一种分离基因平均值和变异趋势的方法,以了解育种实践
Thiago P Oliveira1, Jana Obšteter2, Ivan Pocrnic3
1The Roslin Institute and Royal (Dick) School of Veterinary Studies, University of Edinburgh, Edinburgh, UK. thiago.oliveira@ed.ac.uk.
Genetics, selection, evolution : GSE
|June 2, 2023
概括
在育种计划中量化选择路径对于优化至关重要. 这项研究扩展了分区遗传平均值和变异的方法,帮助育种者理解和改进来自不同选择策略的遗传收益.
科学领域:
- 动物育种与遗传学
- 量化遗传学 量化遗传学
背景情况:
- 在繁殖计划中观察到的遗传变化是多个选择路径的结果.
- 量化个别选择路径的贡献对于程序优化至关重要,但复杂.
- 现有的方法被扩展到将遗传平均值和变异分成两部分.
研究的目的:
- 扩展分区方法以量化选择路径对遗传变异的贡献.
- 将这种方法与马尔科夫链蒙特卡洛集成,以进行可靠的估计.
- 为了解和优化育种计划动态提供工具.
主要方法:
- 扩展了选择路径分区方法,包括遗传变异.
- 与马尔科夫链蒙特卡洛的组合分区用于后部分布采样.
- 在R包AlphaPart中实现了该方法,并在模拟的牛数据上进行了测试.
主要成果:
- 成功量化了选择路径对遗传平均值和变异的贡献.
- 证明不同路径对遗传变异的贡献并不总是独立的.
- 鉴定了基于血统的模型的局限性,表明需要基因组扩展.
结论:
- 一种新的分区方法量化了育种计划中遗传平均值和变异变化的来源.
- 这种方法增强了对选择路径相互作用和优化策略的理解.
- 这种方法为旨在改善遗传收益的育种者和研究人员提供了宝贵的见解.
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