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Optical topometry and machine learning to rapidly phenotype stomatal patterning traits for QTL mapping in maize
bioRxiv - Plant Biology Pub Date : 2020-10-12 , DOI: 10.1101/2020.10.09.333880
Jiayang Xie , Dustin Mayfield-Jones , Gorka Erice , Min Choi , Andrew D.B. Leakey

Stomata are adjustable pores on leaf surfaces that regulate the trade-off of CO2 uptake with water vapor loss, thus having critical roles in controlling photosynthetic carbon gain and plant water use. The lack of easy, rapid methods for phenotyping epidermal cell traits have limited the use of quantitative, forward and reverse genetics to discover the genetic basis of stomatal patterning. A new high-throughput epidermal cell phenotyping pipeline is presented here and used for quantitative trait loci (QTL) mapping in field-grown maize. The locations and sizes of stomatal complexes and pavement cells on images acquired by an optical topometer from mature leaves were automatically determined. Computer estimated stomatal complex density (SCD; R2 = 0.97) and stomatal complex area (SCA; R2 = 0.71) were strongly correlated with human measurements. Leaf gas exchange traits correlated with the dimensions and proportion of stomatal complexes but, unexpectedly, did not correlate with SCD. Genetic variation in epidermal traits were consistent across two field seasons. Out of 143 QTLs in total, 36 QTLs were consistently identified for a given trait in both years. 24 hotspots of overlapping QTLs for multiple traits were identified. Orthologs of genes known to regulate stomatal patterning in Arabidopsis were located within some, but not all, of these regions. This study demonstrates how discovery of the genetic basis for stomatal patterning can be accelerated in maize, a model for C4 species where these processes are poorly understood.

中文翻译:

光学形貌学和机器学习技术可快速对玉米气孔构型性状进行表型分析,以进行玉米QTL定位

气孔是叶片表面上的可调节孔,可调节二氧化碳吸收与水蒸气损失之间的权衡,因此在控制光合作用的碳增加和植物用水方面具有关键作用。缺乏用于表皮细胞性状表型分型的简便,快速的方法,限制了使用定量,正向和反向遗传学来发现气孔模式的遗传基础。本文介绍了一种新的高通量表皮细胞表型分析管道,该管道用于田间种植的玉米中的定量性状基因座(QTL)作图。自动确定光学拓扑仪从成熟叶片上获取的图像上的气孔复合体和路面细胞的位置和大小。计算机估计的气孔复合体密度(SCD; R2 = 0.97)和气孔复合体面积(SCA; R2 = 0.71)与人体测量值密切相关。叶片气体交换性状与气孔复合体的大小和比例有关,但是出乎意料的是,与SCD不相关。表皮性状的遗传变异在两个田间季节一致。在这两年中,在总共143个QTL中,针对给定的性状一致地鉴定出36个QTL。确定了多个性状的重叠QTL的24个热点。已知在拟南芥中调节气孔模式的基因的直系同源基因位于这些区域中的一些但不是全部区域中。这项研究证明了如何加速玉米气孔模式遗传基础的发现,玉米是对这些过程了解甚少的C4物种模型。表皮性状的遗传变异在两个田间季节一致。在这两年中,在总共143个QTL中,针对给定的性状一致地鉴定出36个QTL。确定了多个性状的重叠QTL的24个热点。已知在拟南芥中调节气孔模式的基因的直系同源基因位于这些区域中的一些但不是全部区域中。这项研究证明了如何加速玉米气孔模式遗传基础的发现,玉米是对这些过程了解甚少的C4物种模型。表皮性状的遗传变异在两个田间季节一致。在这两年中,在总共143个QTL中,针对给定的性状一致地鉴定出36个QTL。确定了多个性状的重叠QTL的24个热点。已知在拟南芥中调节气孔模式的基因的直系同源基因位于这些区域中的一些但不是全部区域中。这项研究证明了如何加速玉米气孔模式遗传基础的发现,玉米是对这些过程了解甚少的C4物种模型。已知在拟南芥中调节气孔模式的基因的直系同源基因位于这些区域中的一些但不是全部区域中。这项研究证明了如何加速玉米气孔模式遗传基础的发现,玉米是对这些过程了解甚少的C4物种模型。已知在拟南芥中调节气孔模式的基因的直系同源基因位于这些区域中的一些但不是全部区域中。这项研究证明了如何加速玉米气孔模式遗传基础的发现,玉米是对这些过程了解甚少的C4物种模型。
更新日期:2020-10-12
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