ExpressAnalyst: a unified platform for RNA-seq analysis in non-model species
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA937748 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| Other | ||||
| SRR23593127_1.fastq.gz | Fastqsanger.gz | |||
| SRR23593127_2.fastq.gz | Fastqsanger.gz | |||
| SRR23593128_1.fastq.gz | Fastqsanger.gz | |||
| SRR23593128_2.fastq.gz | Fastqsanger.gz |
Items per page: 5 1 - 5 of 37 |
Similar Datasets
Project description:The increasing application of RNA-seq to study non-model species demands easy-to-use and efficient bioinformatics tools to help researchers quickly uncover biological and functional insights. We developed ExpressAnalyst (www.expressanalyst.ca), a web-based tool for processing, analyzing, and interpreting RNA-seq data from any eukaryotic species. ExpressAnalyst contains a series of modules that enable raw data processing and annotation of FASTQ files, and statistical and functional analysis of counts tables and gene lists. All modules are integrated with EcoOmicsDB, an ortholog database that enables comprehensive analysis for species without a reference transcriptome. By coupling ultra-fast read mapping algorithms with high-resolution ortholog databases through a user-friendly web interface, ExpressAnalyst enables researchers to obtain global expression profiles and gene-level insights from raw RNA-seq reads within 24 hours. Here, we present ExpressAnalyst and demonstrate its utility with a case study of RNA-seq data from multiple non-model salamander species, including two that do not have a reference transcriptome.
2023-04-27 | GSE225876 | GEO
Project description:The increasing application of RNA sequencing to study non-model species demands easy-to-use and efficient bioinformatics tools to help researchers quickly uncover biological and functional insights. We developed ExpressAnalyst ( www.expressanalyst.ca ), a web-based platform for processing, analyzing, and interpreting RNA-sequencing data from any eukaryotic species. ExpressAnalyst contains a series of modules that cover from processing and annotation of FASTQ files to statistical and functional analysis of count tables or gene lists. All modules are integrated with EcoOmicsDB, an ortholog database that enables comprehensive analysis for species without a reference transcriptome. By coupling ultra-fast read mapping algorithms with high-resolution ortholog databases through a user-friendly web interface, ExpressAnalyst allows researchers to obtain global expression profiles and gene-level insights from raw RNA-sequencing reads within 24 h. Here, we present ExpressAnalyst and demonstrate its utility with a case study of RNA-sequencing data from multiple non-model salamander species, including two that do not have a reference transcriptome.
| S-EPMC10209063 | biostudies-literature
Project description:The mechanism underlying the “unified model” of YTHDF proteins
| PRJNA828181 | ENA
Project description:A Unified Nanopore Platform for Direct Sequencing of Individual Full Length RNA Strands
| PRJNA598890 | ENA
Project description:A Unified Nanopore Platform for Direct Sequencing of Individual Full Length RNA Strands
| PRJNA598891 | ENA
Project description:Unified airway disease, including concurrent asthma and chronic rhinosinusitis (CRS), is a common, but poorly understood disorder with no curative treatment options. To establish a murine model of chronic unified eosinophilic airway inflammation, mice were challenged with Aspergillus niger, and sinonasal mucosa and lung tissue were evaluated by immunohistochemistry, flow cytometry and gene expression. Inhalation of A niger conidia resulted in a Th2-biased lung and sinus inflammation that typifies allergic asthma and CRS. Gene network and pathway analysis correlated with human disease with upregulation of the JAK-STAT and helper T cell pathways, but also less expected pathways governing the spliceosome, osteoclast differentiation, and coagulation pathways. Utilizing a specific inhibitor and gene-deficient mice, we demonstrate that STAT6 is required for mycosis induced sinus inflammation. These findings confirm the relevance of this new model and portend future studies that further extend our understanding of the immunopathologic basis of airway mycosis and unified airway disease.
2022-01-15 | GSE193519 | GEO
Project description:Molecular biology aims to understand the molecular basis of cellular responses, unravel dynamic regulatory networks, and model complex biological systems. However, these studies remain challenging in non-model species as a result of poor functional annotation of regulatory proteins, like kinases or phosphatases. To overcome this limitation, we developed a multi-layer neural network that annotates proteins by determining functionality directly from the protein sequence. We annotated the kinases and phosphatases in the non-model species, Glycine max (soybean), achieving a prediction sensitivity of up to 97%. To demonstrate the applicability, we used our functional annotations in combination with Bayesian network principles to predict signaling cascades using time series phosphoproteomics. We shed light on phosphorylation cascades in soybean seedlings upon cold treatment and identified Glyma.10G173000 (TOI5) and Glyma.19G007300 (TOT3) as key temperature response regulators in soybean. Importantly, the signaling cascade predictions do not rely upon known upstream kinases, kinase motifs, or protein interaction data, enabling de novo identification of kinase-substrate interactions. In addition to high accuracy and strong generalization, we showed that our functional prediction neural network is scalable to other model and non-model species, including Oryza sativa (rice), Zea mays (maize), Sorghum bicolor (sorghum), and Triticum aestivum (wheat). Overall, we demonstrated a data-driven systems biology approach for non-model species leveraging our predicted upstream kinases and phosphatases.
2023-06-13 | PXD037601 | Pride
Project description:A unified model for the surveillance of translation in diverse noncoding sequences
| PRJNA860573 | ENA
Project description:As part of the EcoToxChip project, 49 distinct exposure studies were conducted on three lab model species (Japanese quail, fathead minnow, African clawed frog) and three ecologically relevant species (double crested cormorant, rainbow trout, northern leopard frog), at multiple life stages (embryo, adult), exposed to eight chemicals of environmental concern (ethinyl estradiol-EE2, hexabromocyclododecane-HBCD, lead-Pb, selenomethionine-SeMe, 17β trenbolone-TB, chlorpyrifos-CPF, fluoxetine-FLX, and benzo [a] pyrene-BaP. Whole transcriptome analyses were conducted on these samples resulting in a rich RNA seq dataset covering various species, life stages and chemicals, which is one of the largest purposeful complications of RNA seq data within ecotoxicology. Recently, a unified bioinformatics platform of relevance to ecotoxicology, EcoOmicsAnalyst and ExpressAnalyst, was developed to facilitate RNA Seq analysis of non-model species lacking a reference transcriptome. The platform uses the Seq2Fun algorithm to map RNA-seq reads from eukaryotic species to an ortholog database comprised of protein sequences from >600 eukaryotic species (EcoOmicsDB) with a translated search. The availability of these tools presents a unique opportunity to examine the EcoToxChip RNA Seq dataset for cross species comparisons. This work shows the potential of the EcoOmicsAnalyst and Seq2Fun platform to facilitate fast and simple analysis of RNA Seq datasets from non-model organisms with unannotated genomes and conduct comparative transcriptomic analysis across various species and life stages for cross-species extrapolation.
2023-12-05 | GSE239776 | GEO