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Article
Transcriptome landscape of porcine intramuscular adipocytes during differentiation Delin Mo, Kaifan Yu, Hu Chen, Luxi Chen, Xiaohong Liu, Zuyong He, Peiqing Cong, and Yaosheng Chen J. Agric. Food Chem., Just Accepted Manuscript • DOI: 10.1021/acs.jafc.7b02039 • Publication Date (Web): 04 Jul 2017 Downloaded from http://pubs.acs.org on July 9, 2017
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Journal of Agricultural and Food Chemistry
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Transcriptome
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differentiation
landscape
of
porcine
intramuscular
adipocytes
during
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Delin Mo†, Kaifan Yu†, Hu Chen, Luxi Chen, Xiaohong Liu, Zuyong He, Peiqing
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Cong, Yaosheng Chen*
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State Key Laboratory of Biocontrol, School of Life Sciences, Sun Yat-sen University,
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Guangzhou 510006, China
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*
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Road, Guangzhou Higher Education Mega Center, Guangzhou 510006, China. Tel:
Corresponding author. School of Life Sciences, Sun Yat-sen University, North Third
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+86 20 39332788; fax: +86 20 39332940. E-mail:
[email protected].
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†
Delin Mo and Kaifan Yu contributed equally to the work.
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Abstract
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Adipocyte differentiation process, controlled by a tightly regulated transcriptional
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cascade, contributes partly to determine intramuscular adipose tissue (IMAT) mass
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which is associated with meat quality in food animals, and obesity and related
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metabolic complications in human. Thus, this study aimed to characterize genes
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critical for intramuscular preadipocyte differentiation. Primary intramuscular
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preadipocytes were isolated from pigs, and mRNA profiles were performed in several
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key points (0d, 4h, 8h, 1d, 2d, 6d) during adipogenesis using microarrays. By gene
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functional analysis, we identified numerous differentially expressed genes among
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distinct stages of intramuscular preadipocyte differentiation, where numbers of
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transcription factors were observed in the early stages. We obtained 4 clusters of
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differential gene expression pattern, including crucial candidate genes associated with
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adipogenesis of intramuscular adipocytes. Further, we conducted functional
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identification confirming that POSTN and FGFR4 suppressed, whereas AKR1CL1
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increased the expression of adipogenic marker PPARγ and C/EBPα. Taken together,
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our data delineated the transcriptome landscape during porcine intramuscular
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preadipocyte differentiation, which provided a valuable resource for finding the genes
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responsible for IMAT formation.
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Keywords: Intramuscular adipocytes; Adipogenesis; Different stages in adipogenesis;
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Transcriptome
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Introduction
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Intramuscular adipose tissue (IMAT), an ectopic fat depot within muscle fibers,
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has generated great scientific interest over the past 15 to 20 years. For one thing, in
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food animals, intramuscular fat is essential for the eating quality of meat,1-2 which has
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drawn public concern because of the demand for increased meat quality. For another,
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high level of IMAT has been linked to the development of metabolic diseases
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associated with obesity, such as insulin resistance and type 2 diabetes.3-4 Importantly,
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adipocyte differentiation is one of the important processes determining adipose tissue
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mass,5 which triggers elevations in fat content. Thus, understanding the molecular
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events that regulate intramuscular preadipocyte differentiation is necessary to improve
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meat quality in livestock, and prevent human obesity and metabolic diseases.
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The process of adipocyte differentiation occurs in several stages including
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growth-arrested preadipocytes, mitotic clonal expansion, terminal differentiation, and
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mature adipocytes.6 This conversion of preadipocytes to mature adipocytes is
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controlled by a cascade of transcription factors, among which peroxisome
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proliferator-activated receptor γ (PPARγ) and CCAAT/enhancer-binding protein α
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(C/EBPα) are considered as the key adipogenic factors. They function together as
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pleiotropic transcriptional activators of multiple adipocyte-specific genes, such as
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fatty acid binding protein 4 (FABP4), lipoprotein lipase (LPL), fatty acid translocase
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(CD36), and perilipin, which produce the adipocyte phenotype.7-9 Before the
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induction of PPARγ and C/EBPα, there is another wave of transcription factors
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driving the adipogenic program, which comprise CCAAT/enhancer-binding protein β
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(C/EBPβ), C/EBPδ, Krüppel-like factors (KLFs), fibroblast growth factors (FGFs),
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and other early adipogenic factors.10-11
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The molecular mechanisms of adipocyte differentiation have been extensively
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studied using cellular in vitro models, such as 3T3-L1 and 3T3-F442A cell lines.
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However, adipogenesis in these cell lines have not always reflected that of other
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primary preadipocytes. Especially, preadipocytes in distinct fat depots differ in gene
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expression programs and physiologic properties.12-14 The molecular regulatory
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mechanisms underlying specific intramuscular preadipocyte differentiation remain
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unclear. Previous studies have compared gene expression patterns in undifferentiated
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and differentiated intramuscular adipocytes.14-15 Nevertheless, preadipocyte undergo
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dramatic morphological changes with the complex transcriptional regulation in
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different stages in adipogenesis, and the formation of adipocytes determined
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significantly in the early stages.
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Here, we established intramuscular preadipocytes from pigs, and performed
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transcriptional comparisons among several points (0d, 4h, 8h, 1d, 2d, 6d) of
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intramuscular preadipocyte differentiation using microarrays. Functional analysis
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depicted a transcriptome landscape of intramuscular preadipocyte differentiation,
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among which transcription factors were required in early stages of adipogenesis. We
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also obtained 4 clusters of differential gene expression pattern using Short Time-series
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Expression Miner (STEM) analysis, which involve multiple candidate genes
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associated with the differentiation of intramuscular adipocytes. Furthermore, we chose
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periostin (POSTN), aldo-keto reductase family 1, member C-like 1 (AKR1CL1) and
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fibroblast growth factor receptor 4 (FGFR4) as the candidate genes, and confirmed
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that POSTN and FGFR4 down-regulated while AKR1CL1 up-regulated PPARγ and
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C/EBPα mRNA levels, suggesting a crucial role during adipogenesis.
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Material and Methods
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Primary preadipocytes isolation and induction of differentiation
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The animal experiments were performed in accordance with the guidelines of the
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Institutional Animal Care and Use Committee of Sun Yat-sen University. Longissimus
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dorsi (LD) muscle tissue for cell isolation was collected from three seven-day-old
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postnatal male pigs of Landrace. Primary intramuscular preadipocytes were isolated
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using a collagenase digestion procedure modified from previous report.16 Cells were
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maintained in Dulbecco’s Modified Eagle’s Medium/Nutrient Mixture F-12 Ham
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(DMEM/F12) supplemented with 10% fetal bovine serum. For differentiation, upon
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reaching confluence, cells were exposed to adipogenic medium consisting of base
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medium supplemented with 50 nM insulin, 50 nM dexamethasone, 50 µM oleate and
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0.5 mM octanoate (Sigma Aldrich, St Louis, MO, USA) for 7 days.14
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Microarray assay
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Total RNA was extracted from cell samples (0 h, 4 h, 8 h, 1 d, 2 d and 6 d of
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differentiation) of three independent biological replicates in each time point using
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TRIzol reagent (Invitrogen, Carlsbad, CA, USA) following the manufacturer’s
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protocols. The concentration and integrity of RNA was assessed with NanoDrop
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ND-1000 spectrophotometer (Nano-Drop Technologies, Wilmington, DE, USA) and
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denatured for agarose gel electrophoresis. After purification, the RNA was amplified
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and transcribed into fluorescent cRNA using a Low Input Quick Amp Labeling Kit
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(Agilent Technologies, Santa Clara, CA, USA). The labeled cRNAs were then
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hybridized onto Agilent Porcine 4 × 44 K one-color gene expression microarrays at
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65 °C for 17 h. Array images were collected using an Agilent Microarray Scanner.
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Data were analyzed using Agilent Feature Extraction software. Quantile normalization
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and subsequent data processing were performed using the GeneSpring GX v11.5.1
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software package. Differentially expressed genes (DEGs) were identified through
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Fold Change filtering (Fold Change >= 2.0). The microarray assay was conducted by
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KangChen Bio-tech (Shanghai, China).
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Gene ontology, pathway, and STRING analysis
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Gene enrichment in gene ontology (GO) biological processes was performed
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with the DAVID Bioinformatics Resources v6.7 (http://david.abcc.ncifcrf.gov/).
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Kyoto Encyclopedia of Genes and Genomes (KEGG), the major public
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pathway-related database, was used to conduct pathway enrichment analysis. The
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p-value (Fisher-P value) denotes the significance of GO terms and pathway
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enrichment in the DEGs. Lower the p-value, more significant is the GO term or
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Pathway (p-value
