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Linking stress coping styles with the brain gene expression across three different fish species: Atlan:c salmon, European seabass and Gilthead seabream (Salmo salar, Dicentrarchus labrax and Sparus aurata) Sonia Rey and Simon Mackenzie Ins0tute of Aquaculture, University of S0rling, S0rlingshire, FK9 4LA, UK. E-‐mail: [email protected] HYPOTHESIS: Natural varia+ons in levels of specific mRNA transcripts are directly related to the coping style of the individual, and thus coping style is an essen+al resolving variable for the interpreta+on of gene expression data. Introduc:on Objec:ves Resolving phenotype varia0on in response to environmental perturba0on is key to understanding biological adapta0on. Stress 1) Objec:vely iden:fy genes/gene sets involved in different coping styles for 3 different species of importance to European Aquaculture Industry (Atlan:c salmon, European seabass, Gilthead coping styles (SCS) can be used to resolve varia0on in the seabream). transcriptome. Here we combined behavioral screening and gene expression using mRNAs correlated to SCS across three fish species. 2) Characterize target gene expression and correlate to different coping styles. Iden+fica+on of Target mRNAs: Common mRNA transcripts differen0ally expressed in zebrafish screened for coping styles (Rey et al. 2013) were used to iden0fy target genes in the other three species studied in this project. This set of specific target transcripts that display CS-‐specific variance homologous gene sequences were cloned ’in silico’ across all project species. In silico cloning was carried out using genomic resources from all available public libraries and several restricted access collec0ons. To iden0fy specific target genes, itera:ve BLAST (Basic Local Alignment Search Tool) was executed using the filtered target set against each species of interest. Sea bass had 3738 homologues, Sea bream 1734 and Salmon more than 45000 homologues with high e-‐values (<1E-‐20). These mRNA lists were curated and >30 genes selected and validated for each fish species. Validated genes for each species were also cloned and 4 mRNAs for salmon and sea bass and 3 for sea bream were chosen for the gene expression study. Other genes relevant to neuroplas0city have been also iden0fied and cloned to perform ISH in fish brains. • Atlan0c salmon Log10 genecopy number 10 Fig 1. Overview and picture of the behavioural observa:on tanks and tests. On the top of the tanks the door system is visible, and in the first tank it is possible to see the hole between the tanks (from Damsgård 2013, Copewell deliverable D1.5). *** *** Cluster cat 2 Cluster cat 1 Cluster cat 3 *** *** 1 ATPaseα3 IFRD1 CRY PTB Fig 3. Classifica0on by a K-‐means CLUSTER by gene expression was significantly different between all coping styles with a tank effect (MANCOVA, p<0.001). Each cluster represents a stress c o p y i n g s t y l e ( P r o a c 0 v e , intermediate and reac0ve) Fig 2. Different target mRNA copy number related to coping styles screened by hypoxia tolerance test in groups. No significant differences were found (p>0.05). Major points: • the observed rela0onship between the measured mRNA transcript number highlights a strongly consistent pacern within each individual measured. • This pacern varies in global intensity, total mRNA count, between individuals. • Cluster analysis of expression data independently of the behavioural data iden0fied 3 dis0nct groups of individuals in the popula0on. Log10gene copy number • European sea bass Fig 4. Individual and grouped-‐based tests used to screen coping styles in European sea bass Dicentrarchus labrax (from Ferrari et al. 2015, under rev.). The test used for this experiment was the hypoxia test. Fig 5. Classifica0on by the hypoxia tolerance test in groups. No differences were found between coping styles for gene expression (MANCOVA p>0.05) for all fish studied. • Gilthead sea bream Fig 6. Classifica0on by a K-‐means CLUSTER, gene expression was significantly different only for GAPDH gene expression (ANOVA, p<0.001). Each cluster represents a stress copying style (Proac0ve, intermediate and reac0ve) *** Major points: • K-‐means cluster analysis of expression data independent of behavioural analysis iden0fied 3 dis0nct groups of individuals but only differences on GAPDH gene expression were significantly different. • No differences on mRNA transcripts was found for fish screened with the behavioural test. b ATP1A1 10 1 Log10 genecopy number Log10 genecopy number a Reactive Random Proactive Coping Style Log10 genecopy number Overview of the main conclusions found in the different tests used to screen coping styles in Gilthead sea bream Sparus aurata (from Castanheira et al. 2013,copewell first periodic report, Month 18 ) Acknowledgements: this work was supported by the COPEWELL-‐FP7-‐ KBBE Project (EU project 265957). 1 Reactive Random Proactive Coping Style IFRD1 c Individual-‐ and grouped-‐based tests used to screen coping styles in Gilthead sea bream Sparus aurata (from Castanheira et al. 2013). The test used for this experiment was the restraining test. GAPDH 10 8 6 *** 4 2 0 Reactive Random Coping Style Proactive Major points: • IFRD1 mRNA transcript varia0on highlighted the presence of 2 dis0nct groups of individuals within the popula0on. • The two dis0nct groups found with the k-‐means cluster analysis coincided with the behavioural classifica0on in coping styles. References: Castanheira et al. 2013 Plos One8(4):e62037. doi:10.1371/journal.pone.0062037 Rey et al. 2013 Molecular Ecology 22, 6100-‐6115. doi: 10.1111/mec.12556 Ferrari et al. 2015 Applied Animal behaviour (under revision)