CN111733263A - Gene marker related to porcine lipid metabolism capability and detection kit - Google Patents
Gene marker related to porcine lipid metabolism capability and detection kit Download PDFInfo
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Abstract
The invention discloses a gene marker related to the metabolic capability of pig lipids and a detection kit, belonging to the field of pig breeding. The gene marker combination comprises genesATP8、LIPEAndSCDthe detection kit comprises the geneATP8、LIPEAndSCDthe reagent of (1). The method can be used for rapidly determining the lipid metabolism capability of the pig and provides powerful support for pig breeding.
Description
Technical Field
The invention relates to the field of pig breeding, in particular to a gene marker related to the metabolic capability of lard and a detection kit.
Background
Pork quality is the sum of the histological, nutritional, hygienic, and processing characteristics of meat. The local pig breed in China has rich resources, and the pork quality has the advantages of bright red flesh color, strong water binding capacity, high intramuscular fat content, small muscle fiber diameter and the like. Wherein, the water retention capacity is the capacity of keeping original water content when the muscle is acted by external force, normal pork contains about 75 percent of water content, and the moisture content directly influences the taste, aroma, nutrient content, juiciness, tenderness and color of the pork; the combination of the intramuscular fat and the muscle fiber is compact, the diameter of the muscle fiber is thinner, the density is higher, the deposition amount of the intramuscular fat can be more, the retention of water is more facilitated, the water binding capacity is improved, and the taste of meat is more delicate.
Lipids, including lipids including phospholipids and sterols, play an important role in maintaining body functions and energy metabolism together with glucose and proteins. Cholesterol is closely related to diseases such as atherosclerosis, myocardial infarction, coronary heart disease and the like, pork is one of the most main sources of exogenous cholesterol, clinical examination shows that 90% of patients with Alzheimer's disease have atherosclerosis in life, and further research shows that high cholesterol intake can increase the occurrence of Alzheimer's disease.
Therefore, the research on the lipid metabolism of pigs is very important, but an effective marker and a detection kit are not available at present.
Disclosure of Invention
In order to solve the above technical problems, the present invention provides, in one aspect, a genetic marker combination related to the metabolic capacity of porcine metabolism of lipids, the genetic marker combination comprising the genes ATP8, lip and SCD.
In a second aspect, the invention provides a kit for detecting the gene marker combination of claim 1, comprising reagents for detecting the genes ATP8, lip and SCD.
In some embodiments of the invention, the reagents are primer pairs for amplifying the genes ATP8, lip e and SCD, respectively.
In some embodiments of the invention, the primer pair for amplifying the gene ATP8 comprises an upstream primer having the nucleotide sequence shown in SEQ ID No.1 and an upstream primer having the nucleotide sequence shown in SEQ ID No. 2.
In some embodiments of the invention, the primer pair for amplifying the gene LIPE comprises an upstream primer having a nucleotide sequence shown in SEQ ID No.3 and an upstream primer having a nucleotide sequence shown in SEQ ID No. 4.
In some embodiments of the present invention, the primer pair for amplifying the gene SCD comprises an upstream primer having a nucleotide sequence shown in SEQ ID No.5 and an upstream primer having a nucleotide sequence shown in SEQ ID No. 6.
In some embodiments of the invention, the kit further comprises a primer pair for amplifying the reference gene ATCB.
In some embodiments of the invention, the primer pair for amplifying the gene ATCB comprises an upstream primer having a nucleotide sequence shown in SEQ ID No.7 and an upstream primer having a nucleotide sequence shown in SEQ ID No. 8.
In some embodiments of the invention, the kit further comprises a tissue RNA extraction kit.
In some embodiments of the invention, the kit further comprises a reverse transcription reagent.
The invention has the advantages of
The method can be used for rapidly determining the lipid metabolism capability of the pig and provides powerful support for pig breeding.
Drawings
FIG. 1 shows the distribution of transcriptome sequencing Reads in different regions of a reference genome.
FIG. 2 shows the expression levels of the respective genes.
Figure 3 shows a gene expression correlation heatmap.
FIG. 4 shows a differentially expressed gene protein interaction network.
FIG. 5 shows a comparison of fold difference between RNA-seq and qRT-PCR genes.
Detailed Description
In order to make the technical problems, technical solutions and advantageous effects solved by the present invention more apparent, the present invention is further described in detail below with reference to the following embodiments.
Examples
The following examples are used herein to demonstrate preferred embodiments of the invention. It will be appreciated by those of skill in the art that the techniques disclosed in the examples which follow represent techniques discovered by the inventor to function in the invention, and thus can be considered to constitute preferred modes for its practice. Those of skill in the art should, in light of the present disclosure, appreciate that many changes can be made in the specific embodiments which are disclosed and still obtain a like or similar result without departing from the spirit or scope of the invention.
Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs and the disclosures and references cited herein and the materials to which they refer are incorporated by reference.
Those skilled in the art will recognize, or be able to ascertain using no more than routine experimentation, many equivalents to the specific embodiments of the invention described herein. Such equivalents are intended to be encompassed by the following claims.
The experimental procedures in the following examples are conventional unless otherwise specified. The instruments used in the following examples are, unless otherwise specified, laboratory-standard instruments; the test materials used in the following examples were purchased from a conventional biochemical reagent store unless otherwise specified.
Examples
1 method
1.1 test animals and sample Collection
Test animals: selecting 10 (5 male and 5 female) piglets of 70-day-old Gaoligong mountain pigs and Duroc pigs with similar farrowing times and farrowing dates, finishing a feeding test at 260-day-old under the same feeding and management conditions, randomly slaughtering 12 piglets, 6 (3 male and 3 female) piglets of Gaoligong mountain pigs and 6 (3 male and 3 female) piglets of Duroc pigs; the Gaoligong mountain pig is provided by Gaoligong mountain pig breed conservation field in the state of Nujiangzhou, and Duroc pig is provided by Kunming Zhengpo.
Collecting samples: butchering pigs, collecting longissimus dorsi, back fat and liver, placing into RNase-Free freezing tube, placing into liquid nitrogen, and storing in-80 deg.C ultra-low temperature refrigerator; collecting 500g of longissimus dorsi, and storing at-20 deg.C.
1.2 determination of carcass Properties
(1) Live weight before slaughter: weighing before slaughtering for 24h to make it in fasting state to reduce digestive tract content. During this period, sufficient drinking water needs to be supplied, the blood viscosity is reduced to achieve good bleeding, and a 'body condition to be slaughtered' is formed.
(2) Carcass weight: completely depilating after exsanguination, and removing head, tail, hoof and viscera. Removing heads: cutting along the posterior margin of the pig ear root and the first transverse fold below the neck, then separating the atlantoaxial joint, and finally finishing the removal of the head; removing hoofs: firstly, cutting off the wrist joint of the forelimb, and cutting off the hindlimb from the first inter-appendage joint at the inner side of the inter-appendage joint; removing tails and internal organs: the pigtail was cut at the position next to the anus and then opened to remove internal organs, leaving the leaf fat and kidneys. And finally splitting the pig from the middle into a left half carcass and a right half carcass, weighing the two halves within +/-0.5 kg, and recording the weight sum of the two halves of the carcass to obtain the carcass weight.
(3) Slaughter rate: the calculation formula is as follows:
slaughter rate (%) ═ carcass weight/pre-slaughter live weight × 100 (%)
(4) Skin thickness: when the carcass is hung upside down, the thickness of the costal mesothelium is measured by a vernier caliper to 6-7.
(5) Backfat thickness: under the hanging state of the carcass, the average of fat thickness of the shoulder blades at the thickest part of the back midline, the junction of the thoracolumbar vertebra and the junction of the sacral vertebra is called as average backfat thickness.
(6) Eye muscle area: after the carcass is flatly placed, the area of the cross section of the longissimus dorsi at the joint of the thoracolumbar vertebrae of the carcass is increased. The calculation formula is as follows:
eye muscle area (cm)2) Eye muscle thickness (cm) × 0.7.7 ═ eye muscle width (cm) ×
(7) Lean meat percentage: the left half carcass tissue is peeled and divided into four parts, namely fat, bones, muscles (the weight corresponding to the sample to be taken needs to be added) and skin, and the leaf fat and the flower oil of each pig are respectively weighed. The calculation formula is as follows:
carcass lean meat percentage (%). lean meat weight ÷ (lean meat weight + fat weight + skin weight + bone weight) × 100%
1.3 measurement of meat quality Properties
(1) Meat color: muscle color was compared using a color chart. Collecting fresh samples, evaluating once within 2 hours after slaughtering, storing the evaluated samples in a refrigerator at 0-4 ℃, and evaluating once again after 24 hours; marbling evaluation the fresh samples were used simultaneously.
(2) And (3) marbling: measurement of Marble grain the flesh sample was left after flesh color evaluation and was evaluated visually under indoor natural light, and the evaluation of Marble grain was made by 5 points.
(3) Muscle pH: the pH was measured with a pen acidimeter within 45min after slaughtering pigs without breathing and is recorded as pH 1; the pH value is recorded as 24 when the pig is measured 24h after slaughtering.
(4) Cooked meat rate: weighing 100g of psoas major, weighing before steaming, putting the psoas major in an electric cooker, steaming for 30min in boiling water, taking out a sample from the electric cooker, hanging the sample in a cool place indoors, and weighing after cooling for 15-20 min. The calculation formula is as follows:
cooked meat percentage (%) - (weight after steaming/weight before steaming) × 100%
(5) Storage loss: taking the longissimus dorsi within 2h after slaughtering, removing the muscle membrane at the periphery of the meat sample, cutting the meat sample into meat blocks with length, width and height of about 5cm, 3cm and 2cm, weighing and recording, hooking one end of the meat block with an iron hook, suspending the meat block in a plastic food bag, suspending the meat block in a refrigerator at 4 ℃ along the trend of muscle fibers, and weighing and recording after 24 h. The calculation formula is as follows:
storage loss (%) - (pre-storage weight-post-storage weight) ÷ pre-storage weight × 100%
(6) Initial moisture content: taking a meat sample with the longissimus dorsi of about 200g, drying in a 70 ℃ oven for 8h, taking out, cooling at room temperature for 4h, and calculating the initial moisture content according to the weight difference before and after drying.
(7) Dry matter: and (4) measuring by using a drying method.
(8) Intramuscular fat: the determination is carried out by a traditional Soxhlet extraction method.
(9) Crude protein: and (4) measuring by using a full-automatic Kjeldahl apparatus.
(10) Coarse ash content: and (3) measuring by adopting a temperature gradient control method of the high-temperature furnace.
(11) Fatty acid: and determining by GC/MS area normalization method.
(12) Amino acids: refer to GB 5009.124-2016 method.
(13) Cholesterol: refer to GB 5009.128-2016 method.
(14) Diameter of muscle fiber: within 2h after the pig is slaughtered, 1 sample of 0.2cm multiplied by 0.5cm multiplied by 3cm of the longissimus dorsi is taken along the muscle fiber, fixed and marked on a hard paper sheet, and is taken out for flaking after being fixed in 20% nitric acid for 24 h. Under a 10X 40 times microscope, the diameter of 50 muscle fibers is measured by a micrometer, and the average value is multiplied by a corresponding coefficient to obtain the diameter of the muscle fibers of the sample.
(15) Density of muscle fibers: tabletting: preparing a meat block with the length of 3cm, the width of 1.5cm and the height of 0.5cm by taking the longissimus dorsi and the biceps femoris, fixing the long axis of the meat block on a hardboard by a line, immediately putting the meat block into a 4% neutral paraformaldehyde solution for fixing for 24h, then washing a sample by tap water for 24h, sequentially dehydrating the sample by 30% alcohol, 50% alcohol, 70% alcohol and 80% alcohol for 2h, dehydrating the sample by 90% alcohol in a refrigerator at 4 ℃ for overnight, dehydrating by 95% alcohol for 1h (repeated once), dehydrating by 100% alcohol for 1h (repeated once), enabling xylene to be transparent for 20min (repeated once), penetrating wax for 2h, embedding, modifying the slices to be 6 mu m thick, selecting the slices, spreading the slices in 55 ℃ warm water, fishing out the slices, and drying the slices in a 37 ℃ constant temperature cabinet; dewaxing: soaking the slices in xylene for 10min (repeating once) for dewaxing, with anhydrous ethanol for 2min, 95% ethanol, 80% ethanol, and 50% ethanol each for 5 min; dyeing: staining the sliced hematoxylin for 12min, washing with tap water for 10min, washing with distilled water for 1min, differentiating with 0.5% hydrochloric acid alcohol for 30s, washing with distilled water for 30min, soaking in eosin for 3min, soaking in 80% alcohol, 95% alcohol and 100% alcohol for 5min, soaking in xylene for 5min, and sealing with neutral gum; the prepared section is placed in a photomicrograph for measurement.
1.4 extraction of Total RNA
Total RNA extraction was performed according to the method of TIANGEN DP419 kit instructions.
1.5 library preparation and sequencing on machine
After the total RNA sample is qualified, eukaryotic mRNA is enriched by magnetic beads with oligo (dT). Then fragmentation buffer is added to break mRNA into short fragments, the first cDNA strand is synthesized by using mRNA as a template and using hexabasic random primers (randomhexamers), and the second cDNA strand is synthesized by adding buffer, dNTPs, RNase H and DNA polymerase I. And purifying by using a QiaQuick PCR kit, adding EB buffer solution for elution, repairing the tail end, connecting a sequencing joint, performing fragment size selection by using agarose gel electrophoresis, and finally performing PCR amplification to enrich cDNA to finish library preparation.
After the library is constructed, firstly, Qubit 2.0 is used for preliminary quantification, and then Agilent 2100 is used for detecting the insert size of the library, wherein the insert size is a unit for direct sequencing in high-throughput sequencing, and after the insert size meets the expectation, the qPCR method is used for accurately quantifying the effective concentration (>2nM) of the library so as to ensure the quality of the library. After the library is qualified, performing PE150 high-throughput double-end sequencing, namely sequencing the two ends of each insert, and respectively sequencing 150bp at each end, wherein the length distribution of the insert is known, so that the sequences at the two ends of the insert and the length between the two sequences can be known during double-end sequencing, and subsequent comparison and analysis are facilitated.
1.6 RNA-seq bioinformatics analysis
(1) Quality assessment of sequencing data: according to the invention, Fast QC analysis software is used for carrying out sequencing quality evaluation on original Reads files obtained by sequencing, raw Reads obtained by sequencing contain a small amount of repeated low-quality Reads with connectors, and the Reads can influence comparison and subsequent analysis quality, so that offline Reads need to be filtered to obtain clean Reads. Firstly removing reads with low overall mass, then removing reads with the unknown base N proportion of more than 10%, then removing reads with the length of less than 20, and finally removing the adaptor sequence contained in the reads to form clean reads.
(2) Alignment of sequencing reads: clean Reads are compared to a reference genome Susscrofa 11.1 by using HISAT2 software, and Clean Reads are compared to a reference gene by using bowtie2 to perform genome mapping analysis, so that the comparison rate of a sample is influenced by a plurality of factors such as the sample condition and the species genome condition, and generally the ratio is between 60% and 90%.
(3) Quantitative and differential expression analysis: data quality control of qualified samples, their quantitative analysis using Kallisto software, using edgeR calculations to obtain counts values, after standardization using TPM (trans Per Million) values, and analysis of differences between two biological replicates. edgeR is a Bioconductor software package that studies differential expression of repeat count data, primarily using read numbers from different technology platforms to identify differential expression or differential markers. Analyzing the differential expression condition of the gene in each sample by using DESeq software, wherein the differential gene is a gene with obviously different expression amounts by screening a threshold value | logFC | > more than or equal to 1 and an FDR less than or equal to 0.05.
(4) GO enrichment analysis of differentially expressed genes: the GO (Gene association) database has standardized descriptions of gene products from Molecular Function (MF), Biological Process (BP) and Cellular Component (CC), respectively, with GO annotation of differentially expressed genes using goseq1.22.0(http:// bioconductor. org/packages/goseq /). The method comprises the steps of obtaining GO information of each gene by corresponding relation between the known genes and GO term in a GO database, calculating a gene list and the number of the genes of each term by using the differential genes annotated by GO term, finding GO items remarkably enriched in differential expression genes compared with the whole genome background by applying super-geometric inspection, and finding out biological functions remarkably related to the differential expression genes by using P <0.05 as a threshold value of the remarkably enriched genes.
(5) KEGG enrichment analysis of differentially expressed genes: KEGG (Kyoto Encyclopedia of Genes and genomes) is the main public database for Pathway, Pathway analysis of differentially expressed Genes using KOBAS, Pathway software found Pathway with FDR <0.05 compared to the whole genome background was a significantly enriched Pathway for differentially expressed Genes, where FDR values are corrected P values.
1.7 fluorescent quantitation of differential genes
(1) Reverse transcription: obtaining cDNA was performed according to the procedures described for the TSK302S kit, first preparing System I as follows:
RNA template × μ l to 10 ng- μ g
gDNA remover 1μl
10×gDNA remover Buffer 1μl
RNase-free water to 10. mu.l
Incubating the system I at 42 ℃ for 2min, then incubating at 60 ℃ for 5min, adding the following components, uniformly mixing, incubating at 25 ℃ for 10min, then incubating at 55 ℃ for 30min, finally incubating at 85 ℃ for 5min, and refrigerating for later use.
dNTP Mix1μl
Goldenstar Randomer 1μl
5×Goldenstar Buffer 4μl
DTT 1μl
Goldenstar RT6 1μl
RNase-free water 2μl
(2) Primer: primer design is completed by Primer 5.0 software, and the Primer is sent to Kunming Optimae Biotechnology Limited to be synthesized, and the Primer sequence and PCR annealing temperature are shown in Table 1.
TABLE 1 primer sequences
(3) qRT-PCR System: preparation of 20. mu.l of the resulting mixture was carried out according to the method described in the kit of TSE202
The following were used:
2×T5 Fast qPCR Mix 10μl
10μM Primer F 0.8μl
10μM Primer R 0.8μl
50×ROX Reference DyeⅠ 0.4μl
Template cDNA 1μl
ddH2O 7μl
(4) qRT-PCR amplification conditions: qRT-PCR amplification was performed according to the procedures described in the TSE202 kit, and the reaction conditions are shown in Table 2.
TABLE 2 qRT-PCR amplification conditions
1.8 statistics and analysis of data
(1) The Excel table is used for collating the original data of the production performance of the Gaoligong mountain pigs and Duroc pigs, the TTEST program of the SAS9.0 software t test is used for carrying out the difference significance test on data, and the test data is expressed by 'mean +/-standard error (X +/-SE)'; correlation analysis was performed using the CORR process of SAS9.0 software.
(2) When the GO and the KEGG are subjected to the hypergeometric test, the calculation formula of the P value is as follows:
when the GO entry significance analysis is carried out, N is the number of genes with GO annotations in all the genes, N is the number of differentially expressed genes in N, M is the number of genes annotated as a certain specific GO term in all the genes, and M is the number of differentially expressed genes annotated as a certain specific GOterm. When the KEGG Pathway significance analysis is carried out, N is the number of genes with Pathway annotations in all genes, N is the number of differentially expressed genes in N, M is the number of genes annotated as a specific Pathway in all genes, and M is the number of differentially expressed genes annotated as a specific Pathway.
(3) In the fluorescent quantitative test, ACTB (beta-actin) is used as an internal reference gene, a Ct value represents the cycle number of a target amplification product reaching a set threshold value, and a-delta Ct value is used for calculating the difference multiple between an experimental group and a control group, wherein the calculation formula is as follows:
ΔCt＝Cttarget gene－CtInternal reference gene；
－ΔΔCt＝－(ΔCtExperimental group－ΔCtControl group)
2. Results
2.1 comparative analysis of Productivity and Nutrition values of Gaoligong mountain pigs and Duroc pigs
2.1.1 comparative analysis of growth Performance
The average daily gain of the Gaoligong mountain pigs is 276.58g/d, the average daily gain of the Duroc pigs is 502.36g/d, the weight of the Gaoligong mountain pigs is 225.78g/d lower than that of the Duroc pigs (P is less than 0.01), the feed weight ratio of the Gaoligong mountain pigs is 4.02 which is obviously higher than that of the Duroc pigs by 3.08 and 0.94(P is less than 0.05), and the growth performance results of the Gaoligong mountain pigs and the Duroc pigs are shown in Table 3.
TABLE 3 comparison of growth Performance of Gaoligong mountain pigs and Duroc pigs
| Item | Gaoligong mountain pig | Duroc pig |
| Number of |
10 | 10 |
| Day age (d) | 260 | 260 |
| Test period (d) | 170 | 170 |
| Average daily gain (g/d) | 276.58±9.61A | 502.36±39.00B |
| Material to weight ratio | 4.02±0.15a | 3.08±0.24b |
Note: the difference of different lower case letters in the same row is obvious (P < 0.05), and the difference of different upper case letters is extremely obvious (P < 0.01); the same applies below.
2.1.2 comparative analysis of carcass Performance
After the feeding test, the slaughter test of the test pigs was carried out in groups, and the results are shown in Table 4, the live weight (60.28kg) and the eye muscle area (16.10 cm) of the Gaoligong mountain pigs before slaughtering2) The bone rate (9.44 percent) and the lean meat rate (42.05 percent) are respectively lower than those of Duroc pigs by 46.13kg and 30.63cm23.68 percent and 20.34 percent of the total weight of the pigs, the skin rate (13.02 percent) and the fat rate (35.48 percent) of the Gaoligong mountain pigs are respectively 2.89 percent and 22.5 percent higher than those of Duroc pigs, and the difference is very obvious (P is less than 0.01); the carcass weight (43.41kg) of the Gaoligong mountain pig is 34.48kg lower than that of the Duroc pig, the trifoliate thickness (35.38mm) is 11.35mm higher than that of the Duroc pig, and the difference is obvious (P is less than 0.05); the dressing percentage and the skin thickness were not significantly different between the two pig species (P > 0.05). From the carcass performance of the two pig breeds after slaughter, it can be seen that the Gaoligong mountain pigs belong to fatty pigs as the local pig breed in Yunnan, while Duroc pigs belong to lean pigs as the foreign introduced pig breed.
TABLE 4 comparison of carcass Performance in Gaoligong mountain pigs and Duroc pigs
2.1.3 comparative analysis of meat Performance
Meat quality performance of meat samples of two test pig species after slaughter and divisionThe results of the analysis are shown in Table 5, the cooked meat percentage (64.44%) and the crude fat (5.74%) of Gaoligong mountain pigs are respectively 6.55% and 3.62% higher than those of Duroc pigs, the fiber diameters of longissimus dorsi (38.83 μm) and biceps femoris (46.29 μm) are respectively 17.75 μm and 21.97 μm lower than those of Duroc pigs, the difference is extremely significant (P < 0.01), the meat of Gaoligong mountain pigs is more tender and succulent, meanwhile, the storage loss (4.63%) and the cholesterol content (43.20mg/100g) are respectively 8.37% and 10.1mg/100g lower than those of Duroc pigs, the pH is 24, and the longissimus dorsi (305.17N/mm)2) And the muscle fiber density of biceps femoris (248.40N/mm2) is 0.44, 65.67N/mm2 and 49.15N/mm higher than that of Duroc pigs, respectively2The difference is obvious (P is less than 0.05), which indicates that the pork quality of Gaoligong mountain has better water retention and better mouthfeel and is healthier; the crude protein (25.77%), the crude ash (1.14%) and the initial moisture (69.04%) of the Duroc pigs are respectively 1.96%, 0.18% and 5.88% higher than those of the Duroc pigs, and the difference is extremely obvious (P is less than 0.01); there were no significant differences between the two swine species (P > 0.05) in pH1, flesh color score and marbling score.
TABLE 5 comparison of meat quality of Gaoligong mountain pigs and Duroc pigs
2.1.4 comparative analysis of muscle Nutrition of Gaoligong mountain pigs and Duroc pigs
2.1.4.1 fatty acid
The content of octanoic acid in the Gaoligong mountain pigs is 0.002 percent lower than that of Duroc pigs, while the content of eicosapentaenoic acid is 0.396 percent higher than that of the Duroc pigs, and the difference is very obvious (P is less than 0.01); the contents of monounsaturated fatty acid, hexadecenoic acid and eicosanoic acid of the Gaoligong mountain pigs are respectively 4.07 percent, 1.033 percent and 0.098 percent higher than those of Duroc pigs, the content of docosaenoic acid is 0.028 percent lower than that of the Duroc pigs, and the difference is obvious (P is less than 0.05); saturated fatty acids, unsaturated fatty acids, polyunsaturated fatty acids, and the remaining 19 fatty acids tested were not significantly different between the two test groups (P > 0.05).
The analytical results are shown in Table 6.
TABLE 6 comparison of the muscle fatty acids of Gaoligong mountain pigs with Duroc pigs
2.1.4.2 amino acid
The essential amino acids include 8 amino acids of lysine, tryptophan, phenylalanine, methionine, threonine, isoleucine, leucine and valine, and the umami amino acids include 6 amino acids of glutamic acid, aspartic acid, phenylalanine, alanine, glycine and tyrosine. Between the two test groups, the content of essential amino acids, umami amino acids and the remaining 15 amino acids were not significantly different (P > 0.05), except that the content of methionine (Met) in duroc pigs was significantly higher than that in gaolingshan pigs (P < 0.01). The analytical results are shown in Table 7.
TABLE 7 comparison of intramuscular amino acids of Gaoligong mountain pigs and Duroc pigs
| Item | Gaoligong mountain pig | Duroc pig |
| Aspartic acid (Asp) | 2.41±0.09 | 2.53±0.10 |
| Glutamic acid (Glu) | 3.72±0.12 | 3.96±0.10 |
| Serine (Ser) | 0.89±0.03 | 0.95±0.04 |
| Histidine (His) | 0.89±0.06 | 1.00±0.02 |
| Glycine (Gly) | 1.01±0.04 | 1.03±0.08 |
| Threonine (Thr) | 1.03±0.03 | 1.08±0.03 |
| Arginine (Arg) | 1.86±0.10 | 2.00±0.04 |
| Alanine (Ala) | 2.74±0.08 | 2.90±0.07 |
| Tyrosine (Tyr) | 0.84±0.03 | 0.86±0.02 |
| Valine (Val) | 1.11±0.04 | 1.05±0.03 |
| Methionine (Met) | 0.59±0.02A | 0.68±0.01B |
| Phenylalanine (Phe) | 0.99±0.03 | 0.99±0.03 |
| Isoleucine (Ile) | 1.13±0.04 | 1.06±0.04 |
| Leucine (Leu) | 1.96±0.06 | 2.00±0.04 |
| Lysine (Lys) | 1.97±0.11 | 1.97±0.17 |
| Proline (Pro) | 0.75±0.05 | 0.75±0.08 |
| Essential Amino Acids (EAA) | 8.78±0.29 | 8.82±0.31 |
| Delicious Amino Acid (DAA) | 11.72±0.37 | 12.27±0.40 |
| Sum of the above hydrolyzed amino acids | 23.90±0.81 | 24.8±0.84 |
2.2 sequencing data and quality control thereof
In the invention, transcriptome sequencing is carried out on 36 samples of the liver, the longissimus dorsi and the back fat of 6 Gaogong mountain pigs and 6 Duroc pigs, wherein the data quality of 6 samples of 2 Duroc pigs is unqualified and the samples are not used for the comparative transcriptome analysis. The data of the rest 30 samples are qualified, the total data volume of the qualified samples is 352.0G, the average data volume of each sample is 11.7G, and the minimum data volume obtained by liver tissue (GG _6_ Fat) of the Gaoligong mountain pig No.6 is 7.4G. The Raw sequence Raw reads obtained by sequencing are 80,439,504.7 on average, contain connected joints and poor-quality read fragments, and the Clean sequence read Clean reads are 78,308,223.3 on average by filtering the Raw sequence. The analysis of the quality values of the base distribution and the sequencing data shows that the average GC content is 52.7 percent, the average Q30 content is 92.4 percent, the sequencing data quality is reliable, and the subsequent data analysis can be carried out.
2.3 sequence alignment
The obtained Clean reads and a reference genome Sus scrofa11.1 are subjected to sequence alignment analysis, and aligned to three different regions of the genome: exons (Exon), introns (Intron) and Intergenic regions (Intergenic), aligned to about 81% of the sequence in the Exon region, aligned to about 6% of the sequence in the Intron region and aligned to about 13% of the Intergenic region with incomplete gene annotation. The comparison rate of Clean reads and the reference genome of each sample averagely reaches 89.6%, which indicates that the data can be well matched with the reference genome correctly, and the subsequent analysis requirements are completed, as shown in fig. 1.
2.4 Gene quantification and correlation analysis
And carrying out gene quantitative analysis after the data is detected to be qualified. To log2(TPM) standardized gene expression values are mapped, and the overall expression condition of each sample gene is visually reflected, as shown in figure 2. The upper left corner and the upper right corner are gene expression box type diagrams respectivelyAnd violin diagrams, the abscissa is different samples, and the ordinate is a standardized gene expression value; the lower panel shows the expression density of the gene, with the abscissa being the normalized gene expression value and the ordinate being the density value of the different expression values. The degree of dispersion of the gene expression level distribution of duroc and alpine pigs can be checked by TPM box plots.
Log used in the invention2(TPM) normalized gene expression values were used to calculate Pearson correlation coefficient (Pearson correlation coefficient) between samples, reflecting the similarity of gene expression patterns between samples. Fig. 3 shows a heat map of the correlation analysis between samples. Where a color near red represents a higher correlation coefficient than average and a color near green represents a lower correlation coefficient than average. The graph shows that the samples are grouped together according to tissue classification on the whole, for example, Liver tissues D _1_ Liver to GG _5_ Live are grouped together and are of a single type, and the correlation coefficient is the largest and is higher than the average value; the longest dorsi Muscle and the dorsi adipose tissues GG _3_ Fat are grouped into a large group, and the correlation coefficient is small, wherein the longest dorsi Muscle tissues are grouped into a group, the dorsi adipose tissues are grouped into a group, and the D _1_ Fat, GG _3_ Fat and GG _6_ Muscle are crossed between the two tissues, which indicates that the expression values of the longest dorsi Muscle and the dorsi adipose genes are similar.
2.5 analysis of differentially expressed genes in Gaoligong mountain pigs and Duroc pigs
In the present invention, only genes with significant differences (P < 0.05) between two pig species were analyzed, and genes with insignificant differences (P > 0.05) were not discussed.
2.5.1 differentially expressed genes for liver, longissimus dorsi and dorsal lipids
The differential gene takes | logFC | > 1 and FDR ≤ 0.05 as the screening conditions to obtain the gene with significant expression difference, the gene up-regulated in Gaoligong mountain pigs is down-regulated in Duroc pigs, and the gene up-regulated in Duroc pigs is down-regulated in Gaoligong mountain pigs similarly. In the liver, two pig species have 99 differentially significant expression genes, compared with Duroc pigs, the Gaoligong mountain pigs have 51 up-regulated genes and 48 down-regulated genes, wherein the main up-regulated genes of the Gaoligong mountain pigs comprise ASAH2, PAQR4, PLP1, CYP1A1, MUM1L1, LAMB3, WNT11 and the like, and the down-regulated genes comprise PDE1C, CLEC18C, APLNR, BEX1, RRAGD, MGP, EDN3, FZD10 and the like; in longissimus dorsi, 140 differentially and significantly expressed genes are shared between two pig breeds, and compared with Duroc pigs, the Gaoligong mountain pigs have 127 up-regulated genes and 13 down-regulated genes, wherein the main up-regulated genes of the Gaoligong mountain pigs comprise ZNF385A, LAMB3, SNCG, PRG4, MCT7, TPPP3, SCD and the like, and the down-regulated genes comprise LYSMD2, CIT, PDZD9, LRTM1, SLC9A7, SPP1 and the like; in back fat, two pig species share 20 differentially and significantly expressed genes, compared with Duroc pigs, the Gaoligong mountain pigs have 13 up-regulated genes and 7 down-regulated genes, wherein the main up-regulated genes of the Gaoligong mountain pigs comprise CDS1, BASP1, ADAM8, RAB7B, ETNPPL, SCD, PADI2, SCIN and the like, and the down-regulated genes comprise CCL28, ATP8, WFDC2, EDN3 and the like. The genes with obvious expression difference are used for subsequent GO and KEGG enrichment analysis.
2.5.2 GO functional enrichment analysis of three tissues
GO annotation is carried out on differentially expressed genes by using goseq1.22.0(http:// bioconductor. org/packages/goseq /), the known genes in a GO database and GO term are in corresponding relation to obtain GO information of each gene, and GO classification is carried out on the differentially expressed genes according to Biological Processes (BP), Molecular Functions (MF) and Cell Components (CC). And then, calculating a gene list and the number of genes of each term by using the differential genes annotated by the GO term, and finding out GO items which are obviously enriched in the differential expression genes compared with the whole genome background by applying a super-geometric test, thereby finding out the biological functions obviously related to the differential expression genes.
GO enrichment is carried out on differential genes of three tissues between two experimental pig species, 5 GO term genes are found to be simultaneously and obviously enriched in two tissues, and the GO term genes which are simultaneously and obviously enriched in three tissues are not found temporarily. Laminin-5complex (GO: 0005610) and neuron cell bodies (GO: 0043025) of cell components are significantly enriched in liver and longissimus dorsi of the Gaoligong pigs respectively, wherein the included genes LAMB3, DNER and NRSN1 are all significantly highly expressed in the Gaoligong pigs; cellular components in which ATP8 gene is involved: proton-transporting ATP synthase complex (GO: 0000276, GO:0045263, GO:0005753) was significantly enriched in both the liver and back fat of Duroc pigs, respectively.
(1) Functional enrichment analysis of liver differential genes
Carrying out GO function enrichment on differentially expressed genes in livers of Gaoligong mountain pigs and Duroc pigs, and classifying to obtain 412 GO entries, wherein 161 entries are significantly enriched (P is less than 0.05), and 121 (accounting for 75.1%) genes in a biological process contain 30 differential genes; the molecule has 27 functions (16.8 percent) and comprises 17 differential genes; the cell fraction was 13 (8.1%) containing 14 differential genes. It can be concluded that the biological process is the main biological function performed by differentially expressed genes in liver of Gaoligong mountain pigs and Duroc pigs.
Item analysis for enrichment of differentially expressed genes in Gaoligong mountain pigs and Duroc pigs, wherein the differentially expressed genes are up-regulated in the liver of Gaoligong mountain pigs, and the Biological Process (BP) is mainly significantly enriched in drug metabolism process, steroid metabolism process, neuroendocrine cell differentiation, lipid hydroxylation transformation and growth factor β2The Molecular Function (MF) is mainly and remarkably enriched in the activities of oxido-reductase, 2-aminoadipate transaminase, vitamin D24-hydroxylase, estrogen 16 α -hydroxylase and pyridoxal phosphate combination, and the Cell Component (CC) is mainly and remarkably enriched in laminin-5complex, striated muscle thin-filament, very low-density lipoprotein particles, neuron cell body, guanylate cyclase complex, and the like.
The method has the advantages that the differential gene of the expression is reduced in the liver of the Gaoligong mountain pig, and the Biological Process (BP) is mainly and significantly enriched in D-alanine (serine) transport, positive regulation of phosphorylation of inhibitory G protein-coupled receptors, maturation of cerebellar granular layers, a deoxyadenosine catabolic process, negative regulation of adenosine receptor signal pathways and the like; the Molecular Function (MF) is mainly and remarkably enriched in pyrroline-5-carboxylic acid reductase activity, ion transmembrane transporter activity, protein markers, deaminase activity, adenosine deaminase activity, myosin combination, endopeptidase inhibitor activity and the like; the Cell Component (CC) is mainly and remarkably enriched in GTR1-GTR2 GTPase complex, EGO complex, mitochondrial proton transport ATP synthase complex, autophagosome membrane, ADA2/GCN5/ADA3 transcription activation complex and the like
(2) Functional enrichment analysis of the longissimus dorsi differential genes
Carrying out GO function enrichment on differentially expressed genes in longissimus dorsi of Gaoligong mountain pigs and Duroc pigs, and classifying to obtain 956 GO entries, wherein 363 entries are significantly enriched (P is less than 0.05), 273 (accounting for 75.2%) of biological processes contain 74 differential genes; the molecule has 73 functions (accounting for 20.1 percent) and comprises 53 differential genes; the cell fraction was 17 (4.7%) containing 51 differential genes.
Item analysis of differential expression gene enrichment of the Gaoligong mountain pigs and Duroc pigs, wherein the differential gene of up-regulated expression in the longissimus dorsi of the Gaoligong mountain pigs, and the Biological Process (BP) is mainly and significantly enriched in an oxidation-reduction process, fatty acid beta oxidation, positive regulation of fat cell differentiation, negative regulation of smooth muscle cell proliferation, unsaturated fatty acid biosynthesis process, lipid metabolism process and the like; the Molecular Function (MF) is mainly and remarkably enriched in the activities of oxidoreductase, Wnt protein binding, glutathione peroxidase, polysaccharide binding, protein self-binding and the like; the Cellular Component (CC) is mainly significantly enriched in lipid droplets, plasma membrane-immobilized components, mitochondria, and laminin-5complex, etc.
The differential gene of the expression is reduced in the longissimus dorsi of the Gaoligong mountain pigs, and the Biological Process (BP) is mainly and obviously enriched in the androgen decomposition process, the positive control of estradiol secretion, the transmembrane introduction of sodium ions, the pH regulation and the like; the Molecular Function (MF) is mainly and remarkably enriched in proton transporter activity, inversion activity, protein kinase inhibitor activity and the like; cellular Components (CC) are predominantly significantly enriched in the endoplasmic reticulum, the mitochondrial membrane compartment, and the recirculating endosomes surrounding the nucleus.
(3) Functional enrichment analysis of differential genes in back fat
Carrying out GO functional enrichment on differentially expressed genes in the back fat of Gaoligong mountain pigs and Duroc pigs, and classifying into 172 GO entries, wherein 120 entries are significantly enriched (P is less than 0.05), 82 entries are obtained in a biological process (accounting for 68.3 percent), and 13 differential genes are contained; the molecule has 21 functions (accounting for 17.5 percent) and comprises 12 differential genes; the cell fraction was 17 (14.2%) containing 14 differential genes.
Item analysis for enriching differentially expressed genes of Gaoligong mountain pigs and Duroc pigs, wherein the differentially expressed genes are up-regulated in the back fat of the Gaoligong mountain pigs, and the Biological Process (BP) is mainly and significantly enriched in histone H3-R26 citrullination, negative regulation of lymphocyte chemotaxis, positive regulation of C-C chemokine receptor CCR7 signal channel, regulation of lipoprotein metabolic process, positive regulation of acute inflammatory response and the like; molecular Function (MF) is mainly significantly enriched in oxidoreductase activity, stearoyl-CoA 9-desaturase activity, transaminase activity, estrogen receptor binding, etc.; the Cell Component (CC) is mainly and remarkably enriched in phagolysosome, alpha 9-beta 1 integrin-vascular cell adhesion molecule-1 complex, chromatin transcription activity and the like.
Analyzing the items of the enrichment of the differentially expressed genes of the Gaoligong mountain pigs and Duroc pigs, wherein the differentially expressed genes are down-regulated in the back fat of the Gaoligong mountain pigs, and the main significance of the Biological Process (BP) is enriched in the negative regulation of leucocyte restriction or rolling, the regulation of the activity of a signal receptor, the regulation of vasoconstriction, the ATP biosynthesis process, the negative regulation of the activity of peptidase and the like; the Molecular Function (MF) is mainly and remarkably enriched in aspartic endopeptidase inhibitor activity, proton transmembrane transporter activity, peptidase inhibitor activity, chemokine activity and the like; the Cellular Components (CC) are mainly significantly enriched in cells, extracellular regions, mitochondrial membranes, and proton-transporting ATP synthase complexes, among others.
2.5.3 KEGG pathway analysis of differentially expressed genes
Applying hyper-geometric test to the differential genes between the three tissues of the Gaoligong mountain pig and the Duroc pig, and finding out Pathway significantly enriched in the differential expression genes compared with the whole genome background. Pathway analysis was performed using the KEGG database. In liver tissues, Pathway enrichment analysis finds that the differential genes participate in 62 biological metabolic pathways in total, wherein 11 KEGG pathways are obviously enriched (P is less than 0.05), and 31 differential genes are totally contained, wherein the main metabolic pathways comprise tryptophan metabolism, steroid hormone biosynthesis, mTOR signal transduction Pathway, arachidonic acid metabolism, amino acid biosynthesis, purine metabolism and the like. In the longissimus dorsi, Pathway enrichment analysis finds that the differential genes participate in 107 biological metabolic pathways together, 6 KEGG pathways are extremely obviously enriched (P is less than 0.01), 28 differential genes are shared, and the main metabolic pathways comprise a PPAR signal Pathway, an AMPK signal Pathway, fatty acid metabolism, unsaturated fatty acid biosynthesis and the like; there were 3 KEGG pathways significantly enriched (P < 0.05), for a total of 6 differential genes, the metabolic pathways being the vasoconstrictor system, fat digestion absorption and fatty acid degradation. In the back fat tissue, Pathway enrichment analysis finds that the differential genes participate in 26 biological metabolic pathways in total, wherein 1 KEGG Pathway is greatly enriched (P is less than 0.01), 2 differential genes exist, and the metabolic pathways are fat metabolism; there were 2 KEGG pathways significantly enriched (P < 0.05) with a total of 3 distinct genes, the metabolic pathway being the biosynthesis of unsaturated fatty acids and cytokine receptor interactions. From three tissues, it can be seen that fat metabolism and amino acid metabolism are the major pathways for differential gene enrichment in Gaoligong mountain pigs and Duroc pigs.
2.5.4 protein interaction network analysis of differentially expressed genes
In order to better understand the transcriptome difference between two experimental pig species, the three genes with significant tissue expression difference were subjected to protein interaction network analysis, the relationship of gene-regulated protein interactions was analyzed in the STRING network database, the results were visualized and modified using Cytoscape software, and the main protein interaction network was shown in fig. 4. In the figure, the thicker the connecting line, the stronger the action relationship between the two proteins, the more important the functions of the proteins are, the larger the nodes are, and the larger the nodes are, the larger the PPARG (hierarchy-7), lip (hierarchy-6), FASN (hierarchy-4), SCD (hierarchy-4), CIDEC (hierarchy-4), AGT (hierarchy-4), CIDEA (hierarchy-4), PPAP2C (hierarchy-4), and pin 1 (hierarchy-4), which indicate that the connection between these gene-regulated proteins and other gene-regulated proteins is close.
2.6 correlation analysis of production Performance with the differential Gene
In the invention, the test group and the control group are fed under the condition of consistent environmental conditions in the early stage, the difference of the production performance between the two pig breeds is mainly influenced by genetic difference, and the test result shows that a plurality of production performances between the Gaoligong mountain pigs and Duroc pigs have obvious difference, which is presumed to be caused by variety difference and is regulated and controlled by genes. The invention classifies the expression quantity of three genes with significant tissue difference and the production performance with significant difference of two pig species and carries out correlation analysis, the invention discovers that the Duroc is significantly superior to the Gaoligong mountain pig in the aspects of carcass lean meat percentage, fat percentage and eye muscle area, the main up-regulated genes of the Duroc comprise ATP8, RRAGD, PDE1C and UBL5, wherein, the ATP8 gene is significantly expressed in the liver tissue of the Duroc and is strongly negatively correlated with the eye muscle area, and the correlation coefficient is-0.97 (P is less than 0.05); in the aspects of muscle fiber density, diameter and intramuscular fat, the Gaoligong mountain pig is obviously superior to Duroc pigs, and the up-regulated genes of the Gaoligong mountain pig mainly comprise TMOD2, SLC9A7, SCD, FASN and ELOVL5, wherein the FASN gene is obviously expressed in the longissimus dorsi of the Gaoligong mountain pig, is in strong positive correlation with the diameter of muscle fibers, and has a correlation coefficient of 0.83(P < 0.05); in the aspect of muscle cholesterol, the content of the Gaoligong mountain pigs is obviously lower than that of Duroc pigs, and the main up-regulated genes of the Gaoligong mountain pigs comprise CIDEA, CIDEC, LIPE, PLIN1, CYP4B1, CYP1A1, CYP2B22, RETSAT and PCYOX1, wherein CIDEA, CIDEC, LIPE, PLIN1, CYP4B1 and RETSAT genes are obviously expressed in the longissimus dorsi of the Gaoligong mountain pigs and have stronger negative correlation with the cholesterol content, correlation coefficients are-0.86, -0.84, -0.83 and-0.86 (P < 0.05), and the expression level of the LIPE gene is the highest. The genes are obviously related to the production performance, the production performance can be speculated to be possibly regulated by the related genes, the genes can be used as candidate genes of Gaoligong mountain pigs, and the specific regulation mechanism needs to be further researched.
In the aspect of growth performance daily gain, the Gaoligong mountain pigs are extremely lower than Duroc pigs, the main up-regulated genes of the Gaoligong mountain pigs comprise WNT11, NPR2, SDC4, CDS1 and ADAM8, and the correlation with the daily gain of the Gaoligong mountain pigs is not significant (P is more than 0.05); in the aspect of muscle monounsaturated fatty acid, the content of the Gaoligong mountain pigs is obviously higher than that of Duroc pigs, the main up-regulated genes of the Gaoligong mountain pigs comprise AADAT, SCD, FASN, ELOVL5 and ECI1, and the correlation with the content of the monounsaturated fatty acid of the Gaoligong mountain pigs is not obvious (P is more than 0.05); in terms of crude protein of muscle, the Duroc pigs are significantly higher than those of Gaoligong mountain pigs, the main up-regulated genes of the Duroc pigs comprise SLC7A10, ADA and FBXL4, and the correlation with the crude protein content of the Duroc pigs is not significant (P is more than 0.05). The correlation analysis of the productivity with the difference gene is shown in Table 8.
TABLE 8 correlation analysis of production Performance with differential genes
2.7 fluorescent quantitative PCR verification
Verifying whether the RNA-seq result is accurate, selecting 3 major genes related to lipid metabolism, namely ATP8, LIPE, SCD and 1 internal reference ACTB (beta-actin) gene, performing relative quantitative verification in three tissues of two pig species by utilizing qRT-PCR respectively, and measuring the difference multiple of gene expression of Gaoligong mountain pigs and Duroc pigs by using a delta Ct value, wherein the result is shown in a table 9; the fold difference of gene expression measured by RNA-seq in Gaoligong mountain pigs compared to Duroc pigs is expressed as logFC values. The results of the gene difference multiples measured by the two methods are shown in fig. 5, the expression multiples of 3 genes measured by the two methods are slightly different but the expression trends are basically consistent, the difference multiples measured by the two methods are subjected to correlation analysis by using the CORR process of SAS, the data measured by the two methods are obviously correlated (P is less than 0.05), and the correlation coefficient r is 0.79, so that the RNA-Seq result has better accuracy and reliability.
TABLE 9 relative expression levels of ATP8, LIPE, and SCD genes in three tissues
All documents referred to herein are incorporated by reference into this application as if each were individually incorporated by reference. Furthermore, it should be understood that various changes and modifications of the present invention can be made by those skilled in the art after reading the above teachings of the present invention, and these equivalents also fall within the scope of the present invention as defined by the appended claims.
Sequence listing
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<120> gene marker related to porcine lipid metabolism ability and detection kit
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Claims (10)
1. A genetic marker panel associated with the ability of a pig to metabolize lipid comprising the genes ATP8, lip and SCD.
2. A kit for detecting the gene marker combination of claim 1, comprising reagents for detecting the genes ATP8, LIPE and SCD.
3. The kit of claim 2, wherein the reagents are primer pairs for amplifying the genes ATP8, lip and SCD, respectively.
4. The kit according to claim 3, wherein the primer pair for amplifying the gene ATP8 comprises an upstream primer having the nucleotide sequence shown in SEQ ID No.1 and an upstream primer having the nucleotide sequence shown in SEQ ID No. 2.
5. The kit according to claim 3, wherein the primer pair for amplifying the gene LIPE comprises an upstream primer having a nucleotide sequence shown by SEQ ID No.3 and an upstream primer having a nucleotide sequence shown by SEQ ID No. 4.
6. The kit according to claim 3, wherein the primer pair for amplifying gene SCD comprises an upstream primer having a nucleotide sequence shown by SEQ ID No.5 and an upstream primer having a nucleotide sequence shown by SEQ ID No. 6.
7. The kit according to any one of claims 3 to 6, wherein the kit further comprises a primer pair for amplifying an internal reference gene ATCB.
8. The kit according to claim 7, wherein the primer pair for amplifying the gene ATCB comprises an upstream primer having a nucleotide sequence shown in SEQ ID No.7 and an upstream primer having a nucleotide sequence shown in SEQ ID No. 8.
9. The kit of any one of claims 3-6, wherein the kit further comprises a tissue RNA extraction kit.
10. The kit of claim 9, wherein the kit further comprises a reverse transcription reagent.
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