Composite modeling of leaf shape across shoots discriminates Vitis species better than individual leaves

Authors: BRYSON, ABIGAIL - Michigan State University; BROWN, MAYA - Michigan State University; MULLINS, JOEY - Michigan State University; DONG, WEI - Michigan State University; BAHMANI, KEIVAN - Michigan State University; BORNOWSKI, N - Michigan State University; CHIU, CHRISTINA - Michigan State University; ENGELGAU, PHILIP - Michigan State University; GETTINGS, BETHANY - Michigan State University; GOMEZCANO, FABIO - Michigan State University; GREGORY, LUKE - Michigan State University; HABER, ANNA - Michigan State University; HOH, DONGHEE - Michigan State University; JENNINGS, EMILY - Michigan State University; JI, ZHONGJIE - Michigan State University; KAUR, PRABHJOT - Michigan State University; RAFU KENCHANMANE, SUNIL - Michigan State University; LONG, YUNFEI - Michigan State University; LOTRECK, SERENA - Michigan State University; MATHIEU, DAVIS - Michigan State University; RANAWEERA, THILANKA - Michigan State University; RITTER, ELEANORE - Michigan State University; SADOHARA, RIE - Michigan State University; SHROTE, ROBERT - Michigan State University; SMITH, KAILA - Michigan State University; TERESI, SCOTT - Michigan State University; VENEGAS, JULIAN - Michigan State University; WANG, HAO - Michigan State University; WILSON, MCKENA - Michigan State University; TARRANT, ALYSSA - Michigan State University; FRANK, MARGARET - Michigan State University; MIGICOVSKY, ZOE - Dalhousie University; KUMAR, JYOTHI - Michigan State University; VANBUREN, ROBERT - Michigan State University; Londo, Jason; CHITWOOD, DAN - Michigan State University

Submitted to: Applications in Plant Sciences
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 12/3/2020
Publication Date: 12/3/2020
Publication URL: https://handle.nal.usda.gov/10113/7709433
Citation: Bryson, A.E., Brown, M.W., Mullins, J., Dong, W., Bahmani, K., Bornowski, N., Chiu, C., Engelgau, P., Gettings, B., Gomezcano, F., Gregory, L.M., Haber, A.C., Hoh, D., Jennings, E.E., Ji, Z., Kaur, P., Rafu Kenchanmane, S.K., Long, Y., Lotreck, S.G., Mathieu, D.T., Ranaweera, T., Ritter, E.J., Sadohara, R., Shrote, R.Z., Smith, K.E., Teresi, S.J., Venegas, J., Wang, H., Wilson, M.L., Tarrant, A.R., Frank, M.H., Migicovsky, Z., Kumar, J., Vanburen, R., Londo, J.P., Chitwood, D.H. 2020. Composite modeling of leaf shape across shoots discriminates Vitis species better than individual leaves. Applications in Plant Sciences. 1.
DOI: https://doi.org/10.1002/aps3.11404

Interpretive Summary: The shape of leaves along a branch or vine represent a dynamic, continuously changing pattern driven by differences in leaf expansion rates.  Using the shapes of leaves collected from over 200 different grapevine accessions and over four different years, we modeled how consistent leaf shapes are across a vine.  Using this measurement of a "shape of shapes" we determined that grapevine species identity can be predicted with high confidence from shape alone.  We were unable to predict species using single leaf samples, but the composite shapes represent a better representation of the inherent differences between species.  

Technical Abstract: 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. 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. 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. 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.