Article

Extensive transcriptional heterogeneity revealed by isoform profiling

1] Genome Biology Unit, European Molecular Biology Laboratory (EMBL), Meyerhofstrasse 1, 69117 Heidelberg, Germany [2].
Nature (Impact Factor: 41.46). 04/2013; 497(7447). DOI: 10.1038/nature12121
Source: PubMed

ABSTRACT

Transcript function is determined by sequence elements arranged on an individual RNA molecule. Variation in transcripts can affect messenger RNA stability, localization and translation, or produce truncated proteins that differ in localization or function. Given the existence of overlapping, variable transcript isoforms, determining the functional impact of the transcriptome requires identification of full-length transcripts, rather than just the genomic regions that are transcribed. Here, by jointly determining both transcript ends for millions of RNA molecules, we reveal an extensive layer of isoform diversity previously hidden among overlapping RNA molecules. Variation in transcript boundaries seems to be the rule rather than the exception, even within a single population of yeast cells. Over 26 major transcript isoforms per protein-coding gene were expressed in yeast. Hundreds of short coding RNAs and truncated versions of proteins are concomitantly encoded by alternative transcript isoforms, increasing protein diversity. In addition, approximately 70% of genes express alternative isoforms that vary in post-transcriptional regulatory elements, and tandem genes frequently produce overlapping or even bicistronic transcripts. This extensive transcript diversity is generated by a relatively simple eukaryotic genome with limited splicing, and within a genetically homogeneous population of cells. Our findings have implications for genome compaction, evolution and phenotypic diversity between single cells. These data also indicate that isoform diversity as well as RNA abundance should be considered when assessing the functional repertoire of genomes.

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Available from: Vicent Pelechano, Apr 17, 2014
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    • "All other TSSCs were classified as intergenic (I in Supplementary files 1, 3). CUTs, XUTs, and SUTs constituting overlapping transcript populations, when a TSSC was assigned to a pervasive transcript annotated in more than one of these classes we arbitrarily associated the corresponding TSSC in priority to CUTs, then to XUTs and finally to SUTs. mRNA coordinates were extracted from data ofPelechano et al. (2013). ORFs, tRNAs, rRNAs, small nuclear RNAs (snRNAs), and sn(o)RNAs coordinates were retrieved from the SGD (http:// www.yeastgenome.org/). "
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    • "(E) NET-seq reads on sense or antisense strands genome-wide in GLU (red) or GAL (blue) for ORF-Ts with peak expression in phases of the YMC indicated. (G) Strand-specific TIF-seq (Pelechano et al., 2013), microarray and NET-seq data at the HMS2:BAT2 locus. Profiles from cells cultured in GLU or GAL on the Watson strand (top) or Crick strand (bottom) are shown. "
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    Full-text · Article · Nov 2014 · eLife Sciences
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    • "To overcome this limitation, tag-based methods able to detect the co-occurrence of a specific transcription start site and a polyadenylation site has been developed. Methods able to determine both ends are called RNA-PET [88] and TIF-Seq [89]. RNA-PET is a paired-end tag approach, where detection of both 3′ and 5′ ends occurs through paired-end sequencing. "
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    ABSTRACT: Technological advances in the sequencing field support in-depth characterization of the transcriptome. Here, we review genome-wide RNA sequencing methods used to investigate specific aspects of gene expression and its regulation, from transcription to RNA processing and translation. We discuss tag-based methods for studying transcription, alternative initiation and polyadenylation events, shotgun methods for detection of alternative splicing, full-length RNA sequencing for the determination of complete transcript structures, and targeted methods for studying the process of transcription and translation. With the ensemble of technologies available, it is now possible to obtain a comprehensive view on transcriptome complexity and the regulation of transcript diversity.
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