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Exploiting plant transcriptomic databases: Resources, tools, and approaches

There are now more than 300 000 RNA sequencing samples available, stemming from thousands of experiments capturing gene expression in organs, tissues, developmental stages, and experimental treatments for hundreds of plant species. The expression data have great value, as they can be re-analyzed by...

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Detalles Bibliográficos
Autores principales: Lim, Peng Ken, Zheng, Xinghai, Goh, Jong Ching, Mutwil, Marek
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9284291/
https://www.ncbi.nlm.nih.gov/pubmed/35605200
http://dx.doi.org/10.1016/j.xplc.2022.100323
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author Lim, Peng Ken
Zheng, Xinghai
Goh, Jong Ching
Mutwil, Marek
author_facet Lim, Peng Ken
Zheng, Xinghai
Goh, Jong Ching
Mutwil, Marek
author_sort Lim, Peng Ken
collection PubMed
description There are now more than 300 000 RNA sequencing samples available, stemming from thousands of experiments capturing gene expression in organs, tissues, developmental stages, and experimental treatments for hundreds of plant species. The expression data have great value, as they can be re-analyzed by others to ask and answer questions that go beyond the aims of the study that generated the data. Because gene expression provides essential clues to where and when a gene is active, the data provide powerful tools for predicting gene function, and comparative analyses allow us to study plant evolution from a new perspective. This review describes how we can gain new knowledge from gene expression profiles, expression specificities, co-expression networks, differential gene expression, and experiment correlation. We also introduce and demonstrate databases that provide user-friendly access to these tools.
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spelling pubmed-92842912022-07-16 Exploiting plant transcriptomic databases: Resources, tools, and approaches Lim, Peng Ken Zheng, Xinghai Goh, Jong Ching Mutwil, Marek Plant Commun Review Article There are now more than 300 000 RNA sequencing samples available, stemming from thousands of experiments capturing gene expression in organs, tissues, developmental stages, and experimental treatments for hundreds of plant species. The expression data have great value, as they can be re-analyzed by others to ask and answer questions that go beyond the aims of the study that generated the data. Because gene expression provides essential clues to where and when a gene is active, the data provide powerful tools for predicting gene function, and comparative analyses allow us to study plant evolution from a new perspective. This review describes how we can gain new knowledge from gene expression profiles, expression specificities, co-expression networks, differential gene expression, and experiment correlation. We also introduce and demonstrate databases that provide user-friendly access to these tools. Elsevier 2022-04-09 /pmc/articles/PMC9284291/ /pubmed/35605200 http://dx.doi.org/10.1016/j.xplc.2022.100323 Text en © 2022 The Author(s) https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
spellingShingle Review Article
Lim, Peng Ken
Zheng, Xinghai
Goh, Jong Ching
Mutwil, Marek
Exploiting plant transcriptomic databases: Resources, tools, and approaches
title Exploiting plant transcriptomic databases: Resources, tools, and approaches
title_full Exploiting plant transcriptomic databases: Resources, tools, and approaches
title_fullStr Exploiting plant transcriptomic databases: Resources, tools, and approaches
title_full_unstemmed Exploiting plant transcriptomic databases: Resources, tools, and approaches
title_short Exploiting plant transcriptomic databases: Resources, tools, and approaches
title_sort exploiting plant transcriptomic databases: resources, tools, and approaches
topic Review Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9284291/
https://www.ncbi.nlm.nih.gov/pubmed/35605200
http://dx.doi.org/10.1016/j.xplc.2022.100323
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