产量性状是复杂的数量性状, 对种子的单株产量及其构成因素(全株总有效角果数、每角粒数、千粒重)进行QTL定位和上位性分析，确定其在染色体上的位置及其遗传效应,可以探讨油菜杂种优势产生原因，提高育种中对产量性状优良基因型选择的效率，达到提高油菜产量的目的。在双低油菜细胞质雄性不育保持系1141B和双高恢复系垦C1构建的F2作图群体中，运用SRAP、AFLP和SSR三种标记技术构建了一个甘蓝型油菜(Brassica napus L.)的分子标记遗传连锁图谱。共包含244个标记，分布于20个主要连锁群、1个三联体上，图谱总长度为2 769.5 cM。采用Windows QTL Cartographer Version 2.0统计软件及复合区间作图法，对油菜单株产量及其3大构成因素进行QTL定位，共检测到QTLs 16个分布在9个连锁群上，其中第6和13连锁群最多，均有3个。单个QTL解释性状表型变异的0.38%～73.34%。对于同一性状，等位基因的增效作用既来自母本，亦源自父本；采用双向方差分析法对位点间互作及其上位性进行分析，检测到26对影响产量构成性状的上位性互作效应QTL，说明油菜基因组中存在大量控制产量的互作位点，油菜产量性状的上位性存在着多效性，上位性互作包括QTL与非QTL位点，其中以非QTL位点较多。一般互作位点的独立效应值较小，而互作的效应值显著增大，且一般超过两位点独立效应值之和。反映了控制产量性状基因的复杂性。上位性是甘蓝型油菜产量性状杂种优势的重要遗传基础。
Since yield traits are complicated quantitative traits, QTLs mapping and genetic effects analyzed for seed yield and its components can help us to understand the source for heterosis and improve the selecting efficiency for good genotype of seed yield. A genetic linkage map consisting of 244 DNA markers was constructed based on F2 population derived from a cross between double low parent CMS maintainer 1141B and double high CMS restorer KenC1. The markers in the linkage map distributed on all the 20 main linkage groups and 1 triplet and covered 2 769.5 cM of the rapeseed genome. The statistic software of Windows QTL Cartographer Version2.0 and Composite Internal Mapping (CIM) were applied to detect QTLs for seed yield and its components, including seed yield per plant, number of silique per plant, number of seed per silique and 1000-seed weight. A total of 16 QTLs located in nine different linkage groups were identified for seed yield and the three component traits. There were three QTLs (the most QTLs) in LG6 and LG13, respectively. Each of these QTLs explained 0.38%–73.34% of the phenotypic variance. They had additional effect of alleles that came from maternal parent, the others from paternal parent for the same trait. Epistatic effect was screened in all 20 linkage groups using all possible loci pairs by two-way ANOVAs between co-dominant markers. Twenty-six two-locus combinations had significant epistatic effects. The results showed that there were many interaction loci involving the entire genome detected in yield traits. The epistatic interactions had pleiotropic effects, interactions were contained epistasis between QTL and non-QTL (non-significant effect loci) and between non-QTL. The later was the majority. In general, the independent effect of interaction loci was lower, on the opposite, the value of interaction effect was higher, and much higher than the total of independent effects.This indicated that the genes controlling seed yield was complicated. Epistasis interactions might play an important role as the basis of heterosis in Brassica napus L. Some questions about QTLs mapping were also discussed.
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