Development and characterisation of an expressed sequence tags (EST)-derived single nucleotide polymorphisms (SNPs) resource in rainbow trout

BACKGROUND: There is considerable interest in developing high-throughput genotyping with single nucleotide polymorphisms (SNPs) for the identification of genes affecting important ecological or economical traits. SNPs are evenly distributed throughout the genome and are likely to be functionally relevant. In rainbow trout, in silico screening of EST databases represents an attractive approach for de novo SNP identification. Nevertheless, EST sequencing errors and assembly of EST paralogous sequences can lead to the identification of false positive SNPs which renders the reliability of EST-derived SNPs relatively low. Further validation of EST-derived SNPs is therefore required. The objective of this work was to assess the quality of and to validate a large number of rainbow trout EST-derived SNPs. RESULTS: A panel of 1,152 EST-derived SNPs was selected from the INRA Sigenae SNP database and was genotyped in standard and double haploid individuals from several populations using the Illumina GoldenGate BeadXpress assay. High-quality genotyping data were obtained for 958 SNPs representing a genotyping success rate of 83.2 %, out of which, 350 SNPs (36.5 %) were polymorphic in at least one population and were designated as true SNPs. They also proved to be a potential tool to investigate genetic diversity of the species, as the set of SNP successfully sorted individuals into three main groups using STRUCTURE software. Functional annotations revealed 28 non-synonymous SNPs, out of which four substitutions were predicted to affect protein functions. A subset of 223 true SNPs were polymorphic in the two INRA mapping reference families and were integrated into the INRA microsatellite-based linkage map. CONCLUSIONS: Our results represent the first study of EST-derived SNPs validation in rainbow trout, a species whose genome sequences is not yet available. We designed several specific filters in order to improve the genotyping yield. Nevertheless, our selection criteria should be further improved in order to reduce the observed high rate of false positive SNPs which results from the occurrence of whole genome duplications.