CN111455068B - Method for identifying freshness of refrigerated mutton based on functional genes - Google Patents
Method for identifying freshness of refrigerated mutton based on functional genes Download PDFInfo
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Abstract
The invention discloses a method for identifying the freshness of refrigerated mutton based on functional genes, which comprises the steps of extracting total RNA from mutton, carrying out reverse transcription on the RNA by adopting a real-time fluorescence quantitative PCR technology aiming at the functional genes screened by a transcriptomics technology, carrying out quantitative PCR amplification on fresh meat and obtaining the Ct value of the specific functional genes in the refrigeration process, further calculating the relative expression quantity of the specific genes, and judging first-stage fresh meat, second-stage fresh meat, third-stage fresh meat and stale meat according to the expression quantity. The method uses the trace sample to monitor the refrigerating time and the freshness of the mutton from the molecular biology level, lays a foundation for the subsequent high-quality and high-price of the mutton and the processing of high-quality meat products, provides an accurate, efficient and rapid evaluation method for monitoring the freshness of the mutton, is beneficial to creating more profits for meat enterprises, and has wide application prospect.
Description
Technical Field
The invention belongs to the technical field of meat product quality detection, and particularly relates to a method for identifying freshness of refrigerated mutton based on functional genes.
Background
China is the largest mutton producing country and consumer country in the world, and mutton products play a non-trivial role in the diet of residents in China due to the unique advantages of cold defense, nourishing and the like. The consumer forms of raw meat on the market today are typically hot fresh meat, frozen meat and cold fresh meat. The hot fresh meat refers to fresh meat which is directly sold on the market without being processed by cold fresh after being slaughtered, and has complex pollution source and short storage period; the frozen meat serving as frozen food is inhibited in microbial activity due to low storage temperature, is sanitary and safe, but is very unfavorable for maintaining the flavor and the nutritional characteristics of the product due to the phenomena of juice loss, cooking loss, protein denaturation and the like in the unfreezing process of the frozen meat; the cold fresh meat refers to raw fresh meat which is kept in a low-temperature state before eating after cold fresh acid discharge treatment is carried out on carcass subjected to quarantine qualified slaughter, the cold fresh meat generally undergoes transition from a stiff period to a mature period from slaughter to marketing, the meat quality is greatly improved, and the cold fresh meat becomes the mainstream of meat consumption in China at present.
Researchers have generally evaluated meat quality and storage period through macroscopic indicators such as sensory characteristics (including color, taste, etc.), food quality (including hardness, tenderness, elasticity, etc.), nutritional quality (including nutrient content, digestibility, etc.), hygiene indicators (including pH, TVB-N, TBARS, microbial, veterinary drug residues, etc.). However, these methods for studying meat in terms of appearance and chemical substances are cumbersome in detection process, large in sample usage and poor in accuracy. Therefore, it is very important to explore the technology for detecting the freshness of the novel chilled fresh mutton. In recent years, research on post-mortem quality change and regulation mechanism of animals by using proteomics is gradually developed, and obtaining specific functional genes through transcriptomics for analyzing related traits becomes an important way for livestock and poultry research.
Disclosure of Invention
The invention aims to solve the technical problem of identifying the freshness of refrigerated mutton in the prior art and provides a method for efficiently and quickly evaluating the freshness of mutton based on transcriptomics and real-time fluorescent quantitative PCR technology.
Aiming at the purposes, the technical scheme adopted by the invention comprises the following steps:
1. collecting fresh mutton after slaughtering and mutton samples with different refrigeration time, and extracting total RNA of the fresh mutton and the mutton samples after cold and fresh storage.
2. Designing a specific primer according to a sheep beta-globin gene sequence:
an upstream primer: 5' CGGCGGCGGGCGGCGCGGGCTGGGCGGGAAGGCCCATGGCAAGAAGAAGG 3
A downstream primer: 5' GCCGGCCCGCCGCCCGGTCCCGCTCACTCAGCAGCAAAGG
Meanwhile, specific primers of sheep LOC102172960, LOC108633460 and FAM110D genes are designed and synthesized:
LOC102172960 upstream primer: 5' TCGACCCCTTACGCTTTTTTTCT-3
LOC102172960 downstream primer: 5' TTTGAGGGGATCCGGGGAAAA-3
LOC108633460 upstream primer: 5' GGACCATGCACAGGATTC-3
LOC108633460 downstream primer: 5' TGTAAGGGCAGAGAAGGGGGG-3
FAM110D upstream primer: 5' TGGCAAAGTTGAGGAAGGTGC
FAM110D downstream primer: 5' AATGGGCAGCAAAACTCCAG-3
3. Performing real-time fluorescent quantitative PCR detection on the LOC102172960 gene, the LOC108633460 gene and the FAM110D gene after performing reverse transcription on the RNA obtained in the step 1 by taking beta-globin as an internal reference gene to obtain a Ct value of the gene, and adopting 2 -△△Ct ＝2 - ((Ct control-Ct. Beta. -globin) - (Ct test-Ct. Beta. -globin)) Calculating the relative expression quantity of the genes by the method, and judging the freshness of the mutton: if 2 of the LOC102172960 gene -△△Ct Value of 0.56 or less, 2 of LOC108633460 gene -△△Ct Value of 1.53 or less, 2 of FAM110D gene -△△Ct The value is less than or equal to 1.10, and the refrigerated mutton is first-grade fresh meat; if 2 of the LOC102172960 gene -△△Ct A value of 0.56 < 2 -△△Ct 2 of LOC108633460 gene less than or equal to 0.80 -△△Ct A value of 1.53 < 2 -△△Ct Less than or equal to 1.65, 2 of FAM110D gene -△△Ct A value of 1.10 < 2 -△△Ct The frozen mutton is less than or equal to 1.61, and the frozen mutton is second-grade fresh meat; if 2 of the LOC102172960 gene -△△Ct A value of 0.80 < 2 -△△Ct 2 of LOC108633460 gene less than or equal to 2.54 -△△Ct A value of 1.65 < 2 -△△Ct 2 of FAM110D gene of ≤ 1.74 -△△Ct A value of 1.61 < 2 -△△Ct The refrigerated mutton is not more than 2.94, and the refrigerated mutton is three-level fresh meat; if 2 of the LOC102172960 gene -△△Ct Value greater than 2.54, 2 of LOC108633460 Gene -△△Ct Value greater than 1.74, 2 of FAM110D gene -△△Ct The value is more than 2.94, the refrigerated mutton is stale meat, and 2 -△△Ct The larger the value, the more serious the deterioration.
The type of the refrigerated meat in the steps is goat meat, and the storage temperature is 2-4 ℃; the real-time fluorescent quantitative PCR amplification conditions are as follows: pre-denaturation at 95 ℃ for 5min;94 ℃, denaturation 30s,60 ℃, annealing 60s,72 ℃, extension 60s,40 cycles.
The LOC102172960 gene, the LOC108633460 gene and the FAM110D gene are different genes screened by transcriptomics technology.
The invention firstly detects and compares the difference between fresh mutton and stored mutton by carrying out real-time fluorescent quantitative PCR amplification on functional genes LOC102172960, LOC108633460 and FAM110D screened by transcriptomics, and realizes the identification of the storage time and freshness of the mutton under the refrigeration condition according to the Ct value. Compared with the prior art, the invention has the following beneficial effects:
1. the invention can realize the detection of large-scale mutton samples and is beneficial to market monitoring.
2. The invention is tested from the angle of analytics, has high accuracy and small sample usage amount, and has higher economic value.
3. The result obtained by the method on the mutton can be correspondingly used for detecting the freshness of other meats.
4. The invention is beneficial to the classification and classification of meat and has great significance for the high quality and high price of refrigerated meat.
Drawings
FIG. 1 is a graph showing the FPKM value of a specific functional gene in a mutton sample as a function of storage time.
Detailed Description
The invention will be further described in detail with reference to the following figures and examples, but the scope of the invention is not limited to these examples.
The following test was conducted by treating the instruments such as scissors and mortar with 0.1% DEPC aqueous solution for 12 hours, wrapping the treated instruments with tin foil, and sterilizing the wrapped instruments at 120 ℃ for 8 hours; the centrifuge tube, the gun head and the like are disposable plastic vessels without RNase; all reagents used in the test are pre-cooled.
Example 1
1. Sample preparation
Mutton samples are collected from the longissimus dorsi of 3 Shanxi white cashmere goats qualified in 18-month-old quarantine, the sampling amount of each sample is 2cm multiplied by 2cm,3 meat samples are respectively subjected to fascia removal and bloodstain removal, and then are rapidly transported back to a laboratory in dry ice. Each meat sample is divided into 4 small pieces, total RNA extraction is immediately carried out on 1 small piece of meat sample from each mutton sample after division, and 3 groups of samples are mixed and represented by CT after extraction; the remaining 3 samples from each mutton sample were refrigerated at 2-4 ℃, after 2, 4, 7 days respectively, total RNA extraction and sample mixing were performed, and refrigerated for 2, 4, 7 days are indicated by CS2, CS4, CS7 respectively. The mixed samples CT, CS2, CS4 and CS7 are stored in an ultra-low temperature refrigerator (-78 to-80 ℃) and used for subsequent transcriptomics analysis and real-time fluorescence quantitative test.
The RNA extraction method is a Trizol method, and comprises the following specific steps:
(1) 50-100 mg of meat samples were ground to powder in a mortar with liquid nitrogen and transferred to 1.5mL RNase free centrifuge tubes. Add 1mL Trizol lysate, shake and mix well, incubate for 5min at room temperature. Centrifuging at 12000r/min at 4 deg.C for 5min, and transferring the supernatant to a new RNase free centrifuge tube.
(2) Adding 0.2mL of chloroform, violently shaking for 15s, incubating at room temperature for 3min, centrifuging at 4 ℃ for 5min at 12000r/min, and sucking supernatant after the end and transferring the supernatant to a new RNase free centrifuge tube.
(3) And (3) repeating the step (2), and taking out the supernatant liquor rarely or not much.
(4) Adding 500 μ L isopropanol, mixing by inversion, incubating at room temperature for 10min, centrifuging at 4 deg.C at 10000r/min for 10min, discarding the clear solution, and collecting white jelly in the bottom tube.
(5) Adding 1mL of 75% ethanol (prepared by DEPC water), washing the precipitate, centrifuging at 4 deg.C for 5min at 7500r/min, discarding supernatant, and air drying at room temperature.
(6) Adding 50 μ L RNA dissolving solution, dissolving sufficiently to obtain RNA, and storing in-80 deg.C ultra-low temperature freezer.
2. Screening of functional genes
The extracted RNA was shipped to Huada Gene Co in dry ice, and the Huada Gene Co was entrusted with sample detection and sequencing to build a library. The specific process of the transcriptome sequencing project comprises the following steps: sample feeding → sample detection → library construction → sequencing on computer → information analysis → quality control → result, and the bioinformatics analysis method of the result is as follows:
(1) And (5) filtering data. And (3) filtering raw data obtained by sequencing, removing Reads containing joints, reads with unknown base N content of more than 5% and low-quality Reads (Reads with quality value of less than 10 and proportion of bases to the total base number of the Reads of more than 20% are regarded as low-quality Reads), and calling the filtered Reads as 'Clean TQ Reads' and storing the filtered Reads in a FAS format.
(2) Reference genome comparison. Clean reads were aligned to the reference genome using HISAT.
(3) New transcript prediction. Transcript reconstruction was performed for each sample using StringTie, then reconstruction information for all samples was integrated together using cuffmerge, and then transcripts with class code type 'u', 'i', 'o', 'j' were selected as new transcripts by comparing cuffmatch with reference annotation information. Then, CPC is used for predicting protein coding potential of the new transcript, and finally the new transcript with the predicted protein coding potential is added into a reference gene sequence to obtain complete reference sequence information for subsequent analysis.
(4) And (4) analyzing the gene expression level. Clean reads were aligned to reference sequences using Bowtie2 and expression levels of genes and transcripts were calculated using RSEM. Hierarchical clustering analysis was performed using the hclust function in the R software, and gene expression gene numbers between samples were displayed using venn plots.
(5) Differential expression analysis. And (3) carrying out differential gene detection by using a PossiondIS algorithm, carrying out hierarchical clustering analysis by using a Pheatmap function in R software according to a differential gene detection result, and using a K-means clustering (K-means) method for genes with expression modes having similar change trends under different experimental conditions.
(6) GO and KEGG enrichment analysis. Carrying out function classification on the differential genes according to GO annotation results, carrying out enrichment analysis by using a crypter function in R software, and carrying out FDR correction on a p value, wherein the function of which the FDR is less than or equal to 0.01 is regarded as obvious enrichment; and (3) carrying out biological pathway classification on the differential genes according to the KEGG annotation result, carrying out enrichment analysis by using a crypter function in R software, carrying out FDR correction on the p value, and regarding the pathway of which the FDR is less than or equal to 0.01 as obvious enrichment.
Transcriptomics analysis results were as follows:
(1) The analysis of the information results of the overall sequencing data shows that the sequencing sequence numbers of the CS2 group, the CS4 group and the CS7 group are respectively 48.99 multiplied by 10 6 、48.99×10 6 、48.99×10 6 (ii) a The net readings after filtration were 42.79X 10, respectively 6 、42.95×10 6 、42.65×10 6 87.35%, 87.69%, 87.07% of the total reading, respectively; total filter bases were 6.41G, 6.38G, 6.48G, respectively; q20 and Q30 are respectively more than 98 percent and 95 percent. Therefore, the sequencing data is reliable, and the sample quality is high.
(2) Analysis of the distribution result of reads in the sequencing sequence shows that the contents of the connector reads in the CS2 group, the CS4 group and the CS7 group are respectively 5.78%, 5.56% and 3.92%; the low-quality reads content is respectively 6.65%, 6.73% and 8.99%; the clean reads content is respectively high, and is respectively 87.35%, 87.69% and 87.07%. The result shows that the sequencing sample has better quality and higher data yield.
(3) Analysis of base content distribution results shows that except for the beginning, all samples have basically equal GC content, and stable A, T, C and G content, and the base content distribution results conform to the base complementary pairing principle of all nucleotide residues in DNA. The sequencing process is standard, the data source is reliable, and the method can be used for subsequent test analysis.
(4) The results of differential gene analysis at 0, 2, 4 and 7 days of refrigeration show that: compared with the CT group, 18905 genes are identified in the CS2 group, 6592 genes are different, 1388 up-regulated genes and 5204 down-regulated genes comprise the different genes, and the different genes account for 34.87% of the total genes; compared with the CT group, the CS4 group identifies 19172 genes, wherein the difference genes are 4669 and comprise 1427 up-regulated genes and 3242 down-regulated genes, and the difference genes account for 24.35 percent of the total genes; compared with the CT group, 18625 genes are identified in the CS7 group, wherein 5395 differential genes comprise 1995 up-regulated genes and 3400 down-regulated genes, and the differential genes account for 28.97 percent of the total genes; 18304 genes were identified in the CS2 group and the CS4 group, wherein 4568 differential genes, including 3183 up-regulated genes and 1385 down-regulated genes, accounted for 24.95% of the total genes; the CS4 group and CS7 group identified 18545 genes, of which 6700 were differential genes comprising 3442 up-regulated genes and 3258 down-regulated genes, the differential genes accounted for 36.13% of the total genes.
(5) Screening specific difference genes: the trend of FPKM values over time for 3 continuously down-regulated genes during 7 days of cold storage is shown in figure 1. The storage time and FPKM values for the 3 different genes can be fitted to a mathematical equation (where X represents days of storage and Y represents FPKM values), namely: LOC102172960 can be fitted to the equation Y =0.6757X 2 -8.789X+29.038(R 2 = 0.999), LOC108633460 can be fitted to equation Y =0.184X 2 -2.5306X+8.7309(R 2 = 0.9988), FAM110D may be fitted to equation Y =0.2545X 2 -3.4425X+12.266(R 2 = 0.0.9951). Therefore, the LOC102172960 gene, the LOC108633460 gene and the FAM110D gene are used as biomarkers for monitoring the refrigerating time and quality change of the slaughtered mutton for PCR amplification detection.
The analysis shows that the mutton is first-grade fresh meat within 2 days of storage (including day 2), and the FPKM values of LOC102172960, LOC108633460 and FAM110D genes are respectively between 13.66-29.22, 14.25-5.65 and 12.43-5.94; the mutton is stored for more than 2 days (not including day 2) and less than 4 days (including day 4) and is secondary fresh meat, and the FPKM values of LOC102172960, LOC108633460 and FAM110D genes are respectively between 13.66-5.13, 5.65-2.81 and 5.94-2.95; the mutton is stored for more than 4 days (excluding 4 days) and less than 7 days (including 7 days) and is three-grade fresh meat, and the FPKM values of LOC102172960, LOC108633460 and FAM110D genes are respectively 5.13-0.55, 2.81-1.14 and 2.95-0.55; when the storage period of mutton is longer than 7 days, the mutton is not fresh meat, and the FPKM values of LOC102172960, LOC108633460 and FAM110D genes are respectively less than 0.55, 1.14 and 0.55. Therefore, the invention can also identify the freshness of the chilled fresh mutton according to the FPKM value of the LOC102172960 gene, the LOC108633460 gene and the FAM110D gene.
3. Primer design
Designing a specific primer according to a sheep beta-globin gene sequence:
an upstream primer: 5' CGGCGGCGGGCGGCGCGGGCTGGGCGGGAAGGCCCATGGCAAGGAAGG3
A downstream primer: 5' GCCGGCCCGCCGCCCGGTCCCGCTCACTCAGCAGCAAAGG-3
Meanwhile, specific primers of sheep LOC102172960 gene, LOC108633460 gene and FAM110D gene are designed and synthesized:
LOC102172960 upstream primer: 5' TCGACCCCTTACGCTTTTTTTCT-3
LOC102172960 downstream primer: 5' TTTGAGGGGATCCGGGGAAAA-3
LOC108633460 upstream primer: 5' GGACCATGGCACACACAGGATTC-3
LOC108633460 downstream primer: 5' TGTAAGGGCAGAGAAGGGGGG-3
FAM110D upstream primer: 5' TGGCAAAGTTGAGGAAGTGC-3
FAM110D downstream primer: 5' AATGGGCAGCAACTCCAG-containing 3
The primers were synthesized by Invitrogen corporation.
4. Detection of mutton freshness
Performing real-time fluorescent quantitative PCR amplification and detection on the three screened differential genes LOC102172960, LOC108633460 and FAM110D after performing reverse transcription on the obtained RNA by taking beta-globin as an internal reference gene to obtain the Ct value of the gene, and adopting 2 -△△Ct ＝2 - ((Ct control-Ct. Beta. -globin) - (Ct test-Ct. Beta. -globin)) The relative expression quantity of the gene is calculated by the method, and the freshness of the mutton is judged. The fluorescent quantitative PCR amplification method comprises the following steps:
(1) The RNA template, primer Mix, dNTP Mix, DTT (dithioprimer), RT Buffer, hiFiScript, and RNase-Free Water were dissolved and placed on ice for use.
(2) The reaction system was formulated according to table 1.
TABLE 1PCR amplification reaction System
(3) Vortex, shake, mix, centrifuge briefly, collect the solution on the tube wall to the tube bottom.
(4) Performing a cDNA synthesis reaction: incubate at 42 ℃ for 15 minutes and 85 ℃ for 5 minutes.
(5) After the reaction was complete, it was centrifuged briefly and placed on ice for cooling. The reverse transcription product was kept at-20 ℃ until use.
(6) The real-time fluorescent quantitative PCR test is carried out by a 10 mu L reaction system, and 2 is adopted for calculating the relative expression quantity of the differential genes -△△ct The method takes beta-globin as an internal reference gene, and a reaction system of fluorescent quantitative PCR amplification is as follows: 0.3. Mu.L of each of the upstream and downstream primers, 1. Mu.L of cDNA template, 2 × ultra SYBR mix 5. Mu.L and ddH 2 O3.4 μ L; the reaction procedure is as follows: pre-denaturation at 95 ℃ for 5min; denaturation at 94 ℃ 30s,60 ℃, annealing 60s,72 ℃, extension 60s,40 cycles.
And (3) analyzing the fluorescent quantitative PCR amplification result: 2 different genes LOC102172960, LOC108633460 and FAM110D are selected by using beta-globin as reference gene -△△ct The method analyzes the real-time fluorescent quantitative PCR test result to judge the freshness of the mutton. If 2 of the LOC102172960 gene -△△Ct Value of 0.56 or less, 2 of LOC108633460 gene -△△Ct Value of 1.53 or less, 2 of FAM110D gene -△△Ct The value is less than or equal to 1.10, and the refrigerated mutton is first-grade fresh meat; if 2 of the LOC102172960 gene -△△Ct A value of 0.56 < 2 -△△Ct 2 of LOC108633460 gene less than or equal to 0.80 -△△Ct A value of 1.53 < 2 -△△Ct Less than or equal to 1.65, 2 of FAM110D gene -△△Ct A value of 1.10 < 2 -△△Ct The refrigerated mutton is not more than 1.61 and is second-level fresh meat; if 2 of the LOC102172960 gene -△△Ct A value of 0.80 < 2 -△△Ct 2 of LOC108633460 gene less than or equal to 2.54 -△△Ct A value of 1.65 < 2 -△△Ct 2 of FAM110D gene of ≤ 1.74 -△△Ct A value of 1.61 < 2 -△△Ct The refrigerated mutton is not more than 2.94, and the refrigerated mutton is three-level fresh meat; if 2 of the LOC102172960 gene -△△Ct Value greater than 2.54, 2 of LOC108633460 Gene -△△Ct Value greater than 1.74, 2 of FAM110D gene -△△Ct The value is more than 2.94, the refrigerated mutton is stale meat, and 2 -△△Ct The larger the value, the more serious the deterioration.
Claims (4)
1. A method for identifying the freshness of refrigerated mutton based on functional genes is characterized by comprising the following steps:
(1) Collecting fresh slaughtered mutton and mutton samples with different refrigerating time, and extracting total RNA of the fresh mutton and the refrigerated mutton samples;
(2) Designing and synthesizing a specific primer according to a sheep beta-globin gene sequence:
an upstream primer: 5' CGGCGGCGGGCGGCGCGGGCTGGGCGGGAAGGCCCATGGCAAGAAGAAGG 3
A downstream primer: 5' GCCGGCCCGCCGCCCGGTCCCGCTCACTCAGCAGCAAAGG
Meanwhile, specific primers of sheep LOC102172960, LOC108633460 and FAM110D genes are designed and synthesized:
LOC102172960 upstream primer: 5' TCGACCCCTTACGCTTTTTTTCT-3
LOC102172960 downstream primer: 5' TTTGAGGGGATCCGGGGAAAA-3
LOC108633460 upstream primer: 5' GGACCATGCACAGGATTC-3
LOC108633460 downstream primer: 5 'and 3' of TGTAAGGGCAGAAGAAGGGG-
FAM110D upstream primer: 5' TGGCAAAGTTGAGGAAGGTGC
FAM110D downstream primer: 5' AATGGGCAGCAAAACTCCAG-3
(3) Performing reverse transcription on the RNA obtained in the step (1) by taking beta-globin as an internal reference gene, performing real-time fluorescent quantitative PCR amplification and detection on the LOC102172960 gene, the LOC108633460 gene and the FAM110D gene to obtain the Ct value of the gene, and adopting 2 -△△Ct ＝2 - ((Ct control-Ct. Beta. -globin) - (Ct test-Ct. Beta. -globin)) Calculating the relative expression quantity of the gene by the method, and judging the freshness of mutton: if 2 of the LOC102172960 gene -△△Ct Value of 0.56 or less, 2 of LOC108633460 gene -△△Ct Value of 1.53 or less, 2 of FAM110D gene -△△Ct The value is less than or equal to 1.10, and the refrigerated mutton is first-grade fresh meat; if 2 of the LOC102172960 gene -△△Ct A value of 0.56 < 2 -△△Ct Less than or equal to 0.80, LOC108633460 gene 2 -△△Ct A value of 1.53 < 2 -△△Ct Less than or equal to 1.65, 2 of FAM110D gene -△△Ct A value of 1.10 < 2 -△△Ct Not more than 1.61, refrigerating mutton in two stagesFresh meat; if 2 of the LOC102172960 gene -△△Ct A value of 0.80 < 2 -△△Ct 2 of LOC108633460 gene less than or equal to 2.54 -△△Ct A value of 1.65 < 2 -△△Ct 2 of FAM110D gene of ≤ 1.74 -△△Ct A value of 1.61 < 2 -△△Ct The refrigerated mutton is three-level fresh mutton with the temperature less than or equal to 2.94; if 2 of the LOC102172960 gene -△△Ct Value greater than 2.54, 2 of LOC108633460 Gene -△△Ct Value greater than 1.74, 2 of FAM110D Gene -△△Ct Value greater than 2.94, the refrigerated mutton is stale meat, and 2 -△△Ct The larger the value, the more serious the deterioration.
2. The method for identifying the freshness of refrigerated mutton based on functional genes according to claim 1, which is characterized in that: the mutton is goat meat, and the refrigeration temperature is 2-4 ℃.
3. The method for identifying the freshness of refrigerated mutton based on the functional gene according to claim 1, characterized in that: the real-time fluorescent quantitative PCR amplification conditions are as follows: pre-denaturation at 95 ℃ for 5min;94 ℃, denaturation 30s,60 ℃, annealing 60s,72 ℃, extension 60s,40 cycles.
4. The method for identifying the freshness of refrigerated mutton based on functional genes according to claim 1, which is characterized in that: the LOC102172960 gene, the LOC108633460 gene and the FAM110D gene are different genes screened by a transcriptomics technology.
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| WO2009075579A1 (en) * | 2007-12-12 | 2009-06-18 | Erasmus University Medical Center Rotterdam | Biomarkers for cardiovascular disease |
| CN108588187A (en) * | 2018-04-04 | 2018-09-28 | 陕西师范大学 | A method of new fresh mutton storage time is identified using DNA and round pcr |
| CN110564842A (en) * | 2019-09-20 | 2019-12-13 | 南通大学 | Application of cytochrome enzyme CYP26A1 in preparation of medicine for treating neuropathic pain |
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| WO2009075579A1 (en) * | 2007-12-12 | 2009-06-18 | Erasmus University Medical Center Rotterdam | Biomarkers for cardiovascular disease |
| CN101946009A (en) * | 2007-12-12 | 2011-01-12 | 鹿特丹伊拉斯姆斯大学医疗中心 | Biomarkers for cardiovascular disease |
| CN108588187A (en) * | 2018-04-04 | 2018-09-28 | 陕西师范大学 | A method of new fresh mutton storage time is identified using DNA and round pcr |
| CN110564842A (en) * | 2019-09-20 | 2019-12-13 | 南通大学 | Application of cytochrome enzyme CYP26A1 in preparation of medicine for treating neuropathic pain |
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| "Ovarian FAM110C (Family with Sequence Similarity 110C): Induction During the Periovulatory Period and Regulation of Granulosa Cell Cycle Kinetics in Rats";Feixue Li et al.;《BIOLOGY OF REPRODUCTION》;20120328;第86卷(第6期);第1-9页 * |
| "不同贮藏条件下羊肉品质及其DNA质量的研究";赵晶;《中国优秀博硕士学位论文全文数据库（硕士）工程科技I辑》;20190115(第01期);第B024-786页 * |
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