Dataset Information

Mutation Rate Inferred From Synonymous Substitutions in a Long-Term Evolution Experiment With Escherichia coli.

ABSTRACT: The quantification of spontaneous mutation rates is crucial for a mechanistic understanding of the evolutionary process. In bacteria, traditional estimates using experimental or comparative genetic methods are prone to statistical uncertainty and consequently estimates vary by over one order of magnitude. With the advent of next-generation sequencing, more accurate estimates are now possible. We sequenced 19 Escherichia coli genomes from a 40,000-generation evolution experiment and directly inferred the point-mutation rate based on the accumulation of synonymous substitutions. The resulting estimate was 8.9 × 10(-11) per base-pair per generation, and there was a significant bias toward increased AT-content. We also compared our results with published genome sequence datasets for other bacterial evolution experiments. Given the power of our approach, our estimate represents the most accurate measure of bacterial base-substitution rates available to date.

SUBMITTER: Wielgoss S

PROVIDER: S-EPMC3246271 | biostudies-literature | 2011 Aug

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Mutation Rate Inferred From Synonymous Substitutions in a Long-Term Evolution Experiment With Escherichia coli.

Wielgoss Sébastien S Barrick Jeffrey E JE Tenaillon Olivier O Cruveiller Stéphane S Chane-Woon-Ming Béatrice B Médigue Claudine C Lenski Richard E RE Schneider Dominique D

G3 (Bethesda, Md.) 20110801 3

The quantification of spontaneous mutation rates is crucial for a mechanistic understanding of the evolutionary process. In bacteria, traditional estimates using experimental or comparative genetic methods are prone to statistical uncertainty and consequently estimates vary by over one order of magnitude. With the advent of next-generation sequencing, more accurate estimates are now possible. We sequenced 19 Escherichia coli genomes from a 40,000-generation evolution experiment and directly infe ...[more]

PMID: 22207905

Similar Datasets

Project description:UNLABELLED:Large-scale rearrangements may be important in evolution because they can alter chromosome organization and gene expression in ways not possible through point mutations. In a long-term evolution experiment, twelve Escherichia coli populations have been propagated in a glucose-limited environment for over 25 years. We used whole-genome mapping (optical mapping) combined with genome sequencing and PCR analysis to identify the large-scale chromosomal rearrangements in clones from each population after 40,000 generations. A total of 110 rearrangement events were detected, including 82 deletions, 19 inversions, and 9 duplications, with lineages having between 5 and 20 events. In three populations, successive rearrangements impacted particular regions. In five populations, rearrangements affected over a third of the chromosome. Most rearrangements involved recombination between insertion sequence (IS) elements, illustrating their importance in mediating genome plasticity. Two lines of evidence suggest that at least some of these rearrangements conferred higher fitness. First, parallel changes were observed across the independent populations, with ~65% of the rearrangements affecting the same loci in at least two populations. For example, the ribose-utilization operon and the manB-cpsG region were deleted in 12 and 10 populations, respectively, suggesting positive selection, and this inference was previously confirmed for the former case. Second, optical maps from clones sampled over time from one population showed that most rearrangements occurred early in the experiment, when fitness was increasing most rapidly. However, some rearrangements likely occur at high frequency and may have simply hitchhiked to fixation. In any case, large-scale rearrangements clearly influenced genomic evolution in these populations. IMPORTANCE:Bacterial chromosomes are dynamic structures shaped by long histories of evolution. Among genomic changes, large-scale DNA rearrangements can have important effects on the presence, order, and expression of genes. Whole-genome sequencing that relies on short DNA reads cannot identify all large-scale rearrangements. Therefore, deciphering changes in the overall organization of genomes requires alternative methods, such as optical mapping. We analyzed the longest-running microbial evolution experiment (more than 25 years of evolution in the laboratory) by optical mapping, genome sequencing, and PCR analyses. We found multiple large genome rearrangements in all 12 independently evolving populations. In most cases, it is unclear whether these changes were beneficial themselves or, alternatively, hitchhiked to fixation with other beneficial mutations. In any case, many genome rearrangements accumulated over decades of evolution, providing these populations with genetic plasticity reminiscent of that observed in some pathogenic bacteria.

Dataset Information

Mutation Rate Inferred From Synonymous Substitutions in a Long-Term Evolution Experiment With Escherichia coli.

Publications

Mutation Rate Inferred From Synonymous Substitutions in a Long-Term Evolution Experiment With Escherichia coli.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets