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PNAS Plus: 3D phenotyping and quantitative trait locus mapping identify core regions of the rice genome controlling root architecture

机译:PNAS Plus:3D表型和数量性状基因座图谱确定了水稻基因组控制根结构的核心区域

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摘要

Identification of genes that control root system architecture in crop plants requires innovations that enable high-throughput and accurate measurements of root system architecture through time. We demonstrate the ability of a semiautomated 3D in vivo imaging and digital phenotyping pipeline to interrogate the quantitative genetic basis of root system growth in a rice biparental mapping population, Bala × Azucena. We phenotyped >1,400 3D root models and >57,000 2D images for a suite of 25 traits that quantified the distribution, shape, extent of exploration, and the intrinsic size of root networks at days 12, 14, and 16 of growth in a gellan gum medium. From these data we identified 89 quantitative trait loci, some of which correspond to those found previously in soil-grown plants, and provide evidence for genetic tradeoffs in root growth allocations, such as between the extent and thoroughness of exploration. We also developed a multivariate method for generating and mapping central root architecture phenotypes and used it to identify five major quantitative trait loci (r2 = 24–37%), two of which were not identified by our univariate analysis. Our imaging and analytical platform provides a means to identify genes with high potential for improving root traits and agronomic qualities of crops.
机译:鉴定控制作物植物根系结构的基因需要创新,以实现高通量和随时间推移对根系结构的准确测量。我们证明了半自动化的3D体内成像和数字表型管道在水稻双亲作图种群Bala×Azucena中询问根系生长的定量遗传基础的能力。我们对25种性状进行了分类,对超过1,400个3D根模型和大于57,000个2D图像进行了表型化,这些特征量化了吉兰糖胶生长第12、14和16天时根网的分布,形状,探索程度和内在大小介质。从这些数据中,我们确定了89个数量性状位点,其中一些与以前在土壤植物中发现的位点相对应,并为根系生长分配中的遗传折衷提供了证据,例如在探索的程度和彻底性之间。我们还开发了一种用于生成和映射中心根架构表型的多变量方法,并将其用于识别五个主要的数量性状基因座(r 2 = 24-37%),其中两个未被我们的单变量识别分析。我们的成像和分析平台提供了一种手段,可用于鉴定具有改善作物根系特征和农艺品质的高潜力基因。

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