Technical Abstract: Background Genetic maps characterizing the inheritance patterns of traits and markers have been developed for a wide range of species and used to study questions in biomedicine, agriculture, ecology and evolutionary biology. The status of rainbow trout genetic maps has progressed significantly over the last decade due to interest in these species in aquaculture and sport fisheries, and as a model research organism for studies related to carcinogenesis, toxicology, comparative immunology, disease ecology, physiology and nutrition. We constructed a second generation genetic map for rainbow trout using microsatellite markers. The map will facilitate the identification of quantitative trait loci for traits affecting aquaculture production efficiency and the extraction of comparative information from the genome sequences of model fish species. Results A genetic map ordering 1124 microsatellite loci spanning a sex-averaged distance of 2927.10 cM (Kosambi) and having 2.6 cM resolution was constructed by genotyping 10 parents and 150 offspring from the NCCCWA reference family mapping panel. Microsatellite markers, representing pairs of loci resulting from an evolutionarily recent whole genome duplication event, identified 180 homeologous chromosomal regions within the rainbow trout genome. Microsatellites associated with genes through expressed sequence tags or bacterial artificial chromosomes produced comparative assignments with tetraodon, zebrafish, fugu, and medaka resulting in assignments of homology for 199 loci. Conclusions The second generation NCCCWA genetic map provides an increased microsatellite marker density and quantifies differences in recombination rate between the sexes in outbred populations. It has the potential to integrate with cytogenetic and other physical maps, identifying paralogous regions of the rainbow trout genome arising from the evolutionarily recent genome duplication event, and anchoring a comparative map with the zebrafish, medaka, tetraodon, and fugu genomes. This resource will facilitate the identification of genes affecting traits of interest through fine mapping and positional candidate cloning.