Bashar Fadhil Tuama
Abstract
The present study examines a Shami goat, the insulin-like growth factor (IGF-1) gene SNPs in Iraqi livestock farms, and the purpose of the research is to determine the genetic markers in relation to milk production and reproductive performance. They were 70 Shami does that were aged between 2 and 5 years old and were chosen in different breeding farms in different regions of Iraq. Genomic DNA extraction of blood samples was done using commercially available silica membrane-based kits. Amplification of R gene specific regions of SNP identification in polymerase chain reaction (PCR) was carried out with the aid of primers and SNP identification was done by Sanger sequencing. Two different SNPs have been analyzed including SNP1 (g.1247C>T), which is a transition SNP in exon 3, and SNP2 (g.2856A>G), which is a transition SNP in exon 7. In the case of SNP1, three genotypes have been identified (CC, CT, TT) where the allele of C and T are equally distributed (0.62 and 0.38, respectively). General linear models that were used in statistical analysis revealed that there were significant associations between SNP1 genotypes and daily milk output where the TT genotype had the highest mean SNP with 2.34 kg/day milk production (p < 0.05). In SNP2, the GG genotype had a significant positive relation with previous age of first mating (11.2 ± 0.8 months) and litter size (1.89 ±0.14 kids) when compared with the AA genotype (p < 0.05). These SNPs have been identified and could be used as potential molecular markers in marker-assisted selection programs to improve the productivity in the populations of Shami goats. Its findings will help in the comprehension of the genetic foundation of economically significant traits and have a background of breeding methods that are genomic-enabled in the Iraqi livestock farming systems.
Citation format
TUAMA, Bashar Fadhil. Analysis of IGF-1 gene SNP mutations and their impact on milk yield and reproductive traits in shami goat in iraq. Indian Journal of Animal Production and Management, 2026, 42(1): 124–132.