2017年7月25日,国际植物学顶级期刊《Plant Physiology》杂志上在线发表了中国科学院上海生命科学研究院植物生理生态研究所朱新广研究组发表了题为“Leaf photosynthetic parameters related to biomass accumulation in a global rice diversity survey”的研究论文,研究报道了水稻生物产量与叶片光合参数之间的关系。研究利用215份水稻自然群体,通过特征选择策略和基因组遗传力评估,证明了水稻低光的光合利用效率具有高度遗传特性,并与水稻生物量密切相关。文章第一作者为曲明南博士。

改善冠层光合效率是提高作物产量的重要途径。冠层光合效率由三方面决定,包括叶面积指数、冠层形态结构和叶片光合特征。传统作物育种通过改变冠层株型,例如培育半矮杆水稻品种、直立株型和提高叶面积指数等手段来提高冠层光合效率;然而对光合效率本身的改良较少。

本研究利用基因组遗传力(SNP-based Heritability)结合2.3M全基因组覆盖的SNP变异信息,证明低光光合效率(Alow)具有高度遗传性;进一步为量化低光光合效率与生物量的关系,本研究结合线性回归模型(LRMs)和逐步特征选择(Feature selection)方法,发现Alow在不同地点和组合的数据集中均表现出与生物量有高度相关性。同时,在11个当代商业化水稻品种中,Alow表现出很大变异,说明在人工驯化过程中,Alow未受到强烈选择。该项研究首次揭示了叶片低光光合效率与生物产量的关系,这对未来提高水稻产量提供了全新改造靶标。

图注说明:(A)叶片光合参数与生物产量在不同地点的Pearson相关性;(B)特征选择鉴别解释生物量变异的关键光合参数;(C-D)低光光合利用率Alow在204份水稻自然群体和11个当代商业品种中的自然变异。

原文摘要:

Mining natural variations is a major approach to identify new options to improve crop light use efficiency. So far, successes in identifying photosynthetic parameters positively related to crop biomass accumulation through this approach are scarce possibly due to the earlier emphasis on properties related to leaf instead of canopy photosynthetic efficiency. This study aims to uncover rice natural variations to identify leaf physiological parameters that are highly correlated with biomass accumulation, a surrogate of canopy photosynthesis. To do this, we systematically investigated 14 photosynthetic parameters (PTs) and 4 morphological traits (MTs) in a rice population, which consists of 204 USDA-curated minicore accessions collected globally and 11 elite Chinese rice cultivars in both Beijing (BJ) and Shanghai (SH). To identify key components responsible for variance of biomass accumulation, we applied a stepwise feature selection approach based on linear regression models. Though there are large variations in photosynthetic parameters measured in different environments, we observed that photosynthetic rate under low light (Alow) was highly related to biomass accumulation and also exhibited high genomic inheritability in both environments, suggesting its great potential to be used as a target for the future rice breeding programs. Large variations in Alow among modern rice cultivars further suggest great potential of using this parameter in contemporary rice breeding for improvement of biomass and hence yield potential.

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