Comparison of Introgression and Synthetic Breed Strategies for Litter Size Trait in Sheep using Computer Simulation

Message:
Article Type:
Research/Original Article (دارای رتبه معتبر)
Abstract:

The objective of this study was to compare introgression and synthetic breed strategies for litter size trait improvement in sheep using computer simulation. For this purpose, a trait with heritability of 0.1, consisting of two chromosomes was simulated. On chromosome 1, a single QTL as the major gene was created that accounted for 40% of the total genetic variance. The effect of favorable and unfavorable alleles for the QTL was fixed after seven generations in both A and B breeds, respectively. The introgression and synthetic breed strategies were compared using Classical and Classical with gene-assisted selection (GasClassical) methods. The genetic gain in introgression and synthetic breed strategies using GasClassical method was 39% and 16% higher than that of Classical method, respectively. The mean of inbreeding coefficient in the fifth generation in introgression strategy was 0.049 and 0.077 using the Classical and GasClassical methods, respectively, and in synthetic breed strategy was 0.11 and 0.008, respectively. The results of this study showed that the GasClassical method in comparison with the Classical method led to an increasing frequency of favorable allele (major gene) and genetic gain in both introgression and synthetic breed strategies. However, the genetic gain for one percent increase in inbreeding in the synthetic breed strategy was greater than that of introgression strategy, and as a result, the synthetic breed strategy performs better than introgression strategy.

Language:
Persian
Published:
Research On Animal Production, Volume:10 Issue: 25, 2019
Pages:
112 to 119
https://www.magiran.com/p2066514  
سامانه نویسندگان
  • Rashidi، Amir
    Corresponding Author (2)
    Rashidi, Amir
    Full Professor Animal Breeding and Genetics, Dep of Anim Sci, University Of Kurdistan, سنندج, Iran
اطلاعات نویسنده(گان) توسط ایشان ثبت و تکمیل شده‌است. برای مشاهده مشخصات و فهرست همه مطالب، صفحه رزومه را ببینید.
مقالات دیگری از این نویسنده (گان)