Acta Veterinaria et Zootechnica Sinica ›› 2024, Vol. 55 ›› Issue (1): 120-128.doi: 10.11843/j.issn.0366-6964.2024.01.013

• ANIMAL GENETICS AND BREEDING • Previous Articles     Next Articles

Study on Estimates of Genomic Breeding Value of Fleece Traits in Inner Mongolia Cashmere Goats

YAN Xiaochun, XI Haijiao, LI Jinquan, WANG Zhiying*, SU Rui*   

  1. College of Animal Science, Inner Mongolia Agricultural University, Hohhot 010018, China
  • Received:2023-07-25 Online:2024-01-23 Published:2024-01-24

Abstract: The study aimed to investigate the breeding selection efficiency of the Single Step Genome Best Linear Unbiased Prediction(SSGBLUP) method for Inner Mongolia cashmere goat. Based on the Illumina GGP_Goat_70K BeadChip sequencing data from 2 256 individuals of Inner Mongolia cashmere goats (Albas type), the phenotype data and pedigree records of cashmere traits were collected from individuals age 1 to 8 years old. Different matrix parameters of the H inverse matrix in the SSGBLUP method were set(ω,τ) to estimate the genome breeding value. At the same time, the accuracy of breeding value was estimated by five-fold cross-validation method. The results indicated that, as the increasing ω, SSGBLUP method had led to higher accuracy in estimating genomics breeding values for cashmere traits in Inner Mongolia cashmere goats. Combining the genetic parameter estimation results of ABLUP and GBLUP, it could be concluded that when τ was 0.3 and ω was 0.9, the accuracy of genome selection for cashmere traits in Inner Mongolia cashmere goats was relatively good. The accuracy of cashmere length was 0.702 8. The accuracy of cashmere diameter was 0.668 2. The accuracy of cashmere production was 0.713 1. Selecting reasonable scale parameters for the H matrix of SSGBLUP method can improve the accuracy of genetic breeding value estimation for cashmere traits in Inner Mongolia cashmere goats, and accelerate population genetic improvement, and shorten generation intervals.

Key words: Inner Mongolia cashmere goats, SSGBLUP, fleece traits, genome selection, scale parameters

CLC Number: