QTL detection for Aeromonas salmonicida resistance related traits in turbot (Scophthalmus maximus)

• Published in: BMC Genomics
• Main Authors: Rodríguez Ramilo, Silvia Teresa, Toro Ibáñez, Miguel Ángel, Bouza Fernández, María Carmen, Hermida Prieto, Miguel, Gómez Pardo, María Belén, Cabaleiro, Santiago, Martínez Portela, Paulino, Fernández Martín, Jesús
• Other Authors: Universidade de Santiago de Compostela. Departamento de Zooloxía, Xenética e Antropoloxía Física
• Format: Article in Journal/Newspaper
• Language: English
• Published: BMC
• Subjects: Quantitative Trait Locus; Atlantic Salmon; Differentially Express; Differentially Express Gene; Quantitative Trait Locus Detection; Atlantic salmon; Scophthalmus maximus; Turbot
• Online Access: http://hdl.handle.net/10347/22119; https://doi.org/10.1186/1471-2164-12-541

Background Interactions between fish and pathogens, that may be harmless under natural conditions, often result in serious diseases in aquaculture systems. This is especially important due to the fact that the strains used in aquaculture are derived from wild strains that may not have had enough time to adapt to new disease pressures. The turbot is one of the most promising European aquaculture species. Furunculosis, caused by the bacterium Aeromonas salmonicida, produces important losses to turbot industry. An appealing solution is to achieve more robust broodstock, which can prevent or diminish the devastating effects of epizooties. Genomics strategies have been developed in turbot to look for candidate genes for resistance to furunculosis and a genetic map with appropriate density to screen for genomic associations has been also constructed. In the present study, a genome scan for QTL affecting resistance and survival to A. salmonicida in four turbot families was carried out. The objectives were to identify consistent QTL using different statistical approaches (linear regression and maximum likelihood) and to locate the tightest associated markers for their application in genetic breeding strategies. Results Significant QTL for resistance were identified by the linear regression method in three linkage groups (LGs 4, 6 and 9) and for survival in two LGs (6 and 9). The maximum likelihood methodology identified QTL in three LGs (5, 6 and 9) for both traits. Significant association between disease traits and genotypes was detected for several markers, some of them explaining up to 17% of the phenotypic variance. We also identified candidate genes located in the detected QTL using data from previously mapped markers. Conclusions Several regions controlling resistance to A. salmonicida in turbot have been detected. The observed concordance between different statistical methods at particular linkage groups gives consistency to our results. The detected associated markers could be useful for genetic breeding ...