Project Description

Dr Pamela Mukhopadhyay

 

Bioinformatician
QIMR Berghofer Medical Research Institute

MicroRNAs – sequencing, analysis … and then what?

Next generation sequencing & bioinformatics

Tuesday 5 July 2016

MicroRNAs (miRNAs) are an important class of non-coding regulatory RNAs, which interfere with the translation of protein-coding mRNA transcripts. By incorporation into the RNA induced silencing complex (RISC), miRNAs can inhibit translation, promote sequestration of mRNAs to P-bodies, and/or destabilize and degrade target mRNAs. The small size of mature miRNAs (typically only 20 to 24 nucleotides) makes them ideal for characterization using short-tag RNA-sequencing (RNA-seq) technologies as you can capture the entire molecule in a single read. Unlike hybridization approaches such as microarray profiling or Northern blotting, massive-scale sequencing provides a way to discriminate discrete but closely related RNA molecules, and profile miRNAs without a priori knowledge of expression.

MicroRNAs perform their biological roles by binding to mRNAs through Watson-Crick base-pairing. The attractive simplicity of using nucleotide complementarity to identify mRNA targets has given rise to many bioinformatics tools. These are based (to differing extents) on complementarity to the seed, evolutionary conservation, and free energy of binding.

So with great technology and plenty of well researched and well respected bioinformatics tools, miRNAs should be easy, right? This talk will systematically crush this rosy view of miRNAs as a field of study, and lay before you the desolate wasteland to navigate on your path to publication. Those towards the end of their PhD study on miRNAs may wish to avoid this talk.

Dr Pamela Mukhopadhyay received her PhD in Bioinformatics in 2010 from University of Jadavpur, India. Following this, she was a bioinformatician at Queensland Diamantina Institute working on various disease and cancer genomic and sequencing projects with Dr Paul Leo and has gained good knowledge on large scale GWAS studies. In 2013 she conducted her postdoctoral research at QIMR Berghofer Medical Research Institute on UV-induced melanoma mouse models and also to investigate the role of various genetic and epigenetic factors for X-chromosome inactivation in Smchd1 knock-out mouse.

Pamela’s area of expertise involves analysing next-generation sequencing data and developing algorithms and methods for genomic research. She has extensive experience working on R programming language. She also provides training on various techniques involving analysing next-generation sequencing data. Her current bioinformatician role involves providing bioinformatics support to QIMR Berghofer medical researchers and also to understand potential genomic signatures of UV-induced and spontaneous melanomas.