Characterization of an extensive rainbow trout miRNA transcriptome by next generation sequencing

Abstract

Background: MicroRNAs (miRNAs) have emerged as important post-transcriptional regulators of gene expression in a wide variety of physiological processes. They can control both temporal and spatial gene expression and are believed to regulate 30 to 70% of the genes. Data are however limited for fish species, with only 9 out of the 30,000 fish species present in miRBase. The aim of the current study was to discover and characterize rainbow trout (Oncorhynchus mykiss) miRNAs in a large number of tissues using next-generation sequencing in order to provide an extensive repertoire of rainbow trout miRNAs.

Results: A total of 38 different samples corresponding to 16 different tissues or organs were individually sequenced and analyzed independently in order to identify a large number of miRNAs with high confidence. This led to the identification of 2946 miRNA loci in the rainbow trout genome, including 445 already known miRNAs. Differential expression analysis was performed in order to identify miRNAs exhibiting specific or preferential expression among the 16 analyzed tissues. In most cases, miRNAs exhibit a specific pattern of expression in only a few tissues. The expression data from sRNA sequencing were confirmed by RT-qPCR. In addition, novel miRNAs are described in rainbow trout that had not been previously reported in other species.

Conclusion: This study represents the first characterization of rainbow trout miRNA transcriptome from a wide variety of tissue and sets an extensive repertoire of rainbow trout miRNAs. It provides a starting point for future studies aimed at understanding the roles of miRNAs in major physiological process such as growth, reproduction or adaptation to stress. These rainbow trout miRNAs repertoire provide a novel resource to advance genomic research in salmonid species.

Fig. 1

Identification and annotation pipeline of rainbow trout miRNAs using sRNA-sequencing. Fastq files were first cleaned from low quality and adapter sequence. The redundancy was removed from the 38 sample files for the annotation process (Panel 1). Unique sequences were then blasted against rRNA, tRNA and RNA database to remove already known RNA sequences that are not miRNA (Panel 2). A Blast against miRBase database predicts the already identified miRNAs in other species (Panel 2). In parallel, reads were mapped onto the rainbow trout genome to eliminate any contaminant sequences and characterize the miRNA loci. Novel pre-miRNA were also characterized with the specific miRNAs features (Panel 3)

Fig. 2

miRNA prediction and genomic localization. The graph represents the distribution of the prediction score for the 3126 miRNAs predicted loci. A clear drop in score numbers is observed around 800. miRNAs annotated loci are in red and unannotated predicted miRNAs loci are in black

Fig. 3

sRNA-seq reads length repartition. a The graph represents the read length repartition in a muscle sample (that is representative of all samples except gonadal tissue). b The graph represents the read length repartition in the egg sample. c The graph represents the read length repartition in the testis stage I sample. All the profiles are represented in Additional file 3

Fig. 4

Pie charts of miRNA abundance. Distribution of the miRNA abundance by miRNA family. The top 8 miRNA families are represented (relative expression over 1 %) and represents 70 % of the expressed miRNAs. All the others (miRNA representing individually less than 1 % of the global abundance) represents 30 % of the overall expressed miRNA

Fig. 5

miRNA expression in the 16 tissues. Unsupervised average linkage clustering analysis of miRNA isoforms in rainbow trout tissue. Each row represents a miRNA isoform (total of 1946 rows) and each column a tissue RNA sample. Data were median-centered prior to the clustering analysis. For each miRNA, the expression level within samples is indicated using a color density scale

Fig. 6

miRNA expression correlation between sRNA-seq and RT-qPCR. Pearson correlations between sRNA-seq and RT-qPCR data were calculated for 9 miRNAs that show diverse expression profiles (tissue enriched, tissue dominant or ubiquitous miRNAs). RNA-seq data are on the y-axis and qPCR are on the x-axis

Fig. 7

novel miRNAs in rainbow trout: prediction and tissue distribution. a The illustration shows sequence and structure statistics of one predicted miRNA precursor as an example. b The graph shows, as an example, the 54 nt sequence (putative miRNA precursor) along with reads that aligned to this sequence. The secondary structure of the precursor is shown with the orange parenthesis. c Unsupervised average linkage clustering analysis of new miRNA in rainbow trout tissue. Each row represents a new miRNA locus (total of 94 rows) and each column a tissue RNA sample. Data were median-centered prior to the clustering analysis. For each miRNA, the expression level within sample set is indicated using a color density scale

Fig. 8

miRNAs conservation among fish species. Conservation analysis of the rainbow trout miRNAs repertoire among 8 fish species: Atlantic salmon, Atlantic cod, zebrafish, medaka, sea bass, stickleback, tetraodon and fugu (a) Pie chart representing the percentage of rainbow trout miRNAs that are found among the 8 fish genomes (b) Stack histograms representing the conservation of rainbow trout miRNAs in each fish species