Evidence map›Paper›PMID 31640745›Full record

ArticleBiology direct2019

Retrotransposon gag-like 1 (RTL1) and the molecular evolution of self-targeting imprinted microRNAs.

Avantika Mainieri, David Haig

Open access · goldAbstract read
In one paragraph

Article in Biology direct, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
1.3field-weighted citation impact, top 18% 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

6 citing papers in PubMed, 7 citations in OpenAlex.

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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 at 1 institution in 1 country.

Avantika MainieriDepartment of Organismic and Evolutionary Biology, Harvard University, Cambridge, MA, USA.
David HaigDepartment of Organismic and Evolutionary Biology, Harvard University, Cambridge, MA, USA. dhaig@oeb.harvard.edu.ORCID 0000-0001-7377-1605
Harvard University · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundTranscription of the antisense strand of RTL1 produces a sense mRNA that is targeted for degradation by antisense microRNAs transcribed from the sense strand. Translation of the mRNA produces a retrotransposon-derived protein that is implicated in placental development. The sense and antisense transcripts are oppositely imprinted: sense mRNAs are expressed from the paternally-derived chromosome, antisense microRNAs from the maternally-derived chromosome.

resultsTwo microRNAs at the RTL1 locus, miR-431 and the rodent-specific miR-434, are derived from within tandem repeats. We present an evolutionary model for the establishment of a new self-targeting microRNA derived from within a tandem repeat that inhibits production of RTL1 protein when maternally-derived in heterozygotes but not when paternally-derived.

conclusionsThe interaction of sense and antisense transcripts can be interpreted as a form of communication between maternally-derived and paternally-derived RTL1 alleles that possesses many of the features of a greenbeard effect. This interaction is evolutionary stable, unlike a typical greenbeard effect, because of the necessary complementarity between microRNAs and mRNA transcribed from opposite strands of the same double helix. We conjecture that microRNAs and mRNA cooperate to reduce demands on mothers when an allele is paired with itself in homozygous offspring. REVIEWERS: This article was reviewed by Eugene Berezikov and Bernard Crespi.

Indexed as

Evolution, MolecularRetroelementsAnimalsBase SequenceFemaleMammalsMicroRNAsPregnancyPregnancy ProteinsMicroRNAsPregnancy ProteinsRetroelementsRTL1 protein, humanRtl1 protein, mouseChloropogonologyGenomic imprintingGreenbeard effectProtein tandem repeats

Identifiers

PMID31640745
PMCPMC6805670
OpenAlexW2982142701

What OpenQuestion holds

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LicenceCC BY
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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.