bioRxivDevelopmental BiologyPreprint
microRNA expression during early development in the coral Acropora digitifera
Mila GrinblatiD, Arie FridrichiD, Ira CookeiD, Yehu MoraniD, Roger HuerlimanniD, Ramona BrunneriD, Natalia Andrade-RodrigueziD, Nobuo UedaiD, Eldon E. BalliD, David John MilleriD
Abstract
Acropora spp. are the dominant reef-builders of the Indo-Pacific but are also amongst the most stress-sensitive corals. For these reasons, Acropora spp. have become the most studied of corals, two species (A. digitifera and A. millepora) often essentially serving as the basis for understanding molecular responses and processes across the sub-order Refertina and corals in general. The early development of these species has been well-characterised in terms of morphology and gene expression but as yet we have a limited understanding of how transcription is regulated during development. In "higher" animals (bilaterians) microRNAs (miRNAs) are critical regulators of gene expression but until now their involvement in coral development has not been investigated. Building on the existing developmental data for Acropora spp., we catalogued microRNAs (miRNAs) expressed during the early development of Acropora digitifera and profiled their expression in 21 stages from unfertilised eggs to 24h after treatment with a natural settlement cue (CCA chips). 157 miRNAs were recognised, many of which ([~]60%) were novel. These fell into three distinct groups, corresponding to three distinct developmental phases: (1) those present in eggs through to gastrulation (2) a larvally expressed group and (3) those expressed following settlement induction. Exposure of competent larvae to a natural settlement inducer resulted in major changes in the miRNA profile within 10 minutes, indicating that miRNAs may be particularly important in mediating the larva/polyp transition but are also likely to play important regulatory roles throughout early coral development in addition to possible roles in disease resistance.
- organism: non-human primate
- research focus: gene regulatory network inference
- approach: statistical model
- Citations
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