4.7 Article

NvERTx: a gene expression database to compare embryogenesis and regeneration in the sea anemone Nematostella vectensis

Journal

DEVELOPMENT
Volume 145, Issue 10, Pages -

Publisher

COMPANY BIOLOGISTS LTD
DOI: 10.1242/dev.162867

Keywords

Embryogenesis; Regeneration; Transcriptome; Database; Cnidarian; Nematostella vectensis

Funding

  1. ATIP-Avenir (Institut National de la Sante et de la Recherche Medicale) - Plan Cancer (Institut National Du Cancer) [C13992AS]
  2. ATIP-Avenir (Centre National de la Recherche Scientifique) - Plan Cancer (Institut National Du Cancer) [C13992AS]
  3. Seventh Framework Programme [631665]
  4. Association pour la Recherche sur le Cancer [PJA 2014120186, PDF20141202150]
  5. Fondation pour la Recherche Medicale [SPF20130526781]
  6. Ligue Contre le Cancer
  7. Ministere de l'Enseignement Superieur et de la Recherche

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For over a century, researchers have been comparing embryogenesis and regeneration hoping that lessons learned from embryonic development will unlock hidden regenerative potential. This problem has historically been a difficult one to investigate because the best regenerative model systems are poor embryonic models and vice versa. Recently, however, there has been renewed interest in this question, as emerging models have allowed researchers to investigate these processes in the same organism. This interest has been further fueled by the advent of high-throughput transcriptomic analyses that provide virtual mountains of data. Here, we present Nematostella vectensis Embryogenesis and Regeneration Transcriptomics (NvERTx), a platform for comparing gene expression during embryogenesis and regeneration. NvERTx consists of close to 50 transcriptomic data sets spanning embryogenesis and regeneration in Nematostella. These data were used to perform a robust de novo transcriptome assembly, with which users can search, conduct BLAST analyses, and plot the expression of multiple genes during these two developmental processes. The site is also home to the results of gene clustering analyses, to further mine the data and identify groups of co-expressed genes. The site can be accessed at http://nvertx.kahikai.org.

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