Transcription profiling by high throughput sequencing of long non-coding RNAs across multiple rodent species
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Project description:To test the conservation and evolution of long non-coding RNAs across multiple rodent species by transcriptome sequencing and histone modification mapping. Part of experiment series: E-MTAB-867 RNA-Seq, E-MTAB-959 ChIP-Seq.
2012-11-06 | E-MTAB-867 | biostudies-arrayexpress
Project description:To test the conservation and evolution of long non-coding RNAs across multiple rodent species by transcriptome sequencing and histone modification mapping. Part of experiment series: E-MTAB-867 RNA-Seq, E-MTAB-959 ChIP-Seq.
2012-04-01 | E-MTAB-959 | biostudies-arrayexpress
Project description:Long non-coding RNAs (lncRNAs) are defined as non-protein-coding transcripts that are at least 200 nucleotides long. They are known to play pivotal roles in regulating gene expression, especially during stress responses in plants. We used a large collection of in-house transcriptome data from various soybean (Glycine max and Glycine soja) tissues treated under different conditions to perform a comprehensive identification of soybean lncRNAs. We also retrieved publicly available soybean transcriptome data that were of sufficient quality and sequencing depth to enrich our analysis. In total, RNA-seq data of 332 samples were used for this analysis. An integrated reference-based, de novo transcript assembly was developed that identified ~69,000 lncRNA gene loci. We showed that lncRNAs are distinct from both protein-coding transcripts and genomic background noise in terms of length, number of exons, transposable element composition, and sequence conservation level across legume species. The tissue-specific and time-specific transcriptional responses of the lncRNA genes under some stress conditions may suggest their biological relevance. The transcription start sites of lncRNA gene loci tend to be close to their nearest protein-coding genes, and they may be transcriptionally related to the protein-coding genes, particularly for antisense and intronic lncRNAs. A previously unreported subset of small peptide-coding transcripts was identified from these lncRNA loci via tandem mass spectrometry, which paved the way for investigating their functional roles. Our results also highlight the current inadequacy of the bioinformatic definition of lncRNA, which excludes those lncRNA gene loci with small open reading frames (ORFs) from being regarded as protein-coding.
2020-01-09 | PXD014553 | Pride
Project description:Leishmania major is a kinetoplastid protozoan parasite which causes the debilitating infectious disease cutaneous leishmaniasis (CL). This disease results in scars and disfiguration of the infected individuals. The L. major genome was the first leishmanial genome to be sequenced in 2005 and this study resulted in the identification of 8,300 protein coding genes. This landmark study paved the way for further sequencing of other leishmanial parasites (L. infantum, L. braziliensis and L. donovani). A recent study provided the glimpse of the global transcriptome of L. major promastigotes. This study identified 1,884 uniquely expressed non-coding RNAs (ncRNA) in L. major. Additionally, we had previously mapped the global proteome of L. major promastigote using a proteogenomic approach which resulted in identification of 3,613 proteins in L. major promastigotes which covered 43% of its proteome. In the present study, we have carried out extensive analysis of the 1,884 novel ncRNAs using a proteogenomic approach to identify their protein coding potential. Our analysis resulted in identification of 10 novel protein coding genes based on peptide data and additional hundreds of proteins coding genes based on homology searches of previously classified ncRNA genes. We have analyzed each of these novel protein coding genes and in the process have improved the genome annotation of L. major on the basis of mass spectrometry derived peptide data and also based on homology.
2016-05-11 | PXD002465 | Pride
Project description: Not available
| S-EPMC6779387 | biostudies-literature
Project description:Dorsal root ganglion (DRG) neurons provide connectivity between peripheral tissues and spinal cord. Transcriptional plasticity within DRG sensory neurons after peripheral nerve injury contributes to nerve repair but also leads to maladaptive plasticity, including the development of neuropathic pain. This study presents tissue and neuron specific expression profiling of both known and novel Long Non-Coding RNAs (LncRNAs) in rodent DRG following nerve injury. We have identified a large number of novel LncRNAs expressed within rodent DRG, a minority of which were syntenically conserved between mouse and rat and which including both- intergenic and antisense LncRNAs. We have also identified neuron type-specific LncRNAs in mouse DRG, and LncRNAs that are expressed in human IPS cell-derived sensory neurons. We show significant plasticity in LncRNA expression following nerve injury, which in mouse is strain dependant. This resource is publicly available and will aid future studies of DRG neuron identity and the transcriptional landscape in both naïve and injured DRG.
2017-11-21 | GSE107180 | GEO
Project description:Long non-coding RNAs (lncRNAs) form a new class of RNA molecules implicated in various aspects of protein coding gene expression regulation. To study lncRNAs in cancer, we generated expression profiles for 1708 human lncRNAs in the NCI60 cancer cell line panel using a high-throughput nanowell RT-qPCR platform. We describe how qPCR assays were designed and validated and provide processed and normalized expression data for further analysis. Data quality is demonstrated by matching the lncRNA expression profiles with phenotypic and genomic characteristics of the cancer cell lines. This data set can be integrated with publicly available omics and pharmacological data sets to uncover novel associations between lncRNA expression and mRNA expression, miRNA expression, DNA copy number, protein coding gene mutation status or drug response. lncRNA expression profiling of 60 cancer cell lines
2016-06-29 | E-GEOD-80332 | biostudies-arrayexpress
Project description:The dual functional lncRNAs have been intensively studied and identified to be involved in various fundamental cellular processes recently. It is essential to understand in which context when a dual functional lncRNA serves as a non-coding RNA or a template for coding peptide, particularly in some pathological conditions. However, apart from time consuming and cell type specific experiments, there is virtually no in-silico method for predicting the identity of dual functional lncRNAs. Here, we developed a deep-learning model with multi-head self-attention mechanism, LncReader, to identify dual functional lncRNAs based on their sequence, physicochemical and secondary structural features. Our data demonstrated that LncReader showed multiple advantage compared to various classical machine learning methods. Moreover, to obtain independent in-house datasets for robust testing, mass spectrometry proteomics combined with RNA-seq were applied in four leukemia cell lines. Remarkably, LncReader achieved the best performance among all these datasets. Therefore, LncReader provides a sophisticated and practical tool that enables fast dual functional lncRNAs identification.
2023-04-26 | PXD030066 | Pride
Project description:Interventions: Case series:No
Primary outcome(s): long non-coding Ribonucleic Acid
Study Design: Sequential
| 2725570 | ecrin-mdr-crc
Project description:Multiple myeloma (MM) is a malignant proliferation of bone marrow plasma cells (PCs) characterized by highly heterogeneous genetic background and clinical course, and whose pathogenesis remains largely unknown. Long ncRNAs (lncRNAs) are a large class of non-protein-coding RNA, involved in many physiological cellular and genomic processes as well as in carcinogenesis, cancer metastasis and invasion. Although still in its infancy, the knowledge of the role of lncRNAs in MM is progressively expanding. Besides studies on selected candidates, lncRNAs expression at genome-wide transcriptome level is confined to microarray technologies, thus investigating a limited collection of transcripts. Herein, we assessed the lncRNAs expression profiling by RNA-sequencing in a cohort of 30 MM patients, aimed at defining a comprehensive catalogue of lncRNAs specifically associated with the main MM molecular subgroups and genetic alterations. We identified 391 deregulated lncRNAs, 67% of which were also detectable and validated by whole-transcript microarrays. In addition, we identified a list of lncRNAs, with potential relevance in MM, co-expressed and in close proximity to genes that might undergo a cis-regulatory relationship.
2018-06-05 | GSE109342 | GEO