@ARTICLE{TreeBASE2Ref22199, author = {Jessica R Grant and Laura A Katz}, title = {Building a Phylogenomic Pipeline for the Eukaryotic Tree of Life ? Addressing Deep Phylogenies with Genome-Scale Data.}, year = {2014}, keywords = {}, doi = {10.1371/currents.tol.c24b6054aebf3602748ac042ccc8f2e9}, url = {}, pmid = {}, journal = {PLOS Currents Tree of Life}, volume = {April 2}, number = {1}, pages = {}, abstract = {Background: Characterizing genome-scale data from diverse eukaryotes is essential for gene discovery and for inferring major transitions across the eukaryotic tree of life. Yet, the bulk of eukaryotic diversity remains undersampled, particularly for free-living microbial lineages. Analysis of transcriptome data generated from high throughput (e.g. 454) sequencing of mRNAs provides an efficient way to characterize genes from diverse eukaryotes. Results: Here we report analyses of RNA-Seq data from the rhizarian net-like amoeba Corallomyxa tenera, the ciliate Chilodonella uncinata and a recently-described genus representing a novel major clade of eukaryotes, Subulatomonas tetraspora. We generated 16,983, 11,529 and 10,630 contigs plus single reads for these taxa respectively. Given that these organisms cannot be cultured axenically, we developed custom scripts to remove bacterial contaminants through an iterative BLAST based protocol and we then identified expressed genes using BLAST2GO [1;2]. This approach yielded a large number of genes with eukaryotic homologs, as well as numerous novel genes. To assess our approach and to explore the resulting sequences, we searched for genes involved in anaerobic metabolism, RNAi and meiosis. Further, we report the results of a preliminary phylogenomic analysis including these organisms. Conclusions: We characterized the transcriptomes of three phylogenetically diverse eukaryotes. After applying several filters to ensure the retention of only high-quality, non-contaminant data, we identified numerous sequences that can be used for gene discovery and phylogenomics. We found candidate genes involved in RNAi, meiosis, and anaerobic metabolism, and generated phylogenies that place the target taxa in positions predicted by previous analyses. This work supports the use of high throughput approaches for assessing features of non-model organisms, even in instances when species cannot be cultured axenically or grown to large numbers.} }

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