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Integrative Modelling of Gene Expression and Digital Phenotypes to Describe Senescence in Wheat

Senescence is the final stage of leaf development and is critical for plants’ fitness as nutrient relocation from leaves to reproductive organs takes place. Although senescence is key in nutrient relocation and yield determination in cereal grain production, there is limited understanding of the gen...

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Autor principal: Camargo Rodriguez, Anyela Valentina
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8230903/
https://www.ncbi.nlm.nih.gov/pubmed/34208213
http://dx.doi.org/10.3390/genes12060909
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author Camargo Rodriguez, Anyela Valentina
author_facet Camargo Rodriguez, Anyela Valentina
author_sort Camargo Rodriguez, Anyela Valentina
collection PubMed
description Senescence is the final stage of leaf development and is critical for plants’ fitness as nutrient relocation from leaves to reproductive organs takes place. Although senescence is key in nutrient relocation and yield determination in cereal grain production, there is limited understanding of the genetic and molecular mechanisms that control it in major staple crops such as wheat. Senescence is a highly orchestrated continuum of interacting pathways throughout the lifecycle of a plant. Levels of gene expression, morphogenesis, and phenotypic development all play key roles. Yet, most studies focus on a short window immediately after anthesis. This approach clearly leaves out key components controlling the activation, development, and modulation of the senescence pathway before anthesis, as well as during the later developmental stages, during which grain development continues. Here, a computational multiscale modelling approach integrates multi-omics developmental data to attempt to simulate senescence at the molecular and plant level. To recreate the senescence process in wheat, core principles were borrowed from Arabidopsis Thaliana, a more widely researched plant model. The resulted model describes temporal gene regulatory networks and their effect on plant morphology leading to senescence. Digital phenotypes generated from images using a phenomics platform were used to capture the dynamics of plant development. This work provides the basis for the application of computational modelling to advance understanding of the complex biological trait senescence. This supports the development of a predictive framework enabling its prediction in changing or extreme environmental conditions, with a view to targeted selection for optimal lifecycle duration for improving resilience to climate change.
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spelling pubmed-82309032021-06-26 Integrative Modelling of Gene Expression and Digital Phenotypes to Describe Senescence in Wheat Camargo Rodriguez, Anyela Valentina Genes (Basel) Article Senescence is the final stage of leaf development and is critical for plants’ fitness as nutrient relocation from leaves to reproductive organs takes place. Although senescence is key in nutrient relocation and yield determination in cereal grain production, there is limited understanding of the genetic and molecular mechanisms that control it in major staple crops such as wheat. Senescence is a highly orchestrated continuum of interacting pathways throughout the lifecycle of a plant. Levels of gene expression, morphogenesis, and phenotypic development all play key roles. Yet, most studies focus on a short window immediately after anthesis. This approach clearly leaves out key components controlling the activation, development, and modulation of the senescence pathway before anthesis, as well as during the later developmental stages, during which grain development continues. Here, a computational multiscale modelling approach integrates multi-omics developmental data to attempt to simulate senescence at the molecular and plant level. To recreate the senescence process in wheat, core principles were borrowed from Arabidopsis Thaliana, a more widely researched plant model. The resulted model describes temporal gene regulatory networks and their effect on plant morphology leading to senescence. Digital phenotypes generated from images using a phenomics platform were used to capture the dynamics of plant development. This work provides the basis for the application of computational modelling to advance understanding of the complex biological trait senescence. This supports the development of a predictive framework enabling its prediction in changing or extreme environmental conditions, with a view to targeted selection for optimal lifecycle duration for improving resilience to climate change. MDPI 2021-06-11 /pmc/articles/PMC8230903/ /pubmed/34208213 http://dx.doi.org/10.3390/genes12060909 Text en © 2021 by the author. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Camargo Rodriguez, Anyela Valentina
Integrative Modelling of Gene Expression and Digital Phenotypes to Describe Senescence in Wheat
title Integrative Modelling of Gene Expression and Digital Phenotypes to Describe Senescence in Wheat
title_full Integrative Modelling of Gene Expression and Digital Phenotypes to Describe Senescence in Wheat
title_fullStr Integrative Modelling of Gene Expression and Digital Phenotypes to Describe Senescence in Wheat
title_full_unstemmed Integrative Modelling of Gene Expression and Digital Phenotypes to Describe Senescence in Wheat
title_short Integrative Modelling of Gene Expression and Digital Phenotypes to Describe Senescence in Wheat
title_sort integrative modelling of gene expression and digital phenotypes to describe senescence in wheat
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8230903/
https://www.ncbi.nlm.nih.gov/pubmed/34208213
http://dx.doi.org/10.3390/genes12060909
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