Li Lanzhi, Sun Congwei, Chen Yuan, Dai Zhijun, Qu Zhen, Zheng Xingfei, Yu Sibin, Mou Tongmin, Xu Chenwu, Hu Zhongli
Hunan Provincial Key Laboratory for Biology and Control of Plant Disease and Insect Pests, College of Bio-Safety Science and Technology, Hunan Agricultural University, Changsha, People's Republic of China.
J Genet. 2013 Dec;92(3):529-43. doi: 10.1007/s12041-013-0311-6.
The NCII design (North Carolina mating design II) has been widely applied in studies of combining ability and heterosis. The objective of our research was to estimate how different base populations, sample sizes, testcross numbers and heritability influence QTL analyses of combining ability and heterosis. A series of Monte Carlo simulation experiments with QTL mapping were then conducted for the base population performance, testcross population phenotypic values and the general combining ability (GCA), specific combining ability (SCA) and Hmp (midparental heterosis) datasets. The results indicated that: (i) increasing the number of testers did not necessarily enhance the QTL detection power for GCA, but it was significantly related to the QTL effect. (ii) The QTLs identified in the base population may be different from those from GCA dataset. Similar phenomena can be seen from QTL detected in SCA and Hmp datasets. (iii) The QTL detection power for GCA ranked in the order of DH(RIL) based > F2 based > BC based NCII design, when the heritability was low. The recombinant inbred lines (RILs) (or DHs) allows more recombination and offers higher mapping resolution than other populations. Further, their testcross progeny can be repeatedly generated and phenotyped. Thus, RIL based (or DH based) NCII design was highly recommend for combining ability QTL analysis. Our results expect to facilitate selecting elite parental lines with high combining ability and for geneticists to research the genetic basis of combining ability.
NCII设计(北卡罗来纳交配设计II)已广泛应用于配合力和杂种优势研究。我们研究的目的是评估不同的基础群体、样本量、测交次数和遗传力如何影响配合力和杂种优势的QTL分析。然后针对基础群体表现、测交群体表型值以及一般配合力(GCA)、特殊配合力(SCA)和中亲杂种优势(Hmp)数据集,进行了一系列QTL定位的蒙特卡罗模拟实验。结果表明:(i)增加测验种数量不一定能提高GCA的QTL检测能力,但它与QTL效应显著相关。(ii)在基础群体中鉴定出的QTL可能与GCA数据集中的不同。在SCA和Hmp数据集中检测到的QTL也有类似现象。(iii)当遗传力较低时,GCA的QTL检测能力按基于双单倍体(DH)(或重组自交系,RIL)>基于F2>基于回交的NCII设计排序。重组自交系(RILs)(或DHs)比其他群体允许更多重组并提供更高的定位分辨率。此外,它们的测交后代可以重复产生并进行表型分析。因此,强烈推荐基于RIL(或DH)的NCII设计用于配合力QTL分析。我们的结果有望促进高配合力优良亲本系的选择,并有助于遗传学家研究配合力的遗传基础。