Many diseases are associated with changes to the DNA sequence, most notably cancer. Also altered in disease is the way that the DNA is decorated with chemical modifications such as methylation (epigenetic modifications). Being able to extract genetic and epigenetic information using DNA sequencing has revolutionised biomedical research and has led to new ways to diagnose diseases. A particular interest currently is in using genetic and epigenetic characteristics of tumour DNA circulating in the blood or other bodily fluids as a strategy for detecting cancer earlier. However, despite the potential utility of combining genetic and epigenetic information to enhance disease detection, no methods currently exist that can efficiently simultaneously extract this information from the same DNA sequencing data.
Up until now, DNA methylation has predominantly been detected using methods that rely on a process called bisulphite conversion. Bisulphite is a harsh chemical that damages DNA, resulting in decreased sensitivity and a high error rate in the sequencing data. Because it is not known whether any changes in the DNA compared to a reference genome are introduced by bisulphite or real mutations, it is very challenging to simultaneously detect methylation and mutation data using these methods.
Recently, a new bisulphite-free method for detecting DNA methylation called TET-assisted pyridine borane sequencing (TAPS) has been developed by Dr Chunxiao Song and Dr Benjamin Schuster-Böckler (Ludwig Institute for Cancer Research, Oxford Branch). This method is both cheaper than bisulphite sequencing and importantly produces data of higher quality, similar to that of standard DNA sequencing.
In this project, funded by an MRC Methodology Research Grant, Dr Benjamin Schuster-Böckler will collaborate with Professor Gerton Lunter (Visiting Professor, Radcliffe Department of Medicine) to develop algorithms that simultaneously detect mutations and DNA methylation from TAPS data. Experimental data will be provided in collaboration with Ludwig Oxford’s Dr Chunxiao Song and Professor Xin Lu, and Professor Ellie Barnes (Nuffield Department of Medicine). Test data will be used to train machine-learning algorithms to optimise the accuracy of the sequencing method and to establish the best possible experimental parameters for this technique.
The resulting method will greatly increase the utility of the TAPS technique and will make it possible to routinely query a patient’s genetic background, while simultaneously measuring their epigenetic state. This will lead to a much broader understanding of the role of epigenetics in disease and would raise the possibility of using combined genetic and epigenetic information from sequencing data to aid earlier detection of cancer.