Database Commons
Database Commons

a catalog of worldwide biological databases

Database Profile

Borealis DataVerse

General information

URL: https://borealisdata.ca/dataset.xhtml?persistentId=doi:10.5683/SP3/30DEXA
Full name:
Description: The database provides a comprehensive set of predicted miRNA in the soybean cyst nematode (SCN) genome, identified using a species-specific miRNA discovery pipeline. It includes predicted gene targets within SCN and investigates cross-kingdom interactions with soybean mRNA. The predictions are validated through various control experiments and are available through an open repository.
Year founded: 2023
Last update:
Version: v1.0
Accessibility:
Unaccessible
Country/Region: Canada

Classification & Tag

Data type:
RNA
Data object:
Database category:
Major species:
Keywords:

Contact information

University/Institution: Carleton University
Address: Department of Systems and Computer Engineering, Carleton University, Ottawa, K1S 5B6, Canada
City:
Province/State: Ottawa
Country/Region: Canada
Contact name (PI/Team): James R Green
Contact email (PI/Helpdesk): jrgreen@sce.carleton.ca

Publications

37848601
Species-specific microRNA discovery and target prediction in the soybean cyst nematode. [PMID: 37848601]
Ajila V, Colley L, Ste-Croix DT, Nissan N, Cober ER, Mimee B, Samanfar B, Green JR.

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 ).

Sci Rep. 2023:13(1) | 3 Citations (from Europe PMC, 2026-03-28)

Ranking

All databases:
5733/6932 (17.311%)
Gene genome and annotation:
1717/2039 (15.841%)
5733
Total Rank
2
Citations
0.667
z-index

Community reviews

Not Rated
Data quality & quantity:
Content organization & presentation
System accessibility & reliability:

Word cloud

Related Databases

Citing
Cited by

Record metadata

Created on: 2024-07-16
Curated by:
Miaomiao Wang [2024-08-30]
shaosen zhang [2024-07-19]
zheng luo [2024-07-16]