Deepa Agashe, National Centre for Biological Sciences, Bangalore, India
Edward Feil, The Milner Centre for Evolution, University of Bath, UK
Isabel Gordo, Instituto Gulbenkian de Ciência, Portugal
Ruth Hershberg, Technion, Haifa, Israel
Olivier Tenaillon, INSERM, Ecole Polytechnique, France
A major goal of evolutionary biology is to elucidate the mechanisms that generate observable patterns of genetic variation. The advent of whole genome sequencing provides new opportunities to observe variation in prokaryotes on an unprecedented scale. Genome data is now available over ever increasing taxonomic breadth, and data for key species can run into tens of thousands of genomes. These data have revealed patterns of immense variation across a range of genomic traits, including GC content, codon bias, tRNA pools and the size of the pan-genome (the total complement of genes present in a single population). The ultimate source of all this genetic variation is the process of mutation, whose rates and biases are affected by multiple molecular factors (e.g. DNA repair, recombination, division times). Once they occur, the fate of these mutations depends on the fundamental evolutionary forces of natural selection and genetic drift, which are impacted by the effective population size of a species and demographic changes.
Thus, to understand the emergence of patterns of variation, we need to connect processes across vastly different timescales, requiring a synthesis and multi-disciplinary understanding of the underlying molecular mechanisms, evolutionary processes and ecology. In this ESTN we propose to attempt such a synthesis, using evidence from experimental evolution studies with patterns of nucleotide variation observed in natural populations over a wide range of time-scales, from weeks to months (e.g. laboratory evolution or single disease outbreak), to millions of years (e.g. across species from different orders). The synthesis of laboratory evolution data with micro- and macro-evolutionary data from natural populations will shed light on the relative contributions of adaptive and stochastic processes as genomes become more diverged. The inclusion of experimental data is critical, as this allows testing of specific hypotheses regarding, for example, the maintenance of GC content or the drivers of codon bias/tRNA profiles.
1st Network meeting
Our main goal is to establish a network to explore aspects of prokaryotic genome evolution, with the aim of integrating across timescales. Core themes include the predictability of evolution, the dissonance between laboratory and natural evolution, compositional bias, selection at synonymous sites, and the evolution of accessory genes. Our first network meeting will take place in person at the at the Milner Centre for Evolution at the University of Bath, UK, from 30 May to 1 June 2022, with about 30 participants. Alongside talks, we will have plenty of time for discussion.
We invite applications from advanced PhD students and Postdoctoral fellows who would like to join the 1st network meeting and contribute to the synthesis. Accommodation is covered, and we are able to offer some travel support for international participants. Apply here by 15 March 2022.
- Hiroshi Akashi, Japan
- Susan Bailey, USA
- Jeffrey Barrick, USA
- Santiago Castillo-Ramirez, Mexico
- Alejandro Couce, Spain
- Tal Dagan, Germany
- Jamie Hall, UK
- Frederique Le Roux, France
- Haiwei Luo, Hong Kong
- Ivan Matic, France
- Eduardo Rocha, France
- Tiffany Taylor, UK
(a) Identify and address avenues for “bite-sized” syntheses across specific timescales or addressing a particular problem (e.g. HGT or GC content evolution)
(b) Assemble into 3–4 working groups, each focused on a one of the above aspects
© Across 2 years, working groups will meet independently and conduct short, intensive training courses focused on methods for working across micro and macro-evolutionary scales. Working groups could focus on specific timescales, a subset of functionally relevant traits, a taxonomic subset of organisms, or a specific set of data (e.g. clinical and experimental evolution)
(d) Eventually, the whole network will reconvene and develop a broader synthesis; and we will present our findings at a special ESEB symposium or in a special issue of J Evol Bio or Evolution Letters.
Deepa Agashe (firstname.lastname@example.org)
Edward Feil (email@example.com)