Multi-Omics Analysis Reveals Flavor Differences Between Queshan And Yunong Black Pigs

Multi-Omics Analysis Reveals Flavor Differences Between Queshan And Yunong Black Pigs | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Multi-Omics Analysis Reveals Flavor Differences Between Queshan And Yunong Black Pigs Bingjie Wang, Yilin Wei, Chang Wang, Lebin Chang, Tengfei Wang, and 9 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7304887/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 10 Nov, 2025 Read the published version in BMC Genomics → Version 1 posted 10 You are reading this latest preprint version Abstract Background Flavor is an important factor influencing consumers' evaluation of pork. However, the molecular regulatory mechanism of flavor differences among different pig breeds remains unclear. In this study, using flavoromics, transcriptomics and lipidomics techniques, the key genes and substances in the longissimus dorsi muscle of Queshan Black Pig (QS) and Yunong Black Pig (YN) were identified and analyzed. Results Between the two breeds, 37 differential volatile organic compounds (VOCs), 2,559 differentially expressed genes (DEGs) and 460 differential lipids (DELs) were identified. Flavoromics identified phenol, pyridine and 1-hexanol as potential flavor biomarkers. Transcriptomics indicated that DEGs were mainly enriched in pathways such as fatty acid degradation and AMPK signaling pathway. Moreover, 10 lipids, including PC (26:3) and PE (34:6e), emerged as potential biomarkers. Multi-omics analysis further identified 14 VOCs, 15 DEGs and 10 DELs as being associated with pork flavor. These may regulate lipid production and lipolysis by participating in fatty acid (FA) biosynthesis, FA oxidation and glycerophospholipid metabolism. Finally, this study found that ACAA2 promoted the lipid deposition of porcine intramuscular preadipocytes and 3T3-L1 cells. Conclusions These results provide important insights into the flavor differences between QS and YN pork and the underlying molecular regulatory mechanisms. They also offer theoretical references for improving the quality of pork. pigs flavor flavoromics transcriptomics lipidomics ACAA2 Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 1 Introduction Pork is one of the most widely consumed meat products globally, and its quality directly affects consumers' preferences and market value. However, meat quality is a complex multidimensional trait that mainly includes organoleptic attributes such as flavor, tenderness, juiciness and color, and is comprehensively affected by a combination of several factors, including genetics, nutrition, living conditions and slaughter treatment[ 1 ]. Flavor, which encompasses aroma and taste, is a crucial element in evaluating pork quality and profoundly influences consumers' sensory experience[ 2 ]. VOCs mainly include aldehydes, esters, ketones, hydrocarbons, furans, and alcohols, etc. These substances are generated by flavor precursor substances through lipid oxidation, Strecker reaction, Maillard reaction, and thiamine degradation, thereby contributing to the formation of flavor aroma. Flavor precursor substances can be divided into two major categories: water-soluble and lipid-soluble. Among them, the former chiefly comprise amino acids (AAs), reducing sugars, peptides, and thiamine, etc., while lipid-soluble precursor substances mainly include lipids. It has been reported that amino acids and peptides can enhance the flavor of meat, and most amino acids have one or more of the taste qualities such as sweetness, saltiness, bitterness, sourness, or umami [ 3 ]. They can generate sulfur-, nitrogen-, and oxygen-containing aromatic compounds through the Maillard reaction, which constitute the main aroma of cooked meat[ 4 ]. Cysteine and methionine are also considered the biggest contributors to the development of meat flavor[ 2 ]. Lipids, as important lipid-soluble flavor precursor substances, the free fatty acids (FAs) produced by their decomposition can be further converted into specific flavor compounds[ 5 ]. Current research generally believes that phospholipids are the key lipids determining the flavor of meat products, and phosphatidylcholine (PC) is the most abundant phospholipid molecule in muscle, being the main cause of flavor changes[ 6 ]. In addition, phosphatidylethanolamine (PE) is also crucial for the formation of good flavor during processing[ 5 ]. Intramuscular fat (IMF) as an important component of flavor precursors, is mainly composed of lipids and glycerides, with lipids being the main component, accounting for 60–70%[ 7 ]. Studies have shown that meat flavor comes from the interaction of volatile compounds, and high IMF content can increase the content of volatile compounds[ 8 ]. Moreover, gender, age, feeding management, genetics, and slaughtering and processing methods all affect the formation of flavor substances. In recent years, the rapid advancement of omics technologies, including flavomics, transcriptomics and lipidomics have provided new perspectives for in-depth exploration of the formation mechanism of pork flavor[ 9 ]. Among them, two-dimensional gas chromatography-time-of-flight mass spectrometry (GC×GC-TOF-MS), as a highly sensitive and high-resolution analytical method, can more comprehensively identify VOCs in pork, thereby revealing the chemical basis of flavor differences[ 10 , 11 ]. For example, Zhao et al. [ 12 ] employed UHPLC-MS/MS coupled with GC×GC-TOF MS to investigate flavor profiles unique to Guanling, Sinan, and Simmental-crossbred cattle. Pork flavor is regulated by multiple genes. The application of RNA-seq can explore the genetic basis of flavor differences in pork more deeply. At the same time, combined with liquid chromatography-mass spectrometry (LC-MS) technology to accurately analyze the composition and changes of lipid compounds in pork, clarify the key role of lipid oxidation in the formation of flavor, and thereby construct a systematic molecular regulatory network of pork flavor[ 13 ]. Following millennia of domestication and selection, the majority of Chinese native breeds have distinct genetic characteristics of excellent meat quality[ 14 ]. The local Chinese breed QS is well known for its high content of IMF, stable genetic traits, rich flavor and excellent meat quality, and is considered a valuable genetic resource in China's livestock gene banks[ 15 ]. The Duroc pig have been crossbred with the excellent local breeds of Nanyang Black pig, Laiwu Black pig, and Erhualian pig to produce the YN[ 16 , 17 ], which have remarkable traits such as high fertility rate and strong feed tolerance. Therefore, comprehending the differences of meat quality, especially in flavor between Chinese local pigs and new breeds can both reveal the molecular mechanisms underlying pork flavor and offer a theoretical foundation for breeding pigs with excellent meat quality. This study focused on QS and YN as the subjects to systematically combine flavouromic, transcriptomic and lipidomic analyses to compare the key genes and substances in flavor formation among different pork varieties, and to deeply analyze the molecular regulatory mechanisms of pork flavor. Through multi-omics combined analysis, the key gene closely related to fatty acid metabolism and lipid synthesis - Acetyl-CoA acyltransferase 2 ( ACAA2 ) was screened out[ 18 ], and the impact of ACAA2 on adipocyte differentiation was further explored. This research provides new insights on the regulatory mechanism of pork flavor formation and lays the foundation for the breeding and molecular mechanism research of high-quality pork. 2 Materials and Methods 2.1 Animals and samples collection In this study, 10 castrated boars each were selected from QS (provided by the Qushan Black Pig Farm in Henan Province) and YN (provided by Henan Yifa Animal Husbandry Co., Ltd.), and they were reared under similar management and feeding conditions, the diet formulations are detailed in table S1 . These pigs were allowed to feed and drink water without restrictions. All the test pigs were raised and managed under similar conditions. When their body weight reached 101 ± 5.35 kg, they were blinded by electric shock and then slaughtered. The longissimus dorsi (LD) of pigs was collected from the front end of the third thoracic vertebra in the penultimate section for meat quality determination and sample preservation. Three samples were collected from each pig, with the entire collection process completed within 45 minutes. Then, four pigs were randomly selected from the two breeds respectively for sequencing analysis. The remaining samples were stored at − 80°C for subsequent experiments. 2.2 Meat quality, FAs and AAs samples analysis Samples were collected in accordance with the " NY/T 821–2019 Technical Specification for Determination of Pig Muscle Mass." And the meat quality indexes such as water content, crude protein content, IMF, meat color 24h , marbling score, pH at 24h post-slaughter (pH 24h ) and drip loss (DL) were determined. Biological tests were conducted thrice for each index, and the average value was utilized for subsequent analysis. FAs were determined according gas chromatography (DB37/T 3817 − 2019) and AAs were determined by Liquid Chromatography (LC) according to Elite-AKK amino acid analysis manual. 2.3 Flavoromic analysis Flavoromics study of the LD was performed to examine the VOCs in QS and YN. Analyses were conducted using a LECO Pegasus® 4D instrument (LECO Corporation, St. Joseph, MI, USA). High-purity helium (> 99.999%) served as the carrier gas, at a steady flow rate of 1.0 mL/min. The detection of flavor compounds was carried out using the LECO Pegasus BT 4D system. The NIST2020 database and the Chroma TOF (1.2.0.6) search software were utilized to annotate the flavor compounds on the original data off the machine. Additionally, PubChem (2022) and Classyfire (2022) were used to annotate and analyze the types of flavor substances, as well as the number and relative content of various flavor substances[ 19 ]. 2.4 Transcriptomic analysis and validation RNA extraction was conducted using TRIzol reagent (15596018, Thermo Fisher Scientific, Waltham, MA, USA) and its integrity was evaluated using a gel imaging system (Bio-Rad, Hercules, CA, USA), and its purity was measured using a Nanodrop NC2000 spectrophotometer (Thermo Fisher Scientific, Waltham, MA, USA). Utilizing an Illumina NovaSeq 6000 (Novogene Bioinformatics Technology Co., Ltd., Beijing, China), the samples underwent paired-end high-throughput sequencing. The reference genome was mapped to the filtered sequencing reads using the upgraded HISAT2 (2.1.0) software, which is an improved version of TopHat2. The DEGs were detected using the DESeq algorithm, with conditions of P -value 1.2 or FC < 0.83. Reverse transcription was performed using the Evo M-MLV RT Kit (AG11705, Accurate Biotechnology (Hunan) Co., Ltd., Changsha, Hunan, China). Next, quantitative real-time polymerase chain reaction (qRT-PCR) was conducted on the CFX96™ Real-Time System (Thermo Fisher Scientific, Waltham, MA, USA) using SYBR Green Premix Pro Taq HS qPCR Kit (AG11701, Accurate Biotechnology (Hunan) Co., Ltd., Changsha, Hunan, China). Each reaction was conducted in triplicate, with glyceraldehyde-3-phosphate dehydrogenase ( GAPDH ) serving as the normalization controls. The relative levels of gene expression were determined using the 2 −ΔΔCt method. 2.5 Untargeted lipidomic analysis Untargeted lipidomics analysis was performed on LD of QS and YN to examine lipid composition. After lipids were extracted, an ACQUITY UPLC® BEH C18 (2.1 mm × 100 mm, 1.7 m, Waters Corporation, Milford, MA, USA) column kept at 50℃ was utilized for the chromatographic separation. The temperature inside the capillaries was 325℃. The normalized collision energy was 30 eV, and dynamic exclusion was employed to remove extraneous data from the MS/MS spectra. 2.6 Comprehensive analysis of flavoromics, transcriptomics and lipidomics To deeply explore the influence of VOCs, DEGs and DELs on the flavor of pork, this study conducted Pearson correlation analysis on the flavoromics, transcriptomics and lipidomics data through the website of OmicShare tools ( https://www.omicshare.com/ ). In pairwise comparisons and joint analysis among the omics, the strong correlations among VOCs, DEGs nd DELs were identified by the standard of P 0.8, thereby screening out the key VOCs, genes and lipids that affect the flavor of pork. In addition, the interaction relationships among them were visualized by constructing network diagrams. 2.7 Isolation, culture and transfection of porcine intramuscular preadipocytes Porcine intramuscular preadipocytes were isolated according to previously described methods[ 20 ], which were cultured using complete medium containing 89% DMEM (Beijing Solarbio Science & Technology Co., Ltd., Beijing, China), 10% FBS (Gibco, Carlsbad, CA, USA), and 1% penicillin-streptomycin solution (Beijing Solarbio Science & Technology Co., Ltd., Beijing, China) at 37℃ with 5% CO 2 . The cells were transfected after the cell density reached 70–80% after being inoculated into a 6-well cell culture plate. They were then cultured at 37℃ with 5% CO₂, with medium change interval of 2 d. 2.8 Plasmid construction The coding region of porcine ACAA2 was amplified by PCR and subcloned into pcDNA3.1-EGFP as the vector to construct an overexpression plasmid (p-ACAA2). Subsequently, the p-ACAA2 was transfected into porcine intramuscular preadipocytes and 3T3-L1 cells. 2.9 Oil Red O Staining The cells in the 6-well plate were stained according to the Oil Red O kit procedure (Beijing Solarbio Science & Technology Co., Ltd., Beijing, China) at the day 8 of cell differentiation. The lipid droplets were visualized under inverted fluorescence microscope (Leica Microsystems, Wetzlar, Germany). 2.10 Statistical analysis For both statistical analysis and data visualization, the OmicShare tools ( https://www.omicshare.com/tools ) and BioDeep Platform ( https://www.biodeep.cn ) were utilized. The DELs and differential VOCs were identified based on criteria of P 1. Data in this study were expressed as mean ± standard deviation (SD). Statistical analyses were conducted utilizing SPSS 26.0, employing independent sample T-test. When P < 0.05, statistical significance was determined. Significance levels were indicated as follows: * P < 0.05, ** P < 0.01, *** P < 0.001. 3 Results 3.1 Comparison and analysis of muscle quality between QS and YN To study the muscle quality of the two breeds, the meat quality related indexes were measured. The results indicated that the water content of QS was significantly lower than that of YN ( P < 0.05). At the same time, the pH 24h and meat color 24h in QS were higher, and the DL was lower. IMF content and marbling score were significantly higher than YN ( P < 0.01, Table 1 ). Table 1 Comparison of muscle quality between QS and YN Items QS YN Moisture (%) 72.4 ± 1.41 * 73.53 ± 0.37 Protein (%) 22.10 ± 1.62 * 20.44 ± 0.94 IMF (%) 4.52 ± 0.98 ** 3.33 ± 0.21 PH 24h 5.83 ± 0.14 5.71 ± 0.18 DL (%) 1.24 ± 0.21 1.36 ± 0.41 Meat color 24h 3.25 ± 0.50 3.19 ± 0.43 Marbling score 4.50 ± 1.03 *** 2.50 ± 0.35 Note: Data are expressed as mean ± SD 3.2 FAs and AAs composition and content in QS and YN In order to study the changes of FAs and AAs between QS and YN, a total of 15 FAs and 16 AAs were detected by GC and LC (Table S2 and 3). Overall, the content of total AAs, sweet AAs and 5 AAs (cystine, proline, arginine etc.) in QS were significantly higher than those in YN ( P < 0.05), and the contents of essential AAs, umami AAs and 5 AAs (isoleucine, lysine, histidine etc.) in YN were significantly higher than those in QS ( P 0.05, Fig. 1 A and B). The contents of linoleic acid, linolenic acid, arachidonic acid and cis-4,7,10,13,16,19-Docosahexaenoic acid in QS were significantly higher compared to YN ( P 0.05, Fig. 1 C). 3.3 Differential VOCs identification and functional analysis In this study, the VOCs were detected by GC×GC TOF-MS, and orthogonal projections to latent structures-discriminant analysis (OPLS-DA) results showed that there was dispersion between the principal components of QS and YN (Fig. 2 A). And, 1,320 VOCs were identified in QS and 1,173 in YN. Among the 37 significant VOC compounds, 16 increased and 21 decreased in QS compared to YN (Fig. 2 B). The kyoto encyclopedia of genes and genomes (KEGG) enrichment analysis was performed on differential VOCs, mainly including protein digestion and absorption, fatty acid biosynthesis and propanoate metabolism etc. The differential VOCs involved in enriching metabolic pathways mainly include phenol, propanal, ethylbenzene and 1-Hexanol (Fig. 2 C, Table S4). The relative odor activity value (ROAV) of VOCs were shown in the table S5. The results revealed a total of 137 VOCs with ROAV, and 8 VOCs with ROAV ≥ 1 were found in QS and YN. Among them, 2,3-butanedione has the highest ROAV in QS, and 2-Nonenal, (E) - has the highest ROAV in YN. However, only 2-Octenal, (E) -is a differential VOCs and can be considered as the key volatile compound. Besides, the correlation analysis of FAs and differential VOCs was performed, and the results showed that 15 FAs were identified that may lead to the difference in flavor between the two pig breeds through the regulation of differential VOC formation ( P 0.8, Fig. 2 D). 3.4 DEGs identification and functional enrichment analysis To further investigate the genes that may affect the differences in meat quality between QS and YN, transcriptomic was applied. Distinct differences in the principal components between the two breeds were indicated by the partial least squares-discriminant analysis (PLS-DA) results. Specifically, PC1 explained 30.1% of the variance, while PC2 accounted for 19.8% of the variance (Fig. 3 A). In addition, compared with YN, there were 1,446 up-regulated and 1,113 down-regulated DEGs in QS (Fig. 3 B). Gene ontology (GO) analysis indicated that DEGs were significantly enriched in regulation of macromolecular metabolic process, regulation of primary metabolic process, cellular macromolecular metabolic process, and small molecule metabolic process ( P < 0.05, Fig. 3 C and D). According to the results of the KEGG enrichment study, DEGs were mostly engaged in IL-17 signaling pathway, fatty acid degradation, fatty acid elongation and AMPK signaling pathway ( P < 0.05, Fig. 3 E and F, Table S6 and 7). To further explore the critical factors that play a critical role, protein and protein interactions (PPI) were used. The findings suggested a strong correlation and significant connection between hydroxyacyl-CoA dehydrogenase trifunctional multienzyme complex subunit beta ( HADHB ), ACAA2 and peroxisome proliferator activated receptor gamma ( PPARG ) etc., and these DEGs were involved in AMPK signaling pathway, IL-17 signaling pathway and fatty acid metabolism etc. (Fig. 3 G). Besides, some genes in the pathways were involved in multiple pathways, such as carnitine palmitoyltransferase 1B ( CPT1B ), hydroxyacyl-CoA dehydrogenase ( HADH ), hydroxyacyl-CoA dehydrogenase trifunctional multienzyme complex subunit alpha ( HADHA ), HADHB and ACAA2 (Fig. 3 H). 3.5 Validation of transcriptomic data by qRT-PCR Furthermore, to ensure the reliability of transcriptomic sequencing, six DEGs were selected for validation. Notably, the accuracy and dependability of the RNA-seq data were confirmed by the qRT-PCR results. (Fig. 4 ). This consistency underscores the accuracy of our results. 3.6 Analysis of DELs related to pork flavor LC-MS detected 2,210 lipids and 2,209 lipids in QS and YN, which were divided into 51 categories. These lipids included 501 triglycerides (TG), 378 phosphatidylcholine (PC) and 212 phosphatidylethanolamine (PE), as well as 116 and 117 diglyceride (DG) in QS and YN (Table S8). According to the OPLS-DA, there were marked differences between the QS and YN groups, making it easy to distinguish between them (Fig. 5 A). Compared with YN, QS had 208 lipids up-regulated, mostly TG and PC (36 and 51 respectively), while 252 lipids were down-regulated, including 50 PE, 39 PC and 48 TG (Fig. 5 B and C). TG, DG and PC are the three main components of lipids in pork, which are directly related to the meat flavor. Among the DELs detected in this study, there were 90 PC, 84 TG, 61 PE and 31 DG (Table S9). In this study, the relative contents of PC, hemolipin (SM), monohexose ceramide (Hex1Cer), and monogalactosyl glyceride (MGDG) in QS were significantly higher than those in YN, while the contents of TG, PE, and BisMePA were significantly lower than those in YN ( P < 0.05, Fig. 5 D). Pearson correlation analysis was performed on the DELs, found that there were more positively correlated DELs than negatively correlated DELs (Table S10). This may mean that the accumulation of DELs promotes the further accumulation of lipids. Besides, the top 10 lipids of VIP were mostly phospholipids and sphingolipids, and the expression level was high in QS (Fig. 5 E). 3.7 Correlation analysis among the DEGs, DELs and differential VOCs In an effort to further explore the regulation mechanism of pork flavor, the correlation analysis of DEGs and DELs, DELs and differential VOCs, DEGs and differential VOCs were performed. The joint analysis results revealed significant positive or negative correlations among 16 DEGs and 10 DELs (Fig. 6 A), 10 DELs and 16 differential VOCs (Fig. 6 B), 20 DEGs and 18 differential VOCs (Fig. 6 C). Furthermore, the multi-omics joint analysis results showed that there was a correlation among 15 DEGs, 10 DELs and 14 differential VOCs (Fig. 6 D). These VOCs, genes and lipids may interact together to affect the pork flavor. 3.8 Key pathways and interactions regulating pork flavor To further explore the interaction between the above genes and lipids, the associated metabolic pathways were studied. The results showed that FAs could enter the cell through CD36, and the fatty acyl-CoA produced by FAs could interact with glycerol-3-phosphate (G3P), participate in glycerolipid metabolism and glycerophospholipid metabolism, and generate TG. TG can be decomposed to produce FAs, and enter mitochondrion through CPT1B , and ultimately participate in FA oxidation. Besides, adrenoceptor alpha 1A ( ADRA1A ) can inhibit the expression of SREBP1c through AMPK, and then promote the expression of FAS, thereby regulating FA biosynthesis (Fig. 7 ). 3.9 Effects of ACAA2 on differentiation of porcine intramuscular preadipocytes and 3T3-L1 cells In this study, ACAA2 was an important candidate gene. This study investigated its regulatory effect on adipocytes by manipulating its expression in adipocytes. The results showed that after overexpression of ACAA2 , its expression levels were significantly up-regulated in porcine intramuscular preadipocytes and 3T3-L1 cells ( P < 0.01, Fig. 8 A). Additionally, the expression levels of differentiation marker genes, including CCAAT enhancer binding protein alpha ( CEBPA ), PPARG , fatty acid binding protein 4 ( FABP4 ), and Perilipin 1 ( PLIN1 ) were significantly increased after ACAA2 overexpression in both cell types ( P < 0.05, Fig. 8 B). Oil Red O staining results demonstrated a significant increase in lipid droplet deposition after overexpression of ACAA2 ( P < 0.01, Fig. 8 C and D). These results indicated that overexpression of ACAA2 significantly promote the differentiation of porcine intramuscular preadipocytes and 3T3-L1 cells. 4 Discussion China is rich in local breeding resources and these local pig breeds tend to excellent characteristics, such as the QS black pig, are known for their fine meat texture, superior flavor and high IMF. Our team bred a new breed, YN black pig, through crossbreeding to meet the growth rate and meat quality[ 15 ]. In this study, the two breeds were analyzed with multi-omics analyses to reveal the complex molecular mechanisms that regulate the differences in pork flavor between the different pig breeds. The degradation of lipids is a major factor in the formation of meat flavor, lipid hydrolysis produces flavor precursors such as free FAs, which are subsequently oxidized to yield VOCs [ 21 ]. As an important chemical substance that constitutes fat, FAs can not only provide the necessary nutrients for the human body, but also act as flavor precursors to affect the overall flavor of the muscle[ 22 ]. The content and composition of FAs in meat are affected by the breed type[ 23 ]. This study found QS has more palmitoleic acid than YN. Kimata et al. studied the correlation between muscle FAs composition and pork edible quality, and found that SFAs and MUFAs were positively correlated with pork tenderness, juiciness and flavor. In particular, palmitoleic acid content was highly positively correlated with meat flavor[ 24 ]. Linoleic acid, linolenic acid and arachidonic acid are essential FAs within PUFAs, and linoleic acid is one of the essential FAs that cannot be synthesized in humans and animals. Several studies have confirmed that conjugated linoleic acid can enhance the transformation of mesenchymal cells into preadipocytes, increase IMF content and improve meat quality[ 25 ]. cis-4,7,10,13,16,19-Docosahexaenoic acid can assist brain thinning[ 26 ]. This study found the contents of PUFAs and linoleic acid, linolenic acid, arachidonic acid and cis-4,7,10,13,16,19-Docosahexaenoic acid in QS were significantly higher. And PUFAs cannot be produced in humans and must be obtained through dietary consumption and are therefore considered essential for the body. In general, the content of PUFAs in QS was higher than that in YN. Besides, AAs are key compounds for growth, immunity and regulation of metabolic pathways [ 23 ]. It is reported that AAs can enhance the meat flavor, including sour, sweet, bitter, salty, and umami [ 3 , 4 ]. Serine largely determines the meat flavor [ 27 ], and threonine can improve the meat quality[ 28 ]. In the production of mutton, arginine may be utilized to enhance meat quality and protein deposition [ 29 ]. In this study, the contents of total amino acids, sweet amino acids, serine, threonine and arginine in QS were significantly higher than those in YN. Flavor, as the dominant factor, significantly influences both meat quality and consumer purchasing decisions. However, only a few of the major VOCs in food have ROAV that indeed contributes to the overall aroma. Therefore, it is important to figure out which VOCs play an important role in food flavor. Proteins can affect IMF deposition. OTX2 protein is a transcription factor containing a homologous domain and may be involved in the regulation of adipose tissue function [ 30 , 31 ]. Propionate can be converted into lipids by lipogenesis and induce the expression of lipogenic genes. It can also stimulate lipid accumulation in 3T3-L1 adipocytes [ 32 , 33 ]. Thus, genes may regulate the production of phenol, propanal, ethylbenzene and 1-Hexanol by affecting pathways like protein digestion and absorption, fatty acid biosynthesis and propanoate metabolism. Therefore, in order to further explore the genetic basis leading to the difference of pork flavor in different breeds, this study also carried out transcriptome analysis. The AMPK signaling pathway is a critical pathway for lipid metabolism. This pathway's activation enhances fatty acid oxidation and simultaneously inhibits lipid production in adipocytes[ 34 ]. IL-17 can regulate adipogenesis and adipocyte metabolism [ 35 ]. FAs and cholesterol levels in meat are very important due to their effects on human health [ 36 , 37 ]. Fat deposition is governed by the synthesis of FAs as well as the uptake of exogenous FAs [ 38 ]. CPT1B is a rate-limiting enzyme that inhibits the β-oxidation of long-chain fatty acids within the mitochondria of muscle cells. In bovine fetal fibroblasts, elevated expression of CPT1B notably increases triglyceride levels [ 39 ]. The last step of the fatty acid β-oxidation cycle is catalyzed by HADHB , which facilitates the reaction of β-ketoacyl-CoA with a molecule of free coenzyme A, cleaving the carboxyl-terminal two-carbon fragment from the original fatty acid to form acetyl-CoA [ 40 ]. ACAA2 encoded protein catalyzed the last step of mitochondrial fatty acid β-oxidation spiral [ 41 ]. Adipocytes differentiation is tightly regulated by various transcription factors including PPARG and CCAAT/Enhancer Binding Protein – α (C/EBP-α) [ 42 ]. PPARG regulates the expression of numerous key adipocyte genes, these genes are engaing in coordinating fatty acid uptake, metabolism, and storage [ 43 ]. Genes are located in the upstream of regulating metabolic processes, so their expression patterns can lead to differences in VOCs. These genes are closely linked to adipocyte differentiation, fatty acids synthesis, and lipid metabolism, etc. Consequently, they may be the key factors for the difference in pork flavor between the two breeds. Lipids are vital in the formation of unique meat flavor through lipid degradation and fatty acid oxidation [ 2 ]. Current research generally believes that phospholipids are the key lipids determining meat flavor, and the volatile compounds generated from their thermal decomposition and oxidation reactions are important sources of the unique flavor of meat products [ 7 ]. PCs is the most abundant phospholipid molecule in muscle and is the main cause of flavor variation [ 6 , 44 ]. The different lipids have distinct physiological effects on the human body. For instance, sphingolipids (SPs) have the ability to inhibit some cancers [ 5 ]. In this study, QS was found to have a significantly higher level of PC than YN. Besides, SM, Hex1Cer, MGDG, TG, PE and BisMePA were significantly different in QS and YN, so this study speculated that the FAs that affect the different flavors of the two pork were mainly produced by these lipids. To explore the molecular regulatory mechanisms leading to the differences in pork flavor between the two varieties, this study conducted a combined analysis of flavoromics, transcriptomics and lipidomics. Association analysis between flavoromics and lipidomics, SM (t40:5) was found to be significantly positively correlated with pyridine. Surprisingly, ACAA2 exhibited a significant negative correlation with both SM (t40:5) and pyridine. And there was also a significant negative correlation between ACAA2 and pyridine. Acetyl-CoA acyltransferase 1 ( ACAA1 ), acyl-CoA dehydrogenase short chain ( ACADS ) and CPT1B etc. have a directly positive or negative relationship with other DELs and differential VOCs. Therefore, PC (26:3), PC (18:1e_6:0) and PC (29:3) etc. may be the upstream metabolites of pyridine, phenol and 1-Hexanol etc., which can affect the formation of pork-specific flavor. Thus, they may cooperate to regulate meat flavor. It is inferred that these genes and lipids may regulate the FA biosynthesis, FA oxidation, glycerolipid metabolism and glycerophospholipid metabolism, by investigating the metabolic pathways associated with them, thereby regulating lipid production and decomposition. And, these genes were significantly positively correlated with TG and DG contents. Furthermore, they also showed a positive correlation with particular VOCs. Thus, it is speculated that the overexpression of these critical genes may promote the synthesis of TG, thereby facilitating the degradation of TG into glycerol and FAs. And this may accelerate the oxidation of FAs into VOCs. The IMF is essential to the development of pork flavor. Research has shown that the unsaturated fatty acids in IMF, especially the PUFA, are prone to thermal degradation and oxidation reactions, generating volatile compounds such as aldehydes and ketones. These substances are the key factors that give pork its unique aroma. Moreover, the lipid oxidation products can also react with other molecules, further influencing the flavor characteristics[ 45 ]. The deposition of IMF is closely related to lipid metabolism. In-depth study of the lipid metabolism process is helpful in revealing the molecular mechanism of flavor formation. Through joint analysis and literature mining, we found that ACAA2 is important candidate genes that may affect meat quality differences. ACAA2 is a critical gene involved in the lipid metabolism pathway, positively linked with the content of IMF, and is regarded as an important regulatory factor determining the accumulation of IMF[ 46 ]. Studies have shown that ACAA2 can promote the differentiation of preadipocytes. For example, miR-193a-5p inhibits the differentiation of 3T3-L1 preadipocytes by targeting the expression of ACAA2 gene[ 47 ]. This study further verified that ACAA2 can promote lipid deposition in porcine intramuscular preadipocytes and 3T3-L1 cells. The findings suggest that ACAA2 may indirectly affect the generation of flavor substances by regulating lipid accumulation. It is an important regulatory factor connecting lipid metabolism and flavor formation, offering a potential target for further improving pork quality. 5 Conclusion In general, this study compared the differences in pork flavor between the two pig breeds based on the methods of flavoromics, transcriptomics and lipidomics. The results indicated that the contents of total AAs, sweet AAs and 5 AAs (cystine, proline, arginine etc.) in QS were higher than those in YN. In addition, 14 VOCs (pyridine, 1- hexanol, phenol, etc.), 15 DEGs ( ACAA2 , HADHB , CPT1B , etc.) and10 DELs (PC (18:1e_6:0), PC (26:3), PE (34:6e), etc.) may play important roles in pork flavor. In addition, the analysis revealed that these genes may be involved in FA biosynthesis, FA oxidation, and glycerophospholipid metabolism by regulating lipid production and lipid breakdown. Finally, this study found that ACAA2 promoted the lipid deposition of porcine intramuscular preadipocytes and 3T3-L1 cells. These findings provide a theoretical basis for exploring the molecular regulatory mechanisms of multi-omics in influencing the flavor of pork. Abbreviations VOCs, volatile organic compounds; DEGs, differential expressed genes; DELs, differential lipids; FAs, fatty acids; IMF, intramuscular fat; SFAs, saturated fatty acids; MUFAs, monounsaturated fatty acids; PUFAs, polyunsaturated fatty acids; ACAA2, acetyl-CoA acyltransferase 2; LD, longissimus dorsi; AAs, amino acids; pH24h, pH at 24h post-slaughter; DL, drip loss; FC, Fold Change; qRT-PCR, quantitative real-time polymerase chain reaction; GAPDH, glyceraldehyde-3-phosphate dehydrogenase; SD, standard deviation; KEGG, kyoto Encyclopedia of Genes and Genomes; ROAV, relative odor activity value; GO, gene Ontology; PPI, protein-protein interactions; PPARG, peroxisome proliferator activated receptor gamma; CPT1B, carnitine palmitoyltransferase 1B; HADH, hydroxyacyl-CoA dehydrogenase; HADHA, hydroxyacyl-CoA dehydrogenase trifunctional multienzyme complex subunit alpha; TG, triglyceride; PC, phosphatidylcholine; PE, phosphatidylethanolamine; DG, diglyceride; SM, sphingomyelin; Hex1Cer, monohexosyl ceramide; MGDG, monogalactosyl glyceride; G3P, glycerol-3-phosphate; ADRA1A, adrenoceptor alpha 1A; CEBPA, CCAAT enhancer binding protein alpha; FABP4, fatty acid binding protein 4; PLIN1, Perilipin 1; C/EBP-α, CCAAT/Enhancer Binding Protein – α; ACAA1, Acetyl-CoA acyltransferase 1; ACADS, acyl-CoA dehydrogenase short chain. Declarations Ethics approval and consent to participate This study was performed in compliance with the protocols for the care and use of experimental animals established by the People’s Republic of China’s Ministry of Science and Technology (Approval Number: DWLL20211193). And this experiment was approved by the Ethics Committee of Henan Agricultural University. In addition, all test methods were conducted in compliance with applicable regulations and adhered to the ARRIVE guidelines governing animal research. All animal experiments involved in this study were conducted with the informed consent of the owners. Consent for publication Not applicable. Availability of data and materials The RNA-seq data of this study has been deposited in the National Center for Biotechnology Information (NCBI), with the accession number PRJNA1310286. Competing interests The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. Funding This research was financed and supported by the Pig Industry Technology System Innovation Team Project of Henan Province (HARS-22-12-G4), the 14th Five-Year National Key R&D Program (2021YFD1301202), and the Agricultural Breeds Research Project of Henan Province (2022020101). CRediT authorship contribution statement Bingjie Wang: Conceptualization, Visualization, Validation, Formal analysis, Writing – original draft, Writing – review & editing. Yilin Wei: Visualization, Validation. Chang Wang: Validation, Formal analysis. Lebin Chang Validation. Tengfei Wang: Investigation. Xinjian Li: Resources. Tong Yu: Software. Jun Bai: Formal analysis. Liwei Yuan: Validation. Wei Wang: Supervision. Ruimin Qiao: Supervision. Feng Yang: Supervision. Xiuling Li & Xuelei Han: Writing – original draft, Writing – review & editing, Resources, Data Curation, Supervision, Investigation, Project administration, Funding acquisition. Appendix A. Supplementary data Supplementary data to this article can be found online at https://. Table S1: Ingredient composition of pig diets for pigs (%). Table S2: FAs contents (μg/g) in LD of QS and YN. Table S3: AAs contents (%) in LD of QS and YN. Table S4: The KEGG enrichment analysis of differential VOCs. Table S5: The ROAV results of VOCs. Table S6: The KEGG enrichment analysis of up-regulated DEGs. Table S7: The KEGG enrichment analysis of down-regulated DEGs. Table S8: The number of lipids identified in QS and YN. Table S9: The number and proportion of various types of DELs. Table S10: The correlation analysis of DELs classification. Acknowledgements Not applicable. References Geletu US, Usmael MA, Mummed YY, Ibrahim AM: Quality of Cattle Meat and Its Compositional Constituents . Vet Med Int 2021, 2021 :7340495. Khan MI, Jo C, Tariq MR: Meat flavor precursors and factors influencing flavor precursors--A systematic review . Meat Sci 2015, 110 :278-284. Bachmanov AA, Bosak NP, Glendinning JI, Inoue M, Li X, Manita S, McCaughey SA, Murata Y, Reed DR, Tordoff MG et al : Genetics of Amino Acid Taste and Appetite . Adv Nutr 2016, 7 (4):806s-822s. Sohail A, Al-Dalali S, Wang J, Xie J, Shakoor A, Asimi S, Shah H, Patil P: Aroma compounds identified in cooked meat: A review . Food Res Int 2022, 157 :111385. Xiong L, Pei J, Wang X, Guo S, Guo X, Yan P: Effect of Lipids in Yak Muscle under Different Feeding Systems on Meat Quality Based on Untargeted Lipidomics . Animals (Basel) 2022, 12 (20). Jia W, Li R, Wu X, Liu S, Shi L: UHPLC-Q-Orbitrap HRMS-based quantitative lipidomics reveals the chemical changes of phospholipids during thermal processing methods of Tan sheep meat . Food Chem 2021, 360 :130153. Liu H, Hui T, Zheng X, Li S, Wei X, Li P, Zhang D, Wang Z: Characterization of key lipids for binding and generating aroma compounds in roasted mutton by UPLC-ESI-MS/MS and Orbitrap Exploris GC . Food Chem 2022, 374 :131723. Li J, Yang Y, Tang C, Yue S, Zhao Q, Li F, Zhang J: Changes in lipids and aroma compounds in intramuscular fat from Hu sheep . Food Chem 2022, 383 :132611. Wang B, Qin K, Qi K, Zhang R, Xu Z, Men X: Construction of a molecular regulatory network for lipids and volatile flavor in Chinese indigenous and hybrid pig pork through integrating multi-omics analysis . Lwt 2024, 199 . Li W, Chen YP, Blank I, Li F, Li C, Liu Y: GC × GC-ToF-MS and GC-IMS based volatile profile characterization of the Chinese dry-cured hams from different regions . Food Res Int 2021, 142 :110222. Wang X, Xu R, Tong X, Zeng J, Chen M, Lin Z, Cai S, Chen Y, Mo D: Characterization of different meat flavor compounds in Guangdong small-ear spotted and Yorkshire pork using two-dimensional gas chromatography–time-of-flight mass spectrometry and multi-omics . Lwt 2022, 169 . Zhao Y, Zhou J, Luo W, Jiang L, Song F, Ran J, Xu H, Lei L, Ai R, Yu B: An integrated metabolomics-flavoromics analysis reveals flavor diversity in indigenous and hybrid cattle via UHPLC-MS/MS and GC×GC-TOF-MS . Food Chem X 2025, 29 :102801. Li M, Zhu M, Chai W, Wang Y, Song Y, Liu B, Cai C, Song Y, Sun X, Xue P et al : Determination of the Heterogeneity of Intramuscular Fat and Visceral Adipose Tissue From Dezhou Donkey by Lipidomics and Transcriptomics Profiling . Front Nutr 2021, 8 :746684. Zhao QB, Oyelami FO, Qadri QR, Sun H, Xu Z, Wang QS, Pan YC: Identifying the unique characteristics of the Chinese indigenous pig breeds in the Yangtze River Delta region for precise conservation . BMC Genomics 2021, 22 (1):151. Qi K, Liu Y, Li C, Li X, Li X, Wang K, Qiao R, Han X: Construction of circRNA-related ceRNA networks in longissimus dorsi muscle of Queshan Black and Large White pigs . Mol Genet Genomics 2022, 297 (1):101-112. Li M, Li X, Liu C, Han J, Han X, Wang K, Qiao R, Yang F, Li XL, Li XJ: Genome-wide association study reveals the candidate genes for reproduction traits in Yunong black pigs . Anim Genet 2023, 54 (3):403-407. Li X, Li M, Han J, Liu C, Han X, Wang K, Qiao R, Li XL, Li XJ: Correlation between fat accumulation and fecal microbiota in crossbred pigs . J Microbiol 2022, 60 (11):1077-1085. Petit A, Tesseraud S, Collin A, Couroussé N, Berri C, Bihan-Duval EL, Métayer-Coustard S: Ontogeny of hepatic metabolism in two broiler lines divergently selected for the ultimate pH of the Pectoralis major muscle . BMC Genomics 2024, 25 (1):438. Djoumbou Feunang Y, Eisner R, Knox C, Chepelev L, Hastings J, Owen G, Fahy E, Steinbeck C, Subramanian S, Bolton E et al : ClassyFire: automated chemical classification with a comprehensive, computable taxonomy . J Cheminform 2016, 8 :61. Liu Y, Dou Y, Qi K, Li C, Song C, Li X, Li X, Qiao R, Wang K, Han X: CircSETBP1 Acts as a MiR-149-5p Sponge to Promote Intramuscular Fat Deposition by Regulating CRTCs . J Agric Food Chem 2022, 70 (40):12841-12851. Fu Y, Cao S, Yang L, Li Z: Flavor formation based on lipid in meat and meat products: A review . J Food Biochem 2022, 46 (12):e14439. Bjorklund EA, Heins BJ, Dicostanzo A, Chester-Jones H: Fatty acid profiles, meat quality, and sensory attributes of organic versus conventional dairy beef steers . J Dairy Sci 2014, 97 (3):1828-1834. Guo T, Zhang Q, Wang X, Xu X, Wang Y, Wei L, Li N, Liu H, Hu L, Zhao N et al : Targeted and untargeted metabolomics reveals meat quality in grazing yak during different phenology periods on the Qinghai-Tibetan Plateau . Food Chem 2024, 447 :138855. Candek-Potokar M, Monin G, Zlender B: Pork quality, processing, and sensory characteristics of dry-cured hams as influenced by Duroc crossing and sex . J Anim Sci 2002, 80 (4):988-996. Chen J, You R, Lv Y, Liu H, Yang G: Conjugated linoleic acid regulates adipocyte fatty acid binding protein expression via peroxisome proliferator-activated receptor alpha signaling pathway and increases intramuscular fat content . Front Nutr 2022, 9 :1029864. Witte AV, Kerti L, Hermannstadter HM, Fiebach JB, Schreiber SJ, Schuchardt JP, Hahn A, Floel A: Long-chain omega-3 fatty acids improve brain function and structure in older adults . Cereb Cortex 2014, 24 (11):3059-3068. Fu B, Zheng M, Yang H, Zhang J, Li Y, Wang G, Tian J, Zhang K, Xia Y, Li Z et al : The effect of broad bean diet on structure, flavor and taste of fresh grass carp: A comprehensive study using E-nose, E-tongue, TPA, HS-SPME-GC-MS and LC-MS . Food Chem 2024, 436 :137690. Jiang Y, Xie M, Tang J, Zhou Z, Zhang Y, Chen G, Hou S: Effects of genetic selection and threonine on meat quality in Pekin ducks . Poult Sci 2020, 99 (5):2508-2518. Dou L, Sun L, Liu C, Su L, Chen X, Yang Z, Hu G, Zhang M, Zhao L, Jin Y: Effect of dietary arginine supplementation on protein synthesis, meat quality and flavor in growing lambs . Meat Sci 2023, 204 :109291. Dankel SN, Fadnes DJ, Stavrum AK, Stansberg C, Holdhus R, Hoang T, Veum VL, Christensen BJ, Våge V, Sagen JV et al : Switch from stress response to homeobox transcription factors in adipose tissue after profound fat loss . PLoS One 2010, 5 (6):e11033. Cowherd RM, Lyle RE, Miller CP, McGehee RE, Jr.: Developmental profile of homeobox gene expression during 3T3-L1 adipogenesis . Biochem Biophys Res Commun 1997, 237 (2):470-475. Lee SH, Hossner KL: Coordinate regulation of ovine adipose tissue gene expression by propionate . J Anim Sci 2002, 80 (11):2840-2849. Hong YH, Nishimura Y, Hishikawa D, Tsuzuki H, Miyahara H, Gotoh C, Choi KC, Feng DD, Chen C, Lee HG et al : Acetate and propionate short chain fatty acids stimulate adipogenesis via GPCR43 . Endocrinology 2005, 146 (12):5092-5099. Li Q, Tan JX, He Y, Bai F, Li SW, Hou YW, Ji LS, Gao YT, Zhang X, Zhou ZH et al : Atractylenolide III ameliorates Non-Alcoholic Fatty Liver Disease by activating Hepatic Adiponectin Receptor 1-Mediated AMPK Pathway . Int J Biol Sci 2022, 18 (4):1594-1611. Zúñiga LA, Shen WJ, Joyce-Shaikh B, Pyatnova EA, Richards AG, Thom C, Andrade SM, Cua DJ, Kraemer FB, Butcher EC: IL-17 regulates adipogenesis, glucose homeostasis, and obesity . J Immunol 2010, 185 (11):6947-6959. Boz MA, Oz F, Yamak US, Sarica M, Cilavdaroglu E: The carcass traits, carcass nutrient composition, amino acid, fatty acid, and cholesterol contents of local Turkish goose varieties reared in an extensive production system . Poult Sci 2019, 98 (7):3067-3080. Biesek J, Kuźniacka J, Banaszak M, Adamski M: The Quality of Carcass and Meat from Geese Fed Diets with or without Soybean Meal . Animals (Basel) 2020, 10 (2). Vernon RG, Flint DJ: Lipid metabolism in farm animals . Proc Nutr Soc 1988, 47 (3):287-293. He W, Gao M, Yang R, Zhao Z, Mi J, Sun H, Xiao H, Fang X: The effect of CPT1B gene on lipid metabolism and its polymorphism analysis in Chinese Simmental cattle . Anim Biotechnol 2022, 33 (7):1428-1440. Xu WD, Yang XY, Li DH, Zheng KD, Qiu PC, Zhang W, Li CY, Lei KF, Yan GQ, Jin SW et al : Up-regulation of fatty acid oxidation in the ligament as a contributing factor of ankylosing spondylitis: A comparative proteomic study . J Proteomics 2015, 113 :57-72. Miltiadou D, Hager-Theodorides AL, Symeou S, Constantinou C, Psifidi A, Banos G, Tzamaloukas O: Variants in the 3' untranslated region of the ovine acetyl-coenzyme A acyltransferase 2 gene are associated with dairy traits and exhibit differential allelic expression . J Dairy Sci 2017, 100 (8):6285-6297. Ma X, Wei D, Cheng G, Li S, Wang L, Wang Y, Wang X, Zhang S, Wang H, Zan L: Bta-miR-130a/b regulates preadipocyte differentiation by targeting PPARG and CYP2U1 in beef cattle . Mol Cell Probes 2018, 42 :10-17. Gelman L, Fruchart JC, Auwerx J: An update on the mechanisms of action of the peroxisome proliferator-activated receptors (PPARs) and their roles in inflammation and cancer . Cell Mol Life Sci 1999, 55 (6-7):932-943. Yamamoto S, Kato S, Senoo N, Miyoshi N, Morita A, Miura S: Differences in phosphatidylcholine profiles and identification of characteristic phosphatidylcholine molecules in meat animal species and meat cut locations . Biosci Biotechnol Biochem 2021, 85 (5):1205-1214. Li W, LiLi, Wang X: Transcriptomic analysis of different intramuscular fat contents on the flavor of the longissimus dorsi tissues from Guangling donkey . Genomics 2024, 116 (5):110905. Zhang Y, Wang Y, Wang X, Ji Y, Cheng S, Wang M, Zhang C, Yu X, Zhao R, Zhang W et al : Acetyl-coenzyme A acyltransferase 2 promote the differentiation of sheep precursor adipocytes into adipocytes . J Cell Biochem 2019, 120 (5):8021-8031. Han F, Zhou L, Zhao L, Wang L, Liu L, Li H, Qiu J, He J, Liu N: Identification of miRNA in Sheep Intramuscular Fat and the Role of miR-193a-5p in Proliferation and Differentiation of 3T3-L1 . Front Genet 2021, 12 :633295. Additional Declarations No competing interests reported. Supplementary Files Supplementalmaterial.docx Cite Share Download PDF Status: Published Journal Publication published 10 Nov, 2025 Read the published version in BMC Genomics → Version 1 posted Editorial decision: Revision requested 08 Sep, 2025 Reviews received at journal 03 Sep, 2025 Reviews received at journal 28 Aug, 2025 Reviewers agreed at journal 28 Aug, 2025 Reviewers agreed at journal 27 Aug, 2025 Reviewers invited by journal 27 Aug, 2025 Editor assigned by journal 27 Aug, 2025 Editor invited by journal 26 Aug, 2025 Submission checks completed at journal 25 Aug, 2025 First submitted to journal 25 Aug, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-7304887","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":509416594,"identity":"55b7828a-2f76-4063-8de5-5a83d10f9df9","order_by":0,"name":"Bingjie Wang","email":"","orcid":"","institution":"Henan Agricultural University","correspondingAuthor":false,"prefix":"","firstName":"Bingjie","middleName":"","lastName":"Wang","suffix":""},{"id":509416595,"identity":"f9d607a9-69e6-436f-a407-2e9c6bfcafd5","order_by":1,"name":"Yilin Wei","email":"","orcid":"","institution":"Henan Agricultural University","correspondingAuthor":false,"prefix":"","firstName":"Yilin","middleName":"","lastName":"Wei","suffix":""},{"id":509416596,"identity":"3ad788a8-ac90-48e5-97e4-8319b2f5bced","order_by":2,"name":"Chang Wang","email":"","orcid":"","institution":"Henan Agricultural University","correspondingAuthor":false,"prefix":"","firstName":"Chang","middleName":"","lastName":"Wang","suffix":""},{"id":509416597,"identity":"fc4ac67b-0c98-464c-a5a3-d56b87f9485d","order_by":3,"name":"Lebin Chang","email":"","orcid":"","institution":"Henan Agricultural University","correspondingAuthor":false,"prefix":"","firstName":"Lebin","middleName":"","lastName":"Chang","suffix":""},{"id":509416598,"identity":"bf609bd1-c42f-434a-a10b-017063f2bff6","order_by":4,"name":"Tengfei Wang","email":"","orcid":"","institution":"Henan Agricultural University","correspondingAuthor":false,"prefix":"","firstName":"Tengfei","middleName":"","lastName":"Wang","suffix":""},{"id":509416599,"identity":"5875550c-7105-42f5-8306-67f49ac109a4","order_by":5,"name":"Xinjian Li","email":"","orcid":"","institution":"Hainan Provincial Academy of Agricultural Sciences","correspondingAuthor":false,"prefix":"","firstName":"Xinjian","middleName":"","lastName":"Li","suffix":""},{"id":509416600,"identity":"8a7d4165-bac8-4172-a997-cdbaeb34523f","order_by":6,"name":"Tong Yu","email":"","orcid":"","institution":"Henan Agricultural University","correspondingAuthor":false,"prefix":"","firstName":"Tong","middleName":"","lastName":"Yu","suffix":""},{"id":509416601,"identity":"479f60b8-75c2-4ccf-8f4a-9813ffa019ee","order_by":7,"name":"Jun Bai","email":"","orcid":"","institution":"Henan Agricultural University","correspondingAuthor":false,"prefix":"","firstName":"Jun","middleName":"","lastName":"Bai","suffix":""},{"id":509416602,"identity":"75fa2d2e-d46a-4633-8751-29c08cea5eda","order_by":8,"name":"Wei Wang","email":"","orcid":"","institution":"Henan Agricultural University","correspondingAuthor":false,"prefix":"","firstName":"Wei","middleName":"","lastName":"Wang","suffix":""},{"id":509416603,"identity":"ce5ed67f-d320-4355-aace-2658a8373335","order_by":9,"name":"Liwei Yuan","email":"","orcid":"","institution":"Henan Yifa Animal Husbandry Co., Ltd","correspondingAuthor":false,"prefix":"","firstName":"Liwei","middleName":"","lastName":"Yuan","suffix":""},{"id":509416604,"identity":"bf6cb6f4-a84d-4343-90c1-55e9a9b8381d","order_by":10,"name":"Ruimin Qiao","email":"","orcid":"","institution":"Henan Agricultural University","correspondingAuthor":false,"prefix":"","firstName":"Ruimin","middleName":"","lastName":"Qiao","suffix":""},{"id":509416605,"identity":"bd8c237a-8fdb-4397-8e8c-5135e2ddf565","order_by":11,"name":"Feng Yang","email":"","orcid":"","institution":"Henan Agricultural University","correspondingAuthor":false,"prefix":"","firstName":"Feng","middleName":"","lastName":"Yang","suffix":""},{"id":509416606,"identity":"28d59d42-c95b-4bc6-84dd-8f1e8634f2ab","order_by":12,"name":"Xiuling Li","email":"","orcid":"","institution":"Henan Agricultural University","correspondingAuthor":false,"prefix":"","firstName":"Xiuling","middleName":"","lastName":"Li","suffix":""},{"id":509416607,"identity":"ba601e1e-3371-444d-80ce-f5133d6e298e","order_by":13,"name":"Xuelei Han","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAtElEQVRIie3PMQrCMBTG8YRAXZ64ptBD1EmEYj1KSsGph0gIdOoFxHt0TujQpeha6JIjtJuT2NFFeG4O7ze/P3yPMUL+UMqEdgoy2G00OuEmhOSSxI3DJ3Yfsi5LxzMyOciilqp6ABsZn5cKkRwbvybDBPymRXxtMcN6U8uimUAkLhJbVNLxNXndIZIKm/TGpgocAD4ZvAkKSpDgLfKXsXT+Cac8762fF0zygevf7gkhhHz3Bqa1OEmNdfb4AAAAAElFTkSuQmCC","orcid":"","institution":"Henan Agricultural University","correspondingAuthor":true,"prefix":"","firstName":"Xuelei","middleName":"","lastName":"Han","suffix":""}],"badges":[],"createdAt":"2025-08-06 02:38:05","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-7304887/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7304887/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1186/s12864-025-12178-5","type":"published","date":"2025-11-10T15:57:46+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":90616412,"identity":"85efa083-f064-49fe-ad3f-ae4aab3cedf3","added_by":"auto","created_at":"2025-09-04 18:38:51","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":918430,"visible":true,"origin":"","legend":"\u003cp\u003eFAs and AAs composition and contents in QS and YN. \u003cstrong\u003eA\u003c/strong\u003eFAs contents in LD muscles of QS and YN; \u003cstrong\u003eB\u003c/strong\u003e AAs contents in LD muscles of QS and YN; \u003cstrong\u003eC\u003c/strong\u003e Different classifications of AAs and their relative contents.\u003c/p\u003e","description":"","filename":"Figure.1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7304887/v1/44ef7365adf375ca30ff0954.jpg"},{"id":90616415,"identity":"ed259350-89ae-4e2d-813d-c6fb784e4343","added_by":"auto","created_at":"2025-09-04 18:38:51","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":2631596,"visible":true,"origin":"","legend":"\u003cp\u003eDifferential VOCs identification and KEGG enrichment analysis. \u003cstrong\u003eA\u003c/strong\u003e OPLS-DA analysis of the two groups of samples; \u003cstrong\u003eB\u003c/strong\u003e The number of the VOCs were significantly different between QS and YN; \u003cstrong\u003eC\u003c/strong\u003e Significantly differential VOCs were explored through KEGG pathway enrichment analysis; \u003cstrong\u003eD\u003c/strong\u003e Correlation analysis of FAs and differential VOCs.\u003c/p\u003e","description":"","filename":"Figure.2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7304887/v1/f3436c4547d6bbea08637133.jpg"},{"id":90616418,"identity":"a420535e-78a1-44a6-b7d5-1d57ad972421","added_by":"auto","created_at":"2025-09-04 18:38:51","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":6566408,"visible":true,"origin":"","legend":"\u003cp\u003eDEGs identification and functional enrichment analysis. \u003cstrong\u003eA\u003c/strong\u003e PLS-DA analysis of the two pig breeds; \u003cstrong\u003eB\u003c/strong\u003eVolcano plot of all measured genes; \u003cstrong\u003eC - D\u003c/strong\u003e GO analysis for up-regulated and down-regulated DEGs; \u003cstrong\u003eE - F\u003c/strong\u003e KEGG enrichment analysis for up-regulated and down-regulated DEGs; \u003cstrong\u003eG\u003c/strong\u003e PPI analysis of the DEGs; \u003cstrong\u003eH\u003c/strong\u003e The interaction network of pathway and DEGs.\u003c/p\u003e","description":"","filename":"Figure.3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7304887/v1/4a7a44a26b3a80f7e308faa8.jpg"},{"id":90617148,"identity":"03b35d14-2e3c-4909-a3d5-5329fc0fcc33","added_by":"auto","created_at":"2025-09-04 18:54:51","extension":"jpg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":776092,"visible":true,"origin":"","legend":"\u003cp\u003eValidation of transcriptomic data by qRT-PCR. \u003cstrong\u003eA\u003c/strong\u003e The expression levels of DEGs from RNA-Seq data of QS and YN. \u003cstrong\u003eB\u003c/strong\u003e The relative mRNA expression levels of DEGs were detected by qRT-qPCR and expressed as means ± SD. * means \u003cem\u003eP\u003c/em\u003e \u0026lt; 0.05, ** means \u003cem\u003eP\u003c/em\u003e \u0026lt; 0.01.\u003c/p\u003e","description":"","filename":"Figure.4.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7304887/v1/4de02cf58be687aaca4bba09.jpg"},{"id":90617149,"identity":"7323ecfd-d82d-4a1a-8c44-d82497454088","added_by":"auto","created_at":"2025-09-04 18:54:51","extension":"jpg","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":1774803,"visible":true,"origin":"","legend":"\u003cp\u003eAnalysis of DELs related to pork flavor. \u003cstrong\u003eA\u003c/strong\u003e OPLS-DA analysis of the two groups of samples; \u003cstrong\u003eB\u003c/strong\u003e The number of DELs in QS and YN; \u003cstrong\u003eC\u003c/strong\u003e Cluster analysis of DELs in QS and YN; \u003cstrong\u003eD\u003c/strong\u003e Relative lipid content (% total lipids) in QS and YN; \u003cstrong\u003eE\u003c/strong\u003e Cluster analysis of top ten DELs (VIP).\u003c/p\u003e","description":"","filename":"Figure.5.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7304887/v1/606abd9de3633188e1ace717.jpg"},{"id":90616731,"identity":"d27689e1-dee8-431a-9119-bee1bd293f2e","added_by":"auto","created_at":"2025-09-04 18:46:51","extension":"jpg","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":4517944,"visible":true,"origin":"","legend":"\u003cp\u003eCorrelation analysis of DEGs. DELs and differential VOCs. \u003cstrong\u003eA\u003c/strong\u003e Correlation analysis of DEGs and DELs; \u003cstrong\u003eB\u003c/strong\u003e Correlation analysis of DELs and differential VOCs; \u003cstrong\u003eC\u003c/strong\u003e Correlation analysis of DEGs and differential VOCs; \u003cstrong\u003eD\u003c/strong\u003e The results of multi-omics joint analysis.\u003c/p\u003e","description":"","filename":"Figure.6.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7304887/v1/c7dcd342da334782cd6717cd.jpg"},{"id":90616722,"identity":"da287482-18eb-4125-ad46-2a6784bb9a60","added_by":"auto","created_at":"2025-09-04 18:46:51","extension":"jpg","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":1599952,"visible":true,"origin":"","legend":"\u003cp\u003eThe mutual regulation network of key genes and lipids.\u003c/p\u003e","description":"","filename":"Figure.7.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7304887/v1/22e7c22521857656079bfd59.jpg"},{"id":90617390,"identity":"7dd0e8d0-b42e-484d-ac6f-95e02282b342","added_by":"auto","created_at":"2025-09-04 19:02:51","extension":"jpg","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":2893028,"visible":true,"origin":"","legend":"\u003cp\u003eEffects of \u003cem\u003eACAA2\u003c/em\u003eon differentiation of porcine intramuscular preadipocytes and 3T3-L1 cells. \u003cstrong\u003eA\u003c/strong\u003e Detection of \u003cem\u003eACAA2\u003c/em\u003eoverexpression efficiency 8 days after differentiation; \u003cstrong\u003eB\u003c/strong\u003e The effect of overexpression of \u003cem\u003eACAA2\u003c/em\u003e on differentiation marker genes in porcine intramuscular preadipocytes and 3T3-L1 cells; \u003cstrong\u003eC-D\u003c/strong\u003e Oil Red O staining on porcine intramuscular preadipocytes and 3T3-L1 cells after 8 days of differentiation.\u003c/p\u003e","description":"","filename":"Figure.8.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7304887/v1/e32f20ded324e54a1d097ec8.jpg"},{"id":108005649,"identity":"43d994b3-15f8-4238-b4aa-ec33366330f7","added_by":"auto","created_at":"2026-04-28 12:44:26","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":49003499,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7304887/v1/7203f1ce-de57-4ca5-8617-738ef633425f.pdf"},{"id":90617387,"identity":"414155c3-106e-4125-8c66-603243e2d2a9","added_by":"auto","created_at":"2025-09-04 19:02:51","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":210187,"visible":true,"origin":"","legend":"","description":"","filename":"Supplementalmaterial.docx","url":"https://assets-eu.researchsquare.com/files/rs-7304887/v1/90046d0b857ce409db2b94ff.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Multi-Omics Analysis Reveals Flavor Differences Between Queshan And Yunong Black Pigs","fulltext":[{"header":"1 Introduction","content":"\u003cp\u003ePork is one of the most widely consumed meat products globally, and its quality directly affects consumers' preferences and market value. However, meat quality is a complex multidimensional trait that mainly includes organoleptic attributes such as flavor, tenderness, juiciness and color, and is comprehensively affected by a combination of several factors, including genetics, nutrition, living conditions and slaughter treatment[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. Flavor, which encompasses aroma and taste, is a crucial element in evaluating pork quality and profoundly influences consumers' sensory experience[\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. VOCs mainly include aldehydes, esters, ketones, hydrocarbons, furans, and alcohols, etc. These substances are generated by flavor precursor substances through lipid oxidation, Strecker reaction, Maillard reaction, and thiamine degradation, thereby contributing to the formation of flavor aroma. Flavor precursor substances can be divided into two major categories: water-soluble and lipid-soluble. Among them, the former chiefly comprise amino acids (AAs), reducing sugars, peptides, and thiamine, etc., while lipid-soluble precursor substances mainly include lipids. It has been reported that amino acids and peptides can enhance the flavor of meat, and most amino acids have one or more of the taste qualities such as sweetness, saltiness, bitterness, sourness, or umami [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. They can generate sulfur-, nitrogen-, and oxygen-containing aromatic compounds through the Maillard reaction, which constitute the main aroma of cooked meat[\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. Cysteine and methionine are also considered the biggest contributors to the development of meat flavor[\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. Lipids, as important lipid-soluble flavor precursor substances, the free fatty acids (FAs) produced by their decomposition can be further converted into specific flavor compounds[\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. Current research generally believes that phospholipids are the key lipids determining the flavor of meat products, and phosphatidylcholine (PC) is the most abundant phospholipid molecule in muscle, being the main cause of flavor changes[\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. In addition, phosphatidylethanolamine (PE) is also crucial for the formation of good flavor during processing[\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. Intramuscular fat (IMF) as an important component of flavor precursors, is mainly composed of lipids and glycerides, with lipids being the main component, accounting for 60\u0026ndash;70%[\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. Studies have shown that meat flavor comes from the interaction of volatile compounds, and high IMF content can increase the content of volatile compounds[\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. Moreover, gender, age, feeding management, genetics, and slaughtering and processing methods all affect the formation of flavor substances.\u003c/p\u003e\u003cp\u003eIn recent years, the rapid advancement of omics technologies, including flavomics, transcriptomics and lipidomics have provided new perspectives for in-depth exploration of the formation mechanism of pork flavor[\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. Among them, two-dimensional gas chromatography-time-of-flight mass spectrometry (GC\u0026times;GC-TOF-MS), as a highly sensitive and high-resolution analytical method, can more comprehensively identify VOCs in pork, thereby revealing the chemical basis of flavor differences[\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. For example, Zhao et al. [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e] employed UHPLC-MS/MS coupled with GC\u0026times;GC-TOF MS to investigate flavor profiles unique to Guanling, Sinan, and Simmental-crossbred cattle. Pork flavor is regulated by multiple genes. The application of RNA-seq can explore the genetic basis of flavor differences in pork more deeply. At the same time, combined with liquid chromatography-mass spectrometry (LC-MS) technology to accurately analyze the composition and changes of lipid compounds in pork, clarify the key role of lipid oxidation in the formation of flavor, and thereby construct a systematic molecular regulatory network of pork flavor[\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eFollowing millennia of domestication and selection, the majority of Chinese native breeds have distinct genetic characteristics of excellent meat quality[\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. The local Chinese breed QS is well known for its high content of IMF, stable genetic traits, rich flavor and excellent meat quality, and is considered a valuable genetic resource in China's livestock gene banks[\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. The Duroc pig have been crossbred with the excellent local breeds of Nanyang Black pig, Laiwu Black pig, and Erhualian pig to produce the YN[\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e], which have remarkable traits such as high fertility rate and strong feed tolerance. Therefore, comprehending the differences of meat quality, especially in flavor between Chinese local pigs and new breeds can both reveal the molecular mechanisms underlying pork flavor and offer a theoretical foundation for breeding pigs with excellent meat quality. This study focused on QS and YN as the subjects to systematically combine flavouromic, transcriptomic and lipidomic analyses to compare the key genes and substances in flavor formation among different pork varieties, and to deeply analyze the molecular regulatory mechanisms of pork flavor. Through multi-omics combined analysis, the key gene closely related to fatty acid metabolism and lipid synthesis - Acetyl-CoA acyltransferase 2 (\u003cem\u003eACAA2\u003c/em\u003e) was screened out[\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e], and the impact of \u003cem\u003eACAA2\u003c/em\u003e on adipocyte differentiation was further explored. This research provides new insights on the regulatory mechanism of pork flavor formation and lays the foundation for the breeding and molecular mechanism research of high-quality pork.\u003c/p\u003e"},{"header":"2 Materials and Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003e2.1 Animals and samples collection\u003c/h2\u003e\u003cp\u003eIn this study, 10 castrated boars each were selected from QS (provided by the Qushan Black Pig Farm in Henan Province) and YN (provided by Henan Yifa Animal Husbandry Co., Ltd.), and they were reared under similar management and feeding conditions, the diet formulations are detailed in table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e. These pigs were allowed to feed and drink water without restrictions. All the test pigs were raised and managed under similar conditions. When their body weight reached 101\u0026thinsp;\u0026plusmn;\u0026thinsp;5.35 kg, they were blinded by electric shock and then slaughtered. The longissimus dorsi (LD) of pigs was collected from the front end of the third thoracic vertebra in the penultimate section for meat quality determination and sample preservation. Three samples were collected from each pig, with the entire collection process completed within 45 minutes. Then, four pigs were randomly selected from the two breeds respectively for sequencing analysis. The remaining samples were stored at \u0026minus;\u0026thinsp;80\u0026deg;C for subsequent experiments.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec4\" class=\"Section2\"\u003e\u003ch2\u003e2.2 Meat quality, FAs and AAs samples analysis\u003c/h2\u003e\u003cp\u003eSamples were collected in accordance with the \" NY/T 821\u0026ndash;2019 Technical Specification for Determination of Pig Muscle Mass.\" And the meat quality indexes such as water content, crude protein content, IMF, meat color \u003csub\u003e24h\u003c/sub\u003e, marbling score, pH at 24h post-slaughter (pH\u003csub\u003e24h\u003c/sub\u003e) and drip loss (DL) were determined. Biological tests were conducted thrice for each index, and the average value was utilized for subsequent analysis. FAs were determined according gas chromatography (DB37/T 3817\u0026thinsp;\u0026minus;\u0026thinsp;2019) and AAs were determined by Liquid Chromatography (LC) according to Elite-AKK amino acid analysis manual.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec5\" class=\"Section2\"\u003e\u003ch2\u003e2.3 Flavoromic analysis\u003c/h2\u003e\u003cp\u003eFlavoromics study of the LD was performed to examine the VOCs in QS and YN. Analyses were conducted using a LECO Pegasus\u0026reg; 4D instrument (LECO Corporation, St. Joseph, MI, USA). High-purity helium (\u0026gt;\u0026thinsp;99.999%) served as the carrier gas, at a steady flow rate of 1.0 mL/min. The detection of flavor compounds was carried out using the LECO Pegasus BT 4D system. The NIST2020 database and the Chroma TOF (1.2.0.6) search software were utilized to annotate the flavor compounds on the original data off the machine. Additionally, PubChem (2022) and Classyfire (2022) were used to annotate and analyze the types of flavor substances, as well as the number and relative content of various flavor substances[\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e].\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec6\" class=\"Section2\"\u003e\u003ch2\u003e2.4 Transcriptomic analysis and validation\u003c/h2\u003e\u003cp\u003eRNA extraction was conducted using TRIzol reagent (15596018, Thermo Fisher Scientific, Waltham, MA, USA) and its integrity was evaluated using a gel imaging system (Bio-Rad, Hercules, CA, USA), and its purity was measured using a Nanodrop NC2000 spectrophotometer (Thermo Fisher Scientific, Waltham, MA, USA). Utilizing an Illumina NovaSeq 6000 (Novogene Bioinformatics Technology Co., Ltd., Beijing, China), the samples underwent paired-end high-throughput sequencing. The reference genome was mapped to the filtered sequencing reads using the upgraded HISAT2 (2.1.0) software, which is an improved version of TopHat2. The DEGs were detected using the DESeq algorithm, with conditions of \u003cem\u003eP\u003c/em\u003e-value\u0026thinsp;\u0026lt;\u0026thinsp;0.05 and Fold Change (FC)\u0026thinsp;\u0026gt;\u0026thinsp;1.2 or FC\u0026thinsp;\u0026lt;\u0026thinsp;0.83.\u003c/p\u003e\u003cp\u003eReverse transcription was performed using the Evo M-MLV RT Kit (AG11705, Accurate Biotechnology (Hunan) Co., Ltd., Changsha, Hunan, China). Next, quantitative real-time polymerase chain reaction (qRT-PCR) was conducted on the CFX96\u0026trade; Real-Time System (Thermo Fisher Scientific, Waltham, MA, USA) using SYBR Green Premix Pro Taq HS qPCR Kit (AG11701, Accurate Biotechnology (Hunan) Co., Ltd., Changsha, Hunan, China). Each reaction was conducted in triplicate, with glyceraldehyde-3-phosphate dehydrogenase (\u003cem\u003eGAPDH\u003c/em\u003e) serving as the normalization controls. The relative levels of gene expression were determined using the 2\u003csup\u003e\u0026minus;ΔΔCt\u003c/sup\u003e method.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e\u003ch2\u003e2.5 Untargeted lipidomic analysis\u003c/h2\u003e\u003cp\u003eUntargeted lipidomics analysis was performed on LD of QS and YN to examine lipid composition. After lipids were extracted, an ACQUITY UPLC\u0026reg; BEH C18 (2.1 mm \u0026times; 100 mm, 1.7 m, Waters Corporation, Milford, MA, USA) column kept at 50℃ was utilized for the chromatographic separation. The temperature inside the capillaries was 325℃. The normalized collision energy was 30 eV, and dynamic exclusion was employed to remove extraneous data from the MS/MS spectra.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\u003ch2\u003e2.6 Comprehensive analysis of flavoromics, transcriptomics and lipidomics\u003c/h2\u003e\u003cp\u003eTo deeply explore the influence of VOCs, DEGs and DELs on the flavor of pork, this study conducted Pearson correlation analysis on the flavoromics, transcriptomics and lipidomics data through the website of OmicShare tools (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.omicshare.com/\u003c/span\u003e\u003cspan address=\"https://www.omicshare.com/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e). In pairwise comparisons and joint analysis among the omics, the strong correlations among VOCs, DEGs nd DELs were identified by the standard of \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05 and |r| \u0026gt;0.8, thereby screening out the key VOCs, genes and lipids that affect the flavor of pork. In addition, the interaction relationships among them were visualized by constructing network diagrams.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e\u003ch2\u003e2.7 Isolation, culture and transfection of porcine intramuscular preadipocytes\u003c/h2\u003e\u003cp\u003ePorcine intramuscular preadipocytes were isolated according to previously described methods[\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e], which were cultured using complete medium containing 89% DMEM (Beijing Solarbio Science \u0026amp; Technology Co., Ltd., Beijing, China), 10% FBS (Gibco, Carlsbad, CA, USA), and 1% penicillin-streptomycin solution (Beijing Solarbio Science \u0026amp; Technology Co., Ltd., Beijing, China) at 37℃ with 5% CO\u003csub\u003e2\u003c/sub\u003e. The cells were transfected after the cell density reached 70\u0026ndash;80% after being inoculated into a 6-well cell culture plate. They were then cultured at 37℃ with 5% CO₂, with medium change interval of 2 d.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e\u003ch2\u003e2.8 Plasmid construction\u003c/h2\u003e\u003cp\u003eThe coding region of porcine \u003cem\u003eACAA2\u003c/em\u003e was amplified by PCR and subcloned into pcDNA3.1-EGFP as the vector to construct an overexpression plasmid (p-ACAA2). Subsequently, the p-ACAA2 was transfected into porcine intramuscular preadipocytes and 3T3-L1 cells.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\u003ch2\u003e2.9 Oil Red O Staining\u003c/h2\u003e\u003cp\u003eThe cells in the 6-well plate were stained according to the Oil Red O kit procedure (Beijing Solarbio Science \u0026amp; Technology Co., Ltd., Beijing, China) at the day 8 of cell differentiation. The lipid droplets were visualized under inverted fluorescence microscope (Leica Microsystems, Wetzlar, Germany).\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e\u003ch2\u003e2.10 Statistical analysis\u003c/h2\u003e\u003cp\u003eFor both statistical analysis and data visualization, the OmicShare tools (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.omicshare.com/tools\u003c/span\u003e\u003cspan address=\"https://www.omicshare.com/tools\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) and BioDeep Platform (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.biodeep.cn\u003c/span\u003e\u003cspan address=\"https://www.biodeep.cn\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) were utilized. The DELs and differential VOCs were identified based on criteria of \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05, VIP\u0026thinsp;\u0026gt;\u0026thinsp;1. Data in this study were expressed as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation (SD). Statistical analyses were conducted utilizing SPSS 26.0, employing independent sample T-test. When \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05, statistical significance was determined. Significance levels were indicated as follows: * \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05, ** \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01, *** \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001.\u003c/p\u003e\u003c/div\u003e"},{"header":"3 Results","content":"\u003cdiv id=\"Sec14\" class=\"Section2\"\u003e\u003ch2\u003e3.1 Comparison and analysis of muscle quality between QS and YN\u003c/h2\u003e\u003cp\u003eTo study the muscle quality of the two breeds, the meat quality related indexes were measured. The results indicated that the water content of QS was significantly lower than that of YN (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05). At the same time, the pH\u003csub\u003e24h\u003c/sub\u003e and meat color\u003csub\u003e24h\u003c/sub\u003e in QS were higher, and the DL was lower. IMF content and marbling score were significantly higher than YN (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01, Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eComparison of muscle quality between QS and YN\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"3\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eItems\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eQS\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eYN\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMoisture (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e\u003cp\u003e72.4\u0026thinsp;\u0026plusmn;\u0026thinsp;1.41\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e\u003cp\u003e73.53\u0026thinsp;\u0026plusmn;\u0026thinsp;0.37\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eProtein (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e\u003cp\u003e22.10\u0026thinsp;\u0026plusmn;\u0026thinsp;1.62\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e\u003cp\u003e20.44\u0026thinsp;\u0026plusmn;\u0026thinsp;0.94\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eIMF (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e\u003cp\u003e4.52\u0026thinsp;\u0026plusmn;\u0026thinsp;0.98\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e\u003cp\u003e3.33\u0026thinsp;\u0026plusmn;\u0026thinsp;0.21\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePH\u003csub\u003e24h\u003c/sub\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e\u003cp\u003e5.83\u0026thinsp;\u0026plusmn;\u0026thinsp;0.14\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e\u003cp\u003e5.71\u0026thinsp;\u0026plusmn;\u0026thinsp;0.18\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDL (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e\u003cp\u003e1.24\u0026thinsp;\u0026plusmn;\u0026thinsp;0.21\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e\u003cp\u003e1.36\u0026thinsp;\u0026plusmn;\u0026thinsp;0.41\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMeat color\u003csub\u003e24h\u003c/sub\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e\u003cp\u003e3.25\u0026thinsp;\u0026plusmn;\u0026thinsp;0.50\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e\u003cp\u003e3.19\u0026thinsp;\u0026plusmn;\u0026thinsp;0.43\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMarbling score\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e\u003cp\u003e4.50\u0026thinsp;\u0026plusmn;\u0026thinsp;1.03\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e\u003cp\u003e2.50\u0026thinsp;\u0026plusmn;\u0026thinsp;0.35\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"3\"\u003eNote: Data are expressed as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec15\" class=\"Section2\"\u003e\u003ch2\u003e3.2 FAs and AAs composition and content in QS and YN\u003c/h2\u003e\u003cp\u003eIn order to study the changes of FAs and AAs between QS and YN, a total of 15 FAs and 16 AAs were detected by GC and LC (Table S2 and 3). Overall, the content of total AAs, sweet AAs and 5 AAs (cystine, proline, arginine etc.) in QS were significantly higher than those in YN (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05), and the contents of essential AAs, umami AAs and 5 AAs (isoleucine, lysine, histidine etc.) in YN were significantly higher than those in QS (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05), while there was no significant difference in bitter AAs and other AAs between QS and YN (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026gt;\u0026thinsp;0.05, Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eA and B). The contents of linoleic acid, linolenic acid, arachidonic acid and cis-4,7,10,13,16,19-Docosahexaenoic acid in QS were significantly higher compared to YN (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05). However, no significant difference was identified for palmitoleic acid (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026gt;\u0026thinsp;0.05, Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eC).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec16\" class=\"Section2\"\u003e\u003ch2\u003e3.3 Differential VOCs identification and functional analysis\u003c/h2\u003e\u003cp\u003eIn this study, the VOCs were detected by GC\u0026times;GC TOF-MS, and orthogonal projections to latent structures-discriminant analysis (OPLS-DA) results showed that there was dispersion between the principal components of QS and YN (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA). And, 1,320 VOCs were identified in QS and 1,173 in YN. Among the 37 significant VOC compounds, 16 increased and 21 decreased in QS compared to YN (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eB).\u003c/p\u003e\u003cp\u003eThe kyoto encyclopedia of genes and genomes (KEGG) enrichment analysis was performed on differential VOCs, mainly including protein digestion and absorption, fatty acid biosynthesis and propanoate metabolism etc. The differential VOCs involved in enriching metabolic pathways mainly include phenol, propanal, ethylbenzene and 1-Hexanol (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eC, Table S4). The relative odor activity value (ROAV) of VOCs were shown in the table S5. The results revealed a total of 137 VOCs with ROAV, and 8 VOCs with ROAV\u0026thinsp;\u0026ge;\u0026thinsp;1 were found in QS and YN. Among them, 2,3-butanedione has the highest ROAV in QS, and 2-Nonenal, (E) - has the highest ROAV in YN. However, only 2-Octenal, (E) -is a differential VOCs and can be considered as the key volatile compound. Besides, the correlation analysis of FAs and differential VOCs was performed, and the results showed that 15 FAs were identified that may lead to the difference in flavor between the two pig breeds through the regulation of differential VOC formation (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05, |r| \u0026gt;0.8, Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eD).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec17\" class=\"Section2\"\u003e\u003ch2\u003e3.4 DEGs identification and functional enrichment analysis\u003c/h2\u003e\u003cp\u003eTo further investigate the genes that may affect the differences in meat quality between QS and YN, transcriptomic was applied. Distinct differences in the principal components between the two breeds were indicated by the partial least squares-discriminant analysis (PLS-DA) results. Specifically, PC1 explained 30.1% of the variance, while PC2 accounted for 19.8% of the variance (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eA). In addition, compared with YN, there were 1,446 up-regulated and 1,113 down-regulated DEGs in QS (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eB).\u003c/p\u003e\u003cp\u003eGene ontology (GO) analysis indicated that DEGs were significantly enriched in regulation of macromolecular metabolic process, regulation of primary metabolic process, cellular macromolecular metabolic process, and small molecule metabolic process (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05, Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eC and D). According to the results of the KEGG enrichment study, DEGs were mostly engaged in IL-17 signaling pathway, fatty acid degradation, fatty acid elongation and AMPK signaling pathway (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05, Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eE and F, Table S6 and 7). To further explore the critical factors that play a critical role, protein and protein interactions (PPI) were used. The findings suggested a strong correlation and significant connection between hydroxyacyl-CoA dehydrogenase trifunctional multienzyme complex subunit beta (\u003cem\u003eHADHB\u003c/em\u003e), \u003cem\u003eACAA2\u003c/em\u003e and peroxisome proliferator activated receptor gamma (\u003cem\u003ePPARG\u003c/em\u003e) etc., and these DEGs were involved in AMPK signaling pathway, IL-17 signaling pathway and fatty acid metabolism etc. (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eG). Besides, some genes in the pathways were involved in multiple pathways, such as carnitine palmitoyltransferase 1B (\u003cem\u003eCPT1B\u003c/em\u003e), hydroxyacyl-CoA dehydrogenase (\u003cem\u003eHADH\u003c/em\u003e), hydroxyacyl-CoA dehydrogenase trifunctional multienzyme complex subunit alpha (\u003cem\u003eHADHA\u003c/em\u003e), \u003cem\u003eHADHB\u003c/em\u003e and \u003cem\u003eACAA2\u003c/em\u003e (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eH).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec18\" class=\"Section2\"\u003e\u003ch2\u003e3.5 Validation of transcriptomic data by qRT-PCR\u003c/h2\u003e\u003cp\u003eFurthermore, to ensure the reliability of transcriptomic sequencing, six DEGs were selected for validation. Notably, the accuracy and dependability of the RNA-seq data were confirmed by the qRT-PCR results. (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). This consistency underscores the accuracy of our results.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec19\" class=\"Section2\"\u003e\u003ch2\u003e3.6 Analysis of DELs related to pork flavor\u003c/h2\u003e\u003cp\u003eLC-MS detected 2,210 lipids and 2,209 lipids in QS and YN, which were divided into 51 categories. These lipids included 501 triglycerides (TG), 378 phosphatidylcholine (PC) and 212 phosphatidylethanolamine (PE), as well as 116 and 117 diglyceride (DG) in QS and YN (Table S8). According to the OPLS-DA, there were marked differences between the QS and YN groups, making it easy to distinguish between them (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eA). Compared with YN, QS had 208 lipids up-regulated, mostly TG and PC (36 and 51 respectively), while 252 lipids were down-regulated, including 50 PE, 39 PC and 48 TG (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eB and C).\u003c/p\u003e\u003cp\u003eTG, DG and PC are the three main components of lipids in pork, which are directly related to the meat flavor. Among the DELs detected in this study, there were 90 PC, 84 TG, 61 PE and 31 DG (Table S9). In this study, the relative contents of PC, hemolipin (SM), monohexose ceramide (Hex1Cer), and monogalactosyl glyceride (MGDG) in QS were significantly higher than those in YN, while the contents of TG, PE, and BisMePA were significantly lower than those in YN (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05, Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eD). Pearson correlation analysis was performed on the DELs, found that there were more positively correlated DELs than negatively correlated DELs (Table S10). This may mean that the accumulation of DELs promotes the further accumulation of lipids. Besides, the top 10 lipids of VIP were mostly phospholipids and sphingolipids, and the expression level was high in QS (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eE).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec20\" class=\"Section2\"\u003e\u003ch2\u003e3.7 Correlation analysis among the DEGs, DELs and differential VOCs\u003c/h2\u003e\u003cp\u003eIn an effort to further explore the regulation mechanism of pork flavor, the correlation analysis of DEGs and DELs, DELs and differential VOCs, DEGs and differential VOCs were performed. The joint analysis results revealed significant positive or negative correlations among 16 DEGs and 10 DELs (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eA), 10 DELs and 16 differential VOCs (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eB), 20 DEGs and 18 differential VOCs (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eC). Furthermore, the multi-omics joint analysis results showed that there was a correlation among 15 DEGs, 10 DELs and 14 differential VOCs (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eD). These VOCs, genes and lipids may interact together to affect the pork flavor.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec21\" class=\"Section2\"\u003e\u003ch2\u003e3.8 Key pathways and interactions regulating pork flavor\u003c/h2\u003e\u003cp\u003eTo further explore the interaction between the above genes and lipids, the associated metabolic pathways were studied. The results showed that FAs could enter the cell through CD36, and the fatty acyl-CoA produced by FAs could interact with glycerol-3-phosphate (G3P), participate in glycerolipid metabolism and glycerophospholipid metabolism, and generate TG. TG can be decomposed to produce FAs, and enter mitochondrion through \u003cem\u003eCPT1B\u003c/em\u003e, and ultimately participate in FA oxidation. Besides, adrenoceptor alpha 1A (\u003cem\u003eADRA1A\u003c/em\u003e) can inhibit the expression of SREBP1c through AMPK, and then promote the expression of FAS, thereby regulating FA biosynthesis (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec22\" class=\"Section2\"\u003e\u003ch2\u003e3.9 Effects of ACAA2 on differentiation of porcine intramuscular preadipocytes and 3T3-L1 cells\u003c/h2\u003e\u003cp\u003eIn this study, \u003cem\u003eACAA2\u003c/em\u003e was an important candidate gene. This study investigated its regulatory effect on adipocytes by manipulating its expression in adipocytes. The results showed that after overexpression of \u003cem\u003eACAA2\u003c/em\u003e, its expression levels were significantly up-regulated in porcine intramuscular preadipocytes and 3T3-L1 cells (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01, Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003eA). Additionally, the expression levels of differentiation marker genes, including CCAAT enhancer binding protein alpha (\u003cem\u003eCEBPA\u003c/em\u003e), \u003cem\u003ePPARG\u003c/em\u003e, fatty acid binding protein 4 (\u003cem\u003eFABP4\u003c/em\u003e), and Perilipin 1 (\u003cem\u003ePLIN1\u003c/em\u003e) were significantly increased after \u003cem\u003eACAA2\u003c/em\u003e overexpression in both cell types (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05, Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003eB). Oil Red O staining results demonstrated a significant increase in lipid droplet deposition after overexpression of \u003cem\u003eACAA2\u003c/em\u003e (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01, Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003eC and D). These results indicated that overexpression of \u003cem\u003eACAA2\u003c/em\u003e significantly promote the differentiation of porcine intramuscular preadipocytes and 3T3-L1 cells.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e"},{"header":"4 Discussion","content":"\u003cp\u003e China is rich in local breeding resources and these local pig breeds tend to excellent characteristics, such as the QS black pig, are known for their fine meat texture, superior flavor and high IMF. Our team bred a new breed, YN black pig, through crossbreeding to meet the growth rate and meat quality[\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. In this study, the two breeds were analyzed with multi-omics analyses to reveal the complex molecular mechanisms that regulate the differences in pork flavor between the different pig breeds.\u003c/p\u003e\u003cp\u003eThe degradation of lipids is a major factor in the formation of meat flavor, lipid hydrolysis produces flavor precursors such as free FAs, which are subsequently oxidized to yield VOCs [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. As an important chemical substance that constitutes fat, FAs can not only provide the necessary nutrients for the human body, but also act as flavor precursors to affect the overall flavor of the muscle[\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. The content and composition of FAs in meat are affected by the breed type[\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. This study found QS has more palmitoleic acid than YN. Kimata et al. studied the correlation between muscle FAs composition and pork edible quality, and found that SFAs and MUFAs were positively correlated with pork tenderness, juiciness and flavor. In particular, palmitoleic acid content was highly positively correlated with meat flavor[\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. Linoleic acid, linolenic acid and arachidonic acid are essential FAs within PUFAs, and linoleic acid is one of the essential FAs that cannot be synthesized in humans and animals. Several studies have confirmed that conjugated linoleic acid can enhance the transformation of mesenchymal cells into preadipocytes, increase IMF content and improve meat quality[\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. cis-4,7,10,13,16,19-Docosahexaenoic acid can assist brain thinning[\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. This study found the contents of PUFAs and linoleic acid, linolenic acid, arachidonic acid and cis-4,7,10,13,16,19-Docosahexaenoic acid in QS were significantly higher. And PUFAs cannot be produced in humans and must be obtained through dietary consumption and are therefore considered essential for the body. In general, the content of PUFAs in QS was higher than that in YN.\u003c/p\u003e\u003cp\u003eBesides, AAs are key compounds for growth, immunity and regulation of metabolic pathways [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. It is reported that AAs can enhance the meat flavor, including sour, sweet, bitter, salty, and umami [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. Serine largely determines the meat flavor [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e], and threonine can improve the meat quality[\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. In the production of mutton, arginine may be utilized to enhance meat quality and protein deposition [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]. In this study, the contents of total amino acids, sweet amino acids, serine, threonine and arginine in QS were significantly higher than those in YN.\u003c/p\u003e\u003cp\u003eFlavor, as the dominant factor, significantly influences both meat quality and consumer purchasing decisions. However, only a few of the major VOCs in food have ROAV that indeed contributes to the overall aroma. Therefore, it is important to figure out which VOCs play an important role in food flavor. Proteins can affect IMF deposition. OTX2 protein is a transcription factor containing a homologous domain and may be involved in the regulation of adipose tissue function [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e, \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. Propionate can be converted into lipids by lipogenesis and induce the expression of lipogenic genes. It can also stimulate lipid accumulation in 3T3-L1 adipocytes [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e, \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]. Thus, genes may regulate the production of phenol, propanal, ethylbenzene and 1-Hexanol by affecting pathways like protein digestion and absorption, fatty acid biosynthesis and propanoate metabolism.\u003c/p\u003e\u003cp\u003eTherefore, in order to further explore the genetic basis leading to the difference of pork flavor in different breeds, this study also carried out transcriptome analysis. The AMPK signaling pathway is a critical pathway for lipid metabolism. This pathway's activation enhances fatty acid oxidation and simultaneously inhibits lipid production in adipocytes[\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]. IL-17 can regulate adipogenesis and adipocyte metabolism [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]. FAs and cholesterol levels in meat are very important due to their effects on human health [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e, \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e]. Fat deposition is governed by the synthesis of FAs as well as the uptake of exogenous FAs [\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e]. \u003cem\u003eCPT1B\u003c/em\u003e is a rate-limiting enzyme that inhibits the β-oxidation of long-chain fatty acids within the mitochondria of muscle cells. In bovine fetal fibroblasts, elevated expression of \u003cem\u003eCPT1B\u003c/em\u003e notably increases triglyceride levels [\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e]. The last step of the fatty acid β-oxidation cycle is catalyzed by \u003cem\u003eHADHB\u003c/em\u003e, which facilitates the reaction of β-ketoacyl-CoA with a molecule of free coenzyme A, cleaving the carboxyl-terminal two-carbon fragment from the original fatty acid to form acetyl-CoA [\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e]. \u003cem\u003eACAA2\u003c/em\u003e encoded protein catalyzed the last step of mitochondrial fatty acid β-oxidation spiral [\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e]. Adipocytes differentiation is tightly regulated by various transcription factors including \u003cem\u003ePPARG\u003c/em\u003e and CCAAT/Enhancer Binding Protein \u0026ndash; α (C/EBP-α) [\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e]. \u003cem\u003ePPARG\u003c/em\u003e regulates the expression of numerous key adipocyte genes, these genes are engaing in coordinating fatty acid uptake, metabolism, and storage [\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e]. Genes are located in the upstream of regulating metabolic processes, so their expression patterns can lead to differences in VOCs. These genes are closely linked to adipocyte differentiation, fatty acids synthesis, and lipid metabolism, etc. Consequently, they may be the key factors for the difference in pork flavor between the two breeds.\u003c/p\u003e\u003cp\u003eLipids are vital in the formation of unique meat flavor through lipid degradation and fatty acid oxidation [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. Current research generally believes that phospholipids are the key lipids determining meat flavor, and the volatile compounds generated from their thermal decomposition and oxidation reactions are important sources of the unique flavor of meat products [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. PCs is the most abundant phospholipid molecule in muscle and is the main cause of flavor variation [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e]. The different lipids have distinct physiological effects on the human body. For instance, sphingolipids (SPs) have the ability to inhibit some cancers [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. In this study, QS was found to have a significantly higher level of PC than YN. Besides, SM, Hex1Cer, MGDG, TG, PE and BisMePA were significantly different in QS and YN, so this study speculated that the FAs that affect the different flavors of the two pork were mainly produced by these lipids.\u003c/p\u003e\u003cp\u003eTo explore the molecular regulatory mechanisms leading to the differences in pork flavor between the two varieties, this study conducted a combined analysis of flavoromics, transcriptomics and lipidomics. Association analysis between flavoromics and lipidomics, SM (t40:5) was found to be significantly positively correlated with pyridine. Surprisingly, \u003cem\u003eACAA2\u003c/em\u003e exhibited a significant negative correlation with both SM (t40:5) and pyridine. And there was also a significant negative correlation between \u003cem\u003eACAA2\u003c/em\u003e and pyridine. Acetyl-CoA acyltransferase 1 (\u003cem\u003eACAA1\u003c/em\u003e), acyl-CoA dehydrogenase short chain (\u003cem\u003eACADS\u003c/em\u003e) and \u003cem\u003eCPT1B\u003c/em\u003e etc. have a directly positive or negative relationship with other DELs and differential VOCs. Therefore, PC (26:3), PC (18:1e_6:0) and PC (29:3) etc. may be the upstream metabolites of pyridine, phenol and 1-Hexanol etc., which can affect the formation of pork-specific flavor. Thus, they may cooperate to regulate meat flavor. It is inferred that these genes and lipids may regulate the FA biosynthesis, FA oxidation, glycerolipid metabolism and glycerophospholipid metabolism, by investigating the metabolic pathways associated with them, thereby regulating lipid production and decomposition. And, these genes were significantly positively correlated with TG and DG contents. Furthermore, they also showed a positive correlation with particular VOCs. Thus, it is speculated that the overexpression of these critical genes may promote the synthesis of TG, thereby facilitating the degradation of TG into glycerol and FAs. And this may accelerate the oxidation of FAs into VOCs.\u003c/p\u003e\u003cp\u003eThe IMF is essential to the development of pork flavor. Research has shown that the unsaturated fatty acids in IMF, especially the PUFA, are prone to thermal degradation and oxidation reactions, generating volatile compounds such as aldehydes and ketones. These substances are the key factors that give pork its unique aroma. Moreover, the lipid oxidation products can also react with other molecules, further influencing the flavor characteristics[\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e]. The deposition of IMF is closely related to lipid metabolism. In-depth study of the lipid metabolism process is helpful in revealing the molecular mechanism of flavor formation. Through joint analysis and literature mining, we found that \u003cem\u003eACAA2\u003c/em\u003e is important candidate genes that may affect meat quality differences. \u003cem\u003eACAA2\u003c/em\u003e is a critical gene involved in the lipid metabolism pathway, positively linked with the content of IMF, and is regarded as an important regulatory factor determining the accumulation of IMF[\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e]. Studies have shown that \u003cem\u003eACAA2\u003c/em\u003e can promote the differentiation of preadipocytes. For example, miR-193a-5p inhibits the differentiation of 3T3-L1 preadipocytes by targeting the expression of \u003cem\u003eACAA2\u003c/em\u003e gene[\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e]. This study further verified that \u003cem\u003eACAA2\u003c/em\u003e can promote lipid deposition in porcine intramuscular preadipocytes and 3T3-L1 cells. The findings suggest that \u003cem\u003eACAA2\u003c/em\u003e may indirectly affect the generation of flavor substances by regulating lipid accumulation. It is an important regulatory factor connecting lipid metabolism and flavor formation, offering a potential target for further improving pork quality.\u003c/p\u003e"},{"header":"5 Conclusion","content":"\u003cp\u003eIn general, this study compared the differences in pork flavor between the two pig breeds based on the methods of flavoromics, transcriptomics and lipidomics. The results indicated that the contents of total AAs, sweet AAs and 5 AAs (cystine, proline, arginine etc.) in QS were higher than those in YN. In addition, 14 VOCs (pyridine, 1- hexanol, phenol, etc.), 15 DEGs (\u003cem\u003eACAA2\u003c/em\u003e, \u003cem\u003eHADHB\u003c/em\u003e, \u003cem\u003eCPT1B\u003c/em\u003e, etc.) and10 DELs (PC (18:1e_6:0), PC (26:3), PE (34:6e), etc.) may play important roles in pork flavor. In addition, the analysis revealed that these genes may be involved in FA biosynthesis, FA oxidation, and glycerophospholipid metabolism by regulating lipid production and lipid breakdown. Finally, this study found that \u003cem\u003eACAA2\u003c/em\u003e promoted the lipid deposition of porcine intramuscular preadipocytes and 3T3-L1 cells. These findings provide a theoretical basis for exploring the molecular regulatory mechanisms of multi-omics in influencing the flavor of pork.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eVOCs, volatile organic compounds; DEGs, differential expressed genes; DELs, differential lipids; FAs, fatty acids; IMF, intramuscular fat; SFAs, saturated fatty acids; MUFAs, monounsaturated fatty acids; PUFAs, polyunsaturated fatty acids; ACAA2, acetyl-CoA acyltransferase 2; LD, longissimus dorsi; AAs, amino acids; pH24h, pH at 24h post-slaughter; DL, drip loss; FC, Fold Change; qRT-PCR, quantitative real-time polymerase chain reaction; GAPDH, glyceraldehyde-3-phosphate dehydrogenase; SD, standard deviation; KEGG, kyoto Encyclopedia of Genes and Genomes; ROAV, relative odor activity value; GO, gene Ontology; PPI, protein-protein interactions; PPARG, peroxisome proliferator activated receptor gamma; CPT1B, carnitine palmitoyltransferase 1B; HADH, hydroxyacyl-CoA dehydrogenase; HADHA, hydroxyacyl-CoA dehydrogenase trifunctional multienzyme complex subunit alpha; TG, triglyceride; PC, phosphatidylcholine; PE, phosphatidylethanolamine; DG, diglyceride; SM, sphingomyelin; Hex1Cer, monohexosyl ceramide; MGDG, monogalactosyl glyceride; G3P, glycerol-3-phosphate; ADRA1A, adrenoceptor alpha 1A; CEBPA, CCAAT enhancer binding protein alpha; FABP4, fatty acid binding protein 4; PLIN1, Perilipin 1; C/EBP-\u0026alpha;, CCAAT/Enhancer Binding Protein \u0026ndash; \u0026alpha;; ACAA1, Acetyl-CoA acyltransferase 1; ACADS, acyl-CoA dehydrogenase short chain.\u003c/p\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was performed in compliance with the protocols for the care and use of experimental animals established by the People\u0026rsquo;s Republic of China\u0026rsquo;s Ministry of Science and Technology (Approval Number: DWLL20211193).\u0026nbsp;And\u0026nbsp;this experiment was approved by the Ethics Committee of Henan Agricultural University. In addition, all test methods were conducted in compliance with applicable regulations and adhered to the ARRIVE guidelines governing animal research. All animal experiments involved in this study were conducted with the informed consent of the owners.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe RNA-seq data of this study has been deposited in the National Center for Biotechnology Information (NCBI), with the accession number PRJNA1310286.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis research was financed and supported by the Pig Industry Technology System Innovation Team Project of Henan Province (HARS-22-12-G4), the 14th Five-Year National Key R\u0026amp;D Program (2021YFD1301202), and the Agricultural Breeds Research Project of Henan Province (2022020101).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCRediT authorship contribution statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eBingjie Wang: Conceptualization, Visualization, Validation, Formal analysis, Writing \u0026ndash; original draft, Writing \u0026ndash; review \u0026amp; editing. Yilin Wei: Visualization, Validation.\u0026nbsp;Chang Wang: Validation, Formal analysis.\u0026nbsp;Lebin Chang\u0026nbsp;Validation. Tengfei Wang: Investigation. Xinjian Li: Resources. Tong Yu: Software. Jun Bai: Formal analysis. Liwei Yuan: Validation.\u0026nbsp;Wei Wang: Supervision. Ruimin Qiao: Supervision. Feng Yang: Supervision. Xiuling Li \u0026amp; Xuelei Han: Writing \u0026ndash; original draft, Writing \u0026ndash; review \u0026amp; editing, Resources, Data Curation, Supervision, Investigation, Project administration, Funding acquisition.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAppendix A. Supplementary data\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eSupplementary data to this article can be found online at https://. Table S1: Ingredient composition of pig diets for pigs (%). Table S2: FAs contents (\u0026mu;g/g) in LD of QS and YN. Table S3: AAs contents (%) in LD of QS and YN. Table S4: The KEGG enrichment analysis of differential VOCs. Table S5: The ROAV results of VOCs. Table S6: The KEGG enrichment analysis of up-regulated DEGs. Table S7: The KEGG enrichment analysis of down-regulated DEGs. Table S8: The number of lipids identified in QS and YN. Table S9: The number and proportion of various types of DELs. Table S10: The correlation analysis of DELs classification.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eGeletu US, Usmael MA, Mummed YY, Ibrahim AM: \u003cstrong\u003eQuality of Cattle Meat and Its Compositional Constituents\u003c/strong\u003e. \u003cem\u003eVet Med Int \u003c/em\u003e2021, \u003cstrong\u003e2021\u003c/strong\u003e:7340495.\u003c/li\u003e\n\u003cli\u003eKhan MI, Jo C, Tariq MR: \u003cstrong\u003eMeat flavor precursors and factors influencing flavor precursors--A systematic review\u003c/strong\u003e. \u003cem\u003eMeat Sci \u003c/em\u003e2015, \u003cstrong\u003e110\u003c/strong\u003e:278-284.\u003c/li\u003e\n\u003cli\u003eBachmanov AA, Bosak NP, Glendinning JI, Inoue M, Li X, Manita S, McCaughey SA, Murata Y, Reed DR, Tordoff MG\u003cem\u003e et al\u003c/em\u003e: \u003cstrong\u003eGenetics of Amino Acid Taste and Appetite\u003c/strong\u003e. \u003cem\u003eAdv Nutr \u003c/em\u003e2016, \u003cstrong\u003e7\u003c/strong\u003e(4):806s-822s.\u003c/li\u003e\n\u003cli\u003eSohail A, Al-Dalali S, Wang J, Xie J, Shakoor A, Asimi S, Shah H, Patil P: \u003cstrong\u003eAroma compounds identified in cooked meat: A review\u003c/strong\u003e. \u003cem\u003eFood Res Int \u003c/em\u003e2022, \u003cstrong\u003e157\u003c/strong\u003e:111385.\u003c/li\u003e\n\u003cli\u003eXiong L, Pei J, Wang X, Guo S, Guo X, Yan P: \u003cstrong\u003eEffect of Lipids in Yak Muscle under Different Feeding Systems on Meat Quality Based on Untargeted Lipidomics\u003c/strong\u003e. \u003cem\u003eAnimals (Basel) \u003c/em\u003e2022, \u003cstrong\u003e12\u003c/strong\u003e(20).\u003c/li\u003e\n\u003cli\u003eJia W, Li R, Wu X, Liu S, Shi L: \u003cstrong\u003eUHPLC-Q-Orbitrap HRMS-based quantitative lipidomics reveals the chemical changes of phospholipids during thermal processing methods of Tan sheep meat\u003c/strong\u003e. \u003cem\u003eFood Chem \u003c/em\u003e2021, \u003cstrong\u003e360\u003c/strong\u003e:130153.\u003c/li\u003e\n\u003cli\u003eLiu H, Hui T, Zheng X, Li S, Wei X, Li P, Zhang D, Wang Z: \u003cstrong\u003eCharacterization of key lipids for binding and generating aroma compounds in roasted mutton by UPLC-ESI-MS/MS and Orbitrap Exploris GC\u003c/strong\u003e. \u003cem\u003eFood Chem \u003c/em\u003e2022, \u003cstrong\u003e374\u003c/strong\u003e:131723.\u003c/li\u003e\n\u003cli\u003eLi J, Yang Y, Tang C, Yue S, Zhao Q, Li F, Zhang J: \u003cstrong\u003eChanges in lipids and aroma compounds in intramuscular fat from Hu sheep\u003c/strong\u003e. \u003cem\u003eFood Chem \u003c/em\u003e2022, \u003cstrong\u003e383\u003c/strong\u003e:132611.\u003c/li\u003e\n\u003cli\u003eWang B, Qin K, Qi K, Zhang R, Xu Z, Men X: \u003cstrong\u003eConstruction of a molecular regulatory network for lipids and volatile flavor in Chinese indigenous and hybrid pig pork through integrating multi-omics analysis\u003c/strong\u003e. \u003cem\u003eLwt \u003c/em\u003e2024, \u003cstrong\u003e199\u003c/strong\u003e.\u003c/li\u003e\n\u003cli\u003eLi W, Chen YP, Blank I, Li F, Li C, Liu Y: \u003cstrong\u003eGC \u0026times; GC-ToF-MS and GC-IMS based volatile profile characterization of the Chinese dry-cured hams from different regions\u003c/strong\u003e. \u003cem\u003eFood Res Int \u003c/em\u003e2021, \u003cstrong\u003e142\u003c/strong\u003e:110222.\u003c/li\u003e\n\u003cli\u003eWang X, Xu R, Tong X, Zeng J, Chen M, Lin Z, Cai S, Chen Y, Mo D: \u003cstrong\u003eCharacterization of different meat flavor compounds in Guangdong small-ear spotted and Yorkshire pork using two-dimensional gas chromatography\u0026ndash;time-of-flight mass spectrometry and multi-omics\u003c/strong\u003e. \u003cem\u003eLwt \u003c/em\u003e2022, \u003cstrong\u003e169\u003c/strong\u003e.\u003c/li\u003e\n\u003cli\u003eZhao Y, Zhou J, Luo W, Jiang L, Song F, Ran J, Xu H, Lei L, Ai R, Yu B: \u003cstrong\u003eAn integrated metabolomics-flavoromics analysis reveals flavor diversity in indigenous and hybrid cattle via UHPLC-MS/MS and GC\u0026times;GC-TOF-MS\u003c/strong\u003e. \u003cem\u003eFood Chem X \u003c/em\u003e2025, \u003cstrong\u003e29\u003c/strong\u003e:102801.\u003c/li\u003e\n\u003cli\u003eLi M, Zhu M, Chai W, Wang Y, Song Y, Liu B, Cai C, Song Y, Sun X, Xue P\u003cem\u003e et al\u003c/em\u003e: \u003cstrong\u003eDetermination of the Heterogeneity of Intramuscular Fat and Visceral Adipose Tissue From Dezhou Donkey by Lipidomics and Transcriptomics Profiling\u003c/strong\u003e. \u003cem\u003eFront Nutr \u003c/em\u003e2021, \u003cstrong\u003e8\u003c/strong\u003e:746684.\u003c/li\u003e\n\u003cli\u003eZhao QB, Oyelami FO, Qadri QR, Sun H, Xu Z, Wang QS, Pan YC: \u003cstrong\u003eIdentifying the unique characteristics of the Chinese indigenous pig breeds in the Yangtze River Delta region for precise conservation\u003c/strong\u003e. \u003cem\u003eBMC Genomics \u003c/em\u003e2021, \u003cstrong\u003e22\u003c/strong\u003e(1):151.\u003c/li\u003e\n\u003cli\u003eQi K, Liu Y, Li C, Li X, Li X, Wang K, Qiao R, Han X: \u003cstrong\u003eConstruction of circRNA-related ceRNA networks in longissimus dorsi muscle of Queshan Black and Large White pigs\u003c/strong\u003e. \u003cem\u003eMol Genet Genomics \u003c/em\u003e2022, \u003cstrong\u003e297\u003c/strong\u003e(1):101-112.\u003c/li\u003e\n\u003cli\u003eLi M, Li X, Liu C, Han J, Han X, Wang K, Qiao R, Yang F, Li XL, Li XJ: \u003cstrong\u003eGenome-wide association study reveals the candidate genes for reproduction traits in Yunong black pigs\u003c/strong\u003e. \u003cem\u003eAnim Genet \u003c/em\u003e2023, \u003cstrong\u003e54\u003c/strong\u003e(3):403-407.\u003c/li\u003e\n\u003cli\u003eLi X, Li M, Han J, Liu C, Han X, Wang K, Qiao R, Li XL, Li XJ: \u003cstrong\u003eCorrelation between fat accumulation and fecal microbiota in crossbred pigs\u003c/strong\u003e. \u003cem\u003eJ Microbiol \u003c/em\u003e2022, \u003cstrong\u003e60\u003c/strong\u003e(11):1077-1085.\u003c/li\u003e\n\u003cli\u003ePetit A, Tesseraud S, Collin A, Courouss\u0026eacute; N, Berri C, Bihan-Duval EL, M\u0026eacute;tayer-Coustard S: \u003cstrong\u003eOntogeny of hepatic metabolism in two broiler lines divergently selected for the ultimate pH of the Pectoralis major muscle\u003c/strong\u003e. \u003cem\u003eBMC Genomics \u003c/em\u003e2024, \u003cstrong\u003e25\u003c/strong\u003e(1):438.\u003c/li\u003e\n\u003cli\u003eDjoumbou Feunang Y, Eisner R, Knox C, Chepelev L, Hastings J, Owen G, Fahy E, Steinbeck C, Subramanian S, Bolton E\u003cem\u003e et al\u003c/em\u003e: \u003cstrong\u003eClassyFire: automated chemical classification with a comprehensive, computable taxonomy\u003c/strong\u003e. \u003cem\u003eJ Cheminform \u003c/em\u003e2016, \u003cstrong\u003e8\u003c/strong\u003e:61.\u003c/li\u003e\n\u003cli\u003eLiu Y, Dou Y, Qi K, Li C, Song C, Li X, Li X, Qiao R, Wang K, Han X: \u003cstrong\u003eCircSETBP1 Acts as a MiR-149-5p Sponge to Promote Intramuscular Fat Deposition by Regulating CRTCs\u003c/strong\u003e. \u003cem\u003eJ Agric Food Chem \u003c/em\u003e2022, \u003cstrong\u003e70\u003c/strong\u003e(40):12841-12851.\u003c/li\u003e\n\u003cli\u003eFu Y, Cao S, Yang L, Li Z: \u003cstrong\u003eFlavor formation based on lipid in meat and meat products: A review\u003c/strong\u003e. \u003cem\u003eJ Food Biochem \u003c/em\u003e2022, \u003cstrong\u003e46\u003c/strong\u003e(12):e14439.\u003c/li\u003e\n\u003cli\u003eBjorklund EA, Heins BJ, Dicostanzo A, Chester-Jones H: \u003cstrong\u003eFatty acid profiles, meat quality, and sensory attributes of organic versus conventional dairy beef steers\u003c/strong\u003e. \u003cem\u003eJ Dairy Sci \u003c/em\u003e2014, \u003cstrong\u003e97\u003c/strong\u003e(3):1828-1834.\u003c/li\u003e\n\u003cli\u003eGuo T, Zhang Q, Wang X, Xu X, Wang Y, Wei L, Li N, Liu H, Hu L, Zhao N\u003cem\u003e et al\u003c/em\u003e: \u003cstrong\u003eTargeted and untargeted metabolomics reveals meat quality in grazing yak during different phenology periods on the Qinghai-Tibetan Plateau\u003c/strong\u003e. \u003cem\u003eFood Chem \u003c/em\u003e2024, \u003cstrong\u003e447\u003c/strong\u003e:138855.\u003c/li\u003e\n\u003cli\u003eCandek-Potokar M, Monin G, Zlender B: \u003cstrong\u003ePork quality, processing, and sensory characteristics of dry-cured hams as influenced by Duroc crossing and sex\u003c/strong\u003e. \u003cem\u003eJ Anim Sci \u003c/em\u003e2002, \u003cstrong\u003e80\u003c/strong\u003e(4):988-996.\u003c/li\u003e\n\u003cli\u003eChen J, You R, Lv Y, Liu H, Yang G: \u003cstrong\u003eConjugated linoleic acid regulates adipocyte fatty acid binding protein expression via peroxisome proliferator-activated receptor alpha signaling pathway and increases intramuscular fat content\u003c/strong\u003e. \u003cem\u003eFront Nutr \u003c/em\u003e2022, \u003cstrong\u003e9\u003c/strong\u003e:1029864.\u003c/li\u003e\n\u003cli\u003eWitte AV, Kerti L, Hermannstadter HM, Fiebach JB, Schreiber SJ, Schuchardt JP, Hahn A, Floel A: \u003cstrong\u003eLong-chain omega-3 fatty acids improve brain function and structure in older adults\u003c/strong\u003e. \u003cem\u003eCereb Cortex \u003c/em\u003e2014, \u003cstrong\u003e24\u003c/strong\u003e(11):3059-3068.\u003c/li\u003e\n\u003cli\u003eFu B, Zheng M, Yang H, Zhang J, Li Y, Wang G, Tian J, Zhang K, Xia Y, Li Z\u003cem\u003e et al\u003c/em\u003e: \u003cstrong\u003eThe effect of broad bean diet on structure, flavor and taste of fresh grass carp: A comprehensive study using E-nose, E-tongue, TPA, HS-SPME-GC-MS and LC-MS\u003c/strong\u003e. \u003cem\u003eFood Chem \u003c/em\u003e2024, \u003cstrong\u003e436\u003c/strong\u003e:137690.\u003c/li\u003e\n\u003cli\u003eJiang Y, Xie M, Tang J, Zhou Z, Zhang Y, Chen G, Hou S: \u003cstrong\u003eEffects of genetic selection and threonine on meat quality in Pekin ducks\u003c/strong\u003e. \u003cem\u003ePoult Sci \u003c/em\u003e2020, \u003cstrong\u003e99\u003c/strong\u003e(5):2508-2518.\u003c/li\u003e\n\u003cli\u003eDou L, Sun L, Liu C, Su L, Chen X, Yang Z, Hu G, Zhang M, Zhao L, Jin Y: \u003cstrong\u003eEffect of dietary arginine supplementation on protein synthesis, meat quality and flavor in growing lambs\u003c/strong\u003e. \u003cem\u003eMeat Sci \u003c/em\u003e2023, \u003cstrong\u003e204\u003c/strong\u003e:109291.\u003c/li\u003e\n\u003cli\u003eDankel SN, Fadnes DJ, Stavrum AK, Stansberg C, Holdhus R, Hoang T, Veum VL, Christensen BJ, V\u0026aring;ge V, Sagen JV\u003cem\u003e et al\u003c/em\u003e: \u003cstrong\u003eSwitch from stress response to homeobox transcription factors in adipose tissue after profound fat loss\u003c/strong\u003e. \u003cem\u003ePLoS One \u003c/em\u003e2010, \u003cstrong\u003e5\u003c/strong\u003e(6):e11033.\u003c/li\u003e\n\u003cli\u003eCowherd RM, Lyle RE, Miller CP, McGehee RE, Jr.: \u003cstrong\u003eDevelopmental profile of homeobox gene expression during 3T3-L1 adipogenesis\u003c/strong\u003e. \u003cem\u003eBiochem Biophys Res Commun \u003c/em\u003e1997, \u003cstrong\u003e237\u003c/strong\u003e(2):470-475.\u003c/li\u003e\n\u003cli\u003eLee SH, Hossner KL: \u003cstrong\u003eCoordinate regulation of ovine adipose tissue gene expression by propionate\u003c/strong\u003e. \u003cem\u003eJ Anim Sci \u003c/em\u003e2002, \u003cstrong\u003e80\u003c/strong\u003e(11):2840-2849.\u003c/li\u003e\n\u003cli\u003eHong YH, Nishimura Y, Hishikawa D, Tsuzuki H, Miyahara H, Gotoh C, Choi KC, Feng DD, Chen C, Lee HG\u003cem\u003e et al\u003c/em\u003e: \u003cstrong\u003eAcetate and propionate short chain fatty acids stimulate adipogenesis via GPCR43\u003c/strong\u003e. \u003cem\u003eEndocrinology \u003c/em\u003e2005, \u003cstrong\u003e146\u003c/strong\u003e(12):5092-5099.\u003c/li\u003e\n\u003cli\u003eLi Q, Tan JX, He Y, Bai F, Li SW, Hou YW, Ji LS, Gao YT, Zhang X, Zhou ZH\u003cem\u003e et al\u003c/em\u003e: \u003cstrong\u003eAtractylenolide III ameliorates Non-Alcoholic Fatty Liver Disease by activating Hepatic Adiponectin Receptor 1-Mediated AMPK Pathway\u003c/strong\u003e. \u003cem\u003eInt J Biol Sci \u003c/em\u003e2022, \u003cstrong\u003e18\u003c/strong\u003e(4):1594-1611.\u003c/li\u003e\n\u003cli\u003eZ\u0026uacute;\u0026ntilde;iga LA, Shen WJ, Joyce-Shaikh B, Pyatnova EA, Richards AG, Thom C, Andrade SM, Cua DJ, Kraemer FB, Butcher EC: \u003cstrong\u003eIL-17 regulates adipogenesis, glucose homeostasis, and obesity\u003c/strong\u003e. \u003cem\u003eJ Immunol \u003c/em\u003e2010, \u003cstrong\u003e185\u003c/strong\u003e(11):6947-6959.\u003c/li\u003e\n\u003cli\u003eBoz MA, Oz F, Yamak US, Sarica M, Cilavdaroglu E: \u003cstrong\u003eThe carcass traits, carcass nutrient composition, amino acid, fatty acid, and cholesterol contents of local Turkish goose varieties reared in an extensive production system\u003c/strong\u003e. \u003cem\u003ePoult Sci \u003c/em\u003e2019, \u003cstrong\u003e98\u003c/strong\u003e(7):3067-3080.\u003c/li\u003e\n\u003cli\u003eBiesek J, Kuźniacka J, Banaszak M, Adamski M: \u003cstrong\u003eThe Quality of Carcass and Meat from Geese Fed Diets with or without Soybean Meal\u003c/strong\u003e. \u003cem\u003eAnimals (Basel) \u003c/em\u003e2020, \u003cstrong\u003e10\u003c/strong\u003e(2).\u003c/li\u003e\n\u003cli\u003eVernon RG, Flint DJ: \u003cstrong\u003eLipid metabolism in farm animals\u003c/strong\u003e. \u003cem\u003eProc Nutr Soc \u003c/em\u003e1988, \u003cstrong\u003e47\u003c/strong\u003e(3):287-293.\u003c/li\u003e\n\u003cli\u003eHe W, Gao M, Yang R, Zhao Z, Mi J, Sun H, Xiao H, Fang X: \u003cstrong\u003eThe effect of CPT1B gene on lipid metabolism and its polymorphism analysis in Chinese Simmental cattle\u003c/strong\u003e. \u003cem\u003eAnim Biotechnol \u003c/em\u003e2022, \u003cstrong\u003e33\u003c/strong\u003e(7):1428-1440.\u003c/li\u003e\n\u003cli\u003eXu WD, Yang XY, Li DH, Zheng KD, Qiu PC, Zhang W, Li CY, Lei KF, Yan GQ, Jin SW\u003cem\u003e et al\u003c/em\u003e: \u003cstrong\u003eUp-regulation of fatty acid oxidation in the ligament as a contributing factor of ankylosing spondylitis: A comparative proteomic study\u003c/strong\u003e. \u003cem\u003eJ Proteomics \u003c/em\u003e2015, \u003cstrong\u003e113\u003c/strong\u003e:57-72.\u003c/li\u003e\n\u003cli\u003eMiltiadou D, Hager-Theodorides AL, Symeou S, Constantinou C, Psifidi A, Banos G, Tzamaloukas O: \u003cstrong\u003eVariants in the 3\u0026apos; untranslated region of the ovine acetyl-coenzyme A acyltransferase 2 gene are associated with dairy traits and exhibit differential allelic expression\u003c/strong\u003e. \u003cem\u003eJ Dairy Sci \u003c/em\u003e2017, \u003cstrong\u003e100\u003c/strong\u003e(8):6285-6297.\u003c/li\u003e\n\u003cli\u003eMa X, Wei D, Cheng G, Li S, Wang L, Wang Y, Wang X, Zhang S, Wang H, Zan L: \u003cstrong\u003eBta-miR-130a/b regulates preadipocyte differentiation by targeting PPARG and CYP2U1 in beef cattle\u003c/strong\u003e. \u003cem\u003eMol Cell Probes \u003c/em\u003e2018, \u003cstrong\u003e42\u003c/strong\u003e:10-17.\u003c/li\u003e\n\u003cli\u003eGelman L, Fruchart JC, Auwerx J: \u003cstrong\u003eAn update on the mechanisms of action of the peroxisome proliferator-activated receptors (PPARs) and their roles in inflammation and cancer\u003c/strong\u003e. \u003cem\u003eCell Mol Life Sci \u003c/em\u003e1999, \u003cstrong\u003e55\u003c/strong\u003e(6-7):932-943.\u003c/li\u003e\n\u003cli\u003eYamamoto S, Kato S, Senoo N, Miyoshi N, Morita A, Miura S: \u003cstrong\u003eDifferences in phosphatidylcholine profiles and identification of characteristic phosphatidylcholine molecules in meat animal species and meat cut locations\u003c/strong\u003e. \u003cem\u003eBiosci Biotechnol Biochem \u003c/em\u003e2021, \u003cstrong\u003e85\u003c/strong\u003e(5):1205-1214.\u003c/li\u003e\n\u003cli\u003eLi W, LiLi, Wang X: \u003cstrong\u003eTranscriptomic analysis of different intramuscular fat contents on the flavor of the longissimus dorsi tissues from Guangling donkey\u003c/strong\u003e. \u003cem\u003eGenomics \u003c/em\u003e2024, \u003cstrong\u003e116\u003c/strong\u003e(5):110905.\u003c/li\u003e\n\u003cli\u003eZhang Y, Wang Y, Wang X, Ji Y, Cheng S, Wang M, Zhang C, Yu X, Zhao R, Zhang W\u003cem\u003e et al\u003c/em\u003e: \u003cstrong\u003eAcetyl-coenzyme A acyltransferase 2 promote the differentiation of sheep precursor adipocytes into adipocytes\u003c/strong\u003e. \u003cem\u003eJ Cell Biochem \u003c/em\u003e2019, \u003cstrong\u003e120\u003c/strong\u003e(5):8021-8031.\u003c/li\u003e\n\u003cli\u003eHan F, Zhou L, Zhao L, Wang L, Liu L, Li H, Qiu J, He J, Liu N: \u003cstrong\u003eIdentification of miRNA in Sheep Intramuscular Fat and the Role of miR-193a-5p in Proliferation and Differentiation of 3T3-L1\u003c/strong\u003e. \u003cem\u003eFront Genet \u003c/em\u003e2021, \u003cstrong\u003e12\u003c/strong\u003e:633295.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-genomics","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"gics","sideBox":"Learn more about [BMC Genomics](http://bmcgenomics.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/gics","title":"BMC Genomics","twitterHandle":"#BMCGenomics","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"pigs, flavor, flavoromics, transcriptomics, lipidomics, ACAA2","lastPublishedDoi":"10.21203/rs.3.rs-7304887/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7304887/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e\u003cp\u003eFlavor is an important factor influencing consumers' evaluation of pork. However, the molecular regulatory mechanism of flavor differences among different pig breeds remains unclear. In this study, using flavoromics, transcriptomics and lipidomics techniques, the key genes and substances in the longissimus dorsi muscle of Queshan Black Pig (QS) and Yunong Black Pig (YN) were identified and analyzed.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e\u003cp\u003eBetween the two breeds, 37 differential volatile organic compounds (VOCs), 2,559 differentially expressed genes (DEGs) and 460 differential lipids (DELs) were identified. Flavoromics identified phenol, pyridine and 1-hexanol as potential flavor biomarkers. Transcriptomics indicated that DEGs were mainly enriched in pathways such as fatty acid degradation and AMPK signaling pathway. Moreover, 10 lipids, including PC (26:3) and PE (34:6e), emerged as potential biomarkers. Multi-omics analysis further identified 14 VOCs, 15 DEGs and 10 DELs as being associated with pork flavor. These may regulate lipid production and lipolysis by participating in fatty acid (FA) biosynthesis, FA oxidation and glycerophospholipid metabolism. Finally, this study found that \u003cem\u003eACAA2\u003c/em\u003e promoted the lipid deposition of porcine intramuscular preadipocytes and 3T3-L1 cells.\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e\u003cp\u003eThese results provide important insights into the flavor differences between QS and YN pork and the underlying molecular regulatory mechanisms. They also offer theoretical references for improving the quality of pork.\u003c/p\u003e","manuscriptTitle":"Multi-Omics Analysis Reveals Flavor Differences Between Queshan And Yunong Black Pigs","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-09-04 18:38:46","doi":"10.21203/rs.3.rs-7304887/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-09-08T08:39:12+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-09-03T04:37:18+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-08-28T08:13:46+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"91034531548191358316077133660406142344","date":"2025-08-28T06:53:34+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"165424248879752019041953591452117250595","date":"2025-08-28T03:11:31+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-08-28T02:05:03+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-08-27T07:35:39+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2025-08-26T06:57:42+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-08-25T14:28:12+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Genomics","date":"2025-08-25T14:20:42+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-genomics","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"gics","sideBox":"Learn more about [BMC Genomics](http://bmcgenomics.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/gics","title":"BMC Genomics","twitterHandle":"#BMCGenomics","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"ef980e49-c940-4ebe-98b2-37bf896977a7","owner":[],"postedDate":"September 4th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2025-11-17T16:05:15+00:00","versionOfRecord":{"articleIdentity":"rs-7304887","link":"https://doi.org/10.1186/s12864-025-12178-5","journal":{"identity":"bmc-genomics","isVorOnly":false,"title":"BMC Genomics"},"publishedOn":"2025-11-10 15:57:46","publishedOnDateReadable":"November 10th, 2025"},"versionCreatedAt":"2025-09-04 18:38:46","video":"","vorDoi":"10.1186/s12864-025-12178-5","vorDoiUrl":"https://doi.org/10.1186/s12864-025-12178-5","workflowStages":[]},"version":"v1","identity":"rs-7304887","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7304887","identity":"rs-7304887","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}