Pakistan is third largest country in term of goat population with distinct characteristics of breeds and estimated population of 78.2 million. Punjab province has 37% of country’s total population with seven important documented goat breeds namely Beetal, Daira Din Pannah, Nachi, Barbari, Teddi, Pahari and Pothwari. There is paucity of literature on GWAS for economically important traits i.e., body weight and morphometric measurements. Therefore, we performed GWAS using 50 K SNP Chip for growth in term of age adjusted body weight and morphometric measurements in order to identify genomic regions influencing these traits among Punjab goat breeds. Blood samples were collected from 879 unrelated animals of seven goat breeds along with data for body weight and morphometric measurements including body length, body height, pubic bone length, heart girth and chest length. Genomic DNA was extracted and genotyped using 50 K SNP bead chip. Association of genotypic data with the phenotypic data was performed using Plink 1.9 software. Linear mixed model was used for the association study. Genes were annotated from Capra hircus genome using assembly ARS1. We have identified a number of highly significant SNPs and respective candidate genes associated with growth and body conformation traits. The functional aspects of these candidate genes suggested their potential role in body growth. Moreover, pleiotropic effects were observed for some SNPs for body weight and conformation traits. The results of current study contributed to a better understanding of genes influencing growth and body conformation traits in goat.

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Abstract. The identification issue of livestock can be resolved by using molecular identification tools that are acceptable to preserve and maintain pure breeds worldwide. The application of a molecular identification methodology is more important for developing nations, e.g., Pakistan, where uncontrolled crossbreeding has become a common practice and the import of exotic animals and germplasm is ever increasing. This presents a risk to local breeds as also stated by the FAO. Therefore, the current study was designed to develop standard molecular markers for Cholistani cattle to ascertain their purity for breeding purpose. In this study 50 and 48 unrelated males were sampled for Cholistani and each crossbred cattle, respectively. Candidate molecular markers present in Cholistani but absent in crossbred cattle and vice versa were detected using the amplified fragment length polymorphism (AFLP) method. Eleven markers were developed and were converted to single nucleotide polymorphism (SNP) markers for genotyping. The allele frequencies in both breeds were determined for discrimination ability using polymerase-chain-reaction–restriction-fragment-polymorphism (PCR-AFLP). The probability of identifying the Cholistani breed was 0.905 and the probability of misjudgment was 0.073 using a panel of markers. The identified markers can ascertain the breed purity and are likely to extend the facility for breed purity testing before entering into a genetic improvement program in the country.

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A higher body weight at a younger age is an economically important trait for profitable goat farming. This study was focused on the identification of regions of the genome that harbor genetic variants associated with body weight using the Illumina GoatSNP50K Bead Chip. A total of 631 purebred Beetal goats (151 males and 480 females) were recorded for body weight, age and body measurement and then genotyped. Genome wide association analysis was carried out with GEMMA. After application of quality control filters with Plink 1.9, call rate less or equal than 0.9, minor allele frequency less than 0.05 and HWE P value lesser than 0.001, 594 animals and 45,744 SNPs were retained for association analysis. The association analysis for body weight with covariates of age, sex and morphometric measurements and contemporary group yielded 10 significant SNPs (P = -log10e-4 to -log10e-6). Three associated SNPs were within genes i.e., BTAF1, NTM and GRID1 when blasted against ARS1(accession GCA_001704415.1). Moreover, some associated SNPs were localized close to CEP78, ROBO1, ZFP36L2, SPTLC3, CTR9 and ZFHX3 genes. The study identified SNPs and genes with potential role in growth of goat.