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AgriSeqDB: an online RNA-Seq database for functional studies of agriculturally relevant plant species
BACKGROUND: The genome-wide expression profile of genes in different tissues/cell types and developmental stages is a vital component of many functional genomic studies. Transcriptome data obtained by RNA-sequencing (RNA-Seq) is often deposited in public databases that are made available via data po...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6146512/ https://www.ncbi.nlm.nih.gov/pubmed/30231853 http://dx.doi.org/10.1186/s12870-018-1406-2 |
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author | Robinson, Andrew J. Tamiru, Muluneh Salby, Rachel Bolitho, Clayton Williams, Andrew Huggard, Simon Fisch, Eva Unsworth, Kathryn Whelan, James Lewsey, Mathew G. |
author_facet | Robinson, Andrew J. Tamiru, Muluneh Salby, Rachel Bolitho, Clayton Williams, Andrew Huggard, Simon Fisch, Eva Unsworth, Kathryn Whelan, James Lewsey, Mathew G. |
author_sort | Robinson, Andrew J. |
collection | PubMed |
description | BACKGROUND: The genome-wide expression profile of genes in different tissues/cell types and developmental stages is a vital component of many functional genomic studies. Transcriptome data obtained by RNA-sequencing (RNA-Seq) is often deposited in public databases that are made available via data portals. Data visualization is one of the first steps in assessment and hypothesis generation. However, these databases do not typically include visualization tools and establishing one is not trivial for users who are not computational experts. This, as well as the various formats in which data is commonly deposited, makes the processes of data access, sharing and utility more difficult. Our goal was to provide a simple and user-friendly repository that meets these needs for data-sets from major agricultural crops. DESCRIPTION: AgriSeqDB (https://expression.latrobe.edu.au/agriseqdb) is a database for viewing, analysing and interpreting developmental and tissue/cell-specific transcriptome data from several species, including major agricultural crops such as wheat, rice, maize, barley and tomato. The disparate manner in which public transcriptome data is often warehoused and the challenge of visualizing raw data are both major hurdles to data reuse. The popular eFP browser does an excellent job of presenting transcriptome data in an easily interpretable view, but previous implementation has been mostly on a case-by-case basis. Here we present an integrated visualisation database of transcriptome data-sets from six species that did not previously have public-facing visualisations. We combine the eFP browser, for gene-by-gene investigation, with the Degust browser, which enables visualisation of all transcripts across multiple samples. The two visualisation interfaces launch from the same point, enabling users to easily switch between analysis modes. The tools allow users, even those without bioinformatics expertise, to mine into data-sets and understand the behaviour of transcripts of interest across samples and time. We have also incorporated an additional graphic download option to simplify incorporation into presentations or publications. CONCLUSION: Powered by eFP and Degust browsers, AgriSeqDB is a quick and easy-to-use platform for data analysis and visualization in five crops and Arabidopsis. Furthermore, it provides a tool that makes it easy for researchers to share their data-sets, promoting research collaborations and data-set reuse. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12870-018-1406-2) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-6146512 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-61465122018-09-24 AgriSeqDB: an online RNA-Seq database for functional studies of agriculturally relevant plant species Robinson, Andrew J. Tamiru, Muluneh Salby, Rachel Bolitho, Clayton Williams, Andrew Huggard, Simon Fisch, Eva Unsworth, Kathryn Whelan, James Lewsey, Mathew G. BMC Plant Biol Database BACKGROUND: The genome-wide expression profile of genes in different tissues/cell types and developmental stages is a vital component of many functional genomic studies. Transcriptome data obtained by RNA-sequencing (RNA-Seq) is often deposited in public databases that are made available via data portals. Data visualization is one of the first steps in assessment and hypothesis generation. However, these databases do not typically include visualization tools and establishing one is not trivial for users who are not computational experts. This, as well as the various formats in which data is commonly deposited, makes the processes of data access, sharing and utility more difficult. Our goal was to provide a simple and user-friendly repository that meets these needs for data-sets from major agricultural crops. DESCRIPTION: AgriSeqDB (https://expression.latrobe.edu.au/agriseqdb) is a database for viewing, analysing and interpreting developmental and tissue/cell-specific transcriptome data from several species, including major agricultural crops such as wheat, rice, maize, barley and tomato. The disparate manner in which public transcriptome data is often warehoused and the challenge of visualizing raw data are both major hurdles to data reuse. The popular eFP browser does an excellent job of presenting transcriptome data in an easily interpretable view, but previous implementation has been mostly on a case-by-case basis. Here we present an integrated visualisation database of transcriptome data-sets from six species that did not previously have public-facing visualisations. We combine the eFP browser, for gene-by-gene investigation, with the Degust browser, which enables visualisation of all transcripts across multiple samples. The two visualisation interfaces launch from the same point, enabling users to easily switch between analysis modes. The tools allow users, even those without bioinformatics expertise, to mine into data-sets and understand the behaviour of transcripts of interest across samples and time. We have also incorporated an additional graphic download option to simplify incorporation into presentations or publications. CONCLUSION: Powered by eFP and Degust browsers, AgriSeqDB is a quick and easy-to-use platform for data analysis and visualization in five crops and Arabidopsis. Furthermore, it provides a tool that makes it easy for researchers to share their data-sets, promoting research collaborations and data-set reuse. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12870-018-1406-2) contains supplementary material, which is available to authorized users. BioMed Central 2018-09-19 /pmc/articles/PMC6146512/ /pubmed/30231853 http://dx.doi.org/10.1186/s12870-018-1406-2 Text en © The Author(s). 2018 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
spellingShingle | Database Robinson, Andrew J. Tamiru, Muluneh Salby, Rachel Bolitho, Clayton Williams, Andrew Huggard, Simon Fisch, Eva Unsworth, Kathryn Whelan, James Lewsey, Mathew G. AgriSeqDB: an online RNA-Seq database for functional studies of agriculturally relevant plant species |
title | AgriSeqDB: an online RNA-Seq database for functional studies of agriculturally relevant plant species |
title_full | AgriSeqDB: an online RNA-Seq database for functional studies of agriculturally relevant plant species |
title_fullStr | AgriSeqDB: an online RNA-Seq database for functional studies of agriculturally relevant plant species |
title_full_unstemmed | AgriSeqDB: an online RNA-Seq database for functional studies of agriculturally relevant plant species |
title_short | AgriSeqDB: an online RNA-Seq database for functional studies of agriculturally relevant plant species |
title_sort | agriseqdb: an online rna-seq database for functional studies of agriculturally relevant plant species |
topic | Database |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6146512/ https://www.ncbi.nlm.nih.gov/pubmed/30231853 http://dx.doi.org/10.1186/s12870-018-1406-2 |
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