Evidence map›Paper›PMID 37848601›Full record

ArticleScientific reports2023

Species-specific microRNA discovery and target prediction in the soybean cyst nematode.

Victoria Ajila, Laura Colley, Dave T Ste-Croix, Nour Nissan, Elroy R Cober, Benjamin Mimee, Bahram Samanfar, James R Green

Open access · goldAbstract read
In one paragraph

Article in Scientific reports, 2023. 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
1.2field-weighted citation impact, top 15% 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, 3 citations in OpenAlex.

  1. Review
  2. Review
  3. 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

8 authors at 3 institutions in 1 country.

Victoria AjilaDepartment of Systems and Computer Engineering, Carleton University, Ottawa, K1S 5B6, Canada.
Laura ColleyDepartment of Systems and Computer Engineering, Carleton University, Ottawa, K1S 5B6, Canada.
Dave T Ste-CroixSaint-Jean-sur-Richelieu Research and Development Centre, Agriculture and Agri-Food Canada, Saint-Jean-sur-Richelieu, J3B 7B5, Canada.
Nour NissanOttawa Research and Development Centre, Agriculture and Agri-Food Canada, Ottawa, K1A 0C6, Canada.
Elroy R CoberOttawa Research and Development Centre, Agriculture and Agri-Food Canada, Ottawa, K1A 0C6, Canada.
Benjamin MimeeSaint-Jean-sur-Richelieu Research and Development Centre, Agriculture and Agri-Food Canada, Saint-Jean-sur-Richelieu, J3B 7B5, Canada.
Bahram SamanfarOttawa Research and Development Centre, Agriculture and Agri-Food Canada, Ottawa, K1A 0C6, Canada.
James R GreenDepartment of Systems and Computer Engineering, Carleton University, Ottawa, K1S 5B6, Canada. jrgreen@sce.carleton.ca.
Agriculture and Agri-Food Canada · CACarleton University · CAOttawa Research and Development Centre

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The soybean cyst nematode (SCN) is a devastating pathogen for economic and food security considerations. Although the SCN genome has recently been sequenced, the presence of any miRNA has not been systematically explored and reported. This paper describes the development of a species-specific SCN miRNA discovery pipeline and its application to the SCN genome. Experiments on well-documented model nematodes (Caenorhabditis elegans and Pristionchus pacificus) are used to tune the pipeline's hyperparameters and confirm its recall and precision. Application to the SCN genome identifies 3342 high-confidence putative SCN miRNA. Prediction specificity within SCN is confirmed by applying the pipeline to RNA hairpins from known exonic regions of the SCN genome (i.e., sequences known to not be miRNA). Prediction recall is confirmed by building a positive control set of SCN miRNA, based on a limited deep sequencing experiment. Interestingly, a number of novel miRNA are predicted to be encoded within the intronic regions of effector genes, known to be involved in SCN parasitism, suggesting that these miRNA may also be involved in the infection process or virulence. Beyond miRNA discovery, gene targets within SCN are predicted for all high-confidence novel miRNA using a miRNA:mRNA target prediction system. Lastly, cross-kingdom miRNA targeting is investigated, where putative soybean mRNA targets are identified for novel SCN miRNA. All predicted miRNA and gene targets are made available in appendix and through a Borealis DataVerse open repository ( https://borealisdata.ca/dataset.xhtml?persistentId=doi:10.5683/SP3/30DEXA ).

Indexed as

MicroRNAsNematodaTylenchoideaAnimalsCaenorhabditis elegansGlycine maxPlant DiseasesRNA, MessengerMicroRNAsRNA, Messenger

Identifiers

PMID37848601
PMCPMC10582106
OpenAlexW4387705779

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.