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Phenotypic plasticity for improved light harvesting, in tandem with methylome repatterning in reef-building corals - PubMed

Phenotypic plasticity for improved light harvesting, in tandem with methylome repatterning in reef-building corals

Kelly Gomez-Campo et al. Mol Ecol. 2024 Feb.

Abstract

Acclimatization through phenotypic plasticity represents a more rapid response to environmental change than adaptation and is vital to optimize organisms' performance in different conditions. Generally, animals are less phenotypically plastic than plants, but reef-building corals exhibit plant-like properties. They are light dependent with a sessile and modular construction that facilitates rapid morphological changes within their lifetime. We induced phenotypic changes by altering light exposure in a reciprocal transplant experiment and found that coral plasticity is a colony trait emerging from comprehensive morphological and physiological changes within the colony. Plasticity in skeletal features optimized coral light harvesting and utilization and paralleled significant methylome and transcriptome modifications. Network-associated responses resulted in the identification of hub genes and clusters associated to the change in phenotype: inter-partner recognition and phagocytosis, soft tissue growth and biomineralization. Furthermore, we identified hub genes putatively involved in animal photoreception-phototransduction. These findings fundamentally advance our understanding of how reef-building corals repattern the methylome and adjust a phenotype, revealing an important role of light sensing by the coral animal to optimize photosynthetic performance of the symbionts.

Keywords: DNA methylation; biological networks; biomineralization; gene expression; phenotypic plasticity.

© 2023 The Authors. Molecular Ecology published by John Wiley & Sons Ltd.

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Conflict of interest statement

Competing Interest Statement: Authors declare no competing interests.

Figures

Figure 1.
Figure 1.. Phenotypic plasticity of Acropora palmata in response to light availability.

(A) A. palmata colonies have a strong intracolonial light gradient. The branching morphology exhibits modules (polyps) exposed to direct sunlight (HL surfaces) and modules growing in the shade (LL surfaces). (B) Morphological skeletal features of the branch cross-section showing the transition from upperside to underside of the branch. (C) HL surfaces and (D) LL surfaces show distinct skeletal morphology, (E) with corallites significantly taller in the surface exposed to HL. (F-N) Phenotypic traits of HL (n= 21) and LL surfaces (n=21) from 3 genets. Center lines show the median and center squares the mean; box limits indicate the 25th and 75th percentiles; whiskers extend 1 time the interquartile range. For all panels, ***P <0.001; **P <0.01; *P<0.05; nsP >0.05, two-tailed, unpaired Student’s t test. (F) Polyp density (# polyps cm−2), (G) Density of corallites larger than 3 mm in height (# polyps cm−2), (H) soluble host protein (mg protein cm−2), (I) symbiont density (# sym cm−2), (J) Chla per symbiont cell (Ci, pg Chla sym−1), (K) Chla density (mg Chla m−2), (L) photosynthetic efficiency (μmol O2 μmol quanta), (M) respiration rate (μmol O2 m−2 s-1), (N) maximum photosynthetic rate (μmol O2 m−2 s−1).

Figure 2.
Figure 2.. Induced phenotypic plasticity with reciprocal transplants.

(A) Schematic representation of the experimental design. Control fragments from HL (n=7 per genet) and LL (n=7 per genet) remained unchanged, while treatment fragments (HL⇾LL, n=7 per genet; LL⇾HL, n=7 per genet) were manipulated in a reciprocal transplant that altered their light exposure by ~80%. After 13 weeks, light phenotypes were described, and tissue was collected for genomic and epigenomic analyses. (B) Fold change of main phenotypic traits showing the acclimatory mechanism to the destination light condition after 5+ weeks of transplant. (C) Visual inspection of one genet after 5+ weeks showing the change in corallite height and density. (D-E) Changes in optical traits based on specific absorption coefficients, a*Chla which describes the holobiont’s efficiency to absorb light and a*sym, which describes in hospite light absorption efficiency of the algal symbionts.

Figure 3.
Figure 3.. DNA Methylation context and light-mediated methylome repatterning.

(A) Proportion of methylated cytosines (n = 8 per group condition) were highest in the CpG context and neglectable in CHG, and CHH contexts. Pie charts show the number of Cytosines (x 106) in each context. (B) Mean methylation levels of all cytosines were highest at genic regions; 2kb upstream of Transcription Start Site (TSS), and 2kb downstream of Transcription End Site (TES) are shown. Methylation levels were computed, divided to 60 bins, and plotted by genet and group condition. (C) Number of DMPs per group conditions identified by Methyl-IT, with centroid of control groups used as reference. DMPs were always higher in treatments than control samples. Two A. palmata genets are shown for comparison. (D) Hierarchical clustering of DMPs in genic regions classified by Hellinger Divergence. Classification of samples separated control (purple) and treatment (red) samples regardless of genet or destination light treatment.

Figure 4.
Figure 4.. Responsive gene networks integrating methylome and transcriptome data: WGCNA.

The data was prepared by combining DMG and DEG datasets to one large dataset. To estimate the initial number of possible groups we performed a (A) hierarchical clustering, which showed a classification of samples separating controls (purple) and treatments (red) groups regardless of genet or destination light treatment. (B) Whole network of gene-gene interactions. (C) Type I subnetwork showing genes with strongest gene-gene interactions (edges with strongest weights from correlation but low gene-score), denotating genes that have similar contribution to the change in phenotype (n = 199 genes). (D, E) Type II subnetworks of hub genes showing strong interactions and loadings (highest gene-scores), denotes hub genes with strongest contribution to the change in phenotype (discriminatory power of treatments from controls). (F-H) Top 10–20 genes based on gene-score in each subnetwork. The colored line between genes represents weight values from correlation matrix, low weight values (yellow) to high weight values (purple), node color indicates if DMG (yellow), both DMG-DEG (blue), DEG (grey).

Figure 5.
Figure 5.. Responsive gene networks integrating methylome and transcriptome data: curated databases.

Main subnetworks of hub genes retrieved from integration of DMGs and DEGs. (A) photoreception-phototransduction (network from StringApp without attributes:

https://version11.string-db.org/cgi/network.pl?networkId=sqcU0gyKux2Y

). (B) ECM-proteins, cell-cell adhesion and EGF-domains associated with soft tissue growth and calcification (network from StringApp without attributes:

https://version11.string-db.org/cgi/network.pl?networkId=8RQKxPbg9zzZ

). (C) Vesicle/vacuole mediated transport, Ca2+ metabolism and cytoskeletal protein binding associated with symbiont trafficking (network from StringApp without attributes:

https://version11.string-db.org/cgi/network.pl?networkId

=Cefq2PjoZN5R). (D) Innate immune response associated to interpartner recognition (network from StringApp without attributes:

https://version11.string-db.org/cgi/network.pl?networkId=

pZerNp9HZxM0). Larger nodes indicate key regulators or a critical target of a regulatory pathway. The line between genes represents interactions. Node color indicates if DMG (yellow), both DMG-DEG (blue), DEG (grey). Font size represents methylation (signal density variation from Methyl-IT) and font color up (red) - down (blue) regulation. Genet 1 LL to HL are shown for interpretation.

Figure 6.
Figure 6.. Predicted model for light-mediated phenotypic plasticity of structural traits in the branching coral Acropora palmata based on key regulators from DMGs-DEGs integrated networks.

A significant change in the light environment activates photoreception mechanisms to detect cues and transduce information within cells (symbionts, cytoskeleton, extra cellular matrix-ECM, and nucleus-Nu are labeled). This activates signaling pathways to control growth, both soft tissue and skeletal growth; and in parallel, to initiate cellular transport related to symbiont recognition and changes in symbiont population densities (network from StringApp without attributes:

https://version11.string-db.org/cgi/network.pl?networkId=uh6Y1lbNXqJR

).

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