Differentiating Protein-Coding and Noncoding RNA: Challenges and Ambiguities

By Marcel E. Dinger, Ken C. Pang, Tim R. Mercer, John S. Mattick. PLoS Comput. Biol., 2008

554 citations recorded by the source corpus.

The assumption that RNA can be readily classified into either protein-coding or non-protein–coding categories has pervaded biology for close to 50 years. Until recently, discrimination between these two categories was relatively straightforward: most transcripts were clearly identifiable as protein-coding messenger RNAs (mRNAs), and readily distinguished from the small number of well-characterized non-protein–coding RNAs (ncRNAs), such as transfer, ribosomal, and spliceosomal RNAs. Recent genome-wide studies have revealed the existence of thousands of noncoding transcripts, whose function and significance are unclear. The discovery of this hidden transcriptome and the implicit challenge it presents to our understanding of the expression and regulation of genetic information has made the need to distinguish between mRNAs and ncRNAs both more pressing and more complicated. In this Review, we consider the diverse strategies employed to discriminate between protein-coding and noncoding transcripts and the fundamental difficulties that are inherent in what may superficially appear to be a simple problem. Misannotations can also run in both directions: some ncRNAs may actually encode peptides, and some of those currently thought to do so may not. Moreover, recent studies have shown that some RNAs can function both as mRNAs and intrinsically as functional ncRNAs, which may be a relatively widespread phenomenon. We conclude that it is difficult to annotate an RNA unequivocally as protein-coding or noncoding, with overlapping protein-coding and noncoding transcripts further confounding this distinction. In addition, the finding that some transcripts can function both intrinsically at the RNA level and to encode proteins suggests a false dichotomy between mRNAs and ncRNAs. Therefore, the functionality of any transcript at the RNA level should not be discounted.

Subfields: Cancer Research, Molecular Biology

View Paper: https://www.semanticscholar.org/paper/6fe8abaa14f7136dd26299e884332592448fd6c9

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Citations in the corpus

Evolution and functions of long noncoding RNAs. (2009, background): “(Methods that seek to distinguish coding from noncoding transcripts are reviewed elsewhere; see Dinger et al., 2008.)”
Non‐coding RNAs: regulators of disease (2010, background): “Indeed, there is increasing evidence to suggest that mRNAs contain extensive RNA structural features [120,121], raising the possibility that, in addition to their protein-coding functions, mRNAs may intrinsically act as regulatory RNAs [122].”
CPAT: Coding-Potential Assessment Tool using an alignment-free logistic regression model (2013, background): “These include maximum ORF size, dinucleotide usage, codon usage bias, hexamer usage bias, nucleotide composition bias between codon positions and imperfect periodicity in base occurrences (23,26).”
The Genetic Signatures of Noncoding RNAs (2009, background): “-acting regulatory elements, may be incorrect, and there may be a false dichotomy between coding and noncoding RNA”
lncRNAdb v2.0: expanding the reference database for functional long noncoding RNAs (2014, methodology): “Text preprocessing was conducted by an in-house script (available at http://lncrnadb. org/help) and the word cloud was created with R package ‘tm’ (v.0.6) and ‘wordcloud’ (v.2.5). protein-coding genes (30,38–40).”
The GENCODE v7 catalog of human long noncoding RNAs: Analysis of their gene structure, evolution, and expression (2012, result): “In accordance with previous microarray studies (Dinger et al. 2008) and RNA-seq (Fig.”
Genome-wide computational identification and manual annotation of human long noncoding RNA genes. (2010, background): “In particular, while recent studies have focused on cataloging mouse lncRNAs (Dinger et al. 2008a; Ponjavic et al. 2009), there is no available comprehensive catalog of human lncRNAs.”
Sequence Analysis (2020, unknown): “While performing conventional bulk RNA sequencing, these technologies also allow to detect barcode sequences, which are identical for all read pairs sequenced from the same mRNA molecule.”
lincRNAs: Genomics, Evolution, and Mechanisms (2013, unknown): “Due to their considerable lengths, many lincRNAs should by chance contain an ORF of at least 100 aa (Dinger et al., 2008).”