Literature DB >> 35895191

An Automated High-Throughput Phenotyping System for Marchantia polymorpha.

Karina Medina-Jimenez1, Mario A Arteaga-Vazquez2, Argelia Lorence3,4.   

Abstract

High-throughput phenotyping (HTP) allows automation of fast and precise acquisition and analysis of digital images for the detection of key traits in real time. HTP improves characterization of the growth and development of plants in controlled environments in a nondestructive fashion. Marchantia polymorpha has emerged as a very attractive model for studying the evolution of the physiological, cellular, molecular, and developmental adaptations that enabled plants to conquer their terrestrial environments. The availability of the M. polymorpha genome in combination with a full set of functional genomic tools including genetic transformation, homologous recombination, and genome editing has allowed the inspection of its genome through forward and reverse genetics approaches. The increasing number of mutants has made it possible to perform informative genome-wide analyses to study the phenotypic consequences of gene inactivation. Here we present an HTP protocol for M. polymorpha that will aid current efforts to quantify numerous morphological parameters that can potentially reveal genotype-to-phenotype relationships and relevant connections between individual traits.
© 2022. The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature.

Entities:  

Keywords:  High-throughput phenotyping; Marchantia polymorpha; Morphological parameters

Mesh:

Year:  2022        PMID: 35895191     DOI: 10.1007/978-1-0716-2537-8_2

Source DB:  PubMed          Journal:  Methods Mol Biol        ISSN: 1064-3745


  1 in total

1.  Optimizing experimental procedures for quantitative evaluation of crop plant performance in high throughput phenotyping systems.

Authors:  Astrid Junker; Moses M Muraya; Kathleen Weigelt-Fischer; Fernando Arana-Ceballos; Christian Klukas; Albrecht E Melchinger; Rhonda C Meyer; David Riewe; Thomas Altmann
Journal:  Front Plant Sci       Date:  2015-01-20       Impact factor: 5.753

  1 in total

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