首页 | 本学科首页   官方微博 | 高级检索  
     检索      


Genetic variation of plasma insulin-like growth factor-1 in young crossbred ewes and its relationship with their maintenance feed intake at maturity and production traits
Authors:Afolayan R A  Fogarty N M
Institution:The Australian Sheep Industry Cooperative Research Centre, NSW Department of Primary Industries, Orange Agricultural Institute, Orange, NSW 2800, Australia.
Abstract:The genetic variation of plasma IGF-I in crossbred ewe lambs postweaning was evaluated together with its potential use as a physiological marker for selection in meat sheep. Genetic variation for IGF-I was analyzed among 1,246 young crossbred ewes that were the progeny of 30 sires from various maternal breeds and Merino dams. The estimate of heritability of IGF-I was 0.28 +/- 0.10, with sire breed not being significant. Genetic correlations were estimated between IGF-I and performance traits of the ewes, including feed intake, growth, body composition, wool, and reproduction over 3 matings. Although the genetic correlations had high standard errors because of the limited size of the data set, the correlation between IGF-I and grazing feed intake of the mature ewes at maintenance was positive (0.32 +/- 0.31). The genetic correlations of IGF-I with other traits ranged from positive and low to moderate for growth (0.05 to 0.36), positive for ultrasound eye muscle depth (0.15), and negative for ultrasound fat depth (-0.12) in the mature ewes, and close to zero for the wool traits. The genetic correlation between IGF-I and the average number of lambs born per ewe mated was negative (-0.18), whereas that for the average number of lambs weaned per ewe mated was positive (0.10). The parameters indicated that genetic variation exists for IGF-I in sheep, and selection for low IGF-I in young ewes may result in some reduction in feed intake and improvement in maintenance efficiency of mature ewes under grazing, with little impact on other production traits. However, the genetic correlations had high standard errors, and more precise estimates of these parameters are required for genetic evaluation and to predict with confidence the outcome of breeding programs.
Keywords:
本文献已被 PubMed 等数据库收录!
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号