Abstract

Background

   The aim of this study was to investigate the effect of dietary mulberry
   leaves on the transcriptome profiles of finishing pigs. RNA‐Seq was
   used to identify differentially expressed genes (DEGs) in the
   longissimus dorsi of 56 pigs fed either a traditional diet or diets
   supplemented with 3%, 6% or 9% mulberry leaf powder, and both gene
   ontology (GO) function and Kyoto encyclopedia of genes and genomes
   (KEGG) pathway enrichment analyses were performed. Furthermore,
   protein–protein interaction (PPI) network and the subnet module
   analysis were used to identify genes with beneficial potential, and
   quantitative real‐time polymerase chain reaction (qRT‐PCR) was used to
   validate the expression patterns revealed by RNA‐Seq.

Results

   Pigs fed with the 6% mulberry diet exhibited greater average daily
   gain, lower water loss and lower shear force than the control group and
   yielded 531 DEGs, including 271 and 260 upregulated and downregulated
   genes, respectively. Function analysis revealed that the DEGs were
   significantly enriched in functions related to muscle growth and
   development. Furthermore, several genes (i.e. ACOT4, ECHS1, HACD1,
   NPR1, ADCY2, MGLL and IRS1) were enriched in a KEGG pathway that was
   associated with fatty acid metabolism, and in the PPI subnet module,
   four of eight node genes, namely TNNC1, MYL3, TCAP and TNNT1, were
   associated with muscle formation and development. The upregulation of
   these genes, including TNNC1, TNNT1 and MYL3, was confirmed by qRT‐PCR.

Conclusions

   Dietary mulberry leaves (6%) may improve the muscle quality of pigs by
   modulating the expression of several key genes, such as TNNC1, MYL3 and
   TNNT1.

   Keywords: differentially expressed gene, mulberry, pig
     __________________________________________________________________

   The study was aimed to explain the effect of the inclusion of mulberry
   in the diet of pigs on transcriptome profiling. The inclusion of
   mulberry in the diet might be helpful in muscle formation and
   development of pigs by modulating the expression levels of three genes
   including TNNC1, MYL3 and TNNT1

   graphic file with name VMS3-5-526-g005.jpg

1. BACKGROUND

   Along with improving quality of life, one of the main concerns in meat
   production is to improve meat quality. For pork production, the index
   used to evaluate meat quality has typically included various
   characteristics, including flesh colour, amount of intermuscular fat,
   tenderness and extreme pH. However, researchers have now begun to focus
   on improving additional measures of pork quality (e.g. free fatty acid
   concentrations and oxidative stability) by supplementing pig feed with
   various additives, including selenium, lysine, oregano oil,
   N‐carbamylglutamate and chicorytosan (Calvo et al., [32]2017; Schwarz
   et al., [33]2017).

   The leaves of mulberry trees, which are widely distributed and abundant
   throughout China, are traditionally used for rearing silkworm (Acharya,
   Ghosh, & Kundu, [34]2008). In China, mulberry trees are distributed
   widely throughout the country, and mulberry resources are abundant (Liu
   et al., [35]2016). However, mulberry leaves have not been fully
   utilized for other applications, especially after late autumn. As a
   traditional Chinese herbal medicine, mulberry leaves are rich in
   nutrients and active substances (Fan & Xu, [36]2017; Zeng et al.,
   [37]2016). The abundant resources and exceptional nutritional value of
   mulberry leaves have prompted researchers to investigate the use of
   mulberry leaves as a foodstuff for the husbandry of both livestock and
   poultry (Li et al., [38]2017; Ly & Samkol, [39]2014). In fact, previous
   studies have demonstrated that mulberry leaves can significantly
   improve animal production performance, feed conversion efficiency and
   meat quality (Eo & Lim, [40]2016), and in animal husbandry, mulberry
   leaves can be not used as both a green feed and a protein feed.
   Researchers have proposed that the addition of mulberry leaves to
   poultry diets could significantly increase body metabolism, body growth
   and production performance and significantly reduce heavy metal
   accumulation and ammonia emissions (Fan et al., [41]2017; Kobayashi,
   Miyazawa, & Kamei, [42]2010), and Martínez, Motta, Cervera, and Pla
   ([43]2005) reported that supplementing rabbit diets with rabbit leaves
   resulted in leaner carcasses that had leaner meat and increased
   moisture levels. However, the effects of dietary mulberry leaves on pig
   production are yet to be fully investigated. Even though research has
   clearly demonstrated that mulberry leaves can improve meat quality and
   reduce food cost (Tingjuan, Mengzhou, & Lianghong, [44]2017), the
   evaluation of dietary supplementation in pigs has primarily focused on
   the physiological and biochemical analysis of pork quality, and the
   metabolic pathways and gene regulation associated with improvements in
   the quality of mulberry‐fed pork remain unknown.

   Accordingly, the aim of the present study was to explore the molecular
   mechanisms associated with dietary mulberry supplementation by
   transcriptome profiling in pigs. To understand the genetic factors
   associated with meat quality improvement associated with mulberry
   leaves, differentially expressed genes (DEGs) and potential gene
   networks affecting quality improvement in pigs were explored between
   RNA profiling of pigs fed with mulberry leaves as compared with pigs
   fed with conventional feed.

2. MATERIAL AND METHODS

2.1. Experimental animals and sample collection

   The conventional feed and mulberry leaf powder were obtained from
   Shanxi ankang yangsheng Biological Feed Technology Co., Ltd, and the
   composition and major bioactive ingredients of the mulberry leaf powder
   are summarized in Table [45]S1. A total of 56 35‐day‐old, healthy
   Landrace‐Yorkshire hybrid pigs (31.18 ± 4.57 kg) were divided into four
   groups, with 14 pigs (seven female and seven male) assigned to each of
   four treatment groups, and the four groups of pigs were housed in the
   same pen and railed off. Pigs in group I were fed a basal diet, whereas
   those in groups II, III and IV were fed basal diets that were
   supplemented with either 3%, 6% or 9% mulberry leaf powder,
   respectively, and all the diets were maintained for 102 days. The
   composition and nutritional content of the diets are summarized in
   Table [46]S2. There was no significant difference in the starting
   weights of the treatments groups (p> 0.05), and the four groups were
   housed in the same pen, although separated using rails, and allowed to
   drink freely throughout the study. The daily feed intake of each group
   was recorded daily, along with daily weather changes, and both the
   excrement and health status of the pigs were observed at all times. The
   optimal level of mulberry leaf powder supplementation was determined by
   comparing the daily gain, average daily feed intake, feed meat ratio,
   meat colour, pH at 45 min and 24 hr post‐mortem, water loss, cooked
   meat percentage, drip loss, shear force and muscle tenderness of the
   treatment groups.

   The experimental protocol used for the present study was approved by
   the Animal Care and Use Committee of Gansu Agricultural University
   (Lanzhou, China).

   After 102 days, the pigs were anaesthetized, using CO[2], and
   slaughtered at Ankang Minrong slaughtering house. Briefly, when the
   pigs lost consciousness, fell to the ground, and remained completely
   motionless for ~ 1 min, they were hung upside down for bloodletting.
   After slaughter, the longissimus dorsi between the third thoracic and
   fourth lumbar vertebrae were selected to assess meat quality and
   flavour to obtain material for molecular analysis. All the samples were
   collected rapidly after slaughter and then stored in liquid nitrogen.

2.2. Determination of muscle nutrients

   The water loss rate, crude protein, fat and ash levels and pH of the
   muscle samples were measured according to the Association of Official
   Analytical Chemists (AOCC) (Bader & Hogue, [47]2003). Crude fat was
   measured using the Soxhlet extraction method, and crude ash was
   estimated using a 550°C ashing furnace.

2.3. RNA extraction, library construction and sequencing

   Total RNA was extracted from the longissimus dorsi tissue samples
   (50–100 mg) of 14 pigs that had been fed the basal diet and 14 pigs
   that had been fed the basal diet supplemented with 6% mulberry leaf
   powder. For each sample, RNA was extracted using 1‐ml TRIZOL, chilled
   on ice for 5 min, combined with 200‐μl chloroform and then centrifuged
   at 12,000g for 15 min. Each supernatant was subsequently transferred to
   a sterile tube, combined with an equal amount of isopropanol, incubated
   at − 20°C and centrifuged at 12,000g for 15 min. The resulting sediment
   was washed using 1‐ml 75% ethanol, centrifuged at 12,000g for 5 min,
   air dried for 5–10 min and suspended in 20‐μl diethyl pyrocarbonate
   water. The quality of the RNA was measured using an Infinite M100
   PROBio analyzer (TECAN, Switzerland), and all the experiments were
   repeated three times.

   Poly‐dT oligonucleotides were used to reverse‐transcribe RNA into cDNA,
   and after end repair, the cDNA was subject to A‐tailing and adaptor
   ligation, followed by cDNA purification and enrichment. Sequencing was
   performed using an IlluminaHiSeq2000 with 100‐bp paired read
   sequencing.

2.4. Mapping the reads to reference genome

   Before mapping, a quality check was performed using Trimmomatic
   (Bolger, Lohse, & Usadel, [48]2014), and the raw sequences were
   processed to (a) remove linker sequences and reads resulting from
   linker self‐ligation; (b) remove low‐mass (<20) bases at the 3′‐end of
   sequences and eliminate remaining sequences with mass values of < 10;
   (c) remove reads containing > 10% undetermined bases; and (d) discard
   adapters and mass‐pruned sequences of < 20 bp in length. Finally, clean
   data from two samples were subject to further analysis.

   The filtered reads were mapped to the Sus_Scrofa genome and annotated
   using TopHat (v2.1.0; [49]http://ccb.jhu.edu/software/tophat)
   (Trapnell, Pachter, & Salzberg, [50]2009). Up to four mismatched bases
   were allowed, and all other parameters were set as default.

2.5. Transcript assembly, quantification and DEGs analysis

   Using the cufflinks tool (v2.2.1) (Trapnell et al., [51]2010),
   transcript reassembly was performed on six samples using the Sus_scrofa
   genome annotation file (Ensembl, v 91) as a reference (Aken et al.,
   [52]2016), and the resulting multiple gtf files were fused into a more
   comprehensive transcript. The annotation results were then used to
   quantify individual sample gene and transcript expression levels using
   cuffquant and cuffnorm, and both read count and fragments per kilobase
   of transcript per million mapped reads quantitative results were
   obtained. Finally, DEG analysis was performed using cuffdiff and a
   threshold of |log2FC|>0.585 and p < 0.05.

2.6. Gene ontology (GO) and pathway analyses

   Cluster profiler (v6.8) was used to perform gene ontology (GO) function
   and KEGG pathway enrichment analyses of genes that corresponded to
   significant differential transcripts (Yu, Wang, & Han, [53]2012).
   Hypergeometric test p‐values of < 0.05 were considered to indicate
   significant enrichment. The genes enriched in the biological process,
   functional function, functional concentration in the GO function and
   KEGG pathway enrichment analyses were obtained.

2.7. Protein–protein interaction (PPI) network

   The PPI network of the significant differential transcript counterparts
   was analysed using the STRING online tool (Szklarczyk et al.,
   [54]2015), with a required confidence (combined score) threshold
   of > 0.4.

   Cytoscape tools were used to build a protein interaction network,
   analyse network topology and identify important nodes on the basis of
   network connectivity (Shannon et al., [55]2003). The importance of
   nodes in the network was assessed by measuring degree centrality,
   betweenness centrality and closeness centrality.

   In the living body, essential genes with higher degrees of centrality,
   or their translation products, support the basic activities of life
   and, therefore, appear in the entire biological network at a high
   frequency, as do many genetic disease‐related genes (Yoon, Blumer, &
   Lee, [56]2006). In the present study, the connectivity of a node was
   defined as the number of direct connections to other nodes, and degree
   of connectivity indicated the importance of each node in the network.
   The node with the highest connectivity was recognized as the hub node.

   Betweenness centrality was used to demonstrate the role of genes in
   maintaining network tightness (Cukierski & Foran, [57]2008). Media
   centeredness indicated the role played by a certain node in connection
   with other nodes. The node would play better betweenness centrality
   when the larger value was calculated.

   Closeness centrality was as an index of the score of the node in the
   network (Du et al., [58]2015). The intimacy coefficient was also called
   tightness, and these values indicated the distance of genes to the
   centre of the network. The cytoscape plug‐in CytoNCA (parameter
   settings: network with no weight) (Tang, Li, & Wang, [59]2015) was used
   for the three central methods of the computational network, and node
   scores indicated the importance of genes in the network.

2.8. Module analysis

   In PPI networks, proteins with similar functions tend to cluster
   together, and network node distances are related to node functions.
   Therefore, investigating protein complexes or functional clustering
   modules in PPI networks can provide insight into the role of proteins
   with unknown functions. Accordingly, the subnet module of the PPI
   relational network was analysed using MCODE (Bader & Hogue, [60]2003).

2.9. Validation of gene expression

   QRT‐PCR was used to validate the relative expression patterns obtained
   via RNA‐Seq. More specifically, single‐stranded cDNA was synthesized
   from 0.5 μg total RNA using 5 × prime Script RT Master MIX (TAKARA
   Biotechnology, Dalian, China) following the manufacturer's
   instructions, and quantitative PCR analysis was performed for TNNC1,
   MYL3, TNNT1, TCAP, ADCY2 and HACD1 using SYBR premix EX taq, an ABI
   7,500 Real‐Time PCR System (7900HT FAST, Applied Biosystems), and the
   following primers: TNNC1‐sF (GATGACATCTACAAGGCTGCG), TNNC1‐sR
   (GCACGAAGATGTCAAAGGCT), MYL3‐sF (AGGACTTTGTGGAAGGGCTG), MYL3‐sR
   (TCTTGCCCAGCCATCAACTT), TNNT1‐sF (CATCCGCGGTTTAGGAATCTTT), TNNT1‐sR
   (CCCCCTCTGGGATCTTCGG), TCAP‐sF (CGTGAGACCTACCACCAACAG), TCAP‐sR
   (CCACTTTGGCAGGGGTGAAG), ADCY2‐sF (AGCATGACCACAGAGAACGG), ADCY2‐sR
   (GGCAGTGGCTCGGTATTCTT), HACD1‐sF (GGTGTGGCTCGTTACTCACA), and HACD1‐sR
   (AAGTACGGCAAGTGGTCGAG. The mRNA levels were normalized to the levels of
   GAPDH using the following primers: GAPDH‐sF (TCGGAGTGAACGGATTTGGC) and
   GAPDH‐sR (TGACAAGCTTCCCGTTCTCC). The amplification was performed in
   triplicate, and the relative expression levels of the genes were
   calculated using the 2^−ΔΔCT method.

2.10. Statistic analysis

   The growth performance, production performance and meat quality of the
   four treatment groups were compared using SPSS 22.0, and all results
   were calculated as mean ± standard deviation (SD) values. The
   significance of differences between group pairs was calculated using
   Student's t test, and the significance of differences between three
   groups was analysed using one‐way analysis of variance (ANOVA),
   followed by post hoc least significant difference tests. p‐values
   of < 0.05 indicated statistical significance. Graphpad prism 5
   (Graphpad Software, San Diego, CA, USA) was used to generate graphs.
   The threshold was defined as p < 0.05.

3. RESULTS

3.1. Effect of mulberry powder

   The beneficial effect of dietary mulberry leaves on pig performance,
   including growth performance, production performance and meat quality
   is shown in Table [61]1. Pigs fed the 6% mulberry diet exhibited
   greater average daily gain, which was selected for the following
   bioinformatics analysis, and the pigs fed 6% and 9% mulberry diets
   exhibited lower water loss rates and shear force values than the
   control group. However, diet failed to significantly affect feed:meat
   ratio, half carcass weight, slaughter rate, average backfat thickness
   or loin eye area.

Table 1.

   Effect of dietary mulberry powder on the growth performance, production
   performance and meat quality of finishing pigs
     Item Group I Group II Group III Group IV
   N = 16 N = 16 N = 16 N = 16
   Growth performance Initial weight (kg) 31.43 ± 3.17 31.29 ± 2.26
   31.07 ± 2.08 30.93 ± 2.35
   Final weight (kg) 118.29 ± 4.36^b 116.21 ± 3.12^b 127.36 ± 4.87^a
   118.69 ± 4.49^b
   Average daily gain (g) 852 ± 38.57^b 833 ± 36.24^b 944 ± 43.16^a
   927 ± 39.05^a
   Average daily feed intake (kg) 2.49 ± 0.26 2.26 ± 0.15 2.57 ± 0.39
   2.39 ± 0.18
   Feed:meat ratio 2.92 ± 0.21 2.72 ± 0.14 2.72 ± 0.17 2.99 ± 0.31
   Production performance Half carcass weight (kg) 94.83 ± 2.37
   89.33 ± 2.08 94.20 ± 1.18 91.43 ± 4.54
   Slaughter rate (%) 76.68 ± 0.36 75.49 ± 0.43 75.97 ± 0.95 73.94 ± 3.58
   Average backfat thickness (mm) 9.91 ± 1.64 9.38 ± 1.34 9.74 ± 1.58
   9.83 ± 0.70
   Loin eye area (cm^2) 45.38 ± 7.87 40.56 ± 9.83 50.38 ± 0.49
   43.03 ± 7.68
   Meat quality Cooked meat percentage (%) 64.77 ± 3.64 61.21 ± 0.27
   62.40 ± 1.78 64.52 ± 1.27
   Water loss rate (%) 2.46 ± 1.73^a 2.43 ± 1.81^ab 1.66 ± 0.56^b
   1.56 ± 0.31^b
   Drip loss (%) 19.40 ± 0.82 19.33 ± 1.31 19.64 ± 6.26 19.13 ± 9.39
   Shear force (N) 70.30 ± 29.91^a 56.74 ± 23.40^b 47.28 ± 19.44^b
   53.93 ± 29.76^b
   Meat colour 3.53 ± 0.97 4.10 ± 1.20 3.70 ± 1.65 3.97 ± 0.91
   pH (45 min) 5.96 ± 0.21 6.01 ± 0.10 5.96 ± 0.49 5.83 ± 0.57
   pH (24 hr) 5.44 ± 0.26 5.82 ± 0.22 5.68 ± 0.09 5.64 ± 0.18
   Water (%) 71.52 ± 0.21 71.64 ± 0.33 72.13 ± 0.80 72.42 ± 1.23
   Crude protein (%) 19.05 ± 0.70 20.23 ± 0.32 19.59 ± 2.79 18.42 ± 0.68
   Crude ash (%) 27.20 ± 0.30 26.92 ± 0.26 26.62 ± 0.78 26.19 ± 1.01
   Crude fat (%) 2.23 ± 0.34 2.30 ± 0.12 2.28 ± 0.79 1.80 ± 0.77
   [62]Open in a new tab

   The data were presented as mean ± standard deviation (SD). Peer data
   with no shoulder or shoulder note with the same letter indicate no
   significant difference (p> 0.05), adjacent letters indicate significant
   difference (p < 0.05) and separated letters indicate extremely
   significant difference (p < 0.01).

3.2. Transcriptome mapping

   The summary of reads and genes mapped to the Sus_Scrofa transcriptome
   is shown in Tables [63]2 and [64]3. A total of 157,495,967 clean reads
   were obtained from the 159,307,352 raw reads (C1: 27,608,848; C2:
   21,721,642; M1: 23,767,135; C3: 30,667,844; M3: 27,597,924; M2:
   27,943,959). Of the total clean reads from left, 89.00%, 88.35%,
   88.14%, 88.12%, 88.71% and 88.64% of reads from the C1, C2, C3, M1, M2
   and M3 samples, respectively, were aligned to the Sus_scrofa genome.
   Based on right reads, 87.42%, 86.41%, 87.26%, 86.37%, 88.17% and 86.83%
   of reads from the C1, C2, C3, M1, M2 and M3 samples, respectively, were
   aligned to the Sus_scrofa genome.

Table 2.

   Summary of reads, bases and the transcript‐annotated bases per pig
   Sample Raw reads Clean reads Effective rate (%) Error rate (%) Q20 (%)
   Q30 (%) GC content (%)
   C1 27,608,848 27,296,417 98.87 0.02 96.49 91.37 54.61
   C2 21,721,642 21,533,989 99.14 0.02 96.47 91.23 54.27
   C3 30,667,844 30,370,701 99.03 0.02 96.86 92.13 55.03
   M1 23,767,135 23,530,919 99.01 0.02 96.47 91.32 54.84
   M2 27,943,959 27,561,073 98.63 0.02 96.93 92.2 53.44
   M3 27,597,924 27,202,868 98.57 0.02 96.8 91.7 54.34
   [65]Open in a new tab

   Abbreviations: GC content, percentage of total bases comprised of G/C
   bases; Q20, percentage of Phred values> 20; Q30, percentage of Phred
   values> 30. C1, C2 and C3 are control group samples, whereas M1, M2 and
   M3 are samples from the mulberry powder group.

Table 3.

   Clean reads mapped to reference genomes
       C1 C2 C3 M1 M2 M3
   Left reads Input 27,296,417 21,533,989 30,370,701 23,530,919 27,561,073
   27,202,868
   Mapped 24,293,560 19,025,149 26,769,555 20,734,723 24,450,431
   24,111,637
   Mapped rate (%) 89.00 88.35 88.14 88.12 88.71 88.64
   Uniquely mapped 22,770,049 17,873,293 24,985,873 19,491,368 23,007,094
   22,621,345
   Uniquely mapped rate (%) 83.42 83.00 82.27 82.83 83.48 83.16
   Right reads Input 27,296,417 21,533,989 30,370,701 23,530,919
   27,561,073 27,202,868
   Mapped 23,862,418 18,607,271 26,501,605 20,324,256 24,301,235
   23,621,061
   Mapped rate (%) 87.42 86.41 87.26 86.37 88.17 86.83
   Uniquely mapped 22,359,507 17,474,538 24,731,222 19,100,779 22,865,598
   22,149,401
   Uniquely mapped rate (%) 81.91 81.15 81.43 81.17 82.96 81.42
   Overall read mapping rate (%) 88.20 87.40 87.70 87.20 88.40 87.70
   [66]Open in a new tab

3.3. Differentially expressed genes (DEGs)

   Of 531 significant DEGs (under the threshold of |log2FC|>0.585 and
   p < 0.001), 271 were upregulated and 260 were downregulated (Figure
   [67]1).

Figure 1.

   Figure 1
   [68]Open in a new tab

   Two‐dimensional clustering heat maps of differentially expressed
   transcript. Columns represent different samples, whereas rows represent
   differentially expressed genes, with red indicating high expression and
   blue indicating low expression

3.4. Function variation

   In the GO analysis, DEGs were significantly enriched in functions
   related to muscle growth and development, and a total of 27 genes
   (corresponding to 30 transcripts) were associated with the process
   (Figure [69]2, Table [70]S1). Meanwhile, the KEGG pathway enrichment
   analysis revealed that DEGs enriched 13 pathways, including the apelin,
   cGMP‐PKG and notch signalling pathways. Several genes, including ACOT4,
   ECHS1, HACD1, NPR1, ADCY2, MGLL and IRS1, were also enriched in KEGG
   pathways associated with fatty acid metabolism (i.e. ssc00062: fatty
   acid elongation, ssc04923: regulation of lipolysis in adipocytes;
   Figure [71]2d).

Figure 2.

   Figure 2
   [72]Open in a new tab

   Function and pathway enrichment of differentially expressed genes. Top
   12 pathways ordered by p‐value. (a) Biological Process; (b) Cellular
   Component; (c) Molecular Function; (d) Kyoto encyclopedia of genes and
   genomes pathway. The ordinate represents the gene ontology function,
   and the abscissa represents the number of differential genes enriched
   to the term. p‐values indicate the degree of enrichment, with smaller
   p‐values indicating genes that are more likely to play significant
   functional roles

3.5. The construction of PPI network

   A total of 209 nodal genes and 409 pairs were explored in the protein
   interaction network map of DEGs (Figure [73]3). Table [74]S2 lists the
   top 15 network nodes, which were the genes that scored the highest in
   topology properties.

Figure 3.

   Figure 3
   [75]Open in a new tab

   Protein–protein interaction network diagram. Network explored 209 nodal
   genes and 409 pairs. The red circular node represents upregulated
   genes, whereas the green circular node represents downregulated genes
   and the blue circular internal diamond node represents the sub‐network
   module

   A sub‐network module was obtained when cytoscape MCODE was used with
   score > 6 (Figure [76]3). There were eight nodes (i.e. TNNC1, MYL3,
   TCAP, TPM3, MYH7, TNNI1, MYH7B and TNNT1) and 24 interaction pairs in
   the sub‐network module, and four genes of the sub‐network module (i.e.
   TNNC1, MYL3, TCAP and TNNT1) were associated with muscle quality.

3.6. Variation in pig longissimus dorsi

   Figure [77]4 shows the expression levels for using qRT‐PCR DEGs
   obtained by RNA‐Seq. Several genes, including TNNC1, TNNT1 and MYL3,
   were significantly upregulated in pigs fed diets that were supplemented
   with mulberry leaves. However, no significant differences were found
   for the expression levels of TCAP, ADCY2 or HACD1.

Figure 4.

   Figure 4
   [78]Open in a new tab

   Validation of RNA‐Seq data by quantitative real‐time polymerase chain
   reaction. (a) TNNT1; (b) TNNC1; (c) MYCL3; (d) TCAP; (e) HACD1; (f)
   ADCY2. **p < 0.01 versus traditional diet; *p < 0.05 versus traditional
   diet

4. DISCUSSION

   The aim of the present study was to investigate the molecular
   mechanisms underlying the effect of dietary mulberry leaves on
   finishing pigs using high‐throughput RNA‐Seq technology. A total of 531
   genes were differentially expressed in the mulberry‐fed pigs, when
   compared to the control group, with 271 transcripts being upregulated
   and 260 being downregulated. Functional analysis demonstrated that DEGs
   were significantly enriched in functions related to muscle growth and
   development, and several genes (ACOT4, ECHS1, HACD1, NPR1, ADCY2, MGLL
   and IRS1) were enriched in the KEGG pathway associated with fatty acid
   metabolism. Furthermore, four of eight node genes, namely TNNC1, MYL3,
   TCAP and TNNT1, were associated with muscle formation and development,
   and the upregulation of TNNC1, TNNT1 and MYL3 was confirmed using
   qRT‐PCR. Therefore, the inclusion of mulberry leaves in pig diets might
   be helpful for improving the muscle formation and development of pigs,
   and this likely occurs through the modulation of expression levels for
   three genes, namely TNNC1, MYL3 and TNNT1.

   With the development of high‐throughput sequencing methods, the
   Illumina high‐throughput sequencing platform was widely accepted for
   analysing both genomes and transcriptomes, due to its efficiency and
   accuracy. Meanwhile, when compared to traditional microarray
   hybridization, transcriptome analysis provides a more sensitive and
   accuracy platform, especially for interpreting the functional elements
   of genomes (Qiu et al., [79]2013; Wang et al., [80]2014). In the
   present study, a preliminary analysis of comparative transcriptome was
   designed to explore genes variation related with mulberry by RNA‐Seq.
   This efficient deep‐sequencing not only revealed pathways involved in
   muscle formation and development, but verified variation of gene
   expression in vivo.

   A previous study that investigated the development of pig muscle
   tenderness found that the genes related to muscle tenderness were
   mainly involved in three functional networks, namely cell cycle, energy
   metabolism and muscle development (Lobjois et al., [81]2008). In the
   present study, GO analysis indicated that DEGs associated with dietary
   mulberry leaf supplementation were related to muscle and tissue
   structure. Furthermore, other previous studies have shown that
   polyphenols, such as those from hops and grapes, can improve growth and
   feed conversion, possibly by inhibiting inflammatory processes or
   affecting microbiota (Fiesel, Gessner, & Most, [82]2014; Gessner,
   Bonarius, & Most, [83]2017), and mulberry leaves probably contain
   polyphenols that could exert similar effects. Therefore, future studies
   could explore whether dietary polyphenol supplementation affects the
   expression of genes in pig muscle.

   Muscle formation was tightly linked to meat quality, and genes related
   to muscle formation would be important in pig growth. Troponin T (TnT)
   is encoded by three homologous genes, which are specifically expressed
   in slow skeletal muscle (TNNT1), cardiac muscle (TNNT2) and fast
   skeletal muscle (TNNT3) (Amarasinghe, Hossain, & Jin, [84]2016; Novelli
   et al., [85]1992). Previous work has demonstrated that TnT, a 30‐ to
   35‐kDa myofilament protein, functions as an organizer in the calcium
   regulation process of muscle contraction and relaxation and that TnT
   interacts with TnI, TnC, tropomyosin and actin (Davoli et al.,
   [86]2003). Recently, the gene was widely researched for its role in
   muscle function‐related diseases, such as nemaline myopathy and
   Duchenne muscular dystrophy, as well as in resistance exercise in older
   adults (Baker et al., [87]2006; Zhang et al., [88]2010). Meanwhile,
   TNNC1 was also one of the genes expressed in slow skeletal muscle. Such
   slow muscle‐related genes are reportedly upregulated in mouse models
   that lack both dystrophin and the dystrophin homolog utrophin, when
   compared to mice that are only deficient in dystrophin (Baker et al.,
   [89]2006). In contrast to one previous study, the present study found
   that TNNT1 and TNNC1 were both significantly enriched in muscle
   contraction‐related GO terms, and the two genes have also been shown as
   the validation of biomarkers for the quality of pork loin meat
   (Pierzchala et al., [90]2014). In the present study, both TNNT1 and
   TNNC1 were significantly upregulated, which could explain why the
   mulberry‐fed pigs exhibited lower water loss rates and shear force
   values. Thus, the dynamic relationship between pork quality and the
   expression of TNNC1 and TNNT1 should be studied further, in order to
   confirm the role of the genes in pig associated with the effect of
   mulberry leaves.

   In addition, the key role of MYCL3 in muscle quality was indicated by
   PPI network analysis of the DEGs, and expression of the gene was also
   significantly elevated in pigs fed diets that were supplemented with
   mulberry leaves. GO analysis suggested that MYL3 is mainly involved in
   cardiac muscle contraction. Ropka‐Molik et al. ([91]2014 used
   next‐generation RNA‐Seq technology to investigate two different pig
   breeds with different performance in terms of muscularity, growth rate
   and reproduction traits and found that MYCL3 was one of most abundantly
   expressed genes in both breeds. Zhang et al. ([92]2014 reported that
   the downregulation of MYCL3 might indicate the negative regulation of
   intramuscular fat development, and the upregulation of MYCL3 also
   appears to be associated with injury to skeletal muscle, possibly in
   order to facilitate muscle production (Burch et al., [93]2015).
   However, the general role of MYCL3 in muscle production remains
   elusive. Although the significant higher expression levels of MYCL3
   have been evaluated, the gene network associated with intramuscular fat
   developments should be further verified in animal trail.

   The present study possesses several limitations that are worth noting.
   First, even though the study demonstrated the beneficial effects of
   dietary mulberry leaves, the number of pigs enrolled in the trial was
   small. Second, even though the results indicate the potentially
   significant modulatory role of TNNC1, MYL3 and TNNT1 in the development
   of meat quality in pigs, it is important that the molecular mechanism
   associated with the genes in pigs be verified in vivo.

5. CONCLUSIONS

   In conclusion, the data in our study presented here that mulberry
   leaves were benefit in pigs might mainly involve in muscle development,
   which might profit from the upregulated genes including TNNC1, MYL3 and
   TNNT1. However, it should be noted that the dynamic relationship
   between muscle development of pig and the genes expression levels
   should be further studied to confirm the role of the genes in pig
   associated with the effect of mulberry leaves.

CONFLICT OF INTEREST

   The authors declare that they have no conflict of interest.

ETHICAL STATEMENT

   The authors confirm that the ethical policies of the journal, as noted
   on the journal's author guidelines page, have been adhered to and the
   appropriate ethical review committee approval has been received. The US
   National Research Council's guidelines for the Care and Use of
   Laboratory Animals were followed.

Supporting information


   [94]Click here for additional data file.^ (20.5KB, docx)

ACKNOWLEDGEMENTS