Method for analyzing influence of heat stress on meat quality of pig muscles

Abstract

The invention relates to the technical field of livestock and poultry breeding, in particular to a method for analyzing the influence of heat stress on the meat quality of pig muscles. The analysis method comprises the following steps: dividing pig breeds into a room temperature group, a heat stress group and a paired feeding group, respectively feeding the pig breeds, taking skeletal muscles of all groups of pig breeds, and detecting skeletal muscle meat quality indexes; performing transcriptome sequencing and analysis on skeletal muscles of all pig breeds; carrying out metabolome sequencing and analysis on skeletal muscles of all groups of pig breeds; carrying out conjoint analysis on the obtained transcriptome sequencing analysis result and metabolome sequencing analysis result; finally, key genes and metabolites influencing pork quality are obtained by combining skeletal muscle meat quality indexes and conjoint analysis results. According to the invention, the influence of heat stress on skeletal muscle gene expression and metabolite synthesis and potential reasons for meat quality change are analyzed, and a theoretical basis is provided for screening of stress-resistant breeding molecular markers and development of functional feed additives.

Description

Technical Field

[0001] This invention relates to the field of livestock and poultry breeding technology, specifically to an analytical method for the effects of heat stress on the meat quality of pig muscle. Background Technology

[0002] Heat stress refers to the physiological state that occurs when the balance between heat production and heat dissipation in an animal is disrupted, making it unable to maintain a normal body temperature. Ruminants, pigs, and poultry are particularly sensitive to heat stress, primarily due to their rapid metabolic rates, high levels of productivity, and species-specific characteristics such as ruminant fermentation, inadequate sweat gland function, and skin insulation. Heat stress not only involves animal welfare issues but also causes significant economic losses to livestock farming, including decreased growth rates, reduced fertility, increased veterinary costs, inconsistent slaughter performance, and decreased market weight. With global climate change, heat stress has become one of the most important environmental factors affecting livestock production.

[0003] Heat stress is increasingly damaging to my country's pig industry. High temperatures can trigger oxidative stress, metabolic disorders, and endocrine imbalances in pigs, leading to decreased growth performance, reduced feed conversion ratio, and severely impacting pork quality, such as decreased muscle pH, increased drip loss, and reduced intramuscular fat content. Currently, the key genes, molecular pathways, and metabolic regulatory networks by which heat stress affects pork quality remain unclear, and systematic research on gene-metabolism interactions is lacking. Summary of the Invention

[0004] This invention, using superior local pig breeds in my country as examples, studies the effects of heat stress on pork quality, analyzes relevant differentially expressed genes and metabolites, and provides an analytical method for the impact of heat stress on pig muscle quality. This research can provide a theoretical basis for stress-resistant breeding and the development of functional feed additives. The technical solution of this invention is as follows: In a first aspect, the present invention provides an analytical method for the effect of heat stress on the meat quality of pig muscle, comprising the following steps: Step 1: Divide the pigs into a room temperature group, a heat stress group, and a paired feeding group. Place the heat stress group in an environment of 34-36℃ and 65%-75% relative humidity, and feed the room temperature group and the paired feeding group in an environment of 24-26℃ and 65%-75% relative humidity for a period of time. Step 2: Collect skeletal muscle samples from all groups of pigs and test skeletal muscle quality indicators; Step 3: Perform transcriptome sequencing and analysis on the skeletal muscle of all groups of pigs to obtain transcriptome sequencing analysis results; Step 4: Perform metabolomics sequencing and analysis on the skeletal muscle of all groups of pigs to obtain the metabolomics sequencing analysis results; Step 5: Perform joint analysis on the obtained transcriptome sequencing analysis results and metabolome sequencing analysis results to obtain joint analysis results; Step 6: Combine skeletal muscle mass indicators and joint analysis results to obtain key genes and metabolites that affect pork quality.

[0005] Preferably, in step 1, the feeding time is not less than 7 days.

[0006] Preferably, in step 2, the skeletal muscle is the longissimus dorsi muscle; and / or, the skeletal muscle quality indicators include flesh color, pH value, drip loss, electrical conductivity, water content, water-holding capacity, intramuscular fat content, and tenderness.

[0007] Preferably, in step 3, the transcriptome sequencing analysis includes at least sequencing result quality control, differential gene function enrichment analysis, differential gene screening and cluster analysis, common differentially expressed gene function enrichment analysis, and RT-qPCR verification analysis.

[0008] Preferably, in step 4, the metabolomics sequencing is performed using ultra-high performance liquid chromatography combined with mass spectrometry; more preferably, the mobile phase system used in the ultra-high performance liquid chromatography consists of: phase A being an aqueous solution containing 0.1% formic acid, and phase B being an acetonitrile organic phase containing 0.1% formic acid; the gradient program is executed according to the following timing sequence: For 0-2 minutes, maintain the proportion of phase B at 0% and phase A at 100%. Over 2-6 minutes, the concentration of phase B increased linearly to 48%, while the concentration of phase A decreased linearly to 52%. Over 6-10 minutes, the concentration of phase B increases linearly to 100%, while the concentration of phase A decreases linearly to 0% and remains there for 12 minutes; and / or, The mass spectrometer uses a HESI ion source, and the core ionization parameters include: dual-mode spray voltage of 3.8 kV (+) / 3.2 kV (-); capillary temperature of 300~340℃; sheath gas and auxiliary gas flow rates of 25~30 arb and 3~6 arb, respectively; ion transport channel RF field strength (S-Lens RF Level) adjusted to 50±5%; and ion source heating module operating temperature of 340~360℃. Preferably, the primary mass spectrometry workflow is as follows: mass scan range covering 75-1050 mass-to-charge ratio (m / z); resolution set to 70,000 (@m / z 200); automatic gain control target (AGC target) set to 3×10^6; maximum injection time (Maximum IT) limited to 100 ms; dynamic secondary mass spectrometry strategy: real-time triggering of Top 10 high-abundance precursor ion fragmentation based on full scan mode; secondary resolution of 17,500 (@m / z 200); AGC target. The optimal configuration is 1×10⁵ with a 50ms injection time; high-energy collision dissociation (HCD) technology is employed; the parent ion isolation window width is 2 m / z; and the step-normalized collision energy is a gradient of 20, 30, and 40 eV. And / or, metabolomics sequencing analysis includes at least quality assessment, multivariate statistical analysis, univariate statistical analysis and cluster analysis, differential metabolite functional enrichment analysis, and co-differentially expressed metabolite enrichment analysis.

[0009] Preferably, in step 5, the joint analysis includes at least joint enrichment analysis of differentially expressed genes and differentially expressed metabolites, and correlation analysis of differentially expressed genes and differentially expressed metabolites.

[0010] Preferably, in step 6, the key genes affecting pork quality are shown in Tables 4 and 5; and the metabolites affecting pork quality are shown in Table 7.

[0011] More preferably, step 6 further includes correlation analysis of differentially expressed genes and differentially expressed metabolites.

[0012] In a second aspect, the present invention provides the use of reagents for detecting the expression levels of differentially expressed genes in pig muscle and / or reagents for detecting differentially expressed metabolites in pig muscle in the preparation of products for assessing the effects of heat stress on changes in the meat quality of pig muscle.

[0013] Thirdly, the present invention provides the use of reagents for detecting the ATP1A1 gene in the preparation of products for assessing the expression of the metabolite methionine in porcine muscle, or the use of reagents for detecting methionine in the preparation of products for assessing the expression of the ATP1A1 gene in porcine muscle.

[0014] Compared with the prior art, the technical advantages of the present invention are as follows: The analytical methods of this invention fully validate that heat stress has multifaceted effects on the quality characteristics of Rongchang pork, including meat color, drip loss, pH, tenderness, and shear force. It also reveals key genes that influence muscle quality due to heat stress, including KLF5, MYOC, SNTA1, TNNI2, DUSP10, AIF1, ACSL1, CPT1A, and CTH, which are enriched in pathways related to cell proliferation, protein digestion and absorption, inflammation, and immune responses. Furthermore, the invention reveals that the differential metabolites affecting muscle quality due to heat stress are mainly lipids and organic acids, which are enriched in pathways related to protein digestion and absorption, metabolism, and bile synthesis. In addition, this invention found that the ATP1A1 gene and methionine, which are involved in protein digestion and absorption and mineral absorption, are downregulated and significantly positively correlated in the HS group, suggesting that they may be key genes and metabolites causing changes in the quality of Rongchang pork. This invention identified differences in muscle gene expression and metabolites in Rongchang pigs under heat stress. By combining differential gene and metabolite analysis, it elucidated the effects of heat stress on skeletal muscle gene expression and metabolite synthesis, as well as the potential causes of meat quality changes. This provides a theoretical basis for molecular marker screening in stress-resistant breeding and the development of functional feed additives. Attached Figure Description

[0015] The accompanying drawings, which are included to provide a further understanding of the invention and form part of this invention, illustrate exemplary embodiments of the invention and are used to explain the invention, but do not constitute an undue limitation of the invention. In the drawings: Figure 1 The relative expression level of the HSPA4 gene in the heat stress model constructed in Example 1 of this invention.

[0016] Figure 2 This invention illustrates the effect of heat stress on the color of Rongchang pork in different experimental groups in Example 1 of this invention, where A: RT, B: HS, and C: PF.

[0017] Figure 3 The following is an example of the effect of heat stress on the quality indicators of Rongchang pork in Example 1 of this invention: a: L value of the color brightness of the longissimus dorsi muscle in the three experimental groups; b: pH result of the longissimus dorsi muscle 1 hour after slaughter in the three experimental groups; c: pH result of the longissimus dorsi muscle 24 hours after slaughter in the three experimental groups; d: drip loss rate of the longissimus dorsi muscle in the three experimental groups; e: conductivity of the longissimus dorsi muscle in the three experimental groups; f: water-binding capacity of the longissimus dorsi muscle in the three experimental groups; g: moisture content of the longissimus dorsi muscle in the three experimental groups; h: intramuscular fat content of the longissimus dorsi muscle in the three experimental groups; i: shear force of the longissimus dorsi muscle in the three experimental groups.

[0018] Figure 4 The results of differential gene clustering analysis in Example 2 of this invention are shown, where a: HS group vs RT group; b: HS group vs PF group.

[0019] Figure 5 The results of GO enrichment analysis in Example 2 of this invention are shown, where A: HS group vs RT group; B: HS group vs PF group.

[0020] Figure 6 The results of KEGG enrichment analysis in Example 2 of this invention are shown, where A: HS group vs RT group; B: HS group vs PF group.

[0021] Figure 7 The following figures illustrate the results of RT-qPCR verification of transcriptome sequencing accuracy in Example 2 of this invention. Figure A shows the relative expression level of the HSPA4 gene; Figure B shows the relative expression level of the KLF5 gene; Figure C shows the relative expression level of the MYOC gene; Figure D shows the relative expression level of the SNTA1 gene; Figure E shows the relative expression level of the TNNI2 gene; Figure F shows the relative expression level of the ACSL1 gene; Figure G shows the relative expression level of the CPT1A gene; and Figure H shows the relative expression level of the CTH gene.

[0022] Figure 8 The results of differential metabolite analysis in Example 3 of this invention are shown, where A: HS group vs RT group; B: HS group vs PF group.

[0023] Figure 9 This is the classification result of differential metabolites in Example 3 of the present invention.

[0024] Figure 10 The results of the co-enrichment analysis of differentially expressed genes and differentially expressed metabolites (KEGG) in Example 3 of this invention are shown.

[0025] Figure 11 The results of the correlation analysis between differentially expressed genes and differentially expressed metabolites in Example 3 of the present invention are shown, where a: HS group vs RT group; b: HS group vs PF group. Detailed Implementation

[0026] This invention employs combined transcriptomics (RNA-seq) and metabolomics analysis techniques to comprehensively analyze the effects of heat stress on key genes and metabolites in Rongchang pigs and explore their potential regulatory mechanisms.

[0027] In the description of this invention, it should be noted that unless specific conditions are specified in the examples, conventional conditions or conditions recommended by the manufacturer shall apply. Reagents or instruments whose manufacturers are not specified are all commercially available conventional products.

[0028] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0029] Example 1

[0030] This embodiment investigates the effect of heat stress on the longest back muscle tissue of Rongchang pigs, as detailed below: 1. Laboratory animals Nine 100-day-old male Rongchang pigs with uniform body weight (23.49±0.96 kg) were selected and divided into a room temperature group (RT, 24~26 ℃) and a heat stress group (HS, 34~36 ℃). To reduce experimental errors caused by decreased feed intake due to heat stress, a room temperature paired feeding group (PF, 24~26 ℃) was also set up, with the same feed intake as the heat stress group under room temperature treatment conditions. Three pigs were in each of the three groups and were housed at the teaching and research base of the Animal Nutrition Institute of Sichuan Agricultural University. The experiment began one week after the pigs entered the facility and acclimatized. All three groups had free access to water and were fed the same growing diet; humidity was controlled at 65%~75% in all treatments. The PF group was included in the design, and the feed intake of pigs in this group was controlled to be consistent with that of the HS group. By comparing HS with RT and HS with PF, the influence of feed intake changes on heat stress was eliminated, thus helping to accurately identify the core genes and key metabolites of heat stress affecting skeletal muscle.

[0031] The heat stress group underwent a dynamic heat stress intervention for 7 consecutive days, simulating a summer high-temperature environment (34-36℃, relative humidity 65%-75%), to systematically analyze the effects of heat stress on skeletal muscle tissue. The other two groups conducted parallel experiments based on their respective experimental parameters. To verify the success of the heat stress model treatment, this example selected the heat stress protein 70 protein 4 (HSPA4) gene for RT-qPCR validation (the procedure and primers are described in Example 2). The results are as follows... Figure 1 As shown, the expression level of HSPA4 gene in the HS group was significantly higher than that in RT and PF, indicating that the heat stress pig model was successfully established.

[0032] The experiment ended after seven days of heat stress. The complete right longissimus dorsi muscle was harvested, and after removing fat and fascia, sampling was performed according to the People's Republic of China Agricultural Industry Standard NY / T 821-2019, extending from the anterior end of the third thoracic vertebra from the bottom backwards until all samples were collected to meet the requirements of the testing items. The relationship between heat stress and muscle quality was established by testing meat quality indicators such as longissimus dorsi muscle color, pH value (1h / 24h), drip loss, conductivity, moisture content, intramuscular fat content, and tenderness. For water retention, two slices were continuously cut from the anterior end, each approximately 1cm thick; for drip loss, slices were cut after water retention, approximately 8cm thick; for pH and conductivity, slices were cut after drip loss, approximately 5cm thick; for meat color, slices were cut after pH and conductivity, approximately 2cm thick; for tenderness, slices were cut after meat color, approximately 10cm thick; and for intramuscular fat and moisture, the remaining portion after the above sample cuts was used. The total sample weight should be greater than 200g. Meat samples used for determining moisture and intramuscular fat were stored at -20°C, while other meat samples were stored at 0–4°C. The corresponding phenotypes were then determined according to the prescribed procedures. The left longissimus dorsi muscle was harvested, fat and fascia removed, and aliquoted into cryovials. These were then rapidly frozen in liquid nitrogen and subsequently stored at -80°C for RNA and metabolite extraction.

[0033] 2. Experimental Methods (1) Measuring flesh color Meat color was determined using an instrumental method within 45–60 minutes post-slaughter. The colorimeter (D65 light source) was pre-set to Lab mode, calibrated using the included calibration plate, and preheated. A 1 cm thick piece of meat was then cut for measurement, and the luminance value (L) was recorded. Three different sites were measured for each sample. The relative deviation of the results for the same sample should be less than 5%. The final result was expressed as the average of the three measurements, and the judgment criteria are shown in Table 1.

[0034] Table 1. Criteria for Judging Flesh Color

[0035] (2) pH measurement pH was determined using the meat block assay method. The result measured within 45–60 minutes post-slaughter was recorded as pH 1. After measurement, the meat was stored at 0–4°C for 24 hours ± 10 minutes post-slaughter and measured again; the result was recorded as pH 24. A carcass muscle pH meter was used for measurement. Three measurement points were measured for the same sample. The relative deviation of the results for the same sample should be less than 5%. The final result was expressed as the average of the three measurements. The final result interpretation criteria are shown in Table 2.

[0036] Table 2 pH rating criteria

[0037] (3) Measurement of dripping water loss Drip loss (DL) was determined using the bagging method. Within 2 hours post-slaughter, a meat sample of approximately 6 cm was cut, removing peripheral fascia and fat, and trimmed into three pieces approximately 4 cm x 2 cm x 1 cm in length, width, and height. The weight of each piece was recorded as m1. The pieces were strung together with wire and suspended in a paper cup without touching the cup wall, ensuring the muscle fibers were perpendicular to the ground. The cup was then sealed tightly with aluminum foil and refrigerated at 2-4°C for storage and recording. After 48 hours, the sample was removed, surface moisture was blotted with filter paper (avoiding compression), and the meat piece m2 was weighed. The formula for calculating drip loss is shown in Formula I below. The final result is expressed as the average of three calculations, and the relative deviation of the results for the same sample should be less than 15%.

[0038] .

[0039] (4) Conductivity measurement Electrical conductivity was determined using an instrumental method within 45–60 minutes post-slaughter. A carcass meat conductivity meter was used. Three measurement points were taken for the same sample, and the relative deviation of the results for the same sample should be less than 5%. The final result was represented by the average of the three measurements.

[0040] (5) Moisture content determination Moisture content (W) was determined within 72 hours post-slaughter. Within 72 hours, the meat sample was minced using a meat grinder, and the weight was recorded as m3 in a petri dish. The minced meat sample was then spread evenly in another petri dish and weighed again, recorded as m4. The sample was then dried in a 105℃ oven until constant weight was reached, i.e., the difference between two weighings was less than 5 mg. The dried sample was then weighed and recorded as m5. The formula for calculating moisture content is shown in Formula II below.

[0041] .

[0042] (6) Hydraulic measurement Water-holding capacity (WHC) was determined using a pressure gauge method 24 hours post-slaughter. A 2cm section of meat was cut and drilled from the center using a 1.27cm circular sampler. The weight of the sample before pressurization was recorded as m6. A layer of absorbent paper, eight layers of filter paper, and a piece of cardboard were placed above and below the sample. The sample was then placed on a pressurization platform and pressurized to 35kg. Timing was started and maintained at 35kg for 5 minutes. Afterward, the pressure was removed, the sample was removed, and any surface residue was cleaned. The weight of the sample after pressurization was recorded as m7. The formula for calculating water-holding capacity is shown in Equation III below. The same sample was measured twice, and the average of the two results was used to express the result. The relative deviation of the results for the same sample should be less than 10%.

[0043] .

[0044] (7) Intramuscular fat measurement Intramuscular fat (IMF) was determined using Soxhlet extraction. Dried meat samples, after moisture content determination, were ground into powder in a mortar. A filter paper tube was prepared and weighed (m8). Approximately 2.5g of the powder was placed into the filter paper tube and weighed (m9). The filter paper tube was placed inside the extraction tube, connected to a round-bottom flask, and 1.5 times the volume of the extraction tube (60-90℃) of petroleum ether was poured into it. A condenser was then connected, and the water valve was opened. The entire apparatus was fixed to an iron stand, and the round-bottom flask was placed in a 95℃ water bath for heating. The liquid flow rate in the condenser was controlled so that extraction was performed every 10-20 minutes, with each sample extracted at least 20 times. After extraction, the petroleum ether was recovered, the filter paper tube was removed and air-dried in a ventilated area for half a day, then dried in a 105℃ oven for 6 hours. Finally, it was weighed (m10). The formula for calculating intramuscular fat is shown in Equation IV below.

[0045] .

[0046] (8) Tenderness determination Tenderness was determined using the shear force test method. Meat samples were cut, surface fascia and fat were removed, and the samples were stored in a refrigerator at 0-4℃. During testing, the meat samples were placed in a constant temperature water bath and heated to 80℃. When the center temperature of the meat sample reached 70℃, it was removed and cooled to a center temperature of 0-4℃. A circular drill sampler with a diameter of 1.27cm was used to drill the meat sample parallel to the muscle fibers. The hole length was not less than 2.5cm, and the sampling position should be at least 5mm from the edge of the sample. The distance between the edges of two samplings should not be less than 5mm. Holes with obvious defects were discarded. At least two samples were tested, and the test was performed immediately after sampling. The hole sample was placed on the instrument's blade groove, with the muscle fibers perpendicular to the blade direction. The instrument was started to cut the meat sample. The maximum shear force during this cutting process was the measured value of the hole sample shear force. The allowable relative deviation of the measured values ​​of the valid hole samples of the same meat sample should be less than 15%.

[0047] Based on the above measurements, the following results were obtained: the longissimus dorsi muscle in the HS group was darker and grayish-white in color. Figure 2 Analysis of differences in flesh color revealed that the flesh color of the HS group was significantly higher than that of the RT and PF groups. Figure 3Meanwhile, according to the meat color assessment standard, the HS meat color score was 2 points, while the RT and PF meat color scores were between 2 and 3 points, closer to 3 points, indicating that the longissimus dorsi muscle of Rongchang pigs after heat stress tends to be closer to PSE meat. This is also reflected in the drip loss; the loss rate of HS was significantly higher than that of RT and PF, indicating that the longissimus dorsi muscle of Rongchang pigs lost more water after heat stress and was less able to retain moisture. Furthermore, the pH value at 1 hour post-slaughter showed that the pH value of HS was significantly lower than that of RT and PF, while the pH value at 24 hours post-slaughter showed that HS was significantly lower than PF. Although the difference from RT was not significant, there was still a decreasing trend, indicating that the longissimus dorsi muscle of Rongchang pigs after heat stress was acidic, and the acidity was higher than that of RT and PF. Finally, the shear force of the longissimus dorsi muscle of Rongchang pigs in the HS group was significantly higher than that of RT. Although the difference between PF and HS was not significant, the shear force of HS tended to be higher than that of PF, indicating that the shear force of the longissimus dorsi muscle of Rongchang pigs increased after heat stress, and the tenderness of the meat decreased. After heat stress, there were no significant differences in four meat quality indicators of Rongchang pigs: electrical conductivity, moisture content, water-holding capacity, and intramuscular fat content. These results indicate that the experimental results of Example 1 demonstrate that heat stress has multifaceted effects on pork quality, including meat color, drip loss, pH value, and shear force.

[0048] Example 2

[0049] This embodiment investigates the effects of heat stress on genes related to the longissimus dorsi muscle of Rongchang pigs. Transcriptome sequencing was performed on longissimus dorsi muscle samples from three groups (RT, HS, and PF) of Rongchang pigs to analyze differentially expressed genes and regulatory pathways related to meat quality under heat stress, and to screen for key genes responding to heat stress. Details are as follows: 1. RNA extraction and detection 100 mg of Rongchang pig longissimus dorsi muscle sample was placed in 1 mL of Trizol and homogenized using a homogenizer. Total RNA was extracted using the Trizol method. The specific experimental steps are as follows: (1) For every 100 mg of tissue, use 1 mL of Trizol reagent to lyse the tissue or cells. The sample volume should not exceed 10% of the Trizol volume. Transfer the Trizol lysate of the above tissue into a 1.5 mL EP tube and place it on ice for 5 min.

[0050] (2) Add 0.2 mL of chloroform to the above EP tube, shake vigorously in your hand for 15 seconds, let stand on ice for 5 min, and centrifuge at 4℃ and 12000g for 15 min. After centrifugation, the liquid is divided into three layers, namely the supernatant RNA, the intermediate protein layer, and the lower layer DNA and other impurities.

[0051] (3) Transfer the supernatant to a 1.5 mL EP tube, avoiding contact with the protein layer, and add isopropanol at a volume ratio of 1:1. Gently invert the tube to mix. Place on ice for 10 min, then centrifuge at 4 °C and 12000 g for 10 min.

[0052] (4) Gently discard the supernatant, add 1 mL of 75% ethanol for washing, gently mix by blowing and blowing, and centrifuge at 4°C and 7500g for 5 min. Repeat this step once.

[0053] (5) Gently pour off the supernatant and use a pipette to remove any residual liquid clinging to the wall. Then dry on ice for 5 minutes. When there is no obvious residual liquid around the precipitate, add 20-30 μL of DEPC water according to the size of the RNA precipitate.

[0054] RNA quality was assessed using an ultra-micro UV spectrophotometer. Total RNA volume ≥ 800 ng, A260 / 280 ≥ 1.8–2.0, and A260 / 230 ≥ 2.0 were all acceptable. RNA integrity (RIN ≥ 4) was precisely measured using an Agilent 2100 Bioanalyzer, indicating good sample purity.

[0055] 2. RNA reverse transcription RNA reverse transcription was performed using an RNA reverse transcription kit; the specific steps were described in the kit's instructions. After the reaction, the resulting cDNA was diluted as needed and stored at -20°C.

[0056] 3. Quantitative primer design The primer sequences are shown in Table 3.

[0057] Table 3 Primer Sequences

[0058] 4. RT-qPCR Validation Analysis RT-qPCR experiments were performed using ChamQ SYBR qPCR Master Mix. The reaction volume was 10 μL: 5 μL ChamQ SYBR qPCR Master Mix, 0.4 μL upstream primer, 0.4 μL downstream primer, 0.8 μL cDNA, and 3.4 μL ddH2O. The amplification program was: 95℃ for 2 min; 95℃ for 5 s, Tm 10 s, 39 cycles; 65℃~95℃, 0.5℃ / 30 s. The relative gene expression levels were calculated using the 2-ΔΔCt method.

[0059] 5. Transcriptome sequencing RNA samples that passed quality control were subjected to transcriptome sequencing. The experimental procedure involved selectively capturing polyA-tailed mRNA with oligonucleotide (dT) magnetic beads, followed by random mRNA fragmentation mediated by divalent metal ions in a fragmentation buffer. Using the fragmented product as a template, cDNA first-strand synthesis was completed in an M-MuLV reverse transcriptase catalytic system using random hexamer primers. The RNA template was then eliminated using RNase H enzymatic digestion, followed by the construction of a double-strand synthesis system using DNA polymerase I as the core, and the extension of the second strand of cDNA using deoxyribonucleotide triphosphates as substrates. The purified double-stranded cDNA underwent end-leveling, adenosine tail modification, and sequencing adapter ligation. CDNA fragments in the 370-420 bp region were separated using a magnetic bead screening system, specifically amplified, and then purified again to obtain a suitable sequencing library. After library preparation, the concentration was initially determined using the Qubit 2.0 quantitative PCR system. The samples were then serially diluted to achieve a working concentration of 1.5 ng / μL. The molecular fragment length of the library was then verified using an Agilent 2100 bioanalytical system. Once the parameters were confirmed to be within specifications, real-time quantitative PCR was used to accurately quantify the effective library concentration (standard value ≥2 nM) to ensure the library met sequencing requirements. Libraries that passed quality control were mixed according to concentration parameters and target data volume, and then sequenced using a 150 bp paired-end read on the Illumina sequencing platform. During sequencing, four-color fluorescently labeled deoxynucleotides, DNA polymerase, and adapter primers were simultaneously added to the flow cell for bridge amplification. As the sequencing clusters extended, the incorporation of each nucleotide excited a characteristic fluorescence signal. These signals were captured in real time by an optical detection system, and specialized software converted the optical signals into base sequence information, ultimately obtaining complete sequencing data.

[0060] 6. Results Analysis (1) Sequencing quality control results In this embodiment, RNA-seq was performed on nine samples from the RT, HS, and PF groups. First, the raw sequencing data was converted into raw reads after base identification. GC content distribution was detected, and the GC content was between 51.5% and 52.5%, within the normal range. Sequencing quality was assessed in the read files, and the sequencing quality parameter Q20 was above 96.63%, and the sequencing quality parameter Q30 was above 90.60%, indicating high sequencing quality that met the requirements for subsequent analysis. After quality testing, reads with adapters and low quality were filtered out from the raw sequences obtained from the sequencing data. Clean reads of 10.30–12.29 G were obtained from each of the nine libraries for subsequent transcriptome analysis. To verify the reliability of the sequencing results, principal component analysis (PCA) was performed on the sequencing samples. Samples within the RT, HS, and PF groups clustered together, and intergroup separation was good, preliminarily indicating that the experimental treatment had a significant impact on gene expression in Rongchang pigs. The sequencing data were of good quality and could be used for subsequent data analysis.

[0061] (2) Screening and cluster analysis of differentially expressed genes The DEseq2 package was used to analyze differentially expressed genes between HS and RT and between HS and PF. Genes with a p-value < 0.05 and |log2FoldChang| ≥ 0.58 (FoldChang ≥ 1) were considered differentially expressed. The differential expression volcano icon annotates the top ten genes with the highest upregulation and downregulation. Among the genes upregulated by HS compared to RT, 196 genes were identified, with the top ten showing significant differences including PRCP, ESPL1, MCM4, SHCBP1, CCDC3, ZNF367, CCN1, FOXM1, FUT8, and PPP1R18. Among the genes downregulated, 844 genes were identified, with the top ten showing significant differences including TENT5B, MTRR, BDH1, UXS1, ZBTB47, CMYA5, B3GALNT2, PDE4B, YBX2, and CCNYL1. 640 genes were upregulated in HS compared to PF, with the top ten significantly different genes including ZNF503, TNS1, NDRG2, SLC25A34, NT5C3A, HCN1, UQCRFS1, ANPE1, SORBS1, and MYLIP. 770 genes were downregulated, with the top ten significantly different genes including LMNB2, TENT5B, EBP, MMP16, LDLR, CNN1, CRISPLD1, FADS1, KCTD15, and RET. These results indicate that heat stress alters the expression levels of genes in the longissimus dorsi muscle of Rongchang pigs, and most of these differentially expressed genes are downregulated. To further characterize the different expression patterns of differentially expressed genes in HS vs RT and HS vs PF under heat stress, hierarchical cluster analysis was performed using the relative expression levels of the top 100 differentially expressed genes in the two comparison groups. The same color region represents the same cluster grouping information, indicating similar gene expression patterns, similar functions, or involvement in the same biological processes. Results are as follows: Figure 4 As shown, red indicates higher gene expression levels in the comparison group, while blue indicates lower gene expression levels. The differentially expressed genes in HS vs RT and HS vs PF both comprised two major categories with significant differences.

[0062] (3) Functional enrichment analysis of differentially expressed genes In the HS vs RT comparison group, there were 1040 differentially expressed genes. GO analysis of these differentially expressed genes revealed 207 highly significant GO category enrichments (p<0.05). Among them, 178 were annotated to biological processes (BP), 9 to cellular components (CC), and 20 to molecular functions (MF). Figure 5The HS vs RT study presented the top eight items with the most significant differences in three aspects of GO enrichment analysis. These included mitotic cell cycle, regulation of cell population proliferation, cell cycle, mitotic cell cycle process, cell division, cell cycle process, cell migration, and regulation of multicellular organismal development.

[0063] In the comparison between HS and PF, a total of 1410 genes were differentially expressed. GO analysis of these differentially expressed genes revealed that 68 GO categories were significantly enriched (p<0.05). Figure 5 The HS vs PF comparison shows the top eight items with the most significant differences in three aspects of the GO enrichment analysis. These include innate immune response, response to other organisms, response to external biotic stimulus, defense response to symbiont, defense response to other organisms, regulation of immune response, positive regulation of immune system process, and regulation of immune system process.

[0064] The results showed that, based on GO enrichment analysis, the differentially expressed genes between HS and RT were mainly enriched in pathways related to cell proliferation, such as mitosis and cell cycle, indicating that heat stress may affect the meat quality of the longissimus dorsi muscle of Rongchang pigs in the RT group by influencing skeletal muscle cell proliferation. The differentially expressed genes between HS and PF were mainly enriched in immune response-related pathways, such as immune response and response to other organisms, indicating that heat stress may affect the meat quality of the longissimus dorsi muscle of Rongchang pigs in the PF group by influencing skeletal muscle immune response.

[0065] We further performed KEGG pathway enrichment analysis on the differentially expressed genes. Figure 6 The results showed that 324 pathways were enriched in the HS vs RT groups, of which 59 pathways were significantly enriched (p < 0.05), including cell cycle, pertussis, Kaposi sarcoma-associated herpesvirus infection, complement and coagulation cascades, and hepatitis B. These results indicate that the differentially expressed genes between HS and RT mainly enriched pathways related to cell proliferation and disease, suggesting that heat stress may affect the meat quality of the longissimus dorsi muscle of Rongchang pigs in the HS group by influencing skeletal muscle cell proliferation and inducing disease. Furthermore, 327 pathways were enriched in the HS vs PF groups, of which 34 pathways were significantly enriched (p < 0.05), including fatty acid metabolism, PPAR signaling pathway, fatty acid degradation, and protein digestion and absorption. The above results indicate that the differentially expressed genes between HS and PF are mainly enriched in pathways related to fatty acid and amino acid synthesis and metabolism, suggesting that heat stress may affect the meat quality of the longissimus dorsi muscle of Rongchang pigs in the HS group by influencing the synthesis and metabolism of skeletal muscle fatty acids and amino acids.

[0066] (4) Functional enrichment analysis of common differentially expressed genes Among numerous differentially expressed genes, 319 genes were found to be co-expressed by HS vs RT and HS vs PF. These 319 co-expressed genes are considered core genes whose expression changes due to heat stress and warrant further investigation. GO enrichment analysis of the co-expressed differentially expressed genes revealed highly significant enrichment in 14 GO categories (p < 0.05). Table 4 shows that the upregulated gene DUSP10 and the downregulated gene AIF1 were significantly enriched in the aforementioned pathways.

[0067] KEGG enrichment analysis revealed 259 enriched pathways, of which 12 were significantly enriched (p < 0.05). KEGG enrichment analysis of common differentially expressed genes indicated that the core mechanism of heat stress regulation of the longissimus dorsi muscle in Rongchang pigs lies in fatty acid metabolism and pathways related to inflammation and immune responses. Table 5 shows that genes such as NECTIN1, CARD11, ACSL1, and KCNE3 were significantly enriched in these pathways.

[0068] Table 4. GO enrichment analysis of common differentially expressed genes: partial pathways and differentially expressed genes.

[0069] Table 5. KEGG enrichment analysis of common differentially expressed genes: partial pathways and differentially expressed genes.

[0070] (5) RT-qPCR validation analysis To verify the reliability of transcriptome sequencing, four genes related to muscle growth and development (KLF5, MYOC, SNTA1, TNNI2) and three differentially expressed genes related to fatty acid and amino acid metabolism (ACSL1, CPT1A, CTH) were randomly selected from the common differentially expressed genes of HS vs RT and HS vs PF for verification. The relative expression levels of these genes were then compared with those in the sequencing data. Results are as follows: Figure 7 As shown in the AH results, the expression levels of HSPA4, MYOC, SNTA1, TNNI2, and CTH genes in the HS group were significantly higher than those in the RT and PF groups (p < 0.05). The expression levels of KLF5, ACSL1, and CPT1A genes in the HS group were significantly lower than those in the RT and PF groups (p < 0.05). The RT-qPCR results were consistent with the sequencing results, indicating that the sequencing data were accurate and reliable. Example

[0071] This embodiment investigates the effects of heat stress on metabolites related to the longissimus dorsi muscle of Rongchang pigs. Metabolomic sequencing was performed on longissimus dorsi muscle samples from three groups (RT, HS, and PF) of Rongchang pigs to analyze differentially expressed metabolites related to meat quality under heat stress. By jointly analyzing differentially expressed metabolites and differentially expressed genes, key genes and metabolites affecting meat quality under heat stress were identified, thus refining the network of gene-metabolite interactions related to muscle development. Details are as follows: 1. Extraction of metabolites Each group of samples preserved in Example 1 was thawed at 4°C, ground together, and divided into 3 samples. 100 mg of each sample was weighed, 2 steel balls were added, and 500 μL of pre-cooled 80% methanol solution was added. The samples were homogenized at low temperature in a tissue homogenizer, homogenized at -10°C for 5 min, and allowed to stand at -20°C for 30 min. The samples were then centrifuged at 16000g at 4°C for 20 min, and the supernatant was collected for sequencing.

[0072] 2. Metabolomics sequencing (1) Chromatographic separation The entire analysis employed a temperature-controlled injection system (4℃) to maintain sample stability. Separation and analysis were performed using a Shimadzu LC30 ultra-high performance liquid chromatography platform equipped with a Waters ACQUITYUPLC® HSST3 column (2.1 × 100 mm, 1.8 µm particle size). Chromatographic conditions were set as follows: injection volume 10 μL, column oven temperature constant at 40℃, and mobile phase flow rate set at 0.3 mL / min. The mobile phase consisted of two phases: phase A was an aqueous solution containing 0.1% formic acid, and phase B was an acetonitrile organic phase containing 0.1% formic acid. The gradient procedure was executed in the following sequence: In the initial stage (0-2 min), the proportion of phase B was maintained at 0%; in the 2-6 min interval, the concentration of phase B increased linearly to 48%; then, in the 6-10 min period, it continued to increase linearly to 100% and was maintained until 12 min; in the final stage, a gradient reduction procedure was implemented (from 100% to 0% from 12-12.1 min), and the column regeneration was completed by maintaining the baseline equilibrium state during the 12.1-15 min period.

[0073] (2) Mass spectrometry acquisition All samples were analyzed using a bipolar scanning strategy via an electrospray ionization interface, simultaneously performing positive (+) and negative (-) ion detection. The analytes, after chromatographic separation, were analyzed using a QEPlus high-resolution mass spectrometry system (Thermo Scientific), employing a HESI ion source for efficient dissociation. The core ionization parameters were configured as follows: dual-mode spray voltage 3.8 kV (+) / 3.2 kV (-); capillary temperature constant at 320 °C; sheath gas and auxiliary gas flow rates set to 30 arb and 5 arb, respectively; ion transmission channel RF field intensity (S-Lens RF Level) adjusted to 50%; and the ion source heating module maintained at 350 °C. The data acquisition window was set to 15 minutes, and the operating parameters included two dimensions. Primary mass spectrometry workflow: Mass scan range covering 75-1050 m / z; resolution set to 70,000 (@m / z 200); automatic gain control target (AGCtarget) set to 3×10^6; maximum injection time limited to 100 ms. Dynamic secondary mass spectrometry strategy: Real-time triggering of Top 10 high-abundance precursor ion fragmentation based on full scan mode; secondary resolution 17,500 (@m / z 200); AGC target optimized to 1×10^6. 5 It features a 50ms injection time, employs high-energy collision dissociation (HCD) technology, has a parent ion isolation window width of 2 m / z, and uses a stepped normalized collision energy gradient of 20, 30, and 40 eV.

[0074] 3. Results Analysis (1) Experimental quality assessment First, the mass spectra (BasePeak) of the QC samples under positive and negative ion detection modes were displayed and compared. The results showed that a total of 25,257 ion peaks were collected under both positive and negative ion modes. The response intensity and retention time of each chromatographic peak were basically consistent, indicating that the variation caused by instrument error was small throughout the experiment, and the data quality was reliable. PCA analysis results showed that the QC samples were closely clustered together, indicating that the experiment had good repeatability, and the metabolic mass spectrometry differences obtained in the experiment could reflect the biological differences between the samples.

[0075] (2) Multivariate statistical analysis Three multivariate statistical analysis methods were used to analyze the detection data: principal component analysis (PCA), partial least squares-discriminant analysis (PLS-DA), and orthogonal partial least squares-discriminant analysis (OPLS-DA). The multivariate statistical analysis results showed significant differences between HS and RT, and between HS and PF, indicating good clustering of sample points, large distances between different samples, and reliable sequencing results, allowing for further analysis.

[0076] (3) Univariate statistical analysis and cluster analysis Differentially expressed metabolites were screened using |log2FoldChang| ≥ 1, p < 0.05 as the threshold. The volcano plot shows the top ten significantly differentially expressed metabolites; red indicates higher metabolite levels, and blue indicates lower metabolite levels. Figure 8 Of the metabolites expressed by HS relative to RT, 66 were upregulated and 116 were downregulated. The top ten significantly different metabolites included: 4-hydroxybenzaldehyde, N-lactylvaline, p-ethoxylactylaniline, polyhydroxypyrrolizidine A7, 7-phenylhept-2-ene-4,6-diynealdehyde, cinnamic acid, 13-hydroxytridecanoic acid, cisperidin, lysine, and 5-hydroxymaltol. Of the metabolites expressed by HS relative to PF, 88 were upregulated and 151 were downregulated. The top ten significantly different metabolites included: neopentylcarnitine, spermine, propionyl lysine, heptaylcarnitine, tetrahydro-1H-purine-2,6,8(3H)-trione, 3-hydroxyhexanoylcarnitine, succinylcarnitine, ganciclovir, L-hydroxyproline, and 4,1-benzoxazine. These results indicate that heat stress alters the expression of metabolites in the longissimus dorsi muscle of Rongchang pigs. To evaluate the rationality of candidate metabolites and to more comprehensively and intuitively display the relationships between samples and the differences in expression patterns of metabolites in different samples, hierarchical clustering was performed on each group of samples using the expression levels of qualitatively significant differential metabolites. The results showed that the differential metabolites in HS vs RT and HS vs PF both included two major categories with significant differences.

[0077] (4) Functional enrichment analysis of differential metabolites Based on the structure and function of metabolites, differentially metabolites were classified according to the HMDB database. The results are as follows: Figure 9 As shown, different colors represent primary classifications; metabolites without classification information were not counted. Many differentially expressed metabolites in HS vs RT and HS vs PF groups belonged to lipid molecules. Specifically, 79 and 91 metabolites in the HS vs RT and HS vs PF groups were lipid molecules, accounting for 43.41% and 51.41% of the metabolites, respectively. 37 and 32 metabolites in the HS vs RT and HS vs PF groups were organic acids and their derivatives, accounting for 20.33% and 18.08% of the metabolites, respectively. In addition, the enriched compounds included alkaloids and their derivatives, benzene ring compounds, lignans and related compounds, nucleosides, nucleotides and analogues, organic nitrogen compounds, organic oxygen-containing compounds, organic heterocyclic compounds, phenylpropanes, and polyketides. The results indicate that heat stress mainly altered the expression levels of lipids and organic acids in the longissimus dorsi muscle of Rongchang pigs.

[0078] KEGG analysis of differential metabolites revealed that all pathways were enriched in environmental information processing, genetic information processing, metabolism, and biological systems. Specifically, in the HS vs RT study, 60 differential metabolites were identified through KEGG analysis, with 22 pathways significantly enriched (p<0.05), including bile secretion, primary bile acid biosynthesis, protein digestion and absorption, glycine, serine, and threonine metabolism, and cholesterol metabolism. In the HS vs PF study, 93 differential metabolites were identified through KEGG analysis, with 25 pathways significantly enriched (p<0.05), including protein digestion and absorption, amino acid biosynthesis, primary bile acid biosynthesis, and cholesterol metabolism. Metabolism and aminoacyl-tRNA biosynthesis, etc.

[0079] (5) Enrichment analysis of common differentially expressed metabolites Among numerous differentially expressed metabolites, 90 common differentially expressed metabolites were identified for HS vs RT and HS vs PF. These common differentially expressed metabolites are considered key metabolites whose expression changes due to heat stress. KEGG enrichment analysis of these 90 common differentially expressed metabolites revealed significant enrichment in pathways including protein digestion and absorption, amino acid biosynthesis, primary bile acid biosynthesis, valine, leucine, and isoleucine biosynthesis, and bile secretion. As shown in Table 6, metabolites such as methionine, α-ketoisovaleric acid, chenodeoxycholic acid, and L-carnitine were significantly enriched in these pathways.

[0080] Table 6. KEGG enrichment analysis of common differential metabolites: partial pathways and differential metabolites.

[0081] (6) Combined transcriptomic and metabolomic analysis of the longissimus dorsi muscle of Rongchang pigs under heat stress (6-1) Joint enrichment analysis of differentially expressed genes and differentially expressed metabolites KEGG pathway joint analysis was performed on the common differentially expressed genes and metabolites in the HS vs RT and HS vs PF groups. The results are as follows: Figure 10 KEGG co-enrichment analysis of differentially expressed genes and metabolites showed that a total of 18 pathways were enriched, among which the protein digestion and absorption and mineral absorption pathways were significantly enriched. The differentially expressed genes and metabolites enriched in the pathways are shown in Table 7. The differentially expressed genes ATP1A1 and ATP1B2 and the differentially expressed metabolites methionine and threonine were significantly enriched in both pathways.

[0082] Table 7. Pathways, genes, and metabolites enriched by combined analysis

[0083] (6-2) Correlation analysis of differentially expressed genes and differentially expressed metabolites The correlation between differentially expressed genes and metabolites in the comparative groups was analyzed using Pearson analysis, and a 9-quadrant diagram was used. Figure 11 The correlation between genes and metabolites among groups is shown, with Pearson correlation coefficients (PCC) ≥ |0.80| and |log2FoldChang| ≥ 1 as screening criteria. From left to right and top to bottom, quadrants 1-9 are used. Quadrants 1 and 9 indicate negative correlations between differentially expressed genes and metabolites, with opposite expression patterns. Quadrants 3 and 7 show positive correlations, with similar expression patterns. Quadrants 2, 4, 5, 6, and 8 indicate differentially expressed genes or metabolites with |log2FoldChang| < 1. Correlation analysis showed a significant positive correlation between the ATP1A1 gene and methionine, with PCCs of 0.86 and 0.97 in HS vs RT and HS vs PF, respectively. No significant correlations were found between the ATP1A1 gene and threonine, and between the ATP1B2 gene and methionine and threonine, respectively.

[0084] In summary, the present invention yields the following research conclusions: (1) Changes in pH value of the longissimus dorsi muscle after continuous heat stress in pigs are the main cause of changes in meat color and drip loss. Furthermore, this invention speculates that changes in shear force are caused by changes in pH value and muscle fiber type.

[0085] (2) Heat stress mainly affects the longissimus dorsi muscle by influencing the proliferation of skeletal muscle cells. Differentially expressed genes in HS vs PF and common differentially expressed genes in both comparison groups were significantly enriched in inflammation and immune-related pathways, suggesting that heat stress may also induce an inflammatory response in the longissimus dorsi muscle and affect immune-related functions. In addition, functional enrichment analysis of differentially expressed genes in HS vs RT and HS vs PF showed that heat stress can induce an inflammatory response in the longissimus dorsi muscle, leading to muscle damage. Upregulation of DUSP10 gene expression and downregulation of AIF1 gene expression may be a self-protective response of the body to cope with the adverse effects of heat stress.

[0086] (3) The results of the enrichment analysis of common differential metabolites in HS vs RT and HS vs PF and the two comparison groups showed that the pathways of protein digestion and absorption, amino acid biosynthesis, primary bile acid biosynthesis, valine, leucine and isoleucine biosynthesis and bile secretion were significantly enriched, indicating that heat stress had a wide range of effects on the metabolism of the longissimus dorsi muscle of Rongchang pigs.

[0087] (4) Through correlation analysis of differentially expressed genes and differentially expressed metabolites, it was found that the differentially expressed gene ATP1A1 was significantly positively correlated with the differentially expressed metabolite methionine. HS was significantly downregulated relative to RT and PF, suggesting that the two together caused muscle inflammation and led to muscle damage.

[0088] Although embodiments of the present invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions, and variations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the appended claims and their equivalents. The embodiments described above merely illustrate several implementations of the invention, and while the descriptions are relatively specific and detailed, they should not be construed as limiting the scope of the invention. It should be noted that those skilled in the art can make several modifications and improvements without departing from the concept of the invention, and these all fall within the protection scope of the invention. Therefore, the protection scope of this invention should be determined by the appended claims.

Claims

1. A method for analyzing the effect of heat stress on pork muscle quality, characterized by, Comprising the following steps: Step 1, divide the pig breeds into room temperature group, heat stress group, and matched feeding group, place the heat stress group in an environment with a temperature of 34-36℃ and a relative humidity of 65%-75%, and feed the room temperature group and the matched feeding group in an environment with a temperature of 24-26℃ and a relative humidity of 65%-75% for a period of time; Step 2, take the skeletal muscle of the pig breeds in all groups, and detect the skeletal muscle quality indicators; Step 3, perform transcriptome sequencing and analysis on the skeletal muscle of the pig breeds in all groups, and obtain transcriptome sequencing and analysis results; Step 4, perform metabolome sequencing and analysis on the skeletal muscle of the pig breeds in all groups, and obtain metabolome sequencing and analysis results; Step 5, jointly analyze the obtained transcriptome sequencing and analysis results and metabolome sequencing and analysis results, and obtain joint analysis results; Step 6, combine the skeletal muscle quality indicators and the joint analysis results to obtain key genes and metabolites affecting pork quality.

2. The analysis method according to claim 1, characterized in that, In the step 1, the feeding time is not less than 7 days.

3. The analysis method of claim 1, wherein, In the step 2, the skeletal muscle is longissimus dorsi muscle; and / or, the skeletal muscle quality indicators include meat color, pH value, drip loss, conductivity, moisture content, water binding capacity, intramuscular fat content, and tenderness.

4. The analysis method of claim 1, wherein, In the step 3, the transcriptome sequencing and analysis at least includes sequencing result quality control, differential gene function enrichment analysis, differential gene screening and clustering analysis, common differential expression gene function enrichment analysis, and RT-qPCR verification analysis.

5. The analysis method of claim 1, wherein, In the step 4, the metabolome sequencing is performed by using ultra-high performance liquid chromatography combined with mass spectrometry analysis; preferably, the mobile phase system used by the ultra-high performance liquid chromatography comprises: phase A is a 0.1% formic acid aqueous solution, and phase B is a 0.1% formic acid acetonitrile organic phase; the gradient program is executed according to the following time sequence: 0-2min, maintain the proportion of phase B as 0% and the proportion of phase A as 100%; 2-6min, the concentration of phase B is linearly increased to 48% and the concentration of phase A is linearly decreased to 52%; 6-10min, the concentration of phase B is linearly increased to 100% and the concentration of phase A is linearly decreased to 0%, and the state is maintained until 12min; and / or, The mass spectrum adopts HESI ion source, and the core ionization parameters include: double-mode spray voltage 3.8 kV (+) / 3.2 kV (-); capillary temperature 300-340 DEG C; sheath gas and auxiliary gas flow rate is set to 25-30 arb and 3-6 arb respectively; ion transmission channel radio frequency field intensity (S-Lens RF Level) is adjusted to 50+5%; ion source heating module working temperature is 340-360 DEG C; preferably, the working flow of the first mass spectrum: the mass scanning range covers 75-1050 mass-to-charge ratio (m / z); the resolution is set to 70,000 (@m / z 200); the automatic gain control target value (AGC target) is set to 3*10^6; the maximum injection time (Maximum IT) is limited to 100 ms; the dynamic secondary mass spectrum strategy: based on full scan mode (Full scan) to trigger Top10 high-abundance parent ion fragmentation in real time; the secondary resolution is 17,500 (@m / z 200); the AGC target is optimized to 1*10 5 with 50 ms injection time; high-energy collision dissociation technology HCD is adopted; parent ion isolation window width 2 m / z; stepwise normalized collision energy 20, 30, 40 eV gradient; and / or, the metabolome sequencing and analysis at least includes quality evaluation, multivariate statistical analysis, univariate statistical analysis and clustering analysis, differential metabolite function enrichment analysis, and common differential expression metabolite enrichment analysis.

6. The analysis method of claim 1, wherein, In the step 5, the joint analysis at least includes differential expression gene and differential expression metabolite joint enrichment analysis, and differential expression gene and differential expression metabolite correlation analysis.

7. The analysis method of claim 1, wherein, In the step 6, the key genes affecting pork quality are shown in Tables 4 and 5; and the metabolites affecting pork quality are shown in Table 7.

8. The analysis method according to claim 1 or 7, characterized in that, The step 6 further includes differential expression gene and differential expression metabolite correlation analysis.

9. Use of reagents for detecting the expression amount of differential expression genes in pig muscle and / or reagents for detecting differential metabolites in pig muscle in the preparation of a product for evaluating the influence of heat stress on the change of pork quality.

10. Use of a reagent for detecting the ATP1A1 gene in the manufacture of a product for assessing the expression of the metabolite methionine in pig muscle, or alternatively, use of a reagent for detecting methionine in the manufacture of a product for assessing the expression of the ATP1A1 gene in pig muscle.

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