Image-based methods for phenotyping growth dynamics and fitness components in Arabidopsis thaliana

Plant methods 2018

François Vasseur, Justine Bresson, George Wang, Rebecca Schwab, Detlef Weigel

We developed two models to predict plant dry mass and fruit number from the parameters extracted with the analysis of rosette and inflorescence images. Predictive models were trained by sacrificing growing individuals for dry mass estimation, and manually measuring a fraction of individuals for fruit number at maturity. Using a cross-validation approach, we showed that quantitative parameters extracted from image analysis predicts more 90% of both plant dry mass and fruit number. When used on 451 natural accessions, the method allowed modeling growth dynamics, including relative growth rate, throughout the life cycle of various ecotypes. Estimated growth-related traits had high heritability (0.65 < H2 < 0.93), as well as estimated fruit number (H2 = 0.68). In addition, we validated the method for estimating fruit number with rev5, a mutant with increased flower abortion.

Application of the dry mass estimation method to model growth dynamics in A. thaliana.
Statistical modeling of rosette dry mass during ontogeny, M(t), with three-parameter logistic growth curve, on one individual (a) and 451 natural accession accessions (b); absolute growth rate during ontogeny, GR(t), on one individuals (c) and the 451 accessions (d); relative growth rate during ontogeny, RGR (t), on one individuals (e) and the 451 accessions (f). tinf (red dashed line) represents point of growth curve inflection. Individuals on the right panels are colored by duration (days) of plant life cycle. (g–i) Variation of M(tinf), GR(tinf) and RGR (tinf) across the 451 accessions phenotyped, with broad-sense heritability (H2) on the top-left corner of each panel.
Dots represent genotypic mean ±standard error (n= 2)
Application of the method to estimate fruit number in natural accessions and rev5 mutant of A. thaliana.
(a) Variability in fruit number across 441 natural accessions, with broad-sense heritability (H2) on the top-left corner. Dots represent genotypic mean ±standard error (n= 2). (b) Prediction of fruit number (mean ±95% CI) from model trained on accessions and applied to rev5 mutant and Col-0 wild-type (n=5).
Results are compared to observed fruit number manually counted at harvesting

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