sRNATargetDigger

sRNATargetDigger identifies sRNA-target gene pairs and co-regulatory relationships using high-throughput sequencing (HTS) and degradome sequencing data to map miRNA, ta-siRNA, and siRNA regulatory networks in plants.


Key Features:

  • Bidirectional Identification: Two modules, Forward Digger and Reverse Digger, identify sRNA-target pairs starting from known sRNAs or from known target genes.
  • Co-regulatory Network Analysis: Detects unknown sRNAs that co-regulate the same target gene, enabling identification of multi-sRNA co-regulation.
  • Integration with Sequencing Data: Leverages high-throughput sequencing (HTS) and degradome sequencing data for large-scale mining of sRNA-target pairs.

Scientific Applications:

  • Plant regulatory network mapping: Identification of known and novel sRNA-target interactions to study sRNA-mediated control of development, metabolism, and disease resistance in plants.

Methodology:

Computational pipeline uses two modules (Forward Digger and Reverse Digger) to integrate high-throughput sequencing (HTS) and degradome sequencing data for sRNA-target pair identification and co-regulatory relationship detection, and was validated by re-examination of published sRNA-target pairs in Arabidopsis thaliana where 170 novel co-regulatory pairs were identified.

Topics

Details

Added:
1/18/2021
Last Updated:
11/24/2024

Operations

Publications

Ye X, Yang Z, Jiang Y, Yu L, Guo R, Meng Y, Shao C. sRNATargetDigger: A bioinformatics software for bidirectional identification of sRNA-target pairs with co-regulatory sRNAs information. PLOS ONE. 2020;15(12):e0244480. doi:10.1371/journal.pone.0244480. PMID:33370386. PMCID:PMC7769420.

PMID: 33370386
PMCID: PMC7769420
Funding: - National Natural Science Foundation of China: 31771457, 31801102, 31970637 - Zhejiang Provincial Natural Science Foundation of China: LY17C190001 - Public Welfare Technology Application Research Project of Zhejiang Province: 2016C33193