Project description:We sequenced 188 tissue samples comprising 35 organ types retrieved from six humans. To demonstrate evolutionary conservation we sequenced in addition 58 samples from 6 tissues of mice.
Project description:The human transcriptome consists of various RNA biotypes including multiple types of non-coding RNAs (ncRNAs). Current ncRNA compendia remain incomplete partially because they are almost exclusively derived from the interrogation of small- and polyadenylated RNAs. Here, we present a more comprehensive atlas of the human transcriptome that is derived from matching polyA-, total-, and small-RNA profiles of a heterogenous collection of nearly 300 human tissues and cell lines. We report thousands of novel RNA species across all major RNA biotypes, including a hitherto poorly-cataloged class of non-polyadenylated single-exon long non-coding RNAs. In addition, we exploit intron abundance estimates from total RNA-sequencing to predict the regulatory potential of various non-coding RNAs. Our study represents a substantial expansion of the current catalogue of human ncRNAs and their regulatory interactions. All data and results are accessible through the R2 webtool and serve as a basis to further explore RNA biology and function.
Project description:Genetic and epigenetic regulations, mostly driven by small non-coding RNAs, play a crucial role to define genetic programming in plant biology and development. In this work, we focus on miRNAs, the most representative class of small RNAs, to present the first comprehensive miRNA expression atlas in Vitis vinifera L. Our atlas gives a clear picture of miRNA regulation and homeostasis in the whole plant during its lifecycle. We analyzed 68 small RNA libraries, which were prepared from a rich and diverse number of tissues (13) harvested on different developmental stages. We identified 110 known miRNAs and annotated 176 novel, some of which belonging to known families and others completely new. We found that very few miRNAs may be defined as tissue specific. However, interestingly, in the stamen 22 miRNAs were found highly specific. Most of the identified miRNAs show low expression levels, whereas, 32 miRNAs are present in all tissues and mainly highly expressed. Additionally, in each organ, the different developmental stages share 30—70% of miRNAs and their modulation leads the regulation of plant development. We also present a target prediction analysis and suggest a first functional description of hundreds of miRNAs. Our findings represent the most complete expression atlas for grapevine and any other woody species, paving the ground for future functional studies. Genome-wide small RNA profiling was done by Illumina TruSeq sample preparation and Illumina Small RNA Sample Prep kit followed by high-throughput sequencing with Illumina HiSeq 2000 and GA IIx Illumina Sequencer platforms for 13 different organs/tissues of grapevine in different developmental stages, with two replicates each, comprising a total of 70 samples
Project description:Small non-coding RNA profiling of urine exosomal total RNA from patients with or without prostate cancer were performed using Affymetrix GeneChip miRNA 4.0 to identify small non-coding RNA profile that can be used for prostate cancer diagnosis.
Project description:Small non-coding RNA profiling of urine exosomal total RNA from patients with or without prostate cancer were performed using Affymetrix miRNA Gene-Chip 4.0 to identify small non-coding RNA proflie that can be used for prostate cancer diagnosis.
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.
Project description:The role of non-coding RNAs in different biological processes and diseases is continuously expanding. Next-generation sequencing together with the parallel improvement of bioinformatics analyses allows the accurate detection and quantification of an increasing number of RNA species. With the aim of exploring new potential biomarkers for disease classification, a clear overview of the expression levels of common/unique small RNA species among different biospecimens is necessary. However, except for miRNAs in plasma, there are no substantial indications about the pattern of expression of various small RNAs in multiple specimens among healthy humans. Overall, the data reported hereby provide an insight of the constitution of the human miRNome and other small non-coding RNAs in various specimens of healthy individuals. This dataset was submitted by the Extracellular RNA Atlas (http://exrna-atlas.org/exat/datasets/EXR-ANACC1S6lJ1C-AN), and the selected raw and processed data for this dataset corresponds to what is available in that resource. Submitter indicates: "The publication associated with the citation below refers to a slightly larger set of samples (includes cervical scrape samples) and contains an alternative analysis to the processed data files provided here."