BMC BiologyDevelopmental BiologyPeer-reviewed journal article
Major transitions in early coral development: novel insights enabled by visualisation of a comprehensive transcriptomic dataset for Acropora millepora
Ramona BrunneriD, Mila GrinblatiD, Aurélie MoyaiD, Sylvain ForêtiD, David C. HaywardiD, Bruno Lapeyre, Eldon E. BalliD, Ira CookeiD, David John MilleriD
Abstract
BackgroundGiven the ecological importance of reef-building corals (Scleractinia), it is perhaps surprising that the molecular mechanisms underlying many of the morphological and metabolic changes during their development remain unclear. In part, this is due to the lack of a comprehensive transcriptomic dataset for any coral. A second challenge in the analysis of such non-model developmental datasets is that the volume of data often complicates its interpretation. ResultsTo overcome these limitations, we profiled gene expression in Acropora millepora across 26 life stages from unfertilised eggs to juvenile polyps and developed an interactive online tool based on the R-application Shiny to simultaneously visualise changes in the expression of large numbers of genes. As expected, major transcriptomic changes (transitions) occurred during gastrulation and the acquisition of competence. Surprisingly, however, settlement triggered by using the natural inducer CCA did not immediately lead to major changes in gene expression, but a major transition involving many genes was observed 3 - 6 hours after settlement induction. ConclusionsWe hope that providing access to this extensive developmental transcriptome dataset and software to facilitate its analysis will expedite a better understanding of the changes that occur during coral development. The online tool is available at https://amil-deview.mmb.group.
- organism: non-human primate
- assay: bulk RNA-seq
- research focus: cell type annotation
- research focus: dimensionality reduction
- research focus: database / resource
- research focus: software / tool
- approach: statistical model
- Citations
- 1
- FWCI
- 3.47
- Field percentile
- top 14%
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