Population genetic analysis reveals a geographically limited transition zone between two genetically distinct Atlantic salmon lineages in Norway.

Atlantic salmon is characterized by a high degree of population genetic structure throughout its native range. However, while populations inhabiting rivers in Norway and Russia make up a significant proportion of salmon in the Atlantic, thus far, genetic studies in this region have only encompassed low to modest numbers of populations. Here, we provide the first "in-depth" investigation of population genetic structuring in the species in this region. Analysis of 18 microsatellites on >9,000 fish from 115 rivers revealed highly significant population genetic structure throughout, following a hierarchical pattern. The highest and clearest level of division separated populations north and south of the Lofoten region in northern Norway. In this region, only a few populations displayed intermediate genetic profiles, strongly indicating a geographically limited transition zone. This was further supported by a dedicated cline analysis. Population genetic structure was also characterized by a pattern of isolation by distance. A decline in overall genetic diversity was observed from the south to the north, and two of the microsatellites showed a clear decrease in number of alleles across the observed transition zone. Together, these analyses support results from previous studies, that salmon in Norway originate from two main genetic lineages, one from the Barents-White Sea refugium that recolonized northern Norwegian and adjacent Russian rivers, and one from the eastern Atlantic that recolonized the rest of Norway. Furthermore, our results indicate that local conditions in the limited geographic transition zone between the two observed lineages, characterized by open coastline with no obvious barriers to gene flow, are strong enough to maintain the genetic differentiation between them.

Investigating the frequency of triploid Atlantic salmon in wild Norwegian and Russian populations.

BACKGROUND: Fish may display variations in ploidy, including three sets of chromosomes, known as triploidy. A recent study revealed a frequency of ~ 2% spontaneous (i.e., non-intentional) triploidy in domesticated Atlantic salmon produced in Norwegian aquaculture in the period 2007-2014. In contrast, the frequency of triploidy in wild salmon populations has not been studied thus far, and in wild populations of other organisms, it has been very rarely studied. In population genetic data sets, individuals that potentially display chromosome abnormalities, such as triploids with three alleles, are typically excluded on the premise that they may reflect polluted or otherwise compromised samples. Here, we critically re-investigated the microsatellite genetic profile of ~ 6000 wild Atlantic salmon sampled from 80 rivers in Norway and Russia, to investigate the frequency of triploid individuals in wild salmon populations for the first time. RESULTS: We detected a single triploid salmon, and five individuals displaying three alleles at one of the loci, thus regarded as putatively trisomic. This gave an overall frequency of triploid and putatively trisomic individuals in the data set of 0.017 and 0.083% respectively. The triploid salmon was an adult female, and had spent 2 years in freshwater and 2 years in the sea. CONCLUSIONS: We conclude that the frequency of naturally-occurring triploid Atlantic salmon in wild Norwegian and Russian populations is very low, and many-fold lower than the frequency of spontaneous triploids observed in aquaculture. Our results suggest that aquaculture rearing conditions substantially increase the probability of triploidy to develop, and/or permits greater survival of triploid individuals, in comparison to the wild.

Finding markers that make a difference: DNA pooling and SNP-arrays identify population informative markers for genetic stock identification.

Genetic stock identification (GSI) using molecular markers is an important tool for management of migratory species. Here, we tested a cost-effective alternative to individual genotyping, known as allelotyping, for identification of highly informative SNPs for accurate genetic stock identification. We estimated allele frequencies of 2880 SNPs from DNA pools of 23 Atlantic salmon populations using Illumina SNP-chip. We evaluated the performance of four common strategies (global F ST, pairwise F ST, Delta and outlier approach) for selection of the most informative set of SNPs and tested their effectiveness for GSI compared to random sets of SNP and microsatellite markers. For the majority of cases, SNPs selected using the outlier approach performed best followed by pairwise F ST and Delta methods. Overall, the selection procedure reduced the number of SNPs required for accurate GSI by up to 53% compared with randomly chosen SNPs. However, GSI accuracy was more affected by populations in the ascertainment group rather than the ranking method itself. We demonstrated for the first time the compatibility of different large-scale SNP datasets by compiling the largest population genetic dataset for Atlantic salmon to date. Finally, we showed an excellent performance of our top SNPs on an independent set of populations covering the main European distribution range of Atlantic salmon. Taken together, we demonstrate how combination of DNA pooling and SNP arrays can be applied for conservation and management of salmonids as well as other species.

Cost-effective genome-wide estimation of allele frequencies from pooled DNA in Atlantic salmon (Salmo salar L.).

BACKGROUND: New sequencing technologies have tremendously increased the number of known molecular markers (single nucleotide polymorphisms; SNPs) in a variety of species. Concurrently, improvements to genotyping technology have now made it possible to efficiently genotype large numbers of genome-wide distributed SNPs enabling genome wide association studies (GWAS). However, genotyping significant numbers of individuals with large number of SNPs remains prohibitively expensive for many research groups. A possible solution to this problem is to determine allele frequencies from pooled DNA samples, such 'allelotyping' has been presented as a cost-effective alternative to individual genotyping and has become popular in human GWAS. In this article we have tested the effectiveness of DNA pooling to obtain accurate allele frequency estimates for Atlantic salmon (Salmo salar L.) populations using an Illumina SNP-chip. RESULTS: In total, 56 Atlantic salmon DNA pools from 14 populations were analyzed on an Atlantic salmon SNP-chip containing probes for 5568 SNP markers, 3928 of which were bi-allelic. We developed an efficient quality control filter which enables exclusion of loci showing high error rate and minor allele frequency (MAF) close to zero. After applying multiple quality control filters we obtained allele frequency estimates for 3631 bi-allelic loci. We observed high concordance (r > 0.99) between allele frequency estimates derived from individual genotyping and DNA pools. Our results also indicate that even relatively small DNA pools (35 individuals) can provide accurate allele frequency estimates for a given sample. CONCLUSIONS: Despite of higher level of variation associated with array replicates compared to pool construction, we suggest that both sources of variation should be taken into account. This study demonstrates that DNA pooling allows fast and high-throughput determination of allele frequencies in Atlantic salmon enabling cost-efficient identification of informative markers for discrimination of populations at various geographical scales, as well as identification of loci controlling ecologically and economically important traits.