Integrative transcriptomics and proteomics analysis of longissimus dorsi muscles of Canadian double-muscled Large White pigs

Gene 577 (2016) 14–23

Contents lists available at ScienceDirect

Gene journal homepage: www.elsevier.com/locate/gene

Research paper

Integrative transcriptomics and proteomics analysis of longissimus dorsi muscles of Canadian double-muscled Large White pigs Shuqin Liu 1, Wenpeng Han 1, Shunyan Jiang, Chunjiang Zhao ⁎, Changxin Wu College of Animal Science and Technology, China Agricultural University, Beijing 100193, China

a r t i c l e

i n f o

Article history: Received 27 August 2015 Received in revised form 28 October 2015 Accepted 9 November 2015 Available online 18 November 2015 Keywords: Double-muscled Large White pig Longissimus dorsi Microarray Proteomics Muscle development

a b s t r a c t Canadian double-muscled Large White pigs are characterized by notable muscle mass, showing high daily gain and lean rate and good meat quality. In order to identify the major genes or proteins involved in muscle hyperplasia and hypertrophy, three pairs of full-sib pigs with extreme muscle mass difference from Canadian Large White were selected as experimental animals at 3 months age. The phenotypic differences of longissimus dorsi muscles (LD) were investigated with microarray and proteomics (2-DE, MALDI-TOF-MS), and results were verified by real-time PCR and western bolting respectively. The gene expressing profiling identified 57 and 260 and 147 differently expressed genes (DEGs) from the three pairs respectively with Bayesian statistics and significant analysis of microarrays (SAM) (p b 0.05, q b 0.05, fold N 2). From the network of these DEGs, some major genes were displayed, such as EGF, PPARG, FN1, SERPINE1, MYC, JUN, involved in Wnt, MAPK and TGF-β signal pathway respectively, which mainly participated in cell differentiation and proliferation. In parallel, proteomics analyses revealed 50 differently expressed protein (DEP) spots with mass spectrum, and 33 spots of them were found annotated, which took part in energy metabolism and the structure and contraction of muscle fiber. In brief, our integrated study provides a good foundation for the further study on the genetic mechanism of the double muscle traits in pigs. © 2015 Elsevier B.V. All rights reserved.

1. Introduction Pigs are an important source of meat worldwide (Ramayo-Caldas et al. 2012). Traits on skeletal muscles, which are important components of lean meat, are always concerned by breeders and farmers. Muscle development is a complicated process. Muscle arises from the embryonic mesoderm, which differentiates into muscle fibers subsequently (Te Pas et al. 2005; Tang et al. 2007), and the increase of length and girth of the muscle fibers leads to the postnatal growth of muscle (Muráni et al. 2007). Double muscle traits, characterized with the dramatic increase in both skeletal muscle fiber number (hyperplasia) and

Abbreviations: LD, longissimus dorsi muscles; 2-DE, two-dimensional electrophoresis; MALDI-TOS-MS, matrix-assisted laser desorption ionization time of flight mass spectrometry; DEG, differently expressed gene; SAM, significant analysis of microarrays; MAPK, mitogen-activated protein kinase; TGF-β, transforming growth factor beta; DEP, differently expressed protein; BSA, bovine serum albumin; cDNA, complementary DNA; DTT, 1, 4dithiothreitol; DM, double-muscled pig; MyHC, myosin heavy chain; MyHC IIB, myosin heavy chain IIB; PAGE, polyacrylamide gel electrophoresis; Real-time PCR, real-time fluorescent quantitative PCR; RT-PCR, reverse transcription PCR; NM, normal-muscled pig; IGF-I/II, insulin-like growth factor I/II; SDS-PAGE, sodium dodecyl sulfate-polyacrylamide gel electrophoresis; SNP, single nucleotide polymorphism; Tris, trihytroxymethyl amino methane; μg, microgram; μl, microliter; Mg, milligram. ⁎ Corresponding author. E-mail address: [email protected] (C. Zhao). 1 The first two authors contributed equally to this work.

http://dx.doi.org/10.1016/j.gene.2015.11.016 0378-1119/© 2015 Elsevier B.V. All rights reserved.

mass (hypertrophy) were also attracted a lot of interests of genetic studies. In previous studies, many candidate genes such as Myostain, Callipyge and insulin-like growth factor 2 (IGF2) have been determined as major genes affecting muscle development (Grobet et al. 1997; Lien et al. 1999; Headey et al. 2004). However, double muscle traits as one form of muscle hypertrophy were firstly identified and studied in bovines, which is caused by mutations in myostatin (MSTN) gene (McPherron and Lee 1997). The discovery of major gene MSTN makes a tremendous step for other double-muscled species (Kijas et al. 2007; Mosher et al. 2007; Hill et al. 2010). In recent years, studies about pig double muscle trait also have acquired some achievements (Van Laere et al. 2003; Wimmers et al. 2006). A previous study indicated that pig MSTN gene mediated mesoblastic cells differentiating into muscle cells and associated with birth weight and the number of muscle fibers (McCall et al. 1996), and the gene is highly conservative and can be served as one of the candidate genes for studying muscle growth and development and fat deposition of Luchuan pig (Huang et al. 2014). Unlike double-muscled cattle and Callipyge sheep, the double-muscled phenotype in pigs is not a stably heritable trait, and full-sibs from double-muscled parents exhibit a variation in muscle mass traits, which may be attributed to that the trait was regulated by multi-genes. In addition, researchers previously found two major genes, Rynodine receptor (RYR1) gene and Rendement Naploe (RN), which were similar to the genes regulating

S. Liu et al. / Gene 577 (2016) 14–23

15

Table 1 Primers for real-time PCR. Primer MYO1b ABCF2 ATP5C1 CXCL9 Neuritin CYP3A CKM CRYAB PGM1 PYGM TNNT3 ENO3 MRLC2 HSPB1 GAPDH

Sequence (5′ to3′) F: TTTCTGCCAAGTATTGTTTCC R: CACCCTGTACTAATCACCTCTCT F: TTCTGACCTGATAGCGATGC R: TCACCCAAACCCAGCAAA F: TCTTCTCCCTTGATACCGTTGC R: TCTGCTCACTCGTGGTGGACT F: AGTGTTGCCTTGCTTTTGGGTAT R: TCCTTTGGCTGGTGTTGATGC F: AATTCACGCTCACGTCTTTCTAA R: TTCTGGCAGCCGTACCTCTA F: TGCTGCTAGACTTGAGAGGG R: GGGCAGGTAAGTGTAAGGATT CAAGCATCCCAAGTTCGAG CTTCTTCTCCATCTCCACCAT GACCCTCTCACCATTACTTCA CAGCAGGCTTCTCTTCACG CTGTCCTTGCTTGGCTCTC TTCCACCTCTTCGTAATCGT CCCAGTATGCCAGGGAGAT CTGAGGGATTGCGAACAGA CCTCAACATCGACCACCTC CTTCAGCTTCTCCCCGTAC CCTCACAGTCACCAACCCTAA GATGAACGTGTCCTCCGTCTC GTGTTATTCCGTTTTATTTCCC TTTACAACCTCATCCCCATTT CCTGTCACTTTCGAGGCG AGGTGGGGATGGCTGGT CTACTCGGGCCTCTTCTGTG GATTCTCCCGATCAGTCAGC

qualitative traits. Individuals with n/n homozygote genotype of RYR1 had larger eye muscle area than those with M/M and M/n (Zhu et al. 2002). RN gene carrier is superior to the homozygous recessive on growth rate, lean percentage, backfat thickness and eye muscle thickness. Moreover, insulin-like growth factor (IGF) gene and calcineurin gene were also regarded as candidate genes of double muscle trait of pigs (Dunn et al., 1999; Shannon et al., 2000). But the detailed pathways regulating pig double muscle traits still remain unclear. In this study, we applied microarray technique to obtain double muscle DEGs and 2-DE technology to investigate the DEPs from three pair fullsibs, which consisted of pigs with significant difference on muscle mass in each pair. The integrative transcriptomics and proteomics analysis provides new insight into the genetic mechanism of pig double muscle traits. 2. Materials and methods 2.1. Sample collection All animals used in this study were treated according to International Guiding Principles for Biomedical Research Involving Animals. In Beijing Shunxinlong Limited Liability Company, 3 pairs of 3-month-old Canadian Large White full sib boars with distinct muscle mass difference were selected based on selection model D (Lee and MacLean 2011; Liu, 2010). Double muscular trait was exhibited during first 2 to 5 months after born (Xiao and Lai 1999), and this character was more apparent in boars than sows, so we chose 3-month-old full sib boars as experimental animals. According to the results of the phenotypic data analysis, we chose three pair full-sibs with most striking difference among all of the samples. The muscle samples were removed from LD muscle just after slaughter and immediately frozen in liquid nitrogen and stored at −80 °C.

Size (bp)

Tm (°C)

187

60

110

60

144

60

109

60

168

60

196

60

190

60

121

60

100

60

125

60

112

60

184

60

164

60

168

60

112

60

was assessed by electrophoretic analysis of 28S and 18S rRNA subunits, and purity and concentration were measured with Nanodrop and preserved at −80 °C. 2.3. Microarray hybridization and data analysis The cDNA synthesis and purification, cRNA in vitro transcription (IVT) and hybridization were carried out according to the Affymetrix Expression Analysis Technical Manual. Specimens from three different areas at the same LD were used as technical replicates. Hybridization images were scanned with SCAN3000 (Affymetrix) and normalized with Affymetrix GeneChip Operating Software (GCOS 1.2). In order to identify DEGs, normalized expression data was analyzed with Bayesian Statistics (p b 0.05) and SAM (fold ≥ 2, FDR b 0.05). To identify similar expression patterns, gene expression data were processed with hierarchical clustering (HAC) by centroid Cluster 3.0 and TreeView softwares, and k-mean clustering was set 10 expression patterns. 2.4. Protein samples Frozen muscle tissue (approximately 0.5 g per sample) was ground to fine powder in liquid nitrogen and incubated for 30 min in lysis buffer with PMSF (100 mmol/L), then incubated for 30 min after adding 100 mg DTT. Nucleic acid in the samples was broken by 200 W ultrasonic wave for 12 times, and each time lasted 7S and the interval was also 7S. Broken samples were centrifuged at 12,000 rpm for 60 min and the resulting supernatants were used for protein extract. Protein concentration was measured with protein assay system (Bio-Rad) and BSA as the standard and stored at −80 °C. 2.5. Two-dimensional electrophoresis and data analysis

2.2. RNA samples Total RNA was extracted from frozen tissues (approximately 100 mg per individual) using RNeasy Tissue Mini Kit (QIAGEN). RNA integrity

Protein samples (1.2 mg, 3 technical replicates per sample) for preparative gel were applied on 17 cm immobilized pH gradient (IPG, Bio-Rad) strips (3–10 nonlinear). IPG strips were rehydrated overnight

16

S. Liu et al. / Gene 577 (2016) 14–23

Fig. 1. Distribution of DEPs in longissimus dorsi between double-muscled (DM) and normal-muscled (NM) pigs. 1.2 mg protein loaded. 1D: 17 cm, pH 3 ~ 10 NL. 2D: 12% SDS-PAGE. Colloidal Coomassie Brilliant Blue Staining.

with rehydration solution containing 1% DTT, 0.5% (V/V) Bio-lyte (BioRad). After rehydration, isoelectric focusing (IEF) was performed as 250 V (30 min), 1000 V (2 h) and 8000 V (5 h). Then IPG strips were incubated for 15 min with 5 ml of equilibration solution I (50 mM Tris–HCl (pH 8.8), 6 M urea, 2% SDS, 20% glycerol, 2% DTT) and equilibration solution II (50 mM Tris–HCl (pH 8.8), 6 M urea, 2% SDS, 20% glycerol, 2.5% IAA). The IPG strips were transferred onto 12% SDS-polyacrylamide gels and the electrophoresis was performed as 60 V (1 h), 120 V (1 h), 250 V (5 h) until the dye front reached the bottom of the gel. After electrophoresis, strips were washed with deionized water and fixed 30 min and stained with Coomassie brilliant blue (CBB) for 16 h. Stained gels were digitalized using UMAX scanner (UMAX, Taiwan) and the obtained images were analyzed using ImagerMaster2D Platinum Software Version5.0 (GE Healthcare, USA) to determine the number and position of protein spots. Spots differentially expressed greater than 1.5-fold were selected for gel extraction and enzymatic digestion. After enzymatic digestion, the peptide solution was used for analysis. The analysis of MALDI-TOF was performed using AUTOFLEX IITOF (Bruker Daltonics, Germany) to get peptide mass fingerprinting (PMF). Internal calibration of samples was achieved using trypsin

autolysis peptides with protonated masses of 2166.333 and 2273.434. Then Mascot Distiller (MatrixScience) was employed to match proteins in NCBInr database (http://www.matrixscience.com). 2.6. Gene ontology and network analysis In an initial experiment, the DEGs and DEPs were examined in DAVID Bioinformatics Resources (http://david.abcc.ncifcrf.gov/) to obtain gene ontology (GO) consortium functional annotations and classifications (Dennis et al. 2003; Huang et al. 2009). In order to avoid false positive categories, the significant level was set as 0.05 (P b 0.05). Networks were built with the screened genes and proteins using STRING (http://string-db.org/) (Jensen et al. 2009), in which some major genes (proteins) were displayed. 2.7. Real-time PCR and western bolting Microarray results for the transcript profiling experiments were validated by real-time PCR. The first six genes in Table 1 were randomly selected for the validation. And all primers including those for amplifying

S. Liu et al. / Gene 577 (2016) 14–23

17

Table 2 Differential proteomics analysis from double- and normal-muscled groups. Serial number 1030

N

Protein name

1 2

4 1 1

HUMMLC2B Myosin regulatory light chain 2 (MRLC2/MYL2) Myosin light chain phosphorylatable fast skeletal muscle protein Skeletal muscle myosin regulatory light chain 2 Hsp27 (HSPB1) Myosin light chain 2 V (MLC2v)

1

Heat shock protein beta-1 (HSPB1)

1

MLC2v Myosin regulatory light chain (MRLC) ventricular isoform

3 3101 3102 3102 (8–9) 3105

2

Taxonomic source

Accession number

Mw/kD

pI

No. of peptides identified

Score

Expression level DM N NM

[Sus scrofa] [Sus scrofa]

gi|117660856 gi|54111519

19.06635 19.0804

4.82 4.9

15 15

235 233

[Sus scrofa]

gi|106635861

19.05039

4.9

14

208

[Sus scrofa] [Sus scrofa] [Sus scrofa] [Canis lupus familiaris] [Sus scrofa]

gi|59803752 gi|55668280 gi|21261724

10.70427 22.98471 18.8794

4.8 6.23 4.86

9 6 7

145 92.6 93.9

DM N NM DM N NM

gi|50979116

22.92466

6.23

6

86.1

DM b NM DM N NM

[Sus scrofa]

gi|117661254

16.86235

4.57

7

119

gi|21314557

18.8794

4.86

6

95.8

gi|50979116

22.92466

6.23

7

103

DM b NM

gi|55741809

31.22408

5.92

6

108

DM b NM

4101

1

Heat shock protein beta-1 (HSPB1)

4201 4201 (4–6) 4202 4202 (8–9) 4517

1

Troponin T, slow skeletal muscle (TNNT1)

[Canis lupus familiaris] [Sus scrofa]

1

Malate dehydrogenase, cytoplasmic (MDH1)

[Sus scrofa]

sp|P11708|MDHC_PIG

36.71611

6.16

5

74.3

DM b NM

1

Troponin T slow type isoform sTnT1 (TNNT1)

[Sus scrofa]

gi|34393190

31.22408

5.92

11

145

DM b NM

31.22408

5.92

11

145

DM b NM

223.9469 224.0096 97.70198 97.70198 20.11638 26.94097 31.22408 30.73412 43.25994 61.76378 223.9469 224.0096 17.0739 43.25994 32.15665 32.15665 47.44256

5.6 5.6 6.65 6.65 6.76 7.01 5.92 8.69 6.61 6.3 5.6 5.6 6.75 6.61 6.05 6.05 8.05

14 13 22 12 11 15 6 6 8 12 14 13 10 7 8 7 7

122 100 209 103 165 199 103 86.8 96.3 149 122 100 154 100 113 98.3 103

DM N NM

DM N NM DM b NM DM N NM DM N NM DM b NM

gi|126723437

47.38149

7.63

7

104

DM N NM

sp|Q1KYT0|ENOB_PIG gi|2136515

47.44256 36.49716

8.05 7.25

10 7.25

140 73.8

DM N NM

gi|19553291

27.34218

5.02

5.02

66.3

DM b NM

gi|57163939 gi|28461197 gi|6755256

97.70198 97.68799 97.68089

6.65 6.65 6.65

19 19 17

158 158 148

DM N NM DM N NM

sp|C5BKJ6|ATPG_TERTT

31.67728

8.75

4

66.8

DM N NM

gi|329744642

36.04136

8.51

8

105

DM N NM

1

Troponin T, slow skeletal muscle

[Sus scrofa]

gi|55741809

Myosin heavy chain 2× (MyHC 2×) Myosin heavy chain 2b (MyHC 2b) Glycogen phosphorylase, muscle (PYGM) Glycogen phosphorylase, muscle (PYGM) Alpha-crystallin B chain (CRYAB Triosephosphate isomerase (TPI1) Troponin T, slow skeletal muscle (TNNT1) Troponin T fast skeletal muscle type (TNNT3) Creatine kinase M-type (CKM) Phosphoglucomutase-1; (PGM1) Myosin heavy chain 2× (MyHC 2×) Myosin heavy chain 2b (MyHC 2b) Myoglobin (MB) Creatine kinase M-type (CKM) Troponin T, fast skeletal muscle (TNNT3) Troponin T, fast skeletal muscle (TNNT3) Beta-enolase (ENO3)

[Sus scrofa] [Sus scrofa] [Ovis aries] [Ovis aries] [Sus scrofa] [Sus scrofa] [Sus scrofa] [Sus scrofa] [Sus scrofa]

6002 6101 6207 6208 6313

1 2 1 1 1 1 1 1 1 1 1 2 1 1 1 1 1

gi|5360750 gi|5360748 sp|O18751|PYGM_SHEEP gi|57163939 gi|169882027 sp|Q29371|TPIS_PIG gi|55741809 gi|46389785 sp|Q5XLD3|KCRM_PIG gi|21362784 gi|5360750 gi|5360748 gi|47523546 gi|194018722 sp|Q75NG9|TNNT3_PIG sp|Q75NG9|TNNT3_PIG sp|Q1KYT0|ENOB_PIG

6322

1

Beta-enolase (ENO3)

6407 6415

1 1

Beta-enolase (ENO3) Ig gamma 3 chain constant region (IgG3)

2

Imidazole glycerol phosphate synthase subunit HisF (hisF)

6503

1 2 1

Glycogen phosphorylase, muscle (PYGM) Glycogen phosphorylase, muscle (PYGM) Glycogen phosphorylase, muscle (PYGM)

7001

1

ATP synthase gamma chain (atpG)

7213

1

Glyceraldehyde-3-phosphate dehydrogenase (GAPDH)

4603 5101 5104 5114 5202 5302 5306 5403 5502

6501

[Sus scrofa] [Sus scrofa] [Sus scrofa] [Sus scrofa] [Sus scrofa] [Sus scrofa] [Sus scrofa] [Oryctolagus cuniculus] [Sus scrofa] [Sus scrofa] [Corynebacterium glutamicum ATCC 13032] [Ovis aries] [Bos taurus] [Mus musculus] [Teredinibacter turnerae] [Sus scrofa]

DM b NM DM N NM DM N NM DM b NM DM N NM DM b NM DM b NM DM N NM DM N NM

Bold data indicates that genes differentially expressed greater than 1.5-fold in the two groups were selected for analysis.

the reference gene GAPDH (Yao et al. 2009) were designed by Primer Premier5.0 (Premier Biosoft International) and synthesized by Sangon Biotech (Shanghai, China) (Table 1). In parallel, the proteomics results were also validated by real-time PCR and Western blotting. The last eight genes in Table 1, identified with proteomic analysis, were also randomly selected for real-time PCR (Table 1). And six proteins, DEPs, CKM, MRLC2, TNNT3, ENO3 and MB, which were closely related with metabolism and development of muscle, were selected for the validation with western bolt, and βactin was used as a reference protein for normalization. 3. Results and discussion 3.1. DEGs and DEPs In the present study, we applied both transcriptomic and proteomic technologies to study pig double muscle trait. In microarray experiment,

each individual from three different biological replicates was analyzed with three technical replicates. Through HAC analysis, DEGs which showed consistent among the three technical replicates were identified, and then the DEGs further screened by comparing experimental and control groups were chosen for further research (Fig. S1). The DEGs from two of the three studied swine groups formed 10 clusters, and those in the last group resulted in 6 clusters. DEGs in each cluster had very similar expression patterns (Fig. S2). At last, microarray analyses screened 570 and 2560 and 1673 DEGs in three biological replications respectively (p b 0.05), and 62 common genes using Bayes statistics (Table S1). In parallel, SAM statistics identified 76 and 432 and 172 genes (fold ≥ 2, FDR b 0.05) and 12 common genes (Table S2). Using the two methods simultaneously (p b 0.05, q b 0.05, fold N 2), we obtained 57 and 260 and 147 DEGs, respectively (Table S3, S4, S5). These DEGs can be sorted into actin cytoskeleton genes (MYBPC1, MYH8, ACTA2 etc.), genes expressed in extracellular regions (IGF2, CXCL9, FRZB etc.) and genes involved in the cytoplasm component (PDE4D, PPARC1A,

18

S. Liu et al. / Gene 577 (2016) 14–23

Table 3 Pathways enriched in the analysis. Pathway

p-Value

q-Value

Wnt signaling pathway MAPK signaling pathway B cell receptor signaling pathway Axon guidance Complement and coagulation cascades T cell receptor signaling pathway Phenylalanine, tyrosine and tryptophan biosynthesis gamma-Hexachlorocyclohexane degradation Cysteine metabolism Alkaloid biosynthesis I Long-term potentiation Carbon fixation Alanine and aspartate metabolism Linoleic acid metabolism Glutamate metabolism VEGF signaling pathway Arginine and proline metabolism Tyrosine metabolism Phenylalanine metabolism Metabolism of xenobiotics by cytochrome P450 TGF-beta signaling pathway Toll-like receptor signaling pathway Regulation of actin cytoskeleton Apoptosis Focal adhesion Calcium signaling pathway Jak-STAT signaling pathway Cytokine–cytokine receptor interaction

1.37E − 05 5.55E − 05 2.02E − 04 2.02E − 04 0.0021697 0.0021697 0.0066031 0.00989 0.00989 0.0131673 0.0131673 0.016435 0.019693 0.0229415 0.0229415 0.0229415 0.0261803 0.0261803 0.0261803 0.042232 0.0485865 0.0517497 0.0611832 0.0643091 0.0798003 0.0950632 0.136609 0.1736601

2.74E − 05 5.55E − 05 1.16E − 04 1.16E − 04 7.89E − 04 7.89E − 04 0.00188659 0.002327068 0.002327068 0.002508065 0.002508065 0.002739167 0.002908927 0.002908927 0.002908927 0.002908927 0.002908927 0.002908927 0.002908927 0.004223197 0.004627284 0.004704514 0.005320276 0.005359091 0.006384026 0.007312551 0.010119188 0.012404293

NEB etc.). Gene CXCL9 and HLCS were among the DEGs in the three replicates, belonging to the same gene family according to their annotations. The results were verified by real-time PCR, varying patterns of five out of totally six genes between the two groups of studied pigs were coincident with those of microarray, except for ABCF2 (Fig. S3), which may be caused by the sensitivity difference among the different methods (Yao et al. 2014). In order to complement and validate microarray results, we performed proteomics analysis of the same LD samples in three biological replications, respectively (see the Materials and methods section). To reduce the technical variance, each sample was analyzed in 3 technical replicates (Fig. S4), which showed great consistency. In Fig. S5. DEPs were detected in each of brilliant blue stained gels by the computerassisted image analysis. Proteomic analyses (2-DE) yielded a total of 50 DEP spots in the three full-sib pairs. There were some overlapping spots among the study groups, so proteomics analyses identified a total of 41 spots (Fig. 1). According to previous studies, the selected spots were centered largely in pH 5–8. After MALDI-TOF-MS analysis, the 41 screened spots finally obtained high quality PMF (Table 2), and 33 of them had good matching protein annotation using MASCOT software in Sus scrofa and Swissprot databases of NCBI (nr). In Table 2, the successfully identified proteins are listed, together with the standard spot number, the identification parameters, and the indication of their GO annotation. These proteins can be sorted into four types by their functions: proteins or enzymes associated with energy metabolism (GAPDH, TPI1, PGM1, atpG etc.), cell structure (MyHC 2×, MyHC 2b etc.), muscle fiber activity and defensive function (CRYAB, HSPB1 etc.). The results were also verified by real-time PCR, but the expression patterns of MRLC2 and HSPB1 were not consistent with those from 2-DE (Fig. S6). The results were verified by Western blot, the expressions of all five proteins showed the same patterns with the results of 2D electrophoresis (Fig. S7 and Fig. S8). 3.2. Delving into pathway and network complexity Kyoto Encyclopedia of Genes and Genomes (KEGG) database was used for pathway analysis and we obtained 28 significant pathways about the DEGs through MAS program (Table 3). Network analyses

had been performed on transcriptomics and proteomics data, either alone or merged (Figs. 2, 3, 4). In the network figures, genes and proteins were presented as nodes, and the biological relationship between two nodes was represented as a line. Little or no direct overlap between transcriptomics and proteomics data was observed, as previously reported, which may arise from annotation errors, differential regulation of translation and turnover or alternative splicing (Nie et al. 2007; Murgiano et al. 2010). Although proteomics and transcriptomics experimental data sets displayed no overlap, interaction pathway analyses allowed the individuation of central networks sharing the same biological meaning, which is similar with previous report (Timperio et al. 2009). In Table 3, many pathways relevant to muscle hypertrophy occurred in this fraction. All this pathways were not mutually exclusive but interconnected and overlapped in biological processes. The most significant signal pathway was Wnt signaling of secretory glycoproteins, which transduces by Wnt and Frizzeld (FZD) family and plays important roles in embryonic induction, cancer and physiological processes of adult animals (Lie et al. 2005; Katoh and Katoh 2007). Canonical Wnt signaling mainly takes part in cell–cell adhesion, Cartilage, skeletal muscle and myocardial differentiation (Li et al. 2005; Katanaev et al. 2005; Liu et al. 2005). Non-canonical Wnt signaling controls cell migration and tissue polarization, which transduces cascade reaction depending on the Dishevelled(DSH)-dependent (Rho family, GTP enzyme and JNK) or calcium-dependent (NLK and NFAT) signal arising by FZD family receptor and Rob2/RYK complex (Oishi et al. 2003; Lu et al. 2004). FZD4, FRZB, ROR1, SFRP1 and GSK3B play important roles in Wnt signal transduction process. The GSK3B gene is regulated by DSH, and its phosphorylation could inhibit β-catenin, and then inhibit cell proliferation by inhibiting the expressions of c-MYC. Thus the expression of GSK3B decreased in double-muscled groups may promote cell proliferation. In Fig. 2, MYC, as a key node binding to SFRP1 (Fig. 2), can adjust Wnt signal. In addition, Myc-Max and Mad-Max heterodimers bound their common DNA target respectively, and E box recognized by these two structurally similar transcription factor pairs determines whether cells divide and proliferate (Myc-Max) or differentiate and become quiescent (Mad-Max) (Nair and Burley 2003). EGF (Fig. 2) combines its receptor that is able to stimulate cell growth, separation and differentiation (Herbst 2004), especially EGF + FGF-2 could causes expression of αsmooth muscle actin which was along with the activation of Wnt signaling pathway (Chen et al. 2012). Besides, EGF promotes FN1, SERPINE1, EGR1, CDH1, MYC, EGF, and restrains PPARG, which suppresses fat cells cleavage and proliferation, and initiates fibrocyte growth (Rosen et al. 1999). Mitogen-activated protein kinases (MAPK) signal pathway controls embryogenesis, cell differentiation, cell proliferation, and cell death (Pearson et al. 2001). By binding Anastellin, FN1 (Fig. 2) induces the formation of protofiber and activates p38 MAPK signaling pathway (Ambesi et al. 2005). Connective tissue growth factor (CTGF) (Fig. 2) is a cysteinerich polypeptide isolated from angioendothelial cells that can activate FN1 to promote cartilage proliferation and differentiation (Nakanishi et al. 2000; Ball et al. 2003). Anti-proliferative experiment showed that PPAR-γ mRNA increased significantly while CTGF, FN and Col III levels had a significant decrease and fibrosis reduced, which indicated the PPAR-γ activation triggered the above pathway (Kim et al. 2012). TGF-β signal pathway plays a critical role in the process of muscle hypertrophy, and it is believed that TGF-β affects muscle development and postnatal muscle hypertrophy through promoting fibroblast proliferation and neural cell differentiation, and TGF-β also refrains epithelial cell proliferation and mesenchymal cell differentiation. Within the members of TGF-β subfamily, MSTN was regarded as the most critical ligand that affects muscle size and function (Roberta and Marco 2015). There existed a significant negative correlation between II type muscle fibers and MSTN mutations depending on the dose (Bouley et al. 2005). Moreover, endurance and resistance exercise lowered the MSTN expression (Allen et al. 2011), which led to muscle hypertrophy

S. Liu et al. / Gene 577 (2016) 14–23

19

Fig. 2. The interactional image of DEGs in the three biological replications. Arrows, action; T lines, inhibition; segments, reaction; rays, post-translational modification; straight lines, binding.

(Pedersen and Febbraio 2012). By binding to G protein, Rho factors could induce upregulation of MSTN. In this study, the proteins related to down-regulation of G-proteins, such as ARHE and DLC1 in doublemuscled groups, may reduce the MSTN activity. In Fig. 2, JUN also is a key node. JUN-FOS heterodimer binds Smad3 and Smad4 and forms Smad3/Smad4-/JUN/FOS complex to mediate TGF-β-induced transcription (Zhang et al. 1998; Qing et al. 2000). Besides FOS, JUN also interacts with SERPINE1, TPM2, ATF3, EGF and STAT1. SERPINE1 gene encodes plasminogen activator inhibitor type1 (PAI), which was expressed in fat cells and positively correlated with BMI. Furthermore, PAI was

closely related to lipid metabolism, insulin resistance and type2 diabetes (Lijnen 2005; Alessi et al. 2007). Research shows that two SNPs in SERPINE1 gene are significantly associated with loin depth, muscling, growth and fat accretion in female pigs and meat quality in male animals (Weisz et al. 2011). From Fig. 2, It can be found that PPARG, ACVR1B and EGF up-regulate SERPINE1. Phosphorylated ACVR1B activates Smad2 or Smad3, which combine Smad4 and promote cell differentiation (Liu et al. 2002). Previous research showed that cAMP signal induced genetic modification and could increase muscle fiber diameter and promote

20

S. Liu et al. / Gene 577 (2016) 14–23

Fig. 3. The network image of DEPs in longissimus dorsi between double- and normal-muscled groups. Arrows, action; T lines, inhibition; segments, reaction; rays, post-translational modification; straight lines, binding.

transformation of the muscle fiber types (Chen et al. 2009), and the combining of cAMP and PKA is a part of muscle fiber hypertrophied process (Berdeaux and Stewart 2012). In this study, there were many genes (CREB1, PRKAR2B, CYR61 etc.) linked to cAMP, which could go into effect by answering cAMP signal. While AKAP13 and AKAP7 can regulate PKA subunit and interact with ESR1, ESR2, PPARA, RHOA and NME2 (Rubino et al. 1998; Iwashita et al. 2004), GNA12, PRKAR2B, TIAM1 and GPRC5C bind AKAP13 directly. All of above genes play important roles via cAMP signal pathway and could be involved in muscle fiber development. In the present study, some other pathways are also associated with muscle growth and development. For example, Jak-STAT signaling pathway mediates the combination of growth hormone and growth hormone receptor while growth hormone widely exists in muscle, liver, skeleton and adipose tissue, and Calcium signaling pathway could affect glucose metabolism. 3.3. Other DEGs and DEPs related to muscle hypertrophy After analyzing with GO functional annotations on STRING online system, DEGs and DEPs were classified into different categories

including biological process, cellular component and molecular function, and detail information was showed in the supplementary material (Tables S6, S7, S8, S9, S10, S11). In proteomics experiment, one third of the spots were connected with energy metabolism, cellular structure (16%), cellular defense (13%) and muscle contraction (24%). The results were similar with those of the study conducted with bovine skeletal muscle (Bouley et al. 2004). Actin cytoskeleton proteins, such as MYBPC1, MYH8, ACTA2 etc., and striated muscle filament proteins, such as TPM2, TNNT2, TTN etc. participated in cellularity, retractile fiber, myosin filament and myofibril filament. For instance, protein MYBPC1, combining with thick myofilament, was located in crossbridge region and can modify actomyosin ATPase activity. MYBPC1 could prevent its degradation by binding USP25 (Bosch-Comas et al. 2006). MYH8 mainly expresses during the womb stage and regulates the development of myosin heavy chain of sarcomere, and continues to express during the first month after birth. Lacking of function of MYH8 could lead to carney complex variant and peripheral joints spasm (Veugelers et al. 2004; Bonapace et al. 2010). In addition, TMOD3I regulates sarcomere length through controlling actin filament polymerization (Weber et al. 1994; Ono et al. 2005).

S. Liu et al. / Gene 577 (2016) 14–23

21

Fig. 4. The network image of DEGs and DEPs. Arrows, action; T lines, inhibition; segments, reaction; rays, post-translational modification; straight lines, binding.

TMOD3I was identified as a regulatory factor for stopping actin filaments stretching and tropomyosin polymerization, and overexpression of TMOD3 caused myocardial enlargement (Sussman et al. 1998). Candidate proteins MDH1, PYGM, TPI1, PGM1, ENO3 and GAPDH were key members for glycometabolism. Enzyme PYGM could catalyse the degradation of glycogen and leaded to PSE meat (Fujii et al. 1991). Previous study showed that the polymorphism of PYGM gene was significantly associated with lean meat percentage, bone percentage, fat meat percentage, average backfat thickness, loin eye area and carcass length (Xie et al. 2010). In addition, TPI1, PGM1, ENO3 and GAPDH were all key enzymes to the Embden Meyerhof pathway and played an important role in the process. After high intensity selection, western pig breeds have high lean rate and growth speed that lead to glycolytic fiber increase and oxidative

fiber decrease (Lefaucheur et al. 2004). In this study, double-muscled group had higher level of PGM, PYGM, GAPDH, ENO3 and less MDH1 than the control, which showed that double-muscled LD contained richer glycogen and more glycolytic fibers, lower oxidative capacity and protein metabolism, and could increase the fiber diameter of the muscles. There were four major type sarcomeric myosin heavy chains (MYHC) (i.e., I, IIa, IIx, and IIb), and the muscle fiber diameters of IIx and IIb were generally larger than I (van Wessel et al. 2010). Present study showed that the expression level of IIx and IIb in doublemuscled group was higher than the control group. The up-regulated expression of IIx and IIb which are fast-twitch glycolytic muscle fibers results in larger muscle fiber diameters of IIx and IIb. Meanwhile, meat production is positively correlated with proportion of IIb fibers in muscle (Wimmers et al., 2008). ATP, an important energy provider, plays a key role in the process of muscle contraction while enzyme CKM can

22

S. Liu et al. / Gene 577 (2016) 14–23

stimulate ATP regeneration. A study demonstrated that CKM deficiency mice had elevated skeletal muscle glycogen levels, high level of glycogen, which resulted in decreasing of pH value of the muscle (Milan et al. 2000). In the present study, the expression level of the CKM protein was lower in double-muscled group than the control, which may indicate that energy metabolism of muscle contraction was relatively lower in experimental group than the control. This result seems to be consistent with the rising of glycolytic enzyme levels, but it was not sure whether it is identical to pathogenesis of the CKM deficiency mice, which needs further research work to be verified. Myoglobin was highly expressed in skeletal muscle and cardiac muscle, which can transfer oxygen to mitochondria for respiratory metabolism during sustained muscle contraction. It is accordant with previous study that the fiber diameter increases when mitochondrial density increased and normal oxidative metabolism was maintained (Deveci et al. 2001). At last, it is worth mentioning that HLCS belongs to biotin ligase family and is involved in energy metabolism. The lack of this gene raised the content of ketonic acid and organic acid etc. and led to poisoning (Suzuki et al. 2005; Bailey et al. 2008). CXCL9 was a member of chemokines α family, which could affect growth and activity process and participate in inflammatory immune response. 4. Conclusions In the present study, DEGs and DEPs of LD muscles of doublemuscled Large White pig group and control group were detected with DNA microarray and two-dimensional electrophoresis, and the identification of numerous DEGs and DEPs confirms the key pathways and gene networks related to muscle hypertrophy. The DEGs such as EGF, PPARG, FN1, SERPINE1, MYC, and JUN, which were genes in the upstream of pathways in development, may affect cell differentiation and proliferation. Most DEPs located in the downstream had connection with muscle fiber constitutive proteins and energy metabolisms. DEGs and DEPs identified in the present study provide valuable information for the studies on molecular mechanism of muscle hypertrophy, as well as for screening markers associated with pig double muscle trait. Supplementary data to this article can be found online at http://dx. doi.org/10.1016/j.gene.2015.11.016. Acknowledgments The study has been funded by the National Basic Research Program of China (Grant No. 2006CB102101), the Ministry of Education of Doctoral Special Fund Project (Grant No. 20100008110035), and the Program for Changjiang Scholars and Innovative Research Team in University (Grant No. IRT1191). The authors also thank the support from Key Laboratory of Animal Genetics, Breeding and Reproduction, Ministry of Agriculture and Beijing Key Laboratory for Genetic Improvement of Livestock and Poultry. References Alessi, M.C., Poggi, M., Juhan-Vague, I., 2007. Plasminogen activator inhibitor-1, adipose tissue and insulin resistance. Curr. Opin. Lipidol. 18, 240–245. Allen, D.L., Hittel, D.S., McPherron, A.C., 2011. Expression and function of myostatin in obesity, diabetes, and exercise adaptation. Med. Sci. Sports Exerc. 43, 1828–1835. Ambesi, A., Klein, R.M., Pumiglia, K.M., et al., 2005. Anastellin, a fragment of the first type III repeat of fibronectin, inhibits extracellular signal-regulated kinase and causes G(1) arrest in human microvessel endothelial cells. Cancer Res. 65, 148–156. Bailey, L.M., Ivanov, R.A., Jitrapakdee, S., et al., 2008. Reduced half-life of holocarboxylase synthetase from patients with severe multiple carboxylase deficiency. Hum. Mutat. 29, E47–E57. Ball, D.K., Rachfal, A.W., Kemper, S.A., et al., 2003. The heparin-binding 10 kDa fragment of connective tissue growth factor (CTGF) containing module 4 alone stimulates cell adhesion. J. Endocrinol. 176, R1–R7. Berdeaux, R., Stewart, R., 2012. cAMP signaling in skeletal muscle adaptation: hypertrophy, metabolism and regeneration. Am. J. Physiol. Endocrinol. Metal. Bonapace, G., Ceravolo, F., Piccirillo, A., et al., 2010. Germline mosaicism for the c.2021G N A(p.Arg674Gln) mutation in siblings with trismus pseudocamptodactyly. Am. J. Med. Genet. A 152, 2898–2900.

Bosch-Comas, A., Lindsten, K., Gonzàlez-Duarte, R., et al., 2006. The ubiquitin-specific protease USP25 interacts with three sarcomeric proteins. Cell. Mol. Life Sci. 63, 723–734. Bouley, J., Chambon, C., Picard, B., 2004. Mapping of bovine skeletal muscle proteins using two-dimensional gel electrophoresis and mass spectrometry. Proteomics 4, 1811–1824. Bouley, J., Meunier, B., Chambon, C., et al., 2005. Proteomic analysis of bovine skeletal muscle hypertrophy. Proteomics 5, 490–500. Chen, M., Feng, H.Z., Gupta, D., et al., 2009. G(s)alpha deficiency in skeletal muscle leads to reduced muscle mass, fiber-type switching, and glucose intolerance without insulin resistance or deficiency. Am. J. Physiol. Cell Physiol. 296, C930-940. Chen, H.C., Zhu, Y.T., Chen, S.Y., et al., 2012. Wnt signaling induces epithelial– mesenchymal transition with proliferation in ARPE-19 cells upon loss of contact inhibition. Lab. Investig. Dennis, G.J., Sherman, B.T., Hosack, D.A., et al., 2003. DAVID database for annotation, visualization, and integrated discovery. Genome Biol. 4, R60. Deveci, D., Marshall, J.M., Egginton, S., 2001. Relationship between capillary angiogenesis, fiber type, and fiber size in chronic systemic hypoxia. Am. J. Physiol. Heart Circ. Physiol. 281 (1), H241–H252. Dunn, S.E., Burns, J.L., Michel, R.N., 1999. Calcineurin is required for skeletal muscle hypertrophy. J. Biol. Chem. 274 (31), 21908–21912. Fujii, J., Otsuk, Z.F., et al., 1991. Identification of a mutation in porcine ryanadine receptor associated with malignant hypenherinia. Science 253, 448–451. Grobet, L., Martin, L.J.R., Poncelet, D., et al., 1997. A deletion in the bovine myostatin gene causes the double-muscled phenotype in callte. Nat. Genet. 17, 71–74. Headey, S.J., Keizer, D.W., Yao, S., et al., 2004. Binding site for the C-domain of insulin-like growth factor (IGF) binding protein-6 on IGF-II; implications for inhibition of IGF actions. FEBS Lett. 568 (1–3), 19–22. Herbst, R.S., 2004. Review of epidermal growth factor receptor biology. Int. J. Radiat. Oncol. Biol. Phys. 59 (2 Suppl), 21–26. Hill, E.W., McGivney, B.A., Gu, J., et al., 2010. A genome-wide SNP-association study confirms a sequence variant (g.66493737C N T) in the equinemyostatin (MSTN) gene as the most powerful predictor of optimum racing distance for Thoroughbred racehorses. BMC Genomics 11, 552. Huang, D.W., Sherman, B.T., Lempicki, R.A., 2009. Systematic and integrative analysis of large gene lists using DAVID bioinformatics resources. Nat. Protoc. 4 (1), 44–57. Huang, Y.N., Li, L., Wei, L.J., et al., 2014. Gene cloning and sequence analysis of Myostatin in Luchuan pig. J. South. Agric. 45 (4), 659–663. Iwashita, S., Fujii, M., Mukai, H., et al., 2004. Lbc proto-oncogene product binds to and could be negatively regulated by metastasis suppressor nm23-H2. Biochem. Biophys. Res. Commun. 320, 1063–1068. Jensen, L.J., Kuhn, M., Stark, M., et al., 2009. STRING 8—a gloval view on proteins and their functional interactions in 630 organisms. Nucleic Acids Res. 37. Katanaev, V.L., Ponzielli, R., Sémériva, M., et al., 2005. Trimeric G protein-dependent frizzled signaling in drosophila. Cell 120 (1), 111–122. Katoh, M., Katoh, M., 2007. Wnt signaling pathway and stemcell signaling network. Clin. Cancer Res. 13, 4042–4045. Kijas, J.W., McCulloch, R., Edwards, J.E., et al., 2007. Evidence for multiple alleles effecting muscling and fatness at the ovine GDF8 locus. BMC Genet. 8, 80. Kim, J.S., Kim, I.K., Lee, S.Y., et al., 2012. Anti-proliferative effect of rosiglitazone on angiotensin II-induced vascular smooth muscle cell proliferation is mediated by the mTOR pathway. Cell Biol. Int. 36 (3), 305–310. Lee, N.K., MacLean, H.E., 2011. Polyamines, androgens, and skeletal muscle hypertrophy. J. Cell. Physiol. 226 (6), 1453–1460. Lefaucheur, L., Milan, D., Ecolan, P., et al., 2004. Myosin heavy chain composition of different skeletal muscles in Large White and Meishan pigs. J. Anim. Sci. 82, 1931–1941. Li, X., Zhang, Y., Kang, H., et al., 2005. Sclerostin binds to LRP5/6 and antagonizes canonical Wnt signaling. J. Biol. Chem. 280 (20), 19883–19887. Lie, D.C., Colamarino, S.A., Song, H.J., et al., 2005. Wnt signaling regulates adult hippocampal neurogenesis. Nature 437 (7063), 1370–1375. Lien, S., Cockett, N.E., Klungland, H., et al., 1999. High-resolution gametic map of the sheep callipyge region: linkage heterogeneity among rams detected by sperm typing. Anim. Genet. 30, 42–46. Lijnen, H.R., 2005. Pleiotropic functions of plasminogen activator inhibitor-1. J. Thromb. Haemost. 3, 35–45. Liu, G., 2010. Study of MyHC II b gene on muscle development in double-muscled pig. China Agric. Univ. Liu, X., Nagarajan, R.P., Vale, W., et al., 2002. Phosphorylation regulation of the interaction between Smad7 and activin type I receptor. FEBS Lett. 519, 93–98. Liu, X., Rubin, J.S., Kimmel, A.R., 2005. Rapid, Wnt-induced changes in GSK3beta associations that regulate beta-catenin stabilization are mediated by galpha proteins. Curr. Biol. 15 (22), 1989–1997. Lu, W., Yamamoto, V., Ortega, B., et al., 2004. Mammalian Ryk is a Wnt coreceptor required for stimulation of neurite outgrowth. Cell 119, 97–108. McCall, G.E., Byrnes, W.C., Dickinson, A., et al., 1996. Muscle fiber hypertrophy, hyperplasia, and capillary density in college men after resistance training. J. Appl. Physiol. 81, 2004–2012. McPherron, A.C., Lee, S.J., 1997. Double muscling in cattle due to mutations in the myostatin gene. Proc. Natl. Acad. Sci. U. S. A. 94, 12457–12461. Milan, D., Jeon, J.T., Looft, C., et al., 2000. A mutation in PRKAG3 associated with excess glycogen content in pig skeletal muscle. Science 288 (5469), 1248–1251. Mosher, D.S., Quignon, P., Bustamante, C.D., et al., 2007. A mutation in the myostatin gene increases muscle mass and enhances racing performance in heterozygote dogs. PLoS Genet. 3 (5), e79. Muráni, E., Murániová, M., Ponsuksili, S., et al., 2007. Identification of genes differentially expressed during prenatal development of skeletal muscle in two pig breeds differing in muscularity. BMC Dev. Biol. 7, 109.

S. Liu et al. / Gene 577 (2016) 14–23 Murgiano, L., D'Alessandro, A., Egidi, M.G., et al., 2010. Proteomics and transcriptomics investigation on longissimus muscles in Large White and Casertana pig breeds. J. Proteome Res. Nair, S.K., Burley, S.K., 2003. X-ray structures of Myc-Max and Mad-Max recognizing DNA. Molecular bases of regulation by proto-oncogenic transcription factors. Cell 112, 193–205. Nakanishi, T., Nishida, T., Shimo, T., et al., 2000. Effects of CTGF/Hcs24, a product of a hypertrophic chondrocyte specific gene, on the proliferation and differentiation of chondrocytes in culture. Endocrinology 141, 264–273. Nie, L., Wu, G., Culley, D.E., et al., 2007. Integrative analysis of transcriptomic and proteomic data: challenges, solutions and applications. Crit. Rev. Biotechnol. 27 (2), 63–75. Oishi, I., Suzuki, H., Onishi, N., et al., 2003. The receptor tyrosine kinase Ror2 is involved in non canonical Wnt5a/JNK signaling pathway. Genes Cells 8, 645–654. Ono, Y., Schwach, C., Antin, P.B., et al., 2005. Disruption in the tropomodulin1 (Tmod1) gene compromises cardiomyocyte development in murine embryonic stem cells by arresting myofibril maturation. Dev. Biol. 282 (2), 336–348. Pearson, G., Robinson, F., Beers Gibson, T., et al., 2001. Mitogen-activated protein (MAP) kinase pathways: regulation and physiological functions. Endocr. Rev. 22 (2), 153–183. Pedersen, B.K., Febbraio, M.A., 2012. Muscle, exercise and obesity: skeletal muscle as a secretory organ. Nat. Rev. Endocrinol. Qing, J., Zhang, Y., Derynck, R., 2000. Structural and functional characterization of the transforming growth factor-beta-induced Smad3/c-Jun transcriptional cooperativity. J. Biol. Chem. 275, 38802–38812. Ramayo-Caldas, Y., Mach, N., et al., 2012. Liver transcriptome profile in pigs with extreme phenotypes of intramuscular fatty acid composition. Genomics 13, 547. Roberta, S., Marco, S., 2015. Bone and morphogenetic protein signalling and muscle mass. Curr. Opin. Clin. Nutr. Metab. Care 18, 215–220. Rosen, E.D., Sarraf, P., Troy, A.E., et al., 1999. PPAR gamma is required for the differentiation of adipose tissue in vitro and in vivo. Mol. Cell 4, 611–617. Rubino, D., Driggers, P., Arbit, D., et al., 1998. Characterization of Brx, a novel Dbl family member that modulates estrogen receptor action. Oncogene 16, 2513–2526. Shannon, T.R., Ginsburg, K.S., Bers, D.M., 2000. Potentiation of fractional sarcoplasmic reticulum calcium release by total and free intra-sarcoplasmic reticulum calcium concentration. Biophys. J. 78 (1), 334–343. Sussman, M.A., Baqué, S., Uhm, C.S., et al., 1998. Altered expression of tropomodulin in cardiomyocytes disrupts the sarcomeric structure of myofibrils. Circ. Res. 82 (1), 94–105. Suzuki, Y., Yang, X., Aoki, Y., et al., 2005. Mutations in the holocarboxylase synthetase gene HLCS. Hum. Mutat. 26, 285–290.

23

Tang, Z., Li, Y., Wan, P., et al., 2007. LongSAGE analysis of skeletal muscle at three prenatal stages in Tongcheng and Landrace pigs. Genome Biol. 8 (6), R115. Te Pas, M.F., De Wit, A.A., Priem, J., et al., 2005. Transcriptome expression profiles in prenatal pigs in relation to myogenesis. J. Muscle Res. Cell Motil. 26 (2–3), 157–165. Timperio, A.M., D'Alessandro, A., Pariset, L., et al., 2009. Comparative proteomics and transcriptomics analysis of livers from two different Bos taurus breeds: Chianina and Holstein Friesian. J. Proteome 73 (2), 309–322. Van Laere, A.S., Nguyen, M., Braunschweig, M., et al., 2003. A regulatory mutation in IGF2 causes a major QTL effect on muscle growth in the pig. Nature 425, 832–836. van Wessel, T., de Haan, A., van der Laarse, W.J., et al., 2010. The muscle fiber type-fiber size paradox: hypertrophy or oxidative metabolism. Eur. J. Appl. Physiol. 110 (4), 665–694. Veugelers, M., Bressan, M., McDermott, D.A., et al., 2004. Mutation of perinatal myosin heavy chain associated with a Carney complex variant. N. Engl. J. Med. 351, 460–469. Weber, A., Pennise, C.R., Babcock, G.G., et al., 1994. Tropomodulin caps the pointed ends of actin filaments. J. Cell Biol. 127 (1), 1627–1635. Weisz, F., Bartenschlager, H., Knoll, A., et al., 2011. Association analyses of porcine SERPINE1 reveal sex-specific effects on muscling, growth, fat accretion and meat quality. Anim. Genet. Wimmers, K., Fiedler, I., Hardge, T., et al., 2006. QTL for microstructural and biophysical muscle properties and body composition in pigs. BMC Genet. 7, 5. Wimmers, K., Ngu, N.T., Jennen, D.G., et al., 2008. Relationship between myosin heavy chain isoform expression and muscleing in several diverse pig breeds. J. Anim. Sci. 86 (4), 795–803. Xiao, G.Y., Lai, Y.H., 1999. Growth observation of double-muscling pig. Chin. J. Anim. Sci. 35 (4). Xie, H.T., Xiong, Y.Z., et al., 2010. Genetic polymorphism and correlation analysis with meat quality and carcass traits of porcine PYGM gene. Chin. Anim. Hus. Vet. Med. 37 (3), 118–123. Yao, Y.C., Cai, Z.W., Zhang, L.F., et al., 2009. Effects of castration on androgen receptor, IGFIEa, MGF and Myostatin gene expression in skeletal muscles of male pigs. Asian–Aust. J. Anim. Sci. 22, 1069–1077. Yao, X.G., Liu, X.H., et al., 2014. Comparative research on fluorescent quantitation PCR method and gene chips typing method in testing sensitivity of human papilloma virus. Int. J. Lab. Med. 5. Zhang, Y., Feng, X.H., Derynck, R., 1998. Smad3 and Smad4 cooperate with c-Jun/c-Fos to mediate TGF-betainduced transcription. Nature 394, 909–913. Zhu, L., Li, X.W., et al., 2002. Factors influencing the growth of muscle fiber. J. Sichuan Agric. Univ. 20 (1), 37–39.