Uncovering QTL for resistance and survival time to Philasterides dicentrarchi in turbot (Scophthalmus maximus)

• Published in: Animal Genetics
• Main Authors: Rodríguez-Ramilo, S. T., Fernández, J., Toro, M. A., Bouza, C., Hermida, M., Fernández, C., Pardo, B. G., Cabaleiro, S., Martínez, P.
• Format: Article in Journal/Newspaper
• Language: English
• Published: Wiley 2013
• Subjects: Linear regression method; Maximum likelihood method; Quantitative trait loci; Scuticociliatosis; Turbot; Scophthalmus maximus
• Online Access: https://hdl.handle.net/20.500.12792/3848; http://hdl.handle.net/10261/293214; https://doi.org/10.1111/j.1365-2052.2012.02385.x

Disease resistance-related traits have received increasing importance in aquaculture breeding programs worldwide. Currently, genomic information offers new possibilities in breeding to address the improvement of this kind of traits. The turbot is one of the most promising European aquaculture species, and Philasterides dicentrarchi is a scuticociliate parasite causing fatal disease in farmed turbot. An appealing approach to fight against disease is to achieve a more robust broodstock, which could prevent or diminish the devastating effects of scuticociliatosis on farmed individuals. In the present study, a genome scan for quantitative trait loci (QTL) affecting resistance and survival time to P. dicentrarchi in four turbot families was carried out. The objectives were to identify QTL using different statistical approaches [linear regression (LR) and maximum likelihood (ML)] and to locate significantly associated markers for their application in genetic breeding strategies. Several genomic regions controlling resistance and survival time to P. dicentrarchi were detected. When analyzing each family separately, significant QTL for resistance were identified by the LR method in two linkage groups (LG1 and LG9) and for survival time in LG1, while the ML methodology identified QTL for resistance in LG9 and LG23 and for survival time in LG6 and LG23. The analysis of the total data set identified an additional significant QTL for resistance and survival time in LG3 with the LR method. Significant association between disease resistance-related traits and genotypes was detected for several markers, a single one explaining up to 22% of the phenotypic variance. Obtained results will be essential to identify candidate genes for resistance and to apply them in marker-assisted selection programs to improve turbot production. © 2012 The Authors.