Using Experimental Evolution to Unravel the Genomic Causes and Evolutionary Consequences of Biased Adaptive Outcomes

Le 09 Décembre 2022
Webinaire - 11h30

Tiffany taylor

Milner Centre for Evolution, University of Bath, Bath, United Kingdom

Link to seminar:



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Mutation is the raw material for natural selection, providing a source of variation. However, many known mechanisms exist that can bias what types and where mutations are more likely to occur – making some adaptive routes more likely than others. In this talk, I aim to give an overview of work ongoing in my lab that addresses how features of the genome, in combination with natural selection, can bias adaptive outcomes.

We use experimental evolution with an engineered non-motile variant of the model soil microbe, Pseudomonas fluorescens, to explore features of the genome that shape adaptive outcomes. I will discuss two scales of bias we have identified: at the nucleotide and gene regulatory network (GRN) level. Firstly, we have shown that a near-deterministic mutational hotspot can be built and broken via just six silent genetic changes. This hotspot has the potential to confer a strong bias that defines the observed mutational spectrum and results in predictable evolution. Secondly, we uncover how architecture within GRNs can determine opportunities for regulator evolution, by creating and constraining opportunities for promiscuous interactions (or crosstalk). This advances our understanding of the viability of particular regulators for innovation, with broad implications for understanding and predicting bacterial adaptation to novel environments.


Recent publications:

1 Horton, J.S., Flanagan, L.M., Jackson, R.W., Priest, N.K. and Taylor, T. B. (2021) A mutational hotspot that determines highly repeatable evolution can be built and broken by silent genetic changes. Nature Communications (12) 6092

2 Shepherd, M. J., Pierce, A. P., & Taylor, T. B. (2022) Evolutionary innovation through transcription factor promiscuity in microbes is constrained by pre-existing gene regulatory network architecture. bioRxiv.

3 Taylor, T. B., Shepherd, M. J., Jackson, R. W., and Silby, M. S. (2022) Natural selection on crosstalk between gene regulatory networks facilitates bacterial adaptation to novel environments. Current Opinion in Microbiology (67) 102140




Michael Finnegan (CEFE)