Detecting LGTs using a novel probabilistic modelintegrating duplications, LGTs, losses, rate variation,and sequence evolution
2009 (English)Manuscript (preprint) (Other academic)
The debate over the prevalence of lateral gene transfers (LGTs) has been intense.There is now to a large extent consensus around the view that LGT is an important evolutionary force as well as regarding its relative importance across species. This consensus relies, however, mainly on studies of individual gene families.
Up until now, the gold standard for identifying LGTs has been phylogenetic methods where LGTs are inferred from incongruities between a species tree andan associated gene tree. Even in cases where there is evidence of LGT, several concerns have often been raised regarding the significance of the evidence. One common concern has been the possibility that other evolutionary events have caused the incongruities. Another has been the significance of the gene trees involved in the inference; there may for instance be alternative, almost equally likely, gene trees that do not provide evidence for LGT. Independently of these concerns, there has been a need for methods that can be used to quantitatively characterize the level of LGT among sets of species, but also for methods able to pinpoint where in the species tree LGTs have occurred.
Here, we provide the first probabilistic model capturing gene duplication, LGT,gene loss, and point mutations with a relaxed molecular clock. We also provide allfundamental algorithms required to analyze a gene family relative to a given speciestree under this model. Our algorithms are based on Markov chain Monte Carlo(MCMC) methodology but build also on techniques from numerical analysis and involve dynamic programming (DP).
Place, publisher, year, edition, pages
Industrial Biotechnology Computer Science
IdentifiersURN: urn:nbn:se:kth:diva-10971OAI: oai:DiVA.org:kth-10971DiVA: diva2:233574
QC 201008122009-09-012009-09-012016-12-20Bibliographically approved