# Differential DNA methylation analysis across the promoter regions using methylated DNA immunoprecipitation sequencing profiling of porcine loin muscle

Kaj Chokeshaiusaha, Denis Puthier, Thanida Sananmuang, Em-On Olanratmanee, Catherine Nguyen, Roongtham Kedkovid

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Kaj Chokeshaiusaha, Denis Puthier, Thanida Sananmuang, Em-On Olanratmanee, Catherine Nguyen, et al.. Differential DNA methylation analysis across the promoter regions using methylated DNA immunoprecipitation sequencing profiling of porcine loin muscle. Veterinary World, 2020, 13, pp.1113 - 1125. 10.14202/vetworld.2020.1113-1125. hal-03015708

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# Differential DNA methylation analysis across the promoter regions using methylated DNA immunoprecipitation sequencing profiling of porcine loin muscle

Kaj Chokeshaiusaha¹, Denis Puthier², Thanida Sananmuang¹, Em-on Olanratmanee¹, Catherine Nguyen² and Roongtham Kedkovid³,⁴

1. Department of Veterinary Science, Faculty of Veterinary Medicine, Rajamangala University of Technology Tawan-OK, Chon Buri, Thailand; 2. Aix-Marseille University, INSERM UMR 1090, TAGC, Marseille, France; 3. Department of Veterinary Medicine, Faculty of Veterinary Science, Chulalongkorn University, Bangkok, Thailand; 4. Swine Reproduction Research Unit, Chulalongkorn University, Bangkok, Thailand.

**Corresponding author:** Roongtham Kedkovid, e-mail: roongthamk@gmail.com

**Co-authors:** KC: kajchk@gmail.com, DP: denis.puthier@univ-amu.fr, TS: tsananmuang@gmail.com, EO: em-on_ol@rmutto.ac.th, CN: catherine.nguyen@univ-amu.fr

**Received:** 13-01-2020, **Accepted:** 05-05-2020, **Published online:** 16-06-2020

**doi:** www.doi.org/10.14202/vetworld.2020.1113-1125 **How to cite this article:** Chokeshaiusaha K, Puthier D, Sananmuang T, Olanratmanee E, Nguyen C, Kedkovid R (2020) Differential DNA methylation analysis across the promoter regions using methylated DNA immunoprecipitation sequencing profiling of porcine loin muscle, *Veterinary World*, 13(6): 1113-1125.

## Abstract

**Background and Aim:** Pork leanness and marbling are among the essential traits of consumer preference. To acquire knowledge about universal epigenetic regulations for improving breed selection, a meta-analysis of methylated DNA immunoprecipitation sequencing (MeDIP-seq) profiling data of mixed loin muscle types was performed in this study.

**Materials and Methods:** MeDIP-seq profiling datasets of longissimus dorsi muscle and psoas major muscles from male and female pigs of Landrace and Tibetan breeds were preprocessed and aligned to the porcine genome. Analysis of differential methylated DNA regions (DMRs) between the breeds was performed by focusing on transcription start sites (TSSs) of known genes (−20,000-3000 bases from TSS). All associated genes were further reviewed for their functions and predicted for transcription factors (TF) possibly associated with their TSSs.

**Results:** When the methylation levels of DMRs in TSS regions of Landrace breed were compared to those of Tibetan breed, 10 DMRs were hypomethylated (Landrace < Tibetan), and 19 DMRs were hypermethylated (Landrace > Tibetan), accordingly (p≤0.001). According to the reviews about gene functions, all associated genes were pieces of evidence for their roles in a variety of muscle and lipid metabolisms. Prediction of the binding TFs revealed the six most abundant binding TFs to such DMRs-associated TSS (p≤0.0001) as follows: ZNF384, Foxd3, IRF1, KLF9, EWSR1-FLI1, HES5, and TFAP2A.

**Conclusion:** Common DMRs-associated TSS between the lean-type and the marbled-type loin muscles were identified in this study. Interestingly, the genes associated with such regions were strongly evidenced for their possible roles on the muscle trait characteristics by which further novel research topics could be focused on them in the future.

**Keywords:** differential DNA methylation, lean, loin muscle, marbled, methylated DNA immunoprecipitation sequencing, transcription start site.

## Introduction

Pork has been accounted for a large-scale world's meat consumption. Lately, the evolved preference of pork consumers significantly affects its amendment in taste, flavor, juiciness, and tenderness [1,2]. These issues thus become one of the most critical concerns in fields of both veterinary and animal health science as pork leanness and marbling are two essential traits contributing to its quality [1-3]. Diverse cascading gene transcription control by epigenetic modification was well-recognized for its involvement in such phenotypic variations among pig breeds [4-7]. The

knowledge in epigenome concerning porcine musculo-genesis and lipogenesis has thus significantly contributed to advance in swine breeding for decades [3-6,8]. For further explanation, epigenetic gene regulation by DNA methylation involves primarily *cis*-acting DNA elements which are the non-coding DNA binding sites for the gene transcription factors (TFs). Apart from the promoter region, which commonly locates near the transcription start site (TSS), the chromatin loop formation also allows the long-distant *cis*-acting elements such as enhancers and repressors to cooperate in regulation [9]. *Cis*-acting elements in mammals, including pigs, usually contain repeated CpG bases, by which their methylation can interfere TF binding. The methylation patterns are inheritable among animal breeds, including swine, and responsible for different transcription patterns among the tissues of interest [4-6,9,10]. To study the intricate regulation patterns of genome-wide DNA methylome, large-scale identification of enriched methylated sequences is thus

<footnote>Copyright: Chokeshaiusaha, et al. Open Access. This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.</footnote>
required. Isolation of these methylated DNA fragments could be archived by the antibody against 5-methyl-cytosine, the purification technique recognized as methylated DNA immunoprecipitation (MeDIP) [11]. Coupling of MeDIP and short-read sequencing technologies even allow the high-throughput sequencing of methylated DNA fragments, the technology recognized as MeDIP-sequencing (MeDIP-seq) [12]. Despite its recent introduction, MeDIP-seq has been applied with a few cell types to discover differential DNA methylation patterns among different swine breeds [4,5,7,11,13]. Despite the insight into the epigenetic background of swine breeds implied by the past studies, some limitations in such knowledge's application should also be concerned about.

DNA methylation profiling data of a tissue sample are a composited methylation pattern acquired from common cell types in the particular tissue [14]. Methylation profiling of each tissue type should not be considered as a good representative among one another [14,15]. Fortunately, differential DNA methylation analysis between lean-type and obese-type pig breeds was previously performed using the MeDIP-seq technology. With few replicated muscle tissue samples, a pooled library of one muscle type was constructed entirely for both DNA-seq and mRNA-seq analyses [4]. In the analysis of sequencing data, numbers of discrete biological replicate crucially influence representativeness of the differential analysis outcome [16,17]. By mean of this, the inclusion of numbers of different muscle type biosamples in differential methylation analysis should result in different significant patterns which are universal among various muscle-type tissues.

It should be noted that distances of cis-acting DNA elements from their corresponding TSSs could vary from few to further than 20 Kb [9,18]. While methylated elements are commonly presumed to regulate the transcription of the nearest gene promoter, their distant functions were also evidenced [19,20]. With clusters of different TFs possibly associated with these elements, they can complexly control the transcription of the targeted genes [19,20]. Virtualization of the methylated elements' distances from the TSS and their associated TFs' prediction is thus crucial for productive genome-wide DNA methylation profiling observation. Despite such feasibility, procedures to attain such knowledge in porcine muscle MeDIP-seq study were still limitedly demonstrated.

Gradual increase of porcine meat muscle MeDIP-seq profiling data in the public database has offered us an opportunity to demonstrate the analytical process with them. With available datasets acquired from two types of joint meat muscles, differential DNA methylation profiling analysis between lean and marbled meat pig breeds was performed in this study. Distance determination and TF prediction respectable to the regions were also demonstrated. By including numbers of different muscle tissue datasets, methylated DNA regions associated with the several

well-recognized genes between lean and marbled meat muscle were successfully identified.

## Materials and Methods

### Ethical approval

All datasets used in this study were available in NCBI SRA public site, and no ethical approval was required.

### Sample datasets

The list of porcine meat muscle tissue MeDIP-seq profiling datasets is provided in Table-1. Longissimus dorsi muscle and psoas major muscles from both male and female pigs were included in this study. These muscle tissues were generated from two swine breeds: Landrace as the lean-type breed and Tibetan as the marbled-type meat breed.

### Study period and location

The research was conducted at Department of Veterinary Science, Faculty of Veterinary Medicine, Rajamangala University of Technology Tawan-OK, Chon Buri, Thailand, from August 2019 until the end of January 2020.

### Analytical workflow

The analytical workflow of this study is shown in Figure-1. The preprocessed sample datasets were

<table><caption>Table-1: Porcine muscle tissue datasets used in this study.</caption><thead><tr><td>Dataset</td><td>Breed</td><td>Sex</td><td>Muscle tissue</td></tr></thead><tbody><tr><td>SRR307959</td><td>Landrace</td><td>Male</td><td>Longissimus dorsi muscle</td></tr><tr><td>SRR307960</td><td>Landrace</td><td>Male</td><td>Longissimus dorsi muscle</td></tr><tr><td>SRR307961</td><td>Landrace</td><td>Male</td><td>Longissimus dorsi muscle</td></tr><tr><td>SRR307962</td><td>Landrace</td><td>Male</td><td>Psoas major muscle</td></tr><tr><td>SRR307963</td><td>Landrace</td><td>Male</td><td>Psoas major muscle</td></tr><tr><td>SRR307964</td><td>Landrace</td><td>Male</td><td>Psoas major muscle</td></tr><tr><td>SRR307989</td><td>Landrace</td><td>Female</td><td>Longissimus dorsi muscle</td></tr><tr><td>SRR307990</td><td>Landrace</td><td>Female</td><td>Longissimus dorsi muscle</td></tr><tr><td>SRR307991</td><td>Landrace</td><td>Female</td><td>Longissimus dorsi muscle</td></tr><tr><td>SRR307992</td><td>Landrace</td><td>Female</td><td>Psoas major muscle</td></tr><tr><td>SRR307993</td><td>Landrace</td><td>Female</td><td>Psoas major muscle</td></tr><tr><td>SRR307994</td><td>Landrace</td><td>Female</td><td>Psoas major muscle</td></tr><tr><td>SRR308019</td><td>Tibetan</td><td>Male</td><td>Longissimus dorsi muscle</td></tr><tr><td>SRR308020</td><td>Tibetan</td><td>Male</td><td>Longissimus dorsi muscle</td></tr><tr><td>SRR308021</td><td>Tibetan</td><td>Male</td><td>Longissimus dorsi muscle</td></tr><tr><td>SRR308022</td><td>Tibetan</td><td>Male</td><td>Psoas major muscle</td></tr><tr><td>SRR308023</td><td>Tibetan</td><td>Male</td><td>Psoas major muscle</td></tr><tr><td>SRR308024</td><td>Tibetan</td><td>Male</td><td>Psoas major muscle</td></tr><tr><td>SRR308049</td><td>Tibetan</td><td>Female</td><td>Longissimus dorsi muscle</td></tr><tr><td>SRR308050</td><td>Tibetan</td><td>Female</td><td>Longissimus dorsi muscle</td></tr><tr><td>SRR308051</td><td>Tibetan</td><td>Female</td><td>Longissimus dorsi muscle</td></tr><tr><td>SRR308052</td><td>Tibetan</td><td>Female</td><td>Psoas major muscle</td></tr><tr><td>SRR308053</td><td>Tibetan</td><td>Female</td><td>Psoas major muscle</td></tr><tr><td>SRR308054</td><td>Tibetan</td><td>Female</td><td>Psoas major muscle</td></tr></tbody></table>
<figure><img src="image_2.png" /><figcaption>**Figure-1:** Analytical workflow for this study.</figcaption></figure>

aligned to the porcine genome to acquire aligned
datasets and counted for the methylated DNA
sequence reads (read counts). Differential DNA
methylation analysis between muscle datasets of
Landrace and Tibetan pigs was performed. Both dif-
ferential methylation results and read counts in Reads
Per Kilobase Millions were visualized by the Circos
plot (Figure-1). Differentially methylated DNA
regions (DMRs) between Landrace and Tibetan pigs
were subsequently determined for their proximity to
TSSs of the associated genes (–20,000-3000 bases
from TSS) and displayed by a customized plot (linear
genomes displaying in Figure-1). All the associated
genes were reviewed for their functions. Finally, TFs
associated with these regions would then be predicted
(Figure-1).

Data preprocessing and quality assessment

The sequence read archive (SRA) files of porcine muscle MeDIP-Seq datasets were obtained from the SRA database (https://www.ncbi.nlm.nih.gov/sra) (Table-1). Data preprocessing was performed as previously described with some modifications [21]. Briefly, each dataset was aligned to the porcine reference genome (Sus scrofa UCSC susScr3) with the Bowtie2 aligner (version 2.3.4.3) [22]. Duplicated sequences of the aligned datasets were then removed [23]. Phred quality score was determined by FastQC [24]. The assessment of MeDIP-Seq quality and DNA methylation score was performed by Bioconductor package MEDIPS (250-bp windows) after extending read to a length of 300 bp [25].

DMRs between landrace and Tibetan pigs

DMRs between Landrace and Tibetan pigs were
identified (p≤0.001) by edgeR (exact test for negative
binomial distribution) integrated with the MEDIPS
package. TSSs of porcine genes were annotated using
the porcine genome (Sscrofa 11.1) acquired from the
Ensembl database (version 95) (https://asia.ensembl.
org/info/data/ftp/index.html). This study only con-
sidered the DMRs within -20,000-+3000 bases from
TSS. Gene promoter region was considered from
-1000 to +500 bases from TSS and was exclusively

remarked for the presence of differential methylation
within the regions in the karyoplot (Figure-2).

Prediction of binding TFs

RSAT Matrix-Scan (http://rsat.ulb.ac.be/) was
used to detect TF binding sites (http://rsat.sb-roscoff.
fr/) among the DMRs. Individual sites were predicted
using the various position matrix of non-redundant
TF binding profiles of vertebrates (JASPAR CORE,
non-redundant vertebrates database) and filtered using
a threshold on p=10⁻⁶. For matrix-scan, the first-order
Markov chain background model was calculated from
the input sequence set.

Virtualization

Count reads of overall methylated DNA regions
along with their DMRs between Landrace and Tibetan
pigs were illustrated by the Circos plot using the
Bioconductor OmicCircos package [26]. To display
the DMRs associated with the target genes of interest,
the karyoplotER package [27].was utilized to draw the
plot for displaying the locations of DMRs and their
associated TSSs.

Results

Genome-wide DNA methylation profiling and their
differentially methylated DNA regions

After removing the contaminated, low quality,
and adapter sequences, each preprocessed dataset had
approximately 64 million clean reads (40-42 bps) with
at least an 85% alignment rate to the *S. scrofa* refer-
ence genome. The data showed sufficient sequence
depth, and coverage analyses revealed that approx-
imately 95% of all CpGs in the *S. scrofa* genome
was covered at least one-fold, whereas nearly 50%
of CpGs were covered more than five-fold. Patterns
of canonical epigenetic DNA methylation observed
among longissimus dorsi muscle and psoas major
muscle tissues acquired from both Landrace and
Tibetan breeds were similar, by which strong positive
correlation across the breed was demonstrated by cor-
relation analysis (r=0.75-0.95, p<10⁻¹⁶). The compar-
ison of the DNA methylation profiles of the Landrace
and Tibetan breeds revealed 74,009 DMRs (p≤0.001)
<figure><img src="image_3.png" /></figure>

a

<table><thead><tr><th>Chr</th><th>GeneID</th><th>Color</th><th>GeneName</th><th>Start</th><th>End</th><th>log2FC</th></tr></thead><tbody><tr><td rowspan="5">chr1</td><td rowspan="5">ENSSSCG00000027257</td><td rowspan="5">PSMB1</td><td></td><td>12601</td><td>12900</td><td>1.14</td></tr><tr><td></td><td>14401</td><td>14700</td><td>1.46</td></tr><tr><td></td><td>18301</td><td>18600</td><td>1.20</td></tr><tr><td></td><td>23101</td><td>23700</td><td>1.09</td></tr><tr><td></td><td>24301</td><td>25200</td><td>1.47</td></tr><tr><td rowspan="3">chr2</td><td>ENSSSCG00000014560</td><td>COX8H</td><td></td><td>83701</td><td>84000</td><td>1.08</td></tr><tr><td>ENSSSCG00000014561</td><td>NLRP6</td><td></td><td>83701</td><td>84000</td><td>1.08</td></tr><tr><td>ENSSSCG00000025023</td><td>PGGHG</td><td></td><td>83701</td><td>84000</td><td>1.08</td></tr><tr><td rowspan="2">chr3</td><td>ENSSSCG00000007542</td><td>PRKAR1B</td><td>421501</td><td>421800</td><td>1.04</td></tr><tr><td>ENSSSCG00000007543</td><td>DNAAF5</td><td>421501</td><td>421800</td><td>1.04</td></tr><tr><td>chr4</td><td>ENSSSCG000000038957</td><td></td><td></td><td>55801</td><td>56700</td><td>1.87</td></tr><tr><td>chr5</td><td>ENSSSCG00000021265</td><td>ACR</td><td></td><td>33901</td><td>34200</td><td>2.10</td></tr></tbody></table>

<figure><img src="image_4.png" /><figcaption>**Figure-2:** Linear genomes displaying methylated regions associated with gene transcription start sites (TSS). The karyoplot of 18 porcine genes with the presence of methylated DNA regions associated with their TSS (−20,000-3000) and promoter regions (−1000-500). Partial porcine genome sequences acquired from 17 chromosomes (chr) containing all associated gene transcripts were drawn with loci index (a-d). Promoter regions of transcripts presented on the same chromosome were demonstrated in different shaded colors – sky blue, orange, and pink, accordingly. Differentially hypomethylated to hypermethylated regions were demonstrated by gradient colors from deep blue to deep red respective to their −log₁₀ p-values. The levels of differences were indexed by two-fold changes (– for hypomethylated and + for hypermethylated). The bottom legends indicated the Ensembl ID and common names of the targeted genes in each of the chr.</figcaption></figure>
<figure><img src="image_5.png" /><figcaption>**Figure-2:** (Continued).</figcaption></figure>
<figure><img src="image_6.png" /><figcaption>**Figure-2:** (Continued).</figcaption></figure>
<figure><img src="image_7.png" /><figcaption>**Figure-2:** (Continued).</figcaption></figure>
<table><caption>**Table-2:** Methylated TSS associated genes with evidenced roles in muscle tissues.</caption><thead><tr><td>Chr</td><td>GeneID</td><td>Common name</td><td>Function</td><td>References</td></tr></thead><tbody><tr><td>chr1</td><td>ENSSSCG00000027257</td><td>PSMB1</td><td>Upregulated according to obesity, PSMB1 was transcriptional activator of RBP4 – a gene associated with insulin resistance and transcription activation of adipocyte.</td><td>[28,29]</td></tr><tr><td>chr2</td><td>ENSSSCG00000014560</td><td>COX8H</td><td>COX8H was related to cytochrome C oxidase – the crucial enzyme with potential role in oxidative and fatty acid metabolisms of muscle fibers.</td><td>[30,31]</td></tr><tr><td>chr3</td><td>ENSSSCG00000014561</td><td>NLRP6</td><td>NLRP6 was the sensor component of NLPP3 inflammasome which could enhance muscular dystrophy and was strongly associated with obesity.</td><td>[7,32-34]</td></tr><tr><td>chr6</td><td>ENSSSCG00000026662</td><td>hPRDM7</td><td>PGGHG was a catalyzing enzymes of D-glucose, and thus could affect both muscle and adipose cell's metabolisms. PRKAR1B encoded a regulatory subunit of cyclic AMP-dependent protein kinase A in the signaling pathway of the second messenger cAMP – contributing to myofiber size and negatively associating with intramuscular fat.</td><td>[35,36]</td></tr><tr><td>chr7</td><td>ENSSSCG00000029761</td><td>hURAD</td><td>PRDM7 could function as a histone methyltransferase, and thus was likely affect DNA methylation affecting muscle tissue development and function.</td><td>[38]</td></tr><tr><td>chr10</td><td>ENSSSCG00000010801</td><td>CDC73</td><td>URAD enzyme catalyzed anti-oxidant process of uric acid to form allantoin – the marker of oxidative stress in muscle. DUSP22 protein activate the JNK signaling pathway – regulating the phosphorylation state of several kinases in skeletal muscle and requiring for obesity. DUSP22 was an obesity candidate gene which was hypermethylated in obese subject.</td><td>[39,40]</td></tr><tr><td>chr11</td><td>ENSSSCG00000022638</td><td>ATP12A</td><td>ATP12A was responsible for potassium absorption for muscle contraction – by which the lack of potassium could result in muscle destruction by decreased blood flow.</td><td>[51,52]</td></tr><tr><td>chr12</td><td>ENSSSCG00000017137</td><td>METRNL</td><td>METRNL product was associated with adipocyte browning and glucose tolerance.</td><td>[53]</td></tr><tr><td>chr13</td><td>ENSSSCG00000027229</td><td>CPNE4</td><td>Several miRNAs in skeletal muscle could regulate myogenesis, hypertrophy, atrophy, and regeneration. CPNE4 product was calcium-dependent phospholipid-binding protein, and thus can involve in several calcium-mediated processes in muscle tissue.</td><td>[54]</td></tr><tr><td>chr14</td><td>ENSSSCG00000038672</td><td>hCHCHD2</td><td>CHCHD2 was a transcription factor of cytochrome C oxidase required for optimal mitochondrial function of muscle cell.</td><td>[55]</td></tr><tr><td>chr15</td><td>ENSSSCG00000022011</td><td>NMI</td><td>N-myc can functionally replace c-myc in murine development, cellular growth, and differentiation.</td><td>[56]</td></tr><tr><td>chr16</td><td>ENSSSCG00000032942</td><td>DAP</td><td>DAP was necessary for complete myotube development during muscle fiber formation.</td><td>[57]</td></tr><tr><td>chrX</td><td>ENSSSCG00000038044</td><td>GYG2</td><td>Glycogenin was important for muscle glycogenesis – by which glycogen over-accumulation could result in fatigue reduced function of muscle.</td><td>[58]</td></tr></tbody></table>

differential methylation analysis to discover the universal differences in DNA methylation pattern of loin muscle to understand the differences between lean and marbled meat pig breeds. Since only rigid cellular metabolisms were controlled in universal patterns among tissue types, limited numbers of genes with differentially methylated TSS regions were expected as successfully demonstrated in this study.

Several novel genes with TSS-associated DMRs were also exclusively identified in this study. Apart from constructing sample libraries

from different meat tissues, other factors, such as muscle types, dataset numbers, and pig breeds, were also considered as contributors to such achievement (Figure-2). For the available virtualization of these regions' localization following their associated genes, the karyoplot was successfully applied [27]. Among all the presented TSS-associated DMRs, some DMRs in the promoter regions of three coding genes, ESSSCG00000038672 (hCHCHD2), ESSSCG00000027257 (PSMB1), and ESSSCG00000031489 (DUSP22) were also
<table><caption>**Table-3:** Top predicted transcription factors binding to differentially methylated TSS regions.</caption><thead><tr><th>TSS regions</th><th>Transcription factor</th><th>Weight</th><th>p-value</th><th>*Significant score</th></tr></thead><tbody><tr><td>chr1:12601-12900</td><td>EGR4</td><td>8.7</td><td>1.6E-05</td><td>4.796</td></tr><tr><td>chr1:14401-14700</td><td>ZSCAN4</td><td>8.3</td><td>6.3E-06</td><td>5.201</td></tr><tr><td>chr1:18301-18600</td><td>GATA1::TAL1</td><td>10.1</td><td>8.1E-06</td><td>5.092</td></tr><tr><td>chr1:23101-23700</td><td>TEAD1</td><td>9.3</td><td>2.3E-06</td><td>5.638</td></tr><tr><td>chr1:24301-25200</td><td>ZNF143</td><td>9.1</td><td>3.2E-06</td><td>5.495</td></tr><tr><td>chr10:670801-671400</td><td>Foxd3</td><td>10.3</td><td>3.5E-06</td><td>5.456</td></tr><tr><td>chr11:110701-111000</td><td>KLF9</td><td>11.6</td><td>5.8E-07</td><td>6.237</td></tr><tr><td>chr11:120601-120900</td><td>Dmbx1</td><td>10.7</td><td>3.2E-06</td><td>5.495</td></tr><tr><td>chr12:257701-258000</td><td>ZNF384</td><td>10.2</td><td>4.8E-07</td><td>6.319</td></tr><tr><td>chr13:365701-366300</td><td>ZNF384</td><td>10.1</td><td>1.1E-06</td><td>5.959</td></tr><tr><td>chr14:10801-11100</td><td>NFYA</td><td>9.6</td><td>1.2E-05</td><td>4.921</td></tr><tr><td>chr14:26401-26700</td><td>SPI1</td><td>4.7</td><td>2.9E-05</td><td>4.538</td></tr><tr><td>chr14:301-600</td><td>CTCF</td><td>14.2</td><td>6.7E-08</td><td>7.174</td></tr><tr><td>chr14:6601-6900</td><td>Foxd3</td><td>11</td><td>9.1E-07</td><td>6.041</td></tr><tr><td>chr15:922801-923100</td><td>TBP</td><td>10.7</td><td>1.5E-06</td><td>5.824</td></tr><tr><td>chr16:324601-324900</td><td>RBPJ</td><td>9.2</td><td>1E-05</td><td>5</td></tr><tr><td>chr17:193501-194400</td><td>NFIL3</td><td>10</td><td>8.4E-06</td><td>5.076</td></tr><tr><td>chr18:366601-366900</td><td>EWSR1-FLI1</td><td>6.8</td><td>1.3E-06</td><td>5.886</td></tr><tr><td>chr2:83701-84000</td><td>RELB</td><td>8.9</td><td>2E-05</td><td>4.699</td></tr><tr><td>chr3:421501-421800</td><td>SNAI2</td><td>8.7</td><td>1.7E-06</td><td>5.77</td></tr><tr><td>chr4:55801-56700</td><td>HSF4</td><td>11.4</td><td>1.4E-06</td><td>5.854</td></tr><tr><td>chr5:33901-34200</td><td>HIC2</td><td>8.4</td><td>1.1E-05</td><td>4.959</td></tr><tr><td>chr6:67201-67500</td><td>DLX2</td><td>8.3</td><td>7.5E-06</td><td>5.125</td></tr><tr><td>chr6:78901-79200</td><td>Arid5a</td><td>10.1</td><td>3.1E-06</td><td>5.509</td></tr><tr><td>chr7:26101-26400</td><td>SP2</td><td>12.4</td><td>4.2E-07</td><td>6.377</td></tr><tr><td>chr7:34801-35400</td><td>Stat5a::Stat5b</td><td>9.9</td><td>5.7E-06</td><td>5.244</td></tr><tr><td>chr7:43801-44400</td><td>HIF1A</td><td>11.8</td><td>1.6E-07</td><td>6.796</td></tr><tr><td>chr7:44701-45300</td><td>KLF5</td><td>11.2</td><td>8.7E-07</td><td>6.06</td></tr><tr><td>chrX:42301-42600</td><td>Klf1</td><td>11.1</td><td>1.7E-06</td><td>5.77</td></tr></tbody></table>

*Significant score = -log10 (p-value x nb.words). TSS=Transcription start sites

noticeable (Figure-2a-c). Due to the robust influence of promoter on epigenetic gene regulation [9,19]. these differentially methylated genes should be considered as exclusive candidates for further transcription determination. Of note, the current study only focused on TSS-associated methylated regions. Further analysis of other potential epigenetic gene regulation regions, including gene exons [60] and introns [61,62], was thus encouraged in separated studies.

In this study, several novel genes in loin muscles manifested their differences in the TSS region methylation levels in Landrace comparing to Tibetan pigs. Landrace pig is recognized for its lean large muscle bundle, while Tibetan pig muscle is more compact with outstanding marbling levels [63]. The different characteristics of the two breeds thus greatly denoted the diverge metabolisms of their muscle tissues. Supporting this, almost all differentially methylated genes also manifested their evidenced functions relating to musculogenesis and lipid metabolisms in this study (Table-2). Interestingly, two differentially methylated miRNA genes, ENSSSCG00000020190

and ENSSSCG00000020232, were also identified (Figure-2d), contributing new targets for a miRNA study in the skeletal muscles [54].

The regulatory function of the acquired TSS-associated DMRs required further biological evaluation despite the knowledge of their methylation levels. Since DNA methylation could either inhibit or recruit particular TFs in various circumstances [9,20,64], the prediction of candidate TFs binding regions was thus crucial to study their epigenetic gene regulation. Due to the limited demonstration of such process in porcine skeletal muscle MeDIP-seq study, we introduced the RSAT Matrix-Scan as a convenient web-based tool for the prediction of TF binding. Of note, this study intentionally showed only TFs with the highest prediction significant score for demonstration. Since each TSS region could be occupied by various TFs [65]. other significantly predicted TFs (p≤10⁻⁶) should also be considered for any further intensive study.

## Conclusion

In summary, the determination of TSS regions that were differentially methylated between lean-type
and marbled-type pig breeds in loin meat muscle tissues was demonstrated as a novel approach in this study. The procedure rendered the limited numbers of differentially methylated genes, but with strong concatenation with the different muscle characteristics presented between these two breeds. We also introduced a karyoplot for the available virtualization of TSS-associated DMRs along with their candidate TFs binding to them. As a result, the knowledge acquired from this study established several new research topics in lean and marbled meats to evaluate the epigenetic gene regulation. It is worth noting that this study aimed to demonstrate a beneficial strategy for porcine muscle MeDIP-Seq data analysis, which was also applicable to other biological systems.

## Authors' Contributions

KC, TS and RK planned the study design, collected the datasets, and analyzed the data. EO and CN refined the study design and the objective. DP carried out technical coding correction and hardware maintenance. KC and RK drafted and reviewed the manuscript. All authors read and approved the final manuscript.

## Acknowledgments

The authors are thankful to the Office of Academic Resource and Information Technology, Rajamangala University of Technology Tawan-OK for the contribution of server computer for the burden analysis. The authors did not receive any funds for this study.

## Competing Interests

The authors declare that they have no competing interests.

## Publisher's Note

Veterinary World remains neutral with regard to jurisdictional claims in published institutional affiliation.

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