The landscape of long noncoding RNAs in the human transcriptome

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Abstract

Long noncoding RNAs (lncRNAs) are emerging as important regulators of tissue physiology and disease processes including cancer. To delineate genome-wide lncRNA expression, we curated 7,256 RNA sequencing (RNA-seq) libraries from tumors, normal tissues and cell lines comprising over 43 Tb of sequence from 25 independent studies. We applied ab initio assembly methodology to this data set, yielding a consensus human transcriptome of 91,013 expressed genes. Over 68% (58,648) of genes were classified as lncRNAs, of which 79% were previously unannotated. About 1% (597) of the lncRNAs harbored ultraconserved elements, and 7% (3,900) overlapped disease-associated SNPs. To prioritize lineage-specific, disease-associated lncRNA expression, we employed non-parametric differential expression testing and nominated 7,942 lineage- or cancer-associated lncRNA genes. The lncRNA landscape characterized here may shed light on normal biology and cancer pathogenesis and may be valuable for future biomarker development.

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Most cited references 14

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Ab initio reconstruction of transcriptomes of pluripotent and lineage committed cells reveals gene structures of thousands of lincRNAs

Mitchell Guttman, Manuel Garber, Joshua Levin … (2010)

RNA-Seq provides an unbiased way to study a transcriptome, including both coding and non-coding genes. To date, most RNA-Seq studies have critically depended on existing annotations, and thus focused on expression levels and variation in known transcripts. Here, we present Scripture, a method to reconstruct the transcriptome of a mammalian cell using only RNA-Seq reads and the genome sequence. We apply it to mouse embryonic stem cells, neuronal precursor cells, and lung fibroblasts to accurately reconstruct the full-length gene structures for the vast majority of known expressed genes. We identify substantial variation in protein-coding genes, including thousands of novel 5′-start sites, 3′-ends, and internal coding exons. We then determine the gene structures of over a thousand lincRNA and antisense loci. Our results open the way to direct experimental manipulation of thousands of non-coding RNAs, and demonstrate the power of ab initio reconstruction to render a comprehensive picture of mammalian transcriptomes.

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The evolution of lncRNA repertoires and expression patterns in tetrapods.

Anamaria Necsulea, Magali Soumillon, Maria Warnefors … (2014)

Only a very small fraction of long noncoding RNAs (lncRNAs) are well characterized. The evolutionary history of lncRNAs can provide insights into their functionality, but the absence of lncRNA annotations in non-model organisms has precluded comparative analyses. Here we present a large-scale evolutionary study of lncRNA repertoires and expression patterns, in 11 tetrapod species. We identify approximately 11,000 primate-specific lncRNAs and 2,500 highly conserved lncRNAs, including approximately 400 genes that are likely to have originated more than 300 million years ago. We find that lncRNAs, in particular ancient ones, are in general actively regulated and may function predominantly in embryonic development. Most lncRNAs evolve rapidly in terms of sequence and expression levels, but tissue specificities are often conserved. We compared expression patterns of homologous lncRNA and protein-coding families across tetrapods to reconstruct an evolutionarily conserved co-expression network. This network suggests potential functions for lncRNAs in fundamental processes such as spermatogenesis and synaptic transmission, but also in more specific mechanisms such as placenta development through microRNA production.

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Assessment of transcript reconstruction methods for RNA-seq

Tamara Steijger, Josep F Abril, Pär G. Engström … (2013)

RNA sequencing (RNA-seq) is transforming genome biology, enabling comprehensive transcriptome profiling with unprecendented accuracy and detail. Due to technical limitations of current high-throughput sequencing platforms, transcript identity, structure and expression level must be inferred programmatically from partial sequence reads of fragmented gene products. We evaluated 24 protocol variants of 14 independent computational methods for exon identification, transcript reconstruction and expression level quantification from RNA-seq data. Our results show that most algorithms are able to identify discrete transcript components with high success rates, but that assembly of complete isoform structures poses a major challenge even when all constituent elements are identified. Expression level estimates also varied widely across methods, even when based on similar transcript models. Consequently, the complexity of higher eukaryotic genomes imposes severe limitations in transcript recall and splice product discrimination that are likely to remain limiting factors for the analysis of current-generation RNA-seq data.