Extended sequence context shapes mutational bias in <i>Escherichia coli</i>

M Matthew J. Jago (Division of Evolution, Infection and Genomic Sciences, School of Biological Sciences, Faculty of Biology, Medicine and Health, University of Manchester) R Rowan Green (Division of Evolution, Infection and Genomic Sciences, School of Biological Sciences, Faculty of Biology, Medicine and Health, University of Manchester) M Maisie R. Czernuszka (Division of Evolution, Infection and Genomic Sciences, School of Biological Sciences, Faculty of Biology, Medicine and Health, University of Manchester) S Stepan Denisov (Division of Evolution, Infection and Genomic Sciences, School of Biological Sciences, Faculty of Biology, Medicine and Health, University of Manchester) R Rok Krašovec (Division of Evolution, Infection and Genomic Sciences, School of Biological Sciences, Faculty of Biology, Medicine and Health, University of Manchester) C Christopher G. Knight (Department of Earth and Environmental Sciences, Faculty of Science and Engineering, University of Manchester) M Mato Lagator (Division of Evolution, Infection and Genomic Sciences, School of Biological Sciences, Faculty of Biology, Medicine and Health, University of Manchester)

Abstract

Understanding how sequence context influences the likelihood of mutation at a given genomic locus is critical for deciphering evolutionary processes. It is well established that the immediately adjacent bases influence mutation rates, but the role of more distal bases remains poorly understood. Here, we analyze over 100,000 mutations from 32 Escherichia coli mutation accumulation experiments, encompassing strains with varying DNA proofreading and mismatch repair capabilities. By quantifying the frequency of each nucleotide up to 6 bp around mutation sites, we reveal complex mutational biases that extend beyond the immediately adjacent bases and are unique to each type of base pair substitution. Furthermore, which sequence contexts contribute most to mutational bias depends on what repair mechanisms are active and which strand serves as the leading versus lagging template during replication. Mononucleotide runs are prominent mutational hotspots–we systematically characterize which types of runs are the most mutagenic, including a previously undescribed hotspot for G:C→C:G transversions that can increase their frequency by up to four orders of magnitude. Remarkably, extending our analysis to 1,000 bp from mutation sites reveals that sequence context can influence mutational bias over unexpectedly long distances. These findings expose the intricate interactions between extended sequence context and DNA repair systems that shape spontaneous mutagenesis, and shed light on the mechanistic origins and evolutionary consequences of mutational signatures.

Article Details

Volume / Issue Vol. 123, Issue 23
Published June 09, 2026
ISSN 0027-8424
Publisher National Academy of Sciences

Authors (7)

M

Matthew J. Jago

Division of Evolution, Infection and Genomic Sciences, School of Biological Sciences, Faculty of Biology, Medicine and Health, University of Manchester

R

Rowan Green

Division of Evolution, Infection and Genomic Sciences, School of Biological Sciences, Faculty of Biology, Medicine and Health, University of Manchester

M

Maisie R. Czernuszka

Division of Evolution, Infection and Genomic Sciences, School of Biological Sciences, Faculty of Biology, Medicine and Health, University of Manchester

S

Stepan Denisov

Division of Evolution, Infection and Genomic Sciences, School of Biological Sciences, Faculty of Biology, Medicine and Health, University of Manchester

R

Rok Krašovec

Division of Evolution, Infection and Genomic Sciences, School of Biological Sciences, Faculty of Biology, Medicine and Health, University of Manchester

C

Christopher G. Knight

Department of Earth and Environmental Sciences, Faculty of Science and Engineering, University of Manchester

M

Mato Lagator

Division of Evolution, Infection and Genomic Sciences, School of Biological Sciences, Faculty of Biology, Medicine and Health, University of Manchester