Investigating the potential roles of intra-colonial genetic variability in Pocillopora corals using genomics

Abstract

Intra-colonial genetic variability (IGV), the presence of more than one genotype in a single colony, has been increasingly studied in scleractinians, revealing its high prevalence. Several studies hypothesised that IGV brings benefits, but few have investigated its roles from a genetic perspective. Here, using genomic data (SNPs), we investigated these potential benefits in populations of the coral Pocillopora acuta from Reunion Island (southwestern Indian Ocean). As the detection of IGV depends on sequencing and bioinformatics errors, we first explored the impact of the bioinformatics pipeline on its detection. Then, SNPs and genes variable within colonies were characterised. While most of the tested bioinformatics parameters did not significantly impact the detection of IGV, filtering on genotype depth of coverage strongly improved its detection by reducing genotyping errors. Mosaicism and chimerism, the two processes leading to IGV (the first through somatic mutations, the second through fusion of distinct organisms), were found in 7% and 12% of the colonies, respectively. Both processes led to several intra-colonial allelic differences, but most were non-coding or silent. However, 7% of the differences were non-silent and found in genes involved in a high diversity of biological processes, some of which were directly linked to responses to environmental stresses. IGV, therefore, appears as a source of genetic diversity and genetic plasticity, increasing the adaptive potential of colonies. Such benefits undoubtedly play an important role in the maintenance and the evolution of scleractinian populations and appear crucial for the future of coral reefs in the context of ongoing global changes.

Figure 1

Sampling sites (black dots) of Pocillopora acuta colonies in Reunion Island (number of colonies in parentheses). For each site, the distribution of the number of nubbins (three per colony) per genomic species hypothesis (GSH sensu Oury et al.) is indicated. Map generated in R v4.0.4.

Figure 2

Effect of single-nucleotide polymorphism (SNP) calling and filtering parameters on the detection of intra-colonial genetic variability (IGV). Percentage of IGV colonies as a function of the threshold in percentage of different alleles between nubbins. Dots and associated whiskers indicate means (over nine comparisons) and ranges of pairwise distances among sequencing replicates of the same nubbins, respectively.

Figure 3

Distribution of the percentages of different alleles between all pairs of nubbins, with a zoom window between 0 and 2%. GSHs: genomic species hypotheses.

Figure 4

Proportions of the categories of genetic variability (a) per sampling site, (b) per genomic species hypothesis (GSH), and (c) overall colonies (number of colonies in parentheses). Distributions are not significantly different among sampling sites (Fisher exact test; P = 0.06) nor between GSHs (Fisher exact test; P = 1.00).

Figure 5

Characterisation of chimerism. (a) Distribution of the occurrence of single-nucleotide polymorphisms (SNPs) variable within chimeras, with a focus on the nature of the substitutions, (b) details on differences impacts for coding SNPs, and (c) dendrogram based on the dissimilarity of the 40 biological processes gene ontology (GO) terms obtained after term reduction for the genes most impacted by non-silent allelic differences. The relative representation of each GO term is shown as a heatmap.

Figure 6

Characterisation of mosaicism. (a) Distribution of the occurrence of single-nucleotide polymorphisms (SNPs) variable within colonies, with a focus on the nature of the substitutions, (b) details on differences impacts for coding SNPs, and (c) dendrogram based on the dissimilarity of the 74 biological processes gene ontology (GO) terms obtained after term reduction for the genes most impacted by non-silent allelic differences. The relative representation of each GO term is shown as a heatmap.