Integrative analysis of circRNAs, miRNAs and mRNAs profiles reveal that ceRNAs networks in chicken intramuscular and abdominal adipogenesis

doi:10.21203/rs.3.rs-20642/v1

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Research article

Integrative analysis of circRNAs, miRNAs and mRNAs profiles reveal that ceRNAs networks in chicken intramuscular and abdominal adipogenesis

https://doi.org/10.21203/rs.3.rs-20642/v1

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published 26 Aug, 2020

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Background

Tissue-specific fat deposition is regulated by a series of complex regulation mechanisms. Epigenetic regulations, such as circular RNAs (circRNAs), have been proved to be the crucial regulator of diseases, development, metabolism and adipogenesis. To investigate the functional roles of circRNAs in adipogenesis and tissue-specific fat deposition, we comprehensively analyzed the Ribo-Zero RNA-Seq and miRNAs data during chicken abdominal and intramuscular adipogenic differentiation.

Results

Here, we first reported circRNAs and miRNAs profiles during chicken adipogenic differentiation in adipocytes-derived from various adipose tissues. Large amounts of downregulated miRNAs might promote adipogenesis through activating their target genes which were related to fatty metabolism and adipogenic differentiation. Furthermore, we identified several candidate circRNAs by the correlation analysis between the expression levels of circRNAs and adipogenic genes, tissues as well as the dynamic expression patterns of circRNAs during adipogenic differentiation. Moreover, we constructed competing endogenous RNA (ceRNAs) networks during chicken intramuscular and abdominal adipogenesis through combining with miRNAs and mRNAs data. Several candidate circRNAs might affect adipogenesis by regulating miRNAs through PPAR and fatty acid metabolism related pathways, such as circLCLAT1, circFNDC3AL, circCLEC19A and circARMH1.

Conclusion

Over all, our result indicated that some tissue- or cell-specific circRNAs and miRNAs may have notable effects on chicken adipogenesis and tissue-specific fat deposition.

Epigenetics & Genomics

Chicken

CircRNAs

CeRNA

Intramuscular fat

Abdominal fat

Adipogenic differentiation

Different resource and organizational microenvironment contribute to various physiological and biochemical characteristics of adipose tissues [1–3]. As preadipocytes derived from various tissues exhibit different proliferation speed and adipogenic potential, it is believed that transcriptional and post-transcriptional regulation mechanisms result in stage- and tissue-specific fat deposition in animals [4–6].

Increasing number of studies have shown that non-coding RNAs play functional roles in various normal and pathological processes, such as microRNAs (miRNAs) [7–10] and long non-coding RNAs (lncRNAs) [11–13]. Although miRNAs and lncRNAs have been widely studied in adipogenesis recently, the functional roles of other classes of non-coding RNAs are still poorly understood, such as circular RNAs (circRNAs). CircRNAs are a class of non-coding RNAs generated by alternative splicing with weak protein-coding potential [14, 15]. Increasing evidences have indicated that circRNAs play functional roles in various biological processes, such as tummor [16–18], animal development [19, 20] and cell differentiation [21, 22]. CircHECTD1 promotes gastric cancer progression by targeting miR-1256 through activation of the β-catenin/c-Myc pathway [23]. Circ-ZNF609 regulates myogenesis by translating to a functional peptide in human and mouse [24]. CircArhgap5-2 plays a crucial role in adipogenesis and obesity [25]. However, studies of circRNAs related to poultry adipogenesis and tissues-specific fat deposition remain unknown.

In this study, we first provided comprehensive circRNAs atlas during chicken adipogenic differentiation across various tissues-derived preadipocytes. We identified differentiated expressed (DE) circRNAs, miRNAs and their dynamic expression patterns during adipocytes differentiation. Moreover, we integrated the circRNAs and RNA-Seq data and constructed a circRNAs-miRNAs-mRNAs ceRNA network involved in chicken adipogenesis. Our study may contribute to a better understanding of epigenetic regulation mechanisms underlying adipogenesis and tissues-specific fat deposition in birds.

Overview of circRNAs data of Ribo-Zero RNA-Seq in chicken preadipocytes and adipocytes

In the present study, a total of 960 million raw paired-end (PE) reads generated by Ribo-Zero RNA-Seq data were analyzed. After fliting with low-quality reads, we finally got 910 million clean reads. The 88%-94% unique mapping clean reads were mapped to the chicken genome 5 (galGal5) (Table 1). CircRNAs distributed in the majority of chromosomes of chicken genome. To better understand the cirRNAs in chicken adipocytes, we identified and analyzed the expression levels of circRNAs in different adipose tissues-derived adipocytes. As shown in Fig. 1A, intramuscular preadipocytes (IM_Pre) and adipocytes (IM_Ad), abdominal preadipocytes (Ab_Pre) and adipocytes (Ab_Ad) were derived into two clusters, suggesting that the differences between intramuscular and abdominal fat might higher than that between preadipocytes and adipocytes. Moreover, the results of Pearson correlation coefficient (r = 0.86 ~ 0.93) suggested that cell samples within groups have good consistency. The bar plot showed that no obvious difference of global expression levels of circRNAs across different groups (Fig. 1B). To classify the length distribution of circRNAs, we compared the resource of all circRNAs in different gene regions, including exon, intergenic and intron regions. In the present study, we finally identified 787, 710, 980, 1083, 1406, 1426, 1447 and 1004 circRNAs in eight groups (Fig. 1C). Our results showed that the majority of circRNAs (65%) generated from exon regions, followed with intergenic regions (27%) (Fig. 1D) and intron regions (8%). Moreover, our results suggested that most of the intersect circRNAs shared with different software were 200–1000 nt in length (Fig. 1E). The circRNAs distributed across 31 chromosomes (chromosomes 1–28, 33, Z and W) of chicken (Fig. 2). Most circRNAs distributed in chicken chromosome 1, 2, 3 and 21 (Fig. 1F).

Identification of differentially expressed (DE) circRNAs during adipogenic differentiation across various groups

To explore functional roles of circRNAs in tissues-specific adipogenic differentiation, we analyzed and compared the expression levels of circRNAs between different groups. We finally identified 17, 14, 20 and 9 differentiated expressed (DE) circRNAs across different groups (IMPre_vs_IMAd, AbPre_vs_AbAd, AbPre_vs_IMPre and AbAd_vs_IMAb) (Fig. 3, Table 2). We noticed that most of DE circRNAs were specific found in preadipocytes or adipocytes, several DE circRNAs showed different expression patterns during adipogenic differentiation between AbF and IMF groups (Table S1). Among them, we noticed that 7:22323550|22327655 was significantly downregulated in mature adipocytes when comparison with preadipocytes in both IMF and AbF groups. Z:78636651|78640537 (circCDKN2A) was considerably downregulated in AbAd group, while upregulated in IMAd group. In addition, 7:22754779|22756470 (circTNS1) was only found in intramuscular fat preadipocytes and adipocytes, 21:6563897|6564555 (circHSPG2), 3:66699169|66707019 (circSLC22A16), 17:10086299|10108615 (circGAPVD1), 16:242878|309387 (circKIFC1L) were specifically found in intramuscular adipocytes, 3:79378778|79415580 (circBCKDHB), 28:1095851|1096498 and 1:83410785|83437136 were specifically found in abdominal adipocytes.

Functional characterization of DE circRNAs

To investigate the potential functions of DE circRNAs, the host genes of DE circRNAs were performed GO terms analysis. We found that the molecular function (MF) of gene ontology (GO) analysis during adipogenesis were mainly enriched in lipid binding, phospholipase activity and lipase activity, cell component (CC) were mainly enriched in regulation of autophagy, glycerophospholipid biosynthetic process, phosphatidylinositol-mediated signaling and inositol lipid-mediated signaling (Fig. 4).

Validation of circRNAs

To confirm the circRNAs in chicken adipocytes, five DE circRNAs (circFNDC3AL, circHSPG2, circCLEC19A, circARMH1 and circLCLAT1) were randomly selected for validation by PCR and sanger sequencing (Fig. 5A). Divergent and convergent primers were designed for the amplification of circRNAs back-spliced junction (BSJ) site and linear mRNAs. As showed in Fig. 5B, BSJ sites of circRNAs were amplified and validated by sanger sequencing. The PCR products amplified by convergent primers of circRNAs were distinct in both cDNA and gDNA samples, while the divergent primers could only be amplified in the cDNA samples. In addition, PCR products amplified by the divergent primers were identified by Sanger sequencing (Fig. 5B). The sequencing results were consistent with Ribo-zero RNA-Seq data, which suggested that the circRNAs data is reliable.

Expression characteristics of miRNAs in chicken intramuscular and abdominal adipogenesis

To comprehensively analyze the characteristics of miRNAs during tissue-specific adipogenesis, miRNAs expression levels were compared across various groups. We finally identified 80 DE miRNAs (58 upregulated and 22 downregulated) between AbPre and AbAd groups, 225 DE miRNAs (85 downregulated and 140 DE miRNAs upregulated) between AbPre and IMPre groups, 206 DE miRNAs (98 downregulated and 108 upregulated) between AbAd and IMAd groups and 111 DE miRNAs (89 upregulated and 22 upregulated) between IMPre and IMAd groups, respectively (Fig. 6A) (Table S2). Among them, we noticed that 81 and 25 DE miRNAs were specifically identified during Ab adipogenic differentiation and IM adipogenic differentiation, respectively (Fig. 6B). We noticed that most of DE miRNAs were significantly downregulated in mature adipocytes, including miR-130b-5p, miR-148a-5p, miR-15c-5p, miR-16c-5p, miR-30a-3p (Fold change > 2, Qvalue < 0.001). However, miR-146b-5p was significantly upregulated in mature adipocytes in comparison with preadipocytes (Fold change > 4, Qvalue < 0.001). In the present study, heatmaps of DE miRNAs across various groups were displayed in Fig. 6C.

Construction of circRNAs-miRNAs-mRNAs Network

We noticed that IM and Ad groups shared with 31 DE miRNAs during adipogenesis, including miR-15c-5p, miR-206, miR-148a-5p, miR-128-1-5p, miR-30a-3p, miR-27b-5p, miR-92-5p (Fig. 7A). To further investigate the functional roles of miRNAs in chicken adipogenesis, the target genes of DE miRNAs were predicted by the bioinformatics analyses. KEGG pathway analysis suggested that their target genes were mainly enriched in PPAR signaling pathway, Metabolic pathways, Fatty acid metabolism pathway (Fig. 7B). Through integrating analysis of DE cirRNAs, miRNAs and mRNAs data, we constructed a ceRNAs network during chicken adipogenesis (Fig. 7C). It was worth noting that circFNDC3AL, circHSPG2, circLCLAT1 and circCLEC19A were the hub cirRNAs of the ceRNAs network (Fig. 7C). Furthermore, KEGG pathway analysis showed that the ceRNAs network regulate target genes mainly via Fatty acid metabolism, Focal adhesion and ECM-receptor interaction pathways (Fig. 7D).

Candidate circRNAs related to adipogenic differentiation

To further investigate the crucial roles of circRNAs in chicken adiogenesis, correlation analysis between circRNAs and their target genes which based on the ceRNAs network was performed. As shown in Fig. 8A, the expression levels of circFNDC3AL and circHSPG2 were significantly positively related with those of genes related to PPAR signaling pathway in intramuscular adipogenesis (r > 0.90, p < 0.01), such as peroxisome proliferator-activated receptor γ (PPARγ), fatty acid binding protein 4 (FABP4), perilipin 2 (PLIN2), CD36 molecule (CD36). In contrast, the expression level of circLCLAT1 was significantly negatively related with those of genes, while positively related with lysocardiolipin acyltransferase 1 (LCLAT1) and fatty acid desaturase 2 (FADS2) (r > 0.95, p < 0.01) (Fig. 8A). Moreover, the expression level of circARMH1 was significantly negatively related with those of genes in abdominal adipocytes (r > 0.92, p < 0.01), while circCLEC19A was significantly positively related with those of genes (r > 0.90, p < 0.01) (Fig. 8B). To further investigate the potential roles of circRNAs in fat tissue-specific deposition, the expression of cirRNAs were analyzed in different tissues. Our results showed that these four candidate circRNAs were highly expressed in the abdominal fat and breast muscle tissue of chicken (Fig. 8C). In addition, the dynamistic expression patterns of candidate circRNAs during tissue-specific adipogenetic differentiation were detected. Our results showed that circFNDC3AL and circCLEC19A expression levels were gradually increased during intramuscular and abdominal adipogenic differentiation, (Fig. 8D). In contrast, the expression levels of circLCLAT1 and circARMH1 were gradually decreased during intramuscular and abdominal adipogenic differentiation, respectively (Fig. 8D). Interestingly, we noticed that chicken circLCLAT1 was highly conservative among human, mouse and pig (Fig.S1), which suggested circLCLAT1 might play significant roles in animal adipogenesis or lipid metabolism.

Validation of circRNA-miRNA-mRNAs ceRNA networks

To verify the circRNA-miRNA-mRNAs regulation networks during intramuscular adipogenic differentiation, we analyzed their expression levels in intramuscular preadipocytes and mature adipocytes. Bioinformatics analysis suggested that cirFNDC3AL has many MREs (miRNAs response element), such as miR-130a-5p, miR-15c-5p, miR-18a/b-3p (Fig. 9A). RNA-Seq and RT-qPCR results showed that cirFNDC3AL and its’ downstream genes were significantly upregulated in differentiated-mature intramuscular adipocytes (Fig. 9C, 9D and 9F), while several adipogenic differentiation-related miRNAs were significantly downregulated, including miR-222, miR-456-3p, miR-15C-5p, miR-130b-5p, miR-130a-5p (Fig. 9B and 9E). It was worth noting that the target genes of circFNDC3AL were mainly associated with lipid metabolism and adipogenesis, such as PPARG, PLIN2, CPT1A, INSIG1. In addition, our results found that miR-146b-5p and miR-147 might regulate RUNXT1 and FADS2, while miR-34a-5p and miR-30e-5p might regulate PDGFRA, IGF2BP1, FNDC3B, MYH9. circLCLAT1 might affect chicken adipogenesis by sponging these miRNAs, therefore regulating target genes. Our results suggested that circLCLAT1-miRNAs (miR-146b-5p, miR-147, miR-30e-5p and miR-34a-5p)-mRNAs pathway showed the opposite expression patterns during intramuscular adipogenic differentiation (Fig. 10). CircLCLAT1 and its’ downstream genes were significantly downregulated in differentiated-mature intramuscular adipocytes (Fig. 10C, 10D and 10F), while miR-146b-5p and miR-147 were significantly upregulated in mature adipocytes in comparison with preadipocytes (Fig. 10B and 10E).

Previous study reported that preadipocytes-derived from abdominal fat (AbF) has high adipogenic differentiation ability than that from intramuscular fat (IMF) in chickens [26]. Adipogenesis is regulated by a series of complex regulation mechanisms, including transcription level, post-transcription level and so on [27–29]. Noncoding RNAs have notable effects on adipogenesis and lipid metabolism [30, 31]. Large amount of studies about noncoding RNAs on adipogenesis were mainly focused on mammals [11, 12, 30, 31]. However, letter is known about circular RNAs (circRNAs) in poultry adipogenesis.

In this study, we first analyzed Ribo-zero RNA-Seq and corresponding miRNAs data during chicken tissue-specific adipogenic differentiation. Three software (CIRI2, CIRCexplore and find_circRNA) were used for the identification of circRNAs. Although less circRNAs might be obtained by this way, it would improve accuracy rate in the present study. A total of 8843 circRNAs were identified in preadipocytes and adipocytes. Our study suggested that circRNAs were abundant in chicken preadipocytes and adipocytes. The characteristics of circRNAs in length, exon number and genomic distribution were consistent with previous reports in chicken [19, 32]. Previous studies suggested that circRNAs were expressed in tissues- and stage-specific manners [33, 34]. Abdominal and intramuscular fat deposition were result from various and complex molecular mechanisms. CircRNAs might play crucial roles in tissue-specific adipogenesis [25]. In the present study, DE circRNAs were identified across various tissue and cell types. Several DE circRNAs were also found in previous reports in chicken, such as circCELC19A which was suggested to play functional roles in follicle development [32]. In addition, circFNDC3AL and circTNS1 were also identified in chicken embryonic muscle tissues [19].

Our previous studies suggested that miRNAs could be crucial regulator in chicken adipogenesis [8, 35]. So, in this study, we systematically analyzed and compared the expression patterns of miRNAs during intramuscular and abdominal adipogenesis. We found that the majority of miRNAs were significantly downregulated in mature adipocytes. Meanwhile, a large number of genes related to lipid metabolism and adipogenesis were upregulated during the adipogenic differentiation across various tissues, which suggested that these downregulated miRNAs might promote adipogenesis through their target genes in chicken.

Generally, it is believed that circRNAs could act as molecular sponge of miRNAs thus regulating their target genes [36]. Integrated analysis of circRNAs, miRNAs and mRNAs data, we finally constructed hub ceRNAs networks during chicken adipogenic differentiation. We noticed that these hub genes in the ceRNAs network were enriched in fatty acid metabolism, PPAR signaling pathway and p53singnaling pathway. Furthermore, those genes that participated ceRNAs pathways were strongly related with candidate circRNAs in the present study. The RT-qPCR results of circFNDC3AL-miRNAs-mRNAs pathway were consistent with the results of bioinformatically analysis. Interestingly, fibronectin type III domain-containing protein 3B (FNDC3B) and 5 (FNDC5) have been found to play crucial roles during white fat browning and adipogenesis [37–40]. Perlecan (HSPG2, Heparan Sulfate Proteoglycan 2) was found to be a crucial regulator of obesity and lipid deposition [41]. Thus, we speculated that circFNDC3AL and circHSPG2 might play crucial roles in chicken adipogenesis. Further studies need to be done to investigate the functions of chicken circFNDC3AL and circHSPG2 on adipogenic differentiation. Previous studies reported that runt-related transcription factor 1 (RUNX1T1) [42, 43], myosin, heavy chain 9, non-muscle (MYH9), fatty acid desaturase 2 (FADS2), insulin-like growth factor 2 mRNA-binding protein 1 (IGF2BP1) [44–47] were associated with adipogenesis and fat deposition. We found that circLCLAT1 might affect adipogenic differentiation by regulating downstream genes (RUNX1T1, FADS2, MYH9, IGF2BP1 and PDGFRA) via four miRNAs (miR-34a-5p, miR-30e-5p, miR-146b-5p and miR-147). Further studies about the molecular regulation mechanism of circFNDC3AL and circLCLAT1/miRNAs/mRNAs pathway in chicken adipogenesis need to be done in the future.

In summary, we first provided comprehensive cirRNAs expression profiles in adipocytes-derived from various adipose tissues in chicken. Combined with the circRNAs, miRNAs and mRNAs data, we constructed ceRNAs networks which regulated chicken adipogenesis. Over all, our study not only provided insights into poultry tissue-specific adipogenesis, but also revealed new clues for studies about circRNAs on poultry adipogenic differentiation and fat deposition.

Tissues and cell samples collection

The experimental birds were obtained from the Avian Farm of Henan Agriculture University (Zhengzhou, Henan, China). Five kinds of tissues (Heart, liver, breast muscle, abdominal and kidney tissues) were collected and stored at -80 °C until use. The birds were euthanized by intramuscular injection of pentobarbital (Sigma, St. Louis, MO, USA) (40 mg/kg) under deep anaesthesia. Intramuscular and abdominal preadipocyte were isolated from the breast muscle and abdominal adipose tissue of 2 weeks old-chickens following the method described by Zhang et al [8, 26]. Pollution-free treatment of animal carcasses was performed after experimentation. Chicken preadipocytes adipogenic differentiation model in vitro was constructed according to the method by Zhang et al [26]. After 80–90% confluence, cells were exposed to MDIO differentiation medium. Cells samples were harvested at 0, 2, 4, 6, 8, and 10 days after adipogenic induction.

Data resources, annotation and quantification of circRNA

Ribo-Zero RNA-Seq and miRNAs data were download from the NCBI database (No. PRJNA429489 and PRJNA453673). Four groups were included in the PRJNA429489 and PRJNA453673 program, including preadipocytes derived from chicken intramuscular fat (IM_Pre) and abdominal fat (Ab_Pre) and differentiated-mature adipocytes (IM_Ad, Ab_Ad). Each group included two biological replicates. The paired-end (PE) reads were mapped to the GallusGallus 5 genome using BWA (v0.7.17) and Bowtie2 (v2.2.9) with default parameters. The BSJ (backspliced junctions) reads were scanned and analysed by CIRI2 (v2.0.6) and CIRCexplore (v2.3.3) with default parameters, and the output of Bowtie2 was used to identify circRNAs by find_circ with default parameters(v1.0). TPM was used to calculate the relative expression abundance of circRNA.

Identification of differentially expressed (DE) circRNAs and host genes functional annotation

DE circRNAs were analyzed using the edgeR package, with the threshold of p value < 0.05 and fold change ≥ 2. Host genes of circRNAs were used for prediction the potential functions of circRNAs. DAVID (http://david.abcc.ncifcrf.gov/) online software was used for Gene Ontology (GO) enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis in the present study.

The conservative analysis of circRNAs

CircRNAs sequences of human and mouse were download from circBase database (http://www.circbase.org), porcine circRNAs sequences were download from pigcircNet database (http://lnc.rnanet.org/circ/). And the sequences were compared using Clustal Omega (https://www.ebi.ac.uk/Tools/msa/clustalo/) was used for multiple sequence alignment.

Genomic DNA (gDNA) and total RNA extraction, cDNA Synthesis and Quantitative Real-Time PCR (qRT-PCR)

Genomic DNA (gDNA) and total RNA were isolated from tissues/cell samples using animal genomic DNA kit (Tiangen, China) and RNAiso plus (Takara, Dalian, China) according to the manuscript’s instructions, respectively. cDNA was synthesized with PrimeScriptTM RT reagent Kit with gDNA Eraser (Takara, Dalian, China). Primers used for qRT-PCR were designed by primer3plus (Supplementary Table S3). qRT-PCR was performed with SYBR® Premix Ex TaqTM II kit (Takara) on a LightCycler® 96 Real-Time PCR system. GAPDH and U6 were used as the reference genes of circRNAs, mRNAs and miRNAs, respectively. The 2^−ΔΔCt method was used to calculated the gene expression levels.

Validation of circRNAs

To validate the circRNAs related to chicken adipogenesis, we performed PCR and sanger sequencing assays in the present study. Divergent primer was designed to amplify the junction sites of circRNAs, convergent primer was designed to amplify the linear mRNAs (Supplementary Table S3). Random primers were used for cDNA synthesis. Then the cDNA of intramuscular and abdominal preadipocytes and adipocytes were mixed to a cDNA pool. The PCR products were sequencing by Sangon Biotech Co. Ltd (Shanghai, China).

The integrative analysis of circRNAs, miRNAs and mRNAs

As circRNAs can play as miRNA sponges, the present study analyzed potative miRNAs binding sites in chicken. The differentially expressed miRNAs during intramuscular and abdominal adipocytes differentiation were come from our previous study [35]. miRanda and RNAhybrid software were used to predict the miRNA sites in circRNAs with default parameters and investigate putative interactions between miRNAs and circRNAs. The circRNAs-miRNAs-mRNAs ceRNA networks were constructed and visualized using Cytoscape (version 3.5.0).

Statistical analysis

Statistical analyses of the data were performed using SPSS 22.0 (SPSS Inc., Chicago, IL, USA). All results were presented as mean ± S.E.M, two-tailed t-test to analyzed the data. p < 0.05 and ** p < 0.01 were considered significant and extremely significant, respectively.

IMF: intramuscular fat; AbF: abdominal fat; circRNAs: circular RNAs; miRNAs: microRNAs; MREs: miRNAs response element; DE: Differentially expressed; GO: Gene Ontology; KEGG: Kyoto Encyclopedia of Genes and Genomes; BSJ: back-spliced junction; FNDC3AL: fibronectin type III domain containing 3A-like; FNDC3B: fibronectin type III domain-containing protein 3; FNDC5: Fibronectin type III domain-containing protein 5; TNS1: tensin 1; HSPG2: heparan sulfate proteoglycan 2; CLEC19A: C-type lectin domain containing 19A; ARMH1: armadillo like helical domain containing 1; LCLAT1: lysocardiolipin acyltransferase 1; RUNX1T1: runt-related transcription factor 1; MYH9: myosin, heavy chain 9, non-muscle; FADS2: fatty acid desaturase 2; IGF2BP1: insulin-like growth factor 2 mRNA-binding protein 1. PPARγ: peroxisome proliferator-activated receptor γ, FABP4: fatty acid binding protein 4, PLIN2: perilipin 2, CD36: CD36 molecule.

Ethics approval and consent to participate

The animal experiments were performed with the permission of Avian Farm of Henan Agriculture University (Zhengzhou, Henan, China), and was approved by the Institutional Animal Care and Use Committee (IACUC) of Henan Agricultural University (11-0085). All effects were made to minimize birds suffering.

Consent for publication

Not applicable.

Availability of data and materials

The sequencing data has been submitted to NCBI SRA under BioProject ID: PRJNA429489 and PRJNA453673.

Competing interests

The authors declared no competing interest.

Funding

No funding was obtained for this study.

Authors’ contributions

ZL and SZ conceived the project, supervised the experiments and revised the manuscript. MZ and YH performed the experiments and analyzed data, MZ wrote the manuscript. YZ, XM and XA contributed the part of regents and data analysis. The final manuscript was approved by all authors.

Acknowledgements

We would like to thank the Guirong Sun Ph.D. for providing cells and reagents for this research.

Consent for publication

Not Applicable.

Availability of data and materials

Not Applicable.

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Due to technical limitations, Tables 1-2 are provided in the Supplementary Files section.

Table S1. The list of differentiated expressed (DE) circRNAs across various groups.

Table S2. The list of differentiated expressed (DE) miRNAs across various groups.

Table S3. The primers used for qRT-PCR in the present study.

Fig.S1 circLCLAT1 is a sequence-conservative circRNA. (A) Genome locate of chicken circLCLAT1. (B) Multiple sequence alignment analysis of circLCLAT1 among species. (C) The evolutionary tree of circLCLAT1 among species.

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Integrative analysis of circRNAs, miRNAs and mRNAs profiles reveal that ceRNAs networks in chicken intramuscular and abdominal adipogenesis

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Journal Publication

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Abstract

Figures

Background

Results

Overview of circRNAs data of Ribo-Zero RNA-Seq in chicken preadipocytes and adipocytes

Identification of differentially expressed (DE) circRNAs during adipogenic differentiation across various groups

Functional characterization of DE circRNAs

Validation of circRNAs

Expression characteristics of miRNAs in chicken intramuscular and abdominal adipogenesis

Construction of circRNAs-miRNAs-mRNAs Network

Candidate circRNAs related to adipogenic differentiation

Validation of circRNA-miRNA-mRNAs ceRNA networks

Discussion

Conclusions

Methods

Tissues and cell samples collection

Data resources, annotation and quantification of circRNA

Identification of differentially expressed (DE) circRNAs and host genes functional annotation

The conservative analysis of circRNAs

Genomic DNA (gDNA) and total RNA extraction, cDNA Synthesis and Quantitative Real-Time PCR (qRT-PCR)

Validation of circRNAs

The integrative analysis of circRNAs, miRNAs and mRNAs

Statistical analysis

Abbreviations

Declarations

Ethics approval and consent to participate

Consent for publication

Availability of data and materials

Competing interests

Funding

Authors’ contributions

Acknowledgements

Consent for publication

Availability of data and materials

References

Tables

Supplementary Figure / Table Captions

Supplementary Files

Status:

Journal Publication

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