Genetic response to human‐induced habitat changes in the marine environment: A century of evolution of European sprat in Landvikvannet, Norway
Quintela, María et al. (2022), Genetic response to human‐induced habitat changes in the marine environment: A century of evolution of European sprat in Landvikvannet, Norway, Dryad, Dataset, https://doi.org/10.5061/dryad.zs7h44j7h
Habitat changes represent one of the five most pervasive threats to biodiversity. However, anthropogenic activities also have the capacity to create novel niche spaces to which species respond differently. In 1880, one such habitat alterations occurred in Landvikvannet, a freshwater lake on the Norwegian coast of Skagerrak, which became brackish after being artificially connected to the sea. This lake is now home to the European sprat, a pelagic marine fish that managed to develop a self-recruiting population in barely few decades. Landvikvannet sprat proved to be genetically isolated from the three main populations described for this species; i.e. Norwegian fjords, Baltic Sea, and the combination of North Sea, Kattegat and Skagerrak. This distinctness was depicted by an accuracy self-assignment of 89% and a highly significant FST between the lake sprat and each of the remaining samples (average of ≈0.105). The correlation between genetic and environmental variation indicated that salinity could be an important environmental driver of selection (3.3% of the 91 SNPs showed strong associations). Likewise, Isolation by Environment was detected for salinity, although not for temperature, in samples not adhering to an Isolation by Distance pattern. Neighbour-joining tree analysis suggested that the source of the lake sprat is in the Norwegian fjords, rather than in the Baltic Sea despite a similar salinity profile. Strongly drifted allele frequencies and lower genetic diversity in Landvikvannet compared with the Norwegian fjords concur with a founder effect potentially associated with local adaptation to low salinity. Genetic differentiation (FST) between marine and brackish sprat is larger in the comparison Norway- Landvikvannet than in Norway-Baltic, which suggests that the observed divergence was achieved in Landvikvannet in some 65 generations, i.e., 132 years, rather than gradually over thousands of years (the age of the Baltic Sea), thus highlighting the pace at which human-driven evolution can happen.
Sprat were sampled by commercial fishermen and scientific cruises from forty locations in the NE Atlantic. As there is a strong management interest in defining stock affiliation of sprat fished in the Kattegat–Skagerrak areas, sprat were sampled in these areas both during the spring spawning season and outside the spawning season by the pelagic fishery. Norwegian fjord samples spanning most of the sprat's Norwegian distribution range were also sampled. Sampling was directed toward ripe individuals, where possible. However, in some areas, samples were mainly taken outside the main spawning season and may thus represent both local and migratory individuals of mixed origin.
DNA was extracted from fin clips stored in ethanol using the Qiagen DNeasy 96 Blood & Tissue Kit in 96‐well plates, each of which contained two or more negative controls.
A double‐digest RAD library was constructed from eight sprat genomic DNA samples from Hardangerfjorden, comprising a 400–700 base pair region of SbfI‐ and SphI‐restricted DNA and involving individual‐specific inline barcode adapters. The methodology has been previously described in detail by Manousaki et al. (2015). The library was thereafter sequenced on the Illumina MiSeq platform (part of a shared flow cell run, V2 chemistry, 300 cycle kit, 160 base paired‐end reads). Stacks software v1.47 (Catchen, Hohenlohe, Bassham, Amores, & Cresko, 2013) was used to demultiplex sequence reads and identify and score SNPs (de novo assembly; key Stacks parameters m (minimum depth of coverage) = 4, M (maximum distance allowed between stacks) = 2, n (number of mismatches allowed between loci among individuals) = 1). Data were then exported to Microsoft Excel for filtering to identify potential SNPs suitable for Sequenom‐based multiplex SNP assay. This involved selecting RAD loci (trimmed length 135 bases) that contained a single diallelic SNP with at least two occurrences of the minor allele among the eight samples and that the SNP was positioned between base 41 and base 95, to allow for enough flanking sequence for PCR primer design. For the final filtered set, SNP locus primer design, amplification, and genotype calling were performed using the Sequenom MassARRAY iPLEX Platform, as described by Gabriel, Ziaugra, and Tabbaa (2009).
Data consists of individual ID, sample and genotypes (SNPs and microsatellites, respectively).
SNPs have been coded as follows: 1(A), 2 (C), 3 (G), 4 (T) and 0 (missing data). Two columns for locus.
Microsatellites have been coded using the fragment size (bp). Two columns per locus.
Norwegian Department of Trade and Fisheries
European Maritime and Fisheries Fund, Award: 33113-B-16-065
Norges Forskningsråd, Award: 299554
European Maritime and Fisheries Fund, Award: 33113‐B‐16‐065
Norwegian Department of Trade and Fisheries