UVPAR: fast detection of functional shifts in duplicate genes

An update of DIVERGE software for functional divergence analysis of protein family

DIVERGE is a software system for phylogeny-based analyses of protein family evolution and functional divergence. It provides a suite of statistical tools for selection and prioritization of the amino acid sites that are responsible for the functional divergence of a gene family. The synergistic efforts of DIVERGE and other methods have convincingly demonstrated that the pattern of rate change at a particular amino acid site may contain insightful information about the underlying functional divergence following gene duplication. These predicted sites may be used as candidates for further experiments. We are now releasing an updated version of DIVERGE with the following improvements: 1) a feasible approach to examining functional divergence in nearly complete sequences by including deletions and insertions (indels); 2) the calculation of the false discovery rate of functionally diverging sites; 3) estimation of the effective number of functional divergence-related sites that is reliable and insensitive to cutoffs; 4) a statistical test for asymmetric functional divergence; and 5) a new method to infer functional divergence specific to a given duplicate cluster. In addition, we have made efforts to improve software design and produce a well-written software manual for the general user.

Evolution of antifreeze protein genes in the diatom genus fragilariopsis: evidence for horizontal gene transfer, gene duplication and episodic diversifying selection

Hypotheses about horizontal transfer of antifreeze protein genes to ice-living diatoms were addressed using two different statistical methods available in the program Prunier. The role of diversifying selection in driving the differentiation of a set of antifreeze protein genes in the diatom genus Fragilariopsis was also investigated. Four horizontal gene transfer events were identified. Two of these took place between two major eukaryote lineages, that is from the diatom Chaetoceros neogracile to the copepod Stephos longipes and from a basidiomycete clade to a monophyletic group, consisting of the diatom species Fragilariopsis curta and Fragilariopsis cylindrus. The remaining two events included transfers from an ascomycete lineage to the proteobacterium Stigmatella aurantiaca and from the proteobacterium Polaribacter irgensii to a group composed of 4 proteobacterium species. After the Fragilariopsis lineage acquired the antifreeze protein gene from the basidiomycetes, it duplicated and went through episodic evolution, characterized by strong positive selection acting on short segments of the branches in the tree. This selection pattern suggests that the paralogs differentiated functionally over relatively short time periods. Taken together, the results obtained here indicate that the group of antifreeze protein genes considered here have a complex evolutionary history.

A general strategy to determine the congruence between a hierarchical and a non-hierarchical classification

Background

Classification procedures are widely used in phylogenetic inference, the analysis of expression profiles, the study of biological networks, etc. Many algorithms have been proposed to establish the similarity between two different classifications of the same elements. However, methods to determine significant coincidences between hierarchical and non-hierarchical partitions are still poorly developed, in spite of the fact that the search for such coincidences is implicit in many analyses of massive data.

Results

We describe a novel strategy to compare a hierarchical and a dichotomic non-hierarchical classification of elements, in order to find clusters in a hierarchical tree in which elements of a given "flat" partition are overrepresented. The key improvement of our strategy respect to previous methods is using permutation analyses of ranked clusters to determine whether regions of the dendrograms present a significant enrichment. We show that this method is more sensitive than previously developed strategies and how it can be applied to several real cases, including microarray and interactome data. Particularly, we use it to compare a hierarchical representation of the yeast mitochondrial interactome and a catalogue of known mitochondrial protein complexes, demonstrating a high level of congruence between those two classifications. We also discuss extensions of this method to other cases which are conceptually related.

Conclusion

Our method is highly sensitive and outperforms previously described strategies. A PERL script that implements it is available at .