Literature DB >> 28992225

A guideline for leaf senescence analyses: from quantification to physiological and molecular investigations.

Justine Bresson1, Stefan Bieker1, Lena Riester1, Jasmin Doll1, Ulrike Zentgraf1.   

Abstract

Leaf senescence is not a chaotic breakdown but a dynamic process following a precise timetable. It enables plants to economize with their resources and control their own viability and integrity. The onset as well as the progression of leaf senescence are co-ordinated by a complex genetic network that continuously integrates developmental and environmental signals such as biotic and abiotic stresses. Therefore, studying senescence requires an integrative and multi-scale analysis of the dynamic changes occurring in plant physiology and metabolism. In addition to providing an automated and standardized method to quantify leaf senescence at the macroscopic scale, we also propose an analytic framework to investigate senescence at physiological, biochemical, and molecular levels throughout the plant life cycle. We have developed protocols and suggested methods for studying different key processes involved in senescence, including photosynthetic capacities, membrane degradation, redox status, and genetic regulation. All methods presented in this review were conducted on Arabidopsis thaliana Columbia-0 and results are compared with senescence-related mutants. This guideline includes experimental design, protocols, recommendations, and the automated tools for leaf senescence analyses that could also be applied to other species.
© The Author(s) 2017. Published by Oxford University Press on behalf of the Society for Experimental Biology. All rights reserved. For permissions, please email: journals.permissions@oup.com.

Entities:  

Keywords:  Arabidopsis thaliana; automated colourimetric assay; genetic regulation; ion leakage; leaf senescence; lipid peroxidation; photosynthetic capacities; redox regulation

Mesh:

Year:  2018        PMID: 28992225     DOI: 10.1093/jxb/erx246

Source DB:  PubMed          Journal:  J Exp Bot        ISSN: 0022-0957            Impact factor:   6.992


  28 in total

1.  Integrated Genome-Scale Analysis Identifies Novel Genes and Networks Underlying Senescence in Maize.

Authors:  Rajandeep S Sekhon; Christopher Saski; Rohit Kumar; Barry S Flinn; Feng Luo; Timothy M Beissinger; Arlyn J Ackerman; Matthew W Breitzman; William C Bridges; Natalia de Leon; Shawn M Kaeppler
Journal:  Plant Cell       Date:  2019-06-25       Impact factor: 11.277

2.  Senescence and Defense Pathways Contribute to Heterosis.

Authors:  Rebeca Gonzalez-Bayon; Yifei Shen; Michael Groszmann; Anyu Zhu; Aihua Wang; Annapurna D Allu; Elizabeth S Dennis; W James Peacock; Ian K Greaves
Journal:  Plant Physiol       Date:  2019-02-01       Impact factor: 8.340

3.  ASCORBATE PEROXIDASE6 delays the onset of age-dependent leaf senescence.

Authors:  Changming Chen; Yael Galon; Maryam Rahmati Ishka; Shimrit Malihi; Vladislava Shimanovsky; Shir Twito; Abhishek Rath; Olena K Vatamaniuk; Gad Miller
Journal:  Plant Physiol       Date:  2021-03-15       Impact factor: 8.340

4.  Identification of Transcription Factors Regulating Senescence in Wheat through Gene Regulatory Network Modelling.

Authors:  Philippa Borrill; Sophie A Harrington; James Simmonds; Cristobal Uauy
Journal:  Plant Physiol       Date:  2019-05-07       Impact factor: 8.340

5.  A mutation in Arabidopsis SAL1 alters its in vitro activity against IP3 and delays developmental leaf senescence in association with lower ROS levels.

Authors:  Reza Shirzadian-Khorramabad; Taghi Moazzenzadeh; Reza H Sajedi; Hai-Chun Jing; Jacques Hille; Paul P Dijkwel
Journal:  Plant Mol Biol       Date:  2022-02-05       Impact factor: 4.076

6.  The AP2/ERF transcription factor SlERF.F5 functions in leaf senescence in tomato.

Authors:  Yanan Chen; Panpan Feng; Boyan Tang; Zongli Hu; Qiaoli Xie; Shuang Zhou; Guoping Chen
Journal:  Plant Cell Rep       Date:  2022-03-03       Impact factor: 4.570

7.  Mathematical Modeling Reveals That Sucrose Regulates Leaf Senescence via Dynamic Sugar Signaling Pathways.

Authors:  Muhammad Asim; Quaid Hussain; Xiaolin Wang; Yanguo Sun; Haiwei Liu; Rayyan Khan; Shasha Du; Yi Shi; Yan Zhang
Journal:  Int J Mol Sci       Date:  2022-06-10       Impact factor: 6.208

8.  Plant senescence: how plants know when and how to die.

Authors:  Hye Ryun Woo; Céline Masclaux-Daubresse; Pyung Ok Lim
Journal:  J Exp Bot       Date:  2018-02-12       Impact factor: 6.992

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

Authors:  François Vasseur; Justine Bresson; George Wang; Rebecca Schwab; Detlef Weigel
Journal:  Plant Methods       Date:  2018-07-26       Impact factor: 4.993

10.  Identification and Expression Profiling Analysis of the Cation/Ca2+ Exchanger (CCX) Gene Family: Overexpression of SlCCX1-LIKE Regulates the Leaf Senescence in Tomato Flowering Phase.

Authors:  Jiao Li; Yaran Zhao; Chenliang Chang; Xin Liu; Jing Jiang
Journal:  Front Genet       Date:  2021-06-25       Impact factor: 4.599

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