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Abstract Tepary bean (Phaseolus acutifoliusA. Gray), indigenous to the arid climates of northern Mexico and the Southwest United States, diverged from common bean (Phaseolus vulgarisL.), approximately 2 million years ago and exhibits a wide range of resistance to biotic stressors. The tepary genome is highly syntenic to the common bean genome providing a foundation for discovery and breeding of agronomic traits between these two crop species. Although a limited number of adaptive traits from tepary bean have been introgressed into common bean, hybridization barriers between these two species required the development of bridging lines to alleviate this barrier. Thus, to fully utilize the extant tepary bean germplasm as both a crop and as a donor of adaptive traits, we developed a diversity panel of 422 cultivated, weedy, and wild tepary bean accessions which were then genotyped and phenotyped to enable population genetic analyses and genome‐wide association studies for their response to a range of biotic stressors. Population structure analyses of the panel revealed eight subpopulations and the differentiation of botanical varieties withinP. acutifolius. Genome‐wide association studies revealed loci and candidate genes underlying biotic stress resistance including quantitative trait loci for resistance to weevils, common bacterial blight, Fusarium wilt, and bean common mosaic necrosis virus that can be harnessed not only for tepary bean but also common bean improvement. 

PremiseLeaf 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 (Vitisspp.) 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. MethodsUsing 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. ResultsWe 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. DiscussionObservations 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.