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Generation and analysis of transcriptomic resources for a model system on the rise: the sea anemone Aiptasia pallida and its dinoflagellate endosymbiont

Journal Article · · BMC Genomics
 [1];  [2];  [3];  [4];  [5];  [5];  [6];  [2];  [3]
  1. Univ. of California, Merced, CA (United States). School of Natural Sciences; DOE/OSTI
  2. Univ. of California, Merced, CA (United States). School of Natural Sciences
  3. Vassar College, Poughkeepsie, NY (United States). Biology Dept.
  4. Vassar College, Poughkeepsie, NY (United States). Computer Science Dept.
  5. Stanford Univ., CA (United States). Dept. of Genetics
  6. Oregon State Univ., Corvallis, OR (United States). Dept. of Zoology
Background: The most diverse marine ecosystems, coral reefs, depend upon a functional symbiosis between cnidarian hosts and unicellular dinoflagellate algae. The molecular mechanisms underlying the establishment, maintenance, and breakdown of the symbiotic partnership are, however, not well understood. Efforts to dissect these questions have been slow, as corals are notoriously difficult to work with. In order to expedite this field of research, we generated and analyzed a collection of expressed sequence tags (ESTs) from the sea anemone Aiptasia pallida and its dinoflagellate symbiont (Symbiodinium sp.), a system that is gaining popularity as a model to study cellular, molecular, and genomic questions related to cnidarian-dinoflagellate symbioses. Results: A set of 4,925 unique sequences (UniSeqs) comprising 1,427 clusters of 2 or more ESTs (contigs) and 3,498 unclustered ESTs (singletons) was generated by analyzing 10,285 high-quality ESTs from a mixed host/symbiont cDNA library. Using a BLAST-based approach to predict which unique sequences derived from the host versus symbiont genomes, we found that the contribution of the symbiont genome to the transcriptome was surprisingly small (1.6–6.4%). This may reflect low levels of gene expression in the symbionts, low coverage of alveolate genes in the sequence databases, a small number of symbiont cells relative to the total cellular content of the anemones, or failure to adequately lyse symbiont cells. Furthermore, we were able to identify groups of genes that are known or likely to play a role in cnidarian-dinoflagellate symbioses, including oxidative stress pathways that emerged as a prominent biological feature of this transcriptome. All ESTs and UniSeqs along with annotation results and other tools have been made accessible through the implementation of a publicly accessible database named Aiptasia Base. Conclusion: We have established the first large-scale transcriptomic resource for Aiptasia pallida and its dinoflagellate symbiont. These data provide researchers with tools to study questions related to cnidarian-dinoflagellate symbioses on a molecular, cellular, and genomic level. This groundwork represents a crucial step towards the establishment of a tractable model system that can be utilized to better understand cnidarian-dinoflagellate symbioses. With the advent of next generation sequencing methods, the transcriptomic inventory of A. pallida and its symbiont, and thus the extent of Aiptasia Base, should expand dramatically in the near future.
Research Organization:
Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States). National Energy Research Scientific Computing Center (NERSC)
Sponsoring Organization:
USDOE Office of Science (SC), Biological and Environmental Research (BER). Biological Systems Science Division
Grant/Contract Number:
AC02-05CH11231
OSTI ID:
1626399
Journal Information:
BMC Genomics, Journal Name: BMC Genomics Journal Issue: 1 Vol. 10; ISSN 1471-2164
Publisher:
SpringerCopyright Statement
Country of Publication:
United States
Language:
English

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Additional file 1 of Gene expression kinetics of Exaiptasia pallida innate immune response to Vibrio parahaemolyticus infection image January 2020
Additional file 4 of Gene expression kinetics of Exaiptasia pallida innate immune response to Vibrio parahaemolyticus infection dataset January 2020
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Additional file 7 of Gene expression kinetics of Exaiptasia pallida innate immune response to Vibrio parahaemolyticus infection dataset January 2020
Additional file 8 of Gene expression kinetics of Exaiptasia pallida innate immune response to Vibrio parahaemolyticus infection dataset January 2020
Additional file 9 of Gene expression kinetics of Exaiptasia pallida innate immune response to Vibrio parahaemolyticus infection dataset January 2020
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