Integrative Transcriptome, Genome and Quantitative Trait Loci Resources Identify Single Nucleotide Polymorphisms in Candidate Genes for Growth Traits in Turbot
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Abstract
Growth traits represent a main goal in aquaculture breeding programs and may be related to adaptive variation in wild fisheries. Integrating quantitative trait loci (QTL) mapping and next generation sequencing can greatly help to identify variation in candidate genes, which can result in marker-assisted selection and better genetic structure information. Turbot is a commercially important flatfish in Europe and China, with available genomic information on QTLs and genome mapping. Muscle and liver RNA-seq from 18 individuals was carried out to obtain gene sequences and markers functionally related to growth, resulting in a total of 20,447 genes and 85,344 single nucleotide polymorphisms (SNPs). Many growth-related genes and SNPs were identified and placed in the turbot genome and genetic map to explore their co-localization with growth-QTL markers. Forty-five SNPs on growth-related genes were selected based on QTL co-localization and relevant function for growth traits. Forty-three SNPs were technically feasible and validated in a wild Atlantic population, where 91% were polymorphic. The integration of functional and structural genomic resources in turbot provides a practical approach for QTL mining in this species. Validated SNPs represent a useful set of growth-related gene markers for future association, functional and population studies in this flatfish species
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Robledo, D.; Fernández, C.; Hermida, M.; Sciara, A.; Álvarez-Dios, J.A.; Cabaleiro, S.; Caamaño, R.; Martínez, P.; Bouza, C. Integrative Transcriptome, Genome and Quantitative Trait Loci Resources Identify Single Nucleotide Polymorphisms in Candidate Genes for Growth Traits in Turbot. Int. J. Mol. Sci. 2016, 17, 243
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https://doi.org/10.3390/ijms17020243Sponsors
This work was funded by Spanish Ministry of Economy and Competitiveness and European Regional Development Funds (AGL2012-35904), and Ministry of Science and Innovation (Consolider Ingenio, Aquagenomics, CSD200700002). DR was supported by a FPU fellowship funded by Spanish Ministry of Education, Culture and Sport. Thanks to Lucía Ínsua for technical assistance. We thank the High-Throughput Genomics Group at the Wellcome Trust Centre for Human Genetics for the generation of the sequencing data, and the Spanish National Genotyping Center (CEGEN-ISCIII)-USC node for SNP genotyping support. We acknowledge the support of the Centro de Supercomputación de Galicia (CESGA) in the completion of this work
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© 2016 by the authors; licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons by Attribution (CC-BY) license (http://creativecommons.org/licenses/by/4.0/)