Quantifying floral shape variation in 3D using microcomputed tomography: a case study of a hybrid line between actinomorphic and zygomorphic flowers

The quantification of floral shape variations is difficult because flower structures are both diverse and complex. Traditionally, floral shape variations are quantified using the qualitative and linear measurements of two-dimensional (2D) images. The 2D images cannot adequately describe flower structures, and thus lead to unsatisfactory discrimination of the flower shape. This study aimed to acquire three-dimensional (3D) images by using microcomputed tomography (μCT) and to examine the floral shape variations by using geometric morphometrics (GM). To demonstrate the advantages of the 3D-μCT-GM approach, we applied the approach to a second-generation population of florist's gloxinia (Sinningia speciosa) crossed from parents of zygomorphic and actinomorphic flowers. The flowers in the population considerably vary in size and shape, thereby served as good materials to test the applicability of the proposed phenotyping approach. Procedures were developed to acquire 3D volumetric flower images using a μCT scanner, to segment the flower regions from the background, and to select homologous characteristic points (i.e., landmarks) from the flower images for the subsequent GM analysis. The procedures identified 95 landmarks for each flower and thus improved the capability of describing and illustrating the flower shapes, compared with typically lower number of landmarks in 2D analyses. The GM analysis demonstrated that flower opening and dorsoventral symmetry were the principal shape variations of the flowers. The degrees of flower opening and corolla asymmetry were then subsequently quantified directly from the 3D flower images. The 3D-μCT-GM approach revealed shape variations that could not be identified using typical 2D approaches and accurately quantified the flower traits that presented a challenge in 2D images. The approach opens new avenues to investigate floral shape variations.

[1]  Luc Vincent,et al.  Morphological Area Openings and Closings for Grey-scale Images , 1994 .

[2]  M. Chase,et al.  Dactylorhiza (Orchidaceae) in European Russia: combined molecular and morphological analysis. , 2004, American journal of botany.

[3]  J. Bosch,et al.  Spatial variation in selection on corolla shape in a generalist plant is promoted by the preference patterns of its local pollinators , 2008, Proceedings of the Royal Society B: Biological Sciences.

[4]  R. Ohsawa,et al.  Diallel analysis of floral morphology in radish (Raphanus sativus L.) , 2007, Euphytica.

[5]  S. Ninomiya,et al.  Quantitative evaluation of the petal shape variation in Primula sieboldii caused by breeding process in the last 300 years , 2005, Heredity.

[6]  Emanuele Trucco,et al.  Computer and Robot Vision , 1995 .

[7]  Charles Hansen,et al.  The Visualization Handbook , 2011 .

[8]  C. Demayo,et al.  Landmark and outline methods in describing petal, sepal and labellum shapes of the flower of Mokara orchid varieties. , 2011 .

[9]  Bernd Hamann,et al.  Evolutionary morphing , 2005, VIS 05. IEEE Visualization, 2005..

[10]  S. Mooney,et al.  Seeing space: visualization and quantification of plant leaf structure using X-ray micro-computed tomography. , 2013, Journal of experimental botany.

[11]  Dilworth Y Parkinson,et al.  Using high resolution computed tomography to visualize the three dimensional structure and function of plant vasculature. , 2013, Journal of visualized experiments : JoVE.

[12]  Ta-Te Lin,et al.  Quantitative analysis of floral symmetry and tube dilation in an F2 cross of Sinningia speciosa , 2015 .

[13]  Christian Peter Klingenberg,et al.  Evolution and development of shape: integrating quantitative approaches , 2010, Nature Reviews Genetics.

[14]  P. D. Polly,et al.  Geometric morphometrics: recent applications to the study of evolution and development , 2010 .

[15]  F. Rohlf,et al.  Extensions of the Procrustes Method for the Optimal Superimposition of Landmarks , 1990 .

[16]  C. Kuhlemeier,et al.  The genetic dissection of floral pollination syndromes. , 2006, Current opinion in plant biology.

[17]  F. Rohlf,et al.  Geometric morphometrics: Ten years of progress following the ‘revolution’ , 2004 .

[18]  Mihoshi Yokoo,et al.  Quantitative analysis of corolla shapes and petal contours in single-flower cultivars of lisianthus , 2009 .

[19]  C. Klingenberg,et al.  Geometric morphometrics of corolla shape: dissecting components of symmetric and asymmetric variation in Erysimum mediohispanicum (Brassicaceae). , 2012, The New phytologist.

[20]  Richard Kennaway,et al.  Evolution of Allometry in Antirrhinum[C][W] , 2009, The Plant Cell Online.

[21]  J. Gower.  Generalized procrustes analysis , 1975 .

[22]  Jill S Miller,et al.  FLORAL MORPHOMETRICS AND THE EVOLUTION OF SEXUAL DIMORPHISM IN LYCIUM (SOLANACEAE) , 2003, Evolution; international journal of organic evolution.

[23]  Saneyuki Kawabata,et al.  Assessment of the Association between the Three-dimensional Shape of the Corolla and Two-dimensional Shapes of Petals Using Fourier Descriptors and Principal Component Analysis in Eustoma grandiflorum , 2011 .

[24]  S. Ninomiya,et al.  Genetic Combining Ability of Petal Shape in Garden Pansy (Viola × wittrockiana Gams) based on Image Analysis , 2006, Euphytica.

[25]  Charles R. Giardina,et al.  Elliptic Fourier features of a closed contour , 1982, Comput. Graph. Image Process..

[26]  J. Arroyo,et al.  Convergent evolution of flower polymorphism in Narcissus (Amaryllidaceae) , 2003 .

[27]  Griffiths G. Atungulu,et al.  Three-Dimensional Geometric Modeling of Processing Tomatoes , 2011 .

[28]  J. Bangham,et al.  Quantitative Control of Organ Shape by Combinatorial Gene Activity , 2010, PLoS biology.

[29]  Anne C. Gaskett,et al.  Corolla shape vs. size in flower choice by a nocturnal hawkmoth pollinator , 2012 .

[30]  I. Jolliffe.  Principal Component Analysis , 2005 .

[31]  P. K. Endress.  Evolution of floral symmetry. , 2001, Current opinion in plant biology.

[32]  C. Zollikofer,et al.  Three-dimensional geometric morphometrics for studying floral shape variation. , 2010, Trends in plant science.

[33]  Guifang Fu,et al.  Shape mapping: genetic mapping meets geometric morphometrics , 2014, Briefings Bioinform..

[34]  Wilhelm Burger,et al.  Digital Image Processing - An Algorithmic Introduction using Java , 2008, Texts in Computer Science.

[35]  S. Ninomiya,et al.  Ability of bumblebees to discriminate differences in the shape of artificial flowers of Primula sieboldii (Primulaceae). , 2007, Annals of botany.

[36]  Hitoshi Watanabe,et al.  Current status of commercial Calibrachoa cultivars as assessed by morphology and other traits , 2010 .

[37]  S. Kawabata,et al.  Three-dimensional formation of corolla shapes in relation to the developmental distortion of petals in Eustoma grandiflorum , 2011 .

[38]  J. Gómez,et al.  Corolla morphology influences diversification rates in bifid toadflaxes (Linaria sect. Versicolores). , 2013, Annals of botany.

[39]  H. David Sheets,et al.  Geometric morphometrics for biologists : a primer , 2004 .

[40]  F. Perfectti,et al.  Natural Selection on Erysimum mediohispanicum Flower Shape: Insights into the Evolution of Zygomorphy , 2006, The American Naturalist.