Wen Jia, Zhao Xinwang, Wu Guorong, Xiang Dan, Liu Qing, Bu Su-Hong, Yi Can, Song Qijian, Dunwell Jim M, Tu Jinxing, Zhang Tianzhen, Zhang Yuan-Ming
College of Plant Science and Technology, Huazhong Agricultural University, Wuhan 430070, China.
State Key Laboratory of Crop Genetics and Germplasm Enhancement, Nanjing Agricultural University, Nanjing 210095, China.
Sci Rep. 2015 Dec 17;5:18376. doi: 10.1038/srep18376.
Heterosis refers to the phenomenon in which an F1 hybrid exhibits enhanced growth or agronomic performance. However, previous theoretical studies on heterosis have been based on bi-parental segregating populations instead of F1 hybrids. To understand the genetic basis of heterosis, here we used a subset of F1 hybrids, named a partial North Carolina II design, to perform association mapping for dependent variables: original trait value, general combining ability (GCA), specific combining ability (SCA) and mid-parental heterosis (MPH). Our models jointly fitted all the additive, dominance and epistatic effects. The analyses resulted in several important findings: 1) Main components are additive and additive-by-additive effects for GCA and dominance-related effects for SCA and MPH, and additive-by-dominant effect for MPH was partly identified as additive effect; 2) the ranking of factors affecting heterosis was dominance > dominance-by-dominance > over-dominance > complete dominance; and 3) increasing the proportion of F1 hybrids in the population could significantly increase the power to detect dominance-related effects, and slightly reduce the power to detect additive and additive-by-additive effects. Analyses of cotton and rapeseed datasets showed that more additive-by-additive QTL were detected from GCA than from trait phenotype, and fewer QTL were from MPH than from other dependent variables.
杂种优势是指F1杂种表现出增强的生长或农艺性能的现象。然而，先前关于杂种优势的理论研究是基于双亲分离群体而非F1杂种。为了理解杂种优势的遗传基础，我们使用了一部分F1杂种（称为部分北卡罗来纳II设计）对因变量进行关联作图，这些因变量包括：原始性状值、一般配合力（GCA）、特殊配合力（SCA）和中亲杂种优势（MPH）。我们的模型联合拟合了所有的加性、显性和上位性效应。分析得出了几个重要发现：1）GCA的主要成分是加性和加性×加性效应，SCA和MPH的主要成分是显性相关效应，MPH的加性×显性效应部分被确定为加性效应；2）影响杂种优势的因素的排序为显性＞显性×显性＞超显性＞完全显性；3）增加群体中F1杂种的比例可显著提高检测显性相关效应的能力，并略微降低检测加性和加性×加性效应的能力。对棉花和油菜数据集的分析表明，从GCA中检测到的加性×加性QTL比从性状表型中检测到的更多，从MPH中检测到的QTL比从其他因变量中检测到的更少。
