Accumulating mutations in series of haplotypes at the KIT and MITF loci are major determinants of white markings in Franches-Montagnes horses

Abstract

Coat color and pattern variations in domestic animals are frequently inherited as simple monogenic traits, but a number are known to have a complex genetic basis. While the analysis of complex trait data remains a challenge in all species, we can use the reduced haplotypic diversity in domestic animal populations to gain insight into the genomic interactions underlying complex phenotypes. White face and leg markings are examples of complex traits in horses where little is known of the underlying genetics. In this study, Franches-Montagnes (FM) horses were scored for the occurrence of white facial and leg markings using a standardized scoring system. A genome-wide association study (GWAS) was performed for several white patterning traits in 1,077 FM horses. Seven quantitative trait loci (QTL) affecting the white marking score with p-values p≤10(-4) were identified. Three loci, MC1R and the known white spotting genes, KIT and MITF, were identified as the major loci underlying the extent of white patterning in this breed. Together, the seven loci explain 54% of the genetic variance in total white marking score, while MITF and KIT alone account for 26%. Although MITF and KIT are the major loci controlling white patterning, their influence varies according to the basic coat color of the horse and the specific body location of the white patterning. Fine mapping across the MITF and KIT loci was used to characterize haplotypes present. Phylogenetic relationships among haplotypes were calculated to assess their selective and evolutionary influences on the extent of white patterning. This novel approach shows that KIT and MITF act in an additive manner and that accumulating mutations at these loci progressively increase the extent of white markings.

Figure 1. Phenotypic variation in the expression of white markings.

Example of phenotypes. Horse (A) has a total score of white markings of 1 (head = 0; foreleg = 0; hind leg = 1); horse (B) has a total score of white markings of 19 (head = 9; foreleg = 2; hind leg = 8).

Figure 2. GWAS identifies two major loci associated with total white marking scores.

A Manhattan plot showing the negative log of the probability of association (p-value) between individual marker and total white marking score. (A) Analysis included horses of all colors, (B) bay horses only, (C) chestnut horses only. Markers are represented in different colors according to their chromosome. Significance level of p≤1×10⁻⁸ is indicated with a dashed red line; a dashed black line represents association with p≤10⁻⁴.

Figure 3. Fine-scale quantitative association mapping and linkage disequilibrium across MITF and KIT.

Fine–scale quantitative association between total white markings score and linkage disequilibrium (LD) in r² between SNPs across 2 Mb regions in (A) the KIT and (B) the MITF region including all horses. The darker shading represents higher LD, black diamond’s represents an r² of 1.

Figure 4. Phylogenetic relationship between haplotypes at MITF and KIT.

Phylogenetic relationships between haplotypes at MITF (M1–M6) and KIT (K1–K7). Haplotype combinations (hap1 = haplotype 1, hap2 = haplotype 2) and individuals average total white markings score (aTSC = average Total Score) are shown on the right.

Figure 5. Average total white markings score for MITF-KIT haplotype combinations.

Average total white markings score and standard deviation for MITF-KIT haplotype combinations. Adjacent squares represent haplotypes (red = MITF; blue = KIT); color shades represent haplotypes of the phylogenetic relationship trees (MITF: M1–M6; KIT: K1–K7).

Figure 6. Results of the logistic regression model analysis.

Results of the logistic regression model analysis for the relationship between MITF haplotypes, SNPs across the 2 Mb KIT region and KIT haplotypes.