.7 m and is often used as a trail, show, and pleasure horse. To investigate the contribution of genetics to body conformation in the TWH, we collected DNA samples, body measurements, and gait/training information from 282 individuals. We analyzed the 32 body measures with a principal component analysis. Principal component (PC)1 captured 28.5% of the trait variance, while PC2 comprised just 9.5% and PC3 6.4% of trait variance. All 32 measures correlated positively with PC1, indicating that PC1 describes overall body size. We genotyped 109 horses using the EquineSNP70 bead chip and marker association assessed the data using PC1 scores as a phenotype. Mixed-model linear analysis (EMMAX) revealed a well-documented candidate locus on ECA3 (raw P = 3.86 × 10−9) near the LCORL gene. A custom genotyping panel enabled fine-mapping of the PC1 body-size trait to the 3′-end of the LCORL gene ( P = 7.09 × 10−10). This position differs from other reports suggesting single nucleotide polymorphisms (SNPs) upstream of the LCORL coding sequence regulate expression of the gene and, therefore, body size in horses. Fluorescent in situ hybridization analysis defined the position of a highly homologous 5 kb retrogene copy of LCORL (assigned to unplaced contigs of the EquCab 2.0 assembly) at ECA9 q12-q13. This is the first study to identify putative causative SNPs within the LCORL transcript itself, which are associated with skeletal size variation in horses.

The common equine skin tumors known as sarcoids have been causally associated with infection by bovine papillomavirus (BPV). Additionally, there is evidence for host genetic susceptibility to sarcoids. We investigated the genetic basis of susceptibility to sarcoid tumors on a cohort of 82 affected horses and 270 controls genotyped on a genome-wide platform and two custom panels. A Genome Wide Association Study (GWAS) identified candidate regions on six chromosomes. Bayesian probability analysis of the same dataset verified only the regions on equine chromosomes (ECA) 20 and 22. Fine mapping using custom-produced SNP arrays for ECA20 and ECA22 regions identified two marker loci with high levels of significance: SNP BIEC2-530826 (map position 32,787,619) on ECA20 in an intron of the DQA1 gene in the Major Histocompatibility Complex (MHC) class II region (p 5 4.6e-06), and SNP BIEC2-589604 (map position 25,951,536) on ECA22 in a 200 kb region containing four candidate genes: PROCR, EDEM2, EIF6 and MMP24 (p 5 2.14e-06). The marker loci yielded odds ratios of 5.05 and 4.02 for ECA20 and ECA22, respectively. Associations between genetic MHC class II variants and papillomavirus-induced tumors have been reported for human papillomavirus and cottontail rabbit papillomavirus infections. This suggests a common mechanism for susceptibility to tumor progression that may involve subversion of the host immune response. This study also identified a genomic region other than MHC that influenced papillomavirus-induced tumor development in the studied population.