Evidence map›Paper›PMID 25230983›Full record

ArticleJournal of applied genetics2015

The characteristics of the porcine (Sus scrofa) liver miRNAome with the use of next generation sequencing.

Klaudia Pawlina, Artur Gurgul, Maria Oczkowicz, Monika Bugno-Poniewierska

Abstract read
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In one paragraph

Article in Journal of applied genetics, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
0.3field-weighted citation impact, top 38% 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

3 citing papers in PubMed, 5 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

4 authors at 1 institution in 1 country.

Klaudia PawlinaLaboratory of Genomics, National Research Institute of Animal Production, Krakowska 1, 32-083, Balice n. Krakow, Poland, klaudia.pawlina@izoo.krakow.pl.
Artur Gurgul
Maria Oczkowicz
Monika Bugno-Poniewierska
National Research Institute of Animal Production · PL

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

MicroRNAs (miRNAs) are a class of small, noncoding RNAs, which play a vital role in the regulation of gene expression by binding to the 3' untranslated region (3'UTR) of a target mRNA. Despite a significant improvement in the identification of miRNAs in a variety of species, the coverage of the porcine miRNAome is still scarce. To identify porcine miRNAs potentially regulating processes taking place in the liver, we applied next generation sequencing. As a result, we detected 206 distinct miRNAs, of which 68 represented potential novel miRNAs. Among these new miRNAs, there were miRNAs deriving from the opposite arm of a hairpin precursor of already known miRNAs. Moreover, we observed 3' and 5' length and sequence variants, probably constituting so called isomiRs, as well as differentially mapped precursor loci, alternative precursor sequences and clustering of miRNA encoding genes. On the basis of expression levels, reflected by the number of sequence reads, we identified the most abundant miRNAs followed by gene target prediction and pathway analysis. The enriched pathways were connected with cellular and metabolic processes, growth factors as well as enzymatic activity. The obtained results are the first ones to concern the porcine liver miRNAome. Consequently, they will increase the number of known porcine miRNAs and facilitate further research on gene regulation mechanisms as well as biological processes associated with the liver functioning in pigs.

Indexed as

High-Throughput Nucleotide SequencingAnimalsBase SequenceComputational BiologyGene LibraryLiverMicroRNAsMolecular Sequence DataNucleic Acid ConformationSequence Analysis, RNASus scrofaMicroRNAs

Identifiers

PMID25230983
OpenAlexW2091331633

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.