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Biology subjects

Koers, C.

Publications and source records attributed to Koers, C..

2 recordsLinked to original sources

MutagenesisForge: A Framework for Modeling Codon-Level Mutational Biases and Calculating dN/dS

The ratio of nonsynonymous (dN) to synonymous (dS) substitutions in protein-coding genes is a fundamental metric in molecular evolution to test hypotheses about the relative contributions of genetic drift and natural selection in shaping patterns of protein divergence (Williams et al., 2020). However, interpretation of dN/dS ratios may be confounded by sequence context and specific substitution models (Hughes, 2007; Kryazhimskiy & Plotkin, 2008). We present MutagenesisForge, a modular command-line tool and Python package for simulating codon-level mutagenesis and calculating dN/dS under user-specified conditions. At its core is the MutationModel interface which supports specific substitution matrices and ensures consistency across both Exhaustive and Contextual modes of simulation. These modes allow for users to test evolutionary hypotheses or to generate null distributions of dN/dS across a range of biologically relevant models. As large-scale DNA sequencing data sets continue to be generated both within and between species, MutagenesisForge offers a flexible platform for evolutionary analysis and hypothesis testing of mutational processes in protein-coding genes.

evolutionary biology↗

Landscape of human protein-coding somatic mutations across tissues and individuals

Although somatic mutations are fundamentally important to human biology, disease, and aging, many outstanding questions remain about their rates, spectrum, and determinants in apparently healthy tissues. Here, we performed high-coverage exome sequencing on 265 samples from 14 GTEx donors sampled for a median of 17.5 tissues per donor (spanning 46 total tissues). Using a novel probabilistic method tailored to the unique structure of our data, we identified 8,470 somatic variants. We leverage our compendium of somatic mutations to quantify the burden of deleterious somatic variants among tissues and individuals, identify molecular features such as chromatin accessibility that exhibit significantly elevated somatic mutation rates, provide novel biological insights into mutational mechanisms, and infer developmental trajectories based on patterns of multi-tissue somatic mosaicism. Our data provides a high-resolution portrait of somatic mutations across genes, tissues, and individuals.

genomics↗