Abstract
Senegalese sole is an economically important flatfish species in aquaculture. Development of new bioinformatics resources allows the optimization of its breeding in fisheries. Sequencing data from larvae in different development stages obtained from different sequencing platforms (more than 270 M of Illumina paired-end reads and more than 3 M of Roche/454 reads) were used. Due to the high complexity of the samples, an optimized version of TransFlow, an automated, reproducible and flexible framework for de novo transcriptome assembly, was used to get the most complete de novo transcriptome assembly. Best transcriptome selection was based on the principal component analysis provided by TransFlow. Two transcriptomes, one all-Illumina and other reconciling Illumina and Roche/454, were selected and annotated using Full-LengtherNext, and the tentative transcripts were filtered by alignment to partial genomic sequences to avoid artifacts. The reconciled non-redundant assembly composed by Illumina and Roche/454 reads seems to be the best strategy. It consists of 55 440 transcripts of which 22 683 code for 17 570 different proteins described in databases. The obtained v5.0 reduces the number of tentative transcripts by 79,33% compared v4.0, what will increase the precision of future transcriptomic studies.
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Acknowledgments
This work was supported by co-funding through the European Regional Development Fund (ERDF) 2014–2020 “Programa operativo de crecimiento inteligente” together with Spanish AEI “Agencia Estatal de Investigación” (AGL2017-83370-C3-3-R) and INIA “Instituto Nacional de Investigaciones Agrarias” (RTA2013-00068-C03 and RTA2017-00054-C03-03). The authors also thankfully acknowledge the computer resources and the technical support provided by the Plataforma Andaluza de Bioinformatica of the University of Malaga.
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Córdoba-Caballero, J., Seoane-Zonjic, P., Manchado, M., Gonzalo Claros, M. (2019). De novo Transcriptome Assembly of Solea senegalensis v5.0 Using TransFlow. In: Rojas, I., Valenzuela, O., Rojas, F., Ortuño, F. (eds) Bioinformatics and Biomedical Engineering. IWBBIO 2019. Lecture Notes in Computer Science(), vol 11465. Springer, Cham. https://doi.org/10.1007/978-3-030-17938-0_5
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