Thody, Joshua, Folkes, Leighton and Moulton, Vincent ORCID: https://orcid.org/0000-0001-9371-6435 (2020) NATpare: a pipeline for high-throughput prediction and functional analysis of nat-siRNAs. Nucleic Acids Research, 48 (12). 6481–6490. ISSN 0305-1048
Preview |
PDF (Published_Version)
- Published Version
Available under License Creative Commons Attribution. Download (277kB) | Preview |
Abstract
Natural antisense transcript-derived small interfering RNAs (nat-siRNAs) are a class of functional small RNA (sRNA) that have been found in both plant and animals kingdoms. In plants, these sRNAs have been shown to suppress the translation of messenger RNAs (mRNAs) by directing the RNA-induced silencing complex (RISC) to their sequence-specific mRNA target(s). Current computational tools for classification of nat-siRNAs are limited in number and can be computationally infeasible to use. In addition, current methods do not provide any indication of the function of the predicted nat-siRNAs. Here, we present a new software pipeline, called NATpare, for prediction and functional analysis of nat-siRNAs using sRNA and degradome sequencing data. Based on our benchmarking in multiple plant species, NATpare substantially reduces the time required to perform prediction with minimal resource requirements allowing for comprehensive analysis of nat-siRNAs in larger and more complex organisms for the first time. We then exemplify the use of NATpare by identifying tissue and stress specific nat-siRNAs in multiple Arabidopsis thaliana datasets.
Item Type: | Article |
---|---|
Faculty \ School: | Faculty of Science > School of Computing Sciences Faculty of Science > School of Biological Sciences |
UEA Research Groups: | Faculty of Science > Research Groups > Computational Biology Faculty of Science > Research Groups > Norwich Epidemiology Centre Faculty of Medicine and Health Sciences > Research Groups > Norwich Epidemiology Centre |
Depositing User: | LivePure Connector |
Date Deposited: | 03 Jun 2020 00:13 |
Last Modified: | 25 Sep 2024 14:43 |
URI: | https://ueaeprints.uea.ac.uk/id/eprint/75447 |
DOI: | 10.1093/nar/gkaa448 |
Downloads
Downloads per month over past year
Actions (login required)
View Item |