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Background  Single nucleotide polymorphisms (SNPs) represent the most abundant type of DNA variation in the vertebrate genome, and their applications as genetic markers in numerous studies of molecular ecology and conservation of natural populations are emerging. Recent large-scale sequencing projects in several fish species have provided a vast amount of data in public databases, which can be utilized in novel SNP discovery in salmonids. However, the suggested duplicated nature of the salmonid genome may hamper SNP characterization if the primers designed in conserved gene regions amplify multiple loci.    Results  Here we introduce a new intron-primed exon-crossing (IPEC) method in an attempt to overcome this duplication problem, and also evaluate different priming methods for SNP discovery in Atlantic salmon ( Salmo salar ) and other salmonids. A total of 69 loci with differing priming strategies were screened in  S. salar , and 27 of these produced ~13 kb of high-quality sequence data consisting of 19 SNPs or indels (one per 680 bp). The SNP frequency and the overall nucleotide diversity (3.99 × 10 -4 ) in  S. salar  was lower than reported in a majority of other organisms, which may suggest a relative young population history for Atlantic salmon. A subset of primers used in cross-species analyses revealed considerable variation in the SNP frequencies and nucleotide diversities in other salmonids.    Conclusion  Sequencing success was significantly higher with the new IPEC primers; thus the total number of loci to screen in order to identify one potential polymorphic site was six times less with this new strategy. Given that duplication may hamper SNP discovery in some species, the IPEC method reported here is an alternative way of identifying novel polymorphisms in such cases.

bmc genomics

Single nucleotide polymorphism (SNP) discovery in duplicated genomes: intron-primed exon-crossing (IPEC) as a strategy for avoiding amplification of duplicated loci in Atlantic salmon (Salmo salar) and other salmonid fishes