Non-coding yet non-trivial: a review on the computational genomics of lincRNAs
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paper_title: Pervasive Transcription of the Human Genome Produces Thousands of Previously Unidentified Long Intergenic Noncoding RNAs

paper_content:

Known protein coding gene exons compose less than 3% of the human genome. The remaining 97% is largely uncharted territory, with only a small fraction characterized. The recent observation of transcription in this intergenic territory has stimulated debate about the extent of intergenic transcription and whether these intergenic RNAs are functional. Here we directly observed with a large set of RNA-seq data covering a wide array of human tissue types that the majority of the genome is indeed transcribed, corroborating recent observations by the ENCODE project. Furthermore, using de novo transcriptome assembly of this RNA-seq data, we found that intergenic regions encode far more long intergenic noncoding RNAs (lincRNAs) than previously described, helping to resolve the discrepancy between the vast amount of observed intergenic transcription and the limited number of previously known lincRNAs. In total, we identified tens of thousands of putative lincRNAs expressed at a minimum of one copy per cell, significantly expanding upon prior lincRNA annotation sets. These lincRNAs are specifically regulated and conserved rather than being the product of transcriptional noise. In addition, lincRNAs are strongly enriched for trait-associated SNPs suggesting a new mechanism by which intergenic trait-associated regions may function. These findings will enable the discovery and interrogation of novel intergenic functional elements.
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paper_title: Multiple evidence strands suggest that there may be as few as 19 000 human protein-coding genes

paper_content:

Determining the full complement of protein-coding genes is a key goal of genome annotation. The most powerful approach for confirming protein-coding potential is the detection of cellular protein expression through peptide mass spectrometry (MS) experiments. Here, we mapped peptides detected in seven large-scale proteomics studies to almost 60% of the protein-coding genes in the GENCODE annotation of the human genome. We found a strong relationship between detection in proteomics experiments and both gene family age and cross-species conservation. Most of the genes for which we detected peptides were highly conserved. We found peptides for >96% of genes that evolved before bilateria. At the opposite end of the scale, we identified almost no peptides for genes that have appeared since primates, for genes that did not have any protein-like features or for genes with poor cross-species conservation. These results motivated us to describe a set of 2001 potential non-coding genes based on features such as weak conservation, a lack of protein features, or ambiguous annotations from major databases, all of which correlated with low peptide detection across the seven experiments. We identified peptides for just 3% of these genes. We show that many of these genes behave more like non-coding genes than protein-coding genes and suggest that most are unlikely to code for proteins under normal circumstances. We believe that their inclusion in the human protein-coding gene catalogue should be revised as part of the ongoing human genome annotation effort.
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paper_title: Many human large intergenic noncoding RNAs associate with chromatin-modifying complexes and affect gene expression

paper_content:

We recently showed that the mammalian genome encodes >1,000 large intergenic noncoding (linc)RNAs that are clearly conserved across mammals and, thus, functional. Gene expression patterns have implicated these lincRNAs in diverse biological processes, including cell-cycle regulation, immune surveillance, and embryonic stem cell pluripotency. However, the mechanism by which these lincRNAs function is unknown. Here, we expand the catalog of human lincRNAs to ≈3,300 by analyzing chromatin-state maps of various human cell types. Inspired by the observation that the well-characterized lincRNA HOTAIR binds the polycomb repressive complex (PRC)2, we tested whether many lincRNAs are physically associated with PRC2. Remarkably, we observe that ≈20% of lincRNAs expressed in various cell types are bound by PRC2, and that additional lincRNAs are bound by other chromatin-modifying complexes. Also, we show that siRNA-mediated depletion of certain lincRNAs associated with PRC2 leads to changes in gene expression, and that the up-regulated genes are enriched for those normally silenced by PRC2. We propose a model in which some lincRNAs guide chromatin-modifying complexes to specific genomic loci to regulate gene expression.
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paper_title: Multiple knockout mouse models reveal lincRNAs are required for life and brain development

paper_content:

The mammalian genome is comprised of DNA sequences that contain the templates for proteins, and other DNA sequences that do not code for proteins. The coding DNA sequences are transcribed to make messenger RNA molecules, which are then translated to make proteins. Researchers have known for many years that some of the noncoding DNA sequences are also transcribed to make other types of RNA molecules, such as transfer and ribosomal RNA. However, the true breadth and diversity of the roles played by these other RNA molecules have only recently begun to be fully appreciated. Mammalian genomes contain thousands of noncoding DNA sequences that are transcribed. Recent in vitro studies suggest that the resulting long noncoding RNA molecules can act as regulators of transcription, translation, and cell cycle. In vitro studies also suggest that these long noncoding RNA molecules may play a role in mammalian development and disease. Yet few in vivo studies have been performed to support or confirm such hypotheses. Now Sauvageau et al. have developed several lines of knockout mice to investigate a subset of noncoding RNA molecules known as long intergenic noncoding RNAs (lincRNAs). These experiments reveal that lincRNAs have a strong influence on the overall viability of mice, and also on a number of developmental processes, including the development of lungs and the cerebral cortex. Given that the vast majority of the human genome is transcribed, the mouse models developed by Sauvageau et al. represent an important step in determining the physiological relevance, on a genetic level, of the noncoding portion of the genome in vivo.
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paper_title: lincRNAs: Genomics, Evolution, and Mechanisms

paper_content:

Long intervening noncoding RNAs (lincRNAs) are transcribed from thousands of loci in mammalian genomes and might play widespread roles in gene regulation and other cellular processes. This Review outlines the emerging understanding of lincRNAs in vertebrate animals, with emphases on how they are being identified and current conclusions and questions regarding their genomics, evolution and mechanisms of action.
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paper_title: The landscape of long noncoding RNAs in the human transcriptome

paper_content:

Arul Chinnaiyan and colleagues report the curation of 7,256 RNA sequencing libraries from tumors, normal tissues and cell lines. They find 58,648 lncRNAs, of which 79% are previously unnannotated.
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paper_title: Ab initio reconstruction of cell type–specific transcriptomes in mouse reveals the conserved multi-exonic structure of lincRNAs

paper_content:

High-throughput sequencing of total cellular RNA by RNA-Seq promises rapid reconstruction of spliced transcripts in a cell population. Guttman et al. accomplish this using only paired-end RNA-seq data and an unannotated genome sequence, and apply the method to better define many new, conserved long intergenic noncoding RNAs (lincRNAs).
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paper_title: A global map for dissecting phenotypic variants in human lincRNAs

paper_content:

Large intergenic noncoding RNAs (lincRNAs) are emerging as key factors of multiple cellular processes. Cumulative evidence has linked lincRNA polymorphisms to diverse diseases. However, the global properties of lincRNA polymorphisms and their implications for human disease remain largely unknown. Here we performed a systematic analysis of naturally occurring variants in human lincRNAs, with a particular focus on lincRNA polymorphism as novel risk factor of disease etiology. We found that lincRNAs exhibited a relatively low level of polymorphisms, and low single-nucleotide polymorphism (SNP) density lincRNAs might have a broad range of functions. We also found that some polymorphisms in evolutionarily conserved regions of lincRNAs had significant effects on predicted RNA secondary structures, indicating their potential contribution to diseases. We mapped currently available phenotype-associated SNPs to lincRNAs and found that lincRNAs were associated with a wide range of human diseases. Some lincRNAs could be responsible for particular diseases. Our results provided not only a global perspective on genetic variants in human lincRNAs but also novel insights into the function and etiology of lincRNA. All the data in this study can be accessed and retrieved freely via a web server at http://bioinfo.hrbmu.edu.cn/lincPoly.
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paper_title: Overexpression of long noncoding RNA PCAT-1 is a novel biomarker of poor prognosis in patients with colorectal cancer

paper_content:

Long noncoding RNAs (lncRNA) are emerging as key molecules in human cancer. Prostate cancer–associated ncRNA transcripts 1 (PCAT-1), a lncRNA, has been recently revealed involving in human prostate cancer progression. However, whether PCAT-1 could serve as novel biomarker to predict prognosis in colorectal cancer (CRC) or not is unknown. We therefore carried out the present study to explore the correlation between PCAT-1 expression and the progression of CRC. In this study, the expression of PCAT-1 in 108 cases of CRC tissues and matched 81 adjacent normal tissues were determined by quantitative real-time PCR. Furthermore, the copy number variation of PCAT-1 was also measured in 17 tumor tissues and matched normal tissues. Our results showed that PCAT-1 expression in CRC tissues was significantly upregulated compared with the matched normal tissues (p < 0.001) and the overexpression of PCAT-1(upregulated by more than 50 %) was found in 64 % (62/81) of CRC. Moreover, PCAT-1 gene copy number variation explains only a few percent of observed overexpression. In addition, there was a significant association between PCAT-1 expression and distant metastasis (p = 0.04), but not other clinical characteristics. More important, CRC patients with PCAT-1 higher expression have shown significantly poorer overall survival than those with lower PCAT-1 expression (p < 0.001). Also, multivariable Cox regression analysis identified PCAT-1 overexpression as an independent prognostic factor for CRC (p = 0.007, HR = 3.12 95 %CI = 1.355–7.185). In conclusion, our results suggest that high expression of PCAT-1 is involved in CRC progression and could be a novel biomarker of poor prognosis in patient with colorectal cancer.
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paper_title: Ribosome Profiling Provides Evidence that Large Noncoding RNAs Do Not Encode Proteins

paper_content:

Large noncoding RNAs are emerging as an important component in cellular regulation. Considerable evidence indicates that these transcripts act directly as functional RNAs rather than through an encoded protein product. However, a recent study of ribosome occupancy reported that many large intergenic ncRNAs (lincRNAs) are bound by ribosomes, raising the possibility that they are translated into proteins. Here, we show that classical noncoding RNAs and 5′ UTRs show the same ribosome occupancy as lincRNAs, demonstrating that ribosome occupancy alone is not sufficient to classify transcripts as coding or noncoding. Instead, we define a metric based on the known property of translation whereby translating ribosomes are released upon encountering a bona fide stop codon. We show that this metric accurately discriminates between protein-coding transcripts and all classes of known noncoding transcripts, including lincRNAs. Taken together, these results argue that the large majority of lincRNAs do not function through encoded proteins.
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paper_title: Targeted RNA sequencing reveals the deep complexity of the human transcriptome

paper_content:

Transcriptomic analyses have revealed an unexpected complexity to the human transcriptome, whose breadth and depth exceeds current RNA sequencing capability1, 2, 3, 4. Using tiling arrays to target and sequence select portions of the transcriptome, we identify and characterize unannotated transcripts whose rare or transient expression is below the detection limits of conventional sequencing approaches. We use the unprecedented depth of coverage afforded by this technique to reach the deepest limits of the human transcriptome, exposing widespread, regulated and remarkably complex noncoding transcription in intergenic regions, as well as unannotated exons and splicing patterns in even intensively studied protein-coding loci such as p53 and HOX. The data also show that intermittent sequenced reads observed in conventional RNA sequencing data sets, previously dismissed as noise, are in fact indicative of unassembled rare transcripts. Collectively, these results reveal the range, depth and complexity of a human transcriptome that is far from fully characterized.
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paper_title: Catalogues of mammalian long noncoding RNAs: modest conservation and incompleteness

paper_content:

BackgroundDespite increasing interest in the noncoding fraction of transcriptomes, the number, species-conservation and functions, if any, of many non-protein-coding transcripts remain to be discovered. Two extensive long intergenic noncoding RNA (ncRNA) transcript catalogues are now available for mouse: over 3,000 macroRNAs identified by cDNA sequencing, and 1,600 long intergenic noncoding RNA (lincRNA) intervals that are predicted from chromatin-state maps. Previously we showed that macroRNAs tend to be more highly conserved than putatively neutral sequence, although only 5% of bases are predicted as constrained. By contrast, over a thousand lincRNAs were reported as being highly conserved. This apparent difference may account for the surprisingly small fraction (11%) of transcripts that are represented in both catalogues. Here we sought to resolve the reported discrepancy between the evolutionary rates for these two sets.ResultsOur analyses reveal lincRNA and macroRNA exon sequences to be subject to the same relatively low degree of sequence constraint. Nonetheless, our observations are consistent with the functionality of a fraction of ncRNA in these sets, with up to a quarter of ncRNA exons having evolved significantly slower than neighboring neutral sequence. The more tissue-specific macroRNAs are enriched in predicted RNA secondary structures and thus may often act in trans, whereas the more highly and broadly expressed lincRNAs appear more likely to act in the cis-regulation of adjacent transcription factor genes.ConclusionsTaken together, our results indicate that each of the two ncRNA catalogues unevenly and lightly samples the true, much larger, ncRNA repertoire of the mouse.
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paper_title: Integrative annotation of human large intergenic noncoding RNAs reveals global properties and specific subclasses

paper_content:

Large intergenic noncoding RNAs (lincRNAs) are emerging as key regulators of diverse cellular processes. Determining the function of individual lincRNAs remains a challenge. Recent advances in RNA sequencing (RNA-seq) and computational methods allow for an unprecedented analysis of such transcripts. Here, we present an integrative approach to define a reference catalog of >8000 human lincRNAs. Our catalog unifies previously existing annotation sources with transcripts we assembled from RNA-seq data collected from ~4 billion RNA-seq reads across 24 tissues and cell types. We characterize each lincRNA by a panorama of >30 properties, including sequence, structural, transcriptional, and orthology features. We found that lincRNA expression is strikingly tissue-specific compared with coding genes, and that lincRNAs are typically coexpressed with their neighboring genes, albeit to an extent similar to that of pairs of neighboring protein-coding genes. We distinguish an additional subset of transcripts that have high evolutionary conservation but may include short ORFs and may serve as either lincRNAs or small peptides. Our integrated, comprehensive, yet conservative reference catalog of human lincRNAs reveals the global properties of lincRNAs and will facilitate experimental studies and further functional classification of these genes.
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paper_title: Genomewide characterization of non-polyadenylated RNAs

paper_content:

BackgroundRNAs can be physically classified into poly(A)+ or poly(A)- transcripts according to the presence or absence of a poly(A) tail at their 3' ends. Current deep sequencing approaches largely depend on the enrichment of transcripts with a poly(A) tail, and therefore offer little insight into the nature and expression of transcripts that lack poly(A) tails.ResultsWe have used deep sequencing to explore the repertoire of both poly(A)+ and poly(A)- RNAs from HeLa cells and H9 human embryonic stem cells (hESCs). Using stringent criteria, we found that while the majority of transcripts are poly(A)+, a significant portion of transcripts are either poly(A)- or bimorphic, being found in both the poly(A)+ and poly(A)- populations. Further analyses revealed that many mRNAs may not contain classical long poly(A) tails and such messages are overrepresented in specific functional categories. In addition, we surprisingly found that a few excised introns accumulate in cells and thus constitute a new class of non-polyadenylated long non-coding RNAs. Finally, we have identified a specific subset of poly(A)- histone mRNAs, including two histone H1 variants, that are expressed in undifferentiated hESCs and are rapidly diminished upon differentiation; further, these same histone genes are induced upon reprogramming of fibroblasts to induced pluripotent stem cells.ConclusionsWe offer a rich source of data that allows a deeper exploration of the poly(A)- landscape of the eukaryotic transcriptome. The approach we present here also applies to the analysis of the poly(A)- transcriptomes of other organisms.
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paper_title: Landscape of transcription in human cells

paper_content:

Eukaryotic cells make many types of primary and processed RNAs that are found either in specific subcellular compartments or throughout the cells. A complete catalogue of these RNAs is not yet available and their characteristic subcellular localizations are also poorly understood. Because RNA represents the direct output of the genetic information encoded by genomes and a significant proportion of a cell's regulatory capabilities are focused on its synthesis, processing, transport, modification and translation, the generation of such a catalogue is crucial for understanding genome function. Here we report evidence that three-quarters of the human genome is capable of being transcribed, as well as observations about the range and levels of expression, localization, processing fates, regulatory regions and modifications of almost all currently annotated and thousands of previously unannotated RNAs. These observations, taken together, prompt a redefinition of the concept of a gene.
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paper_title: The Antisense Transcriptomes of Human Cells

paper_content:

Transcription in mammalian cells can be assessed at a genome-wide level, but it has been difficult to reliably determine whether individual transcripts are derived from the plus or minus strands of chromosomes. This distinction can be critical for understanding the relationship between known transcripts (sense) and the complementary antisense transcripts that may regulate them. Here, we describe a technique that can be used to (i) identify the DNA strand of origin for any particular RNA transcript, and (ii) quantify the number of sense and antisense transcripts from expressed genes at a global level. We examined five different human cell types and in each case found evidence for antisense transcripts in 2900 to 6400 human genes. The distribution of antisense transcripts was distinct from that of sense transcripts, was nonrandom across the genome, and differed among cell types. Antisense transcripts thus appear to be a pervasive feature of human cells, which suggests that they are a fundamental component of gene regulation.
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paper_title: A Global Clustering Algorithm to Identify Long Intergenic Non-Coding RNA - with Applications in Mouse Macrophages

paper_content:

Identification of diffuse signals from the chromatin immunoprecipitation and high-throughput massively parallel sequencing (ChIP-Seq) technology poses significant computational challenges, and there are few methods currently available. We present a novel global clustering approach to enrich diffuse CHIP-Seq signals of RNA polymerase II and histone 3 lysine 4 trimethylation (H3K4Me3) and apply it to identify putative long intergenic non-coding RNAs (lincRNAs) in macrophage cells. Our global clustering method compares favorably to the local clustering method SICER that was also designed to identify diffuse CHIP-Seq signals. The validity of the algorithm is confirmed at several levels. First, 8 out of a total of 11 selected putative lincRNA regions in primary macrophages respond to lipopolysaccharides (LPS) treatment as predicted by our computational method. Second, the genes nearest to lincRNAs are enriched with biological functions related to metabolic processes under resting conditions but with developmental and immune-related functions under LPS treatment. Third, the putative lincRNAs have conserved promoters, modestly conserved exons, and expected secondary structures by prediction. Last, they are enriched with motifs of transcription factors such as PU.1 and AP.1, previously shown to be important lineage determining factors in macrophages, and 83% of them overlap with distal enhancers markers. In summary, GCLS based on RNA polymerase II and H3K4Me3 CHIP-Seq method can effectively detect putative lincRNAs that exhibit expected characteristics, as exemplified by macrophages in the study.
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paper_title: Conserved Function of lincRNAs in Vertebrate Embryonic Development despite Rapid Sequence Evolution

paper_content:

Thousands of long intervening noncoding RNAs (lincRNAs) have been identified in mammals. To better understand the evolution and functions of these enigmatic RNAs, we used chromatin marks, poly(A)-site mapping and RNA-Seq data to identify more than 550 distinct lincRNAs in zebrafish. Although these shared many characteristics with mammalian lincRNAs, only 29 had detectable sequence similarity with putative mammalian orthologs, typically restricted to a single short region of high conservation. Other lincRNAs had conserved genomic locations without detectable sequence conservation. Antisense reagents targeting conserved regions of two zebrafish lincRNAs caused developmental defects. Reagents targeting splice sites caused the same defects and were rescued by adding either the mature lincRNA or its human or mouse ortholog. Our study provides a roadmap for identification and analysis of lincRNAs in model organisms and shows that lincRNAs play crucial biological roles during embryonic development with functionality conserved despite limited sequence conservation.
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paper_title: Long noncoding intronic RNAs are differentially expressed in primary and metastatic pancreatic cancer

paper_content:

BackgroundPancreatic ductal adenocarcinoma (PDAC) is known by its aggressiveness and lack of effective therapeutic options. Thus, improvement in current knowledge of molecular changes associated with pancreatic cancer is urgently needed to explore novel venues of diagnostics and treatment of this dismal disease. While there is mounting evidence that long noncoding RNAs (lncRNAs) transcribed from intronic and intergenic regions of the human genome may play different roles in the regulation of gene expression in normal and cancer cells, their expression pattern and biological relevance in pancreatic cancer is currently unknown. In the present work we investigated the relative abundance of a collection of lncRNAs in patients' pancreatic tissue samples aiming at identifying gene expression profiles correlated to pancreatic cancer and metastasis.MethodsCustom 3,355-element spotted cDNA microarray interrogating protein-coding genes and putative lncRNA were used to obtain expression profiles from 38 clinical samples of tumor and non-tumor pancreatic tissues. Bioinformatics analyses were performed to characterize structure and conservation of lncRNAs expressed in pancreatic tissues, as well as to identify expression signatures correlated to tissue histology. Strand-specific reverse transcription followed by PCR and qRT-PCR were employed to determine strandedness of lncRNAs and to validate microarray results, respectively.ResultsWe show that subsets of intronic/intergenic lncRNAs are expressed across tumor and non-tumor pancreatic tissue samples. Enrichment of promoter-associated chromatin marks and over-representation of conserved DNA elements and stable secondary structure predictions suggest that these transcripts are generated from independent transcriptional units and that at least a fraction is under evolutionary selection, and thus potentially functional.Statistically significant expression signatures comprising protein-coding mRNAs and lncRNAs that correlate to PDAC or to pancreatic cancer metastasis were identified. Interestingly, loci harboring intronic lncRNAs differentially expressed in PDAC metastases were enriched in genes associated to the MAPK pathway. Orientation-specific RT-PCR documented that intronic transcripts are expressed in sense, antisense or both orientations relative to protein-coding mRNAs. Differential expression of a subset of intronic lncRNAs (PPP3CB, MAP3K14 and DAPK1 loci) in metastatic samples was confirmed by Real-Time PCR.ConclusionOur findings reveal sets of intronic lncRNAs expressed in pancreatic tissues whose abundance is correlated to PDAC or metastasis, thus pointing to the potential relevance of this class of transcripts in biological processes related to malignant transformation and metastasis in pancreatic cancer.
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paper_title: Chromatin signature reveals over a thousand highly conserved large non-coding RNAs in mammals

paper_content:

There is growing recognition that mammalian cells produce many thousands of large intergenic transcripts. However, the functional significance of these transcripts has been particularly controversial. Although there are some well-characterized examples, most (>95%) show little evidence of evolutionary conservation and have been suggested to represent transcriptional noise. Here we report a new approach to identifying large non-coding RNAs using chromatin-state maps to discover discrete transcriptional units intervening known protein-coding loci. Our approach identified ~1,600 large multi-exonic RNAs across four mouse cell types. In sharp contrast to previous collections, these large intervening non-coding RNAs (lincRNAs) show strong purifying selection in their genomic loci, exonic sequences and promoter regions, with greater than 95% showing clear evolutionary conservation. We also developed a functional genomics approach that assigns putative functions to each lincRNA, demonstrating a diverse range of roles for lincRNAs in processes from embryonic stem cell pluripotency to cell proliferation. We obtained independent functional validation for the predictions for over 100 lincRNAs, using cell-based assays. In particular, we demonstrate that specific lincRNAs are transcriptionally regulated by key transcription factors in these processes such as p53, NFκB, Sox2, Oct4 (also known as Pou5f1) and Nanog. Together, these results define a unique collection of functional lincRNAs that are highly conserved and implicated in diverse biological processes.
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paper_title: Many human large intergenic noncoding RNAs associate with chromatin-modifying complexes and affect gene expression

paper_content:

We recently showed that the mammalian genome encodes >1,000 large intergenic noncoding (linc)RNAs that are clearly conserved across mammals and, thus, functional. Gene expression patterns have implicated these lincRNAs in diverse biological processes, including cell-cycle regulation, immune surveillance, and embryonic stem cell pluripotency. However, the mechanism by which these lincRNAs function is unknown. Here, we expand the catalog of human lincRNAs to ≈3,300 by analyzing chromatin-state maps of various human cell types. Inspired by the observation that the well-characterized lincRNA HOTAIR binds the polycomb repressive complex (PRC)2, we tested whether many lincRNAs are physically associated with PRC2. Remarkably, we observe that ≈20% of lincRNAs expressed in various cell types are bound by PRC2, and that additional lincRNAs are bound by other chromatin-modifying complexes. Also, we show that siRNA-mediated depletion of certain lincRNAs associated with PRC2 leads to changes in gene expression, and that the up-regulated genes are enriched for those normally silenced by PRC2. We propose a model in which some lincRNAs guide chromatin-modifying complexes to specific genomic loci to regulate gene expression.
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paper_title: Comparison of CAGE and RNA-seq transcriptome profiling using clonally amplified and single-molecule next-generation sequencing.

paper_content:

CAGE (cap analysis gene expression) and RNA-seq are two major technologies used to identify transcript abundances as well as structures. They measure expression by sequencing from either the 5' end of capped molecules (CAGE) or tags randomly distributed along the length of a transcript (RNA-seq). Library protocols for clonally amplified (Illumina, SOLiD, 454 Life Sciences [Roche], Ion Torrent), second-generation sequencing platforms typically employ PCR preamplification prior to clonal amplification, while third-generation, single-molecule sequencers can sequence unamplified libraries. Although these transcriptome profiling platforms have been demonstrated to be individually reproducible, no systematic comparison has been carried out between them. Here we compare CAGE, using both second- and third-generation sequencers, and RNA-seq, using a second-generation sequencer based on a panel of RNA mixtures from two human cell lines to examine power in the discrimination of biological states, detection of differentially expressed genes, linearity of measurements, and quantification reproducibility. We found that the quantified levels of gene expression are largely comparable across platforms and conclude that CAGE and RNA-seq are complementary technologies that can be used to improve incomplete gene models. We also found systematic bias in the second- and third-generation platforms, which is likely due to steps such as linker ligation, cleavage by restriction enzymes, and PCR amplification. This study provides a perspective on the performance of these platforms, which will be a baseline in the design of further experiments to tackle complex transcriptomes uncovered in a wide range of cell types.
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paper_title: Integrative annotation of human large intergenic noncoding RNAs reveals global properties and specific subclasses

paper_content:

Large intergenic noncoding RNAs (lincRNAs) are emerging as key regulators of diverse cellular processes. Determining the function of individual lincRNAs remains a challenge. Recent advances in RNA sequencing (RNA-seq) and computational methods allow for an unprecedented analysis of such transcripts. Here, we present an integrative approach to define a reference catalog of >8000 human lincRNAs. Our catalog unifies previously existing annotation sources with transcripts we assembled from RNA-seq data collected from ~4 billion RNA-seq reads across 24 tissues and cell types. We characterize each lincRNA by a panorama of >30 properties, including sequence, structural, transcriptional, and orthology features. We found that lincRNA expression is strikingly tissue-specific compared with coding genes, and that lincRNAs are typically coexpressed with their neighboring genes, albeit to an extent similar to that of pairs of neighboring protein-coding genes. We distinguish an additional subset of transcripts that have high evolutionary conservation but may include short ORFs and may serve as either lincRNAs or small peptides. Our integrated, comprehensive, yet conservative reference catalog of human lincRNAs reveals the global properties of lincRNAs and will facilitate experimental studies and further functional classification of these genes.
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paper_title: Long noncoding RNA: an emerging paradigm of cancer research

paper_content:

Recent studies have demonstrated the importance of non-protein coding part of human genome in carcinogenesis and metastasis. Among numerous kinds of non-protein coding RNAs, long noncoding RNAs (lncRNAs) play a key regulatory role in cancer biology. LncRNAs are dysregulated in different kinds of cancer and the expression levels of certain lncRNAs are associated with recurrence, metastasis, and prognosis of cancer. It is also proved that overexpression of certain lncRNAs, behaving like oncogenes, can promote matrix invasion of cancer cells and tumor growth. In this review, we focus our attention on lncRNAs those have been validated in human cancer tissues to suggest reasonable strategies for future research. We introduce an update view of lncRNA, extract cancer-related lncRNAs from literature, and describe the known functions and possible underlying molecular mechanisms of some well investigated lncRNAs (MALAT1, HOX antisense intergenic RNA, and highly upregulated in hepatocellular cancer), as well as their current and potential future application in cancer diagnosis (PCA3) and treatment (H19).
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paper_title: The BLAST Sequence Analysis Tool

paper_content:

Summary The comparison of nucleotide or protein sequences from the same or different organisms is a very powerful tool in molecular biology. By finding similarities between sequences, scientists can infer the function of newly sequenced genes, predict new members of gene families, and explore evolutionary relationships. Now that whole genomes are being sequenced, sequence similarity searching can be used to predict the location and function of protein-coding and transcriptionregulation regions in genomic DNA. Basic Local Alignment Search Tool (BLAST) (1, 2) is the tool most frequently used for calculating sequence similarity. BLAST comes in variations for use with different query sequences against different databases. All BLAST applications, as well as information on which BLAST program to use and other help documentation, are listed on the BLAST homepage [http://www.ncbi. nlm.nih.gov/BLAST/]. This chapter will focus more on how BLAST works, its output, and how both the output and program itself can be further manipulated or customized, rather than on how to use BLAST [http://www.ncbi.nlm.nih.gov/Education/BLASTinfo/information3.html] or interpret BLAST results.
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paper_title: A Global Clustering Algorithm to Identify Long Intergenic Non-Coding RNA - with Applications in Mouse Macrophages

paper_content:

Identification of diffuse signals from the chromatin immunoprecipitation and high-throughput massively parallel sequencing (ChIP-Seq) technology poses significant computational challenges, and there are few methods currently available. We present a novel global clustering approach to enrich diffuse CHIP-Seq signals of RNA polymerase II and histone 3 lysine 4 trimethylation (H3K4Me3) and apply it to identify putative long intergenic non-coding RNAs (lincRNAs) in macrophage cells. Our global clustering method compares favorably to the local clustering method SICER that was also designed to identify diffuse CHIP-Seq signals. The validity of the algorithm is confirmed at several levels. First, 8 out of a total of 11 selected putative lincRNA regions in primary macrophages respond to lipopolysaccharides (LPS) treatment as predicted by our computational method. Second, the genes nearest to lincRNAs are enriched with biological functions related to metabolic processes under resting conditions but with developmental and immune-related functions under LPS treatment. Third, the putative lincRNAs have conserved promoters, modestly conserved exons, and expected secondary structures by prediction. Last, they are enriched with motifs of transcription factors such as PU.1 and AP.1, previously shown to be important lineage determining factors in macrophages, and 83% of them overlap with distal enhancers markers. In summary, GCLS based on RNA polymerase II and H3K4Me3 CHIP-Seq method can effectively detect putative lincRNAs that exhibit expected characteristics, as exemplified by macrophages in the study.
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paper_title: Evidence that functional transcription units cover at least half of the human genome.

paper_content:

Transcriptome analyses have revealed that a large proportion of the human genome is transcribed. However, many of these transcripts might be functionless. To distinguish functional transcription units (FTUs) from spurious transcripts, we searched for the hallmarks of selective pressure against mutations that impair transcription. We analyzed the distribution of transposable elements, which are counter selected within FTUs. We show that these features are sufficiently informative to predict whether a sequence is transcribed and, if transcribed, in which orientation. Our results indicate that FTUs constitute at least 50% of the genome and that approximately one-third of these transcripts apparently do not encode proteins.
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paper_title: The landscape of long noncoding RNAs in the human transcriptome

paper_content:

Arul Chinnaiyan and colleagues report the curation of 7,256 RNA sequencing libraries from tumors, normal tissues and cell lines. They find 58,648 lncRNAs, of which 79% are previously unnannotated.
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paper_title: CPC: assess the protein-coding potential of transcripts using sequence features and support vector machine

paper_content:

Recent transcriptome studies have revealed that a large number of transcripts in mammals and other organisms do not encode proteins but function as noncoding RNAs (ncRNAs) instead. As millions of transcripts are generated by large-scale cDNA and EST sequencing projects every year, there is a need for automatic methods to distinguish protein-coding RNAs from noncoding RNAs accurately and quickly. We developed a support vector machine-based classifier, named Coding Potential Calculator (CPC), to assess the protein-coding potential of a transcript based on six biologically meaningful sequence features. Tenfold cross-validation on the training dataset and further testing on several large datasets showed that CPC can discriminate coding from noncoding transcripts with high accuracy. Furthermore, CPC also runs an order-of-magnitude faster than a previous state-of-the-art tool and has higher accuracy. We developed a user-friendly web-based interface of CPC at http://cpc.cbi.pku.edu.cn. In addition to predicting the coding potential of the input transcripts, the CPC web server also graphically displays detailed sequence features and additional annotations of the transcript that may facilitate users’ further investigation.
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paper_title: Transcriptome sequencing across a prostate cancer cohort identifies PCAT-1, an unannotated lincRNA implicated in disease progression

paper_content:

Noncoding RNAs (ncRNAs) are emerging as key molecules in human cancer, with the potential to serve as novel markers of disease and to reveal uncharacterized aspects of tumor biology. Here we discover 121 unannotated prostate cancer–associated ncRNA transcripts (PCATs) by ab initio assembly of high-throughput sequencing of polyA+ RNA (RNA-Seq) from a cohort of 102 prostate tissues and cells lines. We characterized one ncRNA, PCAT-1, as a prostate-specific regulator of cell proliferation and show that it is a target of the Polycomb Repressive Complex 2 (PRC2). We further found that patterns of PCAT-1 and PRC2 expression stratified patient tissues into molecular subtypes distinguished by expression signatures of PCAT-1–repressed target genes. Taken together, our findings suggest that PCAT-1 is a transcriptional repressor implicated in a subset of prostate cancer patients. These findings establish the utility of RNA-Seq to identify disease-associated ncRNAs that may improve the stratification of cancer subtypes.
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paper_title: iSeeRNA: identification of long intergenic non-coding RNA transcripts from transcriptome sequencing data

paper_content:

BackgroundLong intergenic non-coding RNAs (lincRNAs) are emerging as a novel class of non-coding RNAs and potent gene regulators. High-throughput RNA-sequencing combined with de novo assembly promises quantity discovery of novel transcripts. However, the identification of lincRNAs from thousands of assembled transcripts is still challenging due to the difficulties of separating them from protein coding transcripts (PCTs).ResultsWe have implemented iSeeRNA, a support vector machine (SVM)-based classifier for the identification of lincRNAs. iSeeRNA shows better performance compared to other software. A public available webserver for iSeeRNA is also provided for small size dataset.ConclusionsiSeeRNA demonstrates high prediction accuracy and runs several magnitudes faster than other similar programs. It can be integrated into the transcriptome data analysis pipelines or run as a web server, thus offering a valuable tool for lincRNA study.
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paper_title: Pervasive Transcription of the Human Genome Produces Thousands of Previously Unidentified Long Intergenic Noncoding RNAs

paper_content:

Known protein coding gene exons compose less than 3% of the human genome. The remaining 97% is largely uncharted territory, with only a small fraction characterized. The recent observation of transcription in this intergenic territory has stimulated debate about the extent of intergenic transcription and whether these intergenic RNAs are functional. Here we directly observed with a large set of RNA-seq data covering a wide array of human tissue types that the majority of the genome is indeed transcribed, corroborating recent observations by the ENCODE project. Furthermore, using de novo transcriptome assembly of this RNA-seq data, we found that intergenic regions encode far more long intergenic noncoding RNAs (lincRNAs) than previously described, helping to resolve the discrepancy between the vast amount of observed intergenic transcription and the limited number of previously known lincRNAs. In total, we identified tens of thousands of putative lincRNAs expressed at a minimum of one copy per cell, significantly expanding upon prior lincRNA annotation sets. These lincRNAs are specifically regulated and conserved rather than being the product of transcriptional noise. In addition, lincRNAs are strongly enriched for trait-associated SNPs suggesting a new mechanism by which intergenic trait-associated regions may function. These findings will enable the discovery and interrogation of novel intergenic functional elements.
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paper_title: lncRNA-MFDL: identification of human long non-coding RNAs by fusing multiple features and using deep learning

paper_content:

Long noncoding RNAs (lncRNAs) are emerging as a novel class of noncoding RNAs and potent gene regulators, which play an important and varied role in cellular functions. lncRNAs are closely related with the occurrence and development of some diseases. High-throughput RNA-sequencing techniques combined with de novo assembly have identified a large number of novel transcripts. The discovery of large and ‘hidden’ transcriptomes urgently requires the development of effective computational methods that can rapidly distinguish between coding and long noncoding RNAs. In this study, we developed a powerful predictor (named as lncRNA-MFDL) to identify lncRNAs by fusing multiple features of the open reading frame, k-mer, the secondary structure and the most-like coding domain sequence and using deep learning classification algorithms. Using the same human training dataset and a 10-fold cross validation test, lncRNA-MFDL can achieve 97.1% prediction accuracy which is 5.7, 3.7, and 3.4% higher than that of CPC, CNCI and lncRNA-FMFSVM predictors, respectively. Compared with CPC and CNCI predictors in other species (e.g., anole lizard, zebrafish, chicken, gorilla, macaque, mouse, lamprey, orangutan, xenopus and C. elegans) testing datasets, the new lncRNA-MFDL predictor is also much more effective and robust. These results show that lncRNA-MFDL is a powerful tool for identifying lncRNAs. The lncRNA-MFDL software package is freely available at http://compgenomics.utsa.edu/lncRNA_MDFL/ for academic users.
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paper_title: Computational Identification and Functional Predictions of Long Noncoding RNA in Zea mays

paper_content:

Background ::: Computational analysis of cDNA sequences from multiple organisms suggests that a large portion of transcribed DNA does not code for a functional protein. In mammals, noncoding transcription is abundant, and often results in functional RNA molecules that do not appear to encode proteins. Many long noncoding RNAs (lncRNAs) appear to have epigenetic regulatory function in humans, including HOTAIR and XIST. While epigenetic gene regulation is clearly an essential mechanism in plants, relatively little is known about the presence or function of lncRNAs in plants.
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paper_title: Chromatin signature reveals over a thousand highly conserved large non-coding RNAs in mammals

paper_content:

There is growing recognition that mammalian cells produce many thousands of large intergenic transcripts. However, the functional significance of these transcripts has been particularly controversial. Although there are some well-characterized examples, most (>95%) show little evidence of evolutionary conservation and have been suggested to represent transcriptional noise. Here we report a new approach to identifying large non-coding RNAs using chromatin-state maps to discover discrete transcriptional units intervening known protein-coding loci. Our approach identified ~1,600 large multi-exonic RNAs across four mouse cell types. In sharp contrast to previous collections, these large intervening non-coding RNAs (lincRNAs) show strong purifying selection in their genomic loci, exonic sequences and promoter regions, with greater than 95% showing clear evolutionary conservation. We also developed a functional genomics approach that assigns putative functions to each lincRNA, demonstrating a diverse range of roles for lincRNAs in processes from embryonic stem cell pluripotency to cell proliferation. We obtained independent functional validation for the predictions for over 100 lincRNAs, using cell-based assays. In particular, we demonstrate that specific lincRNAs are transcriptionally regulated by key transcription factors in these processes such as p53, NFκB, Sox2, Oct4 (also known as Pou5f1) and Nanog. Together, these results define a unique collection of functional lincRNAs that are highly conserved and implicated in diverse biological processes.
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paper_title: Integrative transcriptome analysis suggest processing of a subset of long non-coding RNAs to small RNAs

paper_content:

BackgroundThe availability of sequencing technology has enabled understanding of transcriptomes through genome-wide approaches including RNA-sequencing. Contrary to the previous assumption that large tracts of the eukaryotic genomes are not transcriptionally active, recent evidence from transcriptome sequencing approaches have revealed pervasive transcription in many genomes of higher eukaryotes. Many of these loci encode transcripts that have no obvious protein-coding potential and are designated as non-coding RNA (ncRNA). Non-coding RNAs are classified empirically as small and long non-coding RNAs based on the size of the functional RNAs. Each of these classes is further classified into functional subclasses. Although microRNAs (miRNA), one of the major subclass of ncRNAs, have been extensively studied for their roles in regulation of gene expression and involvement in a large number of patho-physiological processes, the functions of a large proportion of long non-coding RNAs (lncRNA) still remains elusive. We hypothesized that some lncRNAs could potentially be processed to small RNA and thus could have a dual regulatory output.ResultsIntegration of large-scale independent experimental datasets in public domain revealed that certain well studied lncRNAs harbor small RNA clusters. Expression analysis of the small RNA clusters in different tissue and cell types reveal that they are differentially regulated suggesting a regulated biogenesis mechanism.ConclusionsOur analysis suggests existence of a potentially novel pathway for lncRNA processing into small RNAs. Expression analysis, further suggests that this pathway is regulated. We argue that this evidence supports our hypothesis, though limitations of the datasets and analysis cannot completely rule out alternate possibilities. Further in-depth experimental verification of the observation could potentially reveal a novel pathway for biogenesis.ReviewersThis article was reviewed by Dr Rory Johnson (nominated by Fyodor Kondrashov), Dr Raya Khanin (nominated by Dr Yuriy Gusev) and Prof Neil Smalheiser. For full reviews, please go to the Reviewer’s comment section.
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paper_title: Distributions of exons and introns in the human genome.

paper_content:

The human genome is revisited using exon and intron distribution profiles. The 26,564 annotated genes in the human genome (build October, 2003) contain 233,785 exons and 207,344 introns. On average, there are 8.8 exons and 7.8 introns per gene. About 80% of the exons on each chromosome are< 200 bp in length. < 0.01% of the introns are < 20 bp in length and < 10% of introns are more than 11,000 bp in length. These results suggest constraints on the splicing machinery to splice out very long or very short introns and provide insight to optimal intron length selection. Interestingly, the total length in introns and intergenic DNA on each chromosome is significantly correlated to the determined chromosome size with a coefficient of correlation r = 0.95 and r = 0.97, respectively. These results suggest their implication in genome design.
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paper_title: Computational identification of human long intergenic non-coding RNAs using a GA-SVM algorithm.

paper_content:

Long intergenic non-coding RNAs (lincRNAs) are a new type of non-coding RNAs and are closely related with the occurrence and development of diseases. In previous studies, most lincRNAs have been identified through next-generation sequencing. Because lincRNAs exhibit tissue-specific expression, the reproducibility of lincRNA discovery in different studies is very poor. In this study, not including lincRNA expression, we used the sequence, structural and protein-coding potential features as potential features to construct a classifier that can be used to distinguish lincRNAs from non-lincRNAs. The GA-SVM algorithm was performed to extract the optimized feature subset. Compared with several feature subsets, the five-fold cross validation results showed that this optimized feature subset exhibited the best performance for the identification of human lincRNAs. Moreover, the LincRNA Classifier based on Selected Features (linc-SF) was constructed by support vector machine (SVM) based on the optimized feature subset. The performance of this classifier was further evaluated by predicting lincRNAs from two independent lincRNA sets. Because the recognition rates for the two lincRNA sets were 100% and 99.8%, the linc-SF was found to be effective for the prediction of human lincRNAs.
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paper_title: Resource GENCODE: The reference human genome annotation for The ENCODE Project

paper_content:

The GENCODE Consortium aims to identify all gene features in the human genome using a combination of computational analysis, manual annotation, and experimental validation. Since the first public release of this annotation data set, few new protein-coding loci have been added, yet the number of alternative splicing transcripts annotated has steadily increased. The GENCODE 7 release contains 20,687 protein-coding and 9640 long noncoding RNA loci and has 33,977 coding transcripts not represented in UCSC genes and RefSeq. It also has the most comprehensive annotation of long noncoding RNA (lncRNA) loci publicly available with the predominant transcript form consisting of two exons. We have examined the completeness of the transcript annotation and found that 35% of transcriptional start sites are supported by CAGE clusters and 62% of protein-coding genes have annotated polyA sites. Over one-third of GENCODE protein-coding genes are supported by peptide hits derived from mass spectrometry spectra submitted to Peptide Atlas. New models derived from the Illumina Body Map 2.0 RNA-seq data identify 3689 new loci not currently in GENCODE, of which 3127 consist of two exon models indicating that they are possibly unannotated long noncoding loci. GENCODE 7 is publicly available from gencodegenes.org and via the Ensembl and UCSC Genome Browsers.
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paper_title: Rfam: annotating non-coding RNAs in complete genomes

paper_content:

Rfam is a comprehensive collection of non-coding RNA (ncRNA) families, represented by multiple sequence alignments and profile stochastic context-free grammars. Rfam aims to facilitate the identification and classification of new members of known sequence families, and distributes annotation of ncRNAs in over 200 complete genome sequences. The data provide the first glimpses of conservation of multiple ncRNA families across a wide taxonomic range. A small number of large families are essential in all three kingdoms of life, with large numbers of smaller families specific to certain taxa. Recent improvements in the database are discussed, together with challenges for the future. Rfam is available on the Web at http://www.sanger.ac.uk/Software/Rfam/ and http://rfam.wustl.edu/.
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paper_title: The UCSC known genes

paper_content:

The University of California Santa Cruz (UCSC) Known Genes dataset is constructed by a fully automated process, based on protein data from Swiss-Prot/TrEMBL (UniProt) and the associated mRNA data from Genbank. The detailed steps of this process are described. Extensive cross-references from this dataset to other genomic and proteomic data were constructed. For each known gene, a details page is provided containing rich information about the gene, together with extensive links to other relevant genomic, proteomic and pathway data. As of July 2005, the UCSC Known Genes are available for human, mouse and rat genomes. The Known Genes serves as a foundation to support several key programs: the Genome Browser, Proteome Browser, Gene Sorter and Table Browser offered at the UCSC website. All the associated data files and program source code are also available. They can be accessed at http://genome.ucsc.edu. The genomic coverage of UCSC Known Genes, RefSeq, Ensembl Genes, H-Invitational and CCDS is analyzed. Although UCSC Known Genes offers the highest genomic and CDS coverage among major human and mouse gene sets, more detailed analysis suggests all of them could be further improved. ::: ::: Contact: fanhsu@soe.ucsc.edu
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paper_title: An integrated encyclopedia of DNA elements in the human genome

paper_content:

The human genome encodes the blueprint of life, but the function of the vast majority of its nearly three billion bases is unknown. The Encyclopedia of DNA Elements (ENCODE) project has systematically mapped regions of transcription, transcription factor association, chromatin structure and histone modification. These data enabled us to assign biochemical functions for 80% of the genome, in particular outside of the well-studied protein-coding regions. Many discovered candidate regulatory elements are physically associated with one another and with expressed genes, providing new insights into the mechanisms of gene regulation. The newly identified elements also show a statistical correspondence to sequence variants linked to human disease, and can thereby guide interpretation of this variation. Overall, the project provides new insights into the organization and regulation of our genes and genome, and is an expansive resource of functional annotations for biomedical research.
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paper_title: Many human large intergenic noncoding RNAs associate with chromatin-modifying complexes and affect gene expression

paper_content:

We recently showed that the mammalian genome encodes >1,000 large intergenic noncoding (linc)RNAs that are clearly conserved across mammals and, thus, functional. Gene expression patterns have implicated these lincRNAs in diverse biological processes, including cell-cycle regulation, immune surveillance, and embryonic stem cell pluripotency. However, the mechanism by which these lincRNAs function is unknown. Here, we expand the catalog of human lincRNAs to ≈3,300 by analyzing chromatin-state maps of various human cell types. Inspired by the observation that the well-characterized lincRNA HOTAIR binds the polycomb repressive complex (PRC)2, we tested whether many lincRNAs are physically associated with PRC2. Remarkably, we observe that ≈20% of lincRNAs expressed in various cell types are bound by PRC2, and that additional lincRNAs are bound by other chromatin-modifying complexes. Also, we show that siRNA-mediated depletion of certain lincRNAs associated with PRC2 leads to changes in gene expression, and that the up-regulated genes are enriched for those normally silenced by PRC2. We propose a model in which some lincRNAs guide chromatin-modifying complexes to specific genomic loci to regulate gene expression.
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paper_title: NONCODEv4: exploring the world of long non-coding RNA genes

paper_content:

NONCODE (http://www.bioinfo.org/noncode/) is an integrated knowledge database dedicated to non-coding RNAs (excluding tRNAs and rRNAs). Non-coding RNAs (ncRNAs) have been implied in diseases and identified to play important roles in various biological processes. Since NONCODE version 3.0 was released 2 years ago, discovery of novel ncRNAs has been promoted by high-throughput RNA sequencing (RNA-Seq). In this update of NONCODE, we expand the ncRNA data set by collection of newly identified ncRNAs from literature published in the last 2 years and integration of the latest version of RefSeq and Ensembl. Particularly, the number of long non-coding RNA (lncRNA) has increased sharply from 73 327 to 210 831. Owing to similar alternative splicing pattern to mRNAs, the concept of lncRNA genes was put forward to help systematic understanding of lncRNAs. The 56 018 and 46 475 lncRNA genes were generated from 95 135 and 67 628 lncRNAs for human and mouse, respectively. Additionally, we present expression profile of lncRNA genes by graphs based on public RNA-seq data for human and mouse, as well as predict functions of these lncRNA genes. The improvements brought to the database also include an incorporation of an ID conversion tool from RefSeq or Ensembl ID to NONCODE ID and a service of lncRNA identification. NONCODE is also accessible through http://www.noncode.org/.
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paper_title: Methods for comprehensive experimental identification of RNA-protein interactions

paper_content:

The importance of RNA-protein interactions in controlling mRNA regulation and non-coding RNA function is increasingly appreciated. A variety of methods exist to comprehensively define RNA-protein interactions. We describe these methods and the considerations required for designing and interpreting these experiments.
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paper_title: Poly-combing the genome for RNA

paper_content:

An unresolved question in mammalian epigenetic regulation is how ubiquitously expressed chromatin-modifying complexes such as Polycomb group complex 2 (PRC2) find their specific target sites across an intricate choreography of localization events in time and space. Two recent studies now provide critical new insights into an intriguing genome-wide role for RNA in PRC2 regulation.
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paper_title: Fine-scale chromatin interaction maps reveal the cis-regulatory landscape of human lincRNA genes

paper_content:

Targeted DNase Hi-C uses DNase I instead of restriction enzymes for chromatin fragmentation and improves the resolution of chromatin interaction maps.
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paper_title: Noncoding RNAs and LRRFIP1 regulate TNF expression.

paper_content:

Noncoding RNAs have been implicated in the regulation of expression of numerous genes; however, the mechanism is not fully understood. We identified bidirectional, long noncoding RNAs upstream of the TNF gene using five different methods. They arose in a region where the repressors LRRFIP1, EZH2, and SUZ12 were demonstrated to bind, suggesting a role in repression. The noncoding RNAs were polyadenylated, capped, and chromatin associated. Knockdown of the noncoding RNAs was associated with derepression of TNF mRNA and diminished binding of LRRFIP1 to both RNA targets and chromatin. Overexpression of the noncoding RNAs led to diminished expression of TNF and recruitment of repressor proteins to the locus. One repressor protein, LRRFIP1, bound directly to the noncoding RNAs. These data place the noncoding RNAs upstream of TNF gene as central to the transcriptional regulation. They appear to serve as a platform for the assembly of a repressive complex.
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paper_title: A short guide to long non-coding RNA gene nomenclature

paper_content:

The HUGO Gene Nomenclature Committee (HGNC) is the only organisation authorised to assign standardised nomenclature to human genes. Of the 38,000 approved gene symbols in our database (http://www.genenames.org), the majority represent protein-coding (pc) genes; however, we also name pseudogenes, phenotypic loci, some genomic features, and to date have named more than 8,500 human non-protein coding RNA (ncRNA) genes and ncRNA pseudogenes. We have already established unique names for most of the small ncRNA genes by working with experts for each class. Small ncRNAs can be defined into their respective classes by their shared homology and common function. In contrast, long non-coding RNA (lncRNA) genes represent a disparate set of loci related only by their size, more than 200 bases in length, share no conserved sequence homology, and have variable functions. As with pc genes, wherever possible, lncRNAs are named based on the known function of their product; a short guide is presented herein to help authors when developing novel gene symbols for lncRNAs with characterised function. Researchers must contact the HGNC with their suggestions prior to publication, to check whether the proposed gene symbol can be approved. Although thousands of lncRNAs have been predicted in the human genome, for the vast majority their function remains unresolved. lncRNA genes with no known function are named based on their genomic context. Working with lncRNA researchers, the HGNC aims to provide unique and, wherever possible, meaningful gene symbols to all lncRNA genes.
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paper_title: Integrative annotation of human large intergenic noncoding RNAs reveals global properties and specific subclasses

paper_content:

Large intergenic noncoding RNAs (lincRNAs) are emerging as key regulators of diverse cellular processes. Determining the function of individual lincRNAs remains a challenge. Recent advances in RNA sequencing (RNA-seq) and computational methods allow for an unprecedented analysis of such transcripts. Here, we present an integrative approach to define a reference catalog of >8000 human lincRNAs. Our catalog unifies previously existing annotation sources with transcripts we assembled from RNA-seq data collected from ~4 billion RNA-seq reads across 24 tissues and cell types. We characterize each lincRNA by a panorama of >30 properties, including sequence, structural, transcriptional, and orthology features. We found that lincRNA expression is strikingly tissue-specific compared with coding genes, and that lincRNAs are typically coexpressed with their neighboring genes, albeit to an extent similar to that of pairs of neighboring protein-coding genes. We distinguish an additional subset of transcripts that have high evolutionary conservation but may include short ORFs and may serve as either lincRNAs or small peptides. Our integrated, comprehensive, yet conservative reference catalog of human lincRNAs reveals the global properties of lincRNAs and will facilitate experimental studies and further functional classification of these genes.
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paper_title: Long non-coding RNAs: insights into functions

paper_content:

In mammals and other eukaryotes most of the genome is transcribed in a developmentally regulated manner to produce large numbers of long non-coding RNAs (ncRNAs). Here we review the rapidly advancing field of long ncRNAs, describing their conservation, their organization in the genome and their roles in gene regulation. We also consider the medical implications, and the emerging recognition that any transcript, regardless of coding potential, can have an intrinsic function as an RNA.
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paper_title: lincRNA HOTAIR as a Novel Promoter of Cancer Progression

paper_content:

Large intergenic non-coding RNAs (lincRNA) regulate development and disease via interactions with their protein partners. Expression of the lincRNA HOX transcript antisense RNA (HOTAIR) is elevated in a variety of malignancies and linked to metastasis and poor prognosis. HOTAIR promotes proliferation, invasion, and metastasis in the preclinical studies of cancer through modulation of chromatin modifying complexes. In the current review we discuss the molecular mechanisms of HOTAIR-mediated aggressive phenotypes of cancer, HOTAIR's potential in cancer intervention, and challenges in exploration of HOTAIR in cancer biology.
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paper_title: The hallmarks of cancer A long non-coding RNA point of view

paper_content:

With the advent of next generation sequencing methods and progress in transcriptome analysis, it became obvious that the human genome contains much more than just protein-coding genes. In fact, up to 70% of our genome is transcribed into RNA that does not serve as templates for proteins. In this review, we focus on the emerging roles of these long non-coding RNAs (lncRNAs) in the field of tumor biology. Long ncRNAs were found to be deregulated in several human cancers and show tissue-specific expression. Functional studies revealed a broad spectrum of mechanisms applied by lncRNAs such as HOTAIR, MALAT1, ANRIL or lincRNA-p21 to fulfill their functions. Here, we link the cellular processes influenced by long ncRNAs to the hallmarks of cancer and therefore provide an ncRNA point-of-view on tumor biology. This should stimulate new research directions and therapeutic options considering long ncRNAs as novel prognostic markers and therapeutic targets.
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paper_title: Transcriptional regulation by Polycomb group proteins

paper_content:

Polycomb group (PcG) proteins function within Polycomb repressive complexes (PRCs), which modify histones and other proteins and silence target genes. This Review highlights new insights into the role of PcG proteins in gene regulation, specifically in controlling self-renewal and differentiation of embryonic stem cells, and into how PRCs are targeted to chromatin.
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paper_title: Many human large intergenic noncoding RNAs associate with chromatin-modifying complexes and affect gene expression

paper_content:

We recently showed that the mammalian genome encodes >1,000 large intergenic noncoding (linc)RNAs that are clearly conserved across mammals and, thus, functional. Gene expression patterns have implicated these lincRNAs in diverse biological processes, including cell-cycle regulation, immune surveillance, and embryonic stem cell pluripotency. However, the mechanism by which these lincRNAs function is unknown. Here, we expand the catalog of human lincRNAs to ≈3,300 by analyzing chromatin-state maps of various human cell types. Inspired by the observation that the well-characterized lincRNA HOTAIR binds the polycomb repressive complex (PRC)2, we tested whether many lincRNAs are physically associated with PRC2. Remarkably, we observe that ≈20% of lincRNAs expressed in various cell types are bound by PRC2, and that additional lincRNAs are bound by other chromatin-modifying complexes. Also, we show that siRNA-mediated depletion of certain lincRNAs associated with PRC2 leads to changes in gene expression, and that the up-regulated genes are enriched for those normally silenced by PRC2. We propose a model in which some lincRNAs guide chromatin-modifying complexes to specific genomic loci to regulate gene expression.
---
paper_title: Poly-combing the genome for RNA

paper_content:

An unresolved question in mammalian epigenetic regulation is how ubiquitously expressed chromatin-modifying complexes such as Polycomb group complex 2 (PRC2) find their specific target sites across an intricate choreography of localization events in time and space. Two recent studies now provide critical new insights into an intriguing genome-wide role for RNA in PRC2 regulation.
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paper_title: ncRNA- and Pc2 Methylation-Dependent Gene Relocation between Nuclear Structures Mediates Gene Activation Programs

paper_content:

Summary Although eukaryotic nuclei contain distinct architectural structures associated with noncoding RNAs (ncRNAs), their potential relationship to regulated transcriptional programs remains poorly understood. Here, we report that methylation/demethylation of Polycomb 2 protein (Pc2) controls relocation of growth-control genes between Polycomb bodies (PcGs) and interchromatin granules (ICGs) in response to growth signals. This movement is the consequence of binding of methylated and unmethylated Pc2 to the ncRNAs TUG1 and MALAT1/NEAT2 , located in PcGs and ICGs, respectively. These ncRNAs mediate assembly of multiple corepressors/coactivators and can serve to switch mark recognition by "readers" of the histone code. Additionally, binding of NEAT2 to unmethylated Pc2 promotes E2F1 SUMOylation, leading to activation of the growth-control gene program. These observations delineate a molecular pathway linking the actions of subnuclear structure-specific ncRNAs and nonhistone protein methylation to relocation of transcription units in the three-dimensional space of the nucleus, thus achieving coordinated gene expression programs. PaperClip
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paper_title: Molecular mechanisms of long noncoding RNAs.

paper_content:

Long noncoding RNAs (lncRNAs) are an important class of pervasive genes involved in a variety of biological functions. Here we discuss the emerging archetypes of molecular functions that lncRNAs execute-as signals, decoys, guides, and scaffolds. For each archetype, examples from several disparate biological contexts illustrate the commonality of the molecular mechanisms, and these mechanistic views provide useful explanations and predictions of biological outcomes. These archetypes of lncRNA function may be a useful framework to consider how lncRNAs acquire properties as biological signal transducers and hint at their possible origins in evolution. As new lncRNAs are being discovered at a rapid pace, the molecular mechanisms of lncRNAs are likely to be enriched and diversified.
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paper_title: LincRNA-p21 activates p21 in cis to promote Polycomb target gene expression and to enforce the G1/S checkpoint.

paper_content:

The p53-regulated long noncoding RNA lincRNA-p21 has been proposed to act in trans via several mechanisms ranging from repressing genes in the p53 transcriptional network to regulating mRNA translation and protein stability. To further examine lincRNA-p21 function, we generated a conditional knockout mouse model. We find that lincRNA-p21 predominantly functions in cis to activate expression of its neighboring gene, p21. Mechanistically, we show that lincRNA-p21 acts in concert with hnRNP-K as a coactivator for p53-dependent p21 transcription. Additional phenotypes of lincRNA-p21 deficiency could be attributed to diminished p21 levels, including deregulated expression and altered chromatin state of some Polycomb target genes, a defective G1/S checkpoint, increased proliferation rates, and enhanced reprogramming efficiency. These findings indicate that lincRNA-p21 affects global gene expression and influences the p53 tumor suppressor pathway by acting in cis as a locus-restricted coactivator for p53-mediated p21 expression.
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paper_title: Long noncoding RNAs: functional surprises from the RNA world

paper_content:

Most of the eukaryotic genome is transcribed, yielding a complex network of transcripts that includes tens of thousands of long noncoding RNAs with little or no protein-coding capacity. Although the vast majority of long noncoding RNAs have yet to be characterized thoroughly, many of these transcripts are unlikely to represent transcriptional "noise" as a significant number have been shown to exhibit cell type-specific expression, localization to subcellular compartments, and association with human diseases. Here, we highlight recent efforts that have identified a myriad of molecular functions for long noncoding RNAs. In some cases, it appears that simply the act of noncoding RNA transcription is sufficient to positively or negatively affect the expression of nearby genes. However, in many cases, the long noncoding RNAs themselves serve key regulatory roles that were assumed previously to be reserved for proteins, such as regulating the activity or localization of proteins and serving as organizational frameworks of subcellular structures. In addition, many long noncoding RNAs are processed to yield small RNAs or, conversely, modulate how other RNAs are processed. It is thus becoming increasingly clear that long noncoding RNAs can function via numerous paradigms and are key regulatory molecules in the cell.
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paper_title: Structural basis of the non-coding RNA RsmZ acting as a protein sponge

paper_content:

MicroRNA and protein sequestration by non-coding RNAs (ncRNAs) has recently generated much interest. In the bacterial Csr/Rsm system, which is considered to be the most general global post-transcriptional regulatory system responsible for bacterial virulence, ncRNAs such as CsrB or RsmZ activate translation initiation by sequestering homodimeric CsrA-type proteins from the ribosome-binding site of a subset of messenger RNAs. However, the mechanism of ncRNA-mediated protein sequestration is not understood at the molecular level. Here we show for Pseudomonas fluorescens that RsmE protein dimers assemble sequentially, specifically and cooperatively onto the ncRNA RsmZ within a narrow affinity range. This assembly yields two different native ribonucleoprotein structures. Using a powerful combination of nuclear magnetic resonance and electron paramagnetic resonance spectroscopy we elucidate these 70-kilodalton solution structures, thereby revealing the molecular mechanism of the sequestration process and how RsmE binding protects the ncRNA from RNase E degradation. Overall, our findings suggest that RsmZ is well-tuned to sequester, store and release RsmE and therefore can be viewed as an ideal protein 'sponge'.
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paper_title: A ceRNA Hypothesis: The Rosetta Stone of a Hidden RNA Language?

paper_content:

Here, we present a unifying hypothesis about how messenger RNAs, transcribed pseudogenes, and long noncoding RNAs "talk" to each other using microRNA response elements (MREs) as letters of a new language. We propose that this "competing endogenous RNA" (ceRNA) activity forms a large-scale regulatory network across the transcriptome, greatly expanding the functional genetic information in the human genome and playing important roles in pathological conditions, such as cancer.
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paper_title: Linc-RNA-RoR acts as a "sponge" against mediation of the differentiation of endometrial cancer stem cells by microRNA-145.

paper_content:

OBJECTIVES ::: Recently, large intergenic non-coding ribonucleic acids-RoR (linc-RoR) was reported to regulate expression of core stem cell transcription factors (TFs), but its role in endometrial tumorsphere is still unknown. ::: ::: ::: METHODS ::: Fluorescence in situ hybridization (FISH) was used to characterize linc-RoR expression in ETs. After construction of adenovirus vectors carrying green fluorescent protein (GFP), these vectors were transfected into ETs to estimate the effects of overexpression or knocked down expression of miR-145, linc-RoR or Dicer. Flow cytometry was employed to ascertain transfection efficiency, and real-time polymerase chain reaction (RT-PCR) was employed to compare their levels. Colony formation was analyzed using cultured gelatin-coated tissue cultures. miR-145 potential targeting sites in linc-RoR were mutated using a site-directed mutagenesis kit to verify its competing endogenous RNA (ceRNA) effects. ::: ::: ::: RESULTS ::: Expression of linc-RoR and core stem cell TFs was associated with the pluripotent state of ETs, whereas miR-145 expression increased after ET differentiation. Greater expression of miR-145 could lead to down-regulation of linc-RoR and core TFs, and decreased colony formation. Converse effects could be achieved after knocked-down miR-145 expression. The effects of miR-145 could be eliminated after increasing the expression of linc-RoR in ETs or mutated targeted sequences in linc-RoR. Knocked-down Dicer expression could improve the expression of linc-RoR and core TFs. ::: ::: ::: CONCLUSIONS ::: Linc-RoR is a ceRNA and acts as a miR-145 "sponge" to inhibit mediation of the differentiation of ETs by miR-145. These results suggest that linc-RoR has an important role during endometrial carcinogenesis.
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paper_title: Plasma HULC as a Promising Novel Biomarker for the Detection of Hepatocellular Carcinoma

paper_content:

Hepatocellular carcinoma (HCC) is a leading cause of cancer death in many Asian and African countries. Lack of early diagnosis tools is one of the clinical obstacles for effective treatment of HCC. Thus, enhanced understanding of the molecular changes associated with HCC is urgently needed to develop novel strategies for the diagnosis and treatment of this dismal disease. While aberrant expression of long noncoding RNAs (lncRNAs) has been functionally associated with certain cancers, the expression profiles and biological relevance of lncRNAs in HCC remain unclear. Highly upregulated in liver cancer (HULC) lncRNA has been implicated in the regulation of hepatoma cell proliferation. In this study, we demonstrate that HULC expression is significantly higher in HCC tumors compared to normal liver tissues. Among the tumor tissues, higher HULC expression is positively associated with Edmondson histological grades or with hepatitis B (HBV) positive status. Moreover, HULC lncRNA is detected with higher frequency in the plasma of HCC patients compared to healthy controls. Higher HULC detection rates are observed in the plasma of patients with higher Edmondson grades or with HBV+ status. These findings indicate for the first time that the expression of HULC in plasma can be used as a noninvasive promising novel biomarker for the diagnosis and/or prognosis of HCC.
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paper_title: Endogenous miRNA Sponge lincRNA-RoR Regulates Oct4, Nanog, and Sox2 in Human Embryonic Stem Cell Self-Renewal

paper_content:

The embryonic stem cell (ESC) transcriptional and epigenetic networks are controlled by a multilayer regulatory circuitry, including core transcription factors (TFs), posttranscriptional modifier microRNAs (miRNAs), and some other regulators. However, the role of large intergenic noncoding RNAs (lincRNAs) in this regulatory circuitry and their underlying mechanism remains undefined. Here, we demonstrate that a lincRNA, linc-RoR, may function as a key competing endogenous RNA to link the network of miRNAs and core TFs, e.g., Oct4, Sox2, and Nanog. We show that linc-RoR shares miRNA-response elements with these core TFs and that linc-RoR prevents these core TFs from miRNA-mediated suppression in self-renewing human ESC. We suggest that linc-RoR forms a feedback loop with core TFs and miRNAs to regulate ESC maintenance and differentiation. These results may provide insights into the functional interactions of the components of genetic networks during development and may lead to new therapies for many diseases.
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paper_title: CREB up-regulates long non-coding RNA, HULC expression through interaction with microRNA-372 in liver cancer

paper_content:

Long non-coding RNA (lncRNA), highly up-regulated in liver cancer (HULC) plays an important role in tumorigenesis. Depletion of HULC resulted in a significant deregulation of several genes involved in liver cancer. Although up-regulation of HULC expression in hepatocellular carcinoma has been reported, the molecular mechanisms remain unknown. In this study, we used in vivo and in vitro approaches to characterize cancer-dependent alterations in the chromatin organization and find a CREB binding site (encompassing from -67 to -53 nt) in the core promoter. Besides, we also provided evidence that PKA pathway may involved in up-regulation of HULC. Furthermore, we demonstrated HULC may act as an endogenous 'sponge', which down-regulates a series of microRNAs (miRNAs) activities, including miR-372. Inhibition of miR-372 leads to reducing translational repression of its target gene, PRKACB, which in turn induces phosphorylation of CREB. Over-expression of miR-372 decreases the association of CREB with the proximal promoter, followed by the dissociation of P300, resulting in a change of the histone 'code', such as in deacetylation and methylation. The study elucidates that fine tuning of HULC expression is part of an auto-regulatory loop in which it's inhibitory to expression and activity of miR-372 allows lncRNA up-regulated expression in liver cancer.
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paper_title: Linc2GO: a human LincRNA function annotation resource based on ceRNA hypothesis

paper_content:

Summary: Large numbers of long intergenic non-coding RNA (lincRNA) have been detected through high-throughput sequencing technology. However, currently we still know very little about their functions. Therefore, a lincRNA function annotation database is needed to facilitate the study in this field. In this article, we present Linc2GO, a web resource that aims to provide comprehensive functional annotations for human lincRNA. MicroRNA-mRNA and microRNA-lincRNA interaction data were integrated to generate lincRNA functional annotations based on the ‘competing endogenous RNA hypothesis’. To the best of our knowledge, Linc2GO is the first database that makes use of the ‘competing endogenous RNA hypothesis’ to predict lincRNA functions. Availability: Freely available at http://www.bioinfo.tsinghua.edu.cn/ ~liuke/Linc2GO/index.html
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paper_title: A ceRNA Hypothesis: The Rosetta Stone of a Hidden RNA Language?

paper_content:

Here, we present a unifying hypothesis about how messenger RNAs, transcribed pseudogenes, and long noncoding RNAs "talk" to each other using microRNA response elements (MREs) as letters of a new language. We propose that this "competing endogenous RNA" (ceRNA) activity forms a large-scale regulatory network across the transcriptome, greatly expanding the functional genetic information in the human genome and playing important roles in pathological conditions, such as cancer.
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paper_title: Volatile evolution of long noncoding RNA repertoires: mechanisms and biological implications

paper_content:

Thousands of genes encoding long noncoding RNAs (lncRNAs) have been identified in all vertebrate genomes thus far examined. The list of lncRNAs partaking in arguably important biochemical, cellular, and developmental activities is steadily growing. However, it is increasingly clear that lncRNA repertoires are subject to weak functional constraint and rapid turnover during vertebrate evolution. We discuss here some of the factors that may explain this apparent paradox, including relaxed constraint on sequence to maintain lncRNA structure/function, extensive redundancy in the regulatory circuits in which lncRNAs act, as well as adaptive and non-adaptive forces such as genetic drift. We explore the molecular mechanisms promoting the birth and rapid evolution of lncRNA genes, with an emphasis on the influence of bidirectional transcription and transposable elements, two pervasive features of vertebrate genomes. Together these properties reveal a remarkably dynamic and malleable noncoding transcriptome which may represent an important source of robustness and evolvability.
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paper_title: Widespread purifying selection on RNA structure in mammals

paper_content:

Evolutionarily conserved RNA secondary structures are a robust indicator of purifying selection and, consequently, molecular function. Evaluating their genome-wide occurrence through comparative genomics has consistently been plagued by high false-positive rates and divergent predictions. We present a novel benchmarking pipeline aimed at calibrating the precision of genome-wide scans for consensus RNA structure prediction. The benchmarking data obtained from two refined structure prediction algorithms, RNAz and SISSIz, were then analyzed to fine-tune the parameters of an optimized workflow for genomic sliding window screens. When applied to consistency-based multiple genome alignments of 35 mammals, our approach confidently identifies >4 million evolutionarily constrained RNA structures using a conservative sensitivity threshold that entails historically low false discovery rates for such analyses (5–22%). These predictions comprise 13.6% of the human genome, 88% of which fall outside any known sequence-constrained element, suggesting that a large proportion of the mammalian genome is functional. As an example, our findings identify both known and novel conserved RNA structure motifs in the long noncoding RNA MALAT1. This study provides an extensive set of functional transcriptomic annotations that will assist researchers in uncovering the precise mechanisms underlying the developmental ontologies of higher eukaryotes.
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paper_title: Transposable elements reveal a stem cell-specific class of long noncoding RNAs

paper_content:

BackgroundNumerous studies over the past decade have elucidated a large set of long intergenic noncoding RNAs (lincRNAs) in the human genome. Research since has shown that lincRNAs constitute an important layer of genome regulation across a wide spectrum of species. However, the factors governing their evolution and origins remain relatively unexplored. One possible factor driving lincRNA evolution and biological function is transposable element (TE) insertions. Here, we comprehensively characterize the TE content of lincRNAs relative to genomic averages and protein coding transcripts.ResultsOur analysis of the TE composition of 9,241 human lincRNAs revealed that, in sharp contrast to protein coding genes, 83% of lincRNAs contain a TE, and TEs comprise 42% of lincRNA sequence. lincRNA TE composition varies significantly from genomic averages - L1 and Alu elements are depleted and broad classes of endogenous retroviruses are enriched. TEs occur in biased positions and orientations within lincRNAs, particularly at their transcription start sites, suggesting a role in lincRNA transcriptional regulation. Accordingly, we observed a dramatic example of HERVH transcriptional regulatory signals correlating strongly with stem cell-specific expression of lincRNAs. Conversely, lincRNAs devoid of TEs are expressed at greater levels than lincRNAs with TEs in all tissues and cell lines, particularly in the testis.ConclusionsTEs pervade lincRNAs, dividing them into classes, and may have shaped lincRNA evolution and function by conferring tissue-specific expression from extant transcriptional regulatory signals.
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paper_title: LincRNA-p21 activates p21 in cis to promote Polycomb target gene expression and to enforce the G1/S checkpoint.

paper_content:

The p53-regulated long noncoding RNA lincRNA-p21 has been proposed to act in trans via several mechanisms ranging from repressing genes in the p53 transcriptional network to regulating mRNA translation and protein stability. To further examine lincRNA-p21 function, we generated a conditional knockout mouse model. We find that lincRNA-p21 predominantly functions in cis to activate expression of its neighboring gene, p21. Mechanistically, we show that lincRNA-p21 acts in concert with hnRNP-K as a coactivator for p53-dependent p21 transcription. Additional phenotypes of lincRNA-p21 deficiency could be attributed to diminished p21 levels, including deregulated expression and altered chromatin state of some Polycomb target genes, a defective G1/S checkpoint, increased proliferation rates, and enhanced reprogramming efficiency. These findings indicate that lincRNA-p21 affects global gene expression and influences the p53 tumor suppressor pathway by acting in cis as a locus-restricted coactivator for p53-mediated p21 expression.
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paper_title: Molecular Mechanisms and Function Prediction of Long Noncoding RNA

paper_content:

The central dogma of gene expression considers RNA as the carrier of genetic information from DNA to protein. However, it has become more and more clear that RNA plays more important roles than simply being the information carrier. Recently, whole genome transcriptomic analyses have identified large numbers of dynamically expressed long noncoding RNAs (lncRNAs), many of which are involved in a variety of biological functions. Even so, the functions and molecular mechanisms of most lncRNAs still remain elusive. Therefore, it is necessary to develop computational methods to predict the function of lncRNAs in order to accelerate the study of lncRNAs. Here, we review the recent progress in the identification of lncRNAs, the molecular functions and mechanisms of lncRNAs, and the computational methods for predicting the function of lncRNAs.
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paper_title: Many human large intergenic noncoding RNAs associate with chromatin-modifying complexes and affect gene expression

paper_content:

We recently showed that the mammalian genome encodes >1,000 large intergenic noncoding (linc)RNAs that are clearly conserved across mammals and, thus, functional. Gene expression patterns have implicated these lincRNAs in diverse biological processes, including cell-cycle regulation, immune surveillance, and embryonic stem cell pluripotency. However, the mechanism by which these lincRNAs function is unknown. Here, we expand the catalog of human lincRNAs to ≈3,300 by analyzing chromatin-state maps of various human cell types. Inspired by the observation that the well-characterized lincRNA HOTAIR binds the polycomb repressive complex (PRC)2, we tested whether many lincRNAs are physically associated with PRC2. Remarkably, we observe that ≈20% of lincRNAs expressed in various cell types are bound by PRC2, and that additional lincRNAs are bound by other chromatin-modifying complexes. Also, we show that siRNA-mediated depletion of certain lincRNAs associated with PRC2 leads to changes in gene expression, and that the up-regulated genes are enriched for those normally silenced by PRC2. We propose a model in which some lincRNAs guide chromatin-modifying complexes to specific genomic loci to regulate gene expression.
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paper_title: Fine-scale chromatin interaction maps reveal the cis-regulatory landscape of human lincRNA genes

paper_content:

Targeted DNase Hi-C uses DNase I instead of restriction enzymes for chromatin fragmentation and improves the resolution of chromatin interaction maps.
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paper_title: Long non-coding RNAs function annotation: a global prediction method based on bi-colored networks

paper_content:

More and more evidences demonstrate that the long non-coding RNAs (lncRNAs) play many key roles in diverse biological processes. There is a critical need to annotate the functions of increasing available lncRNAs. In this article, we try to apply a global network-based strategy to tackle this issue for the first time. We develop a bi-colored network based global function predictor, long non-coding RNA global function predictor (‘lnc-GFP’), to predict probable functions for lncRNAs at large scale by integrating gene expression data and protein interaction data. The performance of lnc-GFP is evaluated on protein-coding and lncRNA genes. Cross-validation tests on protein-coding genes with known function annotations indicate that our method can achieve a precision up to 95%, with a suitable parameter setting. Among the 1713 lncRNAs in the bi-colored network, the 1625 (94.9%) lncRNAs in the maximum connected component are all functionally characterized. For the lncRNAs expressed in mouse embryo stem cells and neuronal cells, the inferred putative functions by our method highly match those in the known literature.
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paper_title: Computational Identification and Functional Predictions of Long Noncoding RNA in Zea mays

paper_content:

Background ::: Computational analysis of cDNA sequences from multiple organisms suggests that a large portion of transcribed DNA does not code for a functional protein. In mammals, noncoding transcription is abundant, and often results in functional RNA molecules that do not appear to encode proteins. Many long noncoding RNAs (lncRNAs) appear to have epigenetic regulatory function in humans, including HOTAIR and XIST. While epigenetic gene regulation is clearly an essential mechanism in plants, relatively little is known about the presence or function of lncRNAs in plants.
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paper_title: Linc2GO: a human LincRNA function annotation resource based on ceRNA hypothesis

paper_content:

Summary: Large numbers of long intergenic non-coding RNA (lincRNA) have been detected through high-throughput sequencing technology. However, currently we still know very little about their functions. Therefore, a lincRNA function annotation database is needed to facilitate the study in this field. In this article, we present Linc2GO, a web resource that aims to provide comprehensive functional annotations for human lincRNA. MicroRNA-mRNA and microRNA-lincRNA interaction data were integrated to generate lincRNA functional annotations based on the ‘competing endogenous RNA hypothesis’. To the best of our knowledge, Linc2GO is the first database that makes use of the ‘competing endogenous RNA hypothesis’ to predict lincRNA functions. Availability: Freely available at http://www.bioinfo.tsinghua.edu.cn/ ~liuke/Linc2GO/index.html
---
paper_title: RNAhybrid: microRNA target prediction easy, fast and flexible

paper_content:

In the elucidation of the microRNA regulatory net- work, knowledge of potential targets is of highest importance. Among existing target prediction methods, RNAhybrid (M. Rehmsmeier, P. Steffen, M. Hochsmann and R. Giegerich (2004) RNA, 10, 1507-1517) is unique in offering a flexible online pre- diction. Recently, some useful features have been added, among these the possibility to disallow G:U base pairs in the seed region, and a seed-match speed-up, which accelerates the program by a factor of 8. In addition, the program can now be used as a webservice for remote calls from user-implemented programs. We demonstrate RNAhybrid's flexibility with the prediction of a non-canonical target site for Caenorhabditis elegans miR-241 in the 3 0 -untrans- lated region of lin-39. RNAhybrid is available at http://bibiserv.techfak.uni-bielefeld.de/rnahybrid.
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paper_title: Computational Tools for Investigating RNA-Protein Interaction Partners

paper_content:

RNA-protein interactions are important in a wide variety of cellular and developmental processes. Recently, high-throughput experiments have begun to provide valuable information about RNA partners and binding sites for many RNA-binding proteins (RBPs), but these experiments are expensive and time consuming. Thus, computational methods for predicting RNA-Protein interactions (RPIs) can be valuable tools for identifying potential interaction partners of a given protein or RNA, and for identifying likely interfacial residues in RNA-protein complexes. This review focuses on the “partner prediction” problem and summarizes available computational methods, web servers and databases that are devoted to it. New computational tools for addressing the related “interface prediction” problem are also discussed. Together, these computational methods for investigating RNA-protein interactions provide the basis for new strategies for integrating RNA-protein interactions into existing genetic and developmental regulatory networks, an important goal of future research.
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paper_title: Methods for comprehensive experimental identification of RNA-protein interactions

paper_content:

The importance of RNA-protein interactions in controlling mRNA regulation and non-coding RNA function is increasingly appreciated. A variety of methods exist to comprehensively define RNA-protein interactions. We describe these methods and the considerations required for designing and interpreting these experiments.
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paper_title: Improving performance of mammalian microRNA target prediction

paper_content:

BackgroundMicroRNAs (miRNAs) are single-stranded non-coding RNAs known to regulate a wide range of cellular processes by silencing the gene expression at the protein and/or mRNA levels. Computational prediction of miRNA targets is essential for elucidating the detailed functions of miRNA. However, the prediction specificity and sensitivity of the existing algorithms are still poor to generate meaningful, workable hypotheses for subsequent experimental testing. Constructing a richer and more reliable training data set and developing an algorithm that properly exploits this data set would be the key to improve the performance current prediction algorithms.ResultsA comprehensive training data set is constructed for mammalian miRNAs with its positive targets obtained from the most up-to-date miRNA target depository called miRecords and its negative targets derived from 20 microarray data. A new algorithm SVMicrO is developed, which assumes a 2-stage structure including a site support vector machine (SVM) followed by a UTR-SVM. SVMicrO makes prediction based on 21 optimal site features and 18 optimal UTR features, selected by training from a comprehensive collection of 113 site and 30 UTR features. Comprehensive evaluation of SVMicrO performance has been carried out on the training data, proteomics data, and immunoprecipitation (IP) pull-down data. Comparisons with some popular algorithms demonstrate consistent improvements in prediction specificity, sensitivity and precision in all tested cases. All the related materials including source code and genome-wide prediction of human targets are available at http://compgenomics.utsa.edu/svmicro.html.ConclusionsA 2-stage SVM based new miRNA target prediction algorithm called SVMicrO is developed. SVMicrO is shown to be able to achieve robust performance. It holds the promise to achieve continuing improvement whenever better training data that contain additional verified or high confidence positive targets and properly selected negative targets are available.
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paper_title: Computational Prediction of Polycomb-Associated Long Non-Coding RNAs

paper_content:

Among thousands of long non-coding RNAs (lncRNAs) only a small subset is functionally characterized and the functional annotation of lncRNAs on the genomic scale remains inadequate. In this study we computationally characterized two functionally different parts of human lncRNAs transcriptome based on their ability to bind the polycomb repressive complex, PRC2. This classification is enabled by the fact that while all lncRNAs constitute a diverse set of sequences, the classes of PRC2-binding and PRC2 non-binding lncRNAs possess characteristic combinations of sequence-structure patterns and, therefore, can be separated within the feature space. Based on the specific combination of features, we built several machine-learning classifiers and identified the SVM-based classifier as the best performing. We further showed that the SVM-based classifier is able to generalize on the independent data sets. We observed that this classifier, trained on the human lncRNAs, can predict up to 59.4% of PRC2-binding lncRNAs in mice. This suggests that, despite the low degree of sequence conservation, many lncRNAs play functionally conserved biological roles.
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paper_title: SVM based prediction of RNA-binding proteins using binding residues and evolutionary information

paper_content:

RNA-binding proteins (RBPs) play crucial role in transcription and gene-regulation. This paper describes a support vector machine (SVM) based method for discriminating and classifying RNA-binding and non-binding proteins using sequence features. With the threshold of 30% interacting residues, RNA-binding amino acid prediction method PPRINT achieved the Matthews correlation coefficient (MCC) of 0.32. BLAST and PSI-BLAST identified RBPs with the coverage of 32.63 and 33.16%, respectively, at the e-value of 1e-4. The SVM models developed with amino acid, dipeptide and four-part amino acid compositions showed the MCC of 0.60, 0.46, and 0.53, respectively. This is the first study in which evolutionary information in form of position specific scoring matrix (PSSM) profile has been successfully used for predicting RBPs. We achieved the maximum MCC of 0.62 using SVM model based on PSSM called PSSM-400. Finally, we developed different hybrid approaches and achieved maximum MCC of 0.66. We also developed a method for predicting three subclasses of RNA binding proteins (e.g., rRNA, tRNA, mRNA binding proteins). The performance of the method was also evaluated on an independent dataset of 69 RBPs and 100 non-RBPs (NBPs). An additional benchmarking was also performed using gene ontology (GO) based annotation. Based on the hybrid approach a web-server RNApred has been developed for predicting RNA binding proteins from amino acid sequences (http://www.imtech.res.in/raghava/rnapred/).
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paper_title: Many human large intergenic noncoding RNAs associate with chromatin-modifying complexes and affect gene expression

paper_content:

We recently showed that the mammalian genome encodes >1,000 large intergenic noncoding (linc)RNAs that are clearly conserved across mammals and, thus, functional. Gene expression patterns have implicated these lincRNAs in diverse biological processes, including cell-cycle regulation, immune surveillance, and embryonic stem cell pluripotency. However, the mechanism by which these lincRNAs function is unknown. Here, we expand the catalog of human lincRNAs to ≈3,300 by analyzing chromatin-state maps of various human cell types. Inspired by the observation that the well-characterized lincRNA HOTAIR binds the polycomb repressive complex (PRC)2, we tested whether many lincRNAs are physically associated with PRC2. Remarkably, we observe that ≈20% of lincRNAs expressed in various cell types are bound by PRC2, and that additional lincRNAs are bound by other chromatin-modifying complexes. Also, we show that siRNA-mediated depletion of certain lincRNAs associated with PRC2 leads to changes in gene expression, and that the up-regulated genes are enriched for those normally silenced by PRC2. We propose a model in which some lincRNAs guide chromatin-modifying complexes to specific genomic loci to regulate gene expression.
---
paper_title: mirMark: a site-level and UTR-level classifier for miRNA target prediction

paper_content:

MiRNAs play important roles in many diseases including cancers. However computational prediction of miRNA target genes is challenging and the accuracies of existing methods remain poor. We report mirMark, a new machine learning-based method of miRNA target prediction at the site and UTR levels. This method uses experimentally verified miRNA targets from miRecords and mirTarBase as training sets and considers over 700 features. By combining Correlation-based Feature Selection with a variety of statistical or machine learning methods for the site- and UTR-level classifiers, mirMark significantly improves the overall predictive performance compared to existing publicly available methods. MirMark is available from https://github.com/lanagarmire/MirMark.
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paper_title: Modelling gene expression data using dynamic bayesian networks

paper_content:

Recently, there has been much interest in reverse engineering genetic networks from time series data. In this paper, we show that most of the proposed discrete time models — including the boolean network model [Kau93, SS96], the linear model of D’haeseleer et al. [DWFS99], and the nonlinear model of Weaver et al. [WWS99] — are all special cases of a general class of models called Dynamic Bayesian Networks (DBNs). The advantages of DBNs include the ability to model stochasticity, to incorporate prior knowledge, and to handle hidden variables and missing data in a principled way. This paper provides a review of techniques for learning DBNs.
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paper_title: LncRNA2Target: a database for differentially expressed genes after lncRNA knockdown or overexpression

paper_content:

Long non-coding RNAs (lncRNAs) have emerged as critical regulators of genes at epigenetic, transcriptional and post-transcriptional levels, yet what genes are regulated by a specific lncRNA remains to be characterized. To assess the effects of the lncRNA on gene expression, an increasing number of researchers profiled the genome-wide or individual gene expression level change after knocking down or overexpressing the lncRNA. Herein, we describe a curated database named LncRNA2Target, which stores lncRNA-to-target genes and is publicly accessible at http://www.lncrna2target.org. A gene was considered as a target of a lncRNA if it is differentially expressed after the lncRNA knockdown or overexpression. LncRNA2Target provides a web interface through which its users can search for the targets of a particular lncRNA or for the lncRNAs that target a particular gene. Both search types are performed either by browsing a provided catalog of lncRNA names or by inserting lncRNA/target gene IDs/names in a search box.
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paper_title: Methods for comprehensive experimental identification of RNA-protein interactions

paper_content:

The importance of RNA-protein interactions in controlling mRNA regulation and non-coding RNA function is increasingly appreciated. A variety of methods exist to comprehensively define RNA-protein interactions. We describe these methods and the considerations required for designing and interpreting these experiments.
---
paper_title: Catalogues of mammalian long noncoding RNAs: modest conservation and incompleteness

paper_content:

BackgroundDespite increasing interest in the noncoding fraction of transcriptomes, the number, species-conservation and functions, if any, of many non-protein-coding transcripts remain to be discovered. Two extensive long intergenic noncoding RNA (ncRNA) transcript catalogues are now available for mouse: over 3,000 macroRNAs identified by cDNA sequencing, and 1,600 long intergenic noncoding RNA (lincRNA) intervals that are predicted from chromatin-state maps. Previously we showed that macroRNAs tend to be more highly conserved than putatively neutral sequence, although only 5% of bases are predicted as constrained. By contrast, over a thousand lincRNAs were reported as being highly conserved. This apparent difference may account for the surprisingly small fraction (11%) of transcripts that are represented in both catalogues. Here we sought to resolve the reported discrepancy between the evolutionary rates for these two sets.ResultsOur analyses reveal lincRNA and macroRNA exon sequences to be subject to the same relatively low degree of sequence constraint. Nonetheless, our observations are consistent with the functionality of a fraction of ncRNA in these sets, with up to a quarter of ncRNA exons having evolved significantly slower than neighboring neutral sequence. The more tissue-specific macroRNAs are enriched in predicted RNA secondary structures and thus may often act in trans, whereas the more highly and broadly expressed lincRNAs appear more likely to act in the cis-regulation of adjacent transcription factor genes.ConclusionsTaken together, our results indicate that each of the two ncRNA catalogues unevenly and lightly samples the true, much larger, ncRNA repertoire of the mouse.
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Title: Non-coding yet non-trivial: a review on the computational genomics of lincRNAs

Section 1: Introduction
Description 1: Provide a broad overview of the significance of long intergenic noncoding RNAs (lincRNAs) in genomic regulation and gene expression, discussing the gaps in traditional understanding and the emerging roles of lincRNAs.

Section 2: Emerging characteristics of lincRNAs
Description 2: Discuss the defining characteristics and unique features of lincRNAs, including their expression patterns, tissue specificity, and secondary structure conservation.

Section 3: Genome-wide detection of lincRNAs
Description 3: Describe the various high-throughput experimental techniques used to detect lincRNAs, such as ChIP-Seq and RNA-Seq, and highlight the challenges and strategies for accurate lincRNA detection.

Section 4: Computational methods to predict lincRNAs
Description 4: Elaborate on computational approaches and pipelines used to predict lincRNAs from RNA-Seq data, including quality control, coding potential assessment, and machine learning methods.

Section 5: lincRNA databases
Description 5: Review existing databases dedicated to lincRNAs and their annotations, and discuss their importance for functional analysis and genomic research.

Section 6: Genomic assays to study lincRNA regulations
Description 6: Detail the genomic techniques employed to study the regulatory roles of lincRNAs, such as RNA immunoprecipitation (RIP) and DNA-centric methods.

Section 7: Known functions and mechanisms of lincRNAs
Description 7: Outline the various known mechanisms by which lincRNAs influence gene expression, such as chromatin remodeling, acting as transcription co-factors, the ceRNA hypothesis, and their roles as evolutionary reservoirs.

Section 8: Computational methods for lincRNA target prediction
Description 8: Discuss computational strategies for predicting lincRNA targets and functions, including correlation studies, microRNA interaction analysis, machine learning approaches, and structural prediction.

Section 9: Conclusion
Description 9: Summarize the current state of research, emphasizing the need for improved experimental techniques and comprehensive databases to enhance lincRNA functional predictions and genomic understanding.