最佳线性无偏预测
选择(遗传算法)
生物
指标选择
统计
限制最大似然
生物技术
数学
计算机科学
最大似然
人工智能
出处
期刊:Genetics
[Oxford University Press]
日期:2005-05-24
卷期号:170 (3): 1247-1259
被引量:258
标识
DOI:10.1534/genetics.104.035956
摘要
Abstract Competition among domesticated plants or animals can have a dramatic negative impact on yield of a stand or farm. The usual quantitative genetic model ignores these competitive interactions and could result in seriously incorrect breeding decisions and acerbate animal well-being. A general solution to this problem is given, for either forest tree breeding or penned animals, with mixed-model methodology (BLUP) utilized to separate effects on the phenotype due to the individuals' own genes (direct effects) and those from competing individuals (associative effects) and thereby to allow an optimum index selection on those effects. Biological verification was based on two lines of Japanese quail selected for 6-week weight; one line was selected only for direct effects (D-BLUP) while the other was selected on an optimal index for both direct and associative effects (C-BLUP). Results over 23 cycles of selection showed that C-BLUP produced a significant positive response to selection (b = 0.52 ± 0.25 g/hatch) whereas D-BLUP resulted in a nonsignificant negative response (b = −0.10 ± 0.25 g/hatch). The regression of percentage of mortality on hatch number was significantly different between methods, decreasing with C-BLUP (b = −0.06 ± 0.15 deaths/hatch) and increasing with D-BLUP (b = 0.32 ± 0.15 deaths/hatch). These results demonstrate that the traditional D-BLUP approach without associative effects not only is detrimental to response to selection but also compromises the well-being of animals. The differences in response show that competitive effects can be included in breeding programs, without measuring new traits, so that costs of the breeding program need not increase.
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