Genet identity and season drive gene expression in outplanted Acropora palmata at different reef sites

Abstract

Coral reefs are experiencing decreases in coral cover due to anthropogenic influences. Coral restoration is addressing this decline by outplanting large volumes of corals onto reef systems. Understanding how outplanted corals react at a transcriptomic level to different outplant locations over time is important, as it will highlight how habitat affects the coral host and influences physiological measures. In this study, the transcriptomic dynamics of four genets of outplanted Acropora palmata were assessed over a year at three reef sites in the Florida Keys. Genet identity was more important than time of sampling or outplant site, with differing levels of baseline immune and protein production the key drivers. Once accounting for genet, enriched growth processes were identified in the winter, and increased survival and immune expression were found in the summer. The effect of the reef site was small, with hypothesized differences in autotrophic versus heterotrophic dependent on outplant depth. We hypothesize that genotype identity is an important consideration for reef restoration, as differing baseline gene expression could play a role in survivorship and growth. Additionally, outplanting during cooler winter months may be beneficial due to higher expression of growth processes, allowing establishment of outplants on the reef system.

Keywords: Acropora palmata; Coral restoration; Florida keys; Immune gene expression; RNA-seq.

Fig. 1

Reef location, outplant sampling summaries, and sea surface temperatures (SST) for the three reef sites. (A) Locations of the three reef sites in the Florida Keys denoted by red dots. Inset map bottom right identifies the location with a square box of the main map image. (B) Field sampling summaries and samples selected for RNA-seq analysis. The table shows each sampling time point (ST; column 1), reef site (column 2), date of sampling (column 3), the total number of days to sample all reef sites for each sampling time point (column 4), and which subset of sampling time points were selected for RNA-seq analysis. (C) Plot of OISST at the three reef sites studied (colored lines). Seasons are indicated on the figure by blue fill (wet season) and red (dry season). Sampling time point ranges are indicated by black vertical bars on the plot.

Fig. 2

Genet identity was the largest driver of gene expression variance, with expression profile clusters identifying different baseline expressions among genets. (A) Principal component (PC) 1 (16% variance) and PC2 (14% variance) of the four genets with 95% confidence intervals. (B) PC 2 (14% variance) and PC3 (12% variance) of the four genets with 95% confidence intervals. (C) PC 3 (12% variance) and PC4 (10% variance) of the four genets with 95% confidence intervals. (D) The six identified clusters from degreport::degpattern of the significant LRT genes identified between the four genets. Each box identifies a cluster, with the x-axis showing the genet, and the y-axis the computed expression z-score for each genet. A value closer to 1 indicates higher expression, a value closer to 0 indicates neutral expression, and a value closer to − 1 indicates lower expression. (E) Inferred function identified from GO and KEGG enrichment analysis for each cluster. Cells with “—” indicate no inferred function due to low or no significantly enriched GO or KEGG terms. For (A)–(D); tan = genet CN2, blue = genet CN4, green = genet HS1, and gray = genet ML2.

Fig. 3

There were significantly correlated co-expression modules to sampling time point and reef location when accounting for genet variance. (A) Heatmap of co-expression modules and their respective correlation and significance to metadata variables of interest. Columns are split into a) sampling time point 2–5 and average OISST, b) reef locations, and c) cluster outplant depth. Heatmap rows are split into sets of co-expression modules. The heatmap fill; red = positive correlation, blue = negative correlation. Text in each cell identifies the Pearson correlation (upper value) and p-value (lower value). White cells denote a significance of >0.05 and were removed. Bar chart to the right of the heatmap indicates the number of genes in each respective co-expression module. (B) Identified hub gene and putative function of each module as ascertained from significant GO and KEGG enrichment pathway analyses. Full GO and KEGG enrichment results used to infer function are available in Supplementary Files S7 and S8 respectively.