Dhakal Kshitiz, Zhu Qian, Zhang Bo, Li Mao, Li Song
School of Plant and Environmental Sciences, Virginia Tech, Blacksburg, VA, United States.
Donald Danforth Plant Science Center, St. Louis, MO, United States.
Front Plant Sci. 2021 Mar 3;12:614926. doi: 10.3389/fpls.2021.614926. eCollection 2021.
Edamame is a type of green, vegetable soybean and improving shoot architecture traits for edamame is important for breeding of high-yield varieties by decreasing potential loss due to harvesting. In this study, we use digital imaging technology and computer vision algorithms to characterize major traits of shoot architecture for edamame. Using a population of edamame PIs, we seek to identify underlying genetic control of different shoot architecture traits. We found significant variations in the shoot architecture of the edamame lines including long-skinny and candle stick-like structures. To quantify the similarity and differences of branching patterns between these edamame varieties, we applied a topological measurement called persistent homology. Persistent homology uses algebraic geometry algorithms to measure the structural similarities between complex shapes. We found intriguing relationships between the topological features of branching networks and pod numbers in our plant population, suggesting combination of multiple topological features contribute to the overall pod numbers on a plant. We also identified potential candidate genes including a lateral organ boundary gene family protein and a MADS-box gene that are associated with the pod numbers. This research provides insight into the genetic regulation of shoot architecture traits and can be used to further develop edamame varieties that are better adapted to mechanical harvesting.
毛豆是一种绿色的蔬菜型大豆，通过减少收获造成的潜在损失来改善毛豆的茎秆结构性状对于高产品种的育种很重要。在本研究中，我们使用数字成像技术和计算机视觉算法来表征毛豆茎秆结构的主要性状。利用一个毛豆种质群体，我们试图确定不同茎秆结构性状的潜在遗传控制。我们发现毛豆品系的茎秆结构存在显著差异，包括细长型和烛台状结构。为了量化这些毛豆品种之间分枝模式的异同，我们应用了一种称为持久同调的拓扑测量方法。持久同调使用代数几何算法来测量复杂形状之间的结构相似性。我们在植物群体中发现了分枝网络的拓扑特征与豆荚数量之间有趣的关系，这表明多种拓扑特征的组合有助于植株上的总体豆荚数量。我们还鉴定出了包括一个侧生器官边界基因家族蛋白和一个与豆荚数量相关的MADS盒基因在内的潜在候选基因。这项研究为茎秆结构性状的遗传调控提供了见解，可用于进一步培育更适合机械收获的毛豆品种。
