Evidence map›Paper›PMID 25326325›Full record

ArticleNucleic acids research2014

Mapping overlapping functional elements embedded within the protein-coding regions of RNA viruses.

Andrew E Firth

Open access · goldAbstract read
In one paragraph

Article in Nucleic acids research, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 67 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
67citing papers in PubMed, 1 pooled it
10.7field-weighted citation impact, top 2% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

67 citing papers in PubMed, 1 synthesis or guideline pooled it, 111 citations in OpenAlex.

  1. Pooled it
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  20. RNA biology · 2023
    Article

7 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

1 author at 1 institution in 1 country.

Andrew E FirthDivision of Virology, Department of Pathology, University of Cambridge, Cambridge CB2 1QP, UK aef24@cam.ac.uk.
University of Cambridge · GB

Funding

Biotechnology and Biological Sciences Research Council BB/J007072/1Biotechnology and Biological Sciences Research Council BB/J015652/1Wellcome Trust 088789
6 · The paper itself

Abstract

Identification of the full complement of genes and other functional elements in any virus is crucial to fully understand its molecular biology and guide the development of effective control strategies. RNA viruses have compact multifunctional genomes that frequently contain overlapping genes and non-coding functional elements embedded within protein-coding sequences. Overlapping features often escape detection because it can be difficult to disentangle the multiple roles of the constituent nucleotides via mutational analyses, while high-throughput experimental techniques are often unable to distinguish functional elements from incidental features. However, RNA viruses evolve very rapidly so that, even within a single species, substitutions rapidly accumulate at neutral or near-neutral sites providing great potential for comparative genomics to distinguish the signature of purifying selection. Computationally identified features can then be efficiently targeted for experimental analysis. Here we analyze alignments of protein-coding virus sequences to identify regions where there is a statistically significant reduction in the degree of variability at synonymous sites, a characteristic signature of overlapping functional elements. Having previously tested this technique by experimental verification of discoveries in selected viruses, we now analyze sequence alignments for ∼700 RNA virus species to identify hundreds of such regions, many of which have not been previously described.

Indexed as

AlgorithmsCodonGenetic VariationGenome, ViralPhylogenyRecombination, GeneticRNA VirusesSequence AlignmentViral ProteinsCodonViral Proteins

Identifiers

PMID25326325
PMCPMC4227794
OpenAlexW2096363048

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.