Detection of growth-related QTL in turbot (Scophthalmus maximus)

• Published in: BMC Genomics
• Main Authors: Sánchez-Molano, Enrique, Cerna, Alex, Toro, Miguel A, Bouza, Carmen, Hermida, Miguel, Pardo, Belén G, Cabaleiro, Santiago, Fernández, Jesús, Martínez, Paulino
• Format: Article in Journal/Newspaper
• Language: English
• Published: Springer Science and Business Media LLC 2011
• Subjects: Genetics; Biotechnology; Scophthalmus maximus; Turbot
• Online Access: http://dx.doi.org/10.1186/1471-2164-12-473; http://link.springer.com/content/pdf/10.1186/1471-2164-12-473.pdf; http://link.springer.com/article/10.1186/1471-2164-12-473/fulltext.html; https://link.springer.com/content/pdf/10.1186/1471-2164-12-473.pdf

Abstract Background The turbot ( Scophthalmus maximus ) is a highly appreciated European aquaculture species. Growth related traits constitute the main goal of the ongoing genetic breeding programs of this species. The recent construction of a consensus linkage map in this species has allowed the selection of a panel of 100 homogeneously distributed markers covering the 26 linkage groups (LG) suitable for QTL search. In this study we addressed the detection of QTL with effect on body weight, length and Fulton's condition factor. Results Eight families from two genetic breeding programs comprising 814 individuals were used to search for growth related QTL using the panel of microsatellites available for QTL screening. Two different approaches, maximum likelihood and regression interval mapping, were used in order to search for QTL. Up to eleven significant QTL were detected with both methods in at least one family: four for weight on LGs 5, 14, 15 and 16; five for length on LGs 5, 6, 12, 14 and 15; and two for Fulton's condition factor on LGs 3 and 16. In these LGs an association analysis was performed to ascertain the microsatellite marker with the highest apparent effect on the trait, in order to test the possibility of using them for marker assisted selection. Conclusions The use of regression interval mapping and maximum likelihood methods for QTL detection provided consistent results in many cases, although the high variation observed for traits mean among families made it difficult to evaluate QTL effects. Finer mapping of detected QTL, looking for tightly linked markers to the causative mutation, and comparative genomics are suggested to deepen in the analysis of QTL in turbot so they can be applied in marker assisted selection programs.