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Network Analysis of Gene Transcriptions of Arabidopsis thaliana in Spaceflight Microgravity
The transcriptomic datasets of the plant model organism Arabidopsis thaliana grown in the International Space Station provided by GeneLab have been mined to isolate the impact of spaceflight microgravity on gene expressions related to root growth. A set of computational tools is used to identify the...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7996555/ https://www.ncbi.nlm.nih.gov/pubmed/33668919 http://dx.doi.org/10.3390/genes12030337 |
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author | Manian, Vidya Orozco, Jairo Gangapuram, Harshini Janwa, Heeralal Agrinsoni, Carlos |
author_facet | Manian, Vidya Orozco, Jairo Gangapuram, Harshini Janwa, Heeralal Agrinsoni, Carlos |
author_sort | Manian, Vidya |
collection | PubMed |
description | The transcriptomic datasets of the plant model organism Arabidopsis thaliana grown in the International Space Station provided by GeneLab have been mined to isolate the impact of spaceflight microgravity on gene expressions related to root growth. A set of computational tools is used to identify the hub genes that respond differently in spaceflight with controlled lighting compared to on the ground. These computational tools based on graph-theoretic approaches are used to infer gene regulatory networks from the transcriptomic datasets. The three main algorithms used for network analyses are Least Absolute Shrinkage and Selection Operator (LASSO), Pearson correlation, and the Hyperlink-Induced Topic Search (HITS) algorithm. Graph-based spectral analyses reveal distinct properties of the spaceflight microgravity networks for the Wassilewskija (WS), Columbia (Col)-0, and mutant phytochromeD (phyD) ecotypes. The set of hub genes that are significantly altered in spaceflight microgravity are mainly involved in cell wall synthesis, protein transport, response to auxin, stress responses, and catabolic processes. Network analysis highlights five important root growth-regulating hub genes that have the highest outdegree distribution in spaceflight microgravity networks. These concerned genes coding for proteins are identified from the Gene Regulatory Networks (GRNs) corresponding to spaceflight total light environment. Furthermore, network analysis uncovers genes that encode nucleotide-diphospho-sugar interconversion enzymes that have higher transcriptional regulation in spaceflight microgravity and are involved in cell wall biosynthesis. |
format | Online Article Text |
id | pubmed-7996555 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-79965552021-03-27 Network Analysis of Gene Transcriptions of Arabidopsis thaliana in Spaceflight Microgravity Manian, Vidya Orozco, Jairo Gangapuram, Harshini Janwa, Heeralal Agrinsoni, Carlos Genes (Basel) Article The transcriptomic datasets of the plant model organism Arabidopsis thaliana grown in the International Space Station provided by GeneLab have been mined to isolate the impact of spaceflight microgravity on gene expressions related to root growth. A set of computational tools is used to identify the hub genes that respond differently in spaceflight with controlled lighting compared to on the ground. These computational tools based on graph-theoretic approaches are used to infer gene regulatory networks from the transcriptomic datasets. The three main algorithms used for network analyses are Least Absolute Shrinkage and Selection Operator (LASSO), Pearson correlation, and the Hyperlink-Induced Topic Search (HITS) algorithm. Graph-based spectral analyses reveal distinct properties of the spaceflight microgravity networks for the Wassilewskija (WS), Columbia (Col)-0, and mutant phytochromeD (phyD) ecotypes. The set of hub genes that are significantly altered in spaceflight microgravity are mainly involved in cell wall synthesis, protein transport, response to auxin, stress responses, and catabolic processes. Network analysis highlights five important root growth-regulating hub genes that have the highest outdegree distribution in spaceflight microgravity networks. These concerned genes coding for proteins are identified from the Gene Regulatory Networks (GRNs) corresponding to spaceflight total light environment. Furthermore, network analysis uncovers genes that encode nucleotide-diphospho-sugar interconversion enzymes that have higher transcriptional regulation in spaceflight microgravity and are involved in cell wall biosynthesis. MDPI 2021-02-25 /pmc/articles/PMC7996555/ /pubmed/33668919 http://dx.doi.org/10.3390/genes12030337 Text en © 2021 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 (http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) ). |
spellingShingle | Article Manian, Vidya Orozco, Jairo Gangapuram, Harshini Janwa, Heeralal Agrinsoni, Carlos Network Analysis of Gene Transcriptions of Arabidopsis thaliana in Spaceflight Microgravity |
title | Network Analysis of Gene Transcriptions of Arabidopsis thaliana in Spaceflight Microgravity |
title_full | Network Analysis of Gene Transcriptions of Arabidopsis thaliana in Spaceflight Microgravity |
title_fullStr | Network Analysis of Gene Transcriptions of Arabidopsis thaliana in Spaceflight Microgravity |
title_full_unstemmed | Network Analysis of Gene Transcriptions of Arabidopsis thaliana in Spaceflight Microgravity |
title_short | Network Analysis of Gene Transcriptions of Arabidopsis thaliana in Spaceflight Microgravity |
title_sort | network analysis of gene transcriptions of arabidopsis thaliana in spaceflight microgravity |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7996555/ https://www.ncbi.nlm.nih.gov/pubmed/33668919 http://dx.doi.org/10.3390/genes12030337 |
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