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PlantExp: a platform for exploration of gene expression and alternative splicing based on public plant RNA-seq samples

Over the last decade, RNA-seq has produced a massive amount of plant transcriptomic sequencing data deposited in public databases. Reanalysis of these public datasets can generate additional novel hypotheses not included in original studies. However, the large data volume and the requirement for spe...

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Autores principales: Liu, Jinding, Zhang, Yaru, Zheng, Yiqing, Zhu, Yali, Shi, Yapin, Guan, Zhuoran, Lang, Kun, Shen, Danyu, Huang, Wen, Dou, Daolong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9825497/
https://www.ncbi.nlm.nih.gov/pubmed/36271793
http://dx.doi.org/10.1093/nar/gkac917
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author Liu, Jinding
Zhang, Yaru
Zheng, Yiqing
Zhu, Yali
Shi, Yapin
Guan, Zhuoran
Lang, Kun
Shen, Danyu
Huang, Wen
Dou, Daolong
author_facet Liu, Jinding
Zhang, Yaru
Zheng, Yiqing
Zhu, Yali
Shi, Yapin
Guan, Zhuoran
Lang, Kun
Shen, Danyu
Huang, Wen
Dou, Daolong
author_sort Liu, Jinding
collection PubMed
description Over the last decade, RNA-seq has produced a massive amount of plant transcriptomic sequencing data deposited in public databases. Reanalysis of these public datasets can generate additional novel hypotheses not included in original studies. However, the large data volume and the requirement for specialized computational resources and expertise present a barrier for experimental biologists to explore public repositories. Here, we introduce PlantExp (https://biotec.njau.edu.cn/plantExp), a database platform for exploration of plant gene expression and alternative splicing profiles based on 131 423 uniformly processed publicly available RNA-seq samples from 85 species in 24 plant orders. In addition to two common retrieval accesses to gene expression and alternative splicing profiles by functional terms and sequence similarity, PlantExp is equipped with four online analysis tools, including differential expression analysis, specific expression analysis, co-expression network analysis and cross-species expression conservation analysis. With these online analysis tools, users can flexibly customize sample groups to reanalyze public RNA-seq datasets and obtain new insights. Furthermore, it offers a wide range of visualization tools to help users intuitively understand analysis results. In conclusion, PlantExp provides a valuable data resource and analysis platform for plant biologists to utilize public RNA-seq. datasets.
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spelling pubmed-98254972023-01-10 PlantExp: a platform for exploration of gene expression and alternative splicing based on public plant RNA-seq samples Liu, Jinding Zhang, Yaru Zheng, Yiqing Zhu, Yali Shi, Yapin Guan, Zhuoran Lang, Kun Shen, Danyu Huang, Wen Dou, Daolong Nucleic Acids Res Database Issue Over the last decade, RNA-seq has produced a massive amount of plant transcriptomic sequencing data deposited in public databases. Reanalysis of these public datasets can generate additional novel hypotheses not included in original studies. However, the large data volume and the requirement for specialized computational resources and expertise present a barrier for experimental biologists to explore public repositories. Here, we introduce PlantExp (https://biotec.njau.edu.cn/plantExp), a database platform for exploration of plant gene expression and alternative splicing profiles based on 131 423 uniformly processed publicly available RNA-seq samples from 85 species in 24 plant orders. In addition to two common retrieval accesses to gene expression and alternative splicing profiles by functional terms and sequence similarity, PlantExp is equipped with four online analysis tools, including differential expression analysis, specific expression analysis, co-expression network analysis and cross-species expression conservation analysis. With these online analysis tools, users can flexibly customize sample groups to reanalyze public RNA-seq datasets and obtain new insights. Furthermore, it offers a wide range of visualization tools to help users intuitively understand analysis results. In conclusion, PlantExp provides a valuable data resource and analysis platform for plant biologists to utilize public RNA-seq. datasets. Oxford University Press 2022-10-22 /pmc/articles/PMC9825497/ /pubmed/36271793 http://dx.doi.org/10.1093/nar/gkac917 Text en © The Author(s) 2022. Published by Oxford University Press on behalf of Nucleic Acids Research. https://creativecommons.org/licenses/by-nc/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial License (https://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com
spellingShingle Database Issue
Liu, Jinding
Zhang, Yaru
Zheng, Yiqing
Zhu, Yali
Shi, Yapin
Guan, Zhuoran
Lang, Kun
Shen, Danyu
Huang, Wen
Dou, Daolong
PlantExp: a platform for exploration of gene expression and alternative splicing based on public plant RNA-seq samples
title PlantExp: a platform for exploration of gene expression and alternative splicing based on public plant RNA-seq samples
title_full PlantExp: a platform for exploration of gene expression and alternative splicing based on public plant RNA-seq samples
title_fullStr PlantExp: a platform for exploration of gene expression and alternative splicing based on public plant RNA-seq samples
title_full_unstemmed PlantExp: a platform for exploration of gene expression and alternative splicing based on public plant RNA-seq samples
title_short PlantExp: a platform for exploration of gene expression and alternative splicing based on public plant RNA-seq samples
title_sort plantexp: a platform for exploration of gene expression and alternative splicing based on public plant rna-seq samples
topic Database Issue
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9825497/
https://www.ncbi.nlm.nih.gov/pubmed/36271793
http://dx.doi.org/10.1093/nar/gkac917
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