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

Background 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. Results 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. Conclusions 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.Publisher PDFPeer reviewe

Muscle fibre size optimisation provides flexibility for energy budgeting in calorie-restricted coho salmon transgenic for growth hormone

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 (to R.H.D.). Deposited in PMC for immediate releaseCoho salmon (Oncorhynchus kisutch) transgenic for growth hormone (GH) show substantially faster growth than wild-type (WT) fish. We fed GH-transgenic salmon either to satiation (1 year; TF) or the same smaller ration of wild-type fish (2 years; TR), resulting in groups matched for body size to WT salmon. The myotomes of TF and WT fish had the same number and size distribution of muscle fibres, indicating a twofold higher rate of fibre recruitment in the GH transgenics. Unexpectedly, calorie restriction was found to decrease the rate of fibre production in transgenics, resulting in a 20% increase in average fibre size and reduced costs of ionic homeostasis. Genes for myotube formation were downregulated in TR relative to TF and WT fish. We suggest that muscle fibre size optimisation allows the reallocation of energy from maintenance to locomotion, explaining the observation that calorie-restricted transgenics grow at the same rate as WT fish whilst exhibiting markedly higher foraging activity.Publisher PDFPeer reviewe

Fast-growing growth hormone transgenic coho salmon (Oncorhynchus kisutch) show a lower incidence of vaterite deposition and malformations in sagittal otoliths

DGS is a Serra Húnter Tenure-Track lecturer, and this work has been partially funded by the Ministerio de Ciencia y Tecnología grant number RTI2018-100757-B-100. RHD acknowledges support from the Canadian Regulatory System for Biotechnology (grant number 61740).In fish otoliths, CaCO3 normally precipitates as aragonite, and more rarely as vaterite or calcite. A higher incidence of vaterite deposition in otoliths from aquaculture-reared fish has been reported and it is thought that high growth rates under farming conditions might promote its deposition. To test this hypothesis, otoliths from growth hormone (GH) transgenic coho salmon (TF) and non-transgenic (NT) fish of matching size were compared. Once morphometric parameters were normalized by animal length, we found that TF fish otoliths were smaller (-24%, -19%, -20% and -30%; P<0.001 for length, width, perimeter and area, respectively) and rounder (-12%, +13.5%, +15% and -15.5% in circularity, form factor, roundness and ellipticity; P<0.001) than otoliths from non-transgenic fish of matching size. Interestingly, transgenic fish had smaller eyes (-30% eye diameter) and showed a strong correlation between eye and otolith size. We also found that the percentage of otoliths showing vaterite deposition was significantly smaller in transgenic fish (21-28%) compared to non-transgenic (69%; P&lt;0.001). Likewise, the area affected with vaterite deposition within individual otoliths was reduced in transgenic fish (21-26%) compared to non-transgenic (42.5%; P<0.001). Our results suggest that high growth rates per se are not sufficient to cause vaterite deposition in all cases, and that GH overexpression might have a protective role against vaterite deposition, an hypothesis that needs further investigation.Publisher PDFPeer reviewe

An exploration of methods for obtaining 0 = dead anchors for latent scale EQ-5D-Y values

Objectives Discrete choice experiments (DCEs) can be used to obtain latent scale values for the EQ-5D-Y, but these require anchoring at 0 = dead to meet the conventions of quality-adjusted life year (QALY) estimation. The primary aim of this study is to compare four preference elicitation methods for obtaining anchors for latent scale EQ-5D-Y values. Methods Four methods were tested: visual analogue scale (VAS), DCE (with a duration attribute), lag-time time trade-off (TTO) and the location-of-dead (LOD) approach. In computer-assisted personal interviews, UK general public respondents valued EQ-5D-3L health states from an adult perspective and EQ-5D-Y health states from a 10-year-old child perspective. Respondents completed valuation tasks using all four methods, under both perspectives. Results 349 interviews were conducted. Overall, respondents gave lower values under the adult perspective compared to the child perspective, with some variation across methods. The mean TTO value for the worst health state (33333) was about equal to dead in the child perspective and worse than dead in the adult perspective. The mean VAS rescaled value for 33333 was also higher in the child perspective. The DCE produced positive child perspective values and negative adult perspective values, though the models were not consistent. The LOD median rescaled value for 33333 was negative under both perspectives and higher in the child perspective. Discussion There was broad agreement across methods. Potential criteria for selecting a preferred anchoring method are presented. We conclude by discussing the decision-making circumstances under which utilities and QALY estimates for children and adults need to be commensurate to achieve allocative efficiency

Growth hormone transgenesis in coho salmon disrupts muscle immune function impacting cross-talk with growth systems

Acknowledgements We thank Dwight Causey (Macqueen lab, University of Aberdeen) for providing critical comments on the manuscript. Funding AA was supported by a PhD studentship from Kuwait University. The research was supported by the Canadian Regulatory System for Biotechnology (RHD, JHK).Peer reviewedPublisher PD

Association analyses of the MAS-QTL data set using grammar, principal components and Bayesian network methodologies

<p>Abstract</p> <p>Background</p> <p>It has been shown that if genetic relationships among individuals are not taken into account for genome wide association studies, this may lead to false positives. To address this problem, we used Genome-wide Rapid Association using Mixed Model and Regression and principal component stratification analyses. To account for linkage disequilibrium among the significant markers, principal components loadings obtained from top markers can be included as covariates. Estimation of Bayesian networks may also be useful to investigate linkage disequilibrium among SNPs and their relation with environmental variables.</p> <p>For the quantitative trait we first estimated residuals while taking polygenic effects into account. We then used a single SNP approach to detect the most significant SNPs based on the residuals and applied principal component regression to take linkage disequilibrium among these SNPs into account. For the categorical trait we used principal component stratification methodology to account for background effects. For correction of linkage disequilibrium we used principal component logit regression. Bayesian networks were estimated to investigate relationship among SNPs.</p> <p>Results</p> <p>Using the Genome-wide Rapid Association using Mixed Model and Regression and principal component stratification approach we detected around 100 significant SNPs for the quantitative trait (p<0.05 with 1000 permutations) and 109 significant (p<0.0006 with local FDR correction) SNPs for the categorical trait. With additional principal component regression we reduced the list to 16 and 50 SNPs for the quantitative and categorical trait, respectively.</p> <p>Conclusions</p> <p>GRAMMAR could efficiently incorporate the information regarding random genetic effects. Principal component stratification should be cautiously used with stringent multiple hypothesis testing correction to correct for ancestral stratification and association analyses for binary traits when there are systematic genetic effects such as half sib family structures. Bayesian networks are useful to investigate relationships among SNPs and environmental variables.</p

Modelling Galaxy and AGN Evolution in the IR: Black Hole Accretion versus Star-Formation Activity

We present a new backward evolution model for galaxies and AGNs in the infrared (IR). What is new in this model is the separate study of the evolutionary properties of the different IR populations (i.e. spiral galaxies, starburst galaxies, low-luminosity AGNs, "unobscured" type 1 AGNs and "obscured" type 2 AGNs) defined through a detailed analysis of the spectral energy distributions (SEDs) of large samples of IR selected sources. The evolutionary parameters have been constrained by means of all the available observables from surveys in the mid- and far-IR (source counts, redshift and luminosity distributions, luminosity functions). By decomposing the SEDs representative of the three AGN classes into three distinct components (a stellar component emitting most of its power in the optical/near-IR, an AGN component due to hot dust heated by the central black hole peaking in the mid-IR, and a starburst component dominating the far-IR spectrum) we have disentangled the AGN contribution to the monochromatic and total IR luminosity emitted by the different populations considered in our model from that due to star-formation activity. We have then obtained an estimate of the total IR luminosity density (and star-formation density - SFD - produced by IR galaxies) and the first ever estimate of the black hole mass accretion density (BHAR) from the IR. The derived evolution of the BHAR is in agreement with estimates from X-rays, though the BHAR values we derive from IR are slightly higher than the X-ray ones. Finally, we have simulated source counts, redshift distributions and SFD and BHAR that we expect to obtain with the future cosmological Surveys in the mid-/far-IR that will be performed with JWST-MIRI and SPICA-SAFARI.Comment: 19 pages, 15 figures, 3 tables. Accepted for publication in MNRA

Effect of population stratification analysis on false-positive rates for common and rare variants

Principal components analysis (PCA) has been successfully used to correct for population stratification in genome-wide association studies of common variants. However, rare variants also have a role in common disease etiology. Whether PCA successfully controls population stratification for rare variants has not been addressed. Thus we evaluate the effect of population stratification analysis on false-positive rates for common and rare variants at the single-nucleotide polymorphism (SNP) and gene level. We use the simulation data from Genetic Analysis Workshop 17 and compare false-positive rates with and without PCA at the SNP and gene level. We found that SNPs’ minor allele frequency (MAF) influenced the ability of PCA to effectively control false discovery. Specifically, PCA reduced false-positive rates more effectively in common SNPs (MAF > 0.05) than in rare SNPs (MAF < 0.01). Furthermore, at the gene level, although false-positive rates were reduced, power to detect true associations was also reduced using PCA. Taken together, these results suggest that sequence-level data should be interpreted with caution, because extremely rare SNPs may exhibit sporadic association that is not controlled using PCA