Completed Genetics & Molecular Biology Cancer

Mutagenesis and its Biomedical Impact

In plain English

AI plain-English summary

Every human genome carries millions of DNA differences, but only a tiny fraction of those differences actually matter for health or disease. Researchers have developed ways to predict which DNA changes are consequential, even when those changes do not alter the protein-coding parts of genes. The problem is that the vast majority of DNA differences fall outside protein-coding regions, and their effects remain mysterious. Current genetic diagnosis and trait prediction rely almost entirely on finding changes that directly alter a protein, leaving most of the genome uninterpreted. This project fills that gap by studying how DNA sequences are inherited across generations in human populations. By comparing the pattern of new mutations with the pattern shaped by health outcomes, the team can identify which types of DNA change are likely to have real biological consequences. If successful, this work could transform genetic diagnosis by making it possible to interpret non-coding DNA changes that currently look like noise. It would improve predictions of disease risk, drug response, and traits like height, and could also help interpret the mutations that drive cancer. This is fundamental science—understanding how the genome works at a basic level—but it directly underpins the next generation of clinical genetic testing.

View original technical description
Of the many thousands of DNA differences between individuals, only a minority have important contributions to disease risk or other traits that differ between them. Finding those rare consequential differences is the basis for genetic diagnosis and predicting traits like height and drug response. It is also often the first step in understanding the basis of a disease at a molecular level. As a community we can only efficiently find the consequential differences if they directly alter an encoded protein, the vast majority don’t. We are developing ways to understand the consequences of the majority of DNA changes regardless of whether they alter a protein. Our approaches are often based on studying how large numbers of DNA sequence differences are inherited through generations of the human population. It allows us to tease apart two patterns, the pattern of new mutations and the pattern shaped by the health of people that carried those mutations. The pattern of new mutations tells us about the underlying biology of the DNA, how it is replicated and repaired as well as showing how likely a piece of DNA is likely to be disrupted by a new mutation. The second pattern is what tells us if a type of DNA change is likely to have a consequence for human health. Although described here in the context of inherited DNA differences, we apply similar approaches to interpret the new mutations that arise in and drive the development of cancer.

View the original record at the funder ↗

Researchers

Martin Taylor (Principal Investigator)

Related Research

Grants with similar aims, by meaning.

Mutagenesis and its biomedical consequences
Origins and impacts of regulatory mutations
Mutation and recombination in the human genome
Advancing the understanding and applications of mutational signatures
Determining the impact of heterochromatin hypomethylation in cancer

Original classification

Intramural

Plain English summaries and category classifications on this site are generated by AI and may not perfectly reflect the original research.