TrainMALTA

Harnessing the power of bioinformatics

Large volumes of biological data are constantly being generated as high-throughput sequencing technologies become increasingly accessible; yet there is often a backlog in the processing and analysis of this data. The TrainMALTA project provides training in bioinformatics analysis, enabling researchers to gain new insights into the genetic causes of disease, as Dr Rosienne Farrugia explains A wide range of bioinformatics techniques and software tools are available today, enabling researchers to draw new insights from biological datasets. The volume of data being generated and the rapid development of bioinformatics techniques means there is an ongoing need to provide high-quality training, an issue which lies at the core of the TrainMALTA project. “We saw a need to provide training, to improve local expertise in bioinformatics, with a specific focus on the analysis of high-throughput sequencing data including genomics, RNA transcriptomics and epigenetics work. We also aim to tie that in with our other ongoing research into the background of disease,” says Dr Rosienne Farrugia, the project’s Principal Investigator.

Bioinformatics is a key element of modern medical research, enabling scientists to analyse biological data in greater depth. “We focus on providing training in the use of informatics, command line open-source tools and high-throughput analysis pipelines, to query biological datasets. The main type of biological data sets that we are looking at are those generated from high throughput sequencing,” continues Dr Farrugia.

This could be whole exome or genome

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sequences from the DNA of a group of people, many with a specific condition. The power of informatics can then be applied to sieve through these huge volumes of data and investigate certain research questions; Dr Farrugia and her colleagues are looking at several biological datasets. “In one of the projects I work on together with Dr Stephanie Bezzina Wettinger, we study relatively rare diseases, and we try to identify the mutation or mutations giving rise to each disease,” she outlines. In another project researchers are investigating myocardial infarction (MI), a highly complex condition. “We usually look at pathways. Which pathways are affected?

Which pathways have accumulated changes?

We look at people who have had a heart attack and people who haven’t, and compare the data,” says Dr Farrugia. “In both of these cases, the rare diseases and MI, we need to query these big volumes of data in different ways, but always within a biological context of the specific condition. Informatics is being used in this way to gain a deeper understanding of biological processes. This cannot be done manually – nobody could manually sieve through all that data in a reasonable timeframe.”

High-throughput sequencing This is due not only to the volume of the data being generated, but also the complexity of it. With high-throughput sequencing, the DNA of an individual is effectively chopped up into many small fragments, which are then ‘read’ using appropriate chemistry. The data from all the fragments then have to be put together again, from which point researchers can start to analyse the data.

“Once the sequence has been put together again, we can start to draw comparisons and pull out a list of variants, a list of differences,” explains Dr Farrugia. With the project on MI, Dr Farrugia says researchers have a collection of approximately 1,000 individuals, including people who have had an MI and people who haven’t. “There may be millions of differences between a patient sample and the control. So you need to pull out these differences, and then find out the difference that is the cause of the condition,” she says.

“For a complex condition like MI, it will very rarely be a single causative mutation. So we look at individual pathways instead of the entire genome, and we investigate whether patients have differences in that pathway when compared to the controls.”

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A number of factors are known to increase the risk of MI, including diabetes, high lipid profile and obesity, which is an important consideration in terms of research into the underlying causes of the condition.

Researchers can look to identify the pathways which control these processes and then investigate them in greater depth; with the project looking at rare diseases, the risk factors are not always as clear. “A patient may present with the characteristics of a particular condition, but the differences between cases and control are not always clear. Sometimes you have to sift through the data, identify differences, and see whether it fits the phenotype, the presentation of the patient,” outlines Dr Farrugia. Bioinformatics techniques have an important role to play here, enabling researchers to analyse large volumes of data in great depth and under different models. “We can design different scenarios and run them all individually. A computer can run different scenarios and give us different possible outcomes after which we can identify which is the most likely,” says Dr Farrugia.

can understand the underlying biology, then you can design your algorithms, scripts or pipelines to address specific biological questions,” explains Dr Farrugia.

Training The priority in the project is to equip researchers with the inter-disciplinary skill sets that they need to analyse data. This includes not only the data from the University of Malta, but also other, publicly available datasets. “The beauty of the way genetics research is going right now is that many of these datasets are publicly available.

So you don’t always need to be tightly interlinked to a consortium to have access to data,” points out Dr Farrugia. Analysis of these data-sets could help researchers learn more about the underlying causes of disease, marking another step towards the wider goal of personalised medicine. “Identifying the genetic basis of a disease will mean that a patient will get put onto the ideal treatment earlier, rather than there having to be a trialand-error approach,” says Dr Farrugia.

“There have also been a lot of studies and

We focus on providing training in the use of informatics, command line open-source tools and high-throughput analysis pipelines, to query biological datasets. The main type of biological data sets that we are looking at are those generated from high throughput sequencing This is not what many of us would imagine as a core part of traditional medical training, underlining the importance of the project’s work and their commitment to sharing knowledge and expertise. The project is providing researchers with the opportunity to learn both how to analyse these datasets and to create novel analytical approaches, which Dr Farrugia hopes will help lay the foundations for future bioinformatics research at the University of Malta. “We see this as a starting point, to set up a core of bioinformatics expertise locally. We are looking into the possibility of setting up a number of post-graduate degree courses, so that we can continuously train more and more people in the bioinformatics field,” she says. This training needs to combine elements of different disciplines. “It’s important that people with an interest in bioinformatics also have an interest and a background in biology.

If you understand biological processes, if you

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investment in identifying novel pathways within particular diseases, so that the pharmaceutical industry can then target those pathways. Sometimes that pathway can be targeted by medication which is already available.”

This is a fast-moving area, and with more data being generated and new techniques emerging, Dr Farrugia believes there is a long-term need for continued training.

Along with training the next generation of scientists, Dr Farrugia also plans to do some functional work on their findings so far.

“When you do genetic testing, generate the data and analyse it, you then need to confirm that your findings actually have the expected functional effect.” she outlines. “So the next stages of the project – besides the training in bioinformatics and the actual analysis – is to then pull out interesting candidates and test them in functional assays, which the project is equipping us to do.”

At a glance Full Project Title Interdisciplinary Training in HighThroughput Sequencing, Bioinformatics and Model Systems: Moving towards Clinical applications of Genomics (TrainMALTA) Project Objectives The TrainMALTA Twinning action aims to enable capacity building in Malta through training on best-practices in bioinformatic analysis, integration of high-throughput sequencing (HTS) data and robust quantitative analytical methods within a biological and clinical context. The use of model systems: the zebrafish model and induced pluripotent stem cells (iPSCs) to validate HTS findings is also part of this training action.

Project Funding This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 692041.

Project Partners • The University of Malta • The University of Cambridge • The Katholieke Universiteit Leuven Contact Details Dr Rosienne Farrugia Researcher & Senior Lecturer Dept. Applied Biomedical Science Faculty of Health Sciences University of Malta T: +356 2340 1107 T: +356) 2340 3281 E: rosienne.farrugia@um.edu.mt E: trainmalta@um.edu.mt W: http://www.um.edu.mt/project/ trainmalta http://www.timesofmalta.com/articles/view/20160731/ life-features/My-genome-reading-the-entire-DNAsequence-of-an-individual.620594

Dr Rosienne Farrugia

Dr Rosienne Farrugia is a researcher and senior lecturer at the Department of Applied Biomedical Science, University of Malta. Her ongoing research interests focus on the application of high throughput sequencing to elucidate the genetic basis of disease; both rare diseases as well as common, complex diseases prevalent in the Maltese population.

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