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

作者：Christopher N. Topp, Anjali S. Iyer‐Pascuzzi, Jill T. Anderson, Cheng‐Ruei Lee, Paul R. Zurek, Olga Symonova, Ying Hui Zheng, Alexander Bucksch, Yuriy Mileyko, Taras Galkovskyi, Brad T. Moore, John Harer, Herbert Edelsbrunner, Thomas Mitchell‐Olds, Joshua S. Weitz, Philip N. Benfey · 发表于：Proceedings of the National Academy of Sciences · 年份：2013 · DOI：10.1073/pnas.1304354110 · 被引用次数：314 · 研究领域：Plant nutrient uptake and metabolism、Rice Cultivation and Yield Improvement、Plant Molecular Biology Research

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 (r(2) = 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.