Abstract

BackgroundSingle nucleotide polymorphisms (SNPs) represent the most widespread type of DNA variation in vertebrates and may be used as genetic markers for a range of applications. This has led to an increased interest in identification of SNP markers in non-model species and farmed animals. The in silico SNP mining method used for discovery of most known SNPs in Atlantic salmon (Salmo salar) has applied a global (genome-wide) approach. In this study we present a targeted 3'UTR-primed SNP discovery strategy that utilizes sequence data from Salmo salar full length sequenced cDNAs (FLIcs). We compare the efficiency of this new strategy to the in silico SNP mining method when using both methods for targeted SNP discovery.ResultsThe SNP discovery efficiency of the two methods was tested in a set of FLIc target genes. The 3'UTR-primed SNP discovery method detected novel SNPs in 35% of the target genes while the in silico SNP mining method detected novel SNPs in 15% of the target genes. Furthermore, the 3'UTR-primed SNP discovery strategy was the less labor intensive one and revealed a higher success rate than the in silico SNP mining method in the initial amplification step. When testing the methods we discovered 112 novel bi-allelic polymorphisms (type I markers) in 88 salmon genes [dbSNP: ss179319972-179320081, ss250608647-250608648], and three of the SNPs discovered were missense substitutions.ConclusionsFull length insert cDNAs (FLIcs) are important genomic resources that have been developed in many farmed animals. The 3'UTR-primed SNP discovery strategy successfully utilized FLIc data to detect novel SNPs in the partially tetraploid Atlantic salmon. This strategy may therefore be useful for targeted SNP discovery in several species, and particularly useful in species that, like salmonids, have duplicated genomes.

Highlights

  • Single nucleotide polymorphisms (SNPs) represent the most widespread type of DNA variation in vertebrates and may be used as genetic markers for a range of applications

  • While single nucleotide polymorphisms (SNPs) discovery projects that have applied the in silico SNP mining method has exploited expressed sequence tags (ESTs) that consist of a combination of coding sequence (CDS) and untranslated regions (UTRs) sequences, a UTR-primed method that utilizes sequence information from annotated Full length insert cDNAs (FLIcs) could target 3’ untranslated region (3’UTR) only, and allow for a SNP search in gene fragments that are expected to have a higher SNP density than the ESTs utilized so far

  • Due to the successful use of the in silico SNP mining method for global SNP discovery we have included this method in our study, and we present results from testing the in silico SNP mining method when applied for targeted SNP discovery in FLIc genes

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Summary

Results

The SNP discovery efficiency of the two methods was tested in a set of FLIc target genes. The 3’UTRprimed SNP discovery method detected novel SNPs in 35% of the target genes while the in silico SNP mining method detected novel SNPs in 15% of the target genes. The 3’UTR-primed SNP discovery strategy was the less labor intensive one and revealed a higher success rate than the in silico SNP mining method in the initial amplification step. When testing the methods we discovered 112 novel bi-allelic polymorphisms (type I markers) in 88 salmon genes [dbSNP: ss179319972-179320081, ss250608647-250608648], and three of the SNPs discovered were missense substitutions

Conclusions
Background
Results and Discussion
Search for random SNP and validation of SNP
Validation of putative SNP by sequencing genomic DNA
Conclusion
Methods
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