Coat colour and various patterns are the hallmarked qualitative traits studied in cattle as well as other livestock; however, variation in this trait is resultant of interactions and epistasis of a set of genes rather than being a product of a single gene. In this study, GWAS has been conducted from 50K SNP genotype data, with a stratified approach on Vrindavani cattle (n=48). The study was conducted in two sets of an experiment wherein set I treats all the solid colours (n=18) as controls and rest spotted or patchy types as cases (n=30), and set II treats brown and brown with white spots as controls (n=15), and rest as cases (n=33). After quality check (MAF>0.01, genotyping rate>90%, and H-W equilibrium at p≤ 0.001) of genotype data, 37247 SNPs were further used for accomplishing Genome-Wide Association Study (GWAS) with coat colour. The distinct phenotypes were classified into four different sub-groups that are solid black, black with white patches, solid brown, and brown with white patches along with greyish white. The allele frequency difference was checked in all sub-groups. The GWAS was conducted in PLINK v1.7 and for graphical representation R was used. Two SNPs in set I and 20 in set II were found to be significantly associated with coat colour in Vrindavani cattle. A ±500 Kb genome scan around the significant SNPs revealed gene BDNF for SNP DIAS-217 in set I and FGF18 for SNP ARS-BFGL-NGS-105192, and CACNA2D1, and HGF for SNP BTB-01885061 in set II, are present around these SNPs. In KEGG-based pathway enrichment analysis, all the above-mentioned genes were found to be involved in well-established MAPK and PI3K-AKT signalling pathways, affecting the biochemical process of coat colour production. Genome-wide F_ST values were low to moderate across the genome, however few associated SNPs had moderate to high F_ST values indicating their power in differentiating the subgroups according to coat colour phenotype. This study provides a preliminary report of markers and genes involved in coat colour expression and revealed that the reported genes around the associated SNPs are involved in brown with white spotting phenotype. However, further researches in this field are essential for a more conclusive result.

毛色和各种图案是在牛和其他牲畜中研究的标志性定性特征。但是，这种性状的变异是一组基因相互作用和上位的结果，而不是单个基因的产物。在这项研究中，GWAS是从50K SNP基因型数据中进行的，采用分层方法对Vrindavani牛（n = 48）进行了研究。该研究在两组实验中进行，其中第一组将所有纯色（n = 18）当作对照，其余的斑点或斑块类型作为案例（n = 30），第二组将棕色和褐色带有白色斑点的情况作为对照。控制（n = 15），其余作为案例（n = 33）。在对基因型数据进行质量检查（MAF> 0.01，基因分型率> 90％，且HW平衡在p≤0.001时）后，进一步将37247个SNP用于完成带有外套颜色的基因组-全基因组关联研究（GWAS）。不同的表型被分为四个不同的亚组，分别为纯黑色，带白色斑点的黑色，纯棕色和带白色斑点的褐色以及灰白色。检查所有亚组中的等位基因频率差异。GWAS在PLINK v1.7中进行，并使用图形表示R。在弗林达瓦尼牛中，发现第一组中的两个SNP和第二组中的20个SNP与皮毛颜色显着相关。在显着的SNP周围进行±500 Kb基因组扫描 在弗林达瓦尼牛中，发现第一组中的两个SNP和第二组中的20个SNP与皮毛颜色显着相关。在显着的SNP周围进行±500 Kb基因组扫描 在弗林达瓦尼牛中，发现第一组中的两个SNP和第二组中的20个SNP与皮毛颜色显着相关。在显着的SNP周围进行±500 Kb基因组扫描BDNF用于SNP DIAS-217组I和FGF18用于SNP ARS-BFGL-NGS-105192，和CACNA2D1，和HGF在组II用于SNP BTB-01885061，存在围绕这些SNP。在基于KEGG的途径富集分析中，发现所有上述基因都与成熟的MAPK和PI3K-AKT信号传导途径有关，从而影响了毛色产生的生化过程。全基因组的F _ST值在基因组中低至中等，但是很少有相关的SNP具有中高F _ST值表示它们根据外套颜色表型区分亚组的能力。这项研究提供了涉及外套颜色表达的标志物和基因的初步报告，并揭示了相关SNPs周围报道的基因涉及带有白色斑点表型的棕色。但是，对该领域的进一步研究对于获得更具决定性的结果是必不可少的。