Evidence map›Paper›PMID 30248141›Full record

ArticlePloS one2018

Characterization and comparative analysis of microRNAs in the rice pest Sogatella furcifera.

Zhao-Xia Chang, Ibukun A Akinyemi, Dong-Yang Guo, Qingfa Wu

Open access · goldAbstract readComparative Study
In one paragraph

Article in PloS one, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
0.1field-weighted citation impact, top 57% 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

4 citing papers in PubMed, 13 citations in OpenAlex.

  1. Article
  2. Article
  3. The lncRNA-mediated ceRNA network ofFrontiers in physiology · 2023
    Article
  4. Review
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

4 authors at 1 institution in 1 country.

Zhao-Xia ChangHefei National Laboratory for Physical Sciences at Microscale, University of Science and Technology of China, Hefei, China.
Ibukun A AkinyemiHefei National Laboratory for Physical Sciences at Microscale, University of Science and Technology of China, Hefei, China.
Dong-Yang GuoHefei National Laboratory for Physical Sciences at Microscale, University of Science and Technology of China, Hefei, China.
Qingfa WuHefei National Laboratory for Physical Sciences at Microscale, University of Science and Technology of China, Hefei, China.ORCID 0000-0001-5420-6213
University of Science and Technology of China · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

MicroRNAs (miRNAs) are a class of endogenous regulatory RNA molecules 21-24 nucleotides in length that act as functional regulators of post-transcriptional repression of messenger RNA. We report the identification and characterization of a conserved miRNA and 171 novel miRNAs in the migratory rice pest Sogatella furcifera by deep sequencing, which were observed to be biased towards female adults of the insect, modulating the functionality and targets of the miRNAs in sex differentiation. A switch in arm usage was also observed in 9 miRNA when compared to the insect ancestor during insect evolution. The miRNA loci showed high 5' fidelity in both miRNA and star species and about 93.4% of WBPH miRNAs conserved within non-planthopper species were homologous with planthopper species. The novel miRNAs identified in this study provide a better understanding of the sRNA and the regulatory role of miRNA in sexual dimorphism and alteration in the expression or function of miRNAs in the rice pest.

Indexed as

AnimalsConserved SequenceEvolution, MolecularFemaleHemipteraMaleMicroRNAsOryzaSequence Analysis, RNASex CharacteristicsMicroRNAs

Identifiers

PMID30248141
PMCPMC6152972
OpenAlexW2892418093

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.