Evidence map›Paper›PMID 24515651›Full record

ArticleGenetica2014

Evolutionary comparisons of miRNA regulation system in six model organisms.

Xiaofan Mao, Li Li, Yicheng Cao

Abstract readComparative Study
PubMed Publisher
In one paragraph

Article in Genetica, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.2field-weighted citation impact, top 42% 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

1 citing paper in PubMed, 7 citations in OpenAlex.

  1. 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

3 authors at 1 institution in 1 country.

Xiaofan MaoSchool of Bioscience and Bioengineering, Higher Education Mega Center, South China University of Technology, Guangzhou, 510006, China, mao.xf@mail.scut.edu.cn.
Li Li
Yicheng Cao
South China University of Technology · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

miRNAs are a class of endogenous small non-coding regulatory RNAs, that can mediate the transcriptional gene silencing as well as gene expression activation. miRNAs, which are found in a wide range of species, participate in cell differentiation, proliferation, development, apoptosis, tumorigenesis, metabolism, immune system, and signaling pathways. Here, we focused on the relationship between evolution and the miRNA system, with an emphasis on both miRNAs and their target genes. Six species from the evolutionary ladder were selected as a focus of this study. Public data were retrieved and combined to compare miRNAs abundance, miRNA families, molecular functions of target genes, biological processes of target genes, protein families of target gene products, transcription factors regulated by the miRNAs, signaling pathways and tissues across the six species. We found that the expansion rate of miRNAs was significantly higher compared to other genes in human evolution. Newborn miRNA families, which were quantitatively larger than dead miRNA families, seem to be closely related to the species complexity and tissue specificity. Additionally, miRNAs in higher order species were more likely to target genes related to signaling and the immune system, while miRNAs from lower order species preferred to target genes related to the embryonic development process, reproduction and growth. Meanwhile, miRNA systems displayed diversity in regulating transcription factors, signaling pathways and tissues. Our research suggested that the miRNA system might promote evolution, especially in higher species.

Indexed as

Evolution, MolecularGene Expression RegulationAnimalsGenesHumansMicroRNAsModels, AnimalMultigene FamilyOrgan SpecificityPhylogenySignal TransductionTranscription FactorsMicroRNAsTranscription Factors

Identifiers

PMID24515651
OpenAlexW2066194059

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.