Parabacteroides faecalis sp. nov. Isolated from Swine Faeces.

A Gram-negative, obligate anaerobic, non-motile, non-spore-forming, rod-shaped bacterial strain designated AGMB00274T was isolated from swine faeces. An 16S rRNA gene analysis indicated that strain AGMB00274T belonged to the genus Parabacteroides, with the highest similarity to Parabacteroides johnsonii (P. johnsonii) DSM 18315T (sequence similarity of 94.9%). The genome size of strain AGMB00274T was 4,308,683 bp, with a DNA G+C content of 42.5 mol%. The biochemical analysis of strain AGMB00274T showed that it was positive for gelatin hydrolysis and α-fucosidase, but negative for the acid production from D-glucose, D-mannitol, D-maltose, salicin, glycerol, D-cellobiose, D-mannose, D-melezitose, D-sorbitol, D-trehalose, and negative for α-arabinosidase, glutamic acid decarboxylase, and pyroglutamic acid arylamidase. The dominant cellular fatty acids (> 10%) of the isolate were anteiso-C15: 0 (23.2%), iso-C15: 0 (16.6%), C18: 1 ω9c (16.4%), summed feature 11 (iso-C17: 0 3-OH and/or C18: 2 DMA) (12.5%), and C16: 0 (11.3%). The major respiratory quinones of strain AGMB00274T were MK-9 (55.4%) and MK-10 (44.6%). The major polar lipid was phosphatidylethanolamine. Based on phylogenetic, genetic, physiological, and chemotaxonomic analyses, as a novel species of the genus Parabacteroides, strain AGMB00274T was proposed with the name Parabacteroides faecalis sp. nov. The type strain used was AGMB00274T (= KCTC 25286T = GDMCC 1.2742T).

Application of single-step genomic evaluation using social genetic effect model for growth in pig.

OBJECTIVE: Social genetic effects (SGE) are an important genetic component for growth, group productivity, and welfare in pigs. The present study was conducted to evaluate i) the feasibility of the single-step genomic best linear unbiased prediction (ssGBLUP) approach with the inclusion of SGE in the model in pigs, and ii) the changes in the contribution of heritable SGE to the phenotypic variance with different scaling ω constants for genomic relationships. METHODS: The dataset included performance tested growth rate records (average daily gain) from 13,166 and 21,762 pigs Landrace (LR) and Yorkshire (YS), respectively. A total of 1,041 (LR) and 964 (YS) pigs were genotyped using the Illumina PorcineSNP60 v2 BeadChip panel. With the BLUPF90 software package, genetic parameters were estimated using a modified animal model for competitive traits. Giving a fixed weight to pedigree relationships (τ: 1), several weights (ωxx, 0.1 to 1.0; with a 0.1 interval) were scaled with the genomic relationship for best model fit with Akaike information criterion (AIC). RESULTS: The genetic variances and total heritability estimates (T2) were mostly higher with ssGBLUP than in the pedigree-based analysis. The model AIC value increased with any level of ω other than 0.6 and 0.5 in LR and YS, respectively, indicating the worse fit of those models. The theoretical accuracies of direct and social breeding value were increased by decreasing ω in both breeds, indicating the better accuracy of ω0.1 models. Therefore, the optimal values of ω to minimize AIC and to increase theoretical accuracy were 0.6 in LR and 0.5 in YS. CONCLUSION: In conclusion, single-step ssGBLUP model fitting SGE showed significant improvement in accuracy compared with the pedigree-based analysis method; therefore, it could be implemented in a pig population for genomic selection based on SGE, especially in South Korean populations, with appropriate further adjustment of tuning parameters for relationship matrices.

Genetic association between sow longevity and social genetic effects on growth in pigs.

OBJECTIVE: Sow longevity is important for efficient and profitable pig farming. Recently, there has been an increasing interest in social genetic effect (SGE) of pigs on stress-tolerance and behavior. The present study aimed to estimate genetic correlations among average daily gain (ADG), stayability (STAY), and number of piglets born alive at the first parity (NBA1) in Korean Yorkshire pigs, using a model including SGE. METHODS: The phenotypic records of ADG and reproductive traits of 33,120 and 11,654 pigs, respectively, were evaluated. The variances and (co) variances of the studied traits were estimated by a multi-trait animal model applying the Bayesian with linear-threshold models using Gibbs sampling. RESULTS: The direct and SGEs on ADG had a significantly negative (-0.30) and neutral (0.04) genetic relationship with STAY, respectively. In addition, the genetic correlation between the social effects on ADG and NBA1 tended to be positive (0.27), unlike the direct effects (-0.04). The genetic correlation of the total effect on ADG with that of STAY was negative (-0.23) but non-significant, owing to the social effect. CONCLUSION: These results suggested that total genetic effect on growth in the SGE model might reduce the negative effect on sow longevity because of the growth potential of pigs. We recommend including social effects as selection criteria in breeding programs to obtain satisfactory genetic changes in both growth and longevity.

Melatonin supplementation during prolonged in vitro maturation improves the quality and development of poor-quality porcine oocytes via anti-oxidative and anti-apoptotic effects.

Poor-quality oocytes (those with 1-2 layers of cumulus cells) typically possess low meiotic competence and development. Prolonging the duration of in vitro maturation (IVM; 52 hr) can enhance the maturation rate of poor-quality oocytes, but it does not improve subsequent embryonic development. This likely reflects the increased reactive oxygen species (ROS) production and apoptosis seen in these oocytes compared with the non-prolonged IVM (44 hr) group. Melatonin is a free radical scavenger, anti-oxidant and anti-apoptotic agent that reported to enhance the quality of embryos by inhibiting ROS generation and apoptosis. Therefore, we herein investigated whether melatonin combined with prolonged IVM (52 hr) could improve the quality and development of poor-quality oocytes. We supplemented IVM and/or in vitro culture (IVC) media with various concentrations (0, 10-7 , 10-6 , 10-5 M) of melatonin, and estimated parameters related to oocyte quality and development. The addition of melatonin (10-6 M) to a prolonged IVM system improved the oocyte quality and development compared with those of the melatonin-free poor-quality oocytes group, and that this was due to decreases in ROS generation, apoptosis, and DNA damage. When melatonin was added during both IVM (10-6 M) and IVC (10-6 M), we observed a cumulative positive influence on the embryonic development and quality; this treatment enhanced the expression level of Oct4 and decreased the levels of ROS, DNA damage, and apoptosis. Together, these findings suggest that the combination of melatonin plus prolonged IVM can improve the quality and development of poor-quality porcine oocytes via anti-oxidative and anti-apoptotic effects.

Whole-genome association and genome partitioning revealed variants and explained heritability for total number of teats in a Yorkshire pig population.

OBJECTIVE: The study was designed to perform a genome-wide association (GWA) and partitioning of genome using Illumina's PorcineSNP60 Beadchip in order to identify variants and determine the explained heritability for the total number of teats in Yorkshire pig. METHODS: After screening with the following criteria: minor allele frequency, MAF≤0.01; Hardy-Weinberg equilibrium, HWE≤0.000001, a pair-wise genomic relationship matrix was produced using 42,953 single nucleotide polymorphisms (SNPs). A genome-wide mixed linear model-based association analysis (MLMA) was conducted. And for estimating the explained heritability with genome- or chromosome-wide SNPs the genetic relatedness estimation through maximum likelihood approach was used in our study. RESULTS: The MLMA analysis and false discovery rate p-values identified three significant SNPs on two different chromosomes (rs81476910 and rs81405825 on SSC8; rs81332615 on SSC13) for total number of teats. Besides, we estimated that 30% of variance could be explained by all of the common SNPs on the autosomal chromosomes for the trait. The maximum amount of heritability obtained by partitioning the genome were 0.22±0.05, 0.16±0.05, 0.10±0.03 and 0.08±0.03 on SSC7, SSC13, SSC1, and SSC8, respectively. Of them, SSC7 explained the amount of estimated heritability along with a SNP (rs80805264) identified by genome-wide association studies at the empirical p value significance level of 2.35E-05 in our study. Interestingly, rs80805264 was found in a nearby quantitative trait loci (QTL) on SSC7 for the teat number trait as identified in a recent study. Moreover, all other significant SNPs were found within and/or close to some QTLs related to ovary weight, total number of born alive and age at puberty in pigs. CONCLUSION: The SNPs we identified unquestionably represent some of the important QTL regions as well as genes of interest in the genome for various physiological functions responsible for reproduction in pigs.

A genome-wide association study of social genetic effects in Landrace pigs.

OBJECTIVE: The genetic effects of an individual on the phenotypes of its social partners, such as its pen mates, are known as social genetic effects. This study aims to identify the candidate genes for social (pen-mates') average daily gain (ADG) in pigs by using the genome-wide association approach. METHODS: Social ADG (sADG) was the average ADG of unrelated pen-mates (strangers). We used the phenotype data (16,802 records) after correcting for batch (week), sex, pen, number of strangers (1 to 7 pigs) in the pen, full-sib rate (0% to 80%) within pen, and age at the end of the test. A total of 1,041 pigs from Landrace breeds were genotyped using the Illumina PorcineSNP60 v2 BeadChip panel, which comprised 61,565 single nucleotide polymorphism (SNP) markers. After quality control, 909 individuals and 39,837 markers remained for sADG in genome-wide association study. RESULTS: We detected five new SNPs, all on chromosome 6, which have not been associated with social ADG or other growth traits to date. One SNP was inside the prostaglandin F2α receptor (PTGFR) gene, another SNP was located 22 kb upstream of gene interferon-induced protein 44 (IFI44), and the last three SNPs were between 161 kb and 191 kb upstream of the EGF latrophilin and seven transmembrane domain-containing protein 1 (ELTD1) gene. PTGFR, IFI44, and ELTD1 were never associated with social interaction and social genetic effects in any of the previous studies. CONCLUSION: The identification of several genomic regions, and candidate genes associated with social genetic effects reported here, could contribute to a better understanding of the genetic basis of interaction traits for ADG. In conclusion, we suggest that the PTGFR, IFI44, and ELTD1 may be used as a molecular marker for sADG, although their functional effect was not defined yet. Thus, it will be of interest to execute association studies in those genes.

Transfer-Efficient Face Routing Using the Planar Graphs of Neighbors in High Density WSNs.

Face routing has been adopted in wireless sensor networks (WSNs) where topological changes occur frequently or maintaining full network information is difficult. For message forwarding in networks, a planar graph is used to prevent looping, and because long edges are removed by planarization and the resulting planar graph is composed of short edges, and messages are forwarded along multiple nodes connected by them even though they can be forwarded directly. To solve this, face routing using information on all nodes within 2-hop range was adopted to forward messages directly to the farthest node within radio range. However, as the density of the nodes increases, network performance plunges because message transfer nodes receive and process increased node information. To deal with this problem, we propose a new face routing using the planar graphs of neighboring nodes to improve transfer efficiency. It forwards a message directly to the farthest neighbor and reduces loads and processing time by distributing network graph construction and planarization to the neighbors. It also decreases the amount of location information to be transmitted by sending information on the planar graph nodes rather than on all neighboring nodes. Simulation results show that it significantly improves transfer efficiency.

Epigallocatechin-3-gallate-induced free-radical production upon adipogenic differentiation in bovine bone-marrow mesenchymal stem cells.

Epigallocatechin-3-gallate (EGCG), a major component of catechin in green tea, has known effects on cancer, diabetes and obesity. We recently reported that the expression levels of various genes and proteins involved in adipogenesis decreases following EGCG treatment. We also assessed apoptosis in EGCG-exposed cells. Here, we explore the variability in free-radical production in bovine bone-marrow mesenchymal stem cells (BMSCs) treated with EGCG. Upon adipogenic differentiation, BMSCs were exposed to various EGCG concentrations (0, 0.1, 1, 5, or 10 µM) for 2, 4, or 6 days. We found that EGCG reduced cell viability and arrested the cell cycle at the gap 2/mitosis phase and that EGCG potentially enhanced the production of free radicals, including reactive oxygen species and reactive nitrogen species, in a concentration- and time-dependent manner. Immunostaining revealed that the expression of genes encoding CCAAT/enhancer-binding protein alpha and stearoyl-CoA desaturase were diminished by EGCG treatment. These findings suggest that EGCG alters free-radical production activity during adipogenic differentiation in BMSCs.

Genomic selection for adjacent genetic markers of yorkshire pigs using regularized regression approaches.

This study considers a problem of genomic selection (GS) for adjacent genetic markers of Yorkshire pigs which are typically correlated. The GS has been widely used to efficiently estimate target variables such as molecular breeding values using markers across the entire genome. Recently, GS has been applied to animals as well as plants, especially to pigs. For efficient selection of variables with specific traits in pig breeding, it is required that any such variable selection retains some properties: i) it produces a simple model by identifying insignificant variables; ii) it improves the accuracy of the prediction of future data; and iii) it is feasible to handle high-dimensional data in which the number of variables is larger than the number of observations. In this paper, we applied several variable selection methods including least absolute shrinkage and selection operator (LASSO), fused LASSO and elastic net to data with 47K single nucleotide polymorphisms and litter size for 519 observed sows. Based on experiments, we observed that the fused LASSO outperforms other approaches.

Application of deep learning with bivariate models for genomic prediction of sow lifetime productivity-related traits.

OBJECTIVE: Pig breeders cannot obtain phenotypic information at the time of selection for sow lifetime productivity (SLP). They would benefit from obtaining genetic information of candidate sows. Genomic data interpreted using deep learning (DL) techniques could contribute to the genetic improvement of SLP to maximize farm profitability because DL models capture nonlinear genetic effects such as dominance and epistasis more efficiently than conventional genomic prediction methods based on linear models. This study aimed to investigate the usefulness of DL for the genomic prediction of two SLP-related traits; lifetime number of litters (LNL) and lifetime pig production (LPP). METHODS: Two bivariate DL models, convolutional neural network (CNN) and local convolutional neural network (LCNN), were compared with conventional bivariate linear models (i.e., genomic best linear unbiased prediction, Bayesian ridge regression, Bayes A, and Bayes B). Phenotype and pedigree data were collected from 40,011 sows that had husbandry records. Among these, 3,652 pigs were genotyped using the PorcineSNP60K BeadChip. RESULTS: The best predictive correlation for LNL was obtained with CNN (0.28), followed by LCNN (0.26) and conventional linear models (approximately 0.21). For LPP, the best predictive correlation was also obtained with CNN (0.29), followed by LCNN (0.27) and conventional linear models (approximately 0.25). A similar trend was observed with the mean squared error of prediction for the SLP traits. CONCLUSION: This study provides an example of a CNN that can outperform against the linear model-based genomic prediction approaches when the nonlinear interaction components are important because LNL and LPP exhibited strong epistatic interaction components. Additionally, our results suggest that applying bivariate DL models could also contribute to the prediction accuracy by utilizing the genetic correlation between LNL and LPP.

Population differentiated copy number variation between Eurasian wild boar and domesticated pig populations.

Sus scrofa is a globally distributed livestock species that still maintains two different ways of life: wild and domesticated. Herein, we detected copy number variation (CNV) of 328 animals using short read alignment on Sscrofa11.1. We compared CNV among five groups of porcine populations: Asian domesticated (AD), European domesticated (ED), Asian wild (AW), European wild (EW), and Near Eastern wild (NEW). In total, 21,673 genes were identified on 154,872 copy number variation region (CNVR). Differences in gene copy numbers between populations were measured by considering the variance-based value [Formula: see text] and the one-way ANOVA test followed by Scheffe test. As a result, 111 genes were suggested as copy number variable genes. Abnormally gained copy number on EEA1 in all populations was suggested the presence of minor CNV in the reference genome assembly, Sscrofa11.1. Copy number variable genes were related to meat quality, immune response, and reproduction traits. Hierarchical clustering of all individuals and mean pairwise [Formula: see text] in breed level were visualized genetic relationship of 328 individuals and 56 populations separately. Our findings have shown how the complex history of pig evolution appears in genome-wide CNV of various populations with different regions and lifestyles.

Knockdown of Y-box binding protein 1 induces autophagy in early porcine embryos.

Y-box binding protein 1 (YBX1) plays important roles in RNA stabilization, translation, transcriptional regulation, and mitophagy. However, its effects on porcine preimplantation embryos remain unclear. In this study, we knocked down YBX1 in the one-cell (1C) stage embryo via small interfering RNA microinjection to determine its function in porcine embryo development. The mRNA level of YBX1 was found to be highly expressed at the four-cell (4C) stage in porcine embryos compared with one-cell (1C) and two-cell (2C) stages. The number of blastocysts was reduced following YBX1 knockdown. Notably, YBX1 knockdown decreased the phosphatase and tensin homolog-induced kinase 1 (PINK1) and parkin RBR E3 ubiquitin protein ligase (PRKN) mRNA levels. YBX1 knockdown also decreased PINK1, active mitochondria, and sirtuin 1 levels, indicating reduced mitophagy and mitochondrial biogenesis. Furthermore, YBX1 knockdown increased the levels of glucose-regulated protein 78 (GRP78) and calnexin, leading to endoplasmic reticulum (ER) stress. Additionally, YBX1 knockdown increased autophagy and apoptosis. In conclusion, knockdown of YBX1 decreases mitochondrial function, while increasing ER stress and autophagy during embryonic development.

Individual and population diversity of 20 representative olfactory receptor genes in pigs.

Understanding the influence of genetic variations in olfactory receptor (OR) genes on the olfaction-influenced phenotypes such as behaviors, reproduction, and feeding is important in animal biology. However, our understanding of the complexity of the OR subgenome is limited. In this study, we analyzed 1120 typing results of 20 representative OR genes belonging to 13 OR families on 14 pig chromosomes from 56 individuals belonging to seven different breeds using a sequence-based OR typing method. We showed that the presence of copy number variations, conservation of locus-specific diversity, abundance of breed-specific alleles, presence of a loss-of-function allele, and low-level purifying selection in pig OR genes could be common characteristics of OR genes in mammals. The observed nucleotide sequence diversity of pig ORs was higher than that of dogs. To the best of our knowledge, this is the first report on the individual- or population-level characterization of a large number of OR family genes in livestock species.

Profiling of differentially expressed proteins between fresh and frozen-thawed Duroc boar semen using ProteinChip CM10.

Many studies have been conducted to improve technology for semen cryopreservation in pigs. However, computer-assisted analysis of sperm motility and morphology is insufficient to predict the molecular function of frozen-thawed semen. More accurate expression patterns of boar sperm proteins may be derived using the isobaric tags for relative and absolute quantification (iTRAQ) technique. In this study, the iTRAQ-labeling system was coupled with liquid chromatography tandem-mass spectrometry (LC-MS/MS) analysis to identify differentially expressed CM10-fractionated proteins between fresh and frozen-thawed boar semen. A total of 76 protein types were identified to be differentially expressed, among which 9 and 67 proteins showed higher and lower expression in frozen-thawed than in fresh sperm samples, respectively. The classified functions of these proteins included oxidative phosphorylation, mitochondrial inner membrane and matrix, and pyruvate metabolic processes, which are involved in adenosine triphosphate (ATP) synthesis; and sperm flagellum and motile cilium, which are involved in sperm tail structure. These results suggest a possible network of biomarkers associated with survival after the cryopreservation of Duroc boar semen.

An intelligent method for pregnancy diagnosis in breeding sows according to ultrasonography algorithms.

Pig breeding management directly contributes to the profitability of pig farms, and pregnancy diagnosis is an important factor in breeding management. Therefore, the need to diagnose pregnancy in sows is emphasized, and various studies have been conducted in this area. We propose a computer-aided diagnosis system to assist livestock farmers to diagnose sow pregnancy through ultrasound. Methods for diagnosing pregnancy in sows through ultrasound include the Doppler method, which measures the heart rate and pulse status, and the echo method, which diagnoses by amplitude depth technique. We propose a method that uses deep learning algorithms on ultrasonography, which is part of the echo method. As deep learning-based classification algorithms, Inception-v4, Xception, and EfficientNetV2 were used and compared to find the optimal algorithm for pregnancy diagnosis in sows. Gaussian and speckle noises were added to the ultrasound images according to the characteristics of the ultrasonography, which is easily affected by noise from the surrounding environments. Both the original and noise added ultrasound images of sows were tested together to determine the suitability of the proposed method on farms. The pregnancy diagnosis performance on the original ultrasound images achieved 0.99 in accuracy in the highest case and on the ultrasound images with noises, the performance achieved 0.98 in accuracy. The diagnosis performance achieved 0.96 in accuracy even when the intensity of noise was strong, proving its robustness against noise.

Genetic Parameter Estimation and Genome-Wide Association Analysis of Social Genetic Effects on Average Daily Gain in Purebreds and Crossbreds.

Average daily gain (ADG) is an important growth trait in the pig industry. The direct genetic effect (DGE) has been studied mainly to assess the association between genetic information and economic traits. The social genetic effect (SGE) has been shown to affect ADG simultaneously with the DGE because of group housing systems. We conducted this study to elucidate the genetic characteristics and relationships of the DGE and SGE of purebred Korean Duroc and crossbred pigs by single-step genomic best linear unbiased prediction and a genome-wide association study. We used the genotype, phenotype, and pedigree data of 1779, 6022, and 7904 animals, respectively. Total heritabilities on ADG were 0.19 ± 0.04 and 0.39 ± 0.08 for purebred and crossbred pigs, respectively. The genetic correlation was the greatest (0.77 ± 0.12) between the SGE of purebred and DGE of crossbred pigs. We found candidate genes located in the quantitative trait loci (QTLs) for the SGE that were associated with behavior and neurodegenerative diseases, and candidate genes in the QTLs for DGE that were related to body mass, size of muscle fiber, and muscle hypertrophy. These results suggest that the genomic selection of purebred animals could be applied for crossbred performance.

Genome-Wide Assessment of a Korean Composite Pig Breed, Woori-Heukdon.

A Korean synthetic pig breed, Woori-Heukdon (WRH; F3), was developed by crossing parental breeds (Korean native pig [KNP] and Korean Duroc [DUC]) with their crossbred populations (F1 and F2). This study in genome-wide assessed a total of 2,074 pigs which include the crossbred and the parental populations using the Illumina PorcineSNP60 BeadChip. After quality control of the initial datasets, we performed population structure, genetic diversity, and runs of homozygosity (ROH) analyses. Population structure analyses showed that crossbred populations were genetically influenced by the parental breeds according to their generation stage in the crossbreeding scheme. Moreover, principal component analysis showed the dispersed cluster of WRH, which might reflect introducing a new breeding group into the previous one. Expected heterozygosity values, which were used to assess genetic diversity, were .365, .349, .336, .330, and .211 for WRH, F2, F1, DUC, and KNP, respectively. The inbreeding coefficient based on ROH was the highest in KNP (.409), followed by WRH (.186), DUC (.178), F2 (.107), and F1 (.035). Moreover, the frequency of short ROH decreased according to the crossing stage (from F1 to WRH). Alternatively, the frequency of medium and long ROH increased, which indicated recent inbreeding in F2 and WRH. Furthermore, gene annotation of the ROH islands in WRH that might be inherited from their parental breeds revealed several interesting candidate genes that may be associated with adaptation, meat quality, production, and reproduction traits in pigs.

Integrative methylome and transcriptome analysis of porcine abdominal fat indicates changes in fat metabolism and immune responses during different development.

Fat is involved in synthesizing fatty acids (FAs), FA circulation, and lipid metabolism. Various genetic studies have been conducted on porcine fat but understanding the growth and specific adipose tissue is insufficient. The purpose of this study is to investigate the epigenetic difference in abdominal fat according to the growth of porcine. The samples were collected from the porcine abdominal fat of different developmental stages (10 and 26 weeks of age). Then, the samples were sequenced using MBD-seq and RNA-seq for profiling DNA methylation and RNA expression. In 26 weeks of age pigs, differentially methylated genes (DMGs) and differentially expressed genes (DEGs) were identified as 2,251 and 5,768, compared with 10 weeks of age pigs, respectively. Gene functional analysis was performed using GO and KEGG databases. In functional analysis results of DMGs and DEGs, immune responses such as chemokine signaling pathways, B cell receptor signaling pathways, and lipid metabolism terms such as PPAR signaling pathways and fatty acid degradation were identified. It is thought that there is an influence between DNA methylation and gene expression through changes in genes with similar functions. The effects of DNA methylation on gene expression were investigated using cis-regulation and trans-regulation analysis to integrate and interpret different molecular layers. In the cis-regulation analysis using 629 overlapping genes between DEGs and DMGs, immune response functions were identified, while in trans-regulation analysis through the TF-target gene network, the co-expression network of lipid metabolism-related functions was distinguished. Our research provides an understanding of the underlying mechanisms for epigenetic regulation in porcine abdominal fat with aging.

Fat is involved in the synthesis of new fatty acids (FAs), FA circulation, and lipid metabolism. Various genetic studies have been conducted on porcine fat but understanding the growth and specific adipose tissue is insufficient. The purpose of this study is to investigate the epigenetic difference in abdominal fat according to the growth of porcine. Modifications in DNA methylation and expression values were confirmed epigenetically with growth. Changed genes in each DNA and RNA showed identical trends in the function of immune response and lipid metabolism. The effects of DNA methylation on gene expression were investigated using cis-regulation (functional enrichment analysis of overlapping genes) and trans-regulation (transcription factor and target gene networking) analysis to integrate and interpret different molecular layers. Our research provides an understanding of the underlying mechanisms for epigenetic regulation in porcine abdominal fat with aging.