Somatic genetic heterogeneity arises when errors are made during the copying of DNA, or when mutagens affect the cell. One of the key goals of the research in my group is to understand why mutations are so different between individuals and between cell types. Our vision is that by understanding the causes of mutagenesis, we will eventually be able to predict a person’s risk of developing cancer, and to design new preventative or therapeutic interventions.
If we want to understand the accumulation of DNA damage in different cell types, we need to look at healthy, pre-cancerous cells. Recently, a number of approaches have been developed to achieve this:
In this DPhil project, you will use existing and newly generated sequencing data to reveal the origins of unique mutational signatures of cells in the upper gastrointestinal tract. To do so, we are collaborating with different groups within the Ludwig Institute. Prof. Xin Lu is running a clinical trial on gastric adenocarcinoma. As part of that project, we are collecting samples and generating organoids that can be used to compare differences in mutation load between patients and cell types. Depending on your interests, you can also get involved in the actual data generation in addition to the downstream analysis.
We are also working closely with the group of Skirmantas Kriaucionis. As part of your DPhil, you could perform experiments to test how the environment and cell metabolism interact to create the patterns of mutations that are observed in some tumours.
Ultimately, we aim to take the findings that we will derive from existing preliminary data and in-vitro experiments into the clinic. You will have the chance to work on data from real patients and contribute to the larger effort to reveal the causal mechanisms behind oesophageal cancer.
This project has a strong computational component, so numeric literacy and basic knowledge of using computational environments like R or Matlab would be highly beneficial. As part of your training, you will get an insight into the analysis of next-generation sequencing data and learn how to process large genomic datasets.
Depending on your background, you could also get involved in the experimental data generation, especially sequencing of single cells as well as any of the high-depth sequencing protocols mentioned above.
Project reference number: 795
|Dr Benjamin Schuster-Böckler||Oxford Ludwig Institute||Oxford University, Old Road Campus Research Building||GBRemail@example.com|
|Professor Skirmantas Kriaucionis||Oxford Ludwig Institute||Oxford University, Old Road Campus Research Building||GBRfirstname.lastname@example.org|
|Professor Xin Lu||Oxford Ludwig Institute||Oxford University, Old Road Campus Research Building||GBRemail@example.com|
CpG dinucleotides are the main mutational hot-spot in most cancers. The characteristic elevated C>T mutation rate in CpG sites has been related to 5-methylcytosine (5mC), an epigenetically modified base which resides in CpGs and plays a role in transcription silencing. In brain nearly a third of 5mCs have recently been found to exist in the form of 5-hydroxymethylcytosine (5hmC), yet the effect of 5hmC on mutational processes is still poorly understood. Here we show that 5hmC is associated with an up to 53% decrease in the frequency of C>T mutations in a CpG context compared to 5mC. Tissue specific 5hmC patterns in brain, kidney and blood correlate with lower regional CpG>T mutation frequency in cancers originating in the respective tissues. Together our data reveal global and opposing effects of the two most common cytosine modifications on the frequency of cancer causing somatic mutations in different cell types. Hide abstract
We present the bottleneck sequencing system (BotSeqS), a next-generation sequencing method that simultaneously quantifies rare somatic point mutations across the mitochondrial and nuclear genomes. BotSeqS combines molecular barcoding with a simple dilution step immediately before library amplification. We use BotSeqS to show age- and tissue-dependent accumulations of rare mutations and demonstrate that somatic mutational burden in normal human tissues can vary by several orders of magnitude, depending on biologic and environmental factors. We further show major differences between the mutational patterns of the mitochondrial and nuclear genomes in normal tissues. Lastly, the mutation spectra of normal tissues were different from each other, but similar to those of the cancers that arose in them. This technology can provide insights into the number and nature of genetic alterations in normal tissues and can be used to address a variety of fundamental questions about the genomes of diseased tissues. Hide abstract
In 1943, Luria and Delbrück used a phage-resistance assay to establish spontaneous mutation as a driving force of microbial diversity. Mutation rates are still studied using such assays, but these can only be used to examine the small minority of mutations conferring survival in a particular condition. Newer approaches, such as long-term evolution followed by whole-genome sequencing, may be skewed by mutational ‘hot’ or ‘cold’ spots. Both approaches are affected by numerous caveats. Here we devise a method, maximum-depth sequencing (MDS), to detect extremely rare variants in a population of cells through error-corrected, high-throughput sequencing. We directly measure locus-specific mutation rates in Escherichia coli and show that they vary across the genome by at least an order of magnitude. Our data suggest that certain types of nucleotide misincorporation occur 10(4)-fold more frequently than the basal rate of mutations, but are repaired in vivo. Our data also suggest specific mechanisms of antibiotic-induced mutagenesis, including downregulation of mismatch repair via oxidative stress, transcription–replication conflicts, and, in the case of fluoroquinolones, direct damage to DNA. Hide abstract
Cancer genome sequencing provides the first direct information on how mutation rates vary across the human genome in somatic cells. Testing diverse genetic and epigenetic features, here we show that mutation rates in cancer genomes are strikingly related to chromatin organization. Indeed, at the megabase scale, a single feature—levels of the heterochromatin-associated histone modification H3K9me3—can account for more than 40% of mutation-rate variation, and a combination of features can account for more than 55%. The strong association between mutation rates and chromatin organization is upheld in samples from different tissues and for different mutation types. This suggests that the arrangement of the genome into heterochromatin- and euchromatin-like domains is a dominant influence on regional mutation-rate variation in human somatic cells. Hide abstract
The somatic mutations present in the genome of a cell accumulate over the lifetime of a multicellular organism. These mutations can provide insights into the developmental lineage tree, the number of divisions that each cell has undergone and the mutational processes that have been operative. Here we describe whole genomes of clonal lines derived from multiple tissues of healthy mice. Using somatic base substitutions, we reconstructed the early cell divisions of each animal, demonstrating the contributions of embryonic cells to adult tissues. Differences were observed between tissues in the numbers and types of mutations accumulated by each cell, which likely reflect differences in the number of cell divisions they have undergone and varying contributions of different mutational processes. If somatic mutation rates are similar to those in mice, the results indicate that precise insights into development and mutagenesis of normal human cells will be possible. Hide abstract