Dataset Information

Quantitative profiling of peptides from RNAs classified as noncoding.

ABSTRACT: Only a small fraction of the mammalian genome codes for messenger RNAs destined to be translated into proteins, and it is generally assumed that a large portion of transcribed sequences--including introns and several classes of noncoding RNAs (ncRNAs)--do not give rise to peptide products. A systematic examination of translation and physiological regulation of ncRNAs has not been conducted. Here we use computational methods to identify the products of non-canonical translation in mouse neurons by analysing unannotated transcripts in combination with proteomic data. This study supports the existence of non-canonical translation products from both intragenic and extragenic genomic regions, including peptides derived from antisense transcripts and introns. Moreover, the studied novel translation products exhibit temporal regulation similar to that of proteins known to be involved in neuronal activity processes. These observations highlight a potentially large and complex set of biologically regulated translational events from transcripts formerly thought to lack coding potential.

SUBMITTER: Prabakaran S

PROVIDER: S-EPMC4416701 | biostudies-literature | 2014 Nov

REPOSITORIES: biostudies-literature

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Quantitative profiling of peptides from RNAs classified as noncoding.

Prabakaran Sudhakaran S Hemberg Martin M Chauhan Ruchi R Winter Dominic D Tweedie-Cullen Ry Y RY Dittrich Christian C Hong Elizabeth E Gunawardena Jeremy J Steen Hanno H Kreiman Gabriel G Steen Judith A JA

Nature communications 20141118

Only a small fraction of the mammalian genome codes for messenger RNAs destined to be translated into proteins, and it is generally assumed that a large portion of transcribed sequences--including introns and several classes of noncoding RNAs (ncRNAs)--do not give rise to peptide products. A systematic examination of translation and physiological regulation of ncRNAs has not been conducted. Here we use computational methods to identify the products of non-canonical translation in mouse neurons b ...[more]

PMID: 25403355

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Project description:Long non-coding RNAs (lncRNAs) are generally defined as RNA transcripts longer than 200 nucleotides that are not translated into proteins. Recently, many small open reading frames (smORFs) embedded in lncRNA scripts have been verified to be able to encode functional polypeptides (namely lncRNA-SEPs here). Although collaborative analysis by advanced genomics, bioinformatics and proteomics largely drives SEPs discovery, the poor predictability, diminutive size and low abundance still challenge systematic identification of SEPs from different biological samples. Here, we took advantage of the NONCODE database that deposited with the most complete collection and annotation of lncRNA transcripts from different species to build a database that to maximally collect all putative small ORFs from human and mouse lncRNA transcripts. Two effective and complementary polypeptides enrichment strategies (30 kDa MWCO filter and C8 SPE column) were also integrated to further improve the discovery of novel lncRNA-SEPs. These efforts led to the discovery of 362 lncRNA-SEPs from 8 human cell lines and 238 lncRNA-SEPs from 3 mouse cell lines and 8 mouse tissues. 18 out of these lncRNA-SEPs were verified experimentally by multiple technologies including in vitro expression, immunoblotting and parallel reaction monitoring-based mass spectrometry (PRM-MS) in 293T cells. Further bioinformatic analysis reveals that the physical and chemical properties of these novel lncRNA-SEPs, such as amino acid composition and codon usage, are varied from canonical proteins. Intriguingly, nearly 70% of the identified lncRNA-SEPs were found to be initiated with non-AUG start codons. Collectively, the efficient workflows presented in this study enables us identify 600 novel lncRNA-SPEs from multiple cell lines and tissues, which should represent the largest number of MS-detected lncRNA-encoding SEPs ever reported to date. These novel lncRNA-SEPs not only could provide new clues for the annotation of the noncoding elements in the genome, but also could serve as a valuable resource for the functional characterization of individual lncRNA-SEPs.

Dataset Information

Quantitative profiling of peptides from RNAs classified as noncoding.

Publications

Quantitative profiling of peptides from RNAs classified as noncoding.

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