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Data from: Seascape genomics of the sugar kelp Saccharina latissima along the North Eastern Atlantic latitudinal gradient

Citation

Guzinski, Jaromir et al. (2020), Data from: Seascape genomics of the sugar kelp Saccharina latissima along the North Eastern Atlantic latitudinal gradient, Dryad, Dataset, https://doi.org/10.5061/dryad.1jwstqjt8

Abstract

Temperature is one of the most important range-limiting factors for many seaweeds. Driven by the recent climatic changes, rapid northward shifts of species’ distribution ranges can potentially modify the phylogeographic signature of Last Glacial Maximum. We explored this question in detail in the cold-tolerant kelp species Saccharina latissima, using microsatellites and double digest restriction site-associated DNA sequencing (ddRAD-seq) derived single nucleotide polymorphisms (SNPs) to analyze the genetic diversity and structure in 11 sites spanning the entire European Atlantic latitudinal range of this species. In addition, we checked for statistical correlation between genetic marker allele frequencies and three environmental proxies (sea surface temperature, salinity, and water turbidity). Our findings revealed that genetic diversity was significantly higher for the northernmost locality (Spitsbergen) compared to the southern ones (Northern Iberia), which we discuss in light of the current state of knowledge on phylogeography of S. latissima and the potential influence of the recent climatic changes on the population structure of this species. Seven SNPs and 12 microsatellite alleles were found to be significantly associated with at least one of the three environmental variables. We speculate on the putative adaptive functions of the genes associated with the outlier markers and the importance of these markers for successful conservation and aquaculture strategies for S. latissima in this age of rapid global change.

Usage Notes

RADseq_SNP_Rcode has the R code for the SNP-based analyses described in the paper. All of the relevant input files are provided, including VCF files with the sample genotypes at the different stages of the RADseq locus and SNP filtering. 

SSR_Rcode has the R code for the SSR-based analyses described in the paper. All of the relevant input files are provided, including a file with the SSR genotypes for the analysed samples.

Funding

IDEALG, Award: ANR-10-BTBR-04

H2020 Project GENIALG, Award: 727892

MARFOR, Award: Biodiversa/0004/2015

IDEALG, Award: ANR-10-BTBR-04

H2020 Project GENIALG, Award: 727892

MARFOR, Award: Biodiversa/0004/2015