Bryson Abigail E, Wilson Brown Maya, Mullins Joey, Dong Wei, Bahmani Keivan, Bornowski Nolan, Chiu Christina, Engelgau Philip, Gettings Bethany, Gomezcano Fabio, Gregory Luke M, Haber Anna C, Hoh Donghee, Jennings Emily E, Ji Zhongjie, Kaur Prabhjot, Kenchanmane Raju Sunil K, Long Yunfei, Lotreck Serena G, Mathieu Davis T, Ranaweera Thilanka, Ritter Eleanore J, Sadohara Rie, Shrote Robert Z, Smith Kaila E, Teresi Scott J, Venegas Julian, Wang Hao, Wilson McKena L, Tarrant Alyssa R, Frank Margaret H, Migicovsky Zoë, Kumar Jyothi, VanBuren Robert, Londo Jason P, Chitwood Daniel H
Genetics Program Michigan State University East Lansing Michigan 48824 USA.
Department of Biochemistry and Molecular Biology Michigan State University East Lansing Michigan 48824 USA.
Appl Plant Sci. 2020 Dec 3;8(12):e11404. doi: 10.1002/aps3.11404. eCollection 2020 Dec.
Leaf morphology is dynamic, continuously deforming during leaf expansion and among leaves within a shoot. Here, we measured the leaf morphology of more than 200 grapevines ( spp.) over four years and modeled changes in leaf shape along the shoot to determine whether a composite leaf shape comprising all the leaves from a single shoot can better capture the variation and predict species identity compared with individual leaves.
Using homologous universal landmarks found in grapevine leaves, we modeled various morphological features as polynomial functions of leaf nodes. The resulting functions were used to reconstruct modeled leaf shapes across the shoots, generating composite leaves that comprehensively capture the spectrum of leaf morphologies present.
We found that composite leaves are better predictors of species identity than individual leaves from the same plant. We were able to use composite leaves to predict the species identity of previously unassigned grapevines, which were verified with genotyping.
Observations of individual leaf shape fail to capture the true diversity between species. Composite leaf shape-an assemblage of modeled leaf snapshots across the shoot-is a better representation of the dynamic and essential shapes of leaves, in addition to serving as a better predictor of species identity than individual leaves.
叶片形态是动态的，在叶片扩展过程中以及同一枝条上的叶片之间会持续变形。在此，我们在四年时间里测量了200多株葡萄（品种）的叶片形态，并对沿枝条的叶片形状变化进行建模，以确定与单个叶片相比，包含单个枝条上所有叶片的复合叶片形状是否能更好地捕捉变异并预测物种身份。
利用在葡萄叶片中发现的同源通用地标，我们将各种形态特征建模为叶节点的多项式函数。所得函数用于重建枝条上的模拟叶片形状，生成能全面捕捉现有叶片形态谱的复合叶片。
我们发现，与同一植株的单个叶片相比，复合叶片是更好的物种身份预测指标。我们能够使用复合叶片来预测先前未鉴定的葡萄品种的物种身份，并通过基因分型进行了验证。
对单个叶片形状的观察无法捕捉物种之间的真正差异。复合叶片形状——整个枝条上模拟叶片快照的集合——除了比单个叶片更能作为物种身份的预测指标外，还能更好地体现叶片的动态和基本形状。
