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Network-Based Analysis to Identify Hub Genes Involved in Spatial Root Response to Mechanical Constrains

Previous studies report that the asymmetric response, observed along the main poplar woody bent root axis, was strongly related to both the type of mechanical forces (compression or tension) and the intensity of force displacement. Despite a large number of targets that have been proposed to trigger...

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Autores principales: Dimitrova, Anastazija, Sferra, Gabriella, Scippa, Gabriella Stefania, Trupiano, Dalila
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9564363/
https://www.ncbi.nlm.nih.gov/pubmed/36231084
http://dx.doi.org/10.3390/cells11193121
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author Dimitrova, Anastazija
Sferra, Gabriella
Scippa, Gabriella Stefania
Trupiano, Dalila
author_facet Dimitrova, Anastazija
Sferra, Gabriella
Scippa, Gabriella Stefania
Trupiano, Dalila
author_sort Dimitrova, Anastazija
collection PubMed
description Previous studies report that the asymmetric response, observed along the main poplar woody bent root axis, was strongly related to both the type of mechanical forces (compression or tension) and the intensity of force displacement. Despite a large number of targets that have been proposed to trigger this asymmetry, an understanding of the comprehensive and synergistic effect of the antistress spatially related pathways is still lacking. Recent progress in the bioinformatics area has the potential to fill these gaps through the use of in silico studies, able to investigate biological functions and pathway overlaps, and to identify promising targets in plant responses. Presently, for the first time, a comprehensive network-based analysis of proteomic signatures was used to identify functions and pivotal genes involved in the coordinated signalling pathways and molecular activities that asymmetrically modulate the response of different bent poplar root sectors and sides. To accomplish this aim, 66 candidate proteins, differentially represented across the poplar bent root sides and sectors, were grouped according to their abundance profile patterns and mapped, together with their first neighbours, on a high-confidence set of interactions from STRING to compose specific cluster-related subnetworks (I–VI). Successively, all subnetworks were explored by a functional gene set enrichment analysis to identify enriched gene ontology terms. Subnetworks were then analysed to identify the genes that are strongly interconnected with other genes (hub gene) and, thus, those that have a pivotal role in the bent root asymmetric response. The analysis revealed novel information regarding the response coordination, communication, and potential signalling pathways asymmetrically activated along the main root axis, delegated mainly to Ca(2+) (for new lateral root formation) and ROS (for gravitropic response and lignin accumulation) signatures. Furthermore, some of the data indicate that the concave side of the bent sector, where the mechanical forces are most intense, communicates to the other (neighbour and distant) sectors, inducing spatially related strategies to ensure water uptake and accompanying cell modification. This information could be critical for understanding how plants maintain and improve their structural integrity—whenever and wherever it is necessary—in natural mechanical stress conditions.
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spelling pubmed-95643632022-10-15 Network-Based Analysis to Identify Hub Genes Involved in Spatial Root Response to Mechanical Constrains Dimitrova, Anastazija Sferra, Gabriella Scippa, Gabriella Stefania Trupiano, Dalila Cells Article Previous studies report that the asymmetric response, observed along the main poplar woody bent root axis, was strongly related to both the type of mechanical forces (compression or tension) and the intensity of force displacement. Despite a large number of targets that have been proposed to trigger this asymmetry, an understanding of the comprehensive and synergistic effect of the antistress spatially related pathways is still lacking. Recent progress in the bioinformatics area has the potential to fill these gaps through the use of in silico studies, able to investigate biological functions and pathway overlaps, and to identify promising targets in plant responses. Presently, for the first time, a comprehensive network-based analysis of proteomic signatures was used to identify functions and pivotal genes involved in the coordinated signalling pathways and molecular activities that asymmetrically modulate the response of different bent poplar root sectors and sides. To accomplish this aim, 66 candidate proteins, differentially represented across the poplar bent root sides and sectors, were grouped according to their abundance profile patterns and mapped, together with their first neighbours, on a high-confidence set of interactions from STRING to compose specific cluster-related subnetworks (I–VI). Successively, all subnetworks were explored by a functional gene set enrichment analysis to identify enriched gene ontology terms. Subnetworks were then analysed to identify the genes that are strongly interconnected with other genes (hub gene) and, thus, those that have a pivotal role in the bent root asymmetric response. The analysis revealed novel information regarding the response coordination, communication, and potential signalling pathways asymmetrically activated along the main root axis, delegated mainly to Ca(2+) (for new lateral root formation) and ROS (for gravitropic response and lignin accumulation) signatures. Furthermore, some of the data indicate that the concave side of the bent sector, where the mechanical forces are most intense, communicates to the other (neighbour and distant) sectors, inducing spatially related strategies to ensure water uptake and accompanying cell modification. This information could be critical for understanding how plants maintain and improve their structural integrity—whenever and wherever it is necessary—in natural mechanical stress conditions. MDPI 2022-10-04 /pmc/articles/PMC9564363/ /pubmed/36231084 http://dx.doi.org/10.3390/cells11193121 Text en © 2022 by the authors. 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
Dimitrova, Anastazija
Sferra, Gabriella
Scippa, Gabriella Stefania
Trupiano, Dalila
Network-Based Analysis to Identify Hub Genes Involved in Spatial Root Response to Mechanical Constrains
title Network-Based Analysis to Identify Hub Genes Involved in Spatial Root Response to Mechanical Constrains
title_full Network-Based Analysis to Identify Hub Genes Involved in Spatial Root Response to Mechanical Constrains
title_fullStr Network-Based Analysis to Identify Hub Genes Involved in Spatial Root Response to Mechanical Constrains
title_full_unstemmed Network-Based Analysis to Identify Hub Genes Involved in Spatial Root Response to Mechanical Constrains
title_short Network-Based Analysis to Identify Hub Genes Involved in Spatial Root Response to Mechanical Constrains
title_sort network-based analysis to identify hub genes involved in spatial root response to mechanical constrains
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9564363/
https://www.ncbi.nlm.nih.gov/pubmed/36231084
http://dx.doi.org/10.3390/cells11193121
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