Michael R. Stratton

The paper reports mutation rates and mutational signatures across 53 normal human cell types, revealing variation in mutation accumulation and identifying known and unknown mutational processes.

The paper identifies and validates a previously missed mutational signature in microsatellite-stable colorectal cancer, showing it is distinct from known signatures and not caused by canonical DNA repair defects.

The paper identifies mutational signatures in normal kidney cells from multiple countries, revealing exposure to exogenous mutagens including aristolochic acids and unknown agents prevalent in Japan.

This study uses sperm sequencing to show that positive selection in the male germline leads to a higher risk of disease-causing mutations in offspring.

This study examines the long-term effects of chemotherapy on normal blood cells by analyzing mutation burdens and cell population structure in treated individuals.

The paper detects a single instance of host-to-tumour horizontal DNA transfer in canine transmissible venereal tumour, showing a 15-megabase genetic element from a dog with Middle Eastern ancestry.

This study uses whole-genome sequencing to analyze somatic mutations in normal gastric epithelium, revealing mutation rates, clonal dynamics, and associations with cancer risk factors.

The paper introduces a high-accuracy sequencing method to detect somatic mutations in tissues, revealing extensive selection and driver mutations in oral epithelium and blood samples.

SigProfilerAssignment refits known substitution, doublet, indel and copy-number mutational signatures to single samples and probabilistically to individual mutations, outperforming four refitting tools on 2,700 synthetic genomes.

SigProfilerExtractor is a tool for de novo mutational signature extraction that outperforms existing methods and identifies four novel signatures, including one linked to tobacco smoking.

This study compares mutational landscapes in somatic and germline cells across 29 anatomical structures, identifying key mutational signatures and their contributions to different cell types.

This study shows that inherited MUTYH mutations increase somatic mutation rates and specific mutational signatures in normal human cells, contributing to cancer risk without causing premature aging.

This study tracks clonal dynamics in human haematopoiesis across age, finding that clonal diversity sharply declines after 70, driven by positive selection on many genes and loss of Y chromosome in males.

This study finds that somatic mutation rates per year decrease with species lifespan across mammals, suggesting evolutionary constraints on mutagenesis and its role in ageing.

This study maps the temporal and spatial dynamics of the human endometrium using single-cell and spatial reference maps, identifying key signaling pathways regulating cell fate in vivo and in vitro.

The paper shows that germline mutations in POLE or POLD1 lead to elevated mutation burdens in normal human cells and tissues, but do not cause premature aging or other phenotypic features beyond early-onset cancer.

The paper quantifies mismatch repair (MMR) activity in human tissues by analyzing mutation rates in individuals with constitutional MMR deficiency, revealing genotype-specific mutational signatures and the role of MMR components in DNA repair.

The paper reconstructs phylogenies of human development using whole-genome sequencing to show variable embryonic patterns and lineage asymmetries across individuals and tissues.

The paper analyzes somatic mutations in colonic crypts of IBD patients and controls, finding higher mutation rates and clonal expansions in IBD-affected tissue.

The paper uses whole genome sequencing and phylogenetic analysis to show that metastases in esophageal adenocarcinoma spread rapidly through a clonal diaspora model.

SigProfilerMatrixGenerator classifies and visualizes small mutational events in cancer genomes, offering faster and more comprehensive analysis than existing tools.

The paper quantifies selection patterns in cancer evolution using evolutionary genomics methods across 7,664 human cancers, finding positive selection dominates and many driver mutations occur in unknown genes.

This paper describes a method to identify drug resistance mutations in cancer using genome-wide chemical mutagenesis and next-generation sequencing, enabling the discovery of both known and novel resistance mechanisms.