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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| Format: | Article |
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MDPI AG
2022-10-01
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| Series: | Cells |
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| Online Access: | https://www.mdpi.com/2073-4409/11/19/3121 |
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| author | Anastazija Dimitrova Gabriella Sferra Gabriella Stefania Scippa Dalila Trupiano |
| author_facet | Anastazija Dimitrova Gabriella Sferra Gabriella Stefania Scippa Dalila Trupiano |
| author_sort | Anastazija Dimitrova |
| collection | DOAJ |
| 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<sup>2+</sup> (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. |
| first_indexed | 2024-03-09T21:53:13Z |
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| institution | Directory Open Access Journal |
| issn | 2073-4409 |
| language | English |
| last_indexed | 2024-03-09T21:53:13Z |
| publishDate | 2022-10-01 |
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| record_format | Article |
| series | Cells |
| spelling | doaj.art-d72d8d488c9d44f38e64cdb265d38bd22023-11-23T20:03:11ZengMDPI AGCells2073-44092022-10-011119312110.3390/cells11193121Network-Based Analysis to Identify Hub Genes Involved in Spatial Root Response to Mechanical ConstrainsAnastazija Dimitrova0Gabriella Sferra1Gabriella Stefania Scippa2Dalila Trupiano3Department of Biosciences and Territory, University of Molise, 86090 Pesche, ItalyDepartment of Biosciences and Territory, University of Molise, 86090 Pesche, ItalyDepartment of Biosciences and Territory, University of Molise, 86090 Pesche, ItalyDepartment of Biosciences and Territory, University of Molise, 86090 Pesche, ItalyPrevious 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<sup>2+</sup> (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.https://www.mdpi.com/2073-4409/11/19/3121poplarfunctional enrichment analysisproteomicsbendinggene ontologiesclusters |
| spellingShingle | Anastazija Dimitrova Gabriella Sferra Gabriella Stefania Scippa Dalila Trupiano Network-Based Analysis to Identify Hub Genes Involved in Spatial Root Response to Mechanical Constrains Cells poplar functional enrichment analysis proteomics bending gene ontologies clusters |
| 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 | poplar functional enrichment analysis proteomics bending gene ontologies clusters |
| url | https://www.mdpi.com/2073-4409/11/19/3121 |
| work_keys_str_mv | AT anastazijadimitrova networkbasedanalysistoidentifyhubgenesinvolvedinspatialrootresponsetomechanicalconstrains AT gabriellasferra networkbasedanalysistoidentifyhubgenesinvolvedinspatialrootresponsetomechanicalconstrains AT gabriellastefaniascippa networkbasedanalysistoidentifyhubgenesinvolvedinspatialrootresponsetomechanicalconstrains AT dalilatrupiano networkbasedanalysistoidentifyhubgenesinvolvedinspatialrootresponsetomechanicalconstrains |