Inferring and validating horizontal gene transfer events using bipartition dissimilarity

Lateral transfer of the denitrification pathway genes among Thermus thermophilus strains

Nitrate respiration is a common and strain-specific property in Thermus thermophilus encoded by the nitrate respiration conjugative element (NCE) that can be laterally transferred by conjugation. In contrast, nitrite respiration and further denitrification steps are restricted to a few isolates of this species. These later steps of the denitrification pathway are under the regulatory control of an NCE-encoded transcription factor, but nothing is known about their coding sequences or its putative genetic linkage to the NCE. In this study we examine the genetic linkage between nitrate and nitrite respiration through lateral gene transfer (LGT) assays and describe a cluster of genes encoding the nitrite-nitric oxide respiration in T. thermophilus PRQ25. We show that the whole denitrification pathway can be transferred from the denitrificant strain PRQ25 to an aerobic strain, HB27, and that the genes coding for nitrite and nitric oxide respiration are encoded near the NCE. Sequence data from the draft genome of PRQ25 confirmed these results and allowed us to describe the most compact nor-nir cluster known thus far and to demonstrate the expression and activities of the encoded enzymes in the HB27 denitrificant derivatives obtained by LGT. We conclude that this NCE nor-nir supercluster constitutes a whole denitrification island that can be spread by lateral transfer among Thermus thermophilus strains.

Bootstrap-based support of HGT inferred by maximum parsimony

Background

Maximum parsimony is one of the most commonly used criteria for reconstructing phylogenetic trees. Recently, Nakhleh and co-workers extended this criterion to enable reconstruction of phylogenetic networks, and demonstrated its application to detecting reticulate evolutionary relationships. However, one of the major problems with this extension has been that it favors more complex evolutionary relationships over simpler ones, thus having the potential for overestimating the amount of reticulation in the data. An ad hoc solution to this problem that has been used entails inspecting the improvement in the parsimony length as more reticulation events are added to the model, and stopping when the improvement is below a certain threshold.

Results

In this paper, we address this problem in a more systematic way, by proposing a nonparametric bootstrap-based measure of support of inferred reticulation events, and using it to determine the number of those events, as well as their placements. A number of samples is generated from the given sequence alignment, and reticulation events are inferred based on each sample. Finally, the support of each reticulation event is quantified based on the inferences made over all samples.

Conclusions

We have implemented our method in the NEPAL software tool (available publicly at http://bioinfo.cs.rice.edu/), and studied its performance on both biological and simulated data sets. While our studies show very promising results, they also highlight issues that are inherently challenging when applying the maximum parsimony criterion to detect reticulate evolution.