University of Portsmouth Featured PhD Programmes
Anglia Ruskin University ARU Featured PhD Programmes

Massively parallel characterisation of viral microRNAs (MOXONS_U21SF)

School of Biological Sciences

About the Project

MicroRNAs (miRNAs) are a class of non-coding RNAs ~22nt in length known to play a pivotal role in the regulation of gene expression in animals. They bind to their targets by Watson-Crick base pairing, leading to translational inhibition, deadenylation, and eventual mRNA degradation. Some viruses can also encode miRNA sequences which are processed by their hosts on infection. These miRNAs can either regulate the viral lifecycle or disrupt host gene expression e.g. by downregulating key genes in the antiviral immune response. At present, very few viral miRNAs have been characterised and studied in detail. Characterisation and understanding of these important regulators are therefore of great importance in the study of human and animal disease. 

This studentship will use a combination of cutting-edge molecular and computational biology in order to classify viral miRNAs on an unparalleled scale. The project is cross-disciplinary and suitable for graduates in either computing or biological sciences.  

For more information on the supervisor for this project, please go here

This is a PhD programme. The start date is 1st October 2021. The mode of study is full time. The studentship length is 3 years. 

Entry requirements: Acceptable first degree 2:1 biological sciences, computer science, mathematics.

Applications are processed as soon as they are received and the project may be filled before the closing date, so early application is encouraged.

Funding Notes

This PhD project is offered on a self-funding basis. It is open to applicants with funding or those applying to funding sources. Details of tuition fees can be found at View Website
A bench fee is also payable on top of the tuition fee to cover specialist equipment or laboratory costs required for the research. Applicants should contact the primary supervisor for further information about the fee associated with the project.


i) Paicu, C., Mohorianu, I., Stocks, M., Xu, P., Coince, A., Billmeier, M., Dalmay, T., Moulton, V. and Moxon, S., 2017. miRCat2: accurate prediction of plant and animal microRNAs from next-generation sequencing datasets. Bioinformatics, 33(16), pp.2446-2454.
ii) FilTar: using RNA-Seq data to improve microRNA target prediction accuracy in animals. Bradley T, Moxon S. Bioinformatics. 2020. 36(8):2410-2416. doi: 10.1093/bioinformatics/btaa007.
iii) Ago2-Dependent Processing Allows miR-451 to Evade the Global MicroRNA Turnover Elicited during Erythropoiesis.Kretov DA, Walawalkar IA, Mora-Martin A, Shafik AM, Moxon S, Cifuentes D. Molecular Cell. 2020 78(2):317-328.e6. doi: 10.1016/j.molcel.2020.02.020.

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