Evolutionary analysis across mammals reveals distinct classes of long noncoding RNAs
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ABSTRACT:
PROVIDER: PRJNA271946 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR1747440.fastq.gz | Fastqsanger.gz | |||
| SRR1747440_1.fastq.gz | Fastqsanger.gz | |||
| SRR1747440_2.fastq.gz | Fastqsanger.gz | |||
| SRR1747441_1.fastq.gz | Fastqsanger.gz | |||
| SRR1747441_2.fastq.gz | Fastqsanger.gz |
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Project description:Recent advances in transcriptome sequencing have enabled the discovery of thousands of long non-coding RNAs (lncRNAs) across many species. Though several lncRNAs have been shown to play important roles in diverse biological processes, the functions and mechanisms of most lncRNAs remain unknown. Two significant obstacles lie between transcriptome sequencing and functional characterization of lncRNAs: identifying truly non-coding genes from de novo reconstructed transcriptomes, and prioritizing the hundreds of resulting putative lncRNAs for downstream experimental interrogation. We present slncky, a computational lncRNA discovery tool that produces a high-quality set of lncRNAs from RNA-sequencing data and further uses evolutionary constraint to prioritize lncRNAs that are likely to be functionally important. Our automated filtering pipeline is comparable to manual curation efforts and more sensitive than previously published computational approaches. Furthermore, we develop a sensitive alignment pipeline for aligning lncRNA loci and propose new evolutionary metrics relevant for analyzing sequence and transcript evolution. Our analysis reveals that evolutionary selection acts in several distinct patterns, and uncovers two notable classes of intergenic lncRNAs: one showing strong purifying selection on RNA sequence and another where constraint is restricted to the regulation but not the sequence of the transcript.
2016-01-07 | GSE64818 | GEO
Project description:Recent advances in transcriptome sequencing have enabled the discovery of thousands of long non-coding RNAs (lncRNAs) across many species. Though several lncRNAs have been shown to play important roles in diverse biological processes, the functions and mechanisms of most lncRNAs remain unknown. Two significant obstacles lie between transcriptome sequencing and functional characterization of lncRNAs: identifying truly non-coding genes from de novo reconstructed transcriptomes, and prioritizing the hundreds of resulting putative lncRNAs for downstream experimental interrogation. We present slncky, a computational lncRNA discovery tool that produces a high-quality set of lncRNAs from RNA-sequencing data and further uses evolutionary constraint to prioritize lncRNAs that are likely to be functionally important. Our automated filtering pipeline is comparable to manual curation efforts and more sensitive than previously published computational approaches. Furthermore, we develop a sensitive alignment pipeline for aligning lncRNA loci and propose new evolutionary metrics relevant for analyzing sequence and transcript evolution. Our analysis reveals that evolutionary selection acts in several distinct patterns, and uncovers two notable classes of intergenic lncRNAs: one showing strong purifying selection on RNA sequence and another where constraint is restricted to the regulation but not the sequence of the transcript. To study a comprehensive and comparable set of lncRNAs expressed in the pluripotent state, we analyzed RNA-Seq data from pluripotent cells derived from several strains and species, and grown in two physiological conditions. First we derived ânaïveâ ES cells (ESCs) from each of three different mice strains: 129SvEv, NOD, and Mus musculus castaneus (cast) mouse, a wild mouse subspecies originally from Thailand, as well as naïve induced pluripotent stem (iPS) cells from rat and human. Next, to facilitate comparisons across pluripotent cells from different species, we also cultured mouse and rat cells in âprimedâ epiblast stem cell (EpiSC) culture conditions, since human iPS cells in culture are much more similar molecularly and functionally to mouse primed EpiSCs rather than to a ground state naïve ESCs. We polyA selected RNA from each cell type and deeply sequenced on HiSeq2500
2016-01-07 | E-GEOD-64818 | biostudies-arrayexpress
Project description:BackgroundRecent advances in transcriptome sequencing have enabled the discovery of thousands of long non-coding RNAs (lncRNAs) across many species. Though several lncRNAs have been shown to play important roles in diverse biological processes, the functions and mechanisms of most lncRNAs remain unknown. Two significant obstacles lie between transcriptome sequencing and functional characterization of lncRNAs: identifying truly non-coding genes from de novo reconstructed transcriptomes, and prioritizing the hundreds of resulting putative lncRNAs for downstream experimental interrogation.ResultsWe present slncky, a lncRNA discovery tool that produces a high-quality set of lncRNAs from RNA-sequencing data and further uses evolutionary constraint to prioritize lncRNAs that are likely to be functionally important. Our automated filtering pipeline is comparable to manual curation efforts and more sensitive than previously published computational approaches. Furthermore, we developed a sensitive alignment pipeline for aligning lncRNA loci and propose new evolutionary metrics relevant for analyzing sequence and transcript evolution. Our analysis reveals that evolutionary selection acts in several distinct patterns, and uncovers two notable classes of intergenic lncRNAs: one showing strong purifying selection on RNA sequence and another where constraint is restricted to the regulation but not the sequence of the transcript.ConclusionOur results highlight that lncRNAs are not a homogenous class of molecules but rather a mixture of multiple functional classes with distinct biological mechanism and/or roles. Our novel comparative methods for lncRNAs reveals 233 constrained lncRNAs out of tens of thousands of currently annotated transcripts, which we make available through the slncky Evolution Browser.
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Project description:NAP-seq Reveals Novel Classes of Structured Noncoding RNAs with Regulatory Functions
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Project description:Purpose:Up to 80% of the human genome produces “dark matter” RNAs, most of which are noncapped RNAs (napRNAs). However, determining the functional impacts and metabolism of napRNAs requires the identification of their full-length sequences. Method:Here, by developing a novel method, NAP-seq, to globally profile the full-length sequences of napRNAs at single-nucleotide resolution, we revealed several novel classes of exceptionally structured noncoding RNAs (ncRNAs). Results:We discovered stably expressed linear intron RNAs (sliRNAs), a novel class of snoRNA-intron RNAs (snotrons), a new class of RNAs embedded in miRNA spacers (misRNAs) and thousands of new structured ncRNAs in humans and mice. These new napRNAs undergo dynamic changes in response to various stimuli and differentiation stages. Importantly, we showed that the novel napRNA DINAP interacts with dyskerin pseudouridine synthase 1 (DKC1) to promote cell proliferation by maintaining DKC1 protein stability. Conclusion:Our approach establishes a paradigm for discovering novel classes of ncRNAs with regulatory potency.
2024-02-19 | GSE192632 | GEO
Project description:The origin and stability of germline noncoding RNAs remain largely uncharacterized in mammals. Here, we demonstrate that the vast majority of pachytene piRNAs originate from less than 100 bi- and unidirectionally transcribed loci in the mouse genome. These loci show features characteristic of transcribed protein-coding genes, including primary transcription by RNA polymerase II, H3K4 trimethylation marking the transcription initiation site, and H3K36 trimethylation present at elongation regions in a highly tissue-specific manner. We identified MYBL1, a spermatocyte-enriched transcription factor, as a potential driver of piRNA precursor transcripts. By similarly mapping piRNA clusters in testes of dog and opossum, we revealed that the regulatory architectures generating piRNAs appear to be highly conserved in mammals. Finally, we discovered that apparently neutral chromosomal rearrangements in evolution can act as an unexpected mechanism to generate novel piRNA clusters in diverse mammals. Thus, our results demonstrate how an integrated, multi-species approach can help define the genomic features and evolutionary mechanisms underlying mammalian germline noncoding RNAs.
2015-09-01 | E-MTAB-1265 | biostudies-arrayexpress
Project description:Long intergenic noncoding RNAs (lincRNAs) play diverse regulatory roles in human development and disease, but little is known about their evolutionary history and constraint. Here, we characterize human lincRNA expression patterns in nine tissues across six mammalian species and multiple individuals. Of the 1898 human lincRNAs expressed in these tissues, we find orthologous transcripts for 80% in chimpanzee, 63% in rhesus, 39% in cow, 38% in mouse, and 35% in rat. Mammalian-expressed lincRNAs show remarkably strong conservation of tissue specificity, suggesting that it is selectively maintained. In contrast, abundant splice-site turnover suggests that exact splice sites are not critical. Relative to evolutionarily young lincRNAs, mammalian-expressed lincRNAs show higher primary sequence conservation in their promoters and exons, increased proximity to protein-coding genes enriched for tissue-specific functions, fewer repeat elements, and more frequent single-exon transcripts. Remarkably, we find that ?20% of human lincRNAs are not expressed beyond chimpanzee and are undetectable even in rhesus. These hominid-specific lincRNAs are more tissue specific, enriched for testis, and faster evolving within the human lineage.
| S-EPMC3975061 | biostudies-literature
Project description:Chromatin signatures at transcriptional start sites separate two equally populated yet distinct classes of intergenic long noncoding RNAs
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Project description:Principles of 3D chromosome folding and evolutionary genome reshuffling in mammals
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Project description:1. Evaluate the diagnostic value of long noncoding RNA (CCAT1) expression by RT-PCR in peripheral blood in colorectal cancer patients versus normal healthy control personal.
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4. Compare long noncoding RNA (CCAT1) expression with traditional marker; carcinoembryonic antigen (CEA) and Carbohydrate antigen 19-9 (CA19-9) in diagnosis of colorectal cancer.
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