Identifying developmental phases in the Arabidopsis thaliana rosette using integrative segmentation models.

Maryline Lièvre, Christine Granier, Yann Guédon
Author Information
  1. Maryline Lièvre: INRA, UMR LEPSE, 34060, Montpellier, France.
  2. Christine Granier: INRA, UMR LEPSE, 34060, Montpellier, France.
  3. Yann Guédon: CIRAD, UMR AGAP and Inria, Virtual Plants, 34095, Montpellier, France.

Abstract

The change in leaf size and shape during ontogeny associated with heteroblastic development is a composite trait for which extensive spatiotemporal data can be acquired using phenotyping platforms. However, only part of the information contained in such data is exploited, and developmental phases are usually defined using a selected organ trait. We here introduce new methods for identifying developmental phases in the Arabidopsis rosette using various traits and minimum a priori assumptions. A pipeline of analysis was developed combining image analysis and statistical models to integrate morphological, shape, dimensional and expansion dynamics traits for the successive leaves of the Arabidopsis rosette. Dedicated segmentation models called semi-Markov switching models were built for selected genotypes in order to identify rosette developmental phases. Four successive developmental phases referred to as seedling, juvenile, transition and adult were identified for the different genotypes. We show that the degree of covering of the leaf abaxial surface with trichomes is insufficient to define these developmental phases. Using our pipeline of analysis, we were able to identify the supplementary seedling phase and to uncover the structuring role of various leaf traits. This enabled us to compare on a more objective basis the vegetative development of Arabidopsis mutants.

Keywords

MeSH Term

Arabidopsis
Genotype
Image Processing, Computer-Assisted
Models, Statistical
Mutation
Phenotype
Plant Leaves
Seedlings

Word Cloud

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