bioRxivGenomicsPreprint
Within-colony color variation in a chalice coral is associated with region-specific pigment expression and higher photoconvertible pigment transcripts
Abstract
A single colony of colonial coral often demonstrates conspicuous color variation. However, the molecular basis of this variation within a single, clonal individual is poorly understood. While coral tissues within a single colony have distinct colors, they share the same genetic background, suggesting differences between them are regulatory rather than genetic. This pilot study aims to characterize the transcriptional mechanisms of color regions in a green-and-orange chalice coral colony through an end-to-end transcriptomic analysis. First, we sampled the green body, an orange oral region, and a transition region between them. Then, a holobiont transcriptome was assembled de novo from paired-end RNA-seq of each color region. In the holobiont transcriptome, coral host transcripts were separated from dinoflagellate symbiont transcripts. Green fluorescent protein (GFP)-like pigment genes were classified phylogenetically. Their expression was then quantified using host-only normalization, which corrects for a large regional difference in symbiont read fraction, and compared across color regions. Relative to the green body, the orange oral region showed higher expression of two sets of host pigment genes: distinct orange fluorescent-protein and chromoprotein transcripts, and green-to-red photoconvertible EosFP-family proteins whose unconverted state is green, implicating photoconversion as a contributing mechanism. This study reveals that distinct color regions within a single colony are associated with region-specific up-regulation of different pigment transcripts, including both directly colored proteins and photoconvertible proteins. Further research is needed to confirm spectrally that photoconversion contributes to the coloration and test whether the pattern holds across multiple colonies.
- organism: non-human primate
- assay: bulk RNA-seq
- research focus: differential expression
- approach: statistical model
- Citations
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