Federico Abascal

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.

This study develops human epithelioids as a 3D culture system that maintains architecture, heterogeneity, and clonal evolution over time, enabling long-term studies of tissue dynamics and therapeutic responses.

The paper identifies 105 dual coding regions under purifying selection in both reading frames, with many linked to brain development and neural functions.

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.

The paper identifies endogenous guanine adducts as drivers of tissue-specific mutagenesis and shows that Polκ and DNA repair mechanisms suppress these mutations.

This study generates chromosome-scale genome assemblies of germline restricted chromosomes (GRCs) in fungus gnats and finds they evolve dynamically with gene-rich content under strong purifying selection.

This study uses duplex sequencing to analyze platinum chemotherapy-induced mutagenesis in pediatric tissues, revealing extensive mutational signatures and tissue-specific effects.

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.

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.

The paper uses saturation genome editing to assess DDX3X variants' functional impact, identifies pathogenic variants for neurodevelopmental disorders, and develops a classifier outperforming existing tools.

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.

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.

This study shows that mutation spectra in C. elegans are shaped by both DNA damage and repair processes, with repair deficiencies altering mutation rates and spectra in many experimental conditions.

The paper analyzes whole-genome sequencing data from cancer samples to identify genomic footprints of telomere maintenance mechanisms, finding specific telomere variant repeat patterns associated with ATRX/DAXX mutations.

The paper introduces the Cancer LncRNA Census (CLC), a curated resource of lncRNAs with causative roles in cancer, and shows their genomic and evolutionary features.

The paper examines how somatic structural variations affect TAD boundaries and gene regulation in human cancers using whole genome sequencing data.

This study identifies germline genetic variants influencing somatic mutation patterns in 2,642 cancer genomes across 39 cancer types.

This study characterizes mitochondrial genomes in 2,700 cancer patients across 37 types using whole-genome sequencing and RNA-seq, revealing mutational patterns, truncating mutations, and nuclear transfer of mitochondrial DNA.

This study analyzes chromothripsis in 2,658 cancers using whole-genome sequencing, finding it prevalent across multiple cancer types with complex structural alterations.

ActivePathways integrates multivariate omics data to identify enriched pathways, revealing cancer driver genes and prognostic pathways in breast cancer.

The paper identifies and characterizes coding and non-coding driver mutations across 2,500 cancer genomes, revealing new candidates and questioning previous findings.