Using phylogenetically-informed annotation (PIA) to search for light-interacting genes in transcriptomes from non-model organisms

• DOI: 10.1186/s12859-014-0350-x
• Publication Date: 2014-11-18T20:03:41Z
• Authors: Daniel I Speiser; M Sabrina Pankey; Alexander K Zaharoff; Barbara A Battelle; Heather D Bracken...; Jesse W Breinholt; Seth M Bybee; Thomas W Cronin; Anders Garm; Annie R Lindgren; Nipam H Patel; Megan L Porter; Meredith E Protas; Ajna S Rivera; Jeanne M Serb; Kirk S Zigler; Keith A Crandall; Todd H Oakley
• Keywords: 0301 basic medicine; Light; Vision; Biochemistry; Mathematical Sciences; Transcriptomes; Sequence Analysis, Protein; Phylogeny; Likelihood Functions; 0303 health sciences; Genome; Genetic transcription; High-Throughput Nucleotide Sequencing; bioinformatics; Biological Sciences; 004; Computer Science Applications; Biological sciences; Information and computing sciences; Sequence Analysis; Algorithms; Biotechnology; vision; 570; next-generation sequence analysis; Bioinformatics; Evolution; Bioinformatics and Computational Biology; Mathematical sciences; phototransduction; 03 medical and health sciences; Ocular; Information and Computing Sciences; Orthology; evolution; transcriptomes; Genetics; Animals; Eye Proteins; Biology; Molecular Biology; Vision, Ocular; Protein; Genetics and Genomics; Molecular Sequence Annotation; eyes; Next-generation sequence analysis; Amino acid sequence -- Methodology; Galaxy; Phototransduction; Eyes; galaxy; Gene expression; Generic health relevance; orthology; Transcriptome; Software

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.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/ ).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.