Bioinformatics tools for the genome-wide analysis of small RNA interaction networks

Lead Research Organisation: University of East Anglia
Department Name: Computing Sciences

Abstract

This project involves the development of cutting-edge bioinformatics tools to analyse small RNAs. The discovery of small RNAs in plants and animals has revolutionised our knowledge gene regulation. However, although much progress has been made on certain small RNAs and their targets (such as microRNAs), very little is known about genome-wide scale small RNA regulatory networks. In this project, the student will work together with a unique combination of world-class experts in bioinformatics, genomics and small RNAs with the aim of identifying, validating and visualising regulatory interaction networks of small RNAs and their target genes. This will build on recent work developed in Moulton's group on genome-wide target identification and validation using the "degradome". In particular, the student will work on developing algorithms and computer programs for visualising and identifying small RNAs regulatory interaction networks in plants with Professors Vincent Moulton and Tamas Dalmay (UEA).

Studentship Projects

Project Reference Relationship Related To Start End Student Name
BB/M011216/1 01/10/2015 31/03/2024
1802507 Studentship BB/M011216/1 01/10/2016 30/09/2020 Joshua Thody
 
Description We Have developed a new method and software tool for identifying gene targets of small RNAs on a genome-wide scale using high-throughput sequencing data. Our method shows vast improvement in computation time and resource requirements compared to current methods, which enables genome-wide degradome analysis of larger and more complex organisms within a reasonable time frame for the very first time.

Since the publication of the above software, we have published another method that uses the same input data to infer targeting criteria for plant miRNAs. The inferred criteria are then incorporated into the previously published tool and performance evaluation show that the newly inferred criteria outperforms previously accepted criteira.
Exploitation Route Our new approach provides flexibility in modelling the dynamics of the small RNA-messenger RNA binding by allowing users to make adjustments in the rule-based edits and gaps within the duplex. We are the first to offer such flexibility within a degradome analysis context and this may open up new avenues of research in understanding the machinery of RNA-silencing.

We have now built on the about outcome and developed another tool that leverages the flexibility of the targeting criteria, which results in an increase in performance.
Sectors Other
 
Title PAREameters: a tool for computational inference of plant miRNA-mRNA targeting rules using small RNA and degradome sequencing data 
Description A first of its kind tool for the inference of plant miRNA targeting criteria from small RNA and degradome sequencing data. 
Type Of Technology Software 
Year Produced 2020 
Open Source License? Yes  
Impact Results show that inferred criteria outperforms criteria published in 2005. 
URL https://doi.org/10.1093/nar/gkz1234
 
Title PAREsnip2: a tool for high-throughput prediction of small RNA targets from degradome sequencing data using configurable targeting rules. 
Description New method and software tool for identifying gene targets of small RNAs on a genome-wide scale using high-throughput degradome sequencing data 
Type Of Technology Software 
Year Produced 2018 
Open Source License? Yes  
Impact Our method shows vast improvement in computation time and resource requirements compared to current methods, which enables genome-wide degradome analysis of larger and more complex organisms within a reasonable time frame for the very first time. Our new approach provides flexibility in modelling the dynamics of the small RNA-messenger RNA binding by allowing users to make adjustments in the rule-based edits and gaps within the duplex. We are the first to offer such flexibility within a degradome analysis context and this may open up new avenues of research in understanding the machinery of RNA-silencing. 
URL http://srna-workbench.cmp.uea.ac.uk/paresnip2/