Oregano dietary supplementation modifies the liver transcriptome profile in broilers: RNASeq analysis

Accepted Manuscript Oregano dietary supplementation modifies the liver transcriptome profile in broilers: RNASeq analysis

Marcella Sabino, Stefano Capomaccio, Katia Cappelli, Andrea Verini-Supplizi, Lorenzo Bomba, Paolo Ajmone-Marsan, Gabriella Cobellis, Oliviero Olivieri, Camillo Pieramati, Massimo Trabalza-Marinucci PII: DOI: Reference:

S0034-5288(17)30008-5 doi:10.1016/j.rvsc.2017.11.009 YRVSC 3461

To appear in:

Research in Veterinary Science

Received date: Revised date: Accepted date:

4 January 2017 17 November 2017 18 November 2017

Please cite this article as: Marcella Sabino, Stefano Capomaccio, Katia Cappelli, Andrea Verini-Supplizi, Lorenzo Bomba, Paolo Ajmone-Marsan, Gabriella Cobellis, Oliviero Olivieri, Camillo Pieramati, Massimo Trabalza-Marinucci , Oregano dietary supplementation modifies the liver transcriptome profile in broilers: RNASeq analysis. The address for the corresponding author was captured as affiliation for all authors. Please check if appropriate. Yrvsc(2017), doi:10.1016/j.rvsc.2017.11.009

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Oregano dietary supplementation modifies the liver transcriptome profile in broilers: RNASeq analysis. Marcella Sabinoa, Stefano Capomaccioa, Katia Cappellia, Andrea Verini-Supplizia* , Lorenzo Bombac, Paolo Ajmone-Marsanb, Gabriella Cobellisa, Oliviero Olivieria, Camillo Pieramatia,

Dipartimento di Medicina Veterinaria, Università degli Studi di Perugia, Via San Costanzo,

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a

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Massimo Trabalza-Marinuccia 


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4, 06126, Perugia, IT b

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Istituto di Zootecnica, Università Cattolica del Sacro Cuore, Via Emilia Parmense, 84,

c

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29122, Piacenza, IT

Wellcome Trust Sanger Institute - Wellcome Genome Campus, Hinxton, Cambridge, CB10

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1SA, UK

*Corresponding author at: Dipartimento di Medicina Veterinaria, Università degli Studi di

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Perugia, Via San Costanzo, 4, 06126, Perugia, Italy.

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e-mail: [email protected]

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Abstract Intensive farming of broilers involves stressful conditions that reduce animal welfare and performance. New dietary strategies to improve performance and meat quality include the

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administration of plant extracts. Oregano (Origanum vulgare L.) is known for its

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antimicrobial, anti-fungal, insecticidal and antioxidant properties. However, studies on diet supplementation with oregano are mainly focused on the evaluation of animal performance,

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while partial information is available on transcriptomics and nutrigenomics and, in particular,

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Next Generation Sequencing (NGS) is not widely applied. In this study we tested the effect of an oregano aqueous extract supplemented diet on gene expression in broiler chickens. Whole

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liver transcriptome of 10 birds fed with a supplemented diet versus 10 controls was analysed using the RNA-Seq technique. One hundred and twenty-nine genes were differentially

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expressed with an absolute log fold change >1.

The analysis reveals a massive down-regulation of genes involved in fatty acid metabolism insulin signalling pathways in broilers fed

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and

with the oregano

aqueous extract

supplementation. Down-regulated genes could be associated to chicken lean line, suggesting

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the potential beneficial effect of oregano supplementation in reducing both abdominal and visceral fat deposition. Down-regulation of insulin signalling pathway related genes suggest that dietary oregano supplementation might be an option in obesity and diabetes conditions. Keywords: Nutrigenomics, differentially expressed genes, fat biosynthesis pathway.

ACCEPTED MANUSCRIPT 1. Introduction Intensive farming of broilers involves stressful conditions for the animals that reduce growth performance and overall health (Quinteiro-Filho et al., 2012; Klanicova et al., 2011). After the EU ban on the use of antibiotics in animal production, a large amount of research has been done to find feed additives that could be used as growth promoters in the poultry

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industry (Lee et al., 2004): natural compounds and plant extracts have been proposed and

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extensively examined because they act as antimicrobials and antioxidants and are well

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accepted by consumers. Many experiments have been conducted both in vivo and in vitro (Lee et al., 2010; Voljc et al., 2011; Du et al., 2015; Abiala et al., 2016; Kelly et al., 2017;

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Recoules et al., 2017).

Published studies reported an improvement in the performance of chickens fed with a

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combination of plant extracts, probably due to a stabilized intestinal microbiota and a better nutrient digestibility (Alcicek and Cabuk, 2004; Jamroz et al., 2006). Moreover, phytogenic

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compounds have been proven to be effective in enhancing feed hygiene, animal oxidative status and immune response (Franciosini et al., 2016). This may additionally result in an

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improvement of meat product quality (Botsoglou et al., 2003; Bampidis et al., 2005). Oregano (Origanum vulgare L.) extracts have been used as dietary supplements in broilers

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(Botsoglou et al., 2002; Mathlouthi et al., 2012; Ghazi et al., 2015; Scocco et al., 2016) because of their antimicrobial (Lee et al., 2004; Lambert et al., 2001), antifungal (Kalemba and Kunicka, 2003), insecticidal (Karpouhtsis et al., 1998) and antioxidant (Cuppett and Hall, 1998; Cervato et al., 2000; Botsoglou et al., 2004) proprieties. Most of these properties appear to be related to its carvacrol and thymol content (Adam et al., 1998; Teixeira et al., 2013). Diet is one of the environmental factors that directly affects gene expression through food bioactive molecular components (Kaput and Rodriguez, 2004): these molecules interact with

ACCEPTED MANUSCRIPT transcription factors as ligands, acting positively or negatively on transduction signalling pathways (Dauncey et al., 2001; Kaput and Rodriguez, 2004). Moreover, food bioactive molecules can affect epigenetic regulation, such as DNA methylation and histone modifications (Choi and Friso, 2010; Kalani et al., 2015). Published studies concerning dietary oregano supplementation have so far been mainly

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focused on animal performance evaluation and low throughput gene expression analyses

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(Akbarian et al., 2013; Lillehoj et al., 2011), whereas nutrigenomics approaches with Next

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Generation Sequencing (NGS) strategies have been rarely used.

Indeed, there are many advantages to using parallel massive sequencing instead of other

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transcriptome analyses such as microarray, because this technology is limited to the existing genomic annotation, while RNA-seq experiments are able to investigate both known and

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unknown transcriptional units (Mortazavi et al., 2008; Nagalakshmi et al., 2008). Moreover, RNA-Seq has the ability to quantify a large dynamic range of expression levels,

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with absolute values derived from reads alignments rather than relative expression levels derived from image analysis data processing and normalization (Ozsolak and Milos, 2011).

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The aim of this study was to identify the effects of an oregano aqueous extract dietary supplementation on liver gene expression in broiler chickens, using the RNA-Seq approach.

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2. Materials and Methods

2.1 Animals, diets and experimental design The experiment was conducted in a commercial poultry house in May-June 2013. A total of 120, one-day-old female broilers (Ross 308), were purchased from a commercial hatchery and randomly divided into two homogeneous experimental groups (control = CTRL; oregano = ORE). Each group included 60 birds. All subjects were vaccinated at the hatchery against infectious bronchitis, coccidiosis, Newcastle disease and Marek disease, and subjected to normal management procedures used in commercial broiler production.

ACCEPTED MANUSCRIPT The birds were floor-raised up to 42 days of age. The two groups received the same maizesoybean based commercial starter and grower/finisher feeds (from day 1 to 21 and from day 22 to 42, respectively), except that the ORE diet was supplemented with 0.2% oregano (Origanum vulgare L.) aqueous extract (Table 1). Oregano aqueous extract preparation and composition details were previously described (Setti and Zanichelli, 2009; Franciosini et al.,

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2016). Diet was administered in mash form, and water was offered ad libitum. Feed analyses

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were conducted following Association of Official Agricultural Chemists (AOAC) procedures

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(1990; 1996; 2000). Animal care procedures complied with European recommendations (Directive 2007/43/EU) which set welfare standards for keeping chickens for meat

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production.

2.2 Tissue collection, RNA extraction and sequencing

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Liver samples from 20 randomly selected subjects – 10 per experimental group, ORE and CTRL – were collected at slaughtering. Tissues were snap frozen in liquid nitrogen and

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stored at -80°C. Total RNA was extracted from all samples according to the Fatty and Fibrous RNA Kit manufacturer specifications (Bio-Rad, CA, USA) from about 25 mg of liver

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tissue per sample, and powdered with a mortar and pestle using liquid nitrogen. To remove genomic DNA from samples, we used DNAse treatment according to the TURBO DNA-free

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kit manufacturer specifications (Ambion – Life Technologies). A NanoDrop 2000 spectrophotometer (Thermo Fisher Scientific, Waltham, MA, USA) and Qubit 2.0 Flurometer (Life Technologies, CA, USA) were used to assess RNA concentration, and microfluidic electrophoresis on the BioAnalyzer 2100 (Agilent Technologies) revealed integrity and suitability for NGS library preparation. Sequences were produced on an Illumina HiSeq 1500 platform generating 101 bp paired end reads according to the TruSeq2 kit. 2.3 Bioinformatic analysis

ACCEPTED MANUSCRIPT 2.3.1 Mapping and counting reads The aligning process was performed after proper quality control of the raw sequences. Quality

control

(QC)

and

trimming

were

(http://www.bioinformatics.babraham.ac.uk/projects/fastqc)

performed and

with

Trimmomatic

FastQC v.

0.33

(Bolger et al., 2014), respectively retaining reads of 60 bp minimum and overall quality of

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20. ILLUMINACLIP flag was also set with the following parameters: 2:30:10:5.

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After QC, quality checked reads were mapped using TopHat/Bowtie 2 (Trapnell et al., 2012),

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guided by the Ensembl v.80 transcript annotation downloaded from the UCSC Table browser, on the Gallus gallus reference genome (Galgal 4.0), adjusting intron spanning parameters

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(max-intron-length 20000) according to the mean length previously reported (Hillier et al., 2004). Common quality parameters in RNA-Seq experiments (insert length, gene mapping

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bias, RNA junctions) were evaluated using RSeQC (Wang et al., 2012). Aligned reads were classified as counts on transcripts with the software featureCounts using

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the Galgal4 Ensembl 82 annotation coordinates (Liao et al., 2014). 2.3.2 Differential gene expression and enrichment analysis

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The genes differentially expressed between CTRL and ORE groups were identified using MetaSeq R package (Moulos and. Hatzis, 2015). This package relies on a meta-analysis

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method that firstly applies up to six common methods in DGE analysis with RNA-Seq data (DESeq, edgeR's exact test, limma with the voom method, NBPSeq, NOISeq and baySeq) and then summarizes the results reducing false hits while maintaining true positives. Briefly, a matrix composed of 17954 rows representing the Ensembl transcript annotation and one column for each library (20) was imported into R and differential gene expression was assessed following best practices for the MetaSeq R package. A transcript was considered differentially expressed if the False Discovery Rate (FDR) adjusted p-value (q value) was lower than 0.05 and log Fold Change comprised between -1

ACCEPTED MANUSCRIPT and +1. Differentially expressed transcripts between CTRL and ORE were annotated using BioMart, (http://www.ensembl.org/biomart/martview/), and corresponding gene names were used to perform Gene Ontology enrichment analysis using the Cytoscape 3.3.0 plugin BiNGO 2.44 (Biological Networks Gene Ontology) and ClueGO 3.2.0. Our differentially genes expressed list was the input for Cytoscape tools, and each Ensembl Transcript ID was

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substituted by the corresponding EntrezGene ID.

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3. Results

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3.1 Bioinformatic analysis

The experiment produced over 400 million reads (403.540.136), distributed as detailed in

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Table 2. The mean number of reads per sample was over 20 million. Quality control and

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trimming procedures retained the vast majority of the sequences produced (99% of the total). Alignment was successful for 86% of the cleaned reads, and a good proportion of "unique

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alignments" (sequences matching only one position throughout the entire genome) was observed (93.85%). Only these sequences were used for the differential gene expression

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assessment to avoid introducing bias through multi- mapper assignment uncertainty. 3.2 Differential gene expression

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After statistical analysis with MetaSeq R package 129 genes differentially expressed transcripts were found in response to ORE diet with q < 0.05 and absolute fold change (logFC) equal or greater than 1. Among them, 104 genes were down regulated (logFC < -1) while 25 were up regulated (Figure 1, Supplementary Table 1). 3.3 Gene ontology and pathway analysis After annotation of the modulated transcript list through BioMart, the gene names retrieved were used to perform enrichment analysis with Cytoscape 3.3.0. Gene Ontology (GO) vocabularies (Cellular Component CC, Biological Process BP and Molecular Function MF) over representation were explored with BiNGO. One hundred

ACCEPTED MANUSCRIPT thirteen gene names were used as input in BiNGO. Results of GO enrichment are displayed in Table 3. Using the ClueGO tool we generated the network with the most significant CC, BP, MF and KEGG (Kyoto Encyclopaedia of Genes and Genomes) pathways (FDR <0.05, after Benjamin-Hochberg correction).

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Our analysis was enriched for 39 GO Terms, which included 33 GO BP, 2 GO CC, 4 GO MF

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and 3 KEGG pathways: Glycolysis/Gluconeogenesis, Pyruvate metabolism and PPAR

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signalling pathway (Table 4 and 5).

With the highly interconnected network identified, we focused on pathways and biological

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processes enriched for network molecules and significant with an FDR <0.05. 4. Discussion

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Differential gene expression analysis, evaluated comparing liver transcriptome from the ORE and CTRL groups, identified interconnected networks, KEGG pathways and enriched GO

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terms significantly associated with performance data and metabolism as reported by Franciosini et al. (2016) and Scocco et al. (2016).

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In our experimental system, the pathways most affected are those related to metabolism and the biosynthesis of lipids, crucial biological processes in current breeding schemes for their

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association with increased body weight in broilers. Indeed, the “fine regulation” of fat deposition is a high value process in broiler breeding (Zhao et al., 2007): increase of abdominal and visceral fat and excessive adiposity is considered a disadvantage, although intramuscular fat improves meat organoleptic characteristics (Emmerson, 1997;

Zhou et al.,

2006; Shu et al., 2011). Efforts to modulate fat deposition in chickens include genetic selection, housing and environmental strategies, and feeding management (Bourneuf et al., 2006; He et al., 2014; Wang et al., 2012; Resnyk et al., 2015). However, since hepatic lipogenesis contributes to more than 80-85% of the total fatty acid storage in chicken adipose

ACCEPTED MANUSCRIPT tissue (O’Hea and Leveille, 1968; Richards et al., 2003; Cai et al., 2009), knowledge of selective fat deposition-related genes may be a new strategy aimed at increasing meat production while enhancing quality (Claire D’Andre et al., 2013). The down-regulation of the fat biosynthetic process in our analyses could be an explanation for the body weight gain reported for the ORE group during the first period of growth of the

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birds (Scocco et al., 2016).

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ClueGO pathways analysis, indeed, revealed that two significant down-regulated DEGs –

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cytosolic phosphoenolpyruvate carboxykinase (Pck1) and stearoyl-CoA desaturase (SCD) – are included in enriched PPAR signalling KEGG pathway (Table 4). Noteworthy, SCD is

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also described by lipid metabolism GO Terms so as other three significant DEGs: fatty acid synthase (FASN), insulin Induced Gene 1 (INSG1) and Lipin 1 (LPIN1) (Table 5).

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The FASN gene encodes for a key enzyme whose main function is to catalyse the synthesis of long-chain saturated fatty acids, mainly palmitic acid (Dervishi et al., 2012). The INSG1 gene

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encodes a protein, which participates in sterol-dependent HMG-CoA reductase degradation and the regulation of a transcription factor (SREBP) that modulates the expression of over 30

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genes involved in cholesterol and fatty acids synthesis; interestingly, one of these genes is FASN (Yabe et al., 2002). FASN has demonstrated a crucial role in chicken liver de novo

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lipogenesis (Claire D’Andre et al., 2013); indeed, Bourneuf and colleagues’ microarray analysis of liver tissue (Bourneuf et al., 2006) revealed up-regulation of FASN in fat chicken line with respect to a lean line. Moreover, both genes are strong candidates for porcine fat tissue accumulation and FA composition (Grzes et al., 2016). SCD gene encodes for a key enzyme in lipid metabolism that catalyses the synthesis triglycerides, cholesterol and wax esters membrane phospholipids using monounsaturated fatty acids as substrates (Heinemann and Ozols, 2003; Miyazaki and Ntambi, 2003; Dridi et al., 2007). SCD is expressed in numerous broiler tissues and gender, diet, hormonal factors

ACCEPTED MANUSCRIPT and environmental stimuli can influence its expression. There is evidence that SCD activity and expression in liver of fat line chickens is higher than in lean line chickens (Legrand et al., 1987; Douaire et al., 1992; Legrand and Hermier, 1992). Finally LPIN1, also down regulated in our analyses, is a gene involved in regulating lipid metabolism which encodes for a phosphatidate phosphatase (PAP) enzyme, implicated in

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triglyceride and phospholipid de novo biosynthesis (Donkor et al., 2007). Its deficiency in

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mice is associated with a fat deposition reduction (Phan et al., 2004), while LPIN1 up

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regulation induce obesity condition (Phan and Reue, 2005). LPIN1 is also up regulated in abdominal fat in fat line chickens (Resnyk et al., 2013) and

its expression is negatively

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correlated with abdominal adipose deposition, circulating level of HDL and total cholesterol (X. K. Wang et al., 2012). Due to its association with obesity, LPIN1 has been proposed as

Pck1

is

enriched

for

lipid

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target gene for the treatment of metabolic diseases (Phan and Reue, 2005; Reitman, 2005). biosynthesis

related

GO-Terms

but

also

with

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Glycolysis/Gluconeogenesis, Pyruvate metabolism and PPAR signalling KEGG pathway. Pck1 is overexpressed in conditions of hyperglycemia (Valera et al., 1994) and insulin

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resistance diabetes (Sun et al., 2002; Cao et al., 2004). Pck1 silencing has a direct impact on glycaemia control and energy metabolism with down-regulation of all regulatory factors and

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enzymes involved in gluconeogenesis, and provides new horizons as a therapeutic target for the treatment of diabetes (Gómez-Valadés et al., 2008). Beyond the ClueGO enrichment analysis, it is worth mentioning the suppressor of cytokine signaling-1 (SOCS1), another significant gene down-regulated in the ORE group. SOCS1 belongs to the family of inflammatory mediators and its overexpression is linked to insulin resistance condition in humans (Rui et al., 2002; Ueki et al., 2004; Qatanani and Lazar, 2007).

ACCEPTED MANUSCRIPT Taken together, our findings reveal that the oregano aqueous extract supplementation may influence the expression of several genes involved in de novo fat synthesis and deposition, which control lipid composition and whole-body lipid redistribution. Our molecular results suggest that the effects of the oregano supplemented diet on broiler growth performance and welfare, as reported by Scocco et al. (2016) and Franciosini et al. (2016), could be primarily

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associated with an increase in lean body mass and not with abdominal and visceral fat

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accumulation.

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The effect of ORE diet in down regulating the key genes involved in insulin pathway and in lipid metabolism is of particular interest when considering that chicken is physiologically

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hyperglycaemic and insulin resistant and already an experimental model of diabetes and obesity in humans (Qatanani and Lazar, 2007; Dupont et al., 2009; Ji et al., 2012; Simon et

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al., 2012).

With this study, we underline the validity and robustness of RNA sequencing as technique of

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choice to investigate the gene expression fine tuning in nutrigenomics studies. Further analyses on other tissues (Bursa of Fabricius, muscle, spleen, and intestine) may better the

beneficial effects on performance and

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explain

immune response that oregano

supplementation appear to provide as Franciosini et al (2016) observed.

None.

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Conflicts of interest

Acknowledgements

We want to thank Mr. Gianluca Alunni for his technical support. Research sponsored by: Fondazione Cassa Risparmio Perugia 2015 - ID ROL 2677- Verini Supplizi A.: Fitoderivati, Qualità delle Carni Avicole e Benessere Animale: Approccio Nutrigenomico. References

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Abiala, M., Olayiwola, J., Babatunde, O., Aiyelaagbe, O., Akinyemi, S., 2016. Evaluation of therapeutic potentials of plant extracts against poultry bacteria threatening public health. BMC Complement. Altern. Med. 16. https://doi.org/10.1186/s12906-016-1399-z Adam, K., Sivropoulou, A., Kokkini, S., Lanaras, T., Arsenakis, M., 1998. Antifungal Activities of Origanum vulgare subsp. hirtum, Mentha spicata, Lavandula angustifolia, and Salvia fruticosa Essential Oils against Human Pathogenic Fungi. J. Agric. Food Chem. 46, 1739– 1745. https://doi.org/10.1021/jf9708296 Akbarian, A., Golian, A., Gilani, A., Kermanshahi, H., Zhaleh, S., Akhavan, A., De Smet, S., Michiels, J., 2013. Effect of feeding citrus peel extracts on growth performance, serum components, and intestinal morphology of broilers exposed to high ambient temperature during the finisher phase. Livest. Sci. 157, 490–497. https://doi.org/10.1016/j.livsci.2013.08.010 Alcicek, A., Cabuk, M.B. and M., 2004. The effect of a mixture of herbal essential oils, an organic acid or a probiotic on broiler performance 34, 217–222. Bampidis, V.A., Christodoulou, V., Florou-Paneri, P., Christaki, E., Chatzopoulou, P.S., Tsiligianni, T., Spais, A.B., 2005. Effect of dietary dried oregano leaves on growth performance, carcase characteristics and serum cholesterol of female early maturing turkeys. Br. Poult. Sci. 46, 595–601. https://doi.org/10.1080/00071660500256057 Bolger, A.M., Lohse, M., Usadel, B., 2014. Trimmomatic: a flexible trimmer for Illumina sequence data. Bioinformatics 30, 2114–2120. https://doi.org/10.1093/bioinformatics/btu170 Botsoglou, N.A., Florou-Paneri, P., Christaki, E., Fletouris, D.J., Spais, A.B., 2002. Effect of dietary oregano essential oil on performance of chickens and on iron-induced lipid oxidation of breast, thigh and abdominal fat tissues. Br. Poult. Sci. 43, 223–230. https://doi.org/10.1080/00071660120121436 Botsoglou, N.A., Florou-Paneri, P., Christaki, E., Giannenas, I., Spais, A.B., 2004. Performance of rabbits and oxidative stability of muscle tissues as affected by dietary supplementation with oregano essential oil. Arch. Anim. Nutr. 58, 209–218. https://doi.org/10.1080/00039420410001701404 Botsoglou, N.A., Grigoropoulou, S.H., Botsoglou, E., Govaris, A., Papageorgiou, G., 2003. The effects of dietary oregano essential oil and α-tocopheryl acetate on lipid oxidation in raw and cooked turkey during refrigerated storage. Meat Sci. 65, 1193–1200. https://doi.org/10.1016/S0309-1740(03)00029-9 Bourneuf, E., Hérault, F., Chicault, C., Carré, W., Assaf, S., Monnier, A., Mottier, S., Lagarrigue, S., Douaire, M., Mosser, J., Diot, C., 2006. Microarray analysis of differential gene expression in the liver of lean and fat chickens. Gene 372, 162–170. https://doi.org/10.1016/j.gene.2005.12.028 Cai, Y., Song, Z., Zhang, X., Wang, X., Jiao, H., Lin, H., 2009. Increased de novo lipogenesis in liver contributes to the augmented fat deposition in dexamethasone exposed broiler chickens (Gallus gallus domesticus). Comp. Biochem. Physiol. Part C Toxicol. Pharmacol. 150, 164–169. https://doi.org/10.1016/j.cbpc.2009.04.005 Cao, H., van der Veer, E., Ban, M.R., Hanley, A.J.G., Zinman, B., Harris, S.B., Young, T.K., Pickering, J.G., Hegele, R.A., 2004. Promoter polymorphism in PCK1 (phosphoenolpyruvate carboxykinase gene) associated with type 2 diabetes mellitus. J. Clin. Endocrinol. Metab. 89, 898–903. https://doi.org/10.1210/jc.2003-031361 Cervato, G., Carabelli, M., Gervasio, S., Cittera, A., Cazzola, R., Cestaro, B., 2000. Antioxbdant Properties of Oregano (origanum Vulgare) Leaf Extracts. J. Food Biochem. 24, 453–465. https://doi.org/10.1111/j.1745-4514.2000.tb00715.x Choi, S.-W., Friso, S., 2010. Epigenetics: A New Bridge between Nutrition and Health. Adv. Nutr. Bethesda Md 1, 8–16. https://doi.org/10.3945/an.110.1004 Claire D’Andre, H., Paul, W., Shen, X., Jia, X., Zhang, R., Sun, L., Zhang, X., 2013. Identification and characterization of genes that control fat deposition in chickens. J. Anim. Sci. Biotechnol. 4, 43. https://doi.org/10.1186/2049-1891-4-43

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Cuppett, S.L., Hall, C.A., 1998. Antioxidant activity of the Labiatae. Adv. Food Nutr. Res. 42, 245–271. Dauncey, M.J., White, P., Burton, K.A., Katsumata, M., 2001. Nutrition–hormone receptor–gene interactions: implications for development and disease. Proc. Nutr. Soc. 60, 63–72. https://doi.org/10.1079/PNS200071 Dervishi, E., Joy, M., Sanz, A., Alvarez-Rodriguez, J., Molino, F., Calvo, J.H., 2012. Forage preservation (grazing vs. hay) fed to ewes affects the fatty acid profile of milk and CPT1B gene expression in the sheep mammary gland. BMC Vet. Res. 8, 106. https://doi.org/10.1186/1746-6148-8106 Donkor, J., Sariahmetoglu, M., Dewald, J., Brindley, D.N., Reue, K., 2007. Three Mammalian Lipins Act as Phosphatidate Phosphatases with Distinct Tissue Expression Patterns. J. Biol. Chem. 282, 3450–3457. https://doi.org/10.1074/jbc.M610745200 Douaire, M., Le Fur, N., El Khadir-Mounier, C., Langlois, P., Flamant, F., Mallard, J., 1992. Identifying Genes Involved in the Variability of Genetic Fatness in the Growing Chicken. Poult. Sci. 71, 1911–1920. https://doi.org/10.3382/ps.0711911 Dridi, S., Taouis, M., Gertler, A., Decuypere, E., Buyse, J., 2007. The regulation of stearoyl-CoA desaturase gene expression is tissue specific in chickens. J. Endocrinol. 192, 229–236. https://doi.org/10.1677/JOE-06-0070 Du, E., Gan, L., Li, Z., Wang, W., Liu, D., Guo, Y., 2015. In vitro antibacterial activity of thymol and carvacrol and their effects on broiler chickens challenged with Clostridium perfringens. J. Anim. Sci. Biotechnol. 6, 58. https://doi.org/10.1186/s40104-015-0055-7 Dupont, J., Tesseraud, S., Simon, J., 2009. Insulin signaling in chicken liver and muscle. Gen. Comp. Endocrinol., 9th International Symposium on Avian EndocrinologyAvian Endocrinology9th International Symposium on Avian Endocrinology 163, 52–57. https://doi.org/10.1016/j.ygcen.2008.10.016 Emmerson, D.A., 1997. Commercial approaches to genetic selection for growth and feed conversion in domestic poultry. Poult. Sci. 76, 1121–1125. Franciosini, M.P., Casagrande-Proietti, P., Forte, C., Beghelli, D., Acuti, G., Zanichelli, D., Bosco, A. dal, Castellini, C., Trabalza-Marinucci, M., 2016. Effects of oregano (Origanum vulgare L.) and rosemary (Rosmarinus officinalis L.) aqueous extracts on broiler performance, immune function and intestinal microbial population. J. Appl. Anim. Res. 44, 474–479. https://doi.org/10.1080/09712119.2015.1091322 Ghazi, S., Amjadian, T., Norouzi, S., 2015. Single and combined effects of vitamin C and oregano essential oil in diet, on growth performance, and blood parameters of broiler chicks reared under heat stress condition. Int. J. Biometeorol. 59, 1019–1024. https://doi.org/10.1007/s00484-014-0915-4 Gómez-Valadés, A.G., Méndez-Lucas, A., Vidal-Alabró, A., Blasco, F.X., Chillon, M., Bartrons, R., Bermúdez, J., Perales, J.C., 2008. Pck1 Gene Silencing in the Liver Improves Glycemia Control, Insulin Sensitivity, and Dyslipidemia in db/db Mice. Diabetes 57, 2199–2210. https://doi.org/10.2337/db07-1087 Grzes, M., Sadkowski, S., Rzewuska, K., Szydlowski, M., Switonski, M., 2016. Pig fatness in relation to FASN and INSIG2 genes polymorphism and their transcript level. Mol. Biol. Rep. 43, 381–389. https://doi.org/10.1007/s11033-016-3969-z He, Q., Wang, S.Z., Leng, L., Na, W., Wang, Q.G., Li, H., 2014. Differentially expressed genes in the liver of lean and fat chickens. Genet. Mol. Res. GMR 13, 10823–10828. https://doi.org/10.4238/2014.December.19.3 Heinemann, F.S., Ozols, J., 2003. Stearoyl-CoA desaturase, a short-lived protein of endoplasmic reticulum with multiple control mechanisms. Prostaglandins Leukot. Essent. Fatty Acids 68, 123–133. Hillier, L.W., Miller, W., Birney, E., Warren, W., Hardison, R.C., Ponting, C.P., Bork, P., Burt, D.W., Groenen, M.A.M., Delany, M.E., Dodgson, J.B., Map, G. fingerprint, Assembly, S.A., Chinwalla, A.T., Cliften, P.F., Clifton, S.W., Delehaunty, K.D., Fronick, C., Fulton, R.S., Graves, T.A.,

ACCEPTED MANUSCRIPT

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Kremitzki, C., Layman, D., Magrini, V., McPherson, J.D., Miner, T.L., Minx, P., Nash, W.E., Nhan, M.N., Nelson, J.O., Oddy, L.G., Pohl, C.S., Randall-Maher, J., Smith, S.M., Wallis, J.W., Yang, S.-P., Mapping, Romanov, M.N., Rondelli, C.M., Paton, B., Smith, J., Morrice, D., Daniels, L., Tempest, H.G., Robertson, L., Masabanda, J.S., Griffin, D.K., Vignal, A., Fillon, V., Jacobbson, L., Kerje, S., Andersson, L., Crooijmans, R.P.M., Aerts, J., Poel, J.J. van der, Ellegren, H., Sequencing, cDNA, Caldwell, R.B., Hubbard, S.J., Grafham, D.V., Kierzek, A.M., McLaren, S.R., Overton, I.M., Arakawa, H., Beattie, K.J., Bezzubov, Y., Boardman, P.E., Bonfield, J.K., Croning, M.D.R., Davies, R.M., Francis, M.D., Humphray, S.J., Scott, C.E., Taylor, R.G., Tickle, C., Brown, W.R.A., Rogers, J., Buerstedde, J.-M., Wilson, S.A., Libraries, O. sequencing and, Stubbs, L., Ovcharenko, I., Gordon, L., Lucas, S., Miller, M.M., Inoko, H., Shiina, T., Kaufman, J., Salomonsen, J., Skjoedt, K., Wong, G.K.-S., Wang, J., Liu, B., Wang, J., Yu, J., Yang, H., Nefedov, M., Koriabine, M., deJong, P.J., Annotation, A. and, Goodstadt, L., Webber, C., Dickens, N.J., Letunic, I., Suyama, M., Torrents, D., Mering, C. von, Zdobnov, E.M., Makova, K., Nekrutenko, A., Elnitski, L., Eswara, P., King, D.C., Yang, S., Tyekucheva, S., Radakrishnan, A., Harris, R.S., Chiaromonte, F., Taylor, J., He, J., Rijnkels, M., Griffiths-Jones, S., Ureta-Vidal, A., Hoffman, M.M., Severin, J., Searle, S.M.J., Law, A.S., Speed, D., Waddington, D., Cheng, Z., Tuzun, E., Eichler, E., Bao, Z., Flicek, P., Shteynberg, D.D., Brent, M.R., Bye, J.M., Huckle, E.J., Chatterji, S., Dewey, C., Pachter, L., Kouranov, A., Mourelatos, Z., Hatzigeorgiou, A.G., Paterson, A.H., Ivarie, R., Brandstrom, M., Axelsson, E., Backstrom, N., Berlin, S., Webster, M.T., Pourquie, O., Reymond, A., Ucla, C., Antonarakis, S.E., Long, M., Emerson, J.J., Betrán, E., Dupanloup, I., Kaessmann, H., Hinrichs, A.S., Bejerano, G., Furey, T.S., Harte, R.A., Raney, B., Siepel, A., Kent, W.J., Haussler, D., Eyras, E., Castelo, R., Abril, J.F., Castellano, S., Camara, F., Parra, G., Guigo, R., Bourque, G., Tesler, G., Pevzner, P.A., Smit, A., Management, P., Fulton, L.A., Mardis, E.R., Wilson, R.K., 2004. Sequence and comparative analysis of the chicken genome provide unique perspectives on vertebrate evolution. Nature 432, 695–716. https://doi.org/10.1038/nature03154 Jamroz, D., Wertelecki, T., Houszka, M., Kamel, C., 2006. Influence of diet type on the inclusion of plant origin active substances on morphological and histochemical characteristics of the stomach and jejunum walls in chicken. J. Anim. Physiol. Anim. Nutr. 90, 255–268. https://doi.org/10.1111/j.1439-0396.2005.00603.x Ji, B., Ernest, B., Gooding, J.R., Das, S., Saxton, A.M., Simon, J., Dupont, J., Métayer-Coustard, S., Campagna, S.R., Voy, B.H., 2012. Transcriptomic and metabolomic profiling of chicken adipose tissue in response to insulin neutralization and fasting. BMC Genomics 13, 441. https://doi.org/10.1186/1471-2164-13-441 Kalani, A., Kamat, P.K., Kalani, K., Tyagi, N., 2015. Epigenetic impact of curcumin on stro ke prevention. Metab. Brain Dis. 30, 427–435. https://doi.org/10.1007/s11011-014-9537-0 Kalemba, D., Kunicka, A., 2003. Antibacterial and antifungal properties of essential oils. Curr. Med. Chem. 10, 813–829. Kaput, J., Rodriguez, R.L., 2004. Nutritional genomics: the next frontier in the postgenomic era. Physiol. Genomics 16, 166–177. https://doi.org/10.1152/physiolgenomics.00107.2003 Karpouhtsis, I., Pardali, E., Feggou, E., Kokkini, S., Scouras, Z.G., Mavragani-Tsipidou, P., 1998. Insecticidal and Genotoxic Activities of Oregano Essential Oils. J. Agric. Food Chem. 46, 1111– 1115. https://doi.org/10.1021/jf970822o Kelly, C., Gundogdu, O., Pircalabioru, G., Cean, A., Scates, P., Linton, M., Pinkerton, L., Magowan, E., Stef, L., Simiz, E., Pet, I., Stewart, S., Stabler, R., Wren, B., Dorrell, N., Corcionivoschi, N., 2017. The In Vitro and In Vivo Effect of Carvacrol in Preventing Campylobacter Infection, Colonization and in Improving Productivity of Chicken Broilers. Foodborne Pathog. Dis. 14, 341–349. https://doi.org/10.1089/fpd.2016.2265 Klanicova, B., Slana, I., Vondruskova, H., Kaevska, M., Pavlik, I., 2011. Real-time quantitative PCR detection of Mycobacterium avium subspecies in meat products. J. Food Prot. 74, 636–640. https://doi.org/10.4315/0362-028X.JFP-10-332

ACCEPTED MANUSCRIPT

AC C

EP T

ED

MA

NU

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RI

PT

K.-W. Lee, H. Everts ., A.C. Beynen ., 2004. Essential Oils in Broiler Nutrition. Int. J. Poult. Sci. 3, 738– 752. https://doi.org/10.3923/ijps.2004.738.752 Lambert, R.J., Skandamis, P.N., Coote, P.J., Nychas, G.J., 2001. A study of the minimum inhibitory concentration and mode of action of oregano essential oil, thymol and carvacrol. J. Appl. Microbiol. 91, 453–462. Lee, S.H., Lillehoj, H.S., Hong, Y.H., Jang, S.I., Lillehoj, E.P., Ionescu, C., Mazuranok, L., Bravo, D., 2010. In vitro effects of plant and mushroom extracts on immunological function of chicken lymphocytes and macrophages. Br. Poult. Sci. 51, 213–221. https://doi.org/10.1080/00071661003745844 Legrand, P., Hermier, D., 1992. Hepatic delta 9 desaturation and plasma VLDL level in genetically lean and fat chickens. Int. J. Obes. Relat. Metab. Disord. J. Int. Assoc. Study Obes. 16, 289–294. Legrand, P., Mallard, J., Bernard-Griffiths, M.A., Douaire, M., Lemarchal, P., 1987. Hepatic lipogenesis in genetically lean and fat chickens. In vitro studies. Comp. Biochem. Physiol. B 87, 789–792. https://doi.org/10.1016/0305-0491(87)90389-0 Liao, Y., Smyth, G.K., Shi, W., 2014. featureCounts: an efficient general purpose program for assigning sequence reads to genomic features. Bioinforma. Oxf. Engl. 30, 923–930. https://doi.org/10.1093/bioinformatics/btt656 Lillehoj, H.S., Kim, D.K., Bravo, D.M., Lee, S.H., 2011. Effects of dietary plant-derived phytonutrients on the genome-wide profiles and coccidiosis resistance in the broiler chickens. BMC Proc. 5 Suppl 4, S34. https://doi.org/10.1186/1753-6561-5-S4-S34 Mathlouthi, N., Bouzaienne, T., Oueslati, I., Recoquillay, F., Hamdi, M., Urdaci, M., Bergaoui, R., 2012. Use of rosemary, oregano, and a commercial blend of essential oils in broiler chickens: in vitro antimicrobial activities and effects on growth performance. J. Anim. Sci. 90, 813–823. https://doi.org/10.2527/jas.2010-3646 Miyazaki, M., Ntambi, J.M., 2003. Role of stearoyl-coenzyme A desaturase in lipid metabolism. Prostaglandins Leukot. Essent. Fatty Acids 68, 113–121. Mortazavi, A., Williams, B.A., McCue, K., Schaeffer, L., Wold, B., 2008. Mapping and quantifying mammalian transcriptomes by RNA-Seq. Nat. Methods 5, 621–628. https://doi.org/10.1038/nmeth.1226 Moulos, P., Hatzis, P., 2015. Systematic integration of RNA-Seq statistical algorithms for accurate detection of differential gene expression patterns. Nucleic Acids Res. 43, e25. https://doi.org/10.1093/nar/gku1273 Nagalakshmi, U., Wang, Z., Waern, K., Shou, C., Raha, D., Gerstein, M., Snyder, M., 2008. The transcriptional landscape of the yeast genome defined by RNA sequencing. Science 320, 1344–1349. https://doi.org/10.1126/science.1158441 O’Hea, E.K., Leveille, G.A., 1968. Lipogenesis in isolated adipose tissue of the domestic chick (Gallus domesticus). Comp. Biochem. Physiol. 26, 111–120. https://doi.org/10.1016/0010406X(68)90317-4 Ozsolak, F., Milos, P.M., 2011. RNA sequencing: advances, challenges and opportunities. Nat. Rev. Genet. 12, 87–98. https://doi.org/10.1038/nrg2934 Phan, J., Péterfy, M., Reue, K., 2004. Lipin Expression Preceding Peroxisome Proliferator-activated Receptor-γ Is Critical for Adipogenesis in Vivo and in Vitro. J. Biol. Chem. 279, 29558–29564. https://doi.org/10.1074/jbc.M403506200 Phan, J., Reue, K., 2005. Lipin, a lipodystrophy and obesity gene. Cell Metab. 1, 73–83. https://doi.org/10.1016/j.cmet.2004.12.002 Qatanani, M., Lazar, M.A., 2007. Mechanisms of obesity-associated insulin resistance: many choices on the menu. Genes Dev. 21, 1443–1455. https://doi.org/10.1101/gad.1550907 Quinteiro-Filho, W.M., Gomes, A.V.S., Pinheiro, M.L., Ribeiro, A., Ferraz-de-Paula, V., Astolfi-Ferreira, C.S., Ferreira, A.J.P., Palermo-Neto, J., 2012. Heat stress impairs performance and induces intestinal inflammation in broiler chickens infected with Salmonella Enteritidis. Avian Pathol. J. WVPA 41, 421–427. https://doi.org/10.1080/03079457.2012.709315

ACCEPTED MANUSCRIPT

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Recoules, E., Sabboh-Jourdan, H., Narcy, A., Lessire, M., Harichaux, G., Labas, V., Duclos, M.J., Réhault-Godbert, S., 2017. Exploring the in vivo digestion of plant proteins in broiler chickens. Poult. Sci. 96, 1735–1747. https://doi.org/10.3382/ps/pew444 Reitman, M.L., 2005. The fat and thin of lipin. Cell Metab. 1, 5–6. https://doi.org/10.1016/j.cmet.2004.12.005 Resnyk, C.W., Carré, W., Wang, X., Porter, T.E., Simon, J., Le Bihan-Duval, E., Duclos, M.J., Aggrey, S.E., Cogburn, L.A., 2013. Transcriptional analysis of abdominal fat in genetically fat and lean chickens reveals adipokines, lipogenic genes and a link between hemostasis and leanness. BMC Genomics 14, 557. https://doi.org/10.1186/1471-2164-14-557 Resnyk, C.W., Chen, C., Huang, H., Wu, C.H., Simon, J., Le Bihan-Duval, E., Duclos, M.J., Cogburn, L.A., 2015. RNA-Seq Analysis of Abdominal Fat in Genetically Fat and Lean Chickens Highlights a Divergence in Expression of Genes Controlling Adiposity, Hemostasis, and Lipid Metabolism. PloS One 10, e0139549. https://doi.org/10.1371/journal.pone.0139549 Richards, M.P., Poch, S.M., Coon, C.N., Rosebrough, R.W., Ashwell, C.M., McMu rtry, J.P., 2003. Feed restriction significantly alters lipogenic gene expression in broiler breeder chickens. J. Nutr. 133, 707–715. Rui, L., Yuan, M., Frantz, D., Shoelson, S., White, M.F., 2002. SOCS-1 and SOCS-3 Block Insulin Signaling by Ubiquitin-mediated Degradation of IRS1 and IRS2. J. Biol. Chem. 277, 42394– 42398. https://doi.org/10.1074/jbc.C200444200 Scocco, P., Forte, C., Franciosini, M.P., Mercati, F., Casagrande-Proietti, P., Dall’Aglio, C., Acuti, G., Tardella, F.M., Trabalza-Marinucci, M., 2016. Gut complex carbohydrates and intestinal microflora in broiler chickens fed with oregano (Origanum vulgare L.) aqueous extract and vitamin E. J. Anim. Physiol. Anim. Nutr. https://doi.org/10.1111/jpn.12588 Setti L., Zanichelli D., 2009. Bioliquefaction as a bio-refinery’s approach for the production of natural bioactive compounds for functional cosmetics., in: Waste Recovery: Strategies, Techniques and Applications in Europe. Morselli L., Passarini F., Vassura I., Italy, Milano, pp. 122–128. Shu, G., Liao, W.Y., Feng, J.Y., Yu, K.F., Zhai, Y.F., Wang, S.B., Khondowe, P., Wang, X.Q., Jiang, Q.Y., 2011. Active immunization of fatty acid translocase specifically decreased visceral fat deposition in male broilers. Poult. Sci. 90, 2557–2564. https://doi.org/10.3382/ps.201001238 Simon, J., Milenkovic, D., Godet, E., Cabau, C., Collin, A., Métayer-Coustard, S., Rideau, N., Tesseraud, S., Derouet, M., Crochet, S., Cailleau-Audouin, E., Hennequet-Antier, C., Gespach, C., Porter, T.E., Duclos, M.J., Dupont, J., Cogburn, L.A., 2012. Insulin immuno-neutralization in fed chickens: effects on liver and muscle transcriptome. Physiol. Genomics 44, 283–292. https://doi.org/10.1152/physiolgenomics.00057.2011 Sun, Y., Liu, S., Ferguson, S., Wang, L., Klepcyk, P., Yun, J.S., Friedman, J.E., 2002. Phosphoenolpyruvate carboxykinase over-expression selectively attenuates insulin signaling and hepatic insulin sensitivity in transgenic mice. J. Biol. Chem. https://doi.org/10.1074/jbc.M200964200 Teixeira, B., Marques, A., Ramos, C., Serrano, C., Matos, O., Neng, N.R., Nogueira, J.M.F., Saraiva, J.A., Nunes, M.L., 2013. Chemical composition and bioactivity of different oregano (Origanum vulgare) extracts and essential oil. J. Sci. Food Agric. 93, 2707–2714. https://doi.org/10.1002/jsfa.6089 Trapnell, C., Roberts, A., Goff, L., Pertea, G., Kim, D., Kelley, D.R., Pimentel, H., Salzberg, S.L., Rinn, J.L., Pachter, L., 2012. Differential gene and transcript expression analysis of RNA -seq experiments with TopHat and Cufflinks. Nat. Protoc. 7, 562–578. https://doi.org/10.1038/nprot.2012.016 Ueki, K., Kondo, T., Kahn, C.R., 2004. Suppressor of cytokine signaling 1 (SOCS-1) and SOCS-3 cause insulin resistance through inhibition of tyrosine phosphorylation of insulin receptor substrate proteins by discrete mechanisms. Mol. Cell. Biol. 24, 5434–5446. https://doi.org/10.1128/MCB.24.12.5434-5446.2004

ACCEPTED MANUSCRIPT

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Valera, A., Pujol, A., Pelegrin, M., Bosch, F., 1994. Transgenic mice overexpressing phosphoenolpyruvate carboxykinase develop non-insulin-dependent diabetes mellitus. Proc. Natl. Acad. Sci. U. S. A. 91, 9151–9154. Voljc, M., Frankic, T., Levart, A., Nemec, M., Salobir, J., 2011. Evaluation of different vitamin E recommendations and bioactivity of α-tocopherol isomers in broiler nutrition by measuring oxidative stress in vivo and the oxidative stability of meat. Poult. Sci. 90, 1478–1488. https://doi.org/10.3382/ps.2010-01223 Wang, L., Wang, S., Li, W., 2012. RSeQC: quality control of RNA-seq experiments. Bioinformatics 28, 2184–2185. https://doi.org/10.1093/bioinformatics/bts356 Wang, S.Z., Hu, X.X., Wang, Z.P., Li, X.C., Wang, Q.G., Wang, Y.X., Tang, Z.Q., Li, H., 2012. Quantitative trait loci associated with body weight and abdominal fat traits on chicken chromosomes 3, 5 and 7. Genet. Mol. Res. GMR 11, 956–965. https://doi.org/10.4238/2012.April.19.1 Wang, X.K., Chen, W., Huang, Y.Q., Kang, X.T., Wang, J.P., Li, G.X., Jiang, R.R., 2012. Identification of the transcript isoforms and expression characteristics for chicken Lpin1. Anim. Int. J. Anim. Biosci. 6, 1897–1903. https://doi.org/10.1017/S1751731112001358 Yabe, D., Brown, M.S., Goldstein, J.L., 2002. Insig-2, a second endoplasmic reticulum protein that binds SCAP and blocks export of sterol regulatory element-binding proteins. Proc. Natl. Acad. Sci. 99, 12753–12758. https://doi.org/10.1073/pnas.162488899 Zhao, S., Ma, H., Zou, S., Chen, W., Zhao, R., 2007. Hepatic Lipogenesis in Broiler Chickens with Different Fat Deposition during Embryonic Development. J. Vet. Med. Ser. A 54, 1–6. https://doi.org/10.1111/j.1439-0442.2007.00898.x Zhou, H., Deeb, N., Evock-Clover, C.M., Ashwell, C.M., Lamont, S.J., 2006. Genome-wide linkage analysis to identify chromosomal regions affecting phenotypic traits in the chicken. II. Body composition. Poult. Sci. 85, 1712–1721.

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Figure 1. Volcano plot of the differentially expressed genes. In green are represented genes

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with absolute logFC >1 and FDR < 0.05.

ACCEPTED MANUSCRIPT Table 1. Ingredient and chemical composition of the basal control diet§

Ingredients (kg/100 kg) Maize Wheat middlings Corn gluten Soybean meal Extruded soybean Soybean oil Calcium carbonate Dicalcium phosphate Sodium chloride Vitamin and mineral premix1 Lysine Methionine Fatty acid supplement2

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55.00 4.84 1.00 32.00 -2.00 1.00 1.50 0.35 0.50 0.15 0.20 0.16

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Nutrient composition (g/kg) Analyzed Moisture Crude protein Crude fat Crude fibre Ash Total calcium Total phosphorus Calculated Lysine Methionine ME (Mcal/Kg)

Grower - Finisher

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Starter

60.00 5.39 1.15 25.00 3.00 1.50 0.50 1.25 0.30 0.50 0.10 0.20 0.16

126.6 207.2 57.9 29.6 54.1 8.47 6.70

128.1 189.4 59.1 30.1 44.6 6.84 6.13

11.9 5.17 3.04

10.4 4.94 3.10

§

In the oregano supplemented diets, 0.2% of oregano aqueous extract was substituted for 0.2% wheat middlings.

1

Supplied per kilogram of diet: vitamin A, 12,500 I.U. (retinol); vitamin D3, 3,000 I.U.; vitamin E, 50 mg (tocopheryl acetate); vitamin K3, 2 mg; thiamine, 2 mg; riboflavin, 4 mg; pyridoxine, 1 mg; cyanocobalamin, 0.015 mg; pantothenic acid 15 mg; folic acid, 50 mg; biotin, 10 mg; choline chloride, 60; iodine, 3 mg; selenium, 20 mg; iron, 3 mg; manganese, 12, mg; copper, 1,5 mg; zinc, 5 mg.

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Supplied per kilogram of diet: C18:2 9c,11t, 2.5 g; C18:2 10t, 12c, 2.5 g; C14:0, 0.16 g; C16:0, 0.45 g; C20:3, 0.02 g; C20:5, 0.02 g; C22:6. 0.63 g; and others, 0.36 g.

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Table 2. Sequencing libraries details

22.170.774 12.470.628 7.681.080 13.816.924 18.558.314 12.133.502 27.382.030 30.526.472 22.203.676

98,60

27.586.576 26.765.846 19.761.728 21.219.202 32.057.234

98,67 98,64 98,61 98,49

98,69 98,63 98,71 98,69 98,69 98,70 98,64 97,34 98,62 98,67

% on Aligned 98,20

91,90

9.925.787

98,78

91,30

18.262.011

98,64

91,17

25.255.826

98,52

PT

13.622.97 4 18.315.64 2 11.966.67 2 27.028.42 4 30.127.59 0 21.912.58 6 27.227.86 8 26.401.75 8 19.235.40 2 20.926.73 8 31.630.92 4

98,64

Unique alignments 10.494.640

RI

19.028.566

98,70

% on Trimmed 91,00

91,07

18.133.075

98,54

90,74

16.830.079

98,79

90,77

19.493.925

98,20

90,88

10.886.800

97,41

90,96

6.789.740

98,67

90,60

12.183.795

98,71

91,65

16.555.363

98,63

91,31

10.782.015

98,67

91,17

24.320.817

98,70

91,73

27.273.304

98,68

91,46

19.742.464

98,51

91,53

24.397.646

97,90

91,11

23.255.340

96,68

91,89

17.433.974

98,63

91,46

18.871.506

98,59

90,93

28.349.994

98,57

SC

20.484.776

98,73

NU

28.487.544

98,69

Aligned reads 10.687.5 10 10.048.4 82 18.514.0 82 25.635.6 94 18.401.8 18 17.036.2 93 19.851.2 53 11.176.6 85 6.881.16 7 12.342.9 77 16.786.1 09 10.927.1 24 24.640.7 71 27.637.2 54 20.040.8 92 24.922.0 33 24.055.0 28 17.675.5 12 19.140.4 36 28.760.6 03

MA

20.539.120

% on RAW 98,57

ED

11.078.272

Trimmed reads 11.744.92 4 10.933.63 6 20.278.71 0 28.117.27 2 20.206.22 6 18.775.84 2 21.868.71 6 12.297.75 6 7.564.936

EP T

RAW reads (R1+R2) 11.915.822

AC C

Sam ple CTR L1 CTR L2 CTR L3 CTR L5 CTR L6 CTR L9 CTR L10 CTR L11 CTR L12 CTR L14 ORE 1 ORE 2 ORE 4 ORE 8 ORE 10 ORE 11 ORE 12 ORE 13 ORE 14 ORE 15

ACCEPTED MANUSCRIPT Table 3. BINGO enrichment analysis summary results according to the GoSlim ontology.

GO -ID

pvalu e

qvalu e

662 9

1,12 E+00

lipid 1,22 metaboli E+02 c process

PT

RI

SC

RBM38|RSAD2|LAMB3|CCK|FOXP1|CIT|NR4A2|MYC L|CACNB4|FASN|GPR183|CDK1|SIK1

PANK1|GPT2|INSIG1|ASL1|CYP26A1|ALDH1A3|CYP2 6B1|GALE|CACNB4|SCD|FASN|UPP2|TK1|PCK1|LPIN1

NU

1,36 E+01

small 4,93 molecule E+02 metaboli c process

NLGN3|COL18A1|LTK|LAMC3|LAMA1|RBPJ|PCSK4|U BE2J1|SOCS1|CCKAR|MFSD2A|WNT4|

ED

MA

cell 3,32 differenti E+02 ation

ACSS2|INSIG1|NEU2|CYP26A1|ALDH1A3|CYP26B1|S CD|FASN|LIPG|PCK1|LPIN1|FDFT1|WNT4

EP T

442 81

6,09 E+00

AC C

301 54

Descripti Genes in test set on

ACCEPTED MANUSCRIPT Table 4. Significantly enriched KEGG pathways obtained via ClueGO.

KEGG pathway

FDR

Nr. Genes

Associated Genes Found

9,2E-3

% Associated Genes 5,56

KEGG:0000010 KEGG:0000620

Glycolysis / Gluconeogenesis Pyruvate metabolism

3,00

2,9E-3

9,09

3,00

[ACSS2, ALDH1A3, PCK1] [ACAT2, ACSS2, PCK1]

KEGG:0003320

PPAR signaling pathway

2,2E-3

6,67

4,00

[ANGPTL4, MMP1, PCK1, SCD]

AC C

EP T

ED

MA

NU

SC

RI

PT

ID

ACCEPTED MANUSCRIPT Table 5. Significantly enriched GO Terms for the three vocabularies obtained via ClueGO.

ID

GO Term

FDR

% Associated Genes

Nr. Genes

GO:0001523

retinoid metabolic process

2,0E-3

12,00

3,00

2,5E-3

6,15

4,00

1,6E-3

8,51

4,00

2,0E-3

8,70

4,00

1,7E-3

10,00

4,00

7,3E-3

6,38

2,2E-3

10,71

2,4E-3

10,00

3,00

[RBM38, SIK1, WNT4]

16,0E3

4,17

3,00

[RBM38, SIK1, WNT4]

GO:0010830 GO:0014902 GO:0016101 GO:0019432 GO:0021536 GO:0021983 GO:0034754 GO:0038127 GO:0042035 GO:0042089 GO:0042107 GO:0042445 GO:0042573 GO:0044242 GO:0045833 GO:0046165

myotube differentiation diterpenoid metabolic process triglyceride biosynthetic process diencephalon development pituitary gland development cellular hormone metabolic process

ERBB signaling pathway regulation of cytokine biosynthetic process cytokine biosynthetic process cytokine metabolic process hormone metabolic process retinoic acid metabolic process cellular lipid catabolic process negative regulation of lipid metabolic process alcohol biosynthetic process

[ALDH1A3, CYP26A1, CYP26B1] [FASN, INSIG1, LOC101750564, SCD]

PT

[INSIG1, LPIN1, PCK1, SIK1] [INSIG1, LPIN1, PCK1, SIK1]

RI

SC

GO:0006721

NU

GO:0006720

MA

GO:0006641

3,00 3,00

[INSIG1, LPIN1, PCK1, SIK1] [ALDH1A3, CYP26A1, CYP26B1] [ALDH1A3, CYP26A1, CYP26B1]

2,1E-3

11,54

3,00

[ALDH1A3, CYP26A1, CYP26B1]

1,7E-3

23,08

3,00

[LPIN1, PCK1, SIK1]

1,4E-3

8,16

4,00

[LOC771308, NR4A2, RBPJ, WNT4]

2,5E-3

9,68

3,00

[LOC771308, RBPJ, WNT4]

2,2E-3

8,89

4,00

[ALDH1A3, CYP26A1, CYP26B1, WNT4]

14,0E3

4,48

3,00

[AREG, EREG, RBPJ]

8,6E-3

5,77

3,00

[EREG, FOXP1, UBE2J1]

5,26

3,00

[EREG, FOXP1, UBE2J1]

5,26

3,00

[EREG, FOXP1, UBE2J1]

1,5E-3

5,88

5,00

[ALDH1A3, CYP26A1, CYP26B1, LOC771308, WNT4]

1,5E-3

30,00

3,00

7,2E-3

4,26

4,00

4,5E-3

7,69

3,00

[INSIG1, SIK1, WNT4]

17,0E3

4,00

3,00

[INSIG1, PCK1, WNT4]

ED

GO:0006639

EP T

GO:0006638

fatty acid biosynthetic process neutral lipid metabolic process acylglycerol metabolic process triglyceride metabolic process isoprenoid metabolic process terpenoid metabolic process regulation of myotube differentiation

AC C

GO:0006633

Associated Genes Found

10,0E3 10,0E3

[ALDH1A3, CYP26A1, CYP26B1] [CYP26A1, CYP26B1, LPIN1, NEU2]

ACCEPTED MANUSCRIPT

GO:0051055 GO:0051147

regulation of muscle cell differentiation

GO:0051153

regulation of striated muscle cell differentiation

GO:0060563

neuroepithelial cell differentiation

21,43

3,00

[LPIN1, PCK1, SIK1]

1,5E-3

21,43

3,00

[LPIN1, PCK1, SIK1]

16,0E3

4,23

3,00

[INSIG1, SIK1, WNT4]

2,5E-3

9,68

3,00

[INSIG1, SIK1, WNT4]

1,7E-3

6,02

5,00

[EREG, RBM38, RBPJ, SIK1, WNT4]

1,4E-3

8,33

4,00

14,0E3

4,41

3,00

monocarboxylic acid catabolic process

8,6E-3

5,77

GO:0072330

monocarboxylic acid biosynthetic process

1,3E-3

5,68

GO:1901991

negative regulation of mitotic cell cycle phase transition

16,0E3

4,23

GO:0005604

basement membrane

2,3E-3

GO:0031968

organelle outer membrane

GO:0004497

monooxygenase activity

GO:0005319

lipid transporter activity

GO:0031406

carboxylic acid binding

GO:0043177

organic acid binding

[MYCL, RBPJ, WNT4] [CYP26A1, CYP26B1, LPIN1]

5,00

[ALDH1A3, FASN, INSIG1, LOC101750564, SCD]

3,00

[CDK1, CDKN2B, RBM38]

6,45

4,00

[COL18A1, LAMA1, LAMB3, LAMC3]

4,55

3,00

[LOC771308, LPIN1, RSAD2]

4,76

3,00

[CYP26A1, CYP26B1, CYP27C1]

4,55

3,00

[MFSD2A, SLCO2A1, SLMO1]

8,6E-3

4,00

4,00

8,6E-3

4,00

4,00

MA

3,00

14,0E3 13,0E3 14,0E3

ED

EP T

AC C

[RBM38, RBPJ, SIK1, WNT4]

NU

GO:0072329

PT

GO:0046890

1,5E-3

RI

GO:0046463

neutral lipid biosynthetic process acylglycerol biosynthetic process regulation of lipid biosynthetic process negative regulation of lipid biosynthetic process

SC

GO:0046460

[CYP26A1, CYP26B1, OSBPL10, PCK1] [CYP26A1, CYP26B1, OSBPL10, PCK1]

ACCEPTED MANUSCRIPT Highlights

AC C

EP T

ED

MA

NU

SC

RI

PT

 RNA-Seq reveals that oregano modulates liver transcriptome expression;  Fat metabolism and pathways are down regulated;  Insights on the molecular basis of lean body mass and visceral fat are speculated.