Chen Hongwei, Zhao Xiuqin, Zhai Laiyuan, Shao Kuitian, Jiang Kunwei, Shen Congcong, Chen Kai, Wang Shu, Wang Yun, Xu Jianlong
Rice Research Institute, Shenyang Agricultural University, Shenyang, China.
Institute of Crop Sciences/National Key Facility for Crop Gene Resources and Genetic Improvement, Chinese Academy of Agricultural Sciences, Beijing, China.
Front Genet. 2020 Jun 9;11:611. doi: 10.3389/fgene.2020.00611. eCollection 2020.
Stomatal density () and size () are an important adaptive mechanism for abiotic stress tolerance and photosynthesis capacity in rice. However, the genetic base of rice stomata-related traits still remains unclear. We identified quantitative trait loci (QTLs) associated with and on abaxial and adaxial leaf surfaces using genome-wide association analysis with 451 diverse accessions in two environments. and S showed significant differences between () and () accessions and significantly negative phenotypic correlations. A total of 64 QTLs influencing eight stomata-related traits were identified using 2,936,762 high-quality single nucleotide polymorphism markers. Twelve QTLs were consistently detected for the same traits in nine chromosomal regions in both environments. In addition, 12 QTL clusters were simultaneously detected for the same stomata-related traits on abaxial and adaxial leaf surfaces in the same environment, probably explaining the genetic bases of significant correlations of the stomata-related traits. We screened 64 candidate genes for the nine consistent QTL regions using haplotype analysis. Among them, for , () for and , for , () or for , and for and were considered as the most likely candidate genes based on functional annotations. The results systematically dissected the genetic base of stomata-related traits and provide useful information for improving rice yield potential via increasing abiotic stress tolerance and photosynthesis capacity under stressed and non-stressed conditions through deploying the favorable alleles underlying stomata-related traits by marker-assisted selection.
气孔密度（）和大小（）是水稻耐受非生物胁迫和光合作用能力的重要适应性机制。然而，水稻气孔相关性状的遗传基础仍不清楚。我们利用全基因组关联分析，在两种环境下对451份不同的材料进行研究，鉴定了与叶片正反两面气孔密度和大小相关的数量性状位点（QTL）。气孔密度和大小在籼稻（）和粳稻（）材料间存在显著差异，且表型呈显著负相关。利用2936762个高质量单核苷酸多态性标记，共鉴定出影响8个气孔相关性状的64个QTL。在两种环境下，有12个QTL在9个染色体区域的相同性状上被一致检测到。此外，在同一环境下，叶片正反两面同时检测到12个与相同气孔相关性状的QTL簇，这可能解释了气孔相关性状显著相关性的遗传基础。我们通过单倍型分析，在9个一致的QTL区域筛选出64个候选基因。其中，基于功能注释， 、 、 、 或 以及 被认为是最有可能的候选基因。这些结果系统地剖析了气孔相关性状的遗传基础，并通过标记辅助选择部署气孔相关性状的有利等位基因，为在胁迫和非胁迫条件下提高水稻产量潜力提供了有用信息，即通过提高非生物胁迫耐受性和光合作用能力来实现。
