Identification of Genes related to Growth and Lipid Deposition from Transcriptome Profiles of Wujin Pigs and Landrace Pigs Muscle Tissue

As is widely recognized, Western pig breeds have the characteristics of high growth rate and high lean meat percentage. However, Chinese pigs own the high IMF content and excellent meat quality [1,2]. In recent years, consumers have increasingly turned their focus towards pork from indigenous breeds due to its succulence and distinctive flavor, paralleling the advancement of the national economy. In contrast to introduced breeds, indigenous breeds exhibit certain drawbacks, including lower percentages of lean meat and reduced water-holding capacity [3]. The Wujin pig, a native Chinese fat-type breed, is renowned for its superior meat quality and comparatively elevated IMF content [4-6]. The Landrace pig, a lean-type breed, is distinguished by its rapid growth rate and high proportion of lean meat [7]. Therefore, these two pig breeds offer valuable models with varying lipid deposition capacities to illuminate the fundamental mechanisms underlying intramuscular fat deposition in both adipose and lean pigs..

Traits related to fatness, such as back fat thickness and IMF content, exhibit positive correlations with meat tenderness, juiciness, and flavor [8]. These traits hold economic significance in pig breeding as they can exert an influence on meat quality and carcass composition. Chinese indigenous pigs, celebrated for their rich meaty flavor, typically possess intramuscular fat content exceeding 5%, in contrast to approximately 2% in imported commercial pigs [9]. Nonetheless, traits related to growth and meat quality are intricate quantitative characteristics influenced by numerous interacting genes. Transcriptome profiling offers an effective means to detect novel and less abundant transcripts.

Several RNA-seq studies have been conducted on muscle tissues from various animal species, including hen [10], cattle [11], large yellow croaker (Larimichthys crocea) [12], grass carp [13], goat [14], and black muscovy duck [15]. These studies have contributed to a more comprehensive understanding of the mRNA transcriptome in animal muscles. Transcriptome profiling enables the simultaneous measurement of differential gene expression in a specific tissue, making it a powerful tool for identifying genes associated with different phenotypes [2]. Our previous findings have suggested that the mechanism behind the elevated IMF content in fatty pigs may be attributed to their heightened lipogenesis and fatty acid transport capacity, while displaying a lower lipolysis capacity. However, research on the screening of genes related to muscle growth and intramuscular fat deposition through high-throughput sequencing technology is still limited, and the precise mechanisms governing muscle growth and fat deposition in both fat and lean pigs remain unclear.

In this study, we generated transcriptome profiles of muscle tissue in the Chinese indigenous pig breeds (Wujin pigs) and the introduced pig breeds (Landrace pigs) and conducted a comparative study of different breeds of pigs, and finally identified the functional genes and the regulation networks that control muscle growth and fat deposition in pigs.

Animal care

The experiments were performed according to the ARRIVE guidelines (https://arriveguidelines.org) and approved by the Ethics Committee of Experimental Animal of Yunnan Agricultural University (Approval Code: 201603017, Approval Date: 14 March 2016).

Animals and sampling

A total of three male Wujin pigs and three male Landrace pigs of the same batch with similar body weight were randomly selected as the study object raised in the pig-breeding institute of the Yunnan Academy of Animal Husbandry and Veterinary Sciences. Pigs of the same breed come from the same maternal parent and parity. They were raised under a standardized feeding regimen with free access to water. Once the pigs reached a body weight of 100 kg, they were transported to the Yunnan Agricultural Center Meats Laboratory and slaughtered following electrical stunning. Muscle tissues from the longissimus dors were collected from each animal. A portion was preserved at -20 °C for IMF content analysis, while the remainder was frozen in liquid nitrogen for total RNA extraction.

Determination of intramuscular fat content

The IMF content of muscle samples was determined after extraction of crude fat using Soxhlet Extraction (SZF-06A, Shanghai Xinjia Electronic Co., Ltd., Shanghai, China) with petroleum ether (boiling temperature range: 60 °C to 90 °C). Three replications were conducted for each sample.

Determination of fatty acid content

Intramuscular fat was extracted through the method of Bligh. The extract was used for Saturated Fatty Acid (SFA), Monounsaturated Fatty Acid (MUFA), and Polyunsaturated Fatty Acid (PUFA) measurements. The SFAs, MUFA, and PUFA were analyzed via Gas Chromatography (GC)..

Transcriptome sample preparation for sequencing

Total RNA was extracted from the longissimus muscle of pigs using the RNA Simple Total RNA kit (TIANGEN, Beijing, China). Sequencing libraries were prepared with the NEBNext Ultra Directional RNA Library Prep Kit for Illumina (NEB, Ipswich, USA), following the manufacturer’s instructions.

Clustering and sequencing

The indexing and clustering of the samples were carried out using a cBot Cluster Generation System, employing the TruSeq PE Cluster Kit v3-cBot-HS (Illumina), following the manufacturer’s guidelines. Subsequently, the prepared libraries were sequenced on an Illumina HiSeq platform, producing 100 bp paired end reads.

Mapping and assembling of reads to the reference genome

The quality filtered fastq files were mapped to the Sus scrofa reference genome build 11.1. Top Hat (version 2.1.0.) and HTSeq (version 0.6.1) were used to count the read numbers mapped to each gene. RPKM of each gene was calculated based on the length of the gene and read counts mapped to this gene.

Differential expression analysis

Prior to differential gene expression analysis, for each sequenced library, the read counts were adjusted by edger program package through one scaling normalized factor. Differential expression analysis of two conditions was performed using the DEGSeq R package (1.12.0). The p values were adjusted using the Benjamini and Hochberg method. Corrected p value of 0.05 and log2 (fold change) of 1 were set as the threshold for significant differential gene expression.

Functional analysis of differentially expressed genes

Gene Ontology (GO) enrichment analysis of differentially expressed genes was implemented by the GOseq R package, in which gene length bias was corrected. GO terms with P-value less than 0.05 were considered significantly enriched by differentially expressed genes. Kyoto Encyclopedia of Genes and Genomes (KEGG) is a database resource by genome sequencing and other high-throughput experimental technologies. KEGG was used to understand the advanced functions and utility of biological systems.

Protein-protein interaction network (PPI) construction and module analysis

The protein-protein interaction network of the DEGs was constructed based on the Search Tool for the Retrieval of Interacting Genes (STRING) database (STRING, version 9.1, http://string91. embl.de/) [16], and predicted by the use of Cytoscape (version 3.0; http://cytoscape.org/). The hub genes were then selected with a connectivity degree 10 after calculating the degree of each node. Module analysis of the PPI network was performed with the parameters of minimum size > 4 and minimum density < 0.05 using Molecular Complex Detection (MCODE) [17].

Data analysis

The acquired data were initially processed in an Excel spreadsheet and analyzed using one-way ANOVA in SPSS 25.0. The results are presented in tables as means with pooled standard errors of the means (SEM). Multiple comparisons of means were conducted using LSD and Duncan methodologies, with significance determined based on P-values. Extremely significant differences were indicated by P < 0.01, significant differences by P < 0.05, and non-significant differences by P > 0.05.

Saturated fatty acid and intramuscular fat content

The results of the SFA, MUFA, PUFA, and IMF content for the two pig breeds are presented in Table 1. Wujin pigs exhibited higher IMF levels compared to Landrace pigs (P < 0.05), while they showed lower SFA and PUFA levels than Landrace pigs (P < 0.05). These results suggest that the muscle tissues the muscle tissues are suitable for identifying genes associated with muscle growth and lipid deposition.

Table 1:Fatty acid and intramuscular fat content of the longissimus dorsi muscle in two pig breeds.

Note: SFA, saturated fatty acid; MUFA, monounsaturated fatty acid; PUFA, polyunsaturated fatty acid; IMF, Intramuscular fat. SFA: C14:0, C16:0, C18:0, C20:0, MUFA: C16:1, C18:1, PUFA: C18:2, C18:3, C20:4, C20:5, C22:5. Data are expressed as means ± SEM and values in the same row with asterisks differ significantly (* P<0.05, ** P <0.01).

High-throughput sequencing and read mapping

In this study, a total of six libraries in muscle tissue were established by high-throughput RNA sequencing. The number of original reads for Wujin pigs was 6,795,774, and Landrace pigs was 7,229,998. After quality control of the original reads with Q20, sequence duplication level, and GC content, there was 6,589,139 clean reads for Wujin pigs, accounting for 99.18% of the original reads, and 7,171,030 clean reads for Landrace pigs, accounting for accounting for 99.18%. The samples were of good quality, and the percentage of reads aligned to the unique location of the reference genome was 80.82% to 94% among the clean reads, and the unique matched reads were 85.16% and 74.64% (Table 2). In summary, the sequencing data was qualified for the subsequent data analysis.

Table 2:Summary of sequencing reads aligned with the Sus scrofa genome and annotated genes.

The detected genes were distributed in all chromosomal regions, and the genome coverage was plotted along the chromosome based on the expression of genes. If the FPKM values of all the detected genes were divided into five intervals, less than 0.1, 0.1 to 0.3, 0.3to 3.75, 3.75 to 15, 15 to 60 and more than 60, the distribution of the FPKM of the genes was shown to be similar (Figure 1).

Figure 1:Summary of RNA sequence (RNA-Seq) mapping data. A. Reads density in chromosome and mapped reads number in chromosome. B. The number of detected genes with different expression levels against the range of fragments per kilobase of exon length million mapped reads (FPKM) values.

Differentially expressed genes analysis

With P < 0.05 and |log2 FC| > 1 as the threshold, a total of 682 DEGs were identified. Among them, we identified 296 up-regulated genes and 386 down-regulated genes when comparing Wujin and Landrace pigs (Figure 2). The most significant 15 up-regulated differentially expressed genes in Wujin pigs and Landrace pigs (Table S1). The most significant 15 down-regulated differentially expressed genes in Wujin pigs and Landrace pigs (Table S2). A number of differentially expressed genes were highly expressed in the muscle tissues of both groups.

Figure 2:Preliminary analysis of transcriptome profiles.
A. Volcano plot of genes differentially expressed between Wujin and Landrace pigs. The y-axis corresponds to the mean expression value of log10 (P-value), and the x-axis displays the log2 (FC) value. The red dots represent the significantly expressed genes (FDR<0.05), the blue dots represent the genes whose expression levels did not reach statistical significance.
B. Cluster heat map of DEGs. Each row represents a gene. Different colors indicate the expression levels of genes in pigs. The redder, the higher the expression level; the bluer, the lower the expression level.

Table S1:List of the most significant15 up-regulated differentially expressed genes in Wujin pigs and Landrace pigs.

Note: “-” represents one or two groups’ reads count were 0.

Table S2:List of the most significant 15 down-regulated differentially expressed genes in Wujin pigs and Landrace pigs..

Note: “-” represents one or two groups’ reads count were 0.

In the 682 DEGs, three genes, TMEM182, AGL, and ADCY9 exhibited prominent differential expression with P < 0.001 and |log2FC| > 1 that are related to lipid deposition (Table 3). Four genes, PDP1, EGR1, IL6R, ATF3 and exhibited prominent differential expression with P < 0.001 and |log2FC|> 1 that are related to muscle growth (Table 4).

Table 3:Differentially expressed genes with |log2FC|>1 and P <0.001 that are related to lipid deposition.

Table 4:Differentially expressed genes with |log2FC|>1 and P<0.001 that are related to muscle growth.

GO annotation and enrichment analysis of differentially expressed genes

Figure 3:GO term enrichment analysis of Differentially Expressed Genes (DEGs). Brown column, violet column and cyan column meant Cellular Component (CC), Molecular Function (MF), and Biological Process (BP), respectively.

To further elucidate the functional roles of the 682 DEGs, GO term enrichment analysis was performed to search for significantly overrepresented categories. A total of 496 terms were significantly enriched in the three categories (P < 0.05), including biological process, cellular component, and molecular function (Table S3). The 34 top terms were obtained by GO enrichment, including 7 terms for biological process, 23 terms for cell component, and 4 terms for molecular function and were further analyzed to determine the associated regulatory functions. Three terms were related to lipid metabolism, including cholesterol import, chylomicron remnant clearance, and cholesterol efflux (Figure 3).

Table S3:GO term enrichment of differentially expressed genes.

Kyoto encyclopedia of genes and genomes enrichment for functional analysis of differentially expressed genes

To identify the pathways these DEGs involved, we integrated the 682 DEGs into the KEGG pathway database, and a total of 185 pathways were enriched (Table S4). KEGG pathway enrichment analysis showed that the DEGs were statistically significantly enriched in 11 pathways (P < 0.05) (Figure 4). The pathways associated with muscle growth and lipid deposition include biosynthesis of unsaturated fatty acids, ErbB signaling pathway, metabolic pathways, and oxidative phosphorylation.

Table S4:KEGG pathways enrichment of differentially expressed genes.

Figure 4:The diagrams for the KEGG pathway enrichment degree of DEGs. The abscissa indicates the value of rich factors (the ratio of annotated DEGs to all genes of the enriched pathway); the ordinate indicates the pathways enriched. The P-value of each term is represented by the color depth. The number of DEGs is indicated by the size of the circle. Note that the complete list of bioinformatics analysis results is shown in Supplementary Tables.

PPI network construction and hub gene dentification

After STRING analysis of the DEGs, the PPI network was constructed with 418 nodes and 863 interactions (Figure 5). After being visualized by Cytoscape the connectivity degree of each node was calculated. NDUFV1 (NADH: Ubiquinone Oxidoreductase Core Subunit V1), NDUFB9 (NADH: Ubiquinone Oxidoreductase Subunit B9), UQCRC1 (Ubiquinol-Cytochrome C Reductase Core Protein 1), NDUFA10 (NADH: Ubiquinone Oxidoreductase Subunit A10), NDUFS2 (NADH: Ubiquinone Oxidoreductase Core Subunit S2), ATP5MC1 (ATP Synthase Membrane Subunit C Locus 1), NDUFS6 (NADH: Ubiquinone Oxidoreductase Subunit S6), COX4I1 (Cytochrome C Oxidase Subunit 4I1), TUFM (Tu Translation Elongation Factor, Mitochondrial), and NDUFB8 (NADH: Ubiquinone Oxidoreductase Subunit B8) were the top 10 hub genes with the closest connections to other nodes (Figure 6A). The whole PPI network was analyzed by MCODE (Figure 6B). A total of 12 modules were identified within the PPI network. Among these, four modules (Modules 1-4) with both MCODE score > 5 and nodes > 5 were further selected for functional analysis. The pathway enrichment analysis revealed that DEGs in module 1 were involved in cellular respiration and energy production and indirectly affect muscle growth. The genes in module 1 were up regulated in Landrace pigs muscle tissue.

Figure 5:PPI network construction.

Figure 6:Hub gene identification. A. Top 10 hub gene identification via cytohubba. B. Module 1 identification via MCODE.

In this study, the longissimus dorsi muscle samples from two pig breeds, comprising a Chinese breed (Wujin pigs) and an introduced breed (Landrace pigs), were used to compare the differences of the transcriptome’s profiles. We identified 682 DEGs that were mainly enriched in GO terms associated with cholesterol import, chylomicron remnant clearance, cholesterol efflux, and regulation of the lipid metabolic process, etc. In previous studies, the amount of DEG in pig muscle tissue is slightly different based on transcriptome analysis [18-21]. It is speculated that the reason is that the experimental design or screening threshold is different. In the present study, we selected a fat-type pig breed (Wujin pigs) known for its characteristics of high lipid deposition and slow body growth and contrasted it with a lean-type pig breed (Landrace pigs) known for its traits of low lipid deposition and fast growth. And SFA, PUFA and IMF content measured in this study (Table 1) confirmed the phenotype difference between the breeds. The three genes associated with muscle growth, as well as the four genes linked to fat deposition, which we have identified, have also been previously documented in earlier studies [22,23].

Fat deposition in adipose is a complex metabolic process involving many genes, including coding and no coding genes [24]. In this study, GO and KEGG analysis results of DEGs showed that Wujin pig muscle had strong lipid deposition capacity. Among them, cholesterol import, chylomicron remnant clearance, cholesterol efflux, and biosynthesis of unsaturated fatty acids were significantly enriched. This may also further explain the characteristics of the high intramuscular fat content characteristics of Wujin pigs. Our previous report indicated that the mechanism of higher IMF content in fatty pig breeds may be due to the higher expression of lipogenic genes and fatty acids transporting genes and the lower expression of lipid catabolic genes in muscle tissue [25]. This conclusion is repeated in this study. In our data, the key lipogenic genes such as ATF3 and EGR1 had higher expression levels in the group with high-IMF content, which may be the reason for the stronger lipid deposition capacity in the Chinese pigs than the introduced pigs.

In this study, the construction of the PPI network and the identification of the hub genes were carried out for the differential expression genes. Ten hub genes were screened, including DUFB8, TUFM, NDUFB9, ATP5MC1, NDUFS2, NDUFA10, NDUFS6, NDUFV1, COX4I1, UQCRC1. The hub genes are primarily associated with the downregulation of the mitochondrial respiratory chain and energy metabolism. Muscle growth and maintenance require a lot of energy, and mitochondria play an important role in energy production in cells [26,27]. The proteins encoded by these genes are involved in the mitochondrial respiratory chain and energy expenditure, which is critical for providing sufficient energy to support the growth, repair, and function of the harvested muscle tissue [28]

ATF3 is a stress-induced transcription factor that plays vital roles in modulating metabolism, immunity, and oncogenesis [29]. The expression of ATF3 gene can be regulated by nutrients and metabolic signals, such as insulin and glucocorticoids. These metabolic signals play an important role in fat deposition and muscle growth. Therefore, the expression of ATF3 gene may have some indirect connection with fat deposition and muscle growth process. There are research reports that PDP1 may function as part of a larger protein/DNA complex that interacts with Myocyte Enhancer Factor 2 (MEF2) to regulate transcription of Drosophila muscle genes [30]. However, the functions of these candidate genes remain to be further investigated.

In conclusion, this study did a transcriptomic analysis in the longissimus dorsi muscle tissue of Wujin pigs and Landrace pigs. In this study, we identified 682 DEGs potentially associated with crucial pathways of muscle growth and lipid deposition, such as cholesterol import, chylomicron remnant clearance, cholesterol efflux, biosynthesis of unsaturated fatty acids, the ErbB signaling pathway, and oxidative phosphorylation. And 3 and 4 of the DEGs were related closely to muscle growth and lipid metabolism, respectively. In summary, this study presents several candidate genes for porcine muscle growth and lipid deposition and provides a basis for future research on the molecular.

Thanks for the support of the National Natural Science Foundation of China (32360808, 31760645, 31260592, 31060331), Major Science and Technology Project of Yunnan Province (202202AE090032), State School Cooperation (2021533416000035).

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