Grandparental immune priming in S.typhle - Gene expression and Size of F2

Data table shows life history (size-length) and gene expression measurements of 44 target genes and 4 housekepping genes for 192 samples (F2 juveniles) of the experiment "Grandparental immune priming in Syngnathus typhle". Gene expression was measured using Fluidigm chip systems in May 2014. Shown are the mean Ct values (Cycle time) of two technical replicates.

Gene expression and physiological changes of the Antarctic krill Euphausia superba under different hypoxia intensities

Antarctic krill (Euphausia superba) from South Georgia comprise one of the most northern and abundant krill stocks. South Georgia waters are undergoing rapid warming, as a result of climate change, which in turn could alter the oxygen concentration of the water. We investigated gene expression in Antarctic krill related to aerobic metabolism, antioxidant defence, and heat-shock response under severe (2.5% O2 saturation or 0.6 kPa) and threshold (20% O2 saturation or 4 kPa) hypoxia exposure compared to in situ levels (normoxic; 100% O2 saturation or 21 kPa). Biochemical metabolic and oxidative stress indicators complemented the genic expression analysis to detect in vivo signs of stress during the hypoxia treatments. Expression levels of the genes citrate synthase (CS), mitochondrial manganese superoxide dismutase (SODMn-m) and one heat-shock protein isoform (E) were higher in euphausiids incubated 6 h at 20% O2 saturation than in animals exposed to control (normoxic) conditions. All biochemical antioxidant defence parameters remained unchanged among treatments. Levels of lipid peroxidation were raised after 6 h of severe hypoxia. Overall, short-term exposure to hypoxia altered mitochondrial metabolic and antioxidant capacity, but did not induce anaerobic metabolism. Antarctic krill are swarming organisms and may experience short periods of hypoxia when present in dense swarms. A future, warmer Southern ocean, where oxygen saturation levels are decreased, may result in smaller, less dense swarms as they act to avoid greater levels of hypoxia.

Gene expression profiling in gills of the great spider crab Hyas araneus in respond to ocean acidification and warming, supplementary data

Hypercapnia and elevated temperatures resulting from climate change may have adverse consequences for many marine organisms. While diverse physiological and ecological effects have been identified, changes in those molecular mechanisms, which shape the physiological phenotype of a species and limit its capacity to compensate, remain poorly understood. Here, we use global gene expression profiling through RNA-Sequencing to study the transcriptional responses to ocean acidification and warming in gills of the boreal spider crab Hyas araneus exposed medium-term (10 weeks) to intermediate (1,120 µatm) and high (1,960 µatm) PCO2 at different temperatures (5°C and 10°C). The analyses reveal shifts in steady state gene expression from control to intermediate and from intermediate to high CO2 exposures. At 5°C acid-base, energy metabolism and stress response related genes were upregulated at intermediate PCO2, whereas high PCO2 induced a relative reduction in expression to levels closer to controls. A similar pattern was found at elevated temperature (10°C). There was a strong coordination between acid-base, metabolic and stress-related processes. Hemolymph parameters at intermediate PCO2 indicate enhanced capacity in acid-base compensation potentially supported by upregulation of a V-ATPase. The likely enhanced energy demand might be met by the upregulation of the electron transport system (ETS), but may lead to increased oxidative stress reflected in upregulated antioxidant defense transcripts. These mechanisms were attenuated by high PCO2, possibly as a result of limited acid-base compensation and metabolic down-regulation. Our findings indicate a PCO2 dependent threshold beyond which compensation by acclimation fails progressively. They also indicate a limited ability of this stenoecious crustacean to compensate for the effects of ocean acidification with and without concomitant warming.

Gene expression changes in the coccolithophore Emiliania huxleyi after 500 generations of selection to ocean acidification

Coccolithophores are unicellular marine algae that produce biogenic calcite scales and substantially contribute to marine primary production and carbon export to the deep ocean. Ongoing ocean acidification particularly impairs calcifying organisms, mostly resulting in decreased growth and calcification. Recent studies revealed that the immediate physiological response in the coccolithophore Emiliania huxleyi to ocean acidification may be partially compensated by evolutionary adaptation, yet the underlying molecular mechanisms are currently unknown. Here, we report on the expression levels of 10 candidate genes putatively relevant to pH regulation, carbon transport, calcification and photosynthesis in E. huxleyi populations short-term exposed to ocean acidification conditions after acclimation (physiological response) and after 500 generations of high CO2 adaptation (adaptive response). The physiological response revealed downregulation of candidate genes, well reflecting the concomitant decrease of growth and calcification. In the adaptive response, putative pH regulation and carbon transport genes were up-regulated, matching partial restoration of growth and calcification in high CO2-adapted populations. Adaptation to ocean acidification in E. huxleyi likely involved improved cellular pH regulation, presumably indirectly affecting calcification. Adaptive evolution may thus have the potential to partially restore cellular pH regulatory capacity and thereby mitigate adverse effects of ocean acidification.

Growth, survival, gene expression, microbiota and tryptic activity during feeding of Scophthalmus maximus first feeding larvae with beta-glucan (MacroGard)

Reflecting the natural biology of mass spawning fish aquaculture production of fish larvae is often hampered by high and unpredictable mortality rates. The present study aimed to enhance larval performance and immunity via the oral administration of an immunomodulator, beta-glucan (MacroGard®) in turbot (Scophthalmus maximus). Rotifers (Brachionus plicatilis) were incubated with or without yeast beta-1,3/1,6-glucan in form of MacroGard® at a concentration of 0.5 g/L. Rotifers were fed to first feeding turbot larvae once a day. From day 13 dph onwards all tanks were additionally fed untreated Artemia sp. nauplii (1 nauplius ml/L). Daily mortality was monitored and larvae were sampled at 11 and 24 dph for expression of 30 genes, trypsin activity and size measurements. Along with the feeding of beta-glucan daily mortality was significantly reduced by ca. 15% and an alteration of the larval microbiota was observed. At 11 dph gene expression of trypsin and chymotrypsin was elevated in the MacroGard® fed fish, which resulted in heightened tryptic enzyme activity. No effect on genes encoding antioxidative proteins was observed, whilst the immune response was clearly modulated by beta-glucan. At 11 dph complement component c3 was elevated whilst cytokines, antimicrobial peptides, toll like receptor 3 and heat shock protein 70 were not affected. At the later time point (24 dph) an anti-inflammatory effect in form of a down-regulation of hsp 70, tnf-alpha and il-1beta was observed. We conclude that the administration of beta-glucan induced an immunomodulatory response and could be used as an effective measure to increase survival in rearing of turbot.

Transgenerational effects persist down the maternal line in marine sticklebacks: gene expression matches physiology in a warming ocean, supplementary material

Transgenerational effects can buffer populations against environmental change, yet little is known about underlying mechanisms, their persistence, or the influence of environmental cue timing. We investigated mitochondrial respiratory capacity (MRC) and gene expression of marine sticklebacks that experienced acute or developmental acclimation to simulated ocean warming (21°C) across three generations. Previous work showed that acute acclimation of grandmothers to 21°C led to lower (optimised) offspring MRCs. Here, developmental acclimation of mothers to 21°C led to higher, but more efficient offspring MRCs. Offspring with a 21°Cx17°C grandmother-mother environment mismatch showed metabolic compensation: their MRCs were as low as offspring with a 17°C thermal history across generations. Transcriptional analyses showed primarily maternal but also grandmaternal environment effects: genes involved in metabolism and mitochondrial protein biosynthesis were differentially expressed when mothers developed at 21°C, whereas 21°C grandmothers influenced genes involved in hemostasis and apoptosis. Genes involved in mitochondrial respiration all showed higher expression when mothers developed at 21° and lower expression in the 21°Cx17°C group, matching the phenotypic pattern for MRCs. Our study links transcriptomics to physiology under climate change, and demonstrates that mechanisms underlying transgenerational effects persist across multiple generations with specific outcomes depending on acclimation type and environmental mismatch between generations.

Using the R package Shiny to create web applications that facilitate quantitative gene expression analysis

Thesis (Master's)--University of Washington, 2016-06

A Mixture model with random-effects components for clustering correlated gene-expression profiles

Motivation: The clustering of gene profiles across some experimental conditions of interest contributes significantly to the elucidation of unknown gene function, the validation of gene discoveries and the interpretation of biological processes. However, this clustering problem is not straightforward as the profiles of the genes are not all independently distributed and the expression levels may have been obtained from an experimental design involving replicated arrays. Ignoring the dependence between the gene profiles and the structure of the replicated data can result in important sources of variability in the experiments being overlooked in the analysis, with the consequent possibility of misleading inferences being made. We propose a random-effects model that provides a unified approach to the clustering of genes with correlated expression levels measured in a wide variety of experimental situations. Our model is an extension of the normal mixture model to account for the correlations between the gene profiles and to enable covariate information to be incorporated into the clustering process. Hence the model is applicable to longitudinal studies with or without replication, for example, time-course experiments by using time as a covariate, and to cross-sectional experiments by using categorical covariates to represent the different experimental classes. Results: We show that our random-effects model can be fitted by maximum likelihood via the EM algorithm for which the E(expectation) and M(maximization) steps can be implemented in closed form. Hence our model can be fitted deterministically without the need for time-consuming Monte Carlo approximations. The effectiveness of our model-based procedure for the clustering of correlated gene profiles is demonstrated on three real datasets, representing typical microarray experimental designs, covering time-course, repeated-measurement and cross-sectional data. In these examples, relevant clusters of the genes are obtained, which are supported by existing gene-function annotation. A synthetic dataset is considered too.

Exploring ant-based algorithms for gene expression data analysis

Objective: Recently, much research has been proposed using nature inspired algorithms to perform complex machine learning tasks. Ant colony optimization (ACO) is one such algorithm based on swarm intelligence and is derived from a model inspired by the collective foraging behavior of ants. Taking advantage of the ACO in traits such as self-organization and robustness, this paper investigates ant-based algorithms for gene expression data clustering and associative classification. Methods and material: An ant-based clustering (Ant-C) and an ant-based association rule mining (Ant-ARM) algorithms are proposed for gene expression data analysis. The proposed algorithms make use of the natural behavior of ants such as cooperation and adaptation to allow for a flexible robust search for a good candidate solution. Results: Ant-C has been tested on the three datasets selected from the Stanford Genomic Resource Database and achieved relatively high accuracy compared to other classical clustering methods. Ant-ARM has been tested on the acute lymphoblastic leukemia (ALL)/acute myeloid leukemia (AML) dataset and generated about 30 classification rules with high accuracy. Conclusions: Ant-C can generate optimal number of clusters without incorporating any other algorithms such as K-means or agglomerative hierarchical clustering. For associative classification, while a few of the well-known algorithms such as Apriori, FP-growth and Magnum Opus are unable to mine any association rules from the ALL/AML dataset within a reasonable period of time, Ant-ARM is able to extract associative classification rules.

Impacts of seawater acidification on mantle gene expression patterns of the Baltic Sea blue mussel: implications for shell formation and energy metabolism, link to supplementary material

Marine organisms have to cope with increasing CO2 partial pressures and decreasing pH in the oceans. We elucidated the impacts of an 8-week acclimation period to four seawater pCO2 treatments (39, 113, 243 and 405 Pa/385, 1,120, 2,400 and 4,000 µatm) on mantle gene expression patterns in the blue mussel Mytilus edulis from the Baltic Sea. Based on the M. edulis mantle tissue transcriptome, the expression of several genes involved in metabolism, calcification and stress responses was assessed in the outer (marginal and pallial zone) and the inner mantle tissues (central zone) using quantitative real-time PCR. The expression of genes involved in energy and protein metabolism (F-ATPase, hexokinase and elongation factor alpha) was strongly affected by acclimation to moderately elevated CO2 partial pressures. Expression of a chitinase, potentially important for the calcification process, was strongly depressed (maximum ninefold), correlating with a linear decrease in shell growth observed in the experimental animals. Interestingly, shell matrix protein candidate genes were less affected by CO2 in both tissues. A compensatory process toward enhanced shell protection is indicated by a massive increase in the expression of tyrosinase, a gene involved in periostracum formation (maximum 220-fold). Using correlation matrices and a force-directed layout network graph, we were able to uncover possible underlying regulatory networks and the connections between different pathways, thereby providing a molecular basis of observed changes in animal physiology in response to ocean acidification.

Effects of CO2 and iron availability on rbcL gene expression in Bering Sea diatoms

Iron (Fe) can limit phytoplankton productivity in approximately 40% of the global ocean, including in high-nutrient, low-chlorophyll (HNLC) waters. However, there is little information available on the impact of CO2-induced seawater acidification on natural phytoplankton assemblages in HNLC regions. We therefore conducted an on-deck experiment manipulating CO2 and Fe using Fe-deficient Bering Sea water during the summer of 2009. The concentrations of CO2 in the incubation bottles were set at 380 and 600 ppm in the non-Fe-added (control) bottles and 180, 380, 600, and 1000 ppm in the Fe-added bottles. The phytoplankton assemblages were primarily composed of diatoms followed by haptophytes in all incubation bottles as estimated by pigment signatures throughout the 5-day (control) or 6-day (Fe-added treatment) incubation period. At the end of incubation, the relative contribution of diatoms to chlorophyll a biomass was significantly higher in the 380 ppm CO2 treatment than in the 600 ppm treatment in the controls, whereas minimal changes were found in the Fe-added treatments. These results indicate that, under Fe-deficient conditions, the growth of diatoms could be negatively affected by the increase in CO2 availability. To further support this finding, we estimated the expression and phylogeny of rbcL (which encodes the large subunit of RuBisCO) mRNA in diatoms by quantitative reverse transcription polymerase chain reaction (PCR) and clone library techniques, respectively. Interestingly, regardless of Fe availability, the transcript abundance of rbcL decreased in the high CO2 treatments (600 and 1000 ppm). The present study suggests that the projected future increase in seawater pCO2 could reduce the RuBisCO transcription of diatoms, resulting in a decrease in primary productivity and a shift in the food web structure of the Bering Sea.