Characterization of fine geographic scale population genetics in sugar kelp (Saccharina latissima) using genome-wide...

Kelps are not only ecologically important, being primary producers and habitat forming species, they also hold substantial economic potential. Expansion of the kelp cultivation industry raises the interest for genetic improvement of kelp for cultivation, as well as concerns about genetic introgression from cultivated to wild populations. Thus, increased understanding of population genetics in natural kelp populations is crucial. Genotyping-by-sequencing (GBS) is a powerful tool for studying population genetics. Here, using Saccharina latissima (sugar kelp) as our study species, we characterize the population genetics at a fine geographic scale, while also investigating the influence of marker type (biallelic SNPs versus multi-allelic short read-backed haplotypes) and minor allele count (MAC) thresholds on estimated population genetic metrics.

We examined 150 sporophytes from 10 locations within a small area in Mid-Norway. Employing GBS, we detected 20,710 bi-allelic SNPs and 42,264 haplotype alleles at 20,297 high quality GBS loci. We used both marker types as well as two MAC filtering thresholds (3 and 15) in the analyses. Overall, higher genetic diversity, more outbreeding and stronger substructure was estimated using haplotypes compared to SNPs, and with MAC 15 compared to MAC 3. The population displayed high genetic diversity (H_E ranging from 0.18-0.37) and significant outbreeding (F_IS ≤  - 0.076). Construction of a genomic relationship matrix, however, revealed a few close relatives within sampling locations. The connectivity between sampling locations was high (F_ST ≤ 0.09), but subtle, yet significant, genetic substructure was detected, even between sampling locations separated by less than 2 km. Isolation-by-distance was significant and explained 15% of the genetic variation, while incorporation of predicted currents in an "isolation-by-oceanography" model explained a larger proportion (~ 27%).

The studied population is diverse, significantly outbred and exhibits high connectivity, partly due to local currents. The use of genome-wide markers combined with permutation testing provides high statistical power to detect subtle population substructure and inbreeding or outbreeding. Short haplotypes extracted from GBS data and removal of rare alleles enhances the resolution. Careful consideration of marker type and filtering thresholds is crucial when comparing independent studies, as they profoundly influence numerical estimates of population genetic metrics.