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Gene discovery from a pilot study of the transcriptomes from three diverse microbial eukaryotes: Corallomyxa tenera, Chilodonella uncinata, and Subulatomonas tetraspora

Jessica R. Grant
  • Department of Biological Sciences, Smith College, 44 College Lane, Northampton, Massachusetts 01063, USA
/ Daniel J.G. Lahr
  • Department of Biological Sciences, Smith College, 44 College Lane, Northampton, Massachusetts 01063, USA
  • Program in Organismic and Evolutionary Biology, University of Massachusetts, 611 North Pleasant Street, Amherst, Massachusetts 01003, USA
  • Department of Zoology, Institute of Biosciences, University of Sao Paulo, Brazil
/ Federico E. Rey
  • Center for Genome Science & Systems Biology, Washington University School of Medicine, St Louis, MO 63108 USA
/ J. Gordon Burleigh
  • Department of Biology, University of Florida, PO Box 118526, Gainseville, FL 32611, USA
/ Jeffrey I. Gordon
  • Center for Genome Science & Systems Biology, Washington University School of Medicine, St Louis, MO 63108 USA
/ Rob Knight
  • Department of Chemistry & Biochemistry, University of Colorado, Boulder, CO 80309 USA
/ Robert E. Molestina
  • American Type Culture Collection, Protistology Collection, 10801 University Blvd., Manassas, Virginia 20110, USA
/ Laura A. Katz
  • Department of Biological Sciences, Smith College, 44 College Lane, Northampton, Massachusetts 01063, USA
  • Program in Organismic and Evolutionary Biology, University of Massachusetts, 611 North Pleasant Street, Amherst, Massachusetts 01003, USA
  • Email:
Published Online: 2012-12-28 | DOI: https://doi.org/10.2478/prge-2012-0002



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.


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.


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.

This article offers supplementary material which is provided at the end of the article.

Keywords: Transcriptome; 454 sequencing; Nonmodel organisms; Phylogenetics; Chilodonella uncinata; Corallomyxa tenera; Subulatomonas tetraspora

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About the article

Received: 2012-09-13

Accepted: 2012-12-19

Published Online: 2012-12-28

Citation Information: Protist Genomics, ISSN (Online) 2299-100X, DOI: https://doi.org/10.2478/prge-2012-0002. Export Citation

©2012 Versita Sp. z o.o.. This content is open access.

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