BACKGROUND: Phylogenetic tools and 'tree-thinking' approaches increasingly permeate all biological research. At the same time, phylogenetic data sets are expanding at breakneck pace, facilitated by increasingly economical sequencing technologies. Therefore, there is an urgent need for accessible, modular, and sharable tools for phylogenetic analysis. RESULTS: We developed a suite of wrappers for new and existing phylogenetics tools for the Galaxy workflow management system that we call Osiris. Osiris and Galaxy provide a sharable, standardized, modular user interface, and the ability to easily create complex workflows using a graphical interface. Osiris enables all aspects of phylogenetic analysis within Galaxy, including de novo assembly of high throughput sequencing reads, ortholog identification, multiple sequence alignment, concatenation, phylogenetic tree estimation, and post-tree comparative analysis. The open source files are available on in the Bitbucket public repository and many of the tools are demonstrated on a public web server (http://galaxy-dev.cnsi.ucsb.edu/osiris/). CONCLUSIONS: Osiris can serve as a foundation for other phylogenomic and phylogenetic tool development within the Galaxy platform.

BACKGROUND: Tools for high throughput sequencing and de novo assembly make the analysis of transcriptomes (i.e. the suite of genes expressed in a tissue) feasible for almost any organism. Yet a challenge for biologists is that it can be difficult to assign identities to gene sequences, especially from non-model organisms. Phylogenetic analyses are one useful method for assigning identities to these sequences, but such methods tend to be time-consuming because of the need to re-calculate trees for every gene of interest and each time a new data set is analyzed. In response, we employed existing tools for phylogenetic analysis to produce a computationally efficient, tree-based approach for annotating transcriptomes or new genomes that we term Phylogenetically-Informed Annotation (PIA), which places uncharacterized genes into pre-calculated phylogenies of gene families. RESULTS: We generated maximum likelihood trees for 109 genes from a Light Interaction Toolkit (LIT), a collection of genes that underlie the function or development of light-interacting structures in metazoans. To do so, we searched protein sequences predicted from 29 fully-sequenced genomes and built trees using tools for phylogenetic analysis in the Osiris package of Galaxy (an open-source workflow management system). Next, to rapidly annotate transcriptomes from organisms that lack sequenced genomes, we repurposed a maximum likelihood-based Evolutionary Placement Algorithm (implemented in RAxML) to place sequences of potential LIT genes on to our pre-calculated gene trees. Finally, we implemented PIA in Galaxy and used it to search for LIT genes in 28 newly-sequenced transcriptomes from the light-interacting tissues of a range of cephalopod mollusks, arthropods, and cubozoan cnidarians. Our new trees for LIT genes are available on the Bitbucket public repository ( http://bitbucket.org/osiris_phylogenetics/pia/ ) and we demonstrate PIA on a publicly-accessible web server ( http://galaxy-dev.cnsi.ucsb.edu/pia/ ). CONCLUSIONS: Our new trees for LIT genes will be a valuable resource for researchers studying the evolution of eyes or other light-interacting structures. We also introduce PIA, a high throughput method for using phylogenetic relationships to identify LIT genes in transcriptomes from non-model organisms. With simple modifications, our methods may be used to search for different sets of genes or to annotate data sets from taxa outside of Metazoa.

MOTIVATION: Gene duplications and losses (GDLs) are important events in genome evolution. They result in expansion or contraction of gene families, with a likely role in phenotypic evolution. As more genomes become available and their annotations are improved, software programs capable of rapidly and accurately identifying the content of ancestral genomes and the timings of GDLs become necessary to understand the unique evolution of each lineage. RESULTS: We report EvolMAP, a new algorithm and software that utilizes a species tree-based gene clustering method to join all-to-all symmetrical similarity comparisons of multiple gene sets in order to infer the gene composition of multiple ancestral genomes. The algorithm further uses Dollo parsimony-based comparison of the inferred ancestral genes to pinpoint the timings of GDLs onto evolutionary intervals marked by speciation events. Using EvolMAP, first we analyzed the expansion of four families of G-protein coupled receptors (GPCRs) within animal lineages. Additional to demonstrating the unique expansion tree for each family, results also show that the ancestral eumetazoan genome contained many fewer GPCRs than modern animals, and these families expanded through concurrent lineage-specific duplications. Second, we analyzed the history of GDLs in mammalian genomes by comparing seven proteomes. In agreement with previous studies, we report that the mammalian gene family sizes have changed drastically through their evolution. Interestingly, although we identified a potential source of duplication for 75% of the gained genes, remaining 25% did not have clear-cut sources, revealing thousands of genes that have likely gained their distinct sequence identities within the descent of mammals. AVAILABILITY: Query server, source code and executable are available at http://kosik-web.mcdb.ucsb.edu/evolmap/index.htm .