Investigation of single nucleotide polymorphisms of insulin-like growth factor 1 (IGF-1) gene and their association with growth traits in Kalahari red goat

Abstract

Weighing scales are typically out of reach for small-scale farmers due to expensive cost and a lack of operational expertise. However, understanding body weight and its relationship to linear body measures are critical for farmers making management decisions. Single nucleotide polymorphisms (SNPs) are significant because they influence the coding area of the DNA, leading to changes to the amino acid sequences, which might affect the animal's phenotype. The current study sought to find genetic indicators of the insulin-like growth factor 1 gene that may be exploited for breeding selection in order to improve the growth traits of Kalahari Red goats. The research was carried out at the Zuurfontein farm in Polokwane. As experimental animals, fifty (n = 50) Kalahari Red goats (8 males and 42 females) aged 2 to 3 years were used. A balance weighing scale was used to record body weight, and a measuring tape was used to capture linear body measures. Blood samples were obtained from the jugular vein once per animal using vacutainer blood collecting tubes. The deoxyribonucleic acid (DNA) was extracted and purified according to the methodology provided by Noegen's Genomic DNA isolation kit. Pearson’s correlation was used to achieve the correlation between the growth traits, Simple linear regression was performed to predict body weight from linear body measurements, Polymerase Chain Reaction-Restriction Fragment Length Polymorphism (PCR-RFLP) was utilized to discover the single nucleotide polymorphism, Chi-square test (χ2) was performed to assess the allele frequencies for Hardy-Weinberg equilibrium and General Linear Model (GLM) was performed for marker-trait association analysis. The mean square error (MSE) and coefficient of determination (R2) were exercised to choose the best regression model. Correlation results indicated a high positive significant correlation (P < 0.01) among BW and RH (r = 0.69), BL (r = 0.92), HG (r = 0.91), WH (r = 0.85) in bucks. While it does, all the linear body measurements indicated a high positive significant correlation (P < 0.01) expect SH (r = 0.41) which had a positive significant correlation (P < 0.05). Simple linear regression findings highlighted that BL had minimum MSE and highest R2 in bucks while in does HG had minimum MSE and highest R2. PCR-RFLP results indicated that two fragment patterns (two fragments and one fragment) were identified. Two genotypes were identified, KK with one fragment and KM with two fragments. The genotype frequency of KK was higher than that of KM and K allele had a higher allelic frequency than the M allele. The χ2 results showed that the Kalahari Red goats population used was not in Hardy Weinberg equilibrium (HWE) (χ2 = 0.39*). Marker-trait association findings by GLM indicated that the genotypes (KK and KM) had no association with the growth traits measured. In conclusion, correlation findings suggest that BW had a higher relationship with BL and HG in Kalahari Red goats. The regression results suggest that in bucks, an increase of 1 cm of BL might increase body weight by 1.24 kg, whereas it does, a 1 cm increase of HG might increase the body weight by 0.73 kg. The χ2 results suggest that the studied population gene and genotypic frequencies keep on changing from generation to generation and the marker-traits association results suggest that the genotypes identified had no relationship with growth traits in Kalahari Red goats. Further studies need to be conducted on single nucleotide polymorphism of IGF-1 and their relationship with growth traits using a larger sample, more growth traits and targeting more exons.