Mao Bei-Bei, Cai Wen-Juan, Zhang Zhi-Hong, Hu Zhong-Li, Li Ping, Zhu Li-Huang, Zhu Ying-Guo
Key Laboratory of the Education Ministry of China for Plant Developmental Biology, College of Life Sciences, Wuhan University, Wuhan 430072, China.
Yi Chuan Xue Bao. 2003 Dec;30(12):1118-26.
A DH population containing 81 DH lines from an indica-japonica cross of rice and an RFLP linkage map consisting of 232 markers were used to map quantitative trait loci(QTLs) for harvest index, biomass, grain yield, sink capacity and plant height by a computer program QTLMapper1.0 based on mixed linear models. A total of 21 significant main-effect QTLs and 9 pairs of epistatic loci were detected. Of these, three detected QTLs for grain yield collectively accounted for 42% of the phenotypic variation with a LOD of 7.10. These three grain yield QTLs were corresponded either to QTLs for harvest index or QTLs for biomass in both locations and directions of additive effects, which sheds light on the genetic basis of the formula 'grain yield = biomass x harvest index'. Four detected QTLs for harvest index collectively explained 46% of the total phenotypic variation and four QTLs for biomass jointly accounted for 64% of the trait variation. No coincidence of harvest index QTLs with any biomass QTLs was found, therefore indicating the possibility of pyramiding favorable alleles for both traits through gene recombination so as to obtain a genotype possessing both high harvest index and heavy plant biomass. Five QTLs for plant height were detected that cumulatively explained 64% of the phenotypic variation with a LOD of 11.62. Among these, three with smaller effects respectively co-located with some of the QTLs for biomass, sink capacity and/or grain yield, but not with any of harvest index QTLs, thus suggesting that plant height was to some extent directly associated with 'source' and 'sink' but not with 'transportation' of the 'source-transportation-sink' concept, at least in this genetic background and environment. In view of a somewhat low resolution of the genetic map used in the study and the fact that when plant height QTLs co-located with those for yield and/or yield related traits, these co-located QTLs were all in the same directions of additive effects, it is more likely that these QTLs co-located in a same chromosomal region might be a single QTL which have effects on multiple traits. If this is true, the above observation have led us to assume that QTLs which have pleotropic effects on yield and/or yield related traits and plant height are very different from those which had relatively large effects only on plant height. The former contribute strongly to yield and/or yield related traits but weakly to plant height while the later contribute mainly to plant height. Obviously, due to that an increase of plant height is always coupled with an increase in lodging susceptibility, discriminating between above two types of QTLs is critical in breaking the traits' undesired association in breeding for improved yield potential of rice. In addition, based on the co-location analysis of main-effect QTLs for the studied traits, five genomic regions were found to be highly associated with harvest index, biomass, sink capacity and grain yield.
利用一个包含81个来自水稻籼粳交的双单倍体(DH)株系的群体和一张由232个标记组成的RFLP连锁图谱,通过基于混合线性模型的计算机程序QTLMapper1.0,对收获指数、生物量、籽粒产量、库容量和株高的数量性状位点(QTL)进行定位。共检测到21个显著的主效QTL和9对上位性位点。其中,检测到的3个籽粒产量QTL共同解释了42%的表型变异,LOD值为7.10。这3个籽粒产量QTL在两个地点和加性效应方向上,均与收获指数QTL或生物量QTL相对应,这为“籽粒产量=生物量×收获指数”这一公式的遗传基础提供了线索。检测到的4个收获指数QTL共同解释了总表型变异的46%,4个生物量QTL共同解释了该性状变异的64%。未发现收获指数QTL与任何生物量QTL的重合,因此表明通过基因重组聚合两个性状的有利等位基因,从而获得兼具高收获指数和重植株生物量的基因型是可能的。检测到5个株高QTL,累计解释了64%的表型变异,LOD值为11.62。其中,3个效应较小的QTL分别与一些生物量、库容量和/或籽粒产量QTL共定位,但不与任何收获指数QTL共定位,因此表明株高在一定程度上与“源-库”概念中的“源”和“库”直接相关,但与“运输”无关,至少在这种遗传背景和环境下是这样。鉴于本研究中使用的遗传图谱分辨率有点低,以及当株高QTL与产量和/或产量相关性状的QTL共定位时,这些共定位的QTL均处于相同的加性效应方向,更有可能的是,这些共定位在同一染色体区域的QTL可能是一个对多个性状有影响的单个QTL。如果是这样,上述观察结果使我们假设,对产量和/或产量相关性状以及株高具有多效性的QTL与那些仅对株高有较大影响的QTL非常不同。前者对产量和/或产量相关性状贡献大,但对株高贡献小,而后者主要对株高有贡献。显然,由于株高的增加总是伴随着倒伏敏感性的增加,区分上述两种类型的QTL对于打破水稻育种中这些性状的不良关联以提高产量潜力至关重要。此外,基于所研究性状的主效QTL的共定位分析,发现5个基因组区域与收获指数、生物量、库容量和籽粒产量高度相关。