Centre for Crop Systems Analysis, Department of Plant Sciences, Wageningen University, PO Box 430, 6700 AK Wageningen, The Netherlands.
J Exp Bot. 2012 Sep;63(14):5137-53. doi: 10.1093/jxb/ers170. Epub 2012 Aug 9.
To understand the physiological basis of genetic variation and resulting quantitative trait loci (QTLs) for photosynthesis in a rice (Oryza sativa L.) introgression line population, 13 lines were studied under drought and well-watered conditions, at flowering and grain filling. Simultaneous gas exchange and chlorophyll fluorescence measurements were conducted at various levels of incident irradiance and ambient CO(2) to estimate parameters of a model that dissects photosynthesis into stomatal conductance (g(s)), mesophyll conductance (g(m)), electron transport capacity (J(max)), and Rubisco carboxylation capacity (V(cmax)). Significant genetic variation in these parameters was found, although drought and leaf age accounted for larger proportions of the total variation. Genetic variation in light-saturated photosynthesis and transpiration efficiency (TE) were mainly associated with variation in g(s) and g(m). One previously mapped major QTL of photosynthesis was associated with variation in g(s) and g(m), but also in J(max) and V(cmax) at flowering. Thus, g(s) and g(m), which were demonstrated in the literature to be responsible for environmental variation in photosynthesis, were found also to be associated with genetic variation in photosynthesis. Furthermore, relationships between these parameters and leaf nitrogen or dry matter per unit area, which were previously found across environmental treatments, were shown to be valid for variation across genotypes. Finally, the extent to which photosynthesis rate and TE can be improved was evaluated. Virtual ideotypes were estimated to have 17.0% higher photosynthesis and 25.1% higher TE compared with the best genotype investigated. This analysis using introgression lines highlights possibilities of improving both photosynthesis and TE within the same genetic background.
为了理解水稻(Oryza sativa L.)导入系群体光合作用的遗传变异和由此产生的数量性状位点(QTL)的生理基础,在开花期和灌浆期对 13 个系在干旱和充分供水条件下进行了研究。在不同的入射辐照度和环境 CO2 水平下进行了同步气体交换和叶绿素荧光测量,以估计将光合作用分解为气孔导度(gs)、叶肉导度(gm)、电子传递能力(Jmax)和 Rubisco 羧化能力(Vcmax)的模型的参数。尽管干旱和叶片年龄占总变异的比例较大,但这些参数存在显著的遗传变异。光饱和光合作用和蒸腾效率(TE)的遗传变异主要与 gs 和 gm 的变异有关。一个先前映射的光合作用主要 QTL 与 gs 和 gm 的变异有关,但在开花期也与 Jmax 和 Vcmax 的变异有关。因此,在文献中被证明是光合作用环境变异的原因的 gs 和 gm,也与光合作用的遗传变异有关。此外,这些参数与叶片氮或单位面积干物质之间的关系,以前在各种环境处理中发现,被证明在基因型之间的变异中是有效的。最后,评估了光合作用速率和 TE 可以提高的程度。虚拟理想型估计比研究的最佳基因型具有 17.0%的更高光合作用和 25.1%的更高 TE。使用导入系的这种分析突出了在相同遗传背景下提高光合作用和 TE 的可能性。