Response to Horizontal gene transfer may explain variation in θs

Response to Horizontal gene transfer may explain variation in \theta_s

Inigo Martincorena, Nicholas M. Luscombe
(Submitted on 5 Nov 2012)

In a short article submitted to ArXiv [1], Maddamsetti et al. argue that the variation in the neutral mutation rate among genes in Escherichia coli that we recently reported [2] might be explained by horizontal gene transfer (HGT). To support their argument they present a reanalysis of synonymous diversity in 10 E.coli strains together with an analysis of a collection of 1,069 synonymous mutations found in repair-deficient strains in a long-term in vitro evolution experiment. Here we respond to this communication. Briefly, we explain that HGT was carefully accounted for in our study by multiple independent phylogenetic and population genetic approaches, and we show that there is no new evidence of HGT affecting our results. We also argue that caution must be exercised when comparing mutations from repair deficient strains to data from wild-type strains, as these conditions are dominated by different mutational processes. Finally, we reanalyse Maddamsetti’s collection of mutations from a long-term in vitro experiment and we report preliminary evidence of non-random variation of the mutation rate in these repair deficient strains.

Horizontal gene transfer may explain variation in θs

Horizontal gene transfer may explain variation in θs
Rohan Maddamsetti, Philip J. Hatcher, Stéphane Cruveiller, Claudine Médigue, Jeffrey E. Barrick, Richard E. Lenski
(Submitted on 28 Sep 2012)

Martincorena et al. estimated synonymous diversity (\theta s = 2N \mu ) across 2,930 orthologous gene alignments from 34 Escherichia coli genomes, and found substantial variation among genes in the density of synonymous polymorphisms. They argue that this pattern reflects variation in the mutation rate per nucleotide (\mu) among genes. However, the effective population size (N) is not necessarily constant across the genome. In particular, different genes may have different histories of horizontal gene transfer (HGT), whereas Martincorena et al. used a model with random recombination to calculate \theta s. They did filter alignments in an effort to minimize the effects of HGT, but we doubt that any procedure can completely eliminate HGT among closely related genomes, such as E. coli living in the complex gut community.
Here we show that there is no significant variation among genes in rates of synonymous substitutions in a long-term evolution experiment with E. coli and that the per-gene rates are not correlated with \theta s estimates from genome comparisons. However, there is a significant association between \theta s and HGT events. Together, these findings imply that \theta s variation reflects different histories of HGT, not local optimization of mutation rates to reduce the risk of deleterious mutations as proposed by Martincorena et al.

Towards the Recapitulation of Ancient History in the Laboratory: Combining Synthetic Biology with Experimental Evolution

Towards the Recapitulation of Ancient History in the Laboratory: Combining Synthetic Biology with Experimental Evolution

Betul Kacar, Eric Gaucher
(Submitted on 23 Sep 2012)

One way to understand the role history plays on evolutionary trajectories is by giving ancient life a second opportunity to evolve. Our ability to empirically perform such an experiment, however, is limited by current experimental designs. Combining ancestral sequence reconstruction with synthetic biology allows us to resurrect the past within a modern context and has expanded our understanding of protein functionality within a historical context. Experimental evolution, on the other hand, provides us with the ability to study evolution in action, under controlled conditions in the laboratory. Here we describe a novel experimental setup that integrates two disparate fields – ancestral sequence reconstruction and experimental evolution. This allows us to rewind and replay the evolutionary history of ancient biomolecules in the laboratory. We anticipate that our combination will provide a deeper understanding of the underlying roles that contingency and determinism play in shaping evolutionary processes.