Dataset Information

Plant stress RNA-seq Nexus: a stress-specific transcriptome database in plant cells.

ABSTRACT: BACKGROUND:Abiotic and biotic stresses severely affect the growth and reproduction of plants and crops. Determining the critical molecular mechanisms and cellular processes in response to stresses will provide biological insight for addressing both climate change and food crises. RNA sequencing (RNA-Seq) is a revolutionary tool that has been used extensively in plant stress research. However, no existing large-scale RNA-Seq database has been designed to provide information on the stress-specific differentially expressed transcripts that occur across diverse plant species and various stresses. RESULTS:We have constructed a comprehensive database, the plant stress RNA-Seq nexus (PSRN), which includes 12 plant species, 26 plant-stress RNA-Seq datasets, and 937 samples. All samples are assigned to 133 stress-specific subsets, which are constructed into 254 subset pairs, a comparison between selected two subsets, for stress-specific differentially expressed transcript identification. CONCLUSIONS:PSRN is an open resource for intuitive data exploration, providing expression profiles of coding-transcript/lncRNA and identifying which transcripts are differentially expressed between different stress-specific subsets, in order to support researchers generating new biological insights and hypotheses in molecular breeding or evolution. PSRN is freely available at http://syslab5.nchu.edu.tw/PSRN .

SUBMITTER: Li JR

PROVIDER: S-EPMC6307140 | biostudies-literature | 2018 Dec

REPOSITORIES: biostudies-literature

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Plant stress RNA-seq Nexus: a stress-specific transcriptome database in plant cells.

Li Jian-Rong JR Liu Chun-Chi CC Sun Chuan-Hu CH Chen Yu-Ting YT

BMC genomics 20181227 1

<h4>Background</h4>Abiotic and biotic stresses severely affect the growth and reproduction of plants and crops. Determining the critical molecular mechanisms and cellular processes in response to stresses will provide biological insight for addressing both climate change and food crises. RNA sequencing (RNA-Seq) is a revolutionary tool that has been used extensively in plant stress research. However, no existing large-scale RNA-Seq database has been designed to provide information on the stress- ...[more]

PMID: 30587128

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Project description:BackgroundThe 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.DescriptionAgriSeqDB ( 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.ConclusionPowered 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.

Project description:BACKGROUND:One of evolution's most important achievements is the development and radiation of multicellular organisms with different types of cells. Complex multicellularity has evolved several times in eukaryotes; yet, in most lineages, an investigation of its molecular background is considerably challenging since the transition occurred too far in the past and, in addition, these lineages evolved a large number of cell types. However, for volvocine green algae, such as Volvox carteri, multicellularity is a relatively recent innovation. Furthermore, V. carteri shows a complete division of labor between only two cell types - small, flagellated somatic cells and large, immotile reproductive cells. Thus, V. carteri provides a unique opportunity to study multicellularity and cellular differentiation at the molecular level. RESULTS:This study provides a whole transcriptome RNA-Seq analysis of separated cell types of the multicellular green alga V. carteri f. nagariensis to reveal cell type-specific components and functions. To this end, 246 million quality filtered reads were mapped to the genome and valid expression data were obtained for 93% of the 14,247 gene loci. In the subsequent search for protein domains with assigned molecular function, we identified 9435 previously classified domains in 44% of all gene loci. Furthermore, in 43% of all gene loci we identified 15,254 domains that are involved in biological processes. All identified domains were investigated regarding cell type-specific expression. Moreover, we provide further insight into the expression pattern of previously described gene families (e.g., pherophorin, extracellular matrix metalloprotease, and VARL families). Our results demonstrate an extensive compartmentalization of the transcriptome between cell types: More than half of all genes show a clear difference in expression between somatic and reproductive cells. CONCLUSIONS:This study constitutes the first transcriptome-wide RNA-Seq analysis of separated cell types of V. carteri focusing on gene expression. The high degree of differential expression indicates a strong differentiation of cell types despite the fact that V. carteri diverged relatively recently from its unicellular relatives. Our expression dataset and the bioinformatic analyses provide the opportunity to further investigate and understand the mechanisms of cell type-specific expression and its transcriptional regulation.

Dataset Information

Plant stress RNA-seq Nexus: a stress-specific transcriptome database in plant cells.

Publications

Plant stress RNA-seq Nexus: a stress-specific transcriptome database in plant cells.

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