The rate and spectrum of new mutations in mice inferred by long-read sequencing

Eugenio López-Cortegano*, Jobran Chebib, Anika Jonas, Anastasia Vock, Sven Künzel, Peter D. Keightley, Diethard Tautz

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

All forms of genetic variation originate from new mutations, making it crucial to understand their rates and mechanisms. Here, we use long-read sequencing from Pacific Biosciences (PacBio) to investigate de novo mutations that accumulated in 12 inbred mouse lines derived from three commonly used inbred strains (C3H, C57BL/6, and FVB) maintained for 8 to 15 generations in a mutation accumulation (MA) experiment. We built chromosome-level genome assemblies based on the MA line founders' genomes and then employed a combination of read and assembly-based methods to call the complete spectrum of new mutations. On average, there are about 45 mutations per haploid genome per generation, about half of which (54%) are insertions and deletions shorter than 50 bp (indels). The remainder are single-nucleotide mutations (SNMs; 44%) and large structural mutations (SMs; 2%). We found that the degree of DNA repetitiveness is positively correlated with SNM and indel rates and that a substantial fraction of SMs can be explained by homology-dependent mechanisms associated with repeat sequences. Most (90%) indels can be attributed to microsatellite contractions and expansions, and there is a marked bias toward 4 bp indels. Among the different types of SMs, tandem repeat mutations have the highest mutation rate, followed by insertions of transposable elements (TEs). We uncover a rich landscape of active TEs, notable differences in their spectrum among MA lines and strains, and a high rate of gene retroposition. Our study offers novel insights into mammalian genome evolution and highlights the importance of repetitive elements in shaping genomic diversity.

Original languageEnglish
Pages (from-to)43-54
Number of pages52
JournalGenome Research
Volume35
Issue number1
Early online date2 Dec 2024
DOIs
Publication statusPublished - Jan 2025

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