Aquaculture Europe 2023

September 18 - 21, 2023

Vienna,Austria

Add To Calendar 19/09/2023 14:00:0019/09/2023 14:15:00Europe/ViennaAquaculture Europe 2023GENETICS DRIVES HEPATIC TRANSCRIPTOME AND DNA METHYLOME OF FARMED GILTHEAD SEA BREAM AFTER BROODSTOCK NUTRITIONAL PROGRAMMINGStolz 0The European Aquaculture Societywebmaster@aquaeas.orgfalseDD/MM/YYYYaaVZHLXMfzTRLzDrHmAi181982

GENETICS DRIVES HEPATIC TRANSCRIPTOME AND DNA METHYLOME OF FARMED GILTHEAD SEA BREAM AFTER BROODSTOCK NUTRITIONAL PROGRAMMING

A. Belenguer1*, F. Naya-Català1, D. Montero2, S. Torrecillas2, B. Soriano1,3, J. Calduch-Giner1, C. Llorens3, R. Fontanillas4 , S. Sarih2 ,  M.J. Zamorano2 , M. Izquierdo2, J. Pérez-Sánchez1

 

1 Nutrigenomics and Fish Growth Endocrinology Group , Institute of Aquaculture Torre de la Sal (IATS, CSIC), Spain; 2Grupo de Investigaci ón en Acuicultura (GIA), IU-ECOAQUA, Universidad de Las Palmas de Gran Canaria, Spain; 3 Biotechvana, Parc Científic Universitat de València, Spain; 4 Skretting Aquaculture Research Centre, Norway . E-mail: a.belenguer@csic.es

 



Introduction

Broodstock nutritional programming improves the offspring utilization of plant-based diets in gilthead sea bream through changes in lipid metabolism .  Attention was initially focused on fatty acid desaturase  2 (fads2) ( the first and rate limiting step in the biosynthesis of n-3  long-chain polyunsaturated fatty acids, LC-PUFA), and  selective breeding for enhanced fads2  expression  in broodstock fish improved the offspring utilization  of plant-based  diets (Xu et al., 2021). Otherwise, de novo fatty acid biosynthesis  of mono-unsaturated fatty acids  offers the possibility to mitigate the signs of deficiencies in n-3 LC-PUFA ,  and the broodstock nutritional programming with a diet rich in α-linolenic acid  served to maintain regulated  the enhanced expression of scd1a  (stearoyl-coenzyme A desaturase) in the gilthead sea bream offspring through changes in DNA-methylation (Perera et al., 2020) . H ow  such regulatory processes  can be driven by a different genetic background is hardly underlined, and the present study aimed to assess how broodstock nutrition affects differentially the  offspring transcriptome and genome-wide DNA methylome of reference and genetically selected fish for growth.

Material and methods

Gilthead sea bream brood fish belonging to reference (REF) or genetically selected (GS) fish within the PROGENSA® selection program received a diet with low fish oil content during the stimulus phase . T wo  5-month old  offspring subsets of each genetic background were fed either a control (15% fish meal and 5.7-7.6% fish oil) or a FUTURE ( 7.5% fish meal and completely devoid of fish oil) diet for about 6 months (challenge phase). At the end of the trial, 6 juvenile fish per each experimental condition w ere anaesthetized and  liver  samples  were  taken for  wide-analyses of gene expression (RNA-seq ) and DNA methylation , using m ethyl-CpG-binding domain sequencing (MBD-seq) for a large coverage of the CpG methylome.

Results and discussion

The offspring of GS fish shared a better performance than those of REF animals during the challenge phase , and differences due to diet (with improved values with the control diet) tended to be lower in GS lineage. Data highlighted a different hepatic transcriptome (RNA-seq) and genome-wide DNA methylation (MBD-seq) pattern depending on the genetic background, which agrees with previous studies in fish (Liu et al., 2022). T he number of differentially expressed transcripts  (comparing control and FUTURE diets) following the challenge phase  varied from 323 in REF fish to 2,009 in GS fish. The number of transcripts of discriminant value by multivariate analysis, and associated enriched  functions (Gene Ontology-Biological Process, GO-BP, terms) , were also markedly higher in GS fish. Moreover, after selecting differentially methylated (DM) regions with  an opposite trend for DNA methylation and  gene  expression, correlation analysis depicted a hyper-methylated and down-regulated gene expression state in GS fish challenged with the FUTURE diet, whereas the opposite pattern was found in REF fish (Figure 1A).  Thus, the resulting epigenetic clock of the latter animals might represent an older phenotype (Piferrer and Anastasiadi, 2023). Moreover, a fter filtering for functions with a high representation in GS fish, 115 genes were retrieved as epigenetic markers nutritionally regulated in this group of fish (Figure 1B). Among them, genes within the GO-BP term Lipid metabolic process (23) were the most reactive following ordering by  gene expression fold-change, which rendered a final list of 10 top markers with a key role on hepatic lipogenesis and fatty acid metabolism (cd36, pitpna , cidea , fasn , g6pd, lipt1 , scd1a, acsbg2 , acsl14 , acsbg2) . T hese top 10 genes also showed a greater concentration of DM CpG sites in the promoter region. Down-regulation of most of those genes agrees with the initial statement that t he epigenetic regulation of gene expression due to nutritional programming may preclude an over-expression of specific genes that might result counterproductive in a changing environment.

Concluding remarks

 Gene expression profiles and DNA methylation signatures  following nutritional programming  were clearly dependent on genetic background in our experimental model. Such assumption affected the magnitude, but also the type and direction of change. Accordingly, the resulting epigenetic clock of REF fish might depict an older phenotype with a lower DNA methylation for the epigenetically responsive genes with a negative methylation-expression pattern. That means that epigenetic markers will be specific of each genetic lineage, serving primarily the broodstock programming in our GS fish to prevent and mitigate later in life the risk of hepatic steatosis  due to an exaggerated and/or poorly regulated hepatic lipogenesis when fish facing low fish oil diets.

Funding.  This work was supported by H2020 Programme under grant agreement 818367 (AquaIMPACT).

References

 Liu Z, Zhou T, Gao D. 2022. Front. Genet. 13, 994471.

Perera E, Turkmen S, Simó- Mirabet P, et al . 2020. Epigenetics 15 , 536–553.

Piferrer F, Anastasiadi D. 2023. Front. Mar. Sci. 10, 1062151.

 Xu H, Ferosehkan S,  Turkmen S, et al.  2017. Aquaculture 535 , 736321.