Date Published: February 25, 2019
Publisher: Public Library of Science
Author(s): Fátima Gomes, Luciana Watanabe, João Vianez, Márcio Nunes, Jedson Cardoso, Clayton Lima, Horacio Schneider, Iracilda Sampaio, Marc Robinson-Rechavi.
The C. macropomum is a characiform fish from the Amazon basin that has been hybridized with other pacu species to produce commercial hybrids, such as the tambacu. However, little is known of the functional genomics of the parental species or these hybrid forms. The transcriptome of C. macropomum and tambacu were sequenced using 454 Roche platform (pyrosequencing) techniques to characterize the domains of Gene Ontology (GO) and to evaluate the levels of gene expression in the two organisms.
The 8,188,945 reads were assembled into 400,845 contigs. A total of 58,322 contigs were annotated with a predominance of biological processes for both organisms, as determined by Gene Ontology (GO). Similar numbers of metabolic pathways were identified in both the C. macropomum and the tambacu, with the metabolism category presenting the largest number of transcripts. The BUSCO analysis indicated that our assembly was more than 40% complete. We identified 21,986 genes for the two fishes. The P and Log2FC values indicated significant differences in the levels of gene expression, with a total of 600 up-regulated genes.
In spite of the lack of a reference genome, the functional annotation was successful, and confirmed a considerable difference in the specificity and levels of gene expression between the two organisms. This report provides a comprehensive baseline for the genetic management of these commercially important fishes, in particular for the identification of specific genes that may represent markers involved in the immunity, growth, and fertility of these organisms, with potential practical applications in aquaculture management.
Next Generation Sequencing (NGS) technologies have provided a range of potential markers for both model and non-model species through the discovery of new genes from an enormous database [1–3]. Over the past few years, NGS has been used increasingly to characterize the transcripts of a number of different species and tissues, in addition to contributing to the evaluation of gene expression in commercial lineages. Fish are especially important, given that they comprise a highly diversified group, with many economically important species, but little information on their functional genomics. The FLX (GS FLX) Genome sequencing system, which uses the 454 sequencing approach, is one of the most widely-used and successful approaches to the evaluation of the fish transcriptome [4–6].
This is the first comparative analysis of the C. macropomum and its hybrid form, the tambacu. The results indicated that the NGS platform used in the study is a powerful tool for the identification of genes and molecular markers in non-model species, in addition to confirming that the combination of distinct assembly methods can enrich the dataset considerably. Despite of the lack of a reference genome, we obtained a satisfactory number of transcripts with functional annotation, associated typically with biological processes, with the skin presenting the greatest number of GO terms. The KEGG analysis also identified similarities in the metabolic pathways of the two organisms, with several transcripts in the metabolism category. There was a degree divergence in the number of exclusive genes, and the levels of gene expression and function between the C. macropomum and tambacu tissues. However, a significant number of genes remained uncharacterized, and are also of particular interest for future studies on the physiology, conservation, and genetic improvement of the native species, as well as the management of hybrid stocks. This research is thus an important contribution to the investigation of genes that contribute to potential advantages or disadvantages in the productivity of the hybrids, their implications for the conservation and management of C. macropomum, and provide a valuable tool for future research in functional genomics.