doi: www.doi.org/10.14202/vetworld.2020.127-133
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Article history: Received: 07-09-2019, Accepted: 09-12-2019, Published online: 18-01-2020
Corresponding author: Edy Kurnianto
E-mail: kurniantoedy17@gmail.com
Citation: Lestari DA, Oikawa T, Sutopo S, Purbowati E, Setiaji A, Kurnianto E (2020) Effect of insulin-like growth factor 1 gene on growth traits of Kejobong goat and its growth analysis, Veterinary World, 13(1): 127-133.Aim: This study aimed to identify the effect of the insulin-like growth factor 1 (IGF1) gene on growth, to uncover the genetic marker at the IGF1 gene, and to predict growth performance by analyzing growth models of Kejobong goats based on their genotype.
Materials and Methods: DNA and records of body weight (BW) and body measurements (BM) of Kejobong goats were collected, the IGF1 gene was amplified from the DNA template by polymerase chain reaction (PCR); the PCR products were then sequenced to determine single nucleotide polymorphisms (SNP). Linear mixed model (LMM) was used to analyze the association between SNP and growth traits. Four non-linear growth models were analyzed using non-LMM to describe the growth model and to compare the growth within genotypes.
Results: An SNP at intron 4 (g5752G→C) genotyped into GG and CC was significantly associated with BW and BM. Goats of genotype GG had a significantly higher BW and BM (p<0.05) than those of genotype CC. Growth analysis showed that the von Bertalanffy model was the most fit for describing BW, the Brody model for chest width and hip height, the Gompertz and Logistic models for heart girth, and the von Bertalanffy and Gompertz models for hip width.
Conclusion: An SNP at intron 4 of the IGF1 gene was associated with the growth trait and was usable as a genetic marker candidate for improvement of growth traits of Kejobong goats while von Bertalanffy model provides proper and accurate estimates of parameters to describe the growth performance of Kejobong goats.
Keywords: genetic markers, goat, growth analysis, growth traits, insulin-like growth factor 1.