A stepwise genomic analysis of sugar kelp population structure in Atlantic Canada using DArTseq to whole genome sequencing
Data files
Jul 21, 2026 version files 403.60 MB
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README.md
4.55 KB
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S_latissima_ANGSD.vcf.gz
398.81 MB
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S_latissima_DArTseq.vcf.gz
705.95 KB
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S_latissima_GATK.vcf.gz
4.08 MB
Abstract
Saccharina latissima (sugar kelp) is a foundation species of growing commercial interest, yet its population genetic structure in Atlantic Canada remains poorly resolved. A two-tiered genomic approach was used to characterize regional patterns of diversity and connectivity across the Estuary and Gulf of St. Lawrence and the coast of Nova Scotia. Reduced-representation genotyping by DArTseq provided broad spatial coverage (603 individuals, 23 sites, 4,386 SNPs), while low-coverage whole-genome sequencing (WGS) of a representative subset of populations generated high-resolution datasets using both GATK- and ANGSD-based pipelines (105–106 variants). Population structure was congruent across datasets. Nova Scotia populations were clearly differentiated from those in Québec, and finer-scale structure was evident among the Gaspé Peninsula, Baie-des-Chaleurs, North Shore and Miquelon. Neutral WGS datasets revealed moderate differentiation and predominantly negative FIS values. Outlier loci showed elevated FST, indicating that adaptive divergence amplifies underlying demographic structure. Although DArTseq produced higher and more variable FST estimates, it recovered the same major groupings, underscoring robustness across marker systems. Lower diversity in estuarine populations and a higher number of private-alleles in Nova Scotia are consistent with serial founder effects during postglacial range expansion, while the Gulf of St. Lawrence likely represents a suture zone where distinct lineages have admixed. These results reveal strong, hierarchical population structure in S. latissima shaped by limited dispersal, environmental heterogeneity and historical colonization processes. The convergence across genomic approaches provides a robust foundation for delineating management units and supporting germplasm banking and selective breeding for sustainable kelp aquaculture in the Northwest Atlantic.
Dataset DOI: 10.5061/dryad.qjq2bvqx5
Citation
Puncher GN, LeCam S, O'Leary SJB, Salvo F, Dufresne F (2026) A stepwise genomic analysis of sugar kelp population structure in Atlantic Canada using DArTseq to whole genome sequencing. Journal of Applied Phycology. doi: 10.1007/s10811-026-03966-x
Contact
For questions about these data, contact gregpuncher@gmail.com.
Description of the data and file structure
Three genotype datasets are provided, corresponding to three genotyping/variant-calling approaches (DArTseq, WGS-GATK, WGS-ANGSD).
Files and variables
File: S_latissima_ANGSD.vcf.gz
Description: Samples: 84 individuals (subset of DArTseq samples + newly collected 2023 samples)
- Markers: ~270,000 SNPs.
- Generation method: Low-coverage WGS (Illumina NovaSeq X Plus, 2×150bp paired-end), aligned to the S. latissima reference genome (DeWeese et al. 2025) with Bowtie2. Genotype likelihoods estimated per population in ANGSD, with site allele frequency likelihoods used to infer per-population site frequency spectra (realSFS) that were supplied back to ANGSD as priors (-pest) for refined genotype calling. A common SNP panel was identified across populations, and ANGSD was rerun on this shared panel to produce hard-called genotypes.
- Filtering applied: uniquely mapped, properly paired reads only; mapping quality ≥30; base quality ≥20; triallelic sites removed; base alignment quality adjustment (-C 50); minimum depth per individual = 3 reads (-setMinDepthInd 3); minimum total site depth = 168 (-setMinDepth 168); maximum total site depth = 840 (-setMaxDepth 840).
File: S_latissima_GATK.vcf.gz
Description: Samples: 84 individuals (subset of DArTseq samples + newly collected 2023 samples)
- Markers: ~136,000 SNPs
- Generation method: Low-coverage WGS (Illumina NovaSeq X Plus, 2×150bp paired-end), aligned to the S. latissima reference genome (DeWeese et al. 2025) with Bowtie2. Variants called with GATK HaplotypeCaller → GenomicsDBImport → GenotypeGVCFs → SelectVariants, merged with bcftools.
- Filtering applied: GATK VariantFiltration thresholds — QD < 2.0, FS > 60.0, MQ < 40.0, MQRankSum < –12.5, ReadPosRankSum < –8.0; ExcessHet > 54.69 removed (paralogs/structural variant artifacts).
File: S_latissima_DArTseq.vcf.gz
Description: Samples: 603 individuals, 23 sites
- Markers: 4,386 SNPs
- Generation method: Reduced-representation genotyping-by-sequencing (DArTseq™, Diversity Arrays Technology), PstI/HpaII digestion, HiSeq 2500 single-read 77bp, scored with DArTsoft14, aligned to the Saccharina japonica reference genome (Ye et al. 2015).
- Filtering applied: Monomorphic loci removed; loci with >5% missing data removed; duplicate loci removed; minor allele frequency (MAF) < 0.01 removed; individuals with >10% missing data removed; loci deviating significantly from Hardy–Weinberg equilibrium (p < 0.01) in ≥25% of populations removed.
Code/software
All 3 files are viewable/parsable with bcftools (v1.22) or vcftools, both freely available at https://github.com/samtools/bcftools and https://vcftools.github.io. Files are bgzipped and tabix-indexed; tabix (part of the HTSlib/SAMtools suite, v1.22.1) is required to use the index. Any text editor can open the uncompressed VCF header/body, but bcftools is recommended for practical use (filtering, subsetting, format conversion).
Access information
Other publicly accessible locations of the data:
- Trimmed and aligned reads underlying the GATK and ANGSD genotype datasets are available at NCBI under BioProject accession PRJNA1492732. Raw sequence processing (adapter/quality trimming with Trimmomatic, alignment to the S. latissima reference genome with Bowtie2) was completed prior to deposition; only the processed, filtered SNP genotype outputs are included in this Dryad submission. Users wishing to reproduce or extend the variant-calling steps described above should begin from the BAM files archived at PRJNA1492732.
Funding and copyright
This research was funded by the Government of Canada. © His Majesty the King in Right of Canada, as represented by the National Research Council of Canada, 2026.
