Abstract:Abstract. Several classes of exclusively -or at least predominantly -unspliced non-coding RNAs have been described in the last years, including totally and partially intronic transcripts and long intergenic RNAs. Functionally, they appear to be involved in regulating gene expression, at least in part by associating with the chromatin. Here we systematically analyze the distribution of unspliced ESTs in the human genome. Most appear in clusters overlapping or in the close vicinity of annotated RefSeq genes. Par… Show more
“…We focus on ESTs rather than NGS data here primarily because the much longer EST sequences are largely mapped unambiguously to the genome and are much more likely to contain splice junctions when they originate from spliced transcripts than the much shorted NGS reads. We update and extend previous investigations in the human uEST data [ 24 , 61 ] and in particular provide a first overview of the similarities and differences of the situation in human and mouse.…”
Section: Introductionsupporting
confidence: 64%
“…The number of reported TINs has increased by a factor of 6.8, while the known PINs increased only by about 10 %, suggesting that the coverage of TINs is much farther from saturation than that of the PINs. While [ 24 ] and our previous study [ 61 ] were concerned with the human transcriptome only, we consider here a comparable data set for the mouse ( Mus musculus ). Fig.…”
BackgroundDespite their abundance, unspliced EST data have received little attention as a source of information on non-coding RNAs. Very little is know, therefore, about the genomic distribution of unspliced non-coding transcripts and their relationship with the much better studied regularly spliced products. In particular, their evolution has remained virtually unstudied.ResultsWe systematically study the evidence on unspliced transcripts available in EST annotation tracks for human and mouse, comprising 104,980 and 66,109 unspliced EST clusters, respectively. Roughly one third of these are located totally inside introns of known genes (TINs) and another third overlaps exonic regions (PINs). Eleven percent are “intergenic”, far away from any annotated gene. Direct evidence for the independent transcription of many PINs and TINs is obtained from CAGE tag and chromatin data. We predict more than 2000 3’UTR-associated RNA candidates for each human and mouse. Fifteen to twenty percent of the unspliced EST cluster are conserved between human and mouse. With the exception of TINs, the sequences of unspliced EST clusters evolve significantly slower than genomic background. Furthermore, like spliced lincRNAs, they show highly tissue-specific expression patterns.ConclusionsUnspliced long non-coding RNAs are an important, rapidly evolving, component of mammalian transcriptomes. Their analysis is complicated by their preferential association with complex transcribed loci that usually also harbor a plethora of spliced transcripts. Unspliced EST data, although typically disregarded in transcriptome analysis, can be used to gain insights into this rarely investigated transcriptome component. The frequently postulated connection between lack of splicing and nuclear retention and the surprising overlap of chromatin-associated transcripts suggests that this class of transcripts might be involved in chromatin organization and possibly other mechanisms of epigenetic control.Electronic supplementary materialThe online version of this article (doi:10.1186/s12862-015-0437-7) contains supplementary material, which is available to authorized users.
“…We focus on ESTs rather than NGS data here primarily because the much longer EST sequences are largely mapped unambiguously to the genome and are much more likely to contain splice junctions when they originate from spliced transcripts than the much shorted NGS reads. We update and extend previous investigations in the human uEST data [ 24 , 61 ] and in particular provide a first overview of the similarities and differences of the situation in human and mouse.…”
Section: Introductionsupporting
confidence: 64%
“…The number of reported TINs has increased by a factor of 6.8, while the known PINs increased only by about 10 %, suggesting that the coverage of TINs is much farther from saturation than that of the PINs. While [ 24 ] and our previous study [ 61 ] were concerned with the human transcriptome only, we consider here a comparable data set for the mouse ( Mus musculus ). Fig.…”
BackgroundDespite their abundance, unspliced EST data have received little attention as a source of information on non-coding RNAs. Very little is know, therefore, about the genomic distribution of unspliced non-coding transcripts and their relationship with the much better studied regularly spliced products. In particular, their evolution has remained virtually unstudied.ResultsWe systematically study the evidence on unspliced transcripts available in EST annotation tracks for human and mouse, comprising 104,980 and 66,109 unspliced EST clusters, respectively. Roughly one third of these are located totally inside introns of known genes (TINs) and another third overlaps exonic regions (PINs). Eleven percent are “intergenic”, far away from any annotated gene. Direct evidence for the independent transcription of many PINs and TINs is obtained from CAGE tag and chromatin data. We predict more than 2000 3’UTR-associated RNA candidates for each human and mouse. Fifteen to twenty percent of the unspliced EST cluster are conserved between human and mouse. With the exception of TINs, the sequences of unspliced EST clusters evolve significantly slower than genomic background. Furthermore, like spliced lincRNAs, they show highly tissue-specific expression patterns.ConclusionsUnspliced long non-coding RNAs are an important, rapidly evolving, component of mammalian transcriptomes. Their analysis is complicated by their preferential association with complex transcribed loci that usually also harbor a plethora of spliced transcripts. Unspliced EST data, although typically disregarded in transcriptome analysis, can be used to gain insights into this rarely investigated transcriptome component. The frequently postulated connection between lack of splicing and nuclear retention and the surprising overlap of chromatin-associated transcripts suggests that this class of transcripts might be involved in chromatin organization and possibly other mechanisms of epigenetic control.Electronic supplementary materialThe online version of this article (doi:10.1186/s12862-015-0437-7) contains supplementary material, which is available to authorized users.
“…ANRASSF1 is one of the thousands of unspliced lncRNAs, named TIN and PIN RNAs, transcribed from the intronic regions of 74% of the protein-coding genes in the human genome [22], [41]. The formation of an RNA/DNA hybrid at the transcription locus could result in a highly location-specific effect for a number of these unspliced intronic lncRNAs.…”
The down-regulation of the tumor-suppressor gene RASSF1A has been shown to increase cell proliferation in several tumors. RASSF1A expression is regulated through epigenetic events involving the polycomb repressive complex 2 (PRC2); however, the molecular mechanisms modulating the recruitment of this epigenetic modifier to the RASSF1 locus remain largely unknown. Here, we identify and characterize ANRASSF1, an endogenous unspliced long noncoding RNA (lncRNA) that is transcribed from the opposite strand on the RASSF1 gene locus in several cell lines and tissues and binds PRC2. ANRASSF1 is transcribed through RNA polymerase II and is 5′-capped and polyadenylated; it exhibits nuclear localization and has a shorter half-life compared with other lncRNAs that bind PRC2. ANRASSF1 endogenous expression is higher in breast and prostate tumor cell lines compared with non-tumor, and an opposite pattern is observed for RASSF1A. ANRASSF1 ectopic overexpression reduces RASSF1A abundance and increases the proliferation of HeLa cells, whereas ANRASSF1 silencing causes the opposite effects. These changes in ANRASSF1 levels do not affect the RASSF1C isoform abundance. ANRASSF1 overexpression causes a marked increase in both PRC2 occupancy and histone H3K27me3 repressive marks, specifically at the RASSF1A promoter region. No effect of ANRASSF1 overexpression was detected on PRC2 occupancy and histone H3K27me3 at the promoter regions of RASSF1C and the four other neighboring genes, including two well-characterized tumor suppressor genes. Additionally, we demonstrated that ANRASSF1 forms an RNA/DNA hybrid and recruits PRC2 to the RASSF1A promoter. Together, these results demonstrate a novel mechanism of epigenetic repression of the RASSF1A tumor suppressor gene involving antisense unspliced lncRNA, in which ANRASSF1 selectively represses the expression of the RASSF1 isoform overlapping the antisense transcript in a location-specific manner. In a broader perspective, our findings suggest that other non-characterized unspliced intronic lncRNAs transcribed in the human genome might contribute to a location-specific epigenetic modulation of genes.
“…TINs make up the majority (~70%) of all non-coding (non-rRNA) nuclear-encoded RNA and 40–50% of all cellular (non-rRNA) RNAs by mass, as established by single-molecule sequencing [50]. Evidence that large numbers of introns encode standalone RNAs originally came from microarray expression profiling [49, 51] and in silico analysis of expressed sequence tag (EST) databases [49, 52]. Even genomes as compact as those of human viruses can encode functional intronic RNAs [53].…”
Section: Criteria and Features Of Existing Classes And Categories Of mentioning
Advances in the depth and quality of transcriptome sequencing have revealed many new classes of long non-coding RNAs (lncRNAs). lncRNA classification has mushroomed to accommodate these new findings, even though the real dimensions and complexity of the non-coding transcriptome remain unknown. Although evidence of functionality of specific lncRNAs continues to accumulate, conflicting, confusing, and overlapping terminology has fostered ambiguity and lack of clarity in the field in general. The lack of fundamental conceptual un-ambiguous classification framework results in a number of challenges in the annotation and interpretation of non-coding transcriptome data. It also might undermine integration of the new genomic methods and datasets in an effort to unravel function of lncRNA. Here, we review existing lncRNA classifications, nomenclature, and terminology. Then we describe the conceptual guidelines that have emerged for their classification and functional annotation based on expanding and more comprehensive use of large systems biology-based datasets.
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