Reinventing quantitative genetics for plant breeding: something old, something new, something borrowed, something BLUE.
Reinventing quantitative genetics for plant breeding: something old, something new, something borrowed, something BLUE.
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DOI：
10.1038/s41437-020-0312-1
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发表时间：
2020-12
期刊：
影响因子：
3.8
通讯作者：
Bernardo R
中科院分区：
文献类型：
--
作者：
Bernardo R
数量遗传学的目标因其应用领域而异。在植物育种中，数量遗传学的主要重点是确定具有最佳基因型值的候选环境的目标群体。保持数量遗传学的最新发展需要保留仍然有用的旧概念，放弃已经过时的概念，并引入支持当代育种的新概念和方法。连续变异是由于多个孟德尔基因座的核心概念保持不变。由于育种计划中可用的全部种质不处于Hardy-Weinberg平衡，因此在植物育种中需要退休假设随机交配的经典概念，例如等位基因的平均效应和加性方差。这样做是可行的，因为使用分子标记，需要最小遗传假设的混合模型方法可以用于最佳线性无偏估计（BLUE）和预测。植物育种将受益于借鉴其他学科中有用的方法。例子包括可靠性作为一个新的措施的影响，遗传与非遗传效应，和操作研究和模拟方法设计育种计划。这种模拟中的遗传实体不应该是通用的，而应该由育种程序中实际种质的谱系、标记数据和表型数据来表示。多年来，植物育种中的数量遗传学变得越来越经验和计算，而理论基础越来越少。随着育种计划中可用数据的数量和类型的增加，这种趋势将继续下去。
The goals of quantitative genetics differ according to its field of application. In plant breeding, the main focus of quantitative genetics is on identifying candidates with the best genotypic value for a target population of environments. Keeping quantitative genetics current requires keeping old concepts that remain useful, letting go of what has become archaic, and introducing new concepts and methods that support contemporary breeding. The core concept of continuous variation being due to multiple Mendelian loci remains unchanged. Because the entirety of germplasm available in a breeding program is not in Hardy–Weinberg equilibrium, classical concepts that assume random mating, such as the average effect of an allele and additive variance, need to be retired in plant breeding. Doing so is feasible because with molecular markers, mixed-model approaches that require minimal genetic assumptions can be used for best linear unbiased estimation (BLUE) and prediction. Plant breeding would benefit from borrowing approaches found useful in other disciplines. Examples include reliability as a new measure of the influence of genetic versus nongenetic effects, and operations research and simulation approaches for designing breeding programs. The genetic entities in such simulations should not be generic but should be represented by the pedigrees, marker data, and phenotypic data for the actual germplasm in a breeding program. Over the years, quantitative genetics in plant breeding has become increasingly empirical and computational and less grounded in theory. This trend will continue as the amount and types of data available in a breeding program increase.
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影响因子：
2.3
作者：
BERNARDO, R
通讯作者：
BERNARDO, R
影响因子：
--
作者：
de Vlaming R;Groenen PJ
通讯作者：
Groenen PJ
影响因子：
1.9
作者：
COMSTOCK, RE;ROBINSON, HF
通讯作者：
ROBINSON, HF
影响因子：
5.4
作者：
Bernardo, Rex
通讯作者：
Bernardo, Rex
DOI：
10.1007/s00122-017-2938-9
发表时间：
2017-10
期刊：
TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik
影响因子：
--
作者：
Cameron JN;Han Y;Wang L;Beavis WD
通讯作者：
Beavis WD