Evidence map›Paper›PMID 23887147›Full record

ArticleRNA (New York, N.Y.)2013

Computational detection of abundant long-range nucleotide covariation in Drosophila genomes.

Eckart Bindewald, Bruce A Shapiro

Abstract read
In one paragraph

Article in RNA (New York, N.Y.), 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
–field-weighted citation impact
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

5 citing papers in PubMed.

  1. Review
  2. Article
  3. Review
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  5. Article
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

2 authors.

Eckart BindewaldSAIC-Frederick, Incorporated, Center for Cancer Research Nanobiology Program, Frederick National Laboratory for Cancer Research, Frederick, Maryland 21702, USA.
Bruce A Shapiro

Funding

Computational Approaches for RNA StructureFunction DeterminationZIABC008382 · NCI · DIVISION OF BASIC SCIENCES - NCI · PI SHAPIRO, BRUCE · 2009 to 2021
$5.8M
CCR NIH HHS HHSN261200800001CIntramural NIH HHSNCI NIH HHS HHSN261200800001EPHS HHS 261200800001E
6 · The paper itself

Abstract

Functionally important nucleotide base-pairing often manifests itself in sequence alignments in the form of compensatory base changes (covariation). We developed a novel index-based computational method (CovaRNA) to detect long-range covariation on a genomic scale, as well as another computational method (CovStat) for determining the statistical significance of observed covariation patterns in alignment pairs. Here we present an all-versus-all search for nucleotide covariation in Drosophila genomic alignments. The search is genome wide, with the restriction that only alignments that correspond to euchromatic regions, which consist of at least 10 Drosophila species, are being considered (59% of the euchromatic genome of Drosophila melanogaster). We find that long-range covariations are especially prevalent between exons of mRNAs as well as noncoding RNAs; the majority of the observed covariations appear as not reverse complementary, but as synchronized mutations, which could be due to interactions with common interaction partners or due to the involvement of genomic elements that are antisense of annotated transcripts. The involved genes are enriched for functions related to regionalization as well as neural and developmental processes. These results are computational evidence that RNA-RNA long-range interactions are a widespread phenomenon that is of fundamental importance to a variety of cellular processes.

Indexed as

Genome, InsectAnimalsBase PairingComputational BiologyConserved SequenceDrosophilaMutationNucleotidesRNARNA, MessengerRNA, UntranslatedSequence AlignmentNucleotidesRNARNA, MessengerRNA, UntranslatedcovariationDrosophilainteraction networklong-range interactionsRNA–RNA

Identifiers

PMID23887147
PMCPMC3753924

What OpenQuestion holds

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Registered trials

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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.