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Staff Profile

Dr Louise Pease

Research Associate

  • Email: louise.pease2@ncl.ac.uk
  • Address: Translational & Clinical Research Institute
    Herschel Building
    Brewery Lane
    Newcastle University
    Newcastle Upon Tyne
    NE1 7RU
Background
My areas of particular interest are functional genomics, molecular biology, biotechnology, bioinformatics, genomic medicine, health, pollution and toxicology.  Following completion of a PhD in toxicogenomics, I have completed an MSc in Bioinformatics which has developed my computing skills, and broadened the range of tools I can use in the analysis of high throughput biological data.    I am applying and developing my expertise, and knowledge of molecular biology, genomics and bioinformatics through functional genomic studies leading to the development of improved techniques for producing and analysing results from omic technologies. 
Research
Newcastle University 2004 (PhD, School of Biology)

PhD Industrial CASE NERC studentship with AstraZeneca: Toxicogenomics, a transcriptomic approach to assess the toxicity of 4-nitrophenol to Saccharomyces cerevisiae.  I secured £2,800 funding from the Consortium for the functional genomics of microbial eukaryotes (COGEME) to carry out a pilot study that would ensure high quality gene expression results could be obtained using pre-selected experimental conditions. Methods for the generation of transcriptomic data from S. cerevisiae were refined generating highly significant results and eliminating previously reported confounders.  Gene expression was measured using Affymetrix microarrays and the results analysed using GeneSpring.  The project identified that 4-nitrophenol treatment disrupts iron handling and increases osmotic stress leading to a reduction in respiration and cell growth inhibition.  The results were supported by physical and chemical investigations into the effects 4-nitrophenol treatment on cells.  Supervised by; Ian Singleton, Ian Head, Simon Avery and Jason Snape.  

https://theses.ncl.ac.uk/jspui/bitstream/10443/1142/4/Pease%2C%20L.%202011.pdf

Newcastle University 2009

I undertook a range of part-time research projects focused on using Ozone to reduce food spoilage by microbes, a technique used by major supermarkets.

Newcastle University 2015 (MSc, School of Computing Science)

MSc Bioinformatics (Distinction) my research proposal detailed extending analysis of experimental data to publicly available omics data to increase the available replicates and compensate for a gender imbalance.  The project analysed epigenetic, transcriptomic and proteomic data and identified age and gender related changes in Mesenchymal Stem Cells and derived cells that may contribute to the development of arthritis, tendonitis and other degenerative diseases. 

Newcastle University 2015 (Bioinformatician, Centre for Ageing and Vitality)

Working on a self-employed basis within the Centre for Ageing and Vitality I extended the analysis of RNAseq data from tissue-engineered tendon to publicly available microarray and RNAseq data from tendon.  The project identified the importance of gender considerations in the analysis of transcriptomic data.  

Newcastle University 2016 - 2017 (Genome Analyst, Institute for Genetic Medicine)

Working as a genome analyst within the Institute for Genetic Medicine (IGM) mitochondrial diseases research group my main role was re-analysing exome sequence data from patients with rare diseases that were genetically unsolved.  My work identified a range of limitations and proposed solutions to further the field of variant analysis.  Additionally I developed batch analysis techniques that implicated compound heterozygous mutations in the development of rare diseases.   I investigated the role of mitochondrial haplotypes in the regulation of gene expression and the development of Parkinsons disease using RNA-seq data. 

Newcastle University 2017-2020 (Research Associate Bioinformatician, NICR - INSTINCT)

Working as a research bioinformatician within the Northern Institute for Cancer Research (NICR) in the high risk childhood brain tumours group I was funded by INSTINCT.  The aims of the project were to use high throughput omics technologies to determine the underlying molecular causes of brain tumours and determine the most viable targeted therapies. 

Patients with variety of syndromes (Gorlin, Turcot, Li-Fraumeni) have an increased risk of developing cancer (Parsons et al. 2011, Jones et al.2012).  These syndromes are associated with germline variants in TP53, PTCH1 and APC respectively (Parsons et al. 2011, Morissy et al .2016, Jones et al. 2012).  Thus far studies have used methods which focused on somatic changes (Parsons et al. 2012, Pugh et al. 2012, Andor et al. 2013, Robinson et al. 2012, Jones et al. 2012), on the basis of the assumption that cancer results from mutations acquired by the cells in the tumour.  Observed increases in cancer prevalence amongst patients with germline variants in the aforementioned genes violates this assumption.  Somatic based variant calling methods, whilst useful for reducing the search space, could miss underlying variants that increase risk.  Germline samples cannot be considered valid controls for tumours and paired analysis methods further confound the results, complicate analysis and may miss important variants already present in germline samples.  

For these reasons I developed novel unpaired variant calling methods which played to the strengths of whole genome sequencing data, these identified germline Copy Number Variants (CNVs) in sex chromosomes (previously removed prior to analyses) and mutations in TP53 and PTCH1 in childhood medulloblastoma whole genome sequencing data that correlated with the subgroup, severity of the tumour and were indicative of metastasis. The results were cross validated using age group, gender and subgroup specific de novo transcriptome assemblies, SNP6 and conumee methylation array CNV calls. Paired analysis methods were applied also confirming they were unable to detect variants present in more than one sample. Variant calling and heterogeneity assessment pipelines were adapted to complete unpaired analyses which identified subgroup specific germline variants at significant frequencies, the impacts of which were time dependent, with medulloblastoma being diagnosed at key developmental stages which coincided with changes in hormone levels. Functional analysis of CNVs, SNVs, transcriptomic and epigenetic data identified key roles for sex hormones, calcium and vitamin D in determining the age of disease onset, severity, and metastasis potential, highlighting the potential for new, less invasive treatments.  Disagreements over the validity of novel unpaired methods in conjunction with sex, subgroup and age group stratification; which permitted the inclusion of sex chromosomes in analyses, mean the work will not be published. 

Newcastle University 2020-current (Research Associate Bioinformatician, Centre for Ageing and Vitality)

Applying novel methods to the analysis of multi-omic data sets to improve our understanding of the molecular mechanisms underpinning ageing and the development of age related diseases. The results of which will be used to inform and calibrate systems biology protein network models for the purposes of better understanding the molecular mechanisms of ageing and disease development in a range of tissues and syndromes.  It is hoped that targeted interventions and therapies to enable healthy ageing can be designed. 


Teaching

Whilst studying for my PhD I worked part-time as a demonstrator for microbiology and animal behaviour practical’s, as well as completing unpaid supervision of MSc Industrial Biotechnology project students.  

I have additional hands-on and observational teaching experience gained in 2009 during the course of a PGCE at Sunderland University. 

I was registered as in instructor on the first two modules of the Genomic Medicine MSc providing support to staff and students.

Publications