- Research article
- Open Access
RNAseq analysis of fast skeletal muscle in restriction-fed transgenic coho salmon (Oncorhynchus kisutch): an experimental model uncoupling the growth hormone and nutritional signals regulating growth
© de la serrana et al. 2015
- Received: 31 March 2015
- Accepted: 15 July 2015
- Published: 31 July 2015
Coho salmon (Oncorhynchus kisutch) transgenic for growth hormone (Gh) express Gh in multiple tissues which results in increased appetite and continuous high growth with satiation feeding. Restricting Gh-transgenics to the same lower ration (TR) as wild-type fish (WT) results in similar growth, but with the recruitment of fewer, larger diameter, muscle skeletal fibres to reach a given body size. In order to better understand the genetic mechanisms behind these different patterns of muscle growth and to investigate how the decoupling of Gh and nutritional signals affects gene regulation we used RNA-seq to compare the fast skeletal muscle transcriptome in TR and WT coho salmon.
Illumina sequencing of individually barcoded libraries from 6 WT and 6 TR coho salmon yielded 704,550,985 paired end reads which were used to construct 323,115 contigs containing 19,093 unique genes of which >10,000 contained >90 % of the coding sequence. Transcripts coding for 31 genes required for myoblast fusion were identified with 22 significantly downregulated in TR relative to WT fish, including 10 (vaspa, cdh15, graf1, crk, crkl, dock1, trio, plekho1a, cdc42a and dock5) associated with signaling through the cell surface protein cadherin. Nineteen out of 44 (43 %) translation initiation factors and 14 of 47 (30 %) protein chaperones were upregulated in TR relative to WT fish.
TR coho salmon showed increased growth hormone transcripts and gene expression associated with protein synthesis and folding than WT fish even though net rates of protein accretion were similar. The uncoupling of Gh and amino acid signals likely results in additional costs of transcription associated with protein turnover in TR fish. The predicted reduction in the ionic costs of homeostasis in TR fish associated with increased fibre size were shown to involve multiple pathways regulating myotube fusion, particularly cadherin signaling.
- Muscle growth
- teleost fish
- Growth hormone transgenics
- Skeletal muscle transcriptome
- Fish nutrition
The growth hormone (Gh) axis in coho salmon (Oncorhynchus kisutch) and other teleosts is normally tightly coupled to energy intake and is modulated by a large number of environmental factors . The normal feedback control systems are essentially disabled in growth hormone-transgenics due to the extra-pituitary expression of Gh in other tissues [2, 3]. High constitutive expression of Gh results in increased aggressiveness, appetite and foraging activity [4, 5] leading to continuous fast growth when fish are fed to satiation . Gh stimulates insulin-like growth factor-1 (Igf1) secretion in the liver. Circulating Igfs bind to Igf receptors and activate the signalling cascades that regulate protein synthesis. Plasma Igf1 and amino acids from the diet further stimulate Igf synthesis in muscle and other tissues via paracrine action [7, 8]. Gh-transgenics exhibit increased plasma insulin-like growth factor-1 (Igf1; ~25 ng/ml), tissue igf1 mRNA and Gh-receptor (ghr) levels relative to wild-type fish (circulating Igf1 was ~8 ng/ml in WT) . Feeding coho salmon Gh-transgenics below appetite (restriction-fed transgenics, TR) with a similar ration size as wild-type fish (WT) results in an uncoupling of the growth hormone and nutritional signals regulating growth. TR fish grow more slowly and show lower circulating Igf1 than Gh-transgenic fish fed to satiation (TF) (10 ng/ml in TR compared with 25 ng/ml to TF animals), which indicates the nutritional regulation of igf1 expression remains functional at the target tissue level . TR animals showed higher circulating Gh (8 ng/ml) levels and unchanged ghr mRNA relative to Gh-transgenics fed to satiation (TF) (4 ng/ml circulating Gh), but retained higher feeding motivation and foraging activity than WT .
Fast skeletal muscle fibres are formed in teleost fish immediately following somite formation and then in the juvenile/adult stages by processes of stratified and mosaic hyperplasia (MH) [9, 10]. Myoblast-myoblast fusion results in the formation of a nascent myotube which elongates and gains additional nuclei through myoblast-myotube fusion. Activation of terminal differentiation and sarcomere formation then results in the production of an immature muscle fibre. Typically, myotube production in fast muscle continues until the fish reaches around 40-50 % of their maximum attainable adult body length .
Hill et al.  provided indirect evidence that Gh-transgenic coho salmon fed to satiation showed enhanced muscle growth by hyperplasia. In a recent study we tested this hypothesis by measuring the number and size distribution of fast myotomal muscle fibres in three groups of coho salmon of similar body length: 1-year old Gh-transgenics fed to satiation (TF), 2-year old restriction-fed Gh-transgenics (TR) and wild type (WT) . TF coho salmon recruited fast muscle fibres at twice the rate as WT fish, but showed a similar contribution of hyperplasia and hypertrophy to reach a given body length i.e. the hypothesis of an increased importance of hyperplasia in transgenics was not supported. Unexpectedly, TR recruited 49 % fewer fibres with a 20 % higher fibre diameter than either WT or TF fish and had larger diameter fibres across the whole range of fibre sizes, i.e. increased hypertrophy was evident for all cohorts of fibres produced during ontogeny . There is direct experimental evidence from inhibitor and Nuclear Magnetic Resonance (NMR) studies that larger diameter muscle fibres have lower costs of ionic homeostasis than smaller ones due to their lower surface to volume (S/V) ratio [14, 15]. Thus the ~40 % reduction in fibre S/V ratio in TR relative to WT fish would be expected to produce proportional savings in routine maintenance costs . Previously we suggested that adjustments in fibre size might permit the reallocation of energy from maintenance to locomotion which would help explain why calorie-restricted transgenics grow at the same rate as WT fish whilst exhibiting markedly higher activity levels .
Preliminary, studies indicated that several genes associated with myotube formation were downregulated in TR relative to WT fish . In order to gain a broader understanding of fast skeletal muscle gene regulation in TR compare to WT fish we have now carried out RNA-seq in 6 TR and 6 WT individual coho salmon for which we had associated data on the number and size of fast muscle fibres , and validated the results by qPCR analysis. RNA was sequenced using Illumina HiSeq2000 and mapped reads (DESEQ normalized counts) were used to study global differences in digital gene expression (DGE) between groups. Following enriched Gene Ontology (GO) analysis we tested specific hypotheses about the effects of uncoupling growth hormone and nutrient signals by analysing the expression of genes related to growth hormone signalling, protein translation, protein-folding and myoblast fusion.
Sequencing and de novo Trinity assembly metrics
Average length (bp)
KAAS annotated maps
Estimation of paralogues content in the coho salmon transcriptome
S. salar paralogue
Coho salmon contig
Annotated contigs were blasted against the KEGG database using the online web-server KAAS to map them against the main metabolic and signaling pathways, yielding a total of 309 KEGG maps where coho salmon contigs were present (Table 1; Hierarchical file with all the details of the KEGG mapped contigs can be found in Additional file 1). Comparative analysis between annotated contigs against the annotated zebrafish proteome (Danio rerio) allowed us to identify 10,030 genes estimated to contain over 90 % of the predicted coding sequence (CDS) (Additional file 2). We also found that 1000 contigs were over >100 % of the CDS, indicating that some coho salmon genes were between 1-20 % longer than their zebrafish orthologues (Additional file 2).
Digital Gene Expression (DGE)
Paired-end reads from individual fish libraries were mapped against the de novo transcriptome (Additional file 3). Mapped reads were normalized by contig length and library depth following a negative binomial using DESEQ and used for DGE analysis. Global DGE comparison between TR and WT yielded an initial list of 384 contigs that were differentially expressed (FDR < 0.05). Contigs with <15 normalized reads mapped and a fold-change <2log2 were discarded. Redundant contigs for all genes from the initial global DGE list were identified in the annotated transcriptome and their DESEQ-counts values were individually investigated. Those genes for which all-redundant “sister” contigs were found to show consistent, but not necessarily significant, changes in expression between groups were retained (see Methods). Care was taken to identify 4R and 3R-paralogues that might be annotated with the same ID by exploring the alignment of the sister contigs. After curation for redundancy and quality control, a total of 186 genes from TR and 199 from WT were considered to be differentially expressed (Additional file 4).
RNAseq has many advantages, but it does present challenges with respect to statistical analysis and interpretation. Firstly, transcription is not tightly coupled to translation in eukaryotes, complicating inferences about the functional significance of changes in transcript abundance. Secondly, the activity of signalling pathways is often dependent on posttranslational modifications such as phosphorylation and/or changes in compartmentalisation within the cell. In addition, functional interpretations based on transcript abundance cannot distinguish between mRNA transcription vs degradation rates. It is also easy to fall into the trap of providing a series of post hoc stories when reporting transcriptomic data rather than testing a priori hypotheses. Standard corrections for multiple testing coupled with long gene lists also leads to a very high barrier for establishing statistical significance, leading to type-2 statistical errors.
Gene ontology analysis
Number of genes
Ribonucleoprotein complex biogenesis
Regulation of translational initiation
Cellular macromolecule metabolic process
Cellular nitrogen compounds metabolic process
Primary metabolic process
Nucleic acid binding
Organic cyclic compound binding
Cellular protein modification process
Cellular response to nutrient levels
Protein modification by small protein conjugation
Growth hormone system and protein synthesis
Morpholino antisense-oligonucleotide-mediated knockdown studies have shown that both dock1 and dock5 and their adaptor proteins crk, crk-like (crkl) and the pleckstrin homology domain containing family member 1a (plekho1a or ckip1) are required for the fusion of fast-type myoblasts in zebrafish . Members of the Rho family of guanosine triphosphatases (GTPases), including Rac1, operate downstream of Dock1 to stimulate myoblast fusion . Rac1 is also activated by M-cadherin-dependent adhesion through Trio during C2C12 myoblast fusion . M-cadherin (also known as cadherin15) and trio transcripts were also both significantly downregulated in TR relative to WT salmon (Fig. 7; Additional file 9). On the basis of differences in the defects observed in dock1 −/− and trio −/− mice it has been suggested that Trio is required for myoblast-myoblast fusion, but not for myoblast-myotube fusion . A further three of the genes downregulated in TR fish were associated with integrins and focal adhesion kinase signaling (Fig. 7; Additional file 9). Also down regulated in TR relative to WT fish were sp1, a component of Mapk-Erk5 signaling pathway, nfkb1 which is involved in the non-canonical NF-kB signaling and tmem8c or myomaker which is required for myoblast-myotube fusion (Fig. 7; Additional file 9) . Nine (aox1, gsk-3ß, cpn3, arf6, arpc4, shp2, cfl2, mrf4 and nfatc2) out of the 99 genes on the list were significantly upregulated in TR relative to WT fish (FDR <0.05) (Fig. 7; Additional file 9). Integrin signaling is mediated by the non-receptor protein kinase Fak promoting myoblast fusion and an associated increase in Caveolin-3 , transcripts of which were downregulated in TR relative to WT fish (Fig. 7; Additional file 9). The differences in DGE observed are consistent with a higher myoblast fusion activity in WT when compared with TR, consistent with the observed differences in fibre number .
Quantitative PCR data validation of DGE
Energy budgeting in the restriction-fed transgenic model
TR fish are more aggressive and exhibit markedly higher levels routine swimming behaviour than WT fish and may have higher metabolic costs associated with the futile expression of mRNAs and proteins required for growth (present study). In spite of these additional costs, TR fish grow at the same rate as WT fish which implies some compensating alterations to energy budgeting. The source of these energy savings includes the cost of ionic homeostasis which has been estimate to contribute 20-40 % of the routine metabolic rate in teleosts , a large part of which can be attributable to maintaining the resting membrane potential of fast skeletal muscle which comprises around 70 % of body mass in salmonids. TR fish have fewer, but larger diameter fast muscle fibres than WT for a given body length , which will result in reduced ion pumping costs [14, 15]. Our working hypothesis is that the uncoupling of the Gh-axis from energy status directly affects one or more of the signaling pathways regulating myotube formation and hypertrophic growth, and several candidate pathways, particularly signaling through cadherin, have been identified in the present study. Calorie restriction in WT fish may not result in changes in muscle cellularity because the metabolic signals normally influencing endogenous Gh regulation remain intact, a hypothesis requiring further assessment.
Experiments on coho salmon (Oncorhynchus kisutch) were conducted in a non-commercial containment facility for transgenic fish at Fisheries and Oceans Canada, West Vancouver. Wild-type (WT) fish were from the 2010 brood of Chehalis River strain (British Columbia, Canada) . The strain of transgenic coho salmon used (M77) was derived from Chehalis River strain produced using the OnMTGH1 construct comprised of 320 bp of sockeye salmon metallothionein-ß promoter fused to the 5′-UTR region of the full-length type-I growth hormone (gh1) gene and the terminator from the same species, as previously described . Fish were reared under standard hatchery conditions in fresh well water (10 ± 1 °C) with a natural photoperiod and fed commercially available salmon diets (Skretting, Vancouver, Canada). The 2010 brood of Gh transgenics (TR group) were fed the same ration to that of the WT group (i.e. pair fed), resulting in similar growth rates in the two groups. Fish were fasted for 24 h prior to humane sacrifice and selected to produce two groups with a similar average fork length (cm) and hence same the developmental stage. All procedures used in the study were approved by the Department of Fisheries and Oceans Pacific Region Animal Care Committee. WT and food-restricted growth hormone transgenic coho salmon (TR) were obtained from the same group used by the authors in a previous study . No significant differences were found in weight or fork length between TR (63.5 ± 3.1 g; 17.4 ± 0.2 cm) and WT (57.7 ± 2 g; 17.1 ± 0.1 cm) used in the present study.
RNA extraction and sequencing
Sections of pure fast skeletal muscle were carefully dissected from dorsal epaxial myotomes of 6 animals from WT and TR groups matched for body length and with known differences in muscle fibre distribution . Total RNA was extracted by homogenization in 1 ml of Trisure (Bioline, London, UK) using D-Matrix tubes (MP Biomedical, Cambridge, UK) and following the manufacturer’s recommendations. Total RNA concentration, 260/230 and 260/280 ratios were estimated by Nanodrop spectrometer N1000 (Thermo Scientific). RNA integrity was estimated by resolving 1 μg of sample in a 1 % (m/v) ethidium bromide agarose gel. A total of 3 μg of RNA per sample was sent to the Sick-Kids Hospital Next Generation Sequencing service (Vancouver, Canada) for sequencing. Individual barcoded libraries for each animal were paired-end sequenced using two lines of Illumina HiSeq2000. Raw reads were deposited in the EBI-SRA database under the accession number PRJEB7712.
cDNA synthesis and qPCR reactions
1 μg of total RNA from 6 individuals for each of the treatments (WT and TR) was reverse transcribed to cDNA using the Quantitec reverse transcription kit (QIAGEN, Manchester, UK) including the gDNA wipe-out step to remove remains of genomic DNA and –RT and NT controls were run in parallel with 1 μg of RNA but no RT enzyme or RT enzyme but no template. cDNA samples were diluted 1/50 in Nuclease-free water (QIAGEN). 6 μl per sample were mixed with 7.5 μl of SensiFAST SYBR Lo-ROX 2X master mix (Bioline) containing 400nM of sense/antisense primers. Reactions were performed in duplicated in a Mx3005P thermocycler (Agilent, Oxford, UK), with 1 cycle of 2 min at 95 °C and x40 cycles of 5 s 95 °c and 20s at 65 °C, followed by a dissociation curve analysis, where a single peak was detected in all cases.
Primers were designed using Primer 3 [http://biotools.umassmed.edu/bioapps/primer3_www.cgi] to amplify products between 100-200 bp from gene sequences retrieved from a de novo coho salmon skeletal muscle transcriptome (primers and sequences used for primer design can be found in Additional file 11). Netprimer (PremierBiosoft) [http://www.premierbiosoft.com/netprimer/] was used to detect primer hairpins and cross-dimmers. When two salmonid paralogues were identified primers were design to bind to the most divergent regions of sequence. Genorm software  was used to evaluate the stability of the four reference genes analysed rpl27, rpl13, ef1a and ßactin. The rpl13 and ef1a were found to be the most stable reference genes (M = 0.058). Normalization of gene expression was performed using the geometric average of rpl13 and ef1a. All expression values are expressed as arbitrary units.
De novo transcriptome assembly and annotation
Quality filtered raw reads were de novo assembled by Sick-Kids Bioinformatic services (Vancouver, Canada) using Trinity software  (the complete de novo assembly can be found in the Additional files 12, 13, 14, 15 and 16). Resulting contigs were identified by BLAST (BLASTx) against the NCBI non-redundant database (nr) and Gene Ontology (GO) annotated using Blast2GO software default settings . In order to identify the number of unique genes BLASTx results were manually investigated to remove duplicates and those contigs annotated as hypothetical proteins or predicted proteins.
Fully annotated contigs (with positive BLAST and GO results) were BLAST against the KEGG collection of metabolic and signaling pathways with the KEGG Automatic Annotation Service (KAAS) using the single-directional best hit (SBH) method against all vertebrates pathways deposited in the database . For identification of coding sequences in the contigs generated during the de novo assembly the complete zebrafish proteome  was blasted (tBLASTn) against all annotated contigs using BioEdit software [www.mbio.ncsu.edu/bioedit/bioedit.html]. Alignment data from positive hits results between coho salmon contigs and zebrafish gene amino acid sequences gave us an estimation of the percentage of coding sequences contained in the de novo contigs.
Digital gene expression
Read mapping, read normalization and global digital expression were carried out by the bioinformatics department of Sick-Kids Hospital, Next Generation Sequencing service (Vancouver, Canada). Quality filtered raw reads from individual libraries were mapped to the complete de novo coho salmon transcriptome and their abundance estimated using the RSEM . DESEQ program from the R-Bioconductor package was used to estimate global differences in digital gene expression (DGE) between TR and WT groups . The DESEQ program normalizes mapped reads for individual samples by contig length and library depth using a negative binomial distribution previous to test differences in reads mapped between conditions. To test specific hypothesis for particular physiological processes DESEQ normalized counts (DESEQ-counts) per individual animal were retrieved.
Gene ontology (GO) enrichment analysis
GO enrichment analysis from those genes differently expressed between TR and WT after the global DGE analysis was performed using the STRING webserver . In order to maximize GO enrichment analysis BLAST results were manually annotated with their human orthologue abbreviated gene name (e.g. contig identified as dedicator of cytokinesis protein 5 was named as DOCK5).
Paralogue identification and phylogenetic analysis
A phylogenetic analysis was carried to confirm the salmonid-specific WGD origin of potential 4R paralogues in the transcriptome. Potential 4R-paralogues were conceptually translated to their amino acid sequence. BLASTp against the non-redundant NCBI database was used to confirm the identities of the translated paralogues. Teleost orthologues for the genes of interest were retrieved from Ensembl including human and mouse orthologues to be used as outgroups. Potential coho salmon 4R paralogues were used as a query against the rainbow trout (Oncorhynchus mykiss) protein collection (BLASTp) and the Atlantic salmon (Salmo salar) Transcriptome Shotgun Assembly (TSA) data deposited in the NCBI (tBLASTn). Positive BLAST hits were included in the analysis. Amino acids sequences were aligned using Guidance webserver  with MAFFT as MSA algorithm. Only aligned sections with a score over 0.93 were used to generate the phylogenetic tree. Evolutionary models were estimated for all alignments using MEGA5 . In all cases the best evolutionary model was estimated to be JTT + G (data not show). Finally Maximum likelihood trees for each alignment were constructed using PhyML webserver  and displayed using FigTree [http://tree.bio.ed.ac.uk/software/figtree].
For global DGE between TR and WT individuals the DESEQ program was used following programmer recommendations and a false discovery rate (FDR) cut-off of FDR < 0.05 was applied for significant differences. The original list of genes differently expressed generated by DESEQ was manually curated and only those contigs with >15 DESEQ-counts and over 2log2 fold-change were used. As expected from previous studies [45, 46], coho salmon de novo transcriptome presented a significant degree of redundancy; therefore, more than one contig shared the same BLAST results (“sister” contigs). The original DESEQ list of genes was further curated, maintaining those genes that showed consistent expression between “sister contigs”, special care was taken to detect 3R and 4R-paralogues annotated with the same ID by investigating the alignment of sister contigs.
Differences in expression for specific groups of genes were estimated using DESEQ-counts values per individual animal for each gene (n = 6 for each experimental group). Significant differences were detected by a two-tailed test between WT and TR individuals followed by a Benjamin-Hochberg (FDR) correction for multiple comparisons. Significant differences were accepted when FDR < 0.05.
Hierarchical clustering analysis of gene expression data was performed using Permutmatrix with gene expression normalized by row using McQuitty’s method . Principal component analysis for gene expression of the 12 coho salmon analysed was performed using PASW Statistic software v21 (IBM).
Differences in gene expression analysed by qPCR were analysed by t-test and a significant threshold of P < 0.05. Pearson correlation was used to study qPCR and DGE expression data obtained for the same genes. In order to facilitate visualization of results data was logarithmically transformed (Log10 for expression data and Log2 for fold-change data) prior to correlation analysis. Pearson correlation was estimated using PASW Statistic software v21.
Gh-transgenic coho salmon show increased appetite and growth relative to wild type fish. We restricted the food intake of transgenic fish (TR) to that of wild-type (WT) fish fed to satiation, resulting in higher levels of muscle Gh expression, but a similar final body size. The two groups had markedly different gene expression signatures, with TR fish showing increased transcript abundance for pathways associated with protein translation and protein folding and reduced expression of genes involved with myotube fusion. The down-regulation of genes with known function in myoblast fusion, particularly cadherin signaling, was correlated with a reduction in average muscle fibre diameter in TR relative to WT fish which is expected to reduce the costs of maintaining ionic homeostasis. This may explain why TR fish are more active than WT fish yet grow at a similar rate.
All supporting data for the present manuscript is included as additional files.
The study was supported by the Marine Alliance for Science and Technology for Scotland (Scottish Funding Council grant HR09011) and by the Canadian Biotechnology Strategy (RHD).
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