Analysis of the black‐chinned tilapia Sarotherodon melanotheron heudelotii reproducing under a wide range of salinities: from RNA‐seq to candidate genes

Abstract

The black-chinned tilapia Sarotherodon melanotheron heudelotii is an ecologically appealing model as it shows exceptional adaptive capacities, especially with regard to salinity. In spite of this, this species is devoid of genomic resources, which impedes the understanding of such remarkable features. De novo assembly of transcript sequences produced by next-generation sequencing technologies offers a rapid approach to obtain expressed gene sequences for non-model organisms. It also facilitates the development of quantitative real-time PCR (qPCR) assays for analysing gene expression under different environmental conditions. Nevertheless, obtaining accurate and reliable qPCR results from such data requires a number of validations prior to interpretation. The transcriptome of S. melanotheron was sequenced to discover transcripts potentially involved in the plasticity of male reproduction in response to salinity variations. A set of 54 candidate and reference genes was selected through a digital gene expression (DGE) approach, and a de novo qPCR assay using these genes was validated for further detailed expression analyses. A user-friendly web interface was created for easy handling of the sequence data. This sequence collection represents a major transcriptomic resource for S. melanotheron and will provide a useful tool for functional genomics and genetics studies.

Comparative Transcriptome Analysis of Two Oysters, Crassostrea gigas and Crassostrea hongkongensis Provides Insights into Adaptation to Hypo-Osmotic Conditions

“…Transcriptome or genome sequencing have been conducted for various marine bivalves, such as clam [19], mussels [2], [20], and oysters [15], [21]. In addition to candidate gene discovery from massive sequencing data, many studies have demonstrated that this is an efficient way to discover genetic variations [22]–[24], perform transcriptome profiling [25]–[27], and identify adaptive genes [28], [29] to provide important insights into the process of adaptive evolution.…”

Significant association of SNP polymorphism in the tilapiaenhancer of polycomb homolog 1gene with salt tolerance

“…In tilapia, some osmoregulation associated genes have been identified, such as transferrin gene, β ‐Hemoglobin , Ca2+transporting plasma membrane ATPase , pro‐opiomelanocortin, beta‐actin (Rengmark & Lingaas, ), prolactin (Streelman & Kocher, ). The transcriptome profiles under different salinity challenges detected many osmoregulation related genes (Avarre et al., ; Xu et al., ). These data suggest that the osmoregulation in fish is under control by many genes and is very complicated.…”

Fitness difference between cryptic salinity-related phenotypes of sea bass (<em>Dicentrarchus labrax</em>)

“…The genomic resources now available for sea bass Magnanou et al 2014) and dedicated molecular techniques such as microarrays (Ferraresso et al 2010) and RNA sequencing (Wang et al 2009) may help to achieve this goal at scales far above the levels of expression of a few genes (e.g. Norman et al 2011, Avarre et al 2014). This should especially motivate future studies (i) in cultured fish for which selective breeding programmes have been initiated (Chatain and Chavanne 2009) and which may need to control for cryptic phenotypes, and (ii) in wild juvenile sea bass distributed naturally over a large range of salinity conditions, but also trophic or temperature conditions that also greatly vary between habitats, to investigate molecular mechanisms involved in the lagoon/estuarine life compared with the coastal/pelagic life in this species.…”

“…Tine et al 2008). In order to retain a reference gene, we adopted a criterion developed in Avarre et al (2014). Briefly, we randomly sampled a set of 15 fish (five fish per condition: SSW, SFW and UFW) and measured their cycle of quantification value (Cq, i.e.…”

“…stability of gene expression) of their Cq values by measuring the standard deviations of Cq (SD Cq ) over the 15 individuals (EF1a: SD Cq =0.337; b-actin: SD Cq =0.646). Avarre et al (2014) set up a criterion of SD Cq <0.5 to qualify genes as 'good' reference genes. We did not use other reference genes in this study as there is no rationale to increase the number reference genes when investigating for gene expression variation at only two target genes.…”