Composite modeling of leaf shape across shoots discriminates Vitis species better than individual leaves
Abigail E Bryson,
Maya Wilson Brown,
Luke M Gregory,
Anna C Haber,
Emily E Jennings,
Sunil K Kenchanmane Raju,
Serena G Lotreck,
Davis T Mathieu,
Eleanore J Ritter,
Robert Z Shrote,
Kaila E Smith,
Scott J Teresi,
McKena L Wilson,
Alyssa R Tarrant,
Margaret H Frank,
Jason P. Londo,
Daniel H Chitwood
Posted 23 Jun 2020
bioRxiv DOI: 10.1101/2020.06.22.163899
Posted 23 Jun 2020
Premise of study: Leaf morphology is dynamic, continuously deforming during leaf expansion and among leaves within a shoot. We measured leaf morphology from over 200 vines over four years, and modeled changes in leaf shape along the shoot to determine if a composite shape of shapes can better capture variation and predict species identity compared to individual leaves. Methods: Using homologous universal landmarks found in grapevine leaves, we modeled various morphological features as a polynomial function of leaf node. The resulting functions are used to reconstruct modeled leaf shapes across shoots, generating composite leaves that comprehensively capture the spectrum of possible leaf morphologies. Results: 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 species identity of previously unassigned vines, which were verified with genotyping. Discussion: 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, as well as serving as a better predictor of species identity than individual leaves. ### Competing Interest Statement The authors have declared no competing interest.
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