Detecting the molecular basis of phenotypic convergence

Accurate Detection of Convergent Mutations in Large Protein Alignments With ConDor

Evolutionary convergences are observed at all levels, from phenotype to DNA and protein sequences, and changes at these different levels tend to be correlated. Notably, convergent mutations can lead to convergent changes in phenotype, such as changes in metabolism, drug resistance, and other adaptations to changing environments. We propose a two-component approach to detect mutations subject to convergent evolution in protein alignments. The "Emergence" component selects mutations that emerge more often than expected, while the "Correlation" component selects mutations that correlate with the convergent phenotype under study. With regard to Emergence, a phylogeny deduced from the alignment is provided by the user and is used to simulate the evolution of each alignment position. These simulations allow us to estimate the expected number of mutations in a neutral model, which is compared to the observed number of mutations in the data studied. In Correlation, a comparative phylogenetic approach, is used to measure whether the presence of each of the observed mutations is correlated with the convergent phenotype. Each component can be used on its own, for example Emergence when no phenotype is available. Our method is implemented in a standalone workflow and a webserver, called ConDor. We evaluate the properties of ConDor using simulated data, and we apply it to three real datasets: sedge PEPC proteins, HIV reverse transcriptase, and fish rhodopsin. The results show that the two components of ConDor complement each other, with an overall accuracy that compares favorably to other available tools, especially on large datasets.

CAAStools: a toolbox to identify and test Convergent Amino Acid Substitutions

MOTIVATION

Coincidence of Convergent Amino Acid Substitutions (CAAS) with phenotypic convergences allow pinpointing genes and even individual mutations that are likely to be associated with trait variation within their phylogenetic context. Such findings can provide useful insights into the genetic architecture of complex phenotypes.

RESULTS

Here we introduce CAAStools, a set of bioinformatics tools to identify and validate CAAS in orthologous protein alignments for predefined groups of species representing the phenotypic values targeted by the user.

AVAILABILITY AND IMPLEMENTATION

CAAStools source code is available at http://github.com/linudz/caastools, along with documentation and examples.

The convergence of bacterial natural products from evolutionarily distinct pathways

As bacteria readily convert simple starting materials into a diverse array of complex molecules with useful bioactivities, these microorganisms and their biosynthetic machinery represent attractive alternatives to traditional chemical syntheses. While the well-documented divergent evolution of biosynthesis has allowed bacteria to explore wide swaths of natural product chemical space, the convergent evolution of these pathways remains a comparably rare phenomenon. The emergence of similar phenotypes within disparate genetic contexts provides a unique opportunity to probe the limitations of natural selection and the predictability and reproducibility of evolution under different constraints. Here, we report several recent examples of functional and structural convergence of bacterial natural products, as well as intra- and inter-domain convergence of bacterial biosynthetic machinery. While the genetic underpinnings of biosynthetic pathway evolution are of fundamental interest, the evolutionary constraints exemplified by phenotypic convergence also have immediate implications for efforts to engineer microorganisms for therapeutic small molecule production.

Detecting adaptive convergent amino acid evolution

In evolutionary genomics, researchers have taken an interest in identifying substitutions that subtend convergent phenotypic adaptations. This is a difficult question that requires distinguishing foreground convergent substitutions that are involved in the convergent phenotype from background convergent substitutions. Those may be linked to other adaptations, may be neutral or may be the consequence of mutational biases. Furthermore, there is no generally accepted definition of convergent substitutions. Various methods that use different definitions have been proposed in the literature, resulting in different sets of candidate foreground convergent substitutions. In this article, we first describe the processes that can generate foreground convergent substitutions in coding sequences, separating adaptive from non-adaptive processes. Second, we review methods that have been proposed to detect foreground convergent substitutions in coding sequences and expose the assumptions that underlie them. Finally, we examine their power on simulations of convergent changes-including in the presence of a change in the efficacy of selection-and on empirical alignments. This article is part of the theme issue 'Convergent evolution in the genomics era: new insights and directions'.