Dr Evgeniia Golovina (far left in the group photo above) is a computational geneticist at the Liggins Institute at the University of Auckland. She and her colleagues use Mahuika to interpret genetic variation within the context of the 3D genome structure.

3D genome modelling for complex diseases

“Analysing this type of data is very computationally heavy. Last week I analysed seven new data sets in two days. Now we have additional 3D structured genome data sets from different tissues and cell types. It is amazing.”

The Challenge:
The 3D human genome structure affects how human cells express themselves. But this is a new, largely unstudied field of science that requires enormous computing power.

The Solution:
NeSI provides computing power and pipeline support to develop 3D models of different cellular genome structures. These models show how mutations in distant areas could affect gene expression and impact health.

The Outcome:
Geneticists established a genome structure database of 77 different cell types. The database provides valuable insights into how differences in structure may affect complex phenotypes including mood disorders, alcohol dependence and other conditions. Through this work, New Zealand researchers are making valuable contributions to a new science field.

 

A New Zealand genomics lab is working on a new field of science with the potential to help improve our understanding of complex diseases (including mental health conditions) and transform how we view genetics. Dr Evgeniia Golovina is a computational geneticist at Genomics and System Biology lab in the Liggins Institute at the University of Auckland. She studies how the 3D structure of the human genome can affect our bodies and minds.

Geneticists study the sequence of nucleotides in DNA to determine how our genes affect our bodies. These nucleotides are four molecules commonly referred to as A, T, C, G, paired into the famous shape of the double helix. This helix folds up within the nucleus of each human cell, but the way it packs into the nucleus differs depending on the cell type, so the folding pattern of the DNA in a brain cell genome is different to what is seen in a skin cell. This folding pattern affects how cells read their DNA, which then affects how our cells grow and behave.

“Traditionally studies looked at the DNA as a linear sequence, but this ignored the information that is encoded within the 3D structure. This additional information that is within the 3D genome structure is very important, because it's highly tissue-specific.” says Evgeniia.

Evgeniia works with Professor O’Sullivan and fellow researchers in the Genomics and System Biology lab in the Liggins Institute. They use NeSI’s Mahuika supercomputer to interpret genetic variation within the context of the 3D genome structure.

“We use the folded structure of the genome to identify if the region of DNA containing the mutation physically interacts with any genes in 3D. If the regions physically interact this can affect how the gene is turned on and off.” 

NeSI helped Evgeniia by providing the HPC infrastructure to help tackle this problem. 3D modelling and genome analysis are both compute-heavy tasks. Each file containing the captured 3D genome structural data can range between 30-50 gigabytes in size. With multiple replicates and 77 different cell types to compute, this would take months of processing on standard computers.

“Analyzing this type of data is very computationally heavy. Last week I analysed seven new data sets in two days. Now we have additional 3D structured genome data sets from different tissues and cell types. It is amazing.”

The Genomics and System Biology Lab’s recent research into genomic alcohol dependence identified some surprising results. It discovered the ADH genes that code the alcohol breakdown proteins in the body was more active in body fat and intestinal tissues. The lab used 3D genome analysis to help interpret how genetic variation might impact on these changes in gene activity. This research highlights the potential importance of the team’s work. A 2018 New Zealand Ministry of Health report found one-in-five New Zealanders consume alcohol in a way harmful to themselves or others. NeSI supported this work, which provides new insights into how genetic variation may affect our vulnerability to alcohol.

“NeSI helped me adjust an open-source pipeline for use on the supercomputer. I’ve also contacted NeSI about how to make this adjusted pipeline available to other researchers,” says Evgeniia.

“We want our work to be reproducible. I work with NeSI to ensure that our analysis pipelines can be shared using Singularity and Docker. The idea is you could be an international researcher but still able to easily import the pipeline and run it automatically.”

The Genomics and System Biology Lab is researching how mutations in the non-coding genome region could affect many complex disorders (e.g. schizophrenia, Parkinson’s, COPD). This is an emerging research area with the potential to improve public health and give humanity a deeper understanding of our biology. But this kind of data-intensive research is impossible without HPC infrastructure and experts in data pipelines. NeSI provides these services so the New Zealand research community can continue to make global impacts.


Do you have an example of how NeSI support or platforms have supported your work? We’re always looking for projects to feature as a case study. Get in touch by emailing support@nesi.org.nz

 

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