Open Access

Revelation of mRNAs and proteins in porcine milk exosomes by transcriptomic and proteomic analysis

  • Ting Chen1,
  • Qian-Yun Xi1,
  • Jia-Jie Sun1,
  • Rui-Song Ye1,
  • Xiao Cheng1,
  • Rui-Ping Sun1, 2,
  • Song-Bo Wang1,
  • Gang Shu1,
  • Li-Na Wang1,
  • Xiao-Tong Zhu1,
  • Qing-Yan Jiang1 and
  • Yong-Liang Zhang1Email author
Contributed equally
BMC Veterinary ResearchBMC series – open, inclusive and trusted201713:101

https://doi.org/10.1186/s12917-017-1021-8

Received: 27 April 2016

Accepted: 3 April 2017

Published: 13 April 2017

Abstract

Background

Milk is a complex liquid that provides nutrition to newborns. Recent reports demonstrated that milk is enriched in maternal-derived exosomes that are involved in fetal physiological and pathological conditions by transmission of exosomal mRNAs, miRNAs and proteins. Until now, there is no such research relevant to exosomal mRNAs and proteins in porcine milk, therefore, we have attempted to investigate porcine milk exosomal mRNAs and proteins using RNA-sequencing and proteomic analysis.

Results

A total of 16,304 (13,895 known and 2,409 novel mRNAs) mRNAs and 639 (571 known, 66 candidate and 2 putative proteins) proteins were identified. GO and KEGG annotation indicated that most proteins were located in the cytoplasm and participated in many immunity and disease-related pathways, and some mRNAs were closely related to metabolisms, degradation and signaling pathways. Interestingly, 19 categories of proteins were tissue-specific and detected in placenta, liver, milk, plasma and mammary. COG analysis divided the identified mRNAs and proteins into 6 and 23 categories, respectively, 18 mRNAs and 10 proteins appeared to be involved in cell cycle control, cell division and chromosome partitioning. Additionally, 14 selected mRNAs were identified by qPCR, meanwhile, 10 proteins related to immunity and cell proliferation were detected by Western blot.

Conclusions

These results provide the first insight into porcine milk exosomal mRNA and proteins, and will facilitate further research into the physiological significance of milk exosomes for infants.

Keywords

Porcine milk exosomes RNA-seq Proteomic analysis

Background

Milk is the primary source of nutrition for newborns, and breastfeeding is known to make a valuable contribution to infant health [1]. Breast milk contains a potent mixture of diverse components including milk fat globules (MFG), immune competent cells, antibodies, soluble proteins, cytokines, and antimicrobial peptides [2] that together protect young infants against infections [3]. In addition, the milk contains growth factors which could promote intestinal development [4] and may protect infants against developing allergies [5]. Meanwhile, milk also contain many microvesicles, such as milk-derieved exosomes, who was reported to transfer contained RNAs to living cells and influenced the development of calf’s gastrointestinal and immune systems [6].

Exosomes are small membrane vesicles (30–100 nm) which released from producing cells into the extracellular environment [7]. Many different cell types have the capacity to produce and release exosomes [813]. Additionally, milk-derived exosomes have been reported in humans, cows and pigs [1417] and which involved in many biological processes. Exosomes contain proteins, mRNAs, miRNAs and lipids. Recent studies revealed that human [18], bovine [19], pig [20], and rat [21] milk contain miRNAs, and mRNAs have also been identified in whey [6, 2123]. 10,948 mRNA transcripts were detected in rat milk, and some immune and development-related mRNAs showed time-dependent expression [21]. 19,320 mRNAs were detected by microarray analyses in bovine milk exosomes, and they had possible effects of human cells [24]. Additionally, Cecilia Lässer et al. demonstrated that mRNAs in breast milk exosomes could be taken up by human macrophages [25].Until now, the components of mRNAs in porcine milk exosmes are still unclear.

Proteins in exosome were dependented on the specific cell-type [26], the dendritic cell-derived exosomes contain several cytosolic proteins [8]. Body fluid derived exosomes CD24, CD9, Annexin-1 and Hsp70 were as positive marker proteins [27]. Anti-MHC-class II- and anti-CD63 beads were used to isolate human breast milk exosmes [28]. In bovine milk exosomes 2,107 proteins were identified, and all major exosome protein markers were abundant [29], as were milk fat globule membrane (MFGM) proteins. Another report showed 2,350 proteins in bovine milk exosome via iTRAQ, and 90 exosomal proteins were found to be differentially regulated by infections [30].

In our previous study, miRNAs in porcine milk exosomes have been revealed by deep sequencing [17], but up to now, porcine milk exosomal mRNAs and proteins remains unknown. Therefore, we further performed RNA-sequencing and proteomic analysis of porcine milk exosomes in order to understand new physiological functions, especially immunity and proliferation related regulation of porcine milk.

Methods

Milk sample preparation

Fresh porcine milk samples were collected from 10 healthy Landrace female pigs that had been lactating for 1 to 5 days (after parturition) at the pig farm of the South China Agriculture University (Guangzhou, China). Milk samples were frozen immediately and kept at −80 °C until used.

Isolation of milk exosomes

Porcine milk exosomes were separated as previously described [17]. Briefly, about 80–100 mL fresh raw porcine milk samples were centrifuged at 2,000 g for 30 min at 4 °C to remove milk fat globules (MFGs) and mammary gland-derived cells [18]. Defatted samples were then subjected to centrifugation at 12,000 g for 30 min at 4 °C to remove residual MFGs, casein, and other debris [6]. From the supernatant, the membrane fraction was prepared by ultracentrifugation at 110,000 g for 2 h using an SW41T rotor (Beckman Coulter Instruments, Fullerton, CA). Then, the exosome purification steps were as previously described [29, 30].

RNA isolation

Total RNA was isolated from porcine milk exosome samples by Trizol reagent (Invitrogen, Carlsbad, CA) according to the manufacturer’s protocol. The quality of RNA was examined by 2% agarose gel electrophoresis and with a BiophotometerNanoDrop 2000 (Thermo, USA), as well as further confirmed using a Bioanalyzer (Agilent Technologies, Santa Clara, CA).

RNA-sequencing

The collected RNA samples were analyzed by IlluminaHiSeq™ 2000 analyzer at Beijing Genomics Institute(BGI, Shenzhen, China) as previously described [31]. Firstly, poly (A) mRNA was isolated from total RNA sample with Oligo(dT) magnetic beads. Secondly, the purified mRNA was fragmented by the RNA fragmentation kit (Ambion), the first-strand cDNA synthesis was performed using random hexamer primers and reverse transcriptase, and the second-strand cDNA was synthesized using RNase H and DNA polymerase I. Then the cDNA libraries were prepared using the Illumina Genomic DNA Sample Prep kit (Illumina) following the manufacturer’s protocol. Finally, the library was sequencing using Illumina HiSeq™ 2000.

Sequencing analysis

The porcine reference genome sequence and annotated transcript set were downloaded from the ensemble database (Sscrofa10.2, http://asia.ensembl.org/Sus_scrofa/Info/Index). After quality control (QC) step of raw reads, then removing low quality reads, reads containing Ns > 5 and reads containing adapters, clean reads were aligned to the reference pig genomic database (Sscrofa 10.2,) with SOAPaligner/SOAP2 [32] and allowing up to 5 mismatches in 90-bp reads. The alignment data were utilized to calculate distribution of reads on pig gene database (http://www.ncbi.nlm.nih.gov/), and the numbers of reads per kilobase of dexon region in a gene per million mapped reads were used as the value of normalized gene expression levels [33]. The unalignment data carried out novel transcript prediction, reads are at least 200 bp away from annotated gene, the transcript is of length over180 bp and the sequencing depth is no less than 2 for novel transcript unit analysis.

qPCR identification of known mRNAs in porcine milk exosome

Total RNA (identical with the RNA-sequencing sample) was first digested with DNase I (Promega, American), and 2 μg of total RNA was reverse transcribed by oligo (dT).The cDNA was diluted by 2-fold with ddH2O, and PCR was performed on a Bio-Rad system (BIO-RAD, USA) in a final 20 μL volume reaction, containing 2 μL PCR cDNA, 10 μL of 2× PCR Mix (Roche, Switzerland) and 1 mM of each primer. The real-time PCR thermal profile was as follows: 5 min at 95 °C, 40 cycles of 30 s at 94 °C, 30 s at the corresponding annealing temperature (Tm) and 72 °C for 30 s, followed by 72 °C at 10 min, and 5S ribosomal RNA was used as an internal control for the PCR [17, 34]. The mRNAs primers were designed with Primer 5.0 (Table 1).
Table 1

Primers for qPCR

ID

Primer

Sequences (5’to3’)

Products length (bp)

ENSSSCG00000000207

LOC100739053-F

CAAAGGAAGCCTACAAGAA

198

LOC100739053-R

CACGGTAGTCCAGCAGA

ENSSSCG00000003930

RPS8-F

GAGAAAGCCCTACCACA

191

RPS8-R

CGTCAATAATCCTCGTCT

ENSSSCG00000004489

EF1ALPH-F

GATTGTTGCTGCTGGTGT

226

EF1ALPH-R

TGCTACTGTATCAGGGTTGT

ENSSSCG00000004177

RPS12-F

TCTACCCGTAACCCACC

219

RPS12-R

CCTCCACCAACTTGACATA

ENSSSCG00000015103

RPS25-F

GCCCAAGGACGACAA

109

RPS25-R

GCCTTTGGACCACTTC

ENSSSCG00000006249

RPS20-F

ACCGCTGTTCGCTCTTC

211

RPS20-R

GTCCCTTCACTTTGAGGTTCT

ENSSSCG00000029830

RPL8-F

CGAGCGACACGGCTACAT

255

RPL8-R

GGCTTCTCCTCCAGACAACAC

ENSSSCG00000009267

CSN3-F

CACCTGAGACCACCACT

140

CSN3-R

TGACTGAAGGCAGATAA

ENSSSCG00000013907

UBA52-F

ACGGGCAAGACCATCAC

196

UBA52-R

GCAGACGAAGCACCAAGT

ENSSSCG00000001502

RPS18-F

AGGGTGTAGGACGGAGAT

134

RPS18-R

CTTGTATTGGCGAGGATT

ENSSSCG00000024825

RPL6-F

CAGAGGCAAGAGGGTCA

128

RPL6-R

TGGTGGAGGTGGCAATA

ENSSSCG00000004970

RPLP1-F

GCACGACGATGAGGTTAC

131

RPLP1-R

TGAGGCTCCCGATGTT

ENSSSCG00000010328

RPS24-F

TTGATGTCCTTCACCCTG

269

RPS24-R

CATTCTGTTCTTGCGTTCT

ENSSSCG00000025527

FABP3-F

GCTGGGATTGAAGTTTGA

163

FABP3-R

GTGGGTGAGTGTCAGGATG

5S

5S–F

TCTACGGCCATACCACCCTGAA

83

5S–R

GGCCCGACCCTGCTTAG

Total protein extraction

RIPA lysis buffer was used to extract porcine milk exosomal proteins according to the assay kit protocol (Bioteke, Beijing). Briefly, 1 mM PMSF was added to the RIPA lysis buffer and 100–200 μL was added to porcine milk exosomes. Following complete exosome lysis, the sample was centrifuged at 10,000–14,000 g for 3–5 min and the supernatant was subjected to further analysis. Proteins were stored at −80 °C until used.

Protein separation by 1D SDS-PAGE and in-gel digestion

Porcine milk exosome proteins were resolved by 12% polyacrylamide gel. The gel was stained with Coomassie blue R-250. 20 bands were excised and destained using 50 mM ammonium bicarbonate in 50% ACN. And then the gel pieces were performed incubating with 10 mM DTT in 25 mM ammonium bicarbonate for 1 h at 60 °C to reduce disulfide bonds and incubating the samples with 55 mM iodoacetamide in 25 mM ammonium bicarbonate for 45 min at room temperature in dark for Alkylation of cysteines. Then, using the Trypsin Gold (Promega, Madison, WI, USA) for digested (37 °C, 16 h) the gel bands. After the peptides sequentially extracted from gel bands by 0.1% formic acid in 50% ACN twice, using 100% ACN twice, the extracted peptides were dried and stored at −80 °C until LC-MS/MS analysis.

Protein sequencing

Protein samples were analyzed using a Q-EXACTIVE mass spectrometer at the Beijing Genomics Institute (BGI, Shenzhen, China). Briefly, samples were separated by 1D SDS-PAGE and in-gel digestion was performed to generate peptides for LC-MS/MS analysis. Peptide fractions were initially separated on a LC-20 AD nanoHPLC (Shimadzu, Kyoto, Japan), then subjected to nanoelectrospray ionization followed by tandem mass spectrometry (MS/MS) using a Q EXACTIVE (ThermoFisher Scientific, San Jose, CA) coupled online to the HPLC.

LC-ESI-MS/MS analysis based on Q EXACTIVE

After a series of processing, we regulated each fraction at the average final concentration of peptide at 0.5 μg/uL and loading 10 uL on a LC-20 AD nanoHPLC (Shimadzu, Kyoto, Japan) by the autosampler onto a 2 cm C18 trap column. Then 10 cm analytical C18 column (inner diameter 75 μm) was used for eluted the peptides. After the sample was loading to the trap column, then bring into the analytical column, and finally the separated peptides were subjected to nanoelectrospray ionization followed by tandem mass spectrometry (MS/MS) in a Q EXACTIVE (ThermoFisher Scientific, San Jose, CA) coupled online to the HPLC. Resolution of 7,000 on Orbitrap was used to detect the intact peptides. Peptides were selected for MS/MS using high-energy collision dissociation (HCD) operating mode with a normalized collision energy setting of 27.0; ion fragments were setting of a resolution of 17,500. A data-dependent procedure that alternated between one MS scan followed by 15 MS/MS scans was applied for the 15 most abundant precursor ions above a threshold ion count of 20,000 in the MS survey scan with a following Dynamic Exclusion duration of 15 s. The electrospray voltage applied was 1.6 kV. The Automatic gain control (AGC) which used to optimize the spectra generated by the orbitrap was target for full MS was 3e6 and 1e5 for MS2. For MS scans, the m/z scan range was 350 to 2,000 Da. For MS2 scans, the m/z scan range was 100–1,800. All those works were carried out in Beijing Genomics Institute (BGI, Shenzhen, China).

Protein data analysis

All raw data were acquired using an Orbitrap, converted to MGF files using Proteome Discoverer 1.2 (PD1.2, Thermo), and the Mascot search engine (Matrix Science, London, UK; version 2.3.02) was used to search against a database containing 25,152 sequences(ftp://ftp.ensembl.org/pub/release-73/fasta/sus_scrofa/pep/).Non-intact (>20 ppm) peptides and fragmented ions (0.6 Da) were removed, with allowance for one missed cleavage in trypsin digests. Next, the fixed carbamidomethyl (C) modification, and potential variable modifications Gln- > pyro-Glu (N-term Q), oxidation (M), deamidation (NQ), and +2 and +3 charge states were considered. Mascot was used to search the automatic decoy database by choosing the decoy checkbox, with the decoy checkbox set to generate a random sequence of database and test for raw spectra, as well as the actual database. Finally, only peptides with significance scores ≥20 at the 99% confidence interval in the Mascot probability analysis were counted as identified proteins [29]. All identified proteins included at least one unique peptide.

Western blot identification

Protein samples (20–30 μg) were measured by BCA assay [35], and separated using 10–15% SDS-PAGE, transferred to a 0.22 μm or 0.45 μm polyvinylidenedifluoride membrane (Millipore), and incubated with specific and HRP-conjugated secondary antibodies, and detected with an enhanced chemiluminescence kit (Roche, Switzerland) using FluorChem M (Proteinsimple) [36]. Anti-EGF (AB20578b), anti-TGFB-3 (AB20578b), anti-MSTN (AB60418a), connective tissue growth factor (CTGF) (AB60212a), anti-PDGFA (AB61078b), anti-CD63 (D260973), anti-IGFBP-7 (AB60509b), anti-CD9 (AB54118), anti-HTRA3 (AB61337a), and anti-THBS1 (AB61391a) were purchased from BBI Antibody (SangonBiotch, Shanghai, China). Lactoferrin (C-15) and β-actin were purchased from Santa Cruz (Santa Cruz, American). Protein’ concentrations were determined using the Pierce BCA Protein Assay Kit (Thermo Fisher, American) using a BSA standard.

Bioinformatics analysis

We performed functional annotation using Blast2GO to search the non-redundant protein database (NR; NCBI) and the COG database (http://www.ncbi.nlm.nih.gov/COG/), which was used to classify and group the identified proteins. All the known mRNAs and proteins were performed Gene Ontology, KEGG pathway and Tissue-specific using DAVID6.7 bioinformatics resources (http://david.abcc.ncifcrf.gov/).

Results

Identification of exosomes by western blotting and extraction of RNA and protein from porcine milk exosome

We previously isolated exosomes from porcine milk and analyzed them using transmission electron microscopy [17]. In the present study, we observed exosomal marker proteins CD63 and CD9 by Western blotting (Fig. 1a). We extracted total RNA from the pellets after ultracentrifugation and examined the RNA by Agilent 2100, and the results showed that the porcine milk exosome contained RNAs and small rRNAs (Fig. 1c), which is consistent with previous studies [4, 6, 17, 20]. Porcine milk proteins were extracted using RIPA lysis buffer and resolved using SDS-PAGE (Fig. 1b), which proteins covered a large molecular weight range, but most of them were fell into the 20–25, 28–35, 35–40 and 43–55 kDa ranges, and these ranges were considered separately.
Fig. 1

Identification of proteins and mRNAs in porcine milk exosomes. a detection of the exosomal marker proteins CD63 and CD9 by Western blotting. b SDS-PAGE. c RNA sample analyzed by the Agilent Bioanalyzer 2100. d distribution of genen’s coverage

Transcript sequencing and analysis

Transcript sequencing

We totally obtained 77,106,888 raw reads, which mapped to porcine genome (sscrofa10.2, www.ensembl.org/Sus_scrofa/). The mapped proportion was 63.76% accounting for 49,161,814 reads, and the perfect match reads were 33,863,808 (43.92%) and the unique match reads were 45,080,932 (58.47%). By blast searching the 77,106,888 reads against pig coding gene database (http://www.ncbi.nlm.nih.gov/), 57,413,016 total match reads (represented 74.46%) and 53,836,128 (69.82%) unique matched reads were identified (Table 2). All the reads represent 13,895 genes (Additional file 1), the subsequent distribution of genes’ coverage analysis showed the number of genes’ coverage >50% contained 9,507 genes and represented 69% of 13,895 genes, the 4,261 (representing 31%) genes coverage are 90%–100% (Fig. 1d).
Table 2

Alignment statistics of RNA-seq data map to reference genome and gene database

 

Map to Genome

Map to Gene

 

Reads number

Percentage

Reads number(control)

Percentage

Total Reads

77,106,888

100.00%

77,106,888

100.00%

Total Base Pairs

6,939,619,920

100.00%

6,939,619,920

100.00%

Total Mapped Reads

49,161,814

63.76%

57,413,016

74.46%

perfect match

33,863,808

43.92%

45,400,239

58.88%

<=5 bp mismatch

15,298,006

19.84%

12,012,777

15.58%

unique match

45,080,932

58.47%

53,836,128

69.82%

multi-position match

4,080,882

5.29%

3,576,888

4.64%

Total Unmapped Reads

27,945,074

36.24%

19,693,872

25.54%

Novel mRNAs predicted in pig exosome milk

Then we performed a novel transcript prediction and annotation according to the criteria described in Method. Results showed we obtained 2,409 novel transcripts (Fig. 2a and Additional file 2), and those novel transcripts were distributed in all the 19 chromosomes. These results would improve the gene annotations of the porcine genome and transcriptome [31].
Fig. 2

Statistics of novel transcripts and qPCR detected randomly from top 50 list in RNA-sequencing. a The number of predicted novel transcripts in porcine milk exosome. b The expression of 14 mRNAs, from left to right, respectively: UBA52, RPS12, RPS20, RPS18, RPL6, RPLP1, EF1ALPH, CSN3, RPS25, RPL8, RPS24, LOC100739053, RPS8, FABP3

qPCR identified for mRNAs

After a series of analysis of RNA sequencing, we randomly selected 14 transcripts genes from the top 50 list (Additional file 3) for evaluated their expression in the porcine milk exosomes by qPCR. The results showed that they were all detected in the sample (Fig. 2b).

Proteome sequencing and data analysis

Following separation by SDS-PAGE, in-gel digestion was performed and peptides were analyzed by mass spectroscopy. The four groups of P130340_6, P130340_8, P130340_10 and P130340_13 (6, 8, 10, and 13 in Fig. 1b) were corresponding to 43–55, 35–40, 28–35 and 20–25 kDa, respectively, which were treated identically, since they displayed a relatively high gray density in the gel. With a false discovery rate (FDR) setting ≤1.2%, 307,390 total spectras were detected, which only 18,638 spectras could be mapped using the Mascot software, and 2,313 peptides represent 639 proteins were ultimately identified from the sample (Sus_scrofa, Table 3 and Additional file 4), and which number of protein matched with a given quality match check criterion with at least possessing one unique peptide can be considered as a reliable protein. Of these, 571 proteins were present in the Sscrofa 10.2 database, 66 were novel candidate proteins and two were putative proteins (Additional file 4). Most of the novel proteins (44) and the two putative proteins were not highly abundant, whereas most of high abundance proteins were known proteins. Analysis of protein and peptide length distribution after digestion revealed that most were between 8 and 54 amino acids, and the majorities were between 9 and 25 residues, with the highest proportion (12%) comprising 13 amino acids (Additional file 5: Figure S1). Analysis of the peptide and spectrogram distribution showed that lots of proteins were represented by between 1 and 10 unique peptides, and one unique peptide was the predominantly case (Additional file 6: Figure S2). In the sequence coverage range of 0% to 20%, 473 proteins were identified (77.02%, Additional file 7: Figure S3e), and the sequence coverage was increased as the number of identified proteins decreased (Additional file 7: Figure S3a, b, c, d, e).
Table 3

Proteins identified in this study

Sample

Total spectra

Identified spectra

Identified peptides

Identified proteins

FDR (%)

Unknown protein

Putative protein

P130340_10

13,430

672 [5.0037%]

92

40

1.05

4

 

P130340_13

17,281

790 [4.5715%]

108

44

0.90

2

 

P130340_6

17,783

721 [4.0544%]

303

94

1.13

12

 

P130340_8

15,140

596 [3.9366%]

180

59

1.03

4

 

Sus_scrofa

307,390

18,638 [6.0633%]

2,313

639

1.04

66

2

Identification by Western blotting

Based on the above results, we randomly selected 10 proteins to confirm their presence in porcine milk exosomes. Specifically, EGF, TGFβ-3, MSTN, CTGF, IGFBP-7, PDGFA, HTRA3, THBS1, β-actin and lactoferrin (LTF) were all successfully detected (Fig. 3).
Fig. 3

Confirmation by Western blotting. All 10 randomly selected proteins were confirmed to be present in porcine milk exosome

COG annotation of mRNAs and proteins

The Cluster of Orthologous Groups of proteins (COG) database was used for protein orthologous classification, and all proteins in this database are assumed to be derived from a common protein ancestor. COG analysis showed that proteins from porcine milk exosomes were connected with multiple biological processes (Fig. 4 and Additional file 8). Interestingly, proteins involved in DNA or RNA synthesis and transport particularly abundant. Furthermore, five proteins were related to intracellular trafficking, secretion, and vesicular transport, with some in the high abundance P130340_13 (Additional file 9: Figure S4b) and P130340_8 groups (Additional file 9: Figure S4d). Additionally, 10 conserved proteins were involved in cell cycle control, cell division and chromosome partitioning. Similarly, enriched 6 COG Ontology in mRNAs, including 31 genes related to intracellular trafficking and secretion and 18 mRNAs of Cell division and chromosome partitioning / Cytoskeleton (Fig. 5 and Additional file 10).
Fig. 4

COG annotation of porcine milk exosome and Sus_Scrofa database proteins

Fig. 5

COG annotation of porcine milk exosome and Sus_Scrofa database mRNAs

Go analysis of mRNAs and proteins

GO annotation was performed using DAVID version 6.7 (http://david.abcc.ncifcrf.gov) with a standard Benjamini < 0.05. We selected the top 10 GO terms of Cellular Component (CC), Molecular Function (MF) and Biological Process (BP) for further analysis. For mRNA, cytoplasm genes account for a high proportion (6.3%), and specific intracellular organelle lumen, nuclear lumen genes account for ~1.9%. Predicted functions included various bindings (including adenyl ribonucleotide, magnesium ion, nuclear hormone receptor and protein kinase) and diverse enzymatic activity (including protein kinase, pyrophosphate, transcription coactivator, exonuclease, small conjugating protein ligase and NADH dehydrogenase), predicted biological processes relative to proteins (include protein metabolic, transport, modification and catabolic process) and RNA (including RNA metabolic, processing and ncRNA processing) (Table 4 and Additional file 10). For proteins, most of them were included in cytoplasm and cytoplasmic part, taking a proportion of 7.1%. Additionally, there were lots of specific membrane-bounded vesicle lumen, granule lumen, vesicle, lytic vacuole and reticulum lumen proteins. And major of those proteins were enriched in the molecular function in terms of diverse activity and predicted biological processes, including acute inflammatory response, complement activation, classical pathway, B cell mediated immunity, negative regulation of blood coagulation and coagulation, activation of immune response and protein maturation and processing (Table 5 and Additional file 5).
Table 4

GO annotation of identified mRNAs

Category

Term

Count

%

Benjamini

GOTERM_BP_5

GO:0044267 ~ cellular protein metabolic process

1,481

1.30

2.054E-42

GOTERM_BP_5

GO:0015031 ~ protein transport

531

0.47

3.262E-27

GOTERM_BP_5

GO:0016070 ~ RNA metabolic process

633

0.56

5.403E-27

GOTERM_BP_5

GO:0006396 ~ RNA processing

388

0.34

1.149E-21

GOTERM_BP_5

GO:0006464 ~ protein modification process

888

0.78

8.933E-18

GOTERM_BP_5

GO:0006886 ~ intracellular protein transport

271

0.24

1.149E-16

GOTERM_BP_5

GO:0030163 ~ protein catabolic process

404

0.36

3.782E-12

GOTERM_BP_5

GO:0043632 ~ modification-dependent macromolecule catabolic process

374

0.33

1.875E-11

GOTERM_BP_5

GO:0044257 ~ cellular protein catabolic process

390

0.34

2.34E-11

GOTERM_BP_5

GO:0034470 ~ ncRNA processing

141

0.12

4.795E-10

GOTERM_CC_5

GO:0005737 ~ cytoplasm

4,253

3.74

1.54E-126

GOTERM_CC_5

GO:0043231 ~ intracellular membrane-bounded organelle

4,485

3.94

5.61E-99

GOTERM_CC_5

GO:0044444 ~ cytoplasmic part

2,924

2.57

9.8E-86

GOTERM_CC_5

GO:0044446 ~ intracellular organelle part

2,530

2.22

5.426E-71

GOTERM_CC_5

GO:0070013 ~ intracellular organelle lumen

1,200

1.06

3.933E-66

GOTERM_CC_5

GO:0044428 ~ nuclear part

1,205

1.06

6.521E-59

GOTERM_CC_5

GO:0031981 ~ nuclear lumen

979

0.86

5.556E-53

GOTERM_CC_5

GO:0005829 ~ cytosol

879

0.77

2.958E-41

GOTERM_CC_5

GO:0005634 ~ nucleus

2,801

2.46

1.904E-33

GOTERM_CC_5

GO:0005654 ~ nucleoplasm

599

0.53

2.982E-32

GOTERM_MF_5

GO:0032559 ~ adenyl ribonucleotide binding

892

0.78

1.822E-20

GOTERM_MF_5

GO:0004672 ~ protein kinase activity

387

0.34

1.894E-13

GOTERM_MF_5

GO:0000287 ~ magnesium ion binding

294

0.26

2.071E-11

GOTERM_MF_5

GO:0016462 ~ pyrophosphatase activity

448

0.39

1.642E-08

GOTERM_MF_5

GO:0035257 ~ nuclear hormone receptor binding

64

0.06

1.128E-07

GOTERM_MF_5

GO:0003713 ~ transcription coactivator activity

147

0.13

1.259E-07

GOTERM_MF_5

GO:0004527 ~ exonuclease activity

45

0.04

1.407E-05

GOTERM_MF_5

GO:0019787 ~ small conjugating protein ligase activity

108

0.09

0.0010606

GOTERM_MF_5

GO:0019901 ~ protein kinase binding

95

0.08

0.0050729

GOTERM_MF_5

GO:0050136 ~ NADH dehydrogenase (quinone) activity

34

0.03

0.0085249

Table 5

GO annotation of identified proteins

Category

Term

Count

%

Benjamini

GOTERM_BP_5

GO:0002526 ~ acute inflammatory response

28

0.47

1.7E-17

GOTERM_BP_5

GO:0006956 ~ complement activation

15

0.25

1.06E-09

GOTERM_BP_5

GO:0016485 ~ protein processing

20

0.33

1.93E-08

GOTERM_BP_5

GO:0030193 ~ regulation of blood coagulation

13

0.22

2.19E-08

GOTERM_BP_5

GO:0006958 ~ complement activation, classical pathway

12

0.20

2.2E-08

GOTERM_BP_5

GO:0030195 ~ negative regulation of blood coagulation

11

0.18

2.31E-08

GOTERM_BP_5

GO:0051604 ~ protein maturation

21

0.35

2.32E-08

GOTERM_BP_5

GO:0050819 ~ negative regulation of coagulation

11

0.18

8.73E-08

GOTERM_BP_5

GO:0019724 ~ B cell mediated immunity

14

0.23

2.36E-07

GOTERM_BP_5

GO:0002253 ~ activation of immune response

16

0.27

2.8E-06

GOTERM_CC_5

GO:0044444 ~ cytoplasmic part

190

3.16

4.07E-16

GOTERM_CC_5

GO:0005737 ~ cytoplasm

242

4.03

1.58E-14

GOTERM_CC_5

GO:0060205 ~ cytoplasmic membrane-bounded vesicle lumen

17

0.28

8.44E-14

GOTERM_CC_5

GO:0031093 ~ platelet alpha granule lumen

16

0.27

4.9E-13

GOTERM_CC_5

GO:0016023 ~ cytoplasmic membrane-bounded vesicle

42

0.70

1.43E-09

GOTERM_CC_5

GO:0031410 ~ cytoplasmic vesicle

44

0.73

1.16E-08

GOTERM_CC_5

GO:0030141 ~ secretory granule

22

0.37

3.97E-08

GOTERM_CC_5

GO:0048770 ~ pigment granule

16

0.27

5.49E-08

GOTERM_CC_5

GO:0000323 ~ lytic vacuole

23

0.38

9.38E-08

GOTERM_CC_5

GO:0005788 ~ endoplasmic reticulum lumen

15

0.25

1.04E-07

GOTERM_MF_5

GO:0004867 ~ serine-type endopeptidase inhibitor activity

19

0.32

5.63E-09

GOTERM_MF_5

GO:0004252 ~ serine-type endopeptidase activity

20

0.33

2.61E-06

GOTERM_MF_5

GO:0008236 ~ serine-type peptidase activity

21

0.35

3.68E-06

GOTERM_MF_5

GO:0004175 ~ endopeptidase activity

31

0.52

3.8E-06

GOTERM_MF_5

GO:0008201 ~ heparin binding

15

0.25

2.18E-05

GOTERM_MF_5

GO:0005509 ~ calcium ion binding

51

0.85

2.98E-05

GOTERM_MF_5

GO:0004869 ~ cysteine-type endopeptidase inhibitor activity

7

0.12

0.010385

GOTERM_MF_5

GO:0051920 ~ peroxiredoxin activity

4

0.07

0.02113

Tissues-specific analysis of mRNAs and proteins

All the known mRNAs and proteins were performed tissues-specific analysis. The results of mRNA analysis showed 8,605 of 13,895 genes were associated with 100 tissues, and were significantly correlated (Benjamini < 0.05) with 50 tissues. According to gene number, the top 5 ranking tissues were brain (3,987 genes), placenta (1,872 genes), epithelium (1,595 genes), lung (1,426 genes) and liver (1,110 genes) (Table 6 and Additional file 10). However, all the proteins were correlated with 33 tissues, and significantly correlated (Benjamini < 0.05) with only 19 tissues, including the components closely relative tissues of milk, such as plasma, blood, milk and mammary gland. More interestingly, the top five enriched tissues were liver (138 proteins), placenta (128 proteins), skin (75 proteins), lung (74 proteins) and plasma (73 proteins), and the highly correlated tissues were plasma, liver and milk (Table 7 and Additional file 8). These results suggest that mRNAs and proteins in porcine milk exosomes may have originated from multiple tissues.
Table 6

mRNAs expressed in a tissue-specific manner

Category

Term

Count

%

Benjamini

UP_TISSUE

Epithelium

1,595

1.40

1.77E-68

UP_TISSUE

Placenta

1,872

1.65

2.06E-44

UP_TISSUE

Skin

1,079

0.95

1.66E-38

UP_TISSUE

Uterus

1,021

0.90

4.31E-35

UP_TISSUE

Brain

3,987

3.51

5.68E-34

UP_TISSUE

Lung

1,426

1.25

1.43E-28

UP_TISSUE

Cervix carcinoma

255

0.22

3.19E-19

UP_TISSUE

Muscle

492

0.43

7.94E-18

UP_TISSUE

Liver

1,110

0.98

9.72E-16

UP_TISSUE

Lymph

400

0.35

1.43E-13

UP_TISSUE

Fetal brain cortex

153

0.13

2.22E-13

UP_TISSUE

Eye

582

0.51

4.51E-13

UP_TISSUE

Platelet

338

0.30

4.58E-13

UP_TISSUE

Bone marrow

431

0.38

4.91E-13

UP_TISSUE

Cervix

308

0.27

7.3E-13

UP_TISSUE

Cajal-Retzius cell

137

0.12

3.21E-11

UP_TISSUE

Colon

642

0.56

1.35E-10

UP_TISSUE

Urinary bladder

137

0.12

1.06E-09

UP_TISSUE

B-cell lymphoma

93

0.08

7.21E-09

UP_TISSUE

Colon carcinoma

124

0.11

7.39E-09

UP_TISSUE

T-cell

199

0.17

2.83E-08

UP_TISSUE

Umbilical cord blood

197

0.17

5.14E-08

UP_TISSUE

Mammary gland

240

0.21

6.05E-08

UP_TISSUE

Ovary

452

0.40

4.35E-07

UP_TISSUE

Kidney

765

0.67

1.81E-06

UP_TISSUE

Pancreas

519

0.46

4.43E-06

UP_TISSUE

B-cell

160

0.14

6.34E-05

UP_TISSUE

Teratocarcinoma

297

0.26

0.000105

UP_TISSUE

Adipose tissue

108

0.09

0.000142

UP_TISSUE

Human small intestine

51

0.04

0.001389

UP_TISSUE

Melanoma

176

0.15

0.001846

UP_TISSUE

Leukemia

46

0.04

0.001979

UP_TISSUE

Keratinocyte

80

0.07

0.003529

UP_TISSUE

Ovarian carcinoma

90

0.08

0.00707

UP_TISSUE

Fetal kidney

106

0.09

0.007677

UP_TISSUE

Renal cell carcinoma

42

0.04

0.008965

UP_TISSUE

Umbilical vein

27

0.02

0.008996

UP_TISSUE

Pituitary

86

0.08

0.010397

UP_TISSUE

Bone

42

0.04

0.014

UP_TISSUE

Skeletal muscle

295

0.26

0.014765

UP_TISSUE

Endometrium carcinoma cell line

19

0.02

0.020668

UP_TISSUE

Embryonic kidney

48

0.04

0.021149

UP_TISSUE

Bladder

48

0.04

0.021149

UP_TISSUE

Hepatoma

128

0.11

0.021469

UP_TISSUE

Embryo

183

0.16

0.026251

UP_TISSUE

Mammary carcinoma

59

0.05

0.033882

UP_TISSUE

Breast

53

0.05

0.036028

UP_TISSUE

Hypothalamus

73

0.06

0.036155

UP_TISSUE

Dendritic cell

49

0.04

0.041269

UP_TISSUE

Fetal brain

391

0.34

0.041334

UP_TISSUE

Carcinoma

33

0.03

0.050043

Table 7

Proteins expressed in a tissue-specific manner

Category

Term

Count

%

Benjamini

UP_TISSUE

Plasma

73

1.22

3.36E-52

UP_TISSUE

Liver

138

2.30

3.01E-31

UP_TISSUE

Milk

17

0.28

2.57E-16

UP_TISSUE

Fetal brain cortex

32

0.53

6.22E-15

UP_TISSUE

Cajal-Retzius cell

30

0.50

2.98E-14

UP_TISSUE

Bile

11

0.18

6.73E-10

UP_TISSUE

Placenta

128

2.13

8.25E-09

UP_TISSUE

Urine

10

0.17

1.45E-07

UP_TISSUE

Saliva

12

0.20

6.37E-07

UP_TISSUE

Skin

75

1.25

5.48E-06

UP_TISSUE

Platelet

34

0.57

7.73E-06

UP_TISSUE

Neutrophil

7

0.12

0.000105

UP_TISSUE

Pancreas

44

0.73

0.000382

UP_TISSUE

Mammary gland

24

0.40

0.000715

UP_TISSUE

B-cell lymphoma

12

0.20

0.002124

UP_TISSUE

Blood

29

0.48

0.021296

UP_TISSUE

Adipose tissue

12

0.20

0.024482

UP_TISSUE

Colon

43

0.72

0.025496

UP_TISSUE

Ovary

32

0.53

0.047235

KEGG pathway analysis of mRNAs and proteins

Due to the incomplete porcine bioinformatics resources in software DAVID [30], we selected the human database as reference. For mRNA, only 8,605 of 13,895 genes were enriched in 63 KEGG pathways, and the top 20 pathways were involved in various substance metabolisms, degradation, signaling pathway and some diseases pathways. Interestingly, we got 83 genes in cell cycle pathways (Fig. 6a and Additional file 10). For proteins, the results showed that only 426 of the 571 proteins (known proteins) were found to be enriched using KEGG pathway in the database. These 426 proteins were enriched in 20 pathways (Fig. 6b and Additional file 8), most associated with immunity and diseases.
Fig. 6

KEGG pathway analysis. a Pathway analysis of mRNAs. b Pathway analysis of proteins

Discussions

In the present study, we totally obtained 13,895 known genes and 2,409 putative novel genes in porcine milk exosomes. It was reported 10,948 mRNA transcripts in rats whey [21] and 19,320 transcripts in bovine milk whey exosome by mRNA microarray. Moreover, in human milk, 14,070 transcripts were found in fat globules [37]. Some of milk protein genes (CSN2, CSN3 and CSN1S1), ribosome-related proteins genes (RPS18, RPL18 and RPLP1) and other genes (e.g UBA52, FABP3 and EEF1A1) were highly expressed in the previous researches [21, 37], which were in accordance with this study (Additional file 3). Furthermore, some genes such as LALBA, TPT1, SPP1 and FASN were not found in rats whey [21], bovine milk whey exosome and human milk fat globules [37]. Additionally, the randomly selected 14 mRNAs among top 50 were further confirmed using qRT-PCR. Differences of mRNAs in milk or milk exosome exist among species, possibly indicating different functions of milk among species.

One of the aims in the present study was to explore the protein content of porcine milk exosomes using proteomics. In the present study, we observed 639 proteins (Fig. 1b) including the exosomal marker proteins CD9 [38] and CD63 [39] using Western blotting (Fig. 1a), as well as the heat shock protein family members HSPA 90 B1, HSPA13, HSPA5, HSPA 9, HSPB1 and HSPCB (Additional file 4), which have been reported in previous exosome research [7, 8, 16]. The Western blotting results in our study confirmed that we successfully isolated porcine milk exosomes. Previous study using iTRAQ identified 2,971 milk proteins with 2,350 from exosomes, 1,012 from MFGM, and 748 from whey (FDR = 0.1%) [30], another study found 2,107 proteins in bovine milk exosomes, including the major exosomal marker proteins lactadherin/MFGE8 and TSG 101 (FDR = 0.05% for proteins and 0.2% for peptides) [29], the actin family members ACTC1, ACTN1, ACTN2, and ACTN4 are cell-specific proteins likely involved in exosome biogenesis and potentially other exosome functions [7], which were also present in porcine milk exosomes. However, xanthine oxidase (~147 kDa), Butyrophilin (~59 kDa), lactadherin/MGF8 (~47 kDa) and adipophilin/perilipin-2 (~49 kDa) and MFGM were identified in bovine milk exosomes [29, 40], which were not detected in porcine milk exosomes. It has also been suggested that exosomes from different sources might contain different components [16] and may play tissue-specific roles in intracellular communication and immune function [4143].

In COG ontology analysis of mRNAs and proteins, we obtained 10 conserved proteins and 18 mRNAs relative to cell cycle. Additionally, many genes and proteins involved in cell cycle and immunity related pathways by KEGG pathways analysis. Then, we randomly selected 10 proteins for Western blotting analysis. Platelet-derived growth factor (PDGF) acts as a potential binding pattern mitogen for mesenchymal cells both in vitro and in vivo [44]. Epidermal growth factor (EGF) plays an important role in regulating cell proliferation and differentiation during development [45]. Thrombospondin1 (THBS1), cysteine-rich protein 61 (Cyr61) and connective tissue growth factor (CTGF) were all involved in the transforming growth factor-beta (TGF-β) signaling pathway [46]. High-temperature requirement A3 (HtrA3) inhibits BMP-4, BMP-2 and TGF-β1 signaling [47]. Lactoferrin (LTF) functions in inflammation [48]. Myostatin (MSTN) was a negative regulator of myogenesis and has been implicated in the regulation of adiposity and controlling the structure and function of tendons [49]. IGFBP-7 acts through autocrine/paracrine pathways to inhibit BRAF-MEK-ERK signaling and induces senescence and apoptosis in cells containing the BRAF oncogene [50]. Additionally, IGFBP-7 inhibits cell growth and induces apoptosis in RKO and SW620 cells [51]. Confirmation of the presence of these 10 proteins in porcine milk exosomes suggests a possible function in the regulation of immunity, cell proliferation and possibly other pathways.

All previously reported exosomal proteins were cytosolic, and many of them were associated with the plasma membrane or membranes of endocytic compartments [7]. Most of the genes and proteins identified in the present study were relatived to cytoplasm or cytoplasmic GO terms (Tables 4 and 5). Analysis of GO, KEGG and COG annotations suggested that most porcine milk exosome genes and proteins might function in activation, immunity and cell cycle. KEGG analysis revealed that four pathways (ECM-receptor interaction, Focal adhesion, Regulation of actin cytoskeleton and Leukocyte transendothelial migration) were enriched in both bovine [29] and porcine milk exosomes (Fig. 6b, Additional file 8). Above results indicate a similar function in different species. Additionally, recent reports showed that the bovine milk exosomes were able to exert endocytosis and transferred their contained molecules to other cells [52]. In this study, proteins in porcine milk exosome were predicated to be involved in pathways of starch and sucrose metabolism, other glycan degradation, N-Glycan biosynthesis, galactose metabolism and glycosphingolipid biosynthesis (Fig. 6b, Additional file 8), it was deduced that porcine milk exosomes might transfer encapsulated materials, which could mediated by those proteins and played key roles in different physiological and pathological conditions. Meanwhile, the KEGG analysis of mRNAs showed lots of genes enriched in Purine metabolism, Pyrimidine metabolism, Insulin signaling pathway, Cell cycle and RNA degradation pathways, which were different to predicated pathways in the KEGG analysis of porcine milk exosomes proteins.

It is reported the viral RNA (hepatitis C virus) was able to transfer to infected cells (plasmacytoid dendritic cells) and trigger an innate immune response, depending on membrane vesicle trafficking [53]. The glioblastoma cells derived-exosome could deliver a specific mRNA transcript to endothelia cells followed by generating functional proteins for patients [54]. When incubated with NIH-3 T3 cells, milk-derived microvesicles could transfer bovine milk related transcripts to living cells and affect the calf’s gastrointestinal development and immune systems [6]. Additionally, recent reports showed that bovine milk exosomes can be uptaken by endocytosis, depending on cell exosome surface glycoproteins [52].The uptaking exosome further affected gene expression [55]. And exosome can also be incorporated into differentiated human cells with containing RNA. These data collectively indicate the exosomes could not only deliver the encapsulated miRNAs, mRNAs and proteins to recipient cells, but also make their specific functions on immunity, thereafter play a key role in different physiological and pathological conditions. Our results provided extensively mRNAs and proteins data, which are beneficial to understand how milk regulates health and development of newborns by exosomes.

Conclusions

In this study, we identified 16,304 mRNAs and 639 proteins in porcine milk exosomes by RNA-sequencing and proteomic analysis, and many of mRNAs and proteins were predicted to be involved in immunity, proliferation and cellular signaling, which would be closely associated with piglets development and healthy. These findings provided a large amount of informations and contributed to increased understanding of the role of genes and proteins in milk exosomes, and build a foundation for future studies on their physiological functions and regulatory mechanisms.

Abbreviations

ACN: 

Acetonitrile

ACTC1: 

Alpha-cardiac actin one

ACTN2: 

Alpha-actin two

ACTN4: 

Alpha-actin four

AGC: 

Automatic gain control

BCA: 

Bicinchoninic acid

BMP-2: 

Bone morphogenetic protein 2

BMP-4: 

Bone morphogenetic protein 4

BP: 

Biological Process

CC: 

Cellular Component

CD24: 

Tetraspan-integrin complexes 24

CD63: 

Tetraspan-integrin complexes 63

CD9: 

Tetraspan-integrin complexes 24

COG: 

Cluster of Orthologous Groups

CSN1S1: 

Casein alpha s1

CSN2: 

Beta-casein

CSN3: 

κ-casein

CTGF: 

Connective tissue growth factor

Cyr61: 

Cysteine-rich protein 61

DTT: 

DL-Dithiothreitol

EEF1A1: 

Elongation factor 1 alpha-1

EGF: 

Epidermal growth factor

FABP3: 

Fatty-acid binding protein 3

FASN: 

Fatty acid synthase

FDR: 

False discovery rate

GO: 

Gene Ontology

HCD: 

High-energy collision dissociation

HRP: 

Horseradish Peroxidase

Hsp70: 

70-kDa heat-shock protein

HSPA 9: 

Heat shock 70kD protein 9

HSPA 90 B1: 

heat shock protein 90 kDa beta,member 1

HSPA13: 

Heat shock protein 70 kDa family, member 13

HSPA5: 

Heat shock 70 kDa protein 5

HSPB1: 

Heat shock 27 kDa protein 1

HSPCB: 

Heat shock 90kD protein beta

HTRA3: 

High-temperature requirement A3

IGFBP-7: 

Insulin-like growth factor binding protein 7

iTRAQ: 

Isobaric tag for relative and absolute quantitation

KEGG: 

Kyoto Encyclopedia of Genes and Genomes

LALBA: 

Lactalbumin alpha

LC-MS/MS: 

Liquid chromatography with tandem mass spectrometric

LTF: 

Lactoferrin

MF: 

Molecular Function

MFG: 

Milk fat globules

MFGE8: 

Milk fat globule-EGF factor 8

MFGM: 

Milk fat globule membrane

MGF: 

Mammary gland factor

MHC-class II: 

Major histocompatibility complex class II

miRNAs: 

MicroRNAs

mRNAs: 

Messager RNA

MSTN: 

Myostatin

NADH: 

Nicotinamide adenine dinucleotide

ncRNA: 

Noncoding RNA

PDGF: 

Platelet-derived growth factor

PDGFA: 

Platelet-derived growth factor A chain

PMSF: 

Phenylmethanesulfonyl fluoride

QC: 

Quality control

RIPA: 

Radio-immunoprecipitation assay

RNA-Seq: 

RNA-sequencing

RPL18: 

60S ribosomal subunit protein L18

RPLP1: 

Ribosomal phosphoprotein P1

RPS18: 

Ribosomal protein S18

rRNA: 

Ribosomal RNA

SPP1: 

Secreted phosphoprotein 1

TGFB-3: 

Transforming growth factor-beta 3

TGF-β1: 

Transforming growth factorβ1

THBS1: 

Thrombospondin1

TPT1: 

Translationally controlled tumor protein 1

TSG 101: 

Tumor susceptibility gene 101

UBA52: 

Ubiquitin A-52 ribosomal protein

Declarations

Acknowledgements

None.

Funding

This work was supported by grants from the Key Project of Guangdong Provincial Nature Science Foundation (S2013020012766), National Nature Science Foundation of China, The National Key Research and Development Program of China (2016YFD0500503) National Basic Research Program of China (973 Program, 2013CB127304), Hainan Provincial research institutes technology development key Project of China (grant number KYYS-2015-02) and Open subject of Hainan Provincial Key Laboratory of Tropical Animal Breeding and Disease Research (HNXMSYS201501). We thank the breeding farm of the Livestock Research Institute (Guangzhou, China) for providing milk samples.

Availability of data and materials

All the RNA-Seq data for analysis in this study have been deposited in https://www.ncbi.nlm.nih.gov/sra/ with an Accession No.: SSR 3436404. And the proteomics data were deposited in https://mynotebook.labarchives.com/ with a DOI: https://doi.org/10.6070/H42J68X8.

Authors’ contrib

TC, QX, JS carried out the proteins and mRNA sequencing and data analysis, and participated in drafted the manuscript. XC, RS carried out the Western blotting and q-PCR. GS, SW participated in the sample collected. XZ, NW performed the raw data analysis. RY, QJ and YZ conceived of the study, and participated in its design and coordination and helped to draft the manuscript. All authors read and approved the final manuscript.

Competing interests

The authors declare that they have no competing interests.

Consent for publication

Not applicable.

Ethics approval

The samples collected were according to the guidelines of Guangdong Province on the Review of Welfare and Ethics of Laboratory Animals approved by the Guangdong Province Administration Office of Laboratory Animals (GPAOLA). And the procedures were as the protocol of SCAU-AEC-2010-0416 approved by the Animal Ethics Committee of South China Agricultural University.

Publisher’s Note

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Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

Authors’ Affiliations

(1)
National Engineering Research Center For Breeding Swine Industry, Guandong Provincial Key Laboratory of Agro-Animal Genomics and Molecular Breeding, Guandong Province Research Center of Woody Forage Engineering and Technology, South China Agricultural University
(2)
Institute of Animal Science and Veterinary Medicine, Hainan Academy of Agricultural Sciences

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