Integrative analysis of transcriptomics and proteomics of skeletal muscles of the Chinese indigenous Shaziling pig compared with the Yorkshire breed
© The Author(s). 2016
Received: 2 November 2015
Accepted: 2 June 2016
Published: 13 June 2016
The Shaziling pig (Sus scrofa) is a well-known indigenous breed in China. One of its main advantages over European breeds is its high meat quality. However, little genetic information is available for the Shaziling pig. To screen for differentially expressed genes and proteins that might be responsible for the meat quality, the longissimus dorsi muscles from Shaziling and Yorkshire pig breeds were investigated using an integrative analysis of transcriptomics and proteomics, involving high-throughput sequencing, the two-dimensional gel electrophoresis, and mass spectrometry.
Sequencing produced 79,320 unigenes by de novo assembly, and 488 differentially expressed genes in the longissimus dorsi muscle of Shaziling pig compared with the Yorkshire breed were identified. Gene Ontology term enrichment of biological functions and Kyoto Encyclopedia of Genes and Genomes analysis showed that the gene products were mainly involved in metabolism, protein binding, and regulation of skeletal muscle development. At the protein level, 23 differentially expressed proteins were identified, which were potentially associated with fatty acid metabolism, the glycolytic pathway, and skeletal muscle growth. Eight differentially expressed genes were confirmed by real-time PCR. These results give an insight into the mechanisms underlying the formation of skeletal muscle in the Shaziling pig.
Certain differentially expressed genes and proteins are involved in fatty acid metabolism, intramuscular fat deposition, and skeletal muscle growth in the Shaziling pig. These results provide candidate genes for improving meat quality and will promote further transcriptomic research in Shaziling pigs.
Pigs are important domestic animals used for meat production worldwide. Pork quality is influenced by many factors, including breed, nutrition, and post-slaughter handling . Among these factors, the breed is the most important. There are more pig breeds in China than in any other country in the word . In China, 118 indigenous pig breeds are listed as the Domestic Animal Diversity in the World index . Over a long period, breeders have attempted to increase muscle yield and decrease carcass fatness, and great progress for these traits has been made in swine breeding. For example, Landrace pigs and Yorkshire pigs grow more quickly and have higher lean meat than other pig breeds. However, some studies suggest that such intensive selection for increased muscle growth and decreased carcass fatness has led to a deterioration in meat quality [4–6]. Compared with European breeds, Chinese native breeds have higher intramuscular fat (IMF), and increased tenderness and meat quality [7–10]. The Shaziling pig is a well-known breed, which has evolved for centuries in Hunan Province, China, where it feeds on grains, tubers, and wild herbs. It is a Chinese fat-type line with high IMF, superior meat quality, and strong resistance to general diseases. Compared with the Shaziling breed, the Yorkshire has a faster growth rate and a leaner meat ratio.
Skeletal muscle contains several fiber types . Muscle fiber types and the proportion of fiber types affect meat quality directly . Therefore, studies on development and growth are beneficial to improve meat quality. Skeletal muscle development is very complicated, and comprises several stages: determination of myoblasts, proliferation of myoblasts, differentiation and fusion of myoblasts into myotubes and myofibers, and growth and maturation [13, 14]. Analyzing these stages would provide a good basis for understanding muscle fiber development. Previous reports showed that muscle fibers could be classified into red and white fibers . These compositional differences between fibers determine their distinct metabolic type and physiological functions and affect meat quality [16, 17]. Skeletal muscles have been explored extensively using molecular biology [18, 19], and proteomics and transcriptomics techniques have been applied to study the porcine skeletal muscle of different breeds [20, 21].
Over the past decade, proteomic technologies have been used successfully to study skeletal muscle [11, 22]. Proteomic analysis based on two-dimensional gel electrophoresis (2-DE) and mass spectrometry (MS) is a classical method in quantitative proteomics to separate mixtures of proteins into two dimensions and has been a powerful tool in meat science [23, 24]. Many reports concerning differential proteomics among different pig breeds have been published [25–27]. Another technology for characterizing molecular changes in skeletal muscle is analysis of the transcriptome. Recently, transcriptome studies have been applied to analyze differentially expressed genes (DEGs), identify novel genes, describe metabolic pathways, and forecast the relationship between genotypes and phenotypes [28–30]. Next-generation sequencing technology has provided a new tool to quantify transcriptomes and analyze gene expression on a global scale. Transcriptional and proteomic methods could be used to analyze the changes from the mRNA expression to the protein abundance. In addition, post-transcriptional regulation is very important for mRNA stability, translation initiation, and protein stability . Thus, it is necessary to combine proteomic and transcriptional methods simultaneously to analyze skeletal muscle growth and development. Currently, several reports have presented results of both proteomic and transcriptional analyses. For instance, longissimus dorsi muscle (LM) proteome and transcriptome profiles of Yorkshire pig and Casertana pig breeds were compared using 2-DE and a microarray. As a result, a large number of genes were identified that are involved in glycolytic metabolism and skeletal muscle growth . In addition, Kim et al.  also compared the LM proteome and transcriptome profiles of different pig breeds using 2-DE and a microarray.
In the present study, we performed transcriptomic and proteomic analyses, along with functional enrichment of Gene Ontology (GO) terms and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis, to characterize the expression profiles in the LM of Shaziling and Yorkshire pigs. The aim of this study was to reveal the differences in breed-related protein and transcript expression patterns between the two breeds. These results could provide an insight into the mechanisms of growth and development of porcine skeletal muscle.
Three 25-day-old, male full-sibs for each of Shaziling pigs and Yorkshire pigs were slaughtered following the Animal Care Guidelines of the Ethics committee of Hunan Agricultural University. Samples of LM were collected from the same area of the ribs and placed in liquid nitrogen immediately. All samples were kept at −80 °C after collection until used.
The frozen LM tissues (100 mg) from Shaziling pigs and Yorkshire pigs were crushed in a mortar containing liquid nitrogen and were then sonicated for 10 s using a Sonoplus (Bandelin Electronic, Berlin Germany). The crushed tissue was homogenized in 1 mL of cold dissolution buffer containing 7 M urea, 2 M thiourea, 1 % dithiothreitol (DTT), 4 % (w/v) CHAPS, 20 μL protease inhibitor cocktail (BBI, Canada), and 2 % (v/v) pharmalyte (pH 3–10; BioRad, Hercules, CA, USA). The homogenate was centrifuged at 15,000 × g, for 20 min at 4 °C. The supernatant fraction was filtered and kept at −80 °C for subsequent analysis. The total protein content was determined using a Bradford assay kit (Bio-Rad).
2-DE and images analysis of gel
Approximately 100 μg of extracted protein was diluted with rehydration buffer [8 M urea, 2 M thiourea, 50 mM DTT, 4 % (w/v) CHAPS, and 0.5 % carrier ampholytes (pH 3–10, Bio-Rad)]. The mix was loaded onto 13-cm, nonlinear, immobilized pH gradient strips (IPG, pH 3–10; BioRad), which were rehydrated overnight. After rehydration, first-dimension isoelectric focusing was carried out at 20 °C at 30 V for 12 h, 500 V for 1 h, 1000 V for 1 h, and then gradually increased to 8,000 V. Isoelectric focusing was performed using an Ettan IPGphor III system (GE Healthcare, USA) gel apparatus. The focused IPG strips were incubated for 15 min in equilibration buffer containing 6 M urea, 50 mM Tris–HCl, pH 8.8, 30 % glycerol, 2 % sodium dodecyl sulfate (SDS), and 1 % DTT. Then, strips were then incubated again for 15 min in a buffer containing 6 M urea, 50 mM Tris–HCl, pH 8.8, 2 % SDS, 30 % glycerol, and 4 % iodoacetamide. In the second dimension, the equilibrated IPG strips were placed onto SDS polyacrylamide gels (12.5 % T, 2.6 % C) for protein separation using the Ettan DALT six electrophoresis system (GE Healthcare). When the bromophenol blue dye front reached the bottom of the gel, electrophoresis was stopped and analytical gels were subjected to silver staining and Coomassie blue was used to stain preparative gels before identification by MS. Each sample was analyzed in triplicate.
Spot choosing and tryptic digestion
Gel images were scanned using an Image Scanner UMax Powerlook 2110XL (GE Amersham) and analyzed using Image Master 2D Platinum software Hofer SE 600 (Version 5.0; GE Amersham). The protein spots were compared automatically using the software, including matching and quality. Spots whose average density was different by more than 1.5-fold between the two pig breeds were analyzed and marked. The differentially abundant spots were cut out from the preparative gel carefully and washed twice with 200 μL of 50 mM ammonium bicarbonate with 50 % acetonitrile and incubated for 15 min at room temperature. The gel pieces were swollen in a digestion solution containing 5 μL of 25 mM ammonium bicarbonate and 10 ng of trypsin at 4 °C for 30 min; in-gel tryptic digestion was run overnight at 37 °C. Subsequently, the supernatant was extracted twice with solvent A (80 % acetonitrile, 0.1 % trifluoroacetic acid) for 15 min at 3 °C. Finally, the digested tryptic peptides were passed through a Zip-Tip to remove salts, according to the manufacturer’s protocol.
The samples were stored at −70 °C before analysis by MALDI-TOF/TOF. Protein identification was performed using a 5800 MALDI-TOF/TOF mass spectrometer (AB SCIEX) according to the manufacturer’s instructions. Mass spectra were acquired in reflector mode, and recorded in the range of 800–4,500 Da. Eight of the most intense ion signals were selected as precursors for the acquisition of MS/MS. The resulting peptide masses were submitted into the database of the National Center for Biotechnology Information non-redundant (NCBI nr) and the Swiss-Prot database using the Mascot server (Matrix Science, London, UK) to identify proteins. The search parameters were set at ± 100 ppm for peptide-mass mapping (PMF), peptide tolerance and ± 0.4 Da for the MS/MS tolerance.
RNA isolation and transcriptome analysis
Total RNA was extracted from the LM of the two breeds of the pig using the total RNA extraction kit (Qiagen, Valencia, CA, USA), in accordance with the manufacturer’s instructions. The RNA quantity and integrity were checked using a NanoDrop 2000 spectrophotometer and bioanalyzer 2100 (Agilent Technologies, Santa Clara, CA, USA). A TruSeq RNA Sample Preparation kit v2 (Illumina, San Diego, CA, USA) was used to construct cDNA libraries. Subsequently, the libraries were sequenced using an Illumina HiSeq 2500 instrument (Illumina, San Diego, CA, USA) that generated paired-end reads of 100 bp.
De novo assembling and functional annotation of reads
Raw sequencing reads of each sample were trimmed and assembled de novo using CLC Genomics Workbench (CLC Bio, Aarhus, Denmark). After the adapter sequences, ambiguous bases and sequences less than 20 nucleotides were removed, credible contigs generated by de novo sequence assembly. The assembled contigs were annotated against the UniProt and NCBI non-redundant (nr) database using BlastX alignment with an E-value cut off of <1e-5. Based on the annotation results, GO terms were extracted using Blast2GO (http://www.blast2go.com) and the results were classified as biological processes, cellular components, and molecular functions. The EuKaryotic Orthologous Groups (KOG) and KEGG databases were used to predict the functions and define the main metabolic pathways, separately.
Gene expression quantification and differential expression analysis
The expression level of each gene was calculated using the reads per kb per million reads values by the Qualimap v0.5 software . The DEGseq program  and R packages were used to identify significantly DEGs between Shaziling pigs and Yorkshire pigs. In this study, the criteria were a fold change (FC) greater than two and cut-off of the false discovery rate of 5 %. For the unigenes that were considered as having differential expression, GO functional enrichment was carried out when the P value was less than 0.05. DEGseq provides statistical routines for determining DEGs.
Validation of DEGs by quantitative real-time PCR (qPCR)
Primer sequences for the quantitative real-time PCR amplification of the differential expressed genes in Shaziling and Yorkshire pigs
Primer sequences (5′-3′)
GenBank sequence no.
Results and discussion
Identification of differentially abundant proteins by 2-DE and MS
Protein differentially expressed for Shaziling pig breeds and Yorkshire were identified by 2-DE and MALDI-TOF-MS/MS
NCBI accession number
Mr, kDa theor
No. of peptides identified
Up-regulated in Yorkshire pigs
mitochondrial ATP synthase, H+ transporting F1 complex beta subunit, partial, ATP5B
PREDICTED: NADH dehydrogenase ubiquinone flavoprotein 2 isoform X1
heat shock protein beta-1
Chain B, Structure Determination Of Aquomet Porcine Hemoglobin At 2.8 Angstrom Resolution
PREDICTED: alpha-crystallin B chain isoform X2
Chain A, High Resolution X-Ray Structures Of Pig Metmyoglobin
Chain A, High Resolution X-Ray Structures Of Pig Metmyoglobin
cytochrome c oxidase subunit 5B, mitochondrial precursor
Chain B, Structure Determination Of Aquomet Porcine Hemoglobin At 2.8 Angstrom Resolution
Up-regulated in Shaziling pigs
keratin, type I cytoskeletal 10 isoform X2
PREDICTED: fibrinogen beta chain isoform X2
triosephosphate isomerase 1
Triosephosphate somerase 1
PREDICTED: pyruvate dehydrogenase protein Xcomponent-like isoform
PREDICTED: actin, alpha cardiac muscle 1 isoform X1
Triosephosphate isomerase 1,TPI1
A-FABP adipocyte fatty acid-binding protein
PREDICTED: alpha-enolase isoform X1
HSPB1 heat shock protein beta-1
PREDICTED: beta-enolase isoform X1
PREDICTED: 14 kDa phosphohistidine phosphatase isoform X2
triosephosphate isomerase 1
troponin T fast skeletal muscle type
PREDICTED: fibrinogen beta chain isoform X2
triosephosphate isomerase 1
HSPB1 heat shock protein beta-1
PREDICTED: troponin T, slow skeletal muscle isoformX1
actin, alpha skeletal muscle
Function analysis of differentially expressed proteins
Enolase 3 was another metabolic enzyme that was differentially abundant between the two breeds. Enolase 3 is a crucial enzyme in glycolysis that catalyzes the interconversion of diphosphoglycerate and phosphoenolpyruvate. Pig muscle Enolase 3 was investigated some time ago . Many isoforms of Enolase 3 have been confirmed to have an influence on IMF in pigs [20, 40].
Muscles are composed primarily of different muscle fibers. Muscle fiber type is an important factor influencing meat quality . For example, increasing the percentage of type IIb fibers could lead to the reduced meat quality because of altered metabolic rates and biochemical processes . ACTA1 is a member of the actin family and is a major constituent of the contractile apparatus in skeletal muscle. Previous reports showed that alpha-actin levels positively correlate with the synthesis of muscle fiber proteins and muscle growth . In this study, ACTA1 was differentially abundant between the two pig breeds.
Heat shock proteins (HSPs) including HSPA1, HSPA8, HSPB1, and other chaperone proteins have been associated with pig meat quality [44, 45]. In the present study, HSPB1 was more abundant in the Shaziling pig compared with the Yorkshire pig. This observation suggested that HSPB1 is correlated with meat quality. In addition to tenderness, further research is needed to confirm whether the IMF content of meat is affected by the expression of HSPB1.
Illumina sequencing and de novo assembly
Statistical summary of the longissimus dorsi muscle transcriptome for assembling
Average length (bp)
Longest length (bp)
Total length (bp)
Functional annotation of longissimus dorsi transcripts
Functional annotations using transcript BLAST analyses
Hit unigenes number
Percentage (hit/total) %
Annotated in nr
Annotated in UniProt
Annotated in GO
Annotated in KOG
Annotated in KEGG
Functional classification of unigenes
Identification and analysis of DEGs
Correlation analysis of mRNA and protein expression
RNA-seq analyses identified 488 DEGs (Additional file 3: Table S3), of which 297 were upregulated in the Shaziling pig and 192 in the Yorkshire pig. Proteomics revealed identified 38 differentially abundant proteins, of which 27 protein spots were upregulated in the Shaziling pig and 11 in the Yorkshire pig. Similar to previous reports, the transcriptomics and proteomics data were divergent. In the present study, ENO1 and ACTC1 were overexpressed in Shaziling pigs, and ATP5B was overexpressed in Yorkshire pigs: only for these three genes were the proteomics results consistent with the transcriptomic results. In 2009, Timperio and colleagues performed a comparative analysis of proteomics and transcriptomics from the livers of Chianina and Holstein Friesian cattle. The results indicated that only three of 39 differentially abundant proteins were validated by microarray analyses . Other research also confirmed that proteomics and transcriptomics data seldom overlap . These differences were probably caused by alternative splicing, differential regulation of translation, and annotation errors of databases . Another aspect concerning little overlap between transcriptomics and proteomics data is biological factors . Although proteomics and transcriptomics data have almost no overlap, interaction pathway analyses could indicate shared biological significance . Taking this into consideration, the differentially abundant proteins and DEGs that converged in the same metabolic pathways, especially regulation of skeletal muscle development, were meaningful. Some of the proteins and upregulated gene transcripts in Shaziling pigs were found to be involved in the same metabolic pathways, particularly the glycolytic pathway (ENO1, TPI1, and HSPB1). ENO1, a glycolytic enzyme, is positively correlated with meat tenderness . TPI is also a glycolytic enzyme, and has been shown to correlate with meat tenderness in porcine muscles . Notably, although the TPI1 result of proteomics and transcriptomics data did not match, pathway analyses of either DEG transcripts or proteins for the Shaziling samples were involved in a metabolic network. HSP proteins are related to protein folding and the oxidative stress response. In our research, HSPB1 was overexpressed in Shaziling pigs, and might be positively correlated with meat quality, which agreed with previous studies [61, 62]. Shaziling pigs have excellent meat quality like other Chinese indigenous pig breeds. The IMF content in Shaziling pigs is 3.5 %, in Jinhua pigs it is 3.38 %, and in Lantang pigs it is 2.46 %. By contrast, Yorkshire pigs and Landrace pigs have IMFs of 1.79 % [7, 63]. Increased IMF content can improve meat quality significantly, especially in terms of tenderness . According to our results, genes related to tenderness have a higher level of expression in Shaziling pigs than in Yorkshire pigs, for example TPI1, HSPB1, and ENO1. Further analysis of the DEGs identified a number of novel genes and pathways (Additional file 1: Tables S1, Additional file 2: Table S2 and Additional file 3: Table S3), which have not been reported to affect meat quality previously. Further characterization of these novel genes might reveal the regulatory mechanism underlying meat quality.
The object of this study was to investigate differences in the growth and development of skeletal muscle between Shaziling and Yorkshire pigs. The combined use of proteomic and transcriptomic analyses was effective in detecting DEGs and proteins. As a result, 38 differentially abundant proteins and 488 DEGs were identified by mass spectrometry and RNA-seq analysis, respectively. Some of the proteins and unigenes are associated with lipid metabolism or glycolytic metabolism, according to previously published results. Based on the putative results of GO term enrichment and KEGG pathway analyses, we determine that many of the differential abundant proteins and DEGs are related to lipid mobilization, energy metabolism, the cytoskeleton, and signal transduction. Our study provided valuable information that could contribute to a deeper understanding of the molecular mechanisms regulating the development and formation of skeletal muscle.
2-DE, two-dimensional fluorescence difference gel electrophoresis; DEGs, differentially expressed genes; GO, gene ontology; IMF, intramuscular fat; KEGG, Kyoto Encyclopedia of Genes and Genomes; LM, longissimus dorsi muscle; MS, mass spectrometry; NGS, next-generation sequencing; qPCR, quantitative real-time PCR
We would like to thank LY for exceptional assistance in the qPCR and DX in collection of samples of pig tissue.
This study was supported by the National High Technology Research and Development Program of China (2011AA100304), the Provincial Natural Science Foundation of Hunan (13JJ1021) and Science and technology project of hunan province (2014NK4135).
Availability of data and materials
The sequencing data from this study has been archived at the NCBI Sequence Read Archive under GEO database [GSE:70673].
HY performed analysis of the transcriptomics and proteomics and drafted the manuscript. XX and JJ participated in the biological experiments and data analysis. HM managed the whole project. All authors read and approved the final manuscript.
The authors declare that they have no competing interests.
Consent for publication
Ethics approval and consent to participate
The experiment and all its procedures were reviewed and approved by the Institutional Animal Care and Use Committee (IACUC) at Hunan Agricultural University.
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.
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