Anti-injury Mechanisms in the Liver and its Molecular Regulatory Networks of the Hezuo Pig under Cold Stress

Anti-injury Mechanisms in the Liver and its Molecular Regulatory Networks of the Hezuo Pig under Cold Stress | 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 Anti-injury Mechanisms in the Liver and its Molecular Regulatory Networks of the Hezuo Pig under Cold Stress Jihong Yan, Yuran Tang, Shuangbao Gun, Pengfei Wang This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7481559/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background Cold stress is a critical environmental factor that adversely affects the production performance and health status of livestock and poultry. To explore the physiological adaptation mechanisms underlying cold resistance differences among pig breeds, this study employed cold-resistant Hezuo pigs and cold-sensitive Bama pigs as models, systematically comparing liver injury phenotypes and molecular response characteristics after 5, 10, 15, and 20 days of cold exposure at -15°C. Results The results demonstrated that: 1) After 20 days of cold stress, serum liver function markers (ALT, AST, LDH) in Bama pigs were significantly elevated ( P < 0.05), while remaining stable in Tibetan pigs. 2) Histological analysis revealed that the α-SMA-positive area in Bama pig livers increased significantly with prolonged cold exposure ( P < 0.05), exceeding that of Tibetan pigs from day 15 onward. 3) Morphological observations showed that Bama pigs developed ear frostbite and liver surface congestion after 15 days of cold stress, whereas Tibetan pigs maintained normal appearances. 4) Ultrastructural analysis indicated mitochondrial swelling and nuclear membrane abnormalities in Bama pig hepatocytes, while Tibetan pigs exhibited relatively normal cellular structures. 5) High-throughput sequencing identified 1,307 differentially expressed mRNAs (DEmRNAs), 320 DElncRNAs, 1,299 DEcircRNAs, and 162 DEmiRNAs in liver tissues between the two breeds under cold stress. Functional enrichment analysis revealed that in Bama pigs, DEmRNAs were primarily involved in metabolic processes, oxidative stress, and liver fibrosis-related pathways, whereas in Tibetan pigs they were enriched in metabolic and antioxidant-related biological processes. RT-qPCR validation confirmed the accuracy and reliability of the sequencing results. Finally, we constructed ceRNA regulatory networks to illustrate their potential roles in the anti-damage mechanisms of Tibetan pig livers. Conclusions Collectively, Bama pigs exhibited greater sensitivity to cold stress with more severe liver damage, while Tibetan pigs demonstrated superior cold tolerance. Three key ceRNA networks were identified as potentially crucial in the cold resistance mechanisms of Tibetan pigs: (circ_023716/008930/007918)—ssc-miR-29b—CYP2A19; circ_000082—ssc-miR-204—(P2RY13/ADORA2B); and MSTRG.7463.1—ssc-miR-204—P2RY13. This study systematically elucidates the phenotypic characteristics and molecular basis of cold adaptation in Tibetan pigs, providing not only novel insights into animal environmental adaptation evolution but also important theoretical foundations and candidate molecular targets for livestock stress-resistant breeding. Hezuo pig Bama pig Cold stress RNA-Seq Liver injury Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 1 Background Cold stress is a significant environmental factor that substantially impacts the health and production performance of livestock and poultry [ 1 – 3 ]. In livestock production, cold environments not only diminish the growth rate of animals [ 4 – 6 ], but also lead to a significant increase in pig mortality rates [ 7 – 9 ] and the incidence of diarrhea [ 10 , 11 ]. Furthermore, such conditions adversely affect meat quality [ 12 , 13 ], resulting in substantial economic losses. Therefore, effectively mitigating the impact of cold stress on livestock and poultry production is a critical scientific issue to be addressed in the field of animal husbandry. The Hezuo pig, a branch of the Tibetan pig, is a unique local breed endemic to Gansu Province. It is primarily distributed in the Gannan Tibetan Autonomous Prefecture, located on the northeastern edge of the Qinghai-Tibet Plateau at an average altitude of approximately 3,000 meters. Through long-term natural selection, the Hezuo pig has developed robust cold-resistant traits [ 14 – 16 ]. The Hezuo pig, characterized by exceptional environmental resilience, cost-efficient husbandry, and consistent market viability, now functions as both a critical livelihood asset for pastoral communities and a catalyst for China's rural revitalization agenda [ 17 , 18 ]. In recent years, research has increasingly focused on the mechanisms by which cold stress impairs organ function in pigs. As a primary thermogenic response, pigs utilize muscle shivering to generate heat [ 19 , 20 ]. Transcriptomic analyses have revealed that cold exposure induces differential gene expression in porcine skeletal muscle, including alterations in lncRNAs and their target genes, which significantly enrich pathways related to ion transport, amino acid metabolism, and carbohydrate metabolism [ 21 – 23 ]. At the cellular level, PRSS8 in skeletal muscle satellite cells has been shown to regulate ERK phosphorylation, thereby influencing energy metabolism and thermogenesis during cold stress [ 1 ]. Beyond skeletal muscle, cold stress exerts systemic effects on metabolic tissues. In adipose tissue, it promotes beige fat generation and enhances thermogenic capacity [ 24 ]. The gastrointestinal system also responds to cold exposure [ 25 , 26 ], with studies demonstrating intestinal mucosal damage and reduced antibiotic resistance gene abundance in the cecum and feces of cold-stressed pigs [ 27 , 28 ]. Concurrently, cold stress triggers pulmonary inflammation [ 29 ] and increases susceptibility to cardiac injury and energy imbalance [ 30 ]. The liver, as a central metabolic organ and key site of non-shivering thermogenesis (NST), undergoes profound changes under cold conditions. Chronic cold exposure disrupts GLP-1R signaling, inducing oxidative stress while promoting inflammation, endoplasmic reticulum stress, and apoptosis in both hepatic and pancreatic tissues [ 31 ]. Acute cold stress, meanwhile, activates the O-GlcNAc/Akt pathway to modulate hepatic glucose metabolism and mitigate apoptosis in cold-exposed piglets [ 32 ]. High-throughput sequencing technology has played a pivotal role in studying gene expression regulatory networks in complex biological processes. By integrating mRNA, lncRNA, circRNA, and miRNA expression profiles, the competing endogenous RNA (ceRNA) regulatory network has been elucidated in specific physiological or pathological contexts. The ceRNA network regulates target gene expression by competitively binding miRNAs, playing a critical role in cellular metabolism, stress responses, and tissue damage repair [ 33 – 37 ]. To date, little is known about the regulatory function of ceRNA networks in cold stress-mediated liver damage. Therefore, this study focuses on Hezuo pigs and Bama pigs as experimental subjects, comparing their liver function, histopathological changes, glucose metabolism levels, and liver injury under cold stress. Through whole transcriptome sequencing analysis, this study will characterize the ceRNA network involved in cold stress resistance in the liver of Hezuo pigs. The investigation will elucidate the molecular mechanisms underlying hepatic homeostasis maintenance during cold stress in this breed, which may contribute to improved strategies for cold-resistant livestock breeding and hepatic protection. 2 Materials and methods 2.1 Ethics statement This study was approved by the Animal Ethics Committee of the College of Animal Science and Technology, Gansu Agricultural University (Approval No. 2006 − 398). All animal experiments were performed in strict compliance with the institutional ethical guidelines for humane treatment of research animals. Euthanasia procedures were conducted following established protocols to minimize animal distress. 2.2 Experimental animals A total of 30 healthy 75-day-old pigs, comprising 15 Bama (BM) and 15 Hezuo (HZ) pigs, were randomly allocated into five experimental groups: a control group (C, 23 ± 2°C) and four cold stress groups (5 d, 10 d, 15 d, and 20 d, -15 ± 2°C). Each group contained three pigs per breed. Following a 7-day acclimation period under ambient conditions, the pigs were subjected to their respective treatments. At designated time points, the animals were humanely euthanized. Blood samples were collected in coagulation-promoting tubes for serum separation. Liver tissues were harvested and preserved under different conditions: snap-frozen at -80°C for RNA extraction, fixed in 4% paraformaldehyde for histological analyses (HE, PAS, and immunohistochemistry), and stored in 3% glutaraldehyde for transmission electron microscopy (TEM). 2.3 Immunohistochemistry of the α-SMA Protein Liver tissue samples were fixed overnight in 4% paraformaldehyde, dehydrated in ethanol, embedded in paraffin, and sectioned. After dewaxing and rehydration, the sections were washed three times with distilled water. Antigen retrieval was performed, followed by the elimination of endogenous peroxidase activity using 3% H 2 O 2 . The sections were blocked with 3% Bovine Serum Albumin (BSA) at room temperature for 30 minutes and then incubated with rabbit anti-α-SMA polyclonal antibody (1:3000, Proteintech, Wuhan, China) at 4°C overnight. HRP-labeled goat anti-rabbit IgG (1:200, Servicebio, Wuhan, China) was added for incubation in the next day. Positive signals (brown) were visualized using a diaminobenzidine (DAB) kit (Servicebio). Subsequently, the nuclei were counterstained, and the sections were dehydrated, mounted, and observed under a microscope. 2.4 Serum biochemical parameter analysis The corresponding parameters were set on a Fully Automated Biochemical Analyzer (Shenzhen Rayto Life Science, Shenzhen, China) to detect Alanine Aminotransferase (ALT), Aspartate Aminotransferase (AST), Alkaline Phosphatase (ALP), Lactate Dehydrogenase (LDH), and blood glucose (GLU). Blood samples from all experimental pigs were collected from the anterior vena cava. Whole blood samples were left at room temperature for 2 hours and then centrifuged at 3000 rpm for 15 minutes at 4°C. The supernatant was collected for analysis using the analyzer. 2.5 Pig Ear Frostbite and Liver Morphological Characteristics The frostbite conditions in the ears, as well as the anatomical and microscopic characteristics of the liver, were observed and analyzed in both pig breeds. Paraffin-embedded liver tissue sections were subjected to conventional HE and PAS staining following the methods described in references [ 38 , 39 ], and histopathological changes were observed under a microscope. Glycogen accumulation was detected using a glycogen assay kit (Solarbio, Beijing, China). The liver tissue samples pre-fixed with 3% glutaraldehyde were further fixed with 1% osmium tetroxide. Subsequently, the samples were dehydrated using a graded acetone series. After infiltration and embedding, the tissues were sectioned into ultrathin slices of approximately 70 nm. The sections were stained at room temperature and then observed under a TEM to examine the morphology of the nuclei and mitochondria. 2.6 RNA Extraction, Library Construction and Sequencing Total RNA was extracted from the liver tissues of all pigs using TRIzol (Life Technologies, CA, USA) according to the manufacturer's instructions. The quality and concentration of all RNA samples were assessed using an Agilent 2100 Bioanalyzer (Agilent Technologies, CA, USA) and 1% agarose gel electrophoresis. RNA samples with an RNA Integrity Number (RIN) ≥ 7.0 were used for RNA-seq and miRNA-seq. For RNA-seq, the ribosomal RNA (rRNA) was depleted using an rRNA removal kit (Epicentre, CA, USA), followed by reverse transcription of the remaining RNA into complementary DNA (cDNA) using random primers. The second strand of cDNA was synthesized using DNA polymerase I, RNase H, dNTPs, and buffer. Subsequently, the cDNA fragments were purified, end-repaired, poly(A)-tailed, and ligated to Illumina sequencing adapters. The second strand cDNA was then degraded using Uracil-N-Glycosylase (UNG). The digested products were size-selected by agarose gel electrophoresis, PCR-amplified, and then used for library construction. The resulting library was sequenced on the Illumina HiSeqTM 4000 platform. For miRNA-seq, RNA molecules in the 18–30 nt range were enriched using polyacrylamide gel electrophoresis (PAGE). The 3' and 5' adapters were ligated to the RNA molecules, followed by reverse transcription and PCR amplification of the ligated products. Finally, bands of approximately 140 bp were recovered and purified using PAGE, dissolved in EB solution, and used for library construction and sequencing. Both RNA-seq and miRNA-seq were performed by Gene Denovo Biotechnology Co., Ltd. (Guangzhou, China). 2.7 Data quality control and genome alignment Raw data were further filtered using FASTP [ 40 ]. Reads containing adapters, reads with more than 10% unknown nucleotides (N), and low-quality reads with over 50% of bases having a quality score (Q) ≤ 20 were removed. Clean reads were aligned to the ribosomal RNA (rRNA) database using Bowtie2 [ 41 ], and reads mapped to rRNA were subsequently removed. The remaining reads were aligned to the pig reference genome using HISAT2 [ 42 ] for paired-end reads. 2.8 Identification of mRNA, lncRNA, circRNA and miRNA Transcripts were assembled using StringTie [ 43 , 44 ], and genes identified in the sequencing data that were not annotated in the reference genome were defined as novel genes. The reconstructed transcripts were compared with known transcripts in the reference genome using Cuffcompare[ 45 ] to filter out known mRNAs. Due to the complexity of lncRNA origins and the significant differences in lncRNAs derived from different transcripts of the same gene, lncRNAs were analyzed based on transcripts. The identification process involved retaining transcripts with a length ≥ 200 bp and exon numbers ≥ 2 based on StringTie-reconstructed transcripts. The coding potential of these novel transcripts was predicted using CPC2 [ 46 ] and CNCI [ 47 ], and the intersection of transcripts without coding potential was considered a reliable prediction result. circRNAs were identified using CIRIquant [ 48 ]. For miRNAs, raw sequencing data underwent quality assessment and filtering, followed by alignment with small RNAs in the GenBank and Rfam databases to identify and remove rRNA, scRNA, snoRNA, snRNA, and tRNA. The data were then aligned to the pig reference genome. Clean tags were searched against the miRBase database to identify existing miRNAs. For miRNA sequences not yet included in miRBase, alignment with miRNAs from other species was performed to identify known miRNAs. Finally, novel miRNAs were identified based on genomic locations and hairpin structures predicted by the miRDeep2 [ 49 ]. 2.9 Differentially Expressed RNA Screening and Functional Annotation Quantitative analysis of the identified ncRNAs and mRNAs was performed using FPKM, RPM, and TPM as normalization methods to quantify the expression abundance of mRNAs, lncRNAs, circRNAs, and miRNAs. The DESeq2 [ 50 ] software was used to identify differentially expressed mRNAs (DEmRNAs) based on FDR 2. Differentially expressed lncRNAs and circRNAs (DElncRNAs/DEcircRNAs) were screened with P 2, while differentially expressed miRNAs (DEmiRNAs) were screened with P 1.5. GO terms and KEGG [ 51 ] pathway enrichment analysis were then employed to further investigate the functions of DEmRNAs. GO terms and KEGG pathways with P < 0.05 were considered significantly enriched. 2.10 Construction and Analysis of ceRNAs Regulatory Network To reveal the roles and interactions of DEmRNAs, DElncRNAs, DEcircRNAs, and DEmiRNAs, two ceRNA networks were constructed based on the ceRNA theory: the lncRNA-miRNA-mRNA network and the circRNA-miRNA-mRNA network. By calculating the Pearson correlation coefficients for the expression levels of the obtained ceRNA pairs, selecting ceRNA pairs with correlation coefficients above 0.7 as potential ceRNA pairs. Based on these results, a hypergeometric distribution test was further applied a hypergeometric distribution test to screen ceRNA pairs with P < 0.05 as the final ceRNA pairs. GO terms and KEGG pathway functional and enrichment analyses were subsequently performed on the two ceRNA networks, with GO terms and KEGG pathways with P < 0.05 considered significantly enriched in DEGs. ceRNAs related to liver injury resistance in Hezuo pigs were selected from these networks. Finally, the interaction networks were visualized using Cytoscape. 2.11 RT-qPCR Validation To validate the accuracy and reliability of the sequencing results, six DEmRNAs, three DElncRNAs, three DEcircRNAs, and three DEmiRNAs were randomly selected, and their expression levels were detected using RT-qPCR. The reactions were performed according to the instructions of the SYBR® Green Pro Taq HS Premix qPCR Kit (Accurate Biotechnology, Hunan, China). The reaction procedure consisted of an initial step at 95°C for 30 s, followed by 40 cycles of 95°C for 5 s and 60°C for 30 s, and a final step at 95°C for 1 min, 60°C for 30 s, and 95°C for 30 s. The relative expression of mRNAs, lncRNAs, circRNAs, and miRNAs was quantified using the2 −ΔΔCt [52] method, normalized to the housekeeping genes GAPDH or U6 . All results are presented as mean ± SD. The primers were designed using Premier 5.0 software and synthesized by GENEWIZ (Suzhou, China). The primer sequences are listed in Table S1 . 3 Results 3.1 Analysis of Liver Injury Severity Bama pigs were more sensitive to cold stress, as evidenced by significant increases in liver function indicators (ALT, AST, LDH) after 20 days of cold exposure ( P < 0.05), whereas Hezuo pigs exhibited stronger tolerance (Fig. 1 A). Immunohistochemical analysis of liver α-SMA revealed that the positive area of α-SMA increased significantly with prolonged cold exposure, and the activation level of HSCs in Bama pigs was significantly higher than that in Hezuo pigs at 15 d and 20 d ( P < 0.05) (Fig. 1 B-C). After 15 days of cold stress, Bama pigs exhibited ear tissue cracking and scabbing, rough and congested liver surfaces (Fig. 2 A), irregular nuclear membranes, and swollen mitochondria in hepatocytes (Fig. 2 B-C). In contrast, Hezuo pigs showed no frostbite in ear tissues and maintained relatively normal liver cell structures with milder liver injury. Additionally, PAS staining and quantification of liver glycogen revealed that Hezuo pigs had significantly higher glycogen reserves than Bama pigs (P < 0.05). Following cold stress, both pig breeds showed significant decreases in blood glucose and liver glycogen levels (P < 0.05) (Fig. 2 D-F). 3.2 Overview of Whole Transcriptome Sequencing Data To ensure data quality, raw reads were filtered prior to bioinformatics analysis. Clean data from all samples ranged from 99.64–99.77%, with average Q20, Q30, and GC content values of 96.52%, 90.79%, and 54.23%, respectively. The majority of reads mapped to the pig reference genome (78.22% ~ 83.25%), confirming high sequencing reliability for the 12 samples (Table S2-4). For miRNA-seq, after filtering low-quality reads, the BC, HC, BT, and HT groups yielded 27.1 ~ 33.4 million clean tags (Table S5). Mapping rates to the pig genome ranged from 75.77–80.89%. Non-coding RNAs were annotated by comparison with GenBank and Rfam, with rRNA, tRNA, snRNA, snoRNA, and repetitive sequences removed (Table S6). Most clean reads were classified as miRNAs, demonstrating successful sequencing. 3.3 Identification of DEmRNAs, DElncRNAs, DEcircRNAs and DEmiRNAs In this study, a total of 1,307 differentially expressed mRNAs (DEmRNAs), 320 differentially expressed lncRNAs (DElncRNAs), 1,299 differentially expressed circRNAs (DEcircRNAs), and 162 differentially expressed miRNAs (DEmiRNAs) were identified (Fig. 3 A-D). Among the comparison groups BC-vs-BT, BC-vs-HC, HC-vs-HT, and BT-vs-HT, there were 317, 581, 258, and 511 DEmRNAs; 102, 143, 92, and 138 DElncRNAs; 399, 521, 275, and 447 DEcircRNAs; and 47, 86, 41, and 71 DEmiRNAs, respectively (Fig. 3 E-H). 3.4 GO terms and KEGG pathways Analysis GO terms enrichment analysis revealed that the BC-vs-BT group was significantly enriched in terms related to metabolic disorders, oxidative stress, and liver fibrosis, such as "alpha-amino acid metabolic process" and "extracellular matrix structural constituent"(Fig. 4 A). The BC-vs-HC group was significantly enriched in terms such as "immune system process" and "cell killing"(Fig. 4 B). Both the HC-vs-HT (Fig. 4 C) and BT-vs-HT (Fig. 4 D) groups were significantly enriched in functions related to metabolic adaptation and antioxidant defense, such as "lipid biosynthetic process" and "oxidoreductase activity". KEGG pathway enrichment analysis showed that the BC-vs-BT group was significantly enriched in pathways related to amino acid metabolism (e.g., "arginine biosynthesis"), glutathione metabolism, and ECM-receptor interaction (Fig. 5 A). The BC-vs-HC group was mainly enriched in immune-related pathways (e.g., "T cell receptor signaling pathway" and "natural killer cell-mediated cytotoxicity") (Fig. 5 B). The HC-vs-HT group was significantly enriched in pathways such as peroxisome, PPAR signaling pathway, and retinol metabolism (Fig. 5 C). The BT-vs-HT group was significantly enriched in immune-related pathways (e.g., "primary immunodeficiency") and lipid metabolism pathways (Fig. 5 D). 3.5 Screening of ceRNA Related to Anti-Damage in Hezuo Pig To investigate the molecular mechanisms conferring liver injury resistance in Hezuo pigs, we constructed two ceRNA regulatory networks: (1) a lncRNA-miRNA-mRNA network (38 lncRNAs, 37 miRNAs, 240 mRNAs; 530 interactions) and (2) a circRNA-miRNA-mRNA network (148 circRNAs, 61 miRNAs, 354 mRNAs; 2,193 interactions). GO and KEGG analyses demonstrated significant enrichment of these networks in cold stress-associated pathways. Immune-related pathways included "immune system process" and "T cell receptor signaling pathway". Signaling-related pathways included "NF-κB signaling pathway" and "Rap1 signaling pathway". Metabolic-related pathways included "nitrogen metabolism" and "fatty acid metabolism". Additionally, pathways such as "biological regulation" and "cellular process" were also involved. Following stringent filtration (mRNAs with expression < 1.0), network analysis revealed miRNAs as central hubs. Topological assessment identified ssc-miR-10382, ssc-miR-204, and ssc-miR-29b as highest-degree nodes, followed by ssc-miR-1388 and ssc-miR-9843-3p. Expression profiling confirmed these miRNAs were among the most abundant, suggesting key regulatory roles. Their target mRNAs ( CYP2A19 , CA3 , P2RY13 , ADORA2B ) may collectively modulate immune responses, signaling cascades, and metabolic adaptation during cold stress. Notably, three circRNAs (circ_023716, circ_008930, circ_007918) showed co-targeting of ssc-miR-29b and CYP2A19 , while circ_000082 interacted with ssc-miR-204 and its targets ( P2RY13 , ADORA2B ). Only one prominent lncRNA-mediated axis was detected: MSTRG.7463.1–ssc-miR-204– P2RY13 . These findings elucidate potential molecular determinants of cold tolerance in Hezuo pigs. 3.6 Validation of RNA-Seq Data by RT-qPCR To validate the accuracy and reliability of the sequencing results, six DEmRNAs ( NAGS , PIK3C2G , DDX58 , CYP2A19 , MBL1 and BBOX1 ), three DElncRNAs (MSTRG.7463.1, MSTRG.15052.4 and MSTRG.6794.1), three DEcircRNAs (circ_023716, circ_000082 and circ_008930), and three DEmiRNAs (ssc-miR-29b, ssc-miR-9843-3p and ssc-miR-129b) were randomly selected, and their expression levels were detected using RT-qPCR. As shown in the figure, comparison with the sequencing data revealed consistent expression trends, indicating that the sequencing results are accurate and reliable. 4 Discussion Cold stress is one of the critical environmental factors affecting the health and production performance of livestock and poultry [ 53 ]. Under low-temperature conditions, livestock and poultry need to increase energy metabolism and adjust physiological functions to maintain body temperature[ 26 , 54 , 55 ]. This study compared serum liver function indicators, liver histopathological characteristics, and glucose metabolism changes in Hezuo pigs (HZ) and Bama pigs (BM) under normal and cold stress conditions at different treatment durations, revealing the physiological adaptation mechanisms and differences between the two pig breeds under cold stress. The study found that cold stress induces increased hepatic oxidative stress and inflammatory responses, leading to the accumulation of reactive oxygen species (ROS), which subsequently causes liver damage [ 56 , 57 ]. Serum ALT and AST are commonly used biomarkers for liver health [ 58 – 60 ]. In this study, with prolonged cold stress, the concentrations of ALT, AST, and LDH in Bama pigs significantly increased, peaking at 20 days, which may be related to cold stress-induced oxidative stress and inflammatory responses, indicating more severe hepatocyte damage in Bama pigs under long-term cold stress. In contrast, the transaminase levels in Hezuo pigs remained relatively stable, and the ALP concentration significantly decreased at 20 days, which may be attributed to Hezuo pigs' unique low-temperature metabolic regulation and cellular protection mechanisms. Liu et al. [ 61 ] found that cold stress promoted hepatocyte apoptosis in juvenile fish, leading to increased serum ALT and AST levels, which is consistent with our findings. α-SMA (α-smooth muscle actin) is a protein expressed in various cell types, particularly in activated hepatic stellate cells (HSCs). When the liver is injured, HSCs are activated and transform into myofibroblast-like cells, leading to a significant increase in α-SMA expression [ 62 ]. In this study, with prolonged cold stress, the expression of α-SMA protein in the livers of both pig breeds significantly increased. At 15 days, the positive area of α-SMA protein expression in Bama pigs was significantly higher than in Hezuo pigs, indicating a higher degree of HSC activation and greater risk of liver fibrosis in Bama pigs. In contrast, Hezuo pigs exhibited lower α-SMA protein expression. The above results suggest that during the initial phase of cold stress, animals may undergo an adaptation period, during which the body attempts to cope with the low-temperature environment through various physiological mechanisms [ 63 , 64 ]. By 15 days, the physiological state of the animals may begin to show the cumulative effects of cold stress [ 65 ]. Mitochondrial swelling is a significant marker of cellular damage, often associated with oxidative stress and energy metabolism imbalance [ 66 , 67 ]. Cold stress can activate endoplasmic reticulum stress, leading to mitochondrial dysfunction and further exacerbating liver damage [ 31 ]. In this study, through HE staining and transmission electron microscopy, significant pathological changes were observed in the liver tissue of Bama pigs after 15 days of cold stress, including reduced intercellular space, decreased binucleated hepatocytes, cytoplasmic condensation, and mitochondrial swelling, indicating energy metabolism disorder and aggravated oxidative stress. In contrast, Hezuo pigs exhibited milder liver tissue damage and relatively normal mitochondrial morphology, suggesting stronger cellular protection capabilities and an efficient antioxidant system under cold stress [ 68 ]. Additionally, cold stress affects hepatic glucose metabolism [ 32 , 69 – 71 ]. Studies have shown that cold stress accelerates glucose consumption in animals [ 72 , 73 ], and animals with higher glucose content exhibit greater cold stress tolerance [ 27 , 29 ]. After cold stress, both pig breeds showed significant decreases in blood glucose and liver glycogen levels, but Hezuo pigs had significantly higher liver glycogen reserves than Bama pigs, as further confirmed by PAS staining results. This difference may be related to the genetic background and metabolic regulation mechanisms of the two pig breeds. To further explore the molecular regulatory mechanisms underlying the anti-damage response in Hezuo pig livers under cold stress, the 15-day cold-treated groups of Hezuo and Bama pigs, along with their respective normal temperature control groups, were selected for high-throughput sequencing analysis of liver mRNA, lncRNA, circRNA, and miRNA expression differences, revealing the molecular regulatory mechanisms and cold tolerance differences between the two pig breeds under cold stress. Through the analysis of sequencing data from 12 samples, high-quality transcriptomic data (Q20 > 96.52%, Q30 > 90.79%) were obtained, providing a reliable data foundation for subsequent functional analysis. GO and KEGG analyses revealed that Bama pigs under cold stress were significantly enriched in amino acid metabolism (e.g., "arginine biosynthesis") and glutathione metabolism-related pathways, suggesting that cold stress activates amino acid metabolism processes [ 74 ] and may be accompanied by insufficient antioxidant capacity. This finding is highly consistent with the metabolic functions of brown adipose tissue (BAT) under cold stress. Studies have shown that BAT provides nitrogen sources by breaking down branched-chain amino acids (BCAAs) to synthesize non-essential amino acids and glutathione, thereby maintaining systemic glucose homeostasis and antioxidant capacity [ 75 ]. Simultaneously, the significant enrichment of the ECM-receptor interaction pathway indicates an increased risk of liver fibrosis in Bama pigs, consistent with the histopathological changes observed in liver tissue through HE staining and transmission electron microscopy. Cold stress enhances lipid metabolism and antioxidant levels in livestock and poultry [ 76 – 78 ]. In contrast, GO analysis of Hezuo pigs under cold stress showed significant enrichment in "lipid biosynthetic processes" and "oxidoreductase activity," while KEGG results indicated significant enrichment in peroxisome and PPAR signaling pathways. This suggests that Hezuo pigs may effectively cope with cold stress by enhancing peroxisome function and lipid metabolism, maintaining cellular function. Additionally, Hezuo pigs exhibited stronger immune regulation capabilities, as evidenced by significant enrichment in "T cell receptor signaling pathway" and "natural killer cell-mediated cytotoxicity," further supporting their anti-damage capacity under cold stress. The metabolic disorder and liver damage in Bama pigs may be related to their weaker antioxidant system and energy metabolism regulation, while Hezuo pigs demonstrated stronger cold tolerance through efficient metabolic adaptation and antioxidant mechanisms. Finally, this study revealed the core regulatory roles of ssc-miR-204 and ssc-miR-29b in the cold stress response through ceRNA network analysis. Previous studies have shown that miR-204 is involved in regulating oxidative stress and apoptosis in the liver [ 79 ], while miR-29b plays an important role in liver fibrosis [ 80 ]. Potential target genes for these miRNAs comprise CYP2A19 , CA3 , P2RY13 , and ADORA2B . CYP2A19 , as an important member of the cytochrome P450 family, is primarily expressed in the liver and participates in the metabolism of various endogenous and exogenous compounds [ 81 – 83 ]. CA3 (carbonic anhydrase 3) is a liver-specific protein that plays a crucial role in lipid metabolism, particularly in regulating hepatic de novo lipogenesis [ 84 ]. P2RY13 belongs to the purinergic receptor family and is a G protein-coupled receptor (GPCR) whose ligand is adenosine diphosphate (ADP). This receptor is widely expressed in adipose tissue, liver, and brain, regulating lipolysis and inflammatory responses to maintain metabolic homeostasis [ 85 ]. The ADORA2B gene encodes the adenosine A2B receptor, which also belongs to the GPCR superfamily and plays important roles in various physiological and pathological processes. Studies have shown that ADORA2B not only regulates cardiovascular function but also exerts hepatoprotective effects by modulating related signaling pathways in the liver, potentially protecting against various types of liver injury [ 86 , 87 ]. The study ultimately revealed that three circular RNAs (circ_023716, circ_008930, and circ_007918) can co-target and regulate the interaction between ssc-miR-29b and CYP2A19 , while circ_000082 was found to form a regulatory network with ssc-miR-204 and its target genes ( P2RY13 , ADORA2B ). Furthermore, the research identified a prominent lncRNA-mediated regulatory axis: MSTRG.7463.1–ssc-miR-204–P2RY13. Future research could further validate the specific mechanisms of these miRNAs and their target genes under cold stress through functional experiments. 5 Conclusion This study systematically elucidates the differences in cold tolerance between Hezuo pigs and Bama pigs and their underlying molecular regulatory mechanisms. Hezuo pigs exhibit stronger cold stress resistance, manifested by milder liver damage and higher hepatic glycogen reserves, which provide a crucial physiological basis for their adaptation to cold environments. Through high-throughput sequencing analysis, we identified 1,307 DEmRNAs, 320 DElncRNAs, 1,299 DEcircRNAs, and 162 DEmiRNAs, which are primarily involved in immune response, signal transduction, and metabolic regulation. Three key ceRNA axes were discovered: (1) (circ_023716/008930/007918)—ssc-miR-29b—CYP2A19; (2) circ_000082—ssc-miR-204—(P2RY13/ADORA2B); and (3) MSTRG.7463.1—ssc-miR-204—P2RY13. These findings not only provide novel molecular insights into cold tolerance divergence among pig breeds but also offer important theoretical foundations and molecular markers for cold-resistant breeding in modern swine production. Declarations Acknowledgment We are grateful to Guangzhou Genedenovo Biotechnology Co., Ltd for assisting in sequencing and bioinformatics analysis. Additionally, we thank Hao Zhu, Kelin Song, Xiao Li, Yawei Lu, Jie Li, etc for their support in the experimental phase. Funding This study was supported by National Natural Science Foundation of China (U22A20507), Outstanding Postgraduate “Innovation Star” from the Education Department of Gansu Province (2022CXZXS-006); Animal Husbandry Pig Industry Technology Innovation Team Project of Gansu Agricultural University (GAU-XKTD-2022-25); Breeding of New Minshan Black Pig and Integrated Promotion of Key Technologies (22ZD6NA044). CRediT authorship contribution statement Jihong Yan: Writing– review & editing, Writing– original draft, Validation, Methodology, Investigation, Data curation. Yuran Tang: Writing– review & editing, Supervision, Methodology, Conceptualization. Shuangbao Gun: Writing– review & editing, Methodology, Investigation, Funding acquisition, Conceptualization. Pengfei Wang: Writing– review & editing, Supervision, Funding acquisition, Formal analysis, Conceptualization. Declaration of competing interest The authors have declared that no competing interest exists. Data availability All data in this study are available from the lead contact upon request. Sequencing data have been deposited under GEO dataset accession number GSE295210 and GSE296226. References Li W, Chen Y, Zhang Y, Zhao N, Zhang W, Shi M, et al. Transcriptome Analysis Revealed Potential Genes of Skeletal Muscle Thermogenesis in Mashen Pigs and Large White Pigs under Cold Stress. Int J Mol Sci. 2023;24(21).https://doi.org/10.3390/ijms242115534 Toghiani S, Hay E, Fragomeni B, Rekaya R, Roberts AJ. Genotype by environment interaction in response to cold stress in a composite beef cattle breed. Animal. 2020;14(8):1576-87.https://doi.org/10.1017/s1751731120000531 Wang D, Cheng X, Fang H, Ren Y, Li X, Ren W, et al. Effect of cold stress on ovarian & uterine microcirculation in rats and the role of endothelin system. Reprod Biol Endocrinol. 2020;18(1):29.https://doi.org/10.1186/s12958-020-00584-1 Qi L, Bravo-Ureta BE, Cabrera VE. From cold to hot: Climatic effects and productivity in Wisconsin dairy farms. J Dairy Sci. 2015;98(12):8664-77.https://doi.org/10.3168/jds.2015-9536 Wang Y, Xia L, Guo T, Heng C, Jiang L, Wang D, et al. Research Note: Metabolic changes and physiological responses of broilers in the final stage of growth exposed to different environmental temperatures. Poult Sci. 2020;99(4):2017-25.https://doi.org/10.1016/j.psj.2019.11.048 Young BA. Cold stress as it affects animal production. J Anim Sci. 1981;52(1):154-63.https://doi.org/10.2527/jas1981.521154x Le Dividich J, Noblet J. Colostrum intake and thermoregulation in the neonatal pig in relation to environmental temperature. Biol Neonate. 1981;40(3-4):167-74.https://doi.org/10.1159/000241486 Iida R, Koketsu Y. Climatic factors associated with peripartum pig deaths during hot and humid or cold seasons. Prev Vet Med. 2014;115(3-4):166-72.https://doi.org/10.1016/j.prevetmed.2014.03.019 Ramirez BC, Hayes MD, Condotta I, Leonard SM. Impact of housing environment and management on pre-/post-weaning piglet productivity. J Anim Sci. 2022;100(6).https://doi.org/10.1093/jas/skac142 Yu J, Chen S, Zeng Z, Xing S, Chen D, Yu B, et al. Effects of Cold Exposure on Performance and Skeletal Muscle Fiber in Weaned Piglets. Animals (Basel). 2021;11(7).https://doi.org/10.3390/ani11072148 Kelley KW, Blecha F, Regnier JA. Cold exposure and absorption of colostral immunoglobulins by neonatal pigs. J Anim Sci. 1982;55(2):363-8.https://doi.org/10.2527/jas1982.552363x Cobanovic N, Stajkovic S, Blagojevic B, Betic N, Dimitrijevic M, Vasilev D, et al. The effects of season on health, welfare, and carcass and meat quality of slaughter pigs. Int J Biometeorol. 2020;64(11):1899-909.https://doi.org/10.1007/s00484-020-01977-y Albert F, Kovács-Weber M, Bodnár Á, Pajor F, Egerszegi I. Seasonal Effects on the Performance of Finishing Pigs' Carcass and Meat Quality in Indoor Environments. Animals (Basel). 2024;14(2).https://doi.org/10.3390/ani14020259 Zhang B, Qiangba Y, Shang P, Wang Z, Ma J, Wang L, et al. A Comprehensive MicroRNA Expression Profile Related to Hypoxia Adaptation in the Tibetan Pig. PLoS One. 2015;10(11).https://doi.org/10.1371/journal.pone.0143260 Wang W, Yang Q, Xie K, Wang P, Luo R, Yan Z, et al. Transcriptional Regulation of HMOX1 Gene in Hezuo Tibetan Pigs: Roles of WT1, Sp1, and C/EBP alpha. Genes. 2020;11(4).https://doi.org/10.3390/genes11040352 Yan J, Wang P, Yan Z, Yang Q, Huang X, Gao X, et al. Cloning of STC-1 and analysis of its differential expression in Hezuo pig. Anim Biotechnol. 2023;34(9):4687-94.https://doi.org/10.1080/10495398.2023.2186890 Yan Z, Wang P, Yang Q, Gun S. Single-Cell RNA Sequencing Reveals an Atlas of Hezuo Pig Testis Cells. Int J Mol Sci. 2024;25(18).https://doi.org/10.3390/ijms25189786 Yan Z, Song K, Wang P, Gun S, Long X. Evaluation of the Genetic Diversity and Population Structure of Four Native Pig Populations in Gansu Province. Int J Mol Sci. 2023;24(24).https://doi.org/10.3390/ijms242417154 Schmidt I, Herpin P. Carnitine palmitoyltransferase I (CPT I) activity and its regulation by malonyl-CoA are modulated by age and cold exposure in skeletal muscle mitochondria from newborn pigs. J Nutr. 1998;128(5):886-93.https://doi.org/10.1093/jn/128.5.886 Nowack J, Vetter SG, Stalder G, Painer J, Kral M, Smith S, et al. Muscle nonshivering thermogenesis in a feral mammal. Sci Rep. 2019;9(1):6378.https://doi.org/10.1038/s41598-019-42756-z Zhang D, Ma S, Wang L, Ma H, Wang W, Xia J, et al. Min pig skeletal muscle response to cold stress. PLoS One. 2022;17(9):e0274184.https://doi.org/10.1371/journal.pone.0274184 Yang C, Cao C, Liu J, Zhao Y, Pan J, Tao C, et al. Distinct Transcriptional Responses of Skeletal Muscle to Short-Term Cold Exposure in Tibetan Pigs and Bama Pigs. Int J Mol Sci. 2023;24(8).https://doi.org/10.3390/ijms24087431 Zhang D, Wang L, Wang W, Liu D. The Role of lncRNAs in Pig Muscle in Response to Cold Exposure. Genes (Basel). 2023;14(10).https://doi.org/10.3390/genes14101901 Yang S, Ma H, Wang L, Wang F, Xia J, Liu D, et al. The Role of β3-Adrenergic Receptors in Cold-Induced Beige Adipocyte Production in Pigs. Cells. 2024;13(8).https://doi.org/10.3390/cells13080709 Liu T, Guo Y, Lu C, Cai C, Gao P, Cao G, et al. Effect of Different Pig Fecal Microbiota Transplantation on Mice Intestinal Function and Microbiota Changes During Cold Exposure. Front Vet Sci. 2022;9:805815.https://doi.org/10.3389/fvets.2022.805815 Zhang Y, Sun L, Zhu R, Zhang S, Liu S, Wang Y, et al. Porcine gut microbiota in mediating host metabolic adaptation to cold stress. NPJ Biofilms Microbiomes. 2022;8(1):18.https://doi.org/10.1038/s41522-022-00283-2 Sun G, Song X, Zou Y, Teng T, Jiang L, Shi B. Dietary Glucose Ameliorates Impaired Intestinal Development and Immune Homeostasis Disorders Induced by Chronic Cold Stress in Pig Model. Int J Mol Sci. 2022;23(14).https://doi.org/10.3390/ijms23147730 Yang Y, Chen N, Sun L, Zhang Y, Wu Y, Wang Y, et al. Short-term cold stress can reduce the abundance of antibiotic resistance genes in the cecum and feces in a pig model. J Hazard Mater. 2021;416:125868.https://doi.org/10.1016/j.jhazmat.2021.125868 Teng T, Yang H, Xu T, Sun G, Song X, Bai G, et al. Activation of Inflammatory Networks in the Lungs Caused by Chronic Cold Stress Is Moderately Attenuated by Glucose Supplementation. Int J Mol Sci. 2022;23(18).https://doi.org/10.3390/ijms231810697 Sun G, Su W, Bao J, Teng T, Song X, Wang J, et al. Dietary full-fat rice bran prevents the risk of heart ferroptosis and imbalance of energy metabolism induced by prolonged cold stimulation. Food Funct. 2023;14(3):1530-44.https://doi.org/10.1039/d2fo03673h Teng T, Zheng Y, Zhang M, Sun G, Li Z, Shi B, et al. Chronic cold stress promotes inflammation and ER stress via inhibiting GLP-1R signaling, and exacerbates the risk of ferroptosis in the liver and pancreas. Environ Pollut. 2024;360:124647.https://doi.org/10.1016/j.envpol.2024.124647 Liu Y, Xu B, Hu Y, Liu P, Lian S, Lv H, et al. O-GlcNAc / Akt pathway regulates glucose metabolism and reduces apoptosis in liver of piglets with acute cold stress. Cryobiology. 2021;100:125-32.https://doi.org/10.1016/j.cryobiol.2021.02.008 Wang X, Yang J, Li H, Mu H, Zeng L, Cai S, et al. miR-484 mediates oxidative stress-induced ovarian dysfunction and promotes granulosa cell apoptosis via SESN2 downregulation. Redox Biol. 2023;62:102684.https://doi.org/10.1016/j.redox.2023.102684 Cheng Q, Wang J, Li M, Fang J, Ding H, Meng J, et al. CircSV2b participates in oxidative stress regulation through miR-5107-5p-Foxk1-Akt1 axis in Parkinson's disease. Redox Biol. 2022;56:102430.https://doi.org/10.1016/j.redox.2022.102430 Quan J, Zhao G, Liu Z, Li L, Lu J, Song G, et al. Competing endogenous RNA (ceRNA) in a non-model animal: Non-coding RNAs respond to heat stress in rainbow trout (Oncorhynchus mykiss) through ceRNA-regulated mechanisms. Int J Biol Macromol. 2023;239:124246.https://doi.org/10.1016/j.ijbiomac.2023.124246 Chen J, Dai X, Xing C, Zhang Y, Cao H, Hu G, et al. Cooperative application of transcriptomics and ceRNA hypothesis: lncRNA-00742/miR-116 targets CD74 to mediate vanadium-induced mitochondrial apoptosis in duck liver. J Hazard Mater. 2024;480:135904.https://doi.org/10.1016/j.jhazmat.2024.135904 Wang Z, Zhao Y, Sun R, Sun Y, Liu D, Lin M, et al. circ-CBFB upregulates p66Shc to perturb mitochondrial dynamics in APAP-induced liver injury. Cell Death Dis. 2020;11(11):953.https://doi.org/10.1038/s41419-020-03160-y Wick MR. The hematoxylin and eosin stain in anatomic pathology-An often-neglected focus of quality assurance in the laboratory. Semin Diagn Pathol. 2019;36(5):303-11.https://doi.org/10.1053/j.semdp.2019.06.003 Zakout YM, Abdellah MA, Abdallah MA, Batran SA. Optimization of PAS stain and similar Schiff's based methods for glycogen demonstration in liver tissue. Histochem Cell Biol. 2024;161(4):359-64.https://doi.org/10.1007/s00418-023-02261-x Chen S, Zhou Y, Chen Y, Gu J. fastp: an ultra-fast all-in-one FASTQ preprocessor. Bioinformatics. 2018;34(17):i884-i90.https://doi.org/10.1093/bioinformatics/bty560 Langmead B, Salzberg SL. Fast gapped-read alignment with Bowtie 2. Nat Methods. 2012;9(4):357-9.https://doi.org/10.1038/nmeth.1923 Kim D, Langmead B, Salzberg SL. HISAT: a fast spliced aligner with low memory requirements. Nat Methods. 2015;12(4):357-60.https://doi.org/10.1038/nmeth.3317 Pertea M, Pertea GM, Antonescu CM, Chang TC, Mendell JT, Salzberg SL. StringTie enables improved reconstruction of a transcriptome from RNA-seq reads. Nat Biotechnol. 2015;33(3):290-5.https://doi.org/10.1038/nbt.3122 Pertea M, Kim D, Pertea GM, Leek JT, Salzberg SL. Transcript-level expression analysis of RNA-seq experiments with HISAT, StringTie and Ballgown. Nat Protoc. 2016;11(9):1650-67.https://doi.org/10.1038/nprot.2016.095 Trapnell C, Williams BA, Pertea G, Mortazavi A, Kwan G, van Baren MJ, et al. Transcript assembly and quantification by RNA-Seq reveals unannotated transcripts and isoform switching during cell differentiation. Nat Biotechnol. 2010;28(5):511-5.https://doi.org/10.1038/nbt.1621 Kong L, Zhang Y, Ye ZQ, Liu XQ, Zhao SQ, Wei L, et al. CPC: assess the protein-coding potential of transcripts using sequence features and support vector machine. Nucleic Acids Res. 2007;35(Web Server issue):W345-9.https://doi.org/10.1093/nar/gkm391 Sun L, Luo H, Bu D, Zhao G, Yu K, Zhang C, et al. Utilizing sequence intrinsic composition to classify protein-coding and long non-coding transcripts. Nucleic Acids Res. 2013;41(17):e166.https://doi.org/10.1093/nar/gkt646 Zhang J, Chen S, Yang J, Zhao F. Accurate quantification of circular RNAs identifies extensive circular isoform switching events. Nat Commun. 2020;11(1):90.https://doi.org/10.1038/s41467-019-13840-9 Friedländer MR, Mackowiak SD, Li N, Chen W, Rajewsky N. miRDeep2 accurately identifies known and hundreds of novel microRNA genes in seven animal clades. Nucleic Acids Res. 2012;40(1):37-52.https://doi.org/10.1093/nar/gkr688 Love MI, Huber W, Anders S. Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol. 2014;15(12):550.https://doi.org/10.1186/s13059-014-0550-8 Kanehisa M, Araki M, Goto S, Hattori M, Hirakawa M, Itoh M, et al. KEGG for linking genomes to life and the environment. Nucleic Acids Res. 2008;36(Database issue):D480-4.https://doi.org/10.1093/nar/gkm882 Livak KJ, Schmittgen TD. Analysis of relative gene expression data using real-time quantitative PCR and the 2(-Delta Delta C(T)) Method. Methods. 2001;25(4):402-8.https://doi.org/10.1006/meth.2001.1262 Chang J, Pan Y, Liu W, Xie Y, Hao W, Xu P, et al. Acute temperature adaptation mechanisms in the native reptile species Eremias argus. Sci Total Environ. 2022;818:151773.https://doi.org/10.1016/j.scitotenv.2021.151773 Bornstein MR, Neinast MD, Zeng X, Chu Q, Axsom J, Thorsheim C, et al. Comprehensive quantification of metabolic flux during acute cold stress in mice. Cell Metab. 2023;35(11):2077-92.e6.https://doi.org/10.1016/j.cmet.2023.09.002 Mota CMD, Madden CJ. Neural circuits of long-term thermoregulatory adaptations to cold temperatures and metabolic demands. Nat Rev Neurosci. 2024;25(3):143-58.https://doi.org/10.1038/s41583-023-00785-8 Guo JR, Nie JS, Chen Z, Wang X, Hu HJ, Xu J, et al. Cold exposure-induced endoplasmic reticulum stress regulates autophagy through the SIRT2/FoxO1 signaling pathway. Journal of Cellular Physiology. 2022;237(10):3960-70.https://doi.org/10.1002/jcp.30856 Huang Y, Xiong K, Wang A, Wang Z, Cui Q, Xie H, et al. Cold stress causes liver damage by inducing ferroptosis through the p38 MAPK/Drp1 pathway. Cryobiology. 2023;113:104563.https://doi.org/10.1016/j.cryobiol.2023.104563 Gao C, Marcketta A, Backman JD, O'Dushlaine C, Staples J, Ferreira MAR, et al. Genome-wide association analysis of serum alanine and aspartate aminotransferase, and the modifying effects of BMI in 388k European individuals. Genet Epidemiol. 2021;45(6):664-81.https://doi.org/10.1002/gepi.22392 Kew MC. Serum aminotransferase concentration as evidence of hepatocellular damage. Lancet. 2000;355(9204):591-2.https://doi.org/10.1016/s0140-6736(99)00219-6 Xu L, Yu Y, Sang R, Li J, Ge B, Zhang X. Protective Effects of Taraxasterol against Ethanol-Induced Liver Injury by Regulating CYP2E1/Nrf2/HO-1 and NF-κB Signaling Pathways in Mice. Oxid Med Cell Longev. 2018;2018:8284107.https://doi.org/10.1155/2018/8284107 Liu T, Li L, Yang Y, Li J, Yang X, Li L, et al. Effects of chronic cold stress and thermal stress on growth performance, hepatic apoptosis, oxidative stress, immune response and gut microbiota of juvenile hybrid sturgeon (Acipenser baerii ? × A. schrenkii ?). Fish Shellfish Immunol. 2025;157:110078.https://doi.org/10.1016/j.fsi.2024.110078 Bates J, Vijayakumar A, Ghoshal S, Marchand B, Yi S, Kornyeyev D, et al. Acetyl-CoA carboxylase inhibition disrupts metabolic reprogramming during hepatic stellate cell activation. J Hepatol. 2020;73(4):896-905.https://doi.org/10.1016/j.jhep.2020.04.037 Keipert S, Gaudry MJ, Kutschke M, Keuper M, Dela Rosa MAS, Cheng Y, et al. Two-stage evolution of mammalian adipose tissue thermogenesis. Science. 2024;384(6700):1111-7.https://doi.org/10.1126/science.adg1947 Rafnsdottir S, Jang K, Halldorsdottir ST, Vinod M, Tomasdottir A, Möller K, et al. SMYD5 is a regulator of the mild hypothermia response. Cell Rep. 2024;43(8):114554.https://doi.org/10.1016/j.celrep.2024.114554 Lyte JM, Eckenberger J, Keane J, Robinson K, Bacon T, Assumpcao A, et al. Cold stress initiates catecholaminergic and serotonergic responses in the chicken gut that are associated with functional shifts in the microbiome. Poult Sci. 2024;103(3):103393.https://doi.org/10.1016/j.psj.2023.103393 Zhang M, Zhou W, Cao Y, Kou L, Liu C, Li X, et al. O-GlcNAcylation regulates long-chain fatty acid metabolism by inhibiting ACOX1 ubiquitination-dependent degradation. Int J Biol Macromol. 2024;266(Pt 2):131151.https://doi.org/10.1016/j.ijbiomac.2024.131151 Ito R, Xie S, Tumenjargal M, Sugahara Y, Yang C, Takahashi H, et al. Mitochondrial biogenesis in white adipose tissue mediated by JMJD1A-PGC-1 axis limits age-related metabolic disease. iScience. 2024;27(4):109398.https://doi.org/10.1016/j.isci.2024.109398 Shin YC, Latorre-Muro P, Djurabekova A, Zdorevskyi O, Bennett CF, Burger N, et al. Structural basis of respiratory complex adaptation to cold temperatures. Cell. 2024;187(23):6584-98.e17.https://doi.org/10.1016/j.cell.2024.09.029 Liu P, Yao RZ, Shi HZ, Liu Y, Lian S, Yang YY, et al. Effects of Cold-inducible RNA-binding Protein (CIRP) on Liver Glycolysis during Acute Cold Exposure in C57BL/6 Mice. International Journal of Molecular Sciences. 2019;20(6).https://doi.org/10.3390/ijms20061470 Liu QF, Zhou ZY, Liu PS, Zhang SY. Comparative proteomic study of liver lipid droplets and mitochondria in mice housed at different temperatures. Febs Letters. 2019;593(16):2118-38.https://doi.org/10.1002/1873-3468.13509 Shi HZ, Yao RZ, Lian S, Liu P, Liu Y, Yang YY, et al. Regulating glycolysis, the TLR4 signal pathway and expression of RBM3 in mouse liver in response to acute cold exposure. Stress-the International Journal on the Biology of Stress. 2019;22(3):366-76.https://doi.org/10.1080/10253890.2019.1568987 Raun SH, Braun JL, Karavaeva I, Henriquez-Olguín C, Ali MS, Møller LLV, et al. Mild Cold Stress at Ambient Temperature Elevates Muscle Calcium Cycling and Exercise Adaptations in Obese Female Mice. Endocrinology. 2024;165(10).https://doi.org/10.1210/endocr/bqae102 Su D, Song Y, Li D, Yang S, Zhan S, Zhong T, et al. Cold exposure affects glucose metabolism, lipid droplet deposition and mitophagy in skeletal muscle of newborn goats. Domest Anim Endocrinol. 2024;88:106847.https://doi.org/10.1016/j.domaniend.2024.106847 Xue C, Zhu S, Li Y, Chen X, Lu L, Su P, et al. Cold exposure accelerates lysine catabolism to promote cold acclimation via remodeling hepatic histone crotonylation. Environ Int. 2024;192:109015.https://doi.org/10.1016/j.envint.2024.109015 Verkerke ARP, Wang D, Yoshida N, Taxin ZH, Shi X, Zheng S, et al. BCAA-nitrogen flux in brown fat controls metabolic health independent of thermogenesis. Cell. 2024;187(10):2359-74.e18.https://doi.org/10.1016/j.cell.2024.03.030 Zhang S, Liu Y, Chai Y, Xing L, Li J. Effects of intermittent cold stimulation on growth performance, meat quality, antioxidant capacity and liver lipid metabolism in broiler chickens. Poult Sci. 2024;103(3):103442.https://doi.org/10.1016/j.psj.2024.103442 Mouisel E, Bodon A, Noll C, Cassant-Sourdy S, Marques MA, Flores-Flores R, et al. Cold-induced thermogenesis requires neutral-lipase-mediated intracellular lipolysis in brown adipocytes. Cell Metab. 2025;37(2):429-40.e5.https://doi.org/10.1016/j.cmet.2024.10.018 Min H, Yang YY, Yang Y. Cold induces brain region-selective cell activity-dependent lipid metabolism. Elife. 2025;13.https://doi.org/10.7554/eLife.98353 Zou Z, Liu X, Yu J, Ban T, Zhang Z, Wang P, et al. Nuclear miR-204-3p mitigates metabolic dysfunction-associated steatotic liver disease in mice. J Hepatol. 2024;80(6):834-45.https://doi.org/10.1016/j.jhep.2024.01.029 Sohail A, Shams F, Nawaz A, Ain QU, Ijaz B. Antifibrotic potential of reserpine (alkaloid) targeting Keap1/Nrf2; oxidative stress pathway in CCl(4)-induced liver fibrosis. Chem Biol Interact. 2025;407:111384.https://doi.org/10.1016/j.cbi.2025.111384 Achour B, Barber J, Rostami-Hodjegan A. Cytochrome P450 Pig liver pie: determination of individual cytochrome P450 isoform contents in microsomes from two pig livers using liquid chromatography in conjunction with mass spectrometry [corrected]. Drug Metab Dispos. 2011;39(11):2130-4.https://doi.org/10.1124/dmd.111.040618 Burkina V, Zlabek V, Rasmussen MK, Zamaratskaia G. End-product inhibition of skatole-metabolising enzymes CYP1A, CYP2A19 and CYP2E1 in porcine and piscine hepatic microsomes. Toxicol Lett. 2019;303:67-71.https://doi.org/10.1016/j.toxlet.2018.12.017 Wang Z, Huang Q, Zhang F, Wu J, Wang L, Sun Y, et al. Key Role of Porcine Cytochrome P450 2A19 in the Bioactivation of Aflatoxin B(1) in the Liver. J Agric Food Chem. 2024;72(4):2334-46.https://doi.org/10.1021/acs.jafc.3c08663 Liu D, Wong CC, Zhou Y, Li C, Chen H, Ji F, et al. Squalene Epoxidase Induces Nonalcoholic Steatohepatitis Via Binding to Carbonic Anhydrase III and is a Therapeutic Target. Gastroenterology. 2021;160(7):2467-82.e3.https://doi.org/10.1053/j.gastro.2021.02.051 Duparc T, Gore E, Combes G, Beuzelin D, Pires Da Silva J, Bouguetoch V, et al. P2Y13 receptor deficiency favors adipose tissue lipolysis and worsens insulin resistance and fatty liver disease. JCI Insight. 2024;9(8).https://doi.org/10.1172/jci.insight.175623 Smith K. Transplantation: ADORA2B helps to block liver injury. Nat Rev Gastroenterol Hepatol. 2013;10(8):444.https://doi.org/10.1038/nrgastro.2013.129 Zimmerman MA, Grenz A, Tak E, Kaplan M, Ridyard D, Brodsky KS, et al. Signaling through hepatocellular A2B adenosine receptors dampens ischemia and reperfusion injury of the liver. Proc Natl Acad Sci U S A. 2013;110(29):12012-7.https://doi.org/10.1073/pnas.1221733110 Additional Declarations No competing interests reported. Supplementary Files Supplementarymaterial.docx Cite Share Download PDF Status: Posted Version 1 posted 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. 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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-7481559","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":509741578,"identity":"8a063c4e-9986-4399-a174-237b71abc6df","order_by":0,"name":"Jihong Yan","email":"","orcid":"","institution":"Gansu Agricultural University","correspondingAuthor":false,"prefix":"","firstName":"Jihong","middleName":"","lastName":"Yan","suffix":""},{"id":509741579,"identity":"a71edfde-7c9e-47d2-9587-50fd572b5507","order_by":1,"name":"Yuran Tang","email":"","orcid":"","institution":"Gansu Agricultural University","correspondingAuthor":false,"prefix":"","firstName":"Yuran","middleName":"","lastName":"Tang","suffix":""},{"id":509741580,"identity":"0e92064a-83c8-451b-a8ac-0fd07ef1890a","order_by":2,"name":"Shuangbao Gun","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA2ElEQVRIiWNgGAWjYJACZiDmsW9vPnDgQwUJWuQMeI4lHpxxhgQtxgYSPsaHeVuIUC4fkXv4c0GNTeJ2CZ4PB3gbGOT5xQ7g12J4Iy9NesaxtMSds3s3HJDcwWA4c3YCAS0zcsyYedgOJzbcObvhgOEZhgSD24S1GH/m+QfUciPnwYHENiK0yEvkGEjzth02NriRw3DgIDFaDHjemEnP7EuTk+w5ZnCw4YwEYb/ItwMdVvDNhoefvfnx5z8VNvL80oRsOYDKl8CvHGxLA2E1o2AUjIJRMNIBAIj3St22BayzAAAAAElFTkSuQmCC","orcid":"","institution":"Gansu Agricultural University","correspondingAuthor":true,"prefix":"","firstName":"Shuangbao","middleName":"","lastName":"Gun","suffix":""},{"id":509741581,"identity":"a90b1987-402b-43a8-886e-30ffd30b560d","order_by":3,"name":"Pengfei Wang","email":"","orcid":"","institution":"Gansu Agricultural University","correspondingAuthor":false,"prefix":"","firstName":"Pengfei","middleName":"","lastName":"Wang","suffix":""}],"badges":[],"createdAt":"2025-08-28 15:08:35","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-7481559/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7481559/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":90908372,"identity":"4e777c06-4dc2-4445-ac37-c0c156e8a12e","added_by":"auto","created_at":"2025-09-09 13:24:41","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":796160,"visible":true,"origin":"","legend":"\u003cp\u003eAnalysis of time-dependent liver injury severity in Bama pigs and Hezuo pigs under cold stress. (A) Evaluation of liver function; (B) Immunohistochemistry of liver α-SMA protein. Scale: 0.500 mm; (C) Differences in α-SMA-positive areas in the liver;\u003c/p\u003e\n\u003cp\u003eNote: BM represents Bama pigs; HZ represents Hezuo pigs. Lowercase letters indicate comparisons among Bama pigs, uppercase letters denote comparisons among Hezuo pigs, with the same letters indicating no significant difference and different letters indicating significant differences; asterisks (*) represent comparisons between the two breeds at the same time point (*\u003cem\u003eP\u003c/em\u003e \u0026lt; 0.05, **\u003cem\u003eP \u003c/em\u003e\u0026lt; 0.01).\u003c/p\u003e","description":"","filename":"image1.png","url":"https://assets-eu.researchsquare.com/files/rs-7481559/v1/ab8071a69ec959dbea6e14eb.png"},{"id":90909997,"identity":"7a534ed0-2210-41a2-b15d-a8a862f602c5","added_by":"auto","created_at":"2025-09-09 13:32:41","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":887188,"visible":true,"origin":"","legend":"\u003cp\u003eAnalysis of liver injury severity in Bama pigs and Hezuo pigs under cold stress (-15 °C for 15 Days). (A) Frostbite conditions in pig ears and liver anatomical morphology; (B) HE staining. Scale: 10 μm; (C) Transmission electron microscopy (TEM). Scale: 2 μm; (D) PAS staining. Scale: 10 μm; (E) Blood glucose concentration; (F) Liver glycogen content.\u003c/p\u003e\n\u003cp\u003eNote: BC represents Bama pigs in the control group; BT represents Bama pigs in the cold-treated group; HC represents Hezuo pigs in the control group; HT represents Hezuo pigs in the cold-treated group; N denotes the nucleus, and M denotes mitochondria. * indicates \u003cem\u003eP\u003c/em\u003e \u0026lt; 0.05, ** indicates \u003cem\u003eP\u003c/em\u003e \u0026lt; 0.01, and no mark indicates \u003cem\u003eP\u003c/em\u003e \u0026gt; 0.05.\u003c/p\u003e","description":"","filename":"image2.png","url":"https://assets-eu.researchsquare.com/files/rs-7481559/v1/c29adff09c34a649fcd37199.png"},{"id":90908374,"identity":"477a4bfb-d785-44cf-ae43-61d86827eb9b","added_by":"auto","created_at":"2025-09-09 13:24:41","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":544989,"visible":true,"origin":"","legend":"\u003cp\u003eMulti-group differential Venn diagrams and scatter plots. (A, E) DEmRNAs; (B, F) DElncRNAs; (C, G) DEcircRNAs; (D, H) DEmiRNAs\u003c/p\u003e","description":"","filename":"image3.png","url":"https://assets-eu.researchsquare.com/files/rs-7481559/v1/d973faf3c6f70440894b8931.png"},{"id":90908389,"identity":"937e4640-8443-4a46-8720-d13c1c8ded56","added_by":"auto","created_at":"2025-09-09 13:24:41","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":774918,"visible":true,"origin":"","legend":"\u003cp\u003eDifferential bubble plot of GO enrichment. (A) BC-vs-HT group; (B) BC-vs-HC group; (C) HC-vs-HT group; and (D) BT-vs-HT group.\u003c/p\u003e\n\u003cp\u003eNote: The vertical axis represents -log10(Qvalue), and the horizontal axis represents the z-score value (the proportion of the difference between the number of upregulated and downregulated differentially expressed genes to the total number of differentially expressed genes). The yellow line indicates the threshold of Qvalue = 0.05. The right side lists the top 20 GO terms by Q-value. Different colors represent different ontologies.\u003c/p\u003e","description":"","filename":"image4.png","url":"https://assets-eu.researchsquare.com/files/rs-7481559/v1/5c062ae88895b30058e01f7a.png"},{"id":90909996,"identity":"c494a73a-e418-4123-864a-f59474e22b7c","added_by":"auto","created_at":"2025-09-09 13:32:41","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":592457,"visible":true,"origin":"","legend":"\u003cp\u003eKEGG enrichment bubble plot. (A) BC-vs-HT group; (B) BC-vs-HC group; (C) HC-vs-HT group; and (D) BT-vs-HT group.\u003c/p\u003e\n\u003cp\u003eNote: The top 20 pathways with the smallest Q-values were used for plotting. The vertical axis represents the pathways, and the horizontal axis represents the enrichment factor (the number of differentially expressed genes in the pathway divided by the total number of genes in the pathway). The size of the bubbles indicates the number of genes, and the redder the color, the smaller the Q-value.\u003c/p\u003e","description":"","filename":"image5.png","url":"https://assets-eu.researchsquare.com/files/rs-7481559/v1/5e1643eacb44cdbf2b181ac1.png"},{"id":90907004,"identity":"4648c85a-bc46-43e4-a888-c7613d9a293b","added_by":"auto","created_at":"2025-09-09 13:16:41","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":648731,"visible":true,"origin":"","legend":"\u003cp\u003eEnrichment analysis of mRNAs in the ceRNA network\u003c/p\u003e\n\u003cp\u003eNote: (A, C) The enrichment analysis of target genes in the lncRNA-miRNA-mRNA regulatory network was conducted. (B, D) presents the enrichment analysis of target genes in the circRNA-miRNA-mRNA regulatory network.\u003c/p\u003e","description":"","filename":"image6.png","url":"https://assets-eu.researchsquare.com/files/rs-7481559/v1/e55d762515e8236fc943b6cb.png"},{"id":90908367,"identity":"996bccbb-338a-4ed2-a4c7-63a5a15dc5c5","added_by":"auto","created_at":"2025-09-09 13:24:41","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":341221,"visible":true,"origin":"","legend":"\u003cp\u003eRegulatory ceRNA network associated with cold stress-induced liver injury resistance in Hezuo pigs\u003c/p\u003e\n\u003cp\u003eNote: Blue circles represent circRNAs, purple circles represent lncRNAs, green triangles represent miRNAs (with larger triangles indicating more connected nodes), and orange circles represent mRNAs.\u003c/p\u003e","description":"","filename":"image7.png","url":"https://assets-eu.researchsquare.com/files/rs-7481559/v1/1c950a51e1e340d387f6d864.png"},{"id":90910000,"identity":"7c24e225-09b3-4f72-b34c-5365e09ef180","added_by":"auto","created_at":"2025-09-09 13:32:41","extension":"png","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":559304,"visible":true,"origin":"","legend":"\u003cp\u003eThe differential expression of mRNAs, lncRNAs, circRNAs and miRNAs in RNA-seq was validated using RT-qPCR.\u003c/p\u003e","description":"","filename":"image8.png","url":"https://assets-eu.researchsquare.com/files/rs-7481559/v1/b6cb8ff1c0e24464137e244f.png"},{"id":95799527,"identity":"f47f7f0e-af82-4d2b-a0c5-0b445806fa16","added_by":"auto","created_at":"2025-11-13 08:20:14","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":6302783,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7481559/v1/014ae294-8cdf-4944-bf48-c7fb31d6a628.pdf"},{"id":90907000,"identity":"1ecde433-526f-47c5-8b76-18efd448cbe1","added_by":"auto","created_at":"2025-09-09 13:16:41","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":29907,"visible":true,"origin":"","legend":"","description":"","filename":"Supplementarymaterial.docx","url":"https://assets-eu.researchsquare.com/files/rs-7481559/v1/6c8890b9eb8ae5c06d1d1c6c.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Anti-injury Mechanisms in the Liver and its Molecular Regulatory Networks of the Hezuo Pig under Cold Stress","fulltext":[{"header":"1 Background","content":"\u003cp\u003eCold stress is a significant environmental factor that substantially impacts the health and production performance of livestock and poultry [\u003cspan additionalcitationids=\"CR2\" citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. In livestock production, cold environments not only diminish the growth rate of animals [\u003cspan additionalcitationids=\"CR5\" citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e], but also lead to a significant increase in pig mortality rates [\u003cspan additionalcitationids=\"CR8\" citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e] and the incidence of diarrhea [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. Furthermore, such conditions adversely affect meat quality [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e], resulting in substantial economic losses. Therefore, effectively mitigating the impact of cold stress on livestock and poultry production is a critical scientific issue to be addressed in the field of animal husbandry.\u003c/p\u003e\u003cp\u003eThe Hezuo pig, a branch of the Tibetan pig, is a unique local breed endemic to Gansu Province. It is primarily distributed in the Gannan Tibetan Autonomous Prefecture, located on the northeastern edge of the Qinghai-Tibet Plateau at an average altitude of approximately 3,000 meters. Through long-term natural selection, the Hezuo pig has developed robust cold-resistant traits [\u003cspan additionalcitationids=\"CR15\" citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. The Hezuo pig, characterized by exceptional environmental resilience, cost-efficient husbandry, and consistent market viability, now functions as both a critical livelihood asset for pastoral communities and a catalyst for China's rural revitalization agenda [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eIn recent years, research has increasingly focused on the mechanisms by which cold stress impairs organ function in pigs. As a primary thermogenic response, pigs utilize muscle shivering to generate heat [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. Transcriptomic analyses have revealed that cold exposure induces differential gene expression in porcine skeletal muscle, including alterations in lncRNAs and their target genes, which significantly enrich pathways related to ion transport, amino acid metabolism, and carbohydrate metabolism [\u003cspan additionalcitationids=\"CR22\" citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. At the cellular level, PRSS8 in skeletal muscle satellite cells has been shown to regulate ERK phosphorylation, thereby influencing energy metabolism and thermogenesis during cold stress [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. Beyond skeletal muscle, cold stress exerts systemic effects on metabolic tissues. In adipose tissue, it promotes beige fat generation and enhances thermogenic capacity [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. The gastrointestinal system also responds to cold exposure [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e], with studies demonstrating intestinal mucosal damage and reduced antibiotic resistance gene abundance in the cecum and feces of cold-stressed pigs [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. Concurrently, cold stress triggers pulmonary inflammation [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e] and increases susceptibility to cardiac injury and energy imbalance [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. The liver, as a central metabolic organ and key site of non-shivering thermogenesis (NST), undergoes profound changes under cold conditions. Chronic cold exposure disrupts GLP-1R signaling, inducing oxidative stress while promoting inflammation, endoplasmic reticulum stress, and apoptosis in both hepatic and pancreatic tissues [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. Acute cold stress, meanwhile, activates the O-GlcNAc/Akt pathway to modulate hepatic glucose metabolism and mitigate apoptosis in cold-exposed piglets [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eHigh-throughput sequencing technology has played a pivotal role in studying gene expression regulatory networks in complex biological processes. By integrating mRNA, lncRNA, circRNA, and miRNA expression profiles, the competing endogenous RNA (ceRNA) regulatory network has been elucidated in specific physiological or pathological contexts. The ceRNA network regulates target gene expression by competitively binding miRNAs, playing a critical role in cellular metabolism, stress responses, and tissue damage repair [\u003cspan additionalcitationids=\"CR34 CR35 CR36\" citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e]. To date, little is known about the regulatory function of ceRNA networks in cold stress-mediated liver damage. Therefore, this study focuses on Hezuo pigs and Bama pigs as experimental subjects, comparing their liver function, histopathological changes, glucose metabolism levels, and liver injury under cold stress. Through whole transcriptome sequencing analysis, this study will characterize the ceRNA network involved in cold stress resistance in the liver of Hezuo pigs. The investigation will elucidate the molecular mechanisms underlying hepatic homeostasis maintenance during cold stress in this breed, which may contribute to improved strategies for cold-resistant livestock breeding and hepatic protection.\u003c/p\u003e"},{"header":"2 Materials and methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003e2.1 Ethics statement\u003c/h2\u003e\u003cp\u003e This study was approved by the Animal Ethics Committee of the College of Animal Science and Technology, Gansu Agricultural University (Approval No. 2006\u0026thinsp;\u0026minus;\u0026thinsp;398). All animal experiments were performed in strict compliance with the institutional ethical guidelines for humane treatment of research animals. Euthanasia procedures were conducted following established protocols to minimize animal distress.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec4\" class=\"Section2\"\u003e\u003ch2\u003e2.2 Experimental animals\u003c/h2\u003e\u003cp\u003eA total of 30 healthy 75-day-old pigs, comprising 15 Bama (BM) and 15 Hezuo (HZ) pigs, were randomly allocated into five experimental groups: a control group (C, 23\u0026thinsp;\u0026plusmn;\u0026thinsp;2\u0026deg;C) and four cold stress groups (5 d, 10 d, 15 d, and 20 d, -15\u0026thinsp;\u0026plusmn;\u0026thinsp;2\u0026deg;C). Each group contained three pigs per breed. Following a 7-day acclimation period under ambient conditions, the pigs were subjected to their respective treatments. At designated time points, the animals were humanely euthanized. Blood samples were collected in coagulation-promoting tubes for serum separation. Liver tissues were harvested and preserved under different conditions: snap-frozen at -80\u0026deg;C for RNA extraction, fixed in 4% paraformaldehyde for histological analyses (HE, PAS, and immunohistochemistry), and stored in 3% glutaraldehyde for transmission electron microscopy (TEM).\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec5\" class=\"Section2\"\u003e\u003ch2\u003e2.3 Immunohistochemistry of the α-SMA Protein\u003c/h2\u003e\u003cp\u003eLiver tissue samples were fixed overnight in 4% paraformaldehyde, dehydrated in ethanol, embedded in paraffin, and sectioned. After dewaxing and rehydration, the sections were washed three times with distilled water. Antigen retrieval was performed, followed by the elimination of endogenous peroxidase activity using 3% H\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e2\u003c/sub\u003e. The sections were blocked with 3% Bovine Serum Albumin (BSA) at room temperature for 30 minutes and then incubated with rabbit anti-α-SMA polyclonal antibody (1:3000, Proteintech, Wuhan, China) at 4\u0026deg;C overnight. HRP-labeled goat anti-rabbit IgG (1:200, Servicebio, Wuhan, China) was added for incubation in the next day. Positive signals (brown) were visualized using a diaminobenzidine (DAB) kit (Servicebio). Subsequently, the nuclei were counterstained, and the sections were dehydrated, mounted, and observed under a microscope.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec6\" class=\"Section2\"\u003e\u003ch2\u003e2.4 Serum biochemical parameter analysis\u003c/h2\u003e\u003cp\u003eThe corresponding parameters were set on a Fully Automated Biochemical Analyzer (Shenzhen Rayto Life Science, Shenzhen, China) to detect Alanine Aminotransferase (ALT), Aspartate Aminotransferase (AST), Alkaline Phosphatase (ALP), Lactate Dehydrogenase (LDH), and blood glucose (GLU). Blood samples from all experimental pigs were collected from the anterior vena cava. Whole blood samples were left at room temperature for 2 hours and then centrifuged at 3000 rpm for 15 minutes at 4\u0026deg;C. The supernatant was collected for analysis using the analyzer.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e\u003ch2\u003e2.5 Pig Ear Frostbite and Liver Morphological Characteristics\u003c/h2\u003e\u003cp\u003eThe frostbite conditions in the ears, as well as the anatomical and microscopic characteristics of the liver, were observed and analyzed in both pig breeds. Paraffin-embedded liver tissue sections were subjected to conventional HE and PAS staining following the methods described in references [\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e, \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e], and histopathological changes were observed under a microscope. Glycogen accumulation was detected using a glycogen assay kit (Solarbio, Beijing, China). The liver tissue samples pre-fixed with 3% glutaraldehyde were further fixed with 1% osmium tetroxide. Subsequently, the samples were dehydrated using a graded acetone series. After infiltration and embedding, the tissues were sectioned into ultrathin slices of approximately 70 nm. The sections were stained at room temperature and then observed under a TEM to examine the morphology of the nuclei and mitochondria.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\u003ch2\u003e2.6 RNA Extraction, Library Construction and Sequencing\u003c/h2\u003e\u003cp\u003eTotal RNA was extracted from the liver tissues of all pigs using TRIzol (Life Technologies, CA, USA) according to the manufacturer's instructions. The quality and concentration of all RNA samples were assessed using an Agilent 2100 Bioanalyzer (Agilent Technologies, CA, USA) and 1% agarose gel electrophoresis. RNA samples with an RNA Integrity Number (RIN)\u0026thinsp;\u0026ge;\u0026thinsp;7.0 were used for RNA-seq and miRNA-seq.\u003c/p\u003e\u003cp\u003eFor RNA-seq, the ribosomal RNA (rRNA) was depleted using an rRNA removal kit (Epicentre, CA, USA), followed by reverse transcription of the remaining RNA into complementary DNA (cDNA) using random primers. The second strand of cDNA was synthesized using DNA polymerase I, RNase H, dNTPs, and buffer. Subsequently, the cDNA fragments were purified, end-repaired, poly(A)-tailed, and ligated to Illumina sequencing adapters. The second strand cDNA was then degraded using Uracil-N-Glycosylase (UNG). The digested products were size-selected by agarose gel electrophoresis, PCR-amplified, and then used for library construction. The resulting library was sequenced on the Illumina HiSeqTM 4000 platform.\u003c/p\u003e\u003cp\u003eFor miRNA-seq, RNA molecules in the 18\u0026ndash;30 nt range were enriched using polyacrylamide gel electrophoresis (PAGE). The 3' and 5' adapters were ligated to the RNA molecules, followed by reverse transcription and PCR amplification of the ligated products. Finally, bands of approximately 140 bp were recovered and purified using PAGE, dissolved in EB solution, and used for library construction and sequencing. Both RNA-seq and miRNA-seq were performed by Gene Denovo Biotechnology Co., Ltd. (Guangzhou, China).\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e\u003ch2\u003e2.7 Data quality control and genome alignment\u003c/h2\u003e\u003cp\u003eRaw data were further filtered using FASTP [\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e]. Reads containing adapters, reads with more than 10% unknown nucleotides (N), and low-quality reads with over 50% of bases having a quality score (Q)\u0026thinsp;\u0026le;\u0026thinsp;20 were removed. Clean reads were aligned to the ribosomal RNA (rRNA) database using Bowtie2 [\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e], and reads mapped to rRNA were subsequently removed. The remaining reads were aligned to the pig reference genome using HISAT2 [\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e] for paired-end reads.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e\u003ch2\u003e2.8 Identification of mRNA, lncRNA, circRNA and miRNA\u003c/h2\u003e\u003cp\u003eTranscripts were assembled using StringTie [\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e, \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e], and genes identified in the sequencing data that were not annotated in the reference genome were defined as novel genes. The reconstructed transcripts were compared with known transcripts in the reference genome using Cuffcompare[\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e] to filter out known mRNAs. Due to the complexity of lncRNA origins and the significant differences in lncRNAs derived from different transcripts of the same gene, lncRNAs were analyzed based on transcripts. The identification process involved retaining transcripts with a length\u0026thinsp;\u0026ge;\u0026thinsp;200 bp and exon numbers\u0026thinsp;\u0026ge;\u0026thinsp;2 based on StringTie-reconstructed transcripts. The coding potential of these novel transcripts was predicted using CPC2 [\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e] and CNCI [\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e], and the intersection of transcripts without coding potential was considered a reliable prediction result. circRNAs were identified using CIRIquant [\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eFor miRNAs, raw sequencing data underwent quality assessment and filtering, followed by alignment with small RNAs in the GenBank and Rfam databases to identify and remove rRNA, scRNA, snoRNA, snRNA, and tRNA. The data were then aligned to the pig reference genome. Clean tags were searched against the miRBase database to identify existing miRNAs. For miRNA sequences not yet included in miRBase, alignment with miRNAs from other species was performed to identify known miRNAs. Finally, novel miRNAs were identified based on genomic locations and hairpin structures predicted by the miRDeep2 [\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e].\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\u003ch2\u003e2.9 Differentially Expressed RNA Screening and Functional Annotation\u003c/h2\u003e\u003cp\u003eQuantitative analysis of the identified ncRNAs and mRNAs was performed using FPKM, RPM, and TPM as normalization methods to quantify the expression abundance of mRNAs, lncRNAs, circRNAs, and miRNAs. The DESeq2 [\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e] software was used to identify differentially expressed mRNAs (DEmRNAs) based on FDR\u0026thinsp;\u0026lt;\u0026thinsp;0.05 and |log2 fold change (FC)| \u0026gt;2. Differentially expressed lncRNAs and circRNAs (DElncRNAs/DEcircRNAs) were screened with \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05 and |fold change (FC)| \u0026gt;2, while differentially expressed miRNAs (DEmiRNAs) were screened with \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05 and |fold change (FC)| \u0026gt;1.5. GO terms and KEGG [\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e] pathway enrichment analysis were then employed to further investigate the functions of DEmRNAs. GO terms and KEGG pathways with \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05 were considered significantly enriched.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e\u003ch2\u003e2.10 Construction and Analysis of ceRNAs Regulatory Network\u003c/h2\u003e\u003cp\u003eTo reveal the roles and interactions of DEmRNAs, DElncRNAs, DEcircRNAs, and DEmiRNAs, two ceRNA networks were constructed based on the ceRNA theory: the lncRNA-miRNA-mRNA network and the circRNA-miRNA-mRNA network. By calculating the Pearson correlation coefficients for the expression levels of the obtained ceRNA pairs, selecting ceRNA pairs with correlation coefficients above 0.7 as potential ceRNA pairs. Based on these results, a hypergeometric distribution test was further applied a hypergeometric distribution test to screen ceRNA pairs with \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05 as the final ceRNA pairs. GO terms and KEGG pathway functional and enrichment analyses were subsequently performed on the two ceRNA networks, with GO terms and KEGG pathways with \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05 considered significantly enriched in DEGs. ceRNAs related to liver injury resistance in Hezuo pigs were selected from these networks. Finally, the interaction networks were visualized using Cytoscape.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec13\" class=\"Section2\"\u003e\u003ch2\u003e2.11 RT-qPCR Validation\u003c/h2\u003e\u003cp\u003eTo validate the accuracy and reliability of the sequencing results, six DEmRNAs, three DElncRNAs, three DEcircRNAs, and three DEmiRNAs were randomly selected, and their expression levels were detected using RT-qPCR. The reactions were performed according to the instructions of the SYBR\u0026reg; Green Pro Taq HS Premix qPCR Kit (Accurate Biotechnology, Hunan, China). The reaction procedure consisted of an initial step at 95\u0026deg;C for 30 s, followed by 40 cycles of 95\u0026deg;C for 5 s and 60\u0026deg;C for 30 s, and a final step at 95\u0026deg;C for 1 min, 60\u0026deg;C for 30 s, and 95\u0026deg;C for 30 s. The relative expression of mRNAs, lncRNAs, circRNAs, and miRNAs was quantified using the2\u003csup\u003e\u0026minus;ΔΔCt [52]\u003c/sup\u003e method, normalized to the housekeeping genes \u003cem\u003eGAPDH\u003c/em\u003e or \u003cem\u003eU6\u003c/em\u003e. All results are presented as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD. The primers were designed using Premier 5.0 software and synthesized by GENEWIZ (Suzhou, China). The primer sequences are listed in Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e.\u003c/p\u003e\u003c/div\u003e"},{"header":"3 Results","content":"\u003cdiv id=\"Sec15\" class=\"Section2\"\u003e\n \u003ch2\u003e3.1 Analysis of Liver Injury Severity\u003c/h2\u003e\n \u003cp\u003eBama pigs were more sensitive to cold stress, as evidenced by significant increases in liver function indicators (ALT, AST, LDH) after 20 days of cold exposure (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05), whereas Hezuo pigs exhibited stronger tolerance (Fig. \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003eA). Immunohistochemical analysis of liver \u0026alpha;-SMA revealed that the positive area of \u0026alpha;-SMA increased significantly with prolonged cold exposure, and the activation level of HSCs in Bama pigs was significantly higher than that in Hezuo pigs at 15 d and 20 d (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05) (Fig. \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003eB-C).\u003c/p\u003e\n \u003cp\u003eAfter 15 days of cold stress, Bama pigs exhibited ear tissue cracking and scabbing, rough and congested liver surfaces (Fig. \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003eA), irregular nuclear membranes, and swollen mitochondria in hepatocytes (Fig. \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003eB-C). In contrast, Hezuo pigs showed no frostbite in ear tissues and maintained relatively normal liver cell structures with milder liver injury. Additionally, PAS staining and quantification of liver glycogen revealed that Hezuo pigs had significantly higher glycogen reserves than Bama pigs (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05). Following cold stress, both pig breeds showed significant decreases in blood glucose and liver glycogen levels (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05) (Fig. \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003eD-F).\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec16\" class=\"Section2\"\u003e\n \u003ch2\u003e3.2 Overview of Whole Transcriptome Sequencing Data\u003c/h2\u003e\n \u003cp\u003eTo ensure data quality, raw reads were filtered prior to bioinformatics analysis. Clean data from all samples ranged from 99.64\u0026ndash;99.77%, with average Q20, Q30, and GC content values of 96.52%, 90.79%, and 54.23%, respectively. The majority of reads mapped to the pig reference genome (78.22% ~ 83.25%), confirming high sequencing reliability for the 12 samples (Table S2-4).\u003c/p\u003e\n \u003cp\u003eFor miRNA-seq, after filtering low-quality reads, the BC, HC, BT, and HT groups yielded 27.1\u0026thinsp;~\u0026thinsp;33.4\u0026nbsp;million clean tags (Table S5). Mapping rates to the pig genome ranged from 75.77\u0026ndash;80.89%. Non-coding RNAs were annotated by comparison with GenBank and Rfam, with rRNA, tRNA, snRNA, snoRNA, and repetitive sequences removed (Table S6). Most clean reads were classified as miRNAs, demonstrating successful sequencing.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec17\" class=\"Section2\"\u003e\n \u003ch2\u003e3.3 Identification of DEmRNAs, DElncRNAs, DEcircRNAs and DEmiRNAs\u003c/h2\u003e\n \u003cp\u003eIn this study, a total of 1,307 differentially expressed mRNAs (DEmRNAs), 320 differentially expressed lncRNAs (DElncRNAs), 1,299 differentially expressed circRNAs (DEcircRNAs), and 162 differentially expressed miRNAs (DEmiRNAs) were identified (Fig. \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003eA-D). Among the comparison groups BC-vs-BT, BC-vs-HC, HC-vs-HT, and BT-vs-HT, there were 317, 581, 258, and 511 DEmRNAs; 102, 143, 92, and 138 DElncRNAs; 399, 521, 275, and 447 DEcircRNAs; and 47, 86, 41, and 71 DEmiRNAs, respectively (Fig. \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003eE-H).\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec18\" class=\"Section2\"\u003e\n \u003ch2\u003e3.4 GO terms and KEGG pathways Analysis\u003c/h2\u003e\n \u003cp\u003eGO terms enrichment analysis revealed that the BC-vs-BT group was significantly enriched in terms related to metabolic disorders, oxidative stress, and liver fibrosis, such as \u0026quot;alpha-amino acid metabolic process\u0026quot; and \u0026quot;extracellular matrix structural constituent\u0026quot;(Fig. \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003eA). The BC-vs-HC group was significantly enriched in terms such as \u0026quot;immune system process\u0026quot; and \u0026quot;cell killing\u0026quot;(Fig. \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003eB). Both the HC-vs-HT (Fig. \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003eC) and BT-vs-HT (Fig. \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003eD) groups were significantly enriched in functions related to metabolic adaptation and antioxidant defense, such as \u0026quot;lipid biosynthetic process\u0026quot; and \u0026quot;oxidoreductase activity\u0026quot;.\u003c/p\u003e\n \u003cp\u003eKEGG pathway enrichment analysis showed that the BC-vs-BT group was significantly enriched in pathways related to amino acid metabolism (e.g., \u0026quot;arginine biosynthesis\u0026quot;), glutathione metabolism, and ECM-receptor interaction (Fig. \u003cspan class=\"InternalRef\"\u003e5\u003c/span\u003eA). The BC-vs-HC group was mainly enriched in immune-related pathways (e.g., \u0026quot;T cell receptor signaling pathway\u0026quot; and \u0026quot;natural killer cell-mediated cytotoxicity\u0026quot;) (Fig. \u003cspan class=\"InternalRef\"\u003e5\u003c/span\u003eB). The HC-vs-HT group was significantly enriched in pathways such as peroxisome, PPAR signaling pathway, and retinol metabolism (Fig. \u003cspan class=\"InternalRef\"\u003e5\u003c/span\u003eC). The BT-vs-HT group was significantly enriched in immune-related pathways (e.g., \u0026quot;primary immunodeficiency\u0026quot;) and lipid metabolism pathways (Fig. \u003cspan class=\"InternalRef\"\u003e5\u003c/span\u003eD).\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec19\" class=\"Section2\"\u003e\n \u003ch2\u003e3.5 Screening of ceRNA Related to Anti-Damage in Hezuo Pig\u003c/h2\u003e\n \u003cp\u003eTo investigate the molecular mechanisms conferring liver injury resistance in Hezuo pigs, we constructed two ceRNA regulatory networks: (1) a lncRNA-miRNA-mRNA network (38 lncRNAs, 37 miRNAs, 240 mRNAs; 530 interactions) and (2) a circRNA-miRNA-mRNA network (148 circRNAs, 61 miRNAs, 354 mRNAs; 2,193 interactions). GO and KEGG analyses demonstrated significant enrichment of these networks in cold stress-associated pathways. Immune-related pathways included \u0026quot;immune system process\u0026quot; and \u0026quot;T cell receptor signaling pathway\u0026quot;. Signaling-related pathways included \u0026quot;NF-\u0026kappa;B signaling pathway\u0026quot; and \u0026quot;Rap1 signaling pathway\u0026quot;. Metabolic-related pathways included \u0026quot;nitrogen metabolism\u0026quot; and \u0026quot;fatty acid metabolism\u0026quot;. Additionally, pathways such as \u0026quot;biological regulation\u0026quot; and \u0026quot;cellular process\u0026quot; were also involved.\u003c/p\u003e\n \u003cp\u003eFollowing stringent filtration (mRNAs with expression\u0026thinsp;\u0026lt;\u0026thinsp;1.0), network analysis revealed miRNAs as central hubs. Topological assessment identified ssc-miR-10382, ssc-miR-204, and ssc-miR-29b as highest-degree nodes, followed by ssc-miR-1388 and ssc-miR-9843-3p. Expression profiling confirmed these miRNAs were among the most abundant, suggesting key regulatory roles. Their target mRNAs (\u003cem\u003eCYP2A19\u003c/em\u003e, \u003cem\u003eCA3\u003c/em\u003e, \u003cem\u003eP2RY13\u003c/em\u003e, \u003cem\u003eADORA2B\u003c/em\u003e) may collectively modulate immune responses, signaling cascades, and metabolic adaptation during cold stress.\u003c/p\u003e\n \u003cp\u003eNotably, three circRNAs (circ_023716, circ_008930, circ_007918) showed co-targeting of ssc-miR-29b and \u003cem\u003eCYP2A19\u003c/em\u003e, while circ_000082 interacted with ssc-miR-204 and its targets (\u003cem\u003eP2RY13\u003c/em\u003e, \u003cem\u003eADORA2B\u003c/em\u003e). Only one prominent lncRNA-mediated axis was detected: MSTRG.7463.1\u0026ndash;ssc-miR-204\u0026ndash;\u003cem\u003eP2RY13\u003c/em\u003e. These findings elucidate potential molecular determinants of cold tolerance in Hezuo pigs.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec20\" class=\"Section2\"\u003e\n \u003ch2\u003e3.6 Validation of RNA-Seq Data by RT-qPCR\u003c/h2\u003e\n \u003cp\u003eTo validate the accuracy and reliability of the sequencing results, six DEmRNAs (\u003cem\u003eNAGS\u003c/em\u003e, \u003cem\u003ePIK3C2G\u003c/em\u003e, \u003cem\u003eDDX58\u003c/em\u003e, \u003cem\u003eCYP2A19\u003c/em\u003e, \u003cem\u003eMBL1\u003c/em\u003e and \u003cem\u003eBBOX1\u003c/em\u003e), three DElncRNAs (MSTRG.7463.1, MSTRG.15052.4 and MSTRG.6794.1), three DEcircRNAs (circ_023716, circ_000082 and circ_008930), and three DEmiRNAs (ssc-miR-29b, ssc-miR-9843-3p and ssc-miR-129b) were randomly selected, and their expression levels were detected using RT-qPCR. As shown in the figure, comparison with the sequencing data revealed consistent expression trends, indicating that the sequencing results are accurate and reliable.\u003c/p\u003e\n\u003c/div\u003e"},{"header":"4 Discussion","content":"\u003cp\u003eCold stress is one of the critical environmental factors affecting the health and production performance of livestock and poultry [\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e]. Under low-temperature conditions, livestock and poultry need to increase energy metabolism and adjust physiological functions to maintain body temperature[\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e, \u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e, \u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e]. This study compared serum liver function indicators, liver histopathological characteristics, and glucose metabolism changes in Hezuo pigs (HZ) and Bama pigs (BM) under normal and cold stress conditions at different treatment durations, revealing the physiological adaptation mechanisms and differences between the two pig breeds under cold stress. The study found that cold stress induces increased hepatic oxidative stress and inflammatory responses, leading to the accumulation of reactive oxygen species (ROS), which subsequently causes liver damage [\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e, \u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e]. Serum ALT and AST are commonly used biomarkers for liver health [\u003cspan additionalcitationids=\"CR59\" citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e]. In this study, with prolonged cold stress, the concentrations of ALT, AST, and LDH in Bama pigs significantly increased, peaking at 20 days, which may be related to cold stress-induced oxidative stress and inflammatory responses, indicating more severe hepatocyte damage in Bama pigs under long-term cold stress. In contrast, the transaminase levels in Hezuo pigs remained relatively stable, and the ALP concentration significantly decreased at 20 days, which may be attributed to Hezuo pigs' unique low-temperature metabolic regulation and cellular protection mechanisms. Liu et al. [\u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e61\u003c/span\u003e] found that cold stress promoted hepatocyte apoptosis in juvenile fish, leading to increased serum ALT and AST levels, which is consistent with our findings. α-SMA (α-smooth muscle actin) is a protein expressed in various cell types, particularly in activated hepatic stellate cells (HSCs). When the liver is injured, HSCs are activated and transform into myofibroblast-like cells, leading to a significant increase in α-SMA expression [\u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e62\u003c/span\u003e]. In this study, with prolonged cold stress, the expression of α-SMA protein in the livers of both pig breeds significantly increased. At 15 days, the positive area of α-SMA protein expression in Bama pigs was significantly higher than in Hezuo pigs, indicating a higher degree of HSC activation and greater risk of liver fibrosis in Bama pigs. In contrast, Hezuo pigs exhibited lower α-SMA protein expression. The above results suggest that during the initial phase of cold stress, animals may undergo an adaptation period, during which the body attempts to cope with the low-temperature environment through various physiological mechanisms [\u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e63\u003c/span\u003e, \u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e64\u003c/span\u003e]. By 15 days, the physiological state of the animals may begin to show the cumulative effects of cold stress [\u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e65\u003c/span\u003e]. Mitochondrial swelling is a significant marker of cellular damage, often associated with oxidative stress and energy metabolism imbalance [\u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e66\u003c/span\u003e, \u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e67\u003c/span\u003e]. Cold stress can activate endoplasmic reticulum stress, leading to mitochondrial dysfunction and further exacerbating liver damage [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. In this study, through HE staining and transmission electron microscopy, significant pathological changes were observed in the liver tissue of Bama pigs after 15 days of cold stress, including reduced intercellular space, decreased binucleated hepatocytes, cytoplasmic condensation, and mitochondrial swelling, indicating energy metabolism disorder and aggravated oxidative stress. In contrast, Hezuo pigs exhibited milder liver tissue damage and relatively normal mitochondrial morphology, suggesting stronger cellular protection capabilities and an efficient antioxidant system under cold stress [\u003cspan citationid=\"CR68\" class=\"CitationRef\"\u003e68\u003c/span\u003e]. Additionally, cold stress affects hepatic glucose metabolism [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e, \u003cspan additionalcitationids=\"CR70\" citationid=\"CR69\" class=\"CitationRef\"\u003e69\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR71\" class=\"CitationRef\"\u003e71\u003c/span\u003e]. Studies have shown that cold stress accelerates glucose consumption in animals [\u003cspan citationid=\"CR72\" class=\"CitationRef\"\u003e72\u003c/span\u003e, \u003cspan citationid=\"CR73\" class=\"CitationRef\"\u003e73\u003c/span\u003e], and animals with higher glucose content exhibit greater cold stress tolerance [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e, \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]. After cold stress, both pig breeds showed significant decreases in blood glucose and liver glycogen levels, but Hezuo pigs had significantly higher liver glycogen reserves than Bama pigs, as further confirmed by PAS staining results. This difference may be related to the genetic background and metabolic regulation mechanisms of the two pig breeds.\u003c/p\u003e\u003cp\u003eTo further explore the molecular regulatory mechanisms underlying the anti-damage response in Hezuo pig livers under cold stress, the 15-day cold-treated groups of Hezuo and Bama pigs, along with their respective normal temperature control groups, were selected for high-throughput sequencing analysis of liver mRNA, lncRNA, circRNA, and miRNA expression differences, revealing the molecular regulatory mechanisms and cold tolerance differences between the two pig breeds under cold stress. Through the analysis of sequencing data from 12 samples, high-quality transcriptomic data (Q20\u0026thinsp;\u0026gt;\u0026thinsp;96.52%, Q30\u0026thinsp;\u0026gt;\u0026thinsp;90.79%) were obtained, providing a reliable data foundation for subsequent functional analysis.\u003c/p\u003e\u003cp\u003eGO and KEGG analyses revealed that Bama pigs under cold stress were significantly enriched in amino acid metabolism (e.g., \"arginine biosynthesis\") and glutathione metabolism-related pathways, suggesting that cold stress activates amino acid metabolism processes [\u003cspan citationid=\"CR74\" class=\"CitationRef\"\u003e74\u003c/span\u003e] and may be accompanied by insufficient antioxidant capacity. This finding is highly consistent with the metabolic functions of brown adipose tissue (BAT) under cold stress. Studies have shown that BAT provides nitrogen sources by breaking down branched-chain amino acids (BCAAs) to synthesize non-essential amino acids and glutathione, thereby maintaining systemic glucose homeostasis and antioxidant capacity [\u003cspan citationid=\"CR75\" class=\"CitationRef\"\u003e75\u003c/span\u003e]. Simultaneously, the significant enrichment of the ECM-receptor interaction pathway indicates an increased risk of liver fibrosis in Bama pigs, consistent with the histopathological changes observed in liver tissue through HE staining and transmission electron microscopy. Cold stress enhances lipid metabolism and antioxidant levels in livestock and poultry [\u003cspan additionalcitationids=\"CR77\" citationid=\"CR76\" class=\"CitationRef\"\u003e76\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR78\" class=\"CitationRef\"\u003e78\u003c/span\u003e]. In contrast, GO analysis of Hezuo pigs under cold stress showed significant enrichment in \"lipid biosynthetic processes\" and \"oxidoreductase activity,\" while KEGG results indicated significant enrichment in peroxisome and PPAR signaling pathways. This suggests that Hezuo pigs may effectively cope with cold stress by enhancing peroxisome function and lipid metabolism, maintaining cellular function. Additionally, Hezuo pigs exhibited stronger immune regulation capabilities, as evidenced by significant enrichment in \"T cell receptor signaling pathway\" and \"natural killer cell-mediated cytotoxicity,\" further supporting their anti-damage capacity under cold stress. The metabolic disorder and liver damage in Bama pigs may be related to their weaker antioxidant system and energy metabolism regulation, while Hezuo pigs demonstrated stronger cold tolerance through efficient metabolic adaptation and antioxidant mechanisms.\u003c/p\u003e\u003cp\u003eFinally, this study revealed the core regulatory roles of ssc-miR-204 and ssc-miR-29b in the cold stress response through ceRNA network analysis. Previous studies have shown that miR-204 is involved in regulating oxidative stress and apoptosis in the liver [\u003cspan citationid=\"CR79\" class=\"CitationRef\"\u003e79\u003c/span\u003e], while miR-29b plays an important role in liver fibrosis [\u003cspan citationid=\"CR80\" class=\"CitationRef\"\u003e80\u003c/span\u003e]. Potential target genes for these miRNAs comprise \u003cem\u003eCYP2A19\u003c/em\u003e, \u003cem\u003eCA3\u003c/em\u003e, \u003cem\u003eP2RY13\u003c/em\u003e, and \u003cem\u003eADORA2B\u003c/em\u003e. \u003cem\u003eCYP2A19\u003c/em\u003e, as an important member of the cytochrome P450 family, is primarily expressed in the liver and participates in the metabolism of various endogenous and exogenous compounds [\u003cspan additionalcitationids=\"CR82\" citationid=\"CR81\" class=\"CitationRef\"\u003e81\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR83\" class=\"CitationRef\"\u003e83\u003c/span\u003e]. \u003cem\u003eCA3\u003c/em\u003e (carbonic anhydrase 3) is a liver-specific protein that plays a crucial role in lipid metabolism, particularly in regulating hepatic de novo lipogenesis [\u003cspan citationid=\"CR84\" class=\"CitationRef\"\u003e84\u003c/span\u003e]. \u003cem\u003eP2RY13\u003c/em\u003e belongs to the purinergic receptor family and is a G protein-coupled receptor (GPCR) whose ligand is adenosine diphosphate (ADP). This receptor is widely expressed in adipose tissue, liver, and brain, regulating lipolysis and inflammatory responses to maintain metabolic homeostasis [\u003cspan citationid=\"CR85\" class=\"CitationRef\"\u003e85\u003c/span\u003e]. The \u003cem\u003eADORA2B\u003c/em\u003e gene encodes the adenosine A2B receptor, which also belongs to the GPCR superfamily and plays important roles in various physiological and pathological processes. Studies have shown that ADORA2B not only regulates cardiovascular function but also exerts hepatoprotective effects by modulating related signaling pathways in the liver, potentially protecting against various types of liver injury [\u003cspan citationid=\"CR86\" class=\"CitationRef\"\u003e86\u003c/span\u003e, \u003cspan citationid=\"CR87\" class=\"CitationRef\"\u003e87\u003c/span\u003e]. The study ultimately revealed that three circular RNAs (circ_023716, circ_008930, and circ_007918) can co-target and regulate the interaction between ssc-miR-29b and \u003cem\u003eCYP2A19\u003c/em\u003e, while circ_000082 was found to form a regulatory network with ssc-miR-204 and its target genes (\u003cem\u003eP2RY13\u003c/em\u003e, \u003cem\u003eADORA2B\u003c/em\u003e). Furthermore, the research identified a prominent lncRNA-mediated regulatory axis: MSTRG.7463.1\u0026ndash;ssc-miR-204\u0026ndash;P2RY13. Future research could further validate the specific mechanisms of these miRNAs and their target genes under cold stress through functional experiments.\u003c/p\u003e"},{"header":"5 Conclusion","content":"\u003cp\u003eThis study systematically elucidates the differences in cold tolerance between Hezuo pigs and Bama pigs and their underlying molecular regulatory mechanisms. Hezuo pigs exhibit stronger cold stress resistance, manifested by milder liver damage and higher hepatic glycogen reserves, which provide a crucial physiological basis for their adaptation to cold environments. Through high-throughput sequencing analysis, we identified 1,307 DEmRNAs, 320 DElncRNAs, 1,299 DEcircRNAs, and 162 DEmiRNAs, which are primarily involved in immune response, signal transduction, and metabolic regulation. Three key ceRNA axes were discovered: (1) (circ_023716/008930/007918)\u0026mdash;ssc-miR-29b\u0026mdash;CYP2A19; (2) circ_000082\u0026mdash;ssc-miR-204\u0026mdash;(P2RY13/ADORA2B); and (3) MSTRG.7463.1\u0026mdash;ssc-miR-204\u0026mdash;P2RY13. These findings not only provide novel molecular insights into cold tolerance divergence among pig breeds but also offer important theoretical foundations and molecular markers for cold-resistant breeding in modern swine production.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgment\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe are grateful to Guangzhou Genedenovo Biotechnology Co., Ltd for assisting in sequencing and bioinformatics analysis.\u0026nbsp;Additionally, we thank Hao Zhu, Kelin Song, Xiao Li, Yawei Lu, Jie Li, etc for their support in the experimental phase.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was supported by National Natural Science Foundation of China (U22A20507), Outstanding Postgraduate \u0026ldquo;Innovation Star\u0026rdquo; from the Education Department of Gansu Province (2022CXZXS-006); Animal Husbandry Pig Industry Technology Innovation Team Project of Gansu Agricultural University (GAU-XKTD-2022-25); Breeding of New Minshan Black Pig and Integrated Promotion of Key Technologies (22ZD6NA044).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCRediT authorship contribution statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eJihong Yan:\u003c/strong\u003e Writing\u0026ndash; review \u0026amp; editing, Writing\u0026ndash; original draft, Validation, Methodology, Investigation, Data curation. \u003cstrong\u003eYuran Tang:\u003c/strong\u003e Writing\u0026ndash; review \u0026amp; editing, Supervision, Methodology, Conceptualization. \u003cstrong\u003eShuangbao Gun:\u0026nbsp;\u003c/strong\u003eWriting\u0026ndash; review \u0026amp; editing, Methodology, Investigation, Funding acquisition, Conceptualization. \u003cstrong\u003ePengfei Wang:\u0026nbsp;\u003c/strong\u003eWriting\u0026ndash; review \u0026amp; editing, Supervision, Funding acquisition, Formal analysis, Conceptualization.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDeclaration of competing interest\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors have declared that no competing interest exists.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll data in this study are available from the lead contact upon request. Sequencing data have been deposited under GEO dataset accession number GSE295210 and GSE296226.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eLi W, Chen Y, Zhang Y, Zhao N, Zhang W, Shi M, et al. Transcriptome Analysis Revealed Potential Genes of Skeletal Muscle Thermogenesis in Mashen Pigs and Large White Pigs under Cold Stress. Int J Mol Sci. 2023;24(21).https://doi.org/10.3390/ijms242115534\u003c/li\u003e\n\u003cli\u003eToghiani S, Hay E, Fragomeni B, Rekaya R, Roberts AJ. Genotype by environment interaction in response to cold stress in a composite beef cattle breed. Animal. 2020;14(8):1576-87.https://doi.org/10.1017/s1751731120000531\u003c/li\u003e\n\u003cli\u003eWang D, Cheng X, Fang H, Ren Y, Li X, Ren W, et al. Effect of cold stress on ovarian \u0026amp; uterine microcirculation in rats and the role of endothelin system. Reprod Biol Endocrinol. 2020;18(1):29.https://doi.org/10.1186/s12958-020-00584-1\u003c/li\u003e\n\u003cli\u003eQi L, Bravo-Ureta BE, Cabrera VE. From cold to hot: Climatic effects and productivity in Wisconsin dairy farms. J Dairy Sci. 2015;98(12):8664-77.https://doi.org/10.3168/jds.2015-9536\u003c/li\u003e\n\u003cli\u003eWang Y, Xia L, Guo T, Heng C, Jiang L, Wang D, et al. Research Note: Metabolic changes and physiological responses of broilers in the final stage of growth exposed to different environmental temperatures. Poult Sci. 2020;99(4):2017-25.https://doi.org/10.1016/j.psj.2019.11.048\u003c/li\u003e\n\u003cli\u003eYoung BA. Cold stress as it affects animal production. J Anim Sci. 1981;52(1):154-63.https://doi.org/10.2527/jas1981.521154x\u003c/li\u003e\n\u003cli\u003eLe Dividich J, Noblet J. Colostrum intake and thermoregulation in the neonatal pig in relation to environmental temperature. Biol Neonate. 1981;40(3-4):167-74.https://doi.org/10.1159/000241486\u003c/li\u003e\n\u003cli\u003eIida R, Koketsu Y. Climatic factors associated with peripartum pig deaths during hot and humid or cold seasons. Prev Vet Med. 2014;115(3-4):166-72.https://doi.org/10.1016/j.prevetmed.2014.03.019\u003c/li\u003e\n\u003cli\u003eRamirez BC, Hayes MD, Condotta I, Leonard SM. Impact of housing environment and management on pre-/post-weaning piglet productivity. J Anim Sci. 2022;100(6).https://doi.org/10.1093/jas/skac142\u003c/li\u003e\n\u003cli\u003eYu J, Chen S, Zeng Z, Xing S, Chen D, Yu B, et al. Effects of Cold Exposure on Performance and Skeletal Muscle Fiber in Weaned Piglets. Animals (Basel). 2021;11(7).https://doi.org/10.3390/ani11072148\u003c/li\u003e\n\u003cli\u003eKelley KW, Blecha F, Regnier JA. Cold exposure and absorption of colostral immunoglobulins by neonatal pigs. J Anim Sci. 1982;55(2):363-8.https://doi.org/10.2527/jas1982.552363x\u003c/li\u003e\n\u003cli\u003eCobanovic N, Stajkovic S, Blagojevic B, Betic N, Dimitrijevic M, Vasilev D, et al. The effects of season on health, welfare, and carcass and meat quality of slaughter pigs. Int J Biometeorol. 2020;64(11):1899-909.https://doi.org/10.1007/s00484-020-01977-y\u003c/li\u003e\n\u003cli\u003eAlbert F, Kov\u0026aacute;cs-Weber M, Bodn\u0026aacute;r \u0026Aacute;, Pajor F, Egerszegi I. Seasonal Effects on the Performance of Finishing Pigs\u0026apos; Carcass and Meat Quality in Indoor Environments. Animals (Basel). 2024;14(2).https://doi.org/10.3390/ani14020259\u003c/li\u003e\n\u003cli\u003eZhang B, Qiangba Y, Shang P, Wang Z, Ma J, Wang L, et al. A Comprehensive MicroRNA Expression Profile Related to Hypoxia Adaptation in the Tibetan Pig. PLoS One. 2015;10(11).https://doi.org/10.1371/journal.pone.0143260\u003c/li\u003e\n\u003cli\u003eWang W, Yang Q, Xie K, Wang P, Luo R, Yan Z, et al. Transcriptional Regulation of HMOX1 Gene in Hezuo Tibetan Pigs: Roles of WT1, Sp1, and C/EBP alpha. Genes. 2020;11(4).https://doi.org/10.3390/genes11040352\u003c/li\u003e\n\u003cli\u003eYan J, Wang P, Yan Z, Yang Q, Huang X, Gao X, et al. Cloning of STC-1 and analysis of its differential expression in Hezuo pig. Anim Biotechnol. 2023;34(9):4687-94.https://doi.org/10.1080/10495398.2023.2186890\u003c/li\u003e\n\u003cli\u003eYan Z, Wang P, Yang Q, Gun S. Single-Cell RNA Sequencing Reveals an Atlas of Hezuo Pig Testis Cells. Int J Mol Sci. 2024;25(18).https://doi.org/10.3390/ijms25189786\u003c/li\u003e\n\u003cli\u003eYan Z, Song K, Wang P, Gun S, Long X. Evaluation of the Genetic Diversity and Population Structure of Four Native Pig Populations in Gansu Province. Int J Mol Sci. 2023;24(24).https://doi.org/10.3390/ijms242417154\u003c/li\u003e\n\u003cli\u003eSchmidt I, Herpin P. Carnitine palmitoyltransferase I (CPT I) activity and its regulation by malonyl-CoA are modulated by age and cold exposure in skeletal muscle mitochondria from newborn pigs. J Nutr. 1998;128(5):886-93.https://doi.org/10.1093/jn/128.5.886\u003c/li\u003e\n\u003cli\u003eNowack J, Vetter SG, Stalder G, Painer J, Kral M, Smith S, et al. Muscle nonshivering thermogenesis in a feral mammal. Sci Rep. 2019;9(1):6378.https://doi.org/10.1038/s41598-019-42756-z\u003c/li\u003e\n\u003cli\u003eZhang D, Ma S, Wang L, Ma H, Wang W, Xia J, et al. Min pig skeletal muscle response to cold stress. PLoS One. 2022;17(9):e0274184.https://doi.org/10.1371/journal.pone.0274184\u003c/li\u003e\n\u003cli\u003eYang C, Cao C, Liu J, Zhao Y, Pan J, Tao C, et al. Distinct Transcriptional Responses of Skeletal Muscle to Short-Term Cold Exposure in Tibetan Pigs and Bama Pigs. Int J Mol Sci. 2023;24(8).https://doi.org/10.3390/ijms24087431\u003c/li\u003e\n\u003cli\u003eZhang D, Wang L, Wang W, Liu D. The Role of lncRNAs in Pig Muscle in Response to Cold Exposure. Genes (Basel). 2023;14(10).https://doi.org/10.3390/genes14101901\u003c/li\u003e\n\u003cli\u003eYang S, Ma H, Wang L, Wang F, Xia J, Liu D, et al. The Role of \u0026beta;3-Adrenergic Receptors in Cold-Induced Beige Adipocyte Production in Pigs. Cells. 2024;13(8).https://doi.org/10.3390/cells13080709\u003c/li\u003e\n\u003cli\u003eLiu T, Guo Y, Lu C, Cai C, Gao P, Cao G, et al. Effect of Different Pig Fecal Microbiota Transplantation on Mice Intestinal Function and Microbiota Changes During Cold Exposure. Front Vet Sci. 2022;9:805815.https://doi.org/10.3389/fvets.2022.805815\u003c/li\u003e\n\u003cli\u003eZhang Y, Sun L, Zhu R, Zhang S, Liu S, Wang Y, et al. Porcine gut microbiota in mediating host metabolic adaptation to cold stress. NPJ Biofilms Microbiomes. 2022;8(1):18.https://doi.org/10.1038/s41522-022-00283-2\u003c/li\u003e\n\u003cli\u003eSun G, Song X, Zou Y, Teng T, Jiang L, Shi B. Dietary Glucose Ameliorates Impaired Intestinal Development and Immune Homeostasis Disorders Induced by Chronic Cold Stress in Pig Model. Int J Mol Sci. 2022;23(14).https://doi.org/10.3390/ijms23147730\u003c/li\u003e\n\u003cli\u003eYang Y, Chen N, Sun L, Zhang Y, Wu Y, Wang Y, et al. Short-term cold stress can reduce the abundance of antibiotic resistance genes in the cecum and feces in a pig model. J Hazard Mater. 2021;416:125868.https://doi.org/10.1016/j.jhazmat.2021.125868\u003c/li\u003e\n\u003cli\u003eTeng T, Yang H, Xu T, Sun G, Song X, Bai G, et al. Activation of Inflammatory Networks in the Lungs Caused by Chronic Cold Stress Is Moderately Attenuated by Glucose Supplementation. Int J Mol Sci. 2022;23(18).https://doi.org/10.3390/ijms231810697\u003c/li\u003e\n\u003cli\u003eSun G, Su W, Bao J, Teng T, Song X, Wang J, et al. Dietary full-fat rice bran prevents the risk of heart ferroptosis and imbalance of energy metabolism induced by prolonged cold stimulation. Food Funct. 2023;14(3):1530-44.https://doi.org/10.1039/d2fo03673h\u003c/li\u003e\n\u003cli\u003eTeng T, Zheng Y, Zhang M, Sun G, Li Z, Shi B, et al. Chronic cold stress promotes inflammation and ER stress via inhibiting GLP-1R signaling, and exacerbates the risk of ferroptosis in the liver and pancreas. Environ Pollut. 2024;360:124647.https://doi.org/10.1016/j.envpol.2024.124647\u003c/li\u003e\n\u003cli\u003eLiu Y, Xu B, Hu Y, Liu P, Lian S, Lv H, et al. O-GlcNAc / Akt pathway regulates glucose metabolism and reduces apoptosis in liver of piglets with acute cold stress. Cryobiology. 2021;100:125-32.https://doi.org/10.1016/j.cryobiol.2021.02.008\u003c/li\u003e\n\u003cli\u003eWang X, Yang J, Li H, Mu H, Zeng L, Cai S, et al. miR-484 mediates oxidative stress-induced ovarian dysfunction and promotes granulosa cell apoptosis via SESN2 downregulation. Redox Biol. 2023;62:102684.https://doi.org/10.1016/j.redox.2023.102684\u003c/li\u003e\n\u003cli\u003eCheng Q, Wang J, Li M, Fang J, Ding H, Meng J, et al. CircSV2b participates in oxidative stress regulation through miR-5107-5p-Foxk1-Akt1 axis in Parkinson\u0026apos;s disease. Redox Biol. 2022;56:102430.https://doi.org/10.1016/j.redox.2022.102430\u003c/li\u003e\n\u003cli\u003eQuan J, Zhao G, Liu Z, Li L, Lu J, Song G, et al. Competing endogenous RNA (ceRNA) in a non-model animal: Non-coding RNAs respond to heat stress in rainbow trout (Oncorhynchus mykiss) through ceRNA-regulated mechanisms. Int J Biol Macromol. 2023;239:124246.https://doi.org/10.1016/j.ijbiomac.2023.124246\u003c/li\u003e\n\u003cli\u003eChen J, Dai X, Xing C, Zhang Y, Cao H, Hu G, et al. Cooperative application of transcriptomics and ceRNA hypothesis: lncRNA-00742/miR-116 targets CD74 to mediate vanadium-induced mitochondrial apoptosis in duck liver. J Hazard Mater. 2024;480:135904.https://doi.org/10.1016/j.jhazmat.2024.135904\u003c/li\u003e\n\u003cli\u003eWang Z, Zhao Y, Sun R, Sun Y, Liu D, Lin M, et al. circ-CBFB upregulates p66Shc to perturb mitochondrial dynamics in APAP-induced liver injury. Cell Death Dis. 2020;11(11):953.https://doi.org/10.1038/s41419-020-03160-y\u003c/li\u003e\n\u003cli\u003eWick MR. The hematoxylin and eosin stain in anatomic pathology-An often-neglected focus of quality assurance in the laboratory. Semin Diagn Pathol. 2019;36(5):303-11.https://doi.org/10.1053/j.semdp.2019.06.003\u003c/li\u003e\n\u003cli\u003eZakout YM, Abdellah MA, Abdallah MA, Batran SA. Optimization of PAS stain and similar Schiff\u0026apos;s based methods for glycogen demonstration in liver tissue. Histochem Cell Biol. 2024;161(4):359-64.https://doi.org/10.1007/s00418-023-02261-x\u003c/li\u003e\n\u003cli\u003eChen S, Zhou Y, Chen Y, Gu J. fastp: an ultra-fast all-in-one FASTQ preprocessor. Bioinformatics. 2018;34(17):i884-i90.https://doi.org/10.1093/bioinformatics/bty560\u003c/li\u003e\n\u003cli\u003eLangmead B, Salzberg SL. Fast gapped-read alignment with Bowtie 2. Nat Methods. 2012;9(4):357-9.https://doi.org/10.1038/nmeth.1923\u003c/li\u003e\n\u003cli\u003eKim D, Langmead B, Salzberg SL. HISAT: a fast spliced aligner with low memory requirements. Nat Methods. 2015;12(4):357-60.https://doi.org/10.1038/nmeth.3317\u003c/li\u003e\n\u003cli\u003ePertea M, Pertea GM, Antonescu CM, Chang TC, Mendell JT, Salzberg SL. StringTie enables improved reconstruction of a transcriptome from RNA-seq reads. Nat Biotechnol. 2015;33(3):290-5.https://doi.org/10.1038/nbt.3122\u003c/li\u003e\n\u003cli\u003ePertea M, Kim D, Pertea GM, Leek JT, Salzberg SL. Transcript-level expression analysis of RNA-seq experiments with HISAT, StringTie and Ballgown. Nat Protoc. 2016;11(9):1650-67.https://doi.org/10.1038/nprot.2016.095\u003c/li\u003e\n\u003cli\u003eTrapnell C, Williams BA, Pertea G, Mortazavi A, Kwan G, van Baren MJ, et al. Transcript assembly and quantification by RNA-Seq reveals unannotated transcripts and isoform switching during cell differentiation. Nat Biotechnol. 2010;28(5):511-5.https://doi.org/10.1038/nbt.1621\u003c/li\u003e\n\u003cli\u003eKong L, Zhang Y, Ye ZQ, Liu XQ, Zhao SQ, Wei L, et al. CPC: assess the protein-coding potential of transcripts using sequence features and support vector machine. Nucleic Acids Res. 2007;35(Web Server issue):W345-9.https://doi.org/10.1093/nar/gkm391\u003c/li\u003e\n\u003cli\u003eSun L, Luo H, Bu D, Zhao G, Yu K, Zhang C, et al. Utilizing sequence intrinsic composition to classify protein-coding and long non-coding transcripts. Nucleic Acids Res. 2013;41(17):e166.https://doi.org/10.1093/nar/gkt646\u003c/li\u003e\n\u003cli\u003eZhang J, Chen S, Yang J, Zhao F. Accurate quantification of circular RNAs identifies extensive circular isoform switching events. Nat Commun. 2020;11(1):90.https://doi.org/10.1038/s41467-019-13840-9\u003c/li\u003e\n\u003cli\u003eFriedl\u0026auml;nder MR, Mackowiak SD, Li N, Chen W, Rajewsky N. miRDeep2 accurately identifies known and hundreds of novel microRNA genes in seven animal clades. Nucleic Acids Res. 2012;40(1):37-52.https://doi.org/10.1093/nar/gkr688\u003c/li\u003e\n\u003cli\u003eLove MI, Huber W, Anders S. Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol. 2014;15(12):550.https://doi.org/10.1186/s13059-014-0550-8\u003c/li\u003e\n\u003cli\u003eKanehisa M, Araki M, Goto S, Hattori M, Hirakawa M, Itoh M, et al. KEGG for linking genomes to life and the environment. Nucleic Acids Res. 2008;36(Database issue):D480-4.https://doi.org/10.1093/nar/gkm882\u003c/li\u003e\n\u003cli\u003eLivak KJ, Schmittgen TD. Analysis of relative gene expression data using real-time quantitative PCR and the 2(-Delta Delta C(T)) Method. Methods. 2001;25(4):402-8.https://doi.org/10.1006/meth.2001.1262\u003c/li\u003e\n\u003cli\u003eChang J, Pan Y, Liu W, Xie Y, Hao W, Xu P, et al. Acute temperature adaptation mechanisms in the native reptile species Eremias argus. Sci Total Environ. 2022;818:151773.https://doi.org/10.1016/j.scitotenv.2021.151773\u003c/li\u003e\n\u003cli\u003eBornstein MR, Neinast MD, Zeng X, Chu Q, Axsom J, Thorsheim C, et al. Comprehensive quantification of metabolic flux during acute cold stress in mice. Cell Metab. 2023;35(11):2077-92.e6.https://doi.org/10.1016/j.cmet.2023.09.002\u003c/li\u003e\n\u003cli\u003eMota CMD, Madden CJ. Neural circuits of long-term thermoregulatory adaptations to cold temperatures and metabolic demands. Nat Rev Neurosci. 2024;25(3):143-58.https://doi.org/10.1038/s41583-023-00785-8\u003c/li\u003e\n\u003cli\u003eGuo JR, Nie JS, Chen Z, Wang X, Hu HJ, Xu J, et al. Cold exposure-induced endoplasmic reticulum stress regulates autophagy through the SIRT2/FoxO1 signaling pathway. Journal of Cellular Physiology. 2022;237(10):3960-70.https://doi.org/10.1002/jcp.30856\u003c/li\u003e\n\u003cli\u003eHuang Y, Xiong K, Wang A, Wang Z, Cui Q, Xie H, et al. Cold stress causes liver damage by inducing ferroptosis through the p38 MAPK/Drp1 pathway. Cryobiology. 2023;113:104563.https://doi.org/10.1016/j.cryobiol.2023.104563\u003c/li\u003e\n\u003cli\u003eGao C, Marcketta A, Backman JD, O\u0026apos;Dushlaine C, Staples J, Ferreira MAR, et al. Genome-wide association analysis of serum alanine and aspartate aminotransferase, and the modifying effects of BMI in 388k European individuals. Genet Epidemiol. 2021;45(6):664-81.https://doi.org/10.1002/gepi.22392\u003c/li\u003e\n\u003cli\u003eKew MC. Serum aminotransferase concentration as evidence of hepatocellular damage. Lancet. 2000;355(9204):591-2.https://doi.org/10.1016/s0140-6736(99)00219-6\u003c/li\u003e\n\u003cli\u003eXu L, Yu Y, Sang R, Li J, Ge B, Zhang X. Protective Effects of Taraxasterol against Ethanol-Induced Liver Injury by Regulating CYP2E1/Nrf2/HO-1 and NF-\u0026kappa;B Signaling Pathways in Mice. Oxid Med Cell Longev. 2018;2018:8284107.https://doi.org/10.1155/2018/8284107\u003c/li\u003e\n\u003cli\u003eLiu T, Li L, Yang Y, Li J, Yang X, Li L, et al. Effects of chronic cold stress and thermal stress on growth performance, hepatic apoptosis, oxidative stress, immune response and gut microbiota of juvenile hybrid sturgeon (Acipenser baerii ? \u0026times; A. schrenkii ?). Fish Shellfish Immunol. 2025;157:110078.https://doi.org/10.1016/j.fsi.2024.110078\u003c/li\u003e\n\u003cli\u003eBates J, Vijayakumar A, Ghoshal S, Marchand B, Yi S, Kornyeyev D, et al. Acetyl-CoA carboxylase inhibition disrupts metabolic reprogramming during hepatic stellate cell activation. J Hepatol. 2020;73(4):896-905.https://doi.org/10.1016/j.jhep.2020.04.037\u003c/li\u003e\n\u003cli\u003eKeipert S, Gaudry MJ, Kutschke M, Keuper M, Dela Rosa MAS, Cheng Y, et al. Two-stage evolution of mammalian adipose tissue thermogenesis. Science. 2024;384(6700):1111-7.https://doi.org/10.1126/science.adg1947\u003c/li\u003e\n\u003cli\u003eRafnsdottir S, Jang K, Halldorsdottir ST, Vinod M, Tomasdottir A, M\u0026ouml;ller K, et al. SMYD5 is a regulator of the mild hypothermia response. Cell Rep. 2024;43(8):114554.https://doi.org/10.1016/j.celrep.2024.114554\u003c/li\u003e\n\u003cli\u003eLyte JM, Eckenberger J, Keane J, Robinson K, Bacon T, Assumpcao A, et al. Cold stress initiates catecholaminergic and serotonergic responses in the chicken gut that are associated with functional shifts in the microbiome. Poult Sci. 2024;103(3):103393.https://doi.org/10.1016/j.psj.2023.103393\u003c/li\u003e\n\u003cli\u003eZhang M, Zhou W, Cao Y, Kou L, Liu C, Li X, et al. O-GlcNAcylation regulates long-chain fatty acid metabolism by inhibiting ACOX1 ubiquitination-dependent degradation. Int J Biol Macromol. 2024;266(Pt 2):131151.https://doi.org/10.1016/j.ijbiomac.2024.131151\u003c/li\u003e\n\u003cli\u003eIto R, Xie S, Tumenjargal M, Sugahara Y, Yang C, Takahashi H, et al. Mitochondrial biogenesis in white adipose tissue mediated by JMJD1A-PGC-1 axis limits age-related metabolic disease. iScience. 2024;27(4):109398.https://doi.org/10.1016/j.isci.2024.109398\u003c/li\u003e\n\u003cli\u003eShin YC, Latorre-Muro P, Djurabekova A, Zdorevskyi O, Bennett CF, Burger N, et al. Structural basis of respiratory complex adaptation to cold temperatures. Cell. 2024;187(23):6584-98.e17.https://doi.org/10.1016/j.cell.2024.09.029\u003c/li\u003e\n\u003cli\u003eLiu P, Yao RZ, Shi HZ, Liu Y, Lian S, Yang YY, et al. Effects of Cold-inducible RNA-binding Protein (CIRP) on Liver Glycolysis during Acute Cold Exposure in C57BL/6 Mice. International Journal of Molecular Sciences. 2019;20(6).https://doi.org/10.3390/ijms20061470\u003c/li\u003e\n\u003cli\u003eLiu QF, Zhou ZY, Liu PS, Zhang SY. Comparative proteomic study of liver lipid droplets and mitochondria in mice housed at different temperatures. Febs Letters. 2019;593(16):2118-38.https://doi.org/10.1002/1873-3468.13509\u003c/li\u003e\n\u003cli\u003eShi HZ, Yao RZ, Lian S, Liu P, Liu Y, Yang YY, et al. Regulating glycolysis, the TLR4 signal pathway and expression of RBM3 in mouse liver in response to acute cold exposure. Stress-the International Journal on the Biology of Stress. 2019;22(3):366-76.https://doi.org/10.1080/10253890.2019.1568987\u003c/li\u003e\n\u003cli\u003eRaun SH, Braun JL, Karavaeva I, Henriquez-Olgu\u0026iacute;n C, Ali MS, M\u0026oslash;ller LLV, et al. Mild Cold Stress at Ambient Temperature Elevates Muscle Calcium Cycling and Exercise Adaptations in Obese Female Mice. Endocrinology. 2024;165(10).https://doi.org/10.1210/endocr/bqae102\u003c/li\u003e\n\u003cli\u003eSu D, Song Y, Li D, Yang S, Zhan S, Zhong T, et al. Cold exposure affects glucose metabolism, lipid droplet deposition and mitophagy in skeletal muscle of newborn goats. Domest Anim Endocrinol. 2024;88:106847.https://doi.org/10.1016/j.domaniend.2024.106847\u003c/li\u003e\n\u003cli\u003eXue C, Zhu S, Li Y, Chen X, Lu L, Su P, et al. Cold exposure accelerates lysine catabolism to promote cold acclimation via remodeling hepatic histone crotonylation. Environ Int. 2024;192:109015.https://doi.org/10.1016/j.envint.2024.109015\u003c/li\u003e\n\u003cli\u003eVerkerke ARP, Wang D, Yoshida N, Taxin ZH, Shi X, Zheng S, et al. BCAA-nitrogen flux in brown fat controls metabolic health independent of thermogenesis. Cell. 2024;187(10):2359-74.e18.https://doi.org/10.1016/j.cell.2024.03.030\u003c/li\u003e\n\u003cli\u003eZhang S, Liu Y, Chai Y, Xing L, Li J. Effects of intermittent cold stimulation on growth performance, meat quality, antioxidant capacity and liver lipid metabolism in broiler chickens. Poult Sci. 2024;103(3):103442.https://doi.org/10.1016/j.psj.2024.103442\u003c/li\u003e\n\u003cli\u003eMouisel E, Bodon A, Noll C, Cassant-Sourdy S, Marques MA, Flores-Flores R, et al. Cold-induced thermogenesis requires neutral-lipase-mediated intracellular lipolysis in brown adipocytes. Cell Metab. 2025;37(2):429-40.e5.https://doi.org/10.1016/j.cmet.2024.10.018\u003c/li\u003e\n\u003cli\u003eMin H, Yang YY, Yang Y. Cold induces brain region-selective cell activity-dependent lipid metabolism. Elife. 2025;13.https://doi.org/10.7554/eLife.98353\u003c/li\u003e\n\u003cli\u003eZou Z, Liu X, Yu J, Ban T, Zhang Z, Wang P, et al. Nuclear miR-204-3p mitigates metabolic dysfunction-associated steatotic liver disease in mice. J Hepatol. 2024;80(6):834-45.https://doi.org/10.1016/j.jhep.2024.01.029\u003c/li\u003e\n\u003cli\u003eSohail A, Shams F, Nawaz A, Ain QU, Ijaz B. Antifibrotic potential of reserpine (alkaloid) targeting Keap1/Nrf2; oxidative stress pathway in CCl(4)-induced liver fibrosis. Chem Biol Interact. 2025;407:111384.https://doi.org/10.1016/j.cbi.2025.111384\u003c/li\u003e\n\u003cli\u003eAchour B, Barber J, Rostami-Hodjegan A. Cytochrome P450 Pig liver pie: determination of individual cytochrome P450 isoform contents in microsomes from two pig livers using liquid chromatography in conjunction with mass spectrometry [corrected]. Drug Metab Dispos. 2011;39(11):2130-4.https://doi.org/10.1124/dmd.111.040618\u003c/li\u003e\n\u003cli\u003eBurkina V, Zlabek V, Rasmussen MK, Zamaratskaia G. End-product inhibition of skatole-metabolising enzymes CYP1A, CYP2A19 and CYP2E1 in porcine and piscine hepatic microsomes. Toxicol Lett. 2019;303:67-71.https://doi.org/10.1016/j.toxlet.2018.12.017\u003c/li\u003e\n\u003cli\u003eWang Z, Huang Q, Zhang F, Wu J, Wang L, Sun Y, et al. Key Role of Porcine Cytochrome P450 2A19 in the Bioactivation of Aflatoxin B(1) in the Liver. J Agric Food Chem. 2024;72(4):2334-46.https://doi.org/10.1021/acs.jafc.3c08663\u003c/li\u003e\n\u003cli\u003eLiu D, Wong CC, Zhou Y, Li C, Chen H, Ji F, et al. Squalene Epoxidase Induces Nonalcoholic Steatohepatitis Via Binding to Carbonic Anhydrase III and is a Therapeutic Target. Gastroenterology. 2021;160(7):2467-82.e3.https://doi.org/10.1053/j.gastro.2021.02.051\u003c/li\u003e\n\u003cli\u003eDuparc T, Gore E, Combes G, Beuzelin D, Pires Da Silva J, Bouguetoch V, et al. P2Y13 receptor deficiency favors adipose tissue lipolysis and worsens insulin resistance and fatty liver disease. JCI Insight. 2024;9(8).https://doi.org/10.1172/jci.insight.175623\u003c/li\u003e\n\u003cli\u003eSmith K. Transplantation: ADORA2B helps to block liver injury. Nat Rev Gastroenterol Hepatol. 2013;10(8):444.https://doi.org/10.1038/nrgastro.2013.129\u003c/li\u003e\n\u003cli\u003eZimmerman MA, Grenz A, Tak E, Kaplan M, Ridyard D, Brodsky KS, et al. Signaling through hepatocellular A2B adenosine receptors dampens ischemia and reperfusion injury of the liver. Proc Natl Acad Sci U S A. 2013;110(29):12012-7.https://doi.org/10.1073/pnas.1221733110\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Hezuo pig, Bama pig, Cold stress, RNA-Seq, Liver injury","lastPublishedDoi":"10.21203/rs.3.rs-7481559/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7481559/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e\u003cp\u003eCold stress is a critical environmental factor that adversely affects the production performance and health status of livestock and poultry. To explore the physiological adaptation mechanisms underlying cold resistance differences among pig breeds, this study employed cold-resistant Hezuo pigs and cold-sensitive Bama pigs as models, systematically comparing liver injury phenotypes and molecular response characteristics after 5, 10, 15, and 20 days of cold exposure at -15\u0026deg;C.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e\u003cp\u003eThe results demonstrated that: 1) After 20 days of cold stress, serum liver function markers (ALT, AST, LDH) in Bama pigs were significantly elevated (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05), while remaining stable in Tibetan pigs. 2) Histological analysis revealed that the α-SMA-positive area in Bama pig livers increased significantly with prolonged cold exposure (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05), exceeding that of Tibetan pigs from day 15 onward. 3) Morphological observations showed that Bama pigs developed ear frostbite and liver surface congestion after 15 days of cold stress, whereas Tibetan pigs maintained normal appearances. 4) Ultrastructural analysis indicated mitochondrial swelling and nuclear membrane abnormalities in Bama pig hepatocytes, while Tibetan pigs exhibited relatively normal cellular structures. 5) High-throughput sequencing identified 1,307 differentially expressed mRNAs (DEmRNAs), 320 DElncRNAs, 1,299 DEcircRNAs, and 162 DEmiRNAs in liver tissues between the two breeds under cold stress. Functional enrichment analysis revealed that in Bama pigs, DEmRNAs were primarily involved in metabolic processes, oxidative stress, and liver fibrosis-related pathways, whereas in Tibetan pigs they were enriched in metabolic and antioxidant-related biological processes. RT-qPCR validation confirmed the accuracy and reliability of the sequencing results. Finally, we constructed ceRNA regulatory networks to illustrate their potential roles in the anti-damage mechanisms of Tibetan pig livers.\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e\u003cp\u003eCollectively, Bama pigs exhibited greater sensitivity to cold stress with more severe liver damage, while Tibetan pigs demonstrated superior cold tolerance. Three key ceRNA networks were identified as potentially crucial in the cold resistance mechanisms of Tibetan pigs: (circ_023716/008930/007918)\u0026mdash;ssc-miR-29b\u0026mdash;CYP2A19; circ_000082\u0026mdash;ssc-miR-204\u0026mdash;(P2RY13/ADORA2B); and MSTRG.7463.1\u0026mdash;ssc-miR-204\u0026mdash;P2RY13. This study systematically elucidates the phenotypic characteristics and molecular basis of cold adaptation in Tibetan pigs, providing not only novel insights into animal environmental adaptation evolution but also important theoretical foundations and candidate molecular targets for livestock stress-resistant breeding.\u003c/p\u003e","manuscriptTitle":"Anti-injury Mechanisms in the Liver and its Molecular Regulatory Networks of the Hezuo Pig under Cold Stress","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-09-09 13:16:36","doi":"10.21203/rs.3.rs-7481559/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"25120b4e-ed29-4a31-9aab-e6ad68a33fee","owner":[],"postedDate":"September 9th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-11-12T09:38:59+00:00","versionOfRecord":[],"versionCreatedAt":"2025-09-09 13:16:36","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7481559","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7481559","identity":"rs-7481559","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}