Skip to main content

Genomic variation of an endosymbiotic dinoflagellate (Symbiodinium fitti) among closely related coral hosts

Cite this dataset

Reich, Hannah et al. (2021). Genomic variation of an endosymbiotic dinoflagellate (Symbiodinium fitti) among closely related coral hosts [Dataset]. Dryad.


Mutualisms where hosts are coupled metabolically to their symbionts often exhibit high partner fidelity. Most reef-building coral species form obligate symbioses with a specific species of photosymbionts, dinoflagellates in the family Symbiodiniaceae, despite needing to acquire symbionts early in their development from environmental sources. Three Caribbean acroporids (Acropora palmata, A. cervicornis, and their F1 hybrid) are geographically sympatric across much of their range, but often occupy different depth and light habitats. Throughout this range, both species and their hybrid associate with the endosymbiotic dinoflagellate Symbiodinium ’fitti’. Because light (and therefore depth) influences the physiology of dinoflagellates, we investigated whether S. ‘fitti’ populations from each host taxon were differentiated genetically. Single nucleotide polymorphisms (SNPs) among S. ‘fitti’ strains, or genotypes, were identified by aligning shallow metagenomic sequences of acroporid colonies sampled from across the Caribbean to a ~600 Mb draft assembly of the S. ‘fitti’ genome (from the CFL14120 A. cervicornis metagenome). Phylogenomic and multivariate analyses revealed that genomic variation among S. ‘fitti’ strains partitioned to each host taxon rather than by biogeographic origin. This is particularly noteworthy because the hybrid has a sparse fossil record and may be of relatively recent origin. A subset (37.6%) of the SNPs putatively under selection were non-synonymous mutations predicted to alter protein efficiency. Differences in genomic variation of S. ‘fitti’ from each host taxon may reflect the unique selection pressures created by the microenvironments associated with each host. The non-random sorting among S. ‘fitti’ strains to different hosts could be the basis for lineage diversification via disruptive selection, leading to ecological specialization and ultimately speciation.

Usage notes


Table of file name & descriptions***

File name File description reference genome used for analyses1
Sfitti_Apalm_v1.fa.gz additional draft assembly2
Sfitti.aa.fasta Sfitti protein sequences3
Sfitti_genome_annotation.csv Annotation information for 37,000+ Sfitti genes (csv format of table S3)4
Sfitti_EVM_all_gff3.bed bed file of 37,000+ Sfitti genes3 gff3 file of 37,000+ Sfitti genes3 VCF file of 58+k "high quality" Sfitti SNPs5 VCF file of 6813 "high quality" Sfitti SNPs without missing data5 VCF file of 16+k "high quality" Sfitti SNPs found in gene regions6 VCF file of 5067 "high quality" Sfitti SNPs identified as selection outliers by BayeScan and PCAdapt6,7,8 VCF file of 58+k "high quality" Sfitti SNPs with SNPEFF Annotation 9


Draft genome assembly of Symbiodinium 'fitti' from Reich et al. The draft assembly ( is from the Acropora cervicornis CFL14120 metagenome. The CFL14120 Sfitti assembly was the reference used for all SNP analyses in Reich et al.

An additional draft S. 'fitti' (PFL1012; Sfitti_Apalm_v1.fa.gz) assembly from an A. palmata metagenome is also available on dryad. Please note that this assembly was not used as a reference for SNP calling in Reich et al because it's completeness metrics are inferior to that of CFL14120.

Location of code for S. 'fitti' gene prediction

Location of code for S. 'fitti' gene prediction annotation (Table S3; Sfitti_genome_annotation.csv) 

Location of code for S. 'fitti' SNP calling and filtering

6 Location of code for identifying high-quality S. 'fitti' SNPs in gene regions (Table S4) and selection outlier SNPs (Table S7)  

7 Location of code for PCAdapt selection outlier detection

8 Location of code for Bayescan selection outlier detection

9 Location of code for SNPEFF summary stats and annotation information (Tables S9 and S10)

***All code for statistical analyses & figure generation can be found on the paper's github. Important files such as VCF, genome annotation, gene bed files, and nexus files are also available