Can exploiting natural genetic variation in leaf photosynthesis contribute to increasing rice productivity? A simulation analysis
Can exploiting natural genetic variation in leaf photosynthesis contribute to increasing rice productivity? A simulation analysis
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DOI：
10.1111/pce.12173
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发表时间：
2014-01-01
影响因子：
7.3
通讯作者：
Struik, Paul C.
中科院分区：
文献类型：
--
作者：
Gu, Junfei;Yin, Xinyou;Struik, Paul C.
水稻生产力可能受到叶片光合同化物的限制。然而，作物产量与叶片光合速率（A）之间缺乏显著的相关性。由于从叶片水平到作物水平的复杂约束和反馈机制，改善叶片光合作用的工程已经被认为对作物生产力的增加很少。在这里，我们研究了A中的自然遗传变异在多大程度上有助于提高水稻产量。利用GECROS机制模型，基于水稻渐渗系群体内各种光合组分的数量性状位点，分析了A的遗传变异对作物生物量生产的影响。我们发现，A中25%的遗传变异可以同等地扩大到作物水平，导致不同地点和年份的生物量增加22 - 29%。这可能是因为A的遗传变异不仅来自Rubisco（核酮糖1，5-二磷酸羧化酶/加氧酶）限制的光合作用，而且来自电子传递限制的光合作用，因此，冠层中光饱和和光限制叶片的光合速率都得到了提高。挖掘现有种质资源的自然变异，特别是决定光限光合作用参数的变异，可以显著提高水稻的生产力。
Rice productivity can be limited by available photosynthetic assimilates from leaves. However, the lack of significant correlation between crop yield and leaf photosynthetic rate (A) is noted frequently. Engineering for improved leaf photosynthesis has been argued to yield little increase in crop productivity because of complicated constraints and feedback mechanisms when moving up from leaf to crop level. Here we examined the extent to which natural genetic variation in A can contribute to increasing rice productivity. Using the mechanistic model GECROS, we analysed the impact of genetic variation in A on crop biomass production, based on the quantitative trait loci for various photosynthetic components within a rice introgression line population. We showed that genetic variation in A of 25% can be scaled up equally to crop level, resulting in an increase in biomass of 22-29% across different locations and years. This was probably because the genetic variation in A resulted not only from Rubisco (ribulose 1,5-bisphosphate carboxylase/oxygenase)-limited photosynthesis but also from electron transport-limited photosynthesis; as a result, photosynthetic rates could be improved for both light-saturated and light-limited leaves in the canopy. Rice productivity could be significantly improved by mining the natural variation in existing germ-plasm, especially the variation in parameters determining light-limited photosynthesis.