Primer composition for integrated detection of SNP (Single Nucleotide Polymorphism) genetic marker and DNA (Deoxyribose Nucleic Acid) methylation molecular marker and application thereof

Abstract

The invention discloses a primer composition for integrated detection of an SNP (Single Nucleotide Polymorphism) genetic marker and a DNA (Deoxyribose Nucleic Acid) methylation molecular marker and application of the primer composition. The primer composition provided by the invention is composed of 142 kinds of primers; the nucleotide sequences of the 142 primers are sequentially as shown in SEQ ID NO: 1 to SEQ ID NO: 142. According to the primer composition, multiple PCR amplification is carried out in the same system, high-throughput sequencing is carried out after PCR amplification products are subjected to library building, and integrated detection of 55 SNP and 11 DNA methylation molecular markers of the same sample can be achieved at a time. By adopting the integrated detection system provided by the invention, the peripheral blood, vaginal secretion and seminal fluid of people can be identified, and the age of a peripheral blood sample donor can be deduced. According to the invention, a good technical basis is provided for obtaining diversified biological information of on-site detected materials in forensic medicine research and practice.

Description

Technical Field

[0001] The invention belongs to the field of forensic medicine and relates to a primer composition for integrated detection of SNP genetic markers and DNA methylation molecular markers and an application thereof. Background Art

[0002] Single nucleotide polymorphism (SNP) genetic markers, commonly used in the field of forensic science, are deoxyribonucleic acid (DNA) genetic markers. They play an important role in individual identification, kinship determination, ancestry inference, and phenotypic characterization in forensic science due to their low mutation rate, large number, ability to be detected by short fragments, and the rich genetic information they carry.

[0003] DNA methylation is an epigenetic regulatory mechanism whose function is independent of the primary structure of DNA. It has unique advantages in solving problems such as biological age inference, biological tissue property inference, and identical twin identification in the field of forensic science.

[0004] Existing technologies often test SNP genetic markers and DNA methylation molecular markers independently in different testing processes, resulting in time-consuming and labor-intensive operations, high sample consumption, and high experimental costs. Integrated testing technology can simultaneously obtain information on multiple biomarkers by performing a single test on a single sample, effectively simplifying experimental steps and reducing experimental costs and sample consumption. Next-generation sequencing (NGS) technology, with its high-throughput and integrated technical features, supports the integrated testing of a large number of genetic markers of various types in a single sample, providing a new approach to the integrated testing of SNP genetic markers and DNA methylation molecular markers. Summary of the Invention

[0005] The purpose of the present invention is to provide a primer combination for the integrated detection of SNP genetic markers and DNA methylation molecular markers and its application.

[0006] The primer composition provided by the present invention consists of 142 primers; the nucleotide sequences of the 142 primers are shown in SEQ ID NO: 1 to SEQ ID NO: 142 in sequence.

[0007] In the primer composition, the molar ratio of the primers in the order from the primer shown in SEQ ID NO: 1 to the primer shown in SEQ ID NO: 142 is: 0.3: 0.3: 0.15: 0.15: 0.3: 0.3: 0.15: 0.45: 0.45: 0.2: 0.2: 0.15: 0.15: 0.25: 0.25: 0.3: 0.3: 0.3: 0.3: 0.3: 0.3: 0.3: 0.3: 0.3: 0.3: 0.3: 0.3: 0.3: 0.3: 0.3: 0.45: 0 .45: 0.3: 0.3: 0.3: 0.3: 0.15: 0.15: 0.3: 0.3: 0.3: 0.3: 0.25: 0.25: 0.45: 0.45: 0.3: 0.3: 0.45: 0.45: 0.3: 0.3: 0.3: 0.3: 0.3: 0.3: 0.3: 0.3: 0.45: 0.45: 0.3: 0.3: 0.3: 0.3: 0.3: 0.2: 0.2: 0.25: 0.25: 0 .45: 0.45: 0.3: 0.3: 0.3: 0.3: 0.3: 0.3: 0.3: 0.3: 0.2: 0.2: 0.3: 0.3: 0.3: 0.3: 0.3: 0.3: 0.3: 0.3: 0.3: 0.3: 0.3: 0.3: 0.45: 0.45: 0.15: 0.15: 0.3: 0.3: 0.3: 0.3: 0.3: 0.3: 0.3: 0.3: 0.45: 0.45: 0.3: 0.3: 0. 3: 0.3: 0.45: 0.45: 0.5: 0.5: 0.25: 0.25: 0.35: 0.35: 1.5: 1.5: 1.5: 1.5: 1.5: 0.25: 0.25: 0.25: 0.3: 0.3: 0.3: 0.75: 0.75: 0.75: 0.45: 0.45: 0.45: 0.45: 0.45: 0.3: 0.3.

[0008] Primers are single-stranded DNA molecules.

[0009] The function of the primer composition is forensic identification or kinship identification.

[0010] The sample for forensic identification is a sample from a human.

[0011] The purpose of the forensic identification is to identify the individual and / or identify the sample type and / or identify the age of the individual.

[0012] The sample type refers to the sample being peripheral blood and / or semen and / or vaginal fluid.

[0013] The kinship identification refers to the kinship identification of people.

[0014] The primer combination was used to identify 55 human SNPs and 11 human methylation markers.

[0015] The present invention also protects the use of the primer combination in preparing a kit.

[0016] The function of the kit is forensic identification or kinship identification.

[0017] The sample for forensic identification is a sample from a human.

[0018] The purpose of the forensic identification is to identify the individual and / or identify the sample type and / or identify the age of the individual.

[0019] The sample type refers to the sample being peripheral blood and / or semen and / or vaginal fluid.

[0020] The kinship identification refers to the kinship identification of people.

[0021] The kit is used to identify 55 human SNPs and 11 human methylation markers.

[0022] The present invention also protects a kit comprising the primer composition.

[0023] The function of the kit is forensic identification or kinship identification.

[0024] The sample for forensic identification is a sample from a human.

[0025] The purpose of the forensic identification is to identify the individual and / or identify the sample type and / or identify the age of the individual.

[0026] The sample type refers to the sample being peripheral blood and / or semen and / or vaginal fluid.

[0027] The kinship identification refers to the kinship identification of people.

[0028] The kit is used to identify 55 human SNPs and 11 human methylation markers.

[0029] The kit also includes Component I, which is a reagent or reagent combination for converting methylated C in DNA into DHU. As an example, Component I is a Recombinant Ten-Eleven Translocase 2.0 kit.

[0030] The kit also includes Component II, which comprises a reagent or reagent combination for DNA library construction. As an example, Component II is the TruSeq DNA PCR-Free High Throughput Library Prep Kit. The TruSeq DNA PCR-Free High Throughput Library Prep Kit is available from Illumina, catalog number 20015963.

[0031] The kit also includes component III; component III comprises a reagent or reagent combination for DNA sequencing. As an example, component III comprises a MiSeq v2 kit (300 cycles). MiSeq v2 kit (300 cycles): Illumina, catalog number MS-102-2002.

[0032] The kit also includes component IV, which is a premix for multiplex PCR amplification. As an example, component IV is KAPA HiFi HotStart Uracil + ReadyMix. KAPA HiFi HotStart Uracil + ReadyMix is ​​available from KAPA Biosystems, catalog number KK2801.

[0033] The kit also includes component V, which is a reagent or reagent combination for DNA extraction. As an example, component V is a QIAamp DNA Investigator Kit. The QIAamp DNA Investigator Kit is available from Qiagen, catalog number 56504.

[0034] The kit also includes component VI, which is a reagent or reagent combination for purifying the amplified products of multiplex PCR amplification. As an example, component VI comprises magnetic beads. As an example, component VI comprises 0.8× magnetic beads. Magnetic beads (AMPure XP): Beckman, catalog number A63881.

[0035] The kit further includes component VII, which is a reagent or reagent combination for library quantification. As an example, component VII is the KAPA Library Quantification Kit. KAPA Library Quantification Kit: KAPA Biosystems, product catalog number KK4824.

[0036] The kit further comprises a carrier recording a multivariate linear regression model for age prediction;

[0037] The multivariate linear regression model for age prediction was: 43.634-56.117×methylation level of CpG1+73.395×methylation level of CpG2+32.036×methylation level of CpG3-2.782×methylation level of CpG4+106.139×methylation level of CpG5.

[0038] The present invention also provides a method for preparing the kit, comprising the steps of: mixing and packaging all primers in the primer combination. Specifically, all primers in the primer combination are mixed and packaged according to the above molar ratio.

[0039] The present invention also protects the use of the primer composition or the kit, which is as follows (a) or (b):

[0040] (a) Forensic medical examination;

[0041] (b) Kinship identification.

[0042] The sample for forensic identification is a sample from a human.

[0043] The purpose of the forensic identification is to identify the individual and / or identify the sample type and / or identify the age of the individual.

[0044] The sample type refers to the sample being peripheral blood and / or semen and / or vaginal fluid.

[0045] The kinship identification refers to the kinship identification of people.

[0046] The present invention also protects the use of the primer composition or the kit, which is as follows (c) and / or (d) and / or (e):

[0047] (c) individual identification;

[0048] (d) Identify the sample type;

[0049] (e) Identify the age of the individual.

[0050] The individual identification refers to the individual identification of a person.

[0051] The sample type refers to the sample being human peripheral blood and / or human semen and / or human vaginal secretions.

[0052] The individual age refers to the individual age of a person.

[0053] The present invention also protects the use of the primer composition or the kit for identifying 55 human SNPs and 11 human methylation markers.

[0054] The present invention also provides a method for identifying 55 SNPs and 11 methylation markers in a test sample derived from a human, comprising the following steps:

[0055] (1) Take the test sample, extract DNA, and then perform pretreatment to convert the methylated C in the DNA into DHU;

[0056] (2) using the product of step (1) as a template and employing the primer combination to perform multiplex PCR amplification;

[0057] (3) Purifying the amplified product of step (2) and then constructing the library;

[0058] (4) The library constructed in step (3) is subjected to high-throughput sequencing to output the original sequencing results, and the genetic information of the 55 SNPs and 11 methylation markers of the test sample is obtained based on the original sequencing results.

[0059] The present invention also provides a method for performing forensic identification on a test sample, comprising the following steps:

[0060] (1) Take the test sample, extract DNA, and then perform pretreatment to convert the methylated C in the DNA into DHU;

[0061] (2) using the product of step (1) as a template and employing the primer combination to perform multiplex PCR amplification;

[0062] (3) Purifying the amplified product of step (2) and then constructing the library;

[0063] (4) Performing high-throughput sequencing on the library constructed in step (3), outputting the original sequencing results, and performing data analysis on the original sequencing results.

[0064] Specifically, the DNA was extracted using a QIAamp DNA Investigator kit.

[0065] Specifically, any of the above pretreatment methods is: using the recombinant TET enzyme 2.0 kit and operating according to the instructions.

[0066] Specifically, any of the above pretreatment methods includes the following steps:

[0067] ① Take 1 μL 125×Fe 2+ Solution, add 124 μL of water to obtain 1×Fe 2+ Solution, vortex mix, centrifuge briefly, and place on ice in the dark until ready for use;

[0068] ② Prepare the oxidation reaction system in a PCR tube, then place the PCR tube on a PCR instrument, heat the cover at 60°C, and incubate at 37°C for 2 hours; oxidation reaction system (25 μL): 1.9 μL eTET2.0 Reaction Buffer, 6 μL eTET2.0 Enzymemix, 0.9 μL 1×Fe 2+ Solution, sample to be processed (for example, DNA content is 100 ng), add water to 25 μL;

[0069] ③After completing step ②, add 1 μL Termination Buffer and 1 μL Termination Enzyme to the PCR tube, then place the PCR tube in a PCR instrument with a heated lid at 60°C and incubate at 50°C for 30 minutes;

[0070] ④After completing step ③, add 9 μL Conversion Reagent and 2 μL Conversion Enhancer to the PCR tube, then place the PCR tube in a thermal cycler with a heated lid at 60°C and incubate at 37°C for 16 hours;

[0071] ⑤After completing step ④, add 34 μL of Neutralizer to the PCR tube and mix thoroughly by pipetting;

[0072] ⑥After completing step ⑤, purify the DNA to obtain a product solution.

[0073] As an example, the step ⑥ is: after completing step ⑤, purify the DNA using an Oligo Clean & Concentrator kit to obtain 15 μL of product solution.

[0074] Recombinant Ten-Eleven Translocase 2.0 Kit: Yisheng Company, catalog number 12212ES24. The components of the recombinant TET enzyme 2.0 kit are as follows: eTET2.0 Reaction Buffer (component number 12212-A), eTET2.0 Enzyme mix (component number 12212-B), 125×Fe 2+Solution (component number 12212-C), Termination Buffer (component number 12212-D), Termination Enzyme (component number 12212-E), Conversion Reagent (component number 12212-F), Conversion Enhancer (component number 12212-G), Neutralizer (component number 12212-H).

[0075] Specifically, the amplification reaction system (20 μL) for the multiplex PCR amplification was: 10 μL of KAPA HiFi HotStart Uracil + ReadyMix, a primer combination solution, the pretreated product solution (DNA content: 1 ng), and water added to 20 μL. The primer combination solution provided 142 primers (represented by SEQ ID NO: 1 to SEQ ID NO: 142, respectively).

[0076] In the amplification reaction system, the concentrations of the primers in the order from SEQ ID NO: 1 to SEQ ID NO: 142 are (all units are μM): 0.3: 0.3: 0.15: 0.15: 0.3: 0.3: 0.15: 0.15: 0.45: 0.45: 0.2: 0.2: 0.15: 0.15: 0.25: 0.25: 0.3 ... .45: 0.45: 0.3: 0.3: 0.3: 0.3: 0.15: 0.15: 0.3: 0.3: 0.3: 0.3: 0.25: 0.25: 0.45: 0.45: 0.3: 0.3: 0.45: 0.45: 0.3: 0.3: 0.3: 0.3: 0.3: 0.3: 0.3: 0.3: 0.45: 0.45: 0.3: 0.3: 0.3: 0.3: 0.3: 0.2: 0.2: 0.25: 0.2 5: 0.45: 0.45: 0.3: 0.3: 0.3: 0.3: 0.3: 0.3: 0.3: 0.3: 0.2: 0.2: 0.3: 0.3: 0.3: 0.3: 0.3: 0.3: 0.3: 0.3: 0.3: 0.3: 0.3: 0.45: 0.45: 0.15: 0.15: 0.3: 0.3: 0.3: 0.3: 0.3: 0.3: 0.3: 0.3: 0.45: 0.45: 0.3: 0.3: 0 .3:0.3:0.45:0.45:0.5:0.5:0.25:0.25:0.35:0.35:1.5:1.5:1.5:1.5:1.5:0.25:0.25:0.25:0.25:0.3:0.3:0.3:0.3:0.75:0.75:0.75:0.45:0.45:0.45:0.45:0.45:0.3:0.3.

[0077] Specifically, the amplification reaction program of the multiplex PCR amplification is: 98°C for 45s; 98°C for 15s, 60°C for 30s, 72°C

[0078] 30s, 28 cycles; 72℃ for 1min.

[0079] In step (3), the amplified product of step (2) is purified using magnetic beads. As an example, the magnetic beads are 0.8× magnetic beads.

[0080] In step (3), the library was constructed using the TruSeq DNA PCR-Free High Throughput Library Prep Kit, and then the library was quantified using the KAPA Library Quantification Kit, and then the library was normalized to obtain a library solution.

[0081] The high-throughput sequencing is second-generation sequencing.

[0082] In step (4), the MiSeq v2 kit (300 cycles) was used to perform the TM Sequencing was performed using the Forensic Genome Analysis System (Illumina).

[0083] The method for data analysis of raw sequencing results is as follows:

[0084] Get MiSeq FGx TM Paired-end FASTQ files generated by the Forensic Genomic Analysis System;

[0085] The sequencing depth of the target CpG site is analyzed using analysis software (such as MHTyper analysis software). If the sequencing depth of the target CpG position is greater than 50×, the marker is considered to be detected. The methylation level of the methylation site is equal to the sum of the number of reads with the bases TG and CA at the CpG position divided by the sum of the number of reads with the bases TG, CA, and CG at the CpG position respectively.

[0086] Use analysis software (e.g., SNPTyper analysis software) to obtain the sequencing depth and typing results of the target SNP; a SNP site is considered detected if its sequencing depth is greater than 100×; for unbalanced SNP sites, the minor allele is considered to be an allele if its sequencing depth is greater than 10% of the total sequencing depth;

[0087] Software (such as SPSS software) was used to perform statistical analysis on the average sequencing depth of the samples.

[0088] The 55 human SNPs are as follows: rs10914803, rs10888979, rs4847034, rs6687760, rs1413212, rs798443, rs918331, rs2053911, rs2033849, rs13019672, rs13034774, rs9809528, rs3430 9901, rs10034991, rs279844, rs4484354, rs1487052, rs1156358, rs158803, rs1005 7763, rs2235254, rs6933870, rs7767965, rs1358856, rs2503107, rs2272998, rs1177 9605, rs6473257, rs944662, rs826472, rs3780962, rs2435344, rs7911308, rs65911 47. rs1863370, rs7962675, rs2920816, rs2730648, rs6581429, rs7980449, rs959897 , rs7979370, rs11617748, rs1413577, rs430046, rs4796362, rs1493232, rs576261, rs4813947, rs12480506, rs6639398, rs7060326, rs5915052, rs4826248, rs6649211.

[0089] The 11 human methylation markers are as follows: CpG1, CpG2, CpG3, CpG4, CpG5, CpG6, CpG7, CpG8, CpG9, CpG10 and CpG11; the CpG1 is located at position 207823681 of chromosome 1 (chr1:207823681); the CpG2 is located at position 105399282 of chromosome 2 (chr2:105399282); the CpG3 is located at position 160450189 of chromosome 3 (chr3:160450189); the CpG4 is located at position 11044628 of chromosome 6 (chr6:11044628); the CpG5 is located at position 130734355 of chromosome 7 (chr The CpG6 is located at position 3344275 of chromosome 19 (chr19:3344275); the CpG7 is located at position 108562706 of chromosome 6 (chr6:108562706); the CpG8 is located at position 219514322 of chromosome 2 (chr2:219514322); the CpG9 is located at position 143943879 of chromosome 8 (chr8:143943879); the CpG10 is located at position 27251959 of chromosome 7 (chr7:27251959); and the CpG11 is located at position 53961752 of chromosome 12 (chr12:53961752).

[0090] The positions are those corresponding to the human reference genome hg38.

[0091] The position is the position of C in CpG.

[0092] CpG1, CpG2, CpG3, CpG4 and CpG5 are age-related markers.

[0093] CpG6 and CpG7 are specific markers for peripheral blood.

[0094] CpG8 and CpG9 are semen-specific markers.

[0095] CpG10 and CpG11 are specific markers for vaginal secretions.

[0096] The methylation levels of CpG1, CpG2, CpG3, CpG4 and CpG5 were used to predict age using a multiple linear regression model; the multiple linear regression model was: 43.634-56.117×CpG1 methylation level + 73.395×CpG2 methylation level + 32.036×CpG3 methylation level -2.782×CpG4 methylation level + 106.139×CpG5 methylation level.

[0097] The primer combination provided by the present invention performs multiplex PCR amplification in the same system, and performs high-throughput sequencing after the PCR amplification products are built into a library, which can realize the integrated detection of 55 SNPs and 11 DNA methylation molecular markers of the same sample at one time. The results have been verified: the SNP typing results of the sample in the integrated detection system are respectively consistent with the SNP typing results of the whole genome sequencing of the sample, and the SNP typing results of 2800M in the integrated detection system are consistent with its known SNP typing results; the methylation levels of methylation markers in human methylated DNA standards are greater than 0.8, and the methylation levels of methylation markers in human unmethylated DNA standards are less than 0.05. The primer combination provided by the present invention has individual recognition capabilities, the ability to distinguish peripheral blood, semen, and vaginal secretions, and the ability to infer age. The present invention simplifies the test procedure, effectively saves the amount of test samples, effectively saves test time, and effectively saves test costs. Using the integrated detection system of the present invention, the cumulative individual recognition ability of 50 autosomal SNPs reaches 1-2.18×10 -21 The 11 DNA methylation molecular markers can be used to identify human peripheral blood, vaginal secretions, and semen, as well as to infer the age of peripheral blood sample donors. This invention provides a good technical foundation for obtaining diversified biological information from on-site specimens in forensic research and practice. BRIEF DESCRIPTION OF THE DRAWINGS

[0098] Figure 1 Schematic diagram of target DNA molecules prepared using λDNA.

[0099] Figure 2 Schematic diagram of the detection principle of pretreatment effect.

[0100] Figure 3 This is a comparison of the effects of different pretreatment methods (the product solution prepared in step 3 is used as an exemplary result for the test sample).

[0101] Figure 4 This is a comparison of the effects of different pretreatment methods (the product solution prepared in step 4 is used as an exemplary result for the test sample).

[0102] Figure 5 This is a comparison of the effects of different pretreatment methods (the product solution prepared in step 5 is used as an exemplary result for the test sample).

[0103] Figure 6 is the methylation level of DNA methylation molecular markers in WMS and WNS.

[0104] Figure 7 The methylation differences of DNA methylation molecular markers in different body fluids (**P<0.01).

[0105] Figure 8 This is the linear correlation analysis between DNA methylation molecular markers and age.

[0106] Figure 9 is the correlation between actual age and predicted age. DETAILED DESCRIPTION

[0107] The present invention will be further described in detail below in conjunction with specific embodiments. The examples provided are only for illustrating the present invention and are not intended to limit the scope of the present invention. The examples provided below can serve as a guide for further improvements by those skilled in the art and are not intended to limit the present invention in any way.

[0108] Unless otherwise specified, the experimental methods in the following examples are conventional methods and were performed according to the techniques or conditions described in literature in the field or according to product specifications. Materials and reagents used in the following examples are commercially available unless otherwise specified. Quantitative assays in the following examples were performed in triplicate, and the results were averaged. The samples used in these experiments have been reviewed by the Scientific Research Ethics Review Committee of the Public Security Bureau's Identification Center (Approval No. 2023-001), and all subjects provided signed informed consent. Information on the human reference genome hg38 (GRCh38_reference_genome) is available at: https: / / www.ncbi.nlm.nih.gov / datasets / genome / GCF_000001405.26 / . Primers are all single-stranded DNA molecules. Unless otherwise specified, primer orientation is 5'→3'. Physical locations in this disclosure refer to genomic coordinates based on the human reference genome hg38. Water in the examples is nuclease-free, unless otherwise specified. DHU: dihydrouracil.

[0109] 2800M is a commercially available control DNA (single-source male human genomic DNA), from Promega, Catalog No. DD7101. λDNA (restriction enzyme digestion substrate): Takara, Catalog No. 3010. HpaII methyltransferase: New England Biolabs, Catalog No. M0214S. HpaII restriction endonuclease: New England Biolabs, Catalog No. R0171V. Agilent DNA 1000 Kit: Agilent, Catalog No. 5067-1504. Oligo Clean & Concentrator Kits: Zymo Research, Catalog No. D4060. Recombinant human Tet2 protein solution (1.14 mg / ml): Abcam, Catalog No. ab271754. Proteinase K solution (concentration 20 mg / mL): QIAGEN, product number 19133. Pyridine borane complex solution (concentration 10 M) (brand: AlfaAesar TM ) from ThermoFisher, Cat. No. L13178. Magnetic beads (AMPure XP): Beckman, Cat. No. A63881. QIAamp DNA Investigator Kit: Qiagen, Cat. No. 56504. Double-stranded DNA Rapid Quantification Kit (dsDNA Rapid Quantification Kit): Sangon Biotechnology, Cat. No. N608301.

[0110] Example 1: Screening and Detecting the Optimal Pretreatment Method for DNA Methylation Molecular Markers

[0111] 1. Preparation of negative and positive control samples

[0112] Using λDNA as a template, PCR amplification was performed using a primer pair consisting of primers F0 and R0 (primer F0: GAATGATTTCCAGTTGCTAC; primer R0: TGCTAACCAATTCCTAGGCAGG) to prepare a target DNA molecule (the target DNA molecule is the negative control sample). The target DNA molecule is a double-stranded DNA molecule, and the sequence is shown in Figure 1 . Figure 1 In the figure, CCGG in the red box is the target sequence of HpaⅡ methyltransferase 5'-CCGG-3', 5'-C C The underlined C in GG-3' is the target site.

[0113] Take the target DNA molecule and treat it with HpaⅡ methyltransferase (according to the instructions) so that all Cs at the target sites in the target DNA molecule are converted into 5mC, which is the positive control sample.

[0114] PCR amplification was performed on negative and positive control samples using primer pairs consisting of primers F0 and R0. The samples were then digested with the HpaII restriction endonuclease (according to the manufacturer's instructions). The digestion products were analyzed on an Agilent 2100 bioanalyzer using the Agilent DNA 1000 kit (according to the manufacturer's instructions). The results showed that all negative control samples were digested (none were not digested), indicating that the target sites in all negative control samples were C. All positive control samples were not digested (none were digested), indicating that the target sites in all positive control samples were 5mC.

[0115] 2. Preparation of Reagents

[0116] 1. Preparation of TET2 Buffer 1

[0117] 1M HEPES solution: Dissolve 1.1915g HEPES in 3.5mL of water, adjust the pH to 7.0 with 1M NaOH, and then add water to 5mL. TET2 Buffer 1 (29.5mL): Dissolve 4926.5μL of 1M HEPES solution, 194.7μL of 0.5M α-ketoglutaric acid solution, 787.06μL of 0.25M ascorbic acid solution, 1180μL of 0.1M ATP solution, 1964.7μL of 5M NaCl solution, and 122.87μL of 2M DTT solution, mix, and add water to 29.5mL. Aliquot TET2 Buffer 1 into 200μL / tubes and store at -80°C in the dark.

[0118] 2. Fe 2+ Preparation of solution 1

[0119] Take 44.1mg Fe(NH4)2·(SO4)2·6H2O and dissolve it in 1mL water. Make it up to 3mL with water to prepare the storage solution. Store it at 4℃ in the dark. Before use, dilute the storage solution to 24 times the volume with water to prepare Fe 2+ solution1.

[0120] 3. Preparation of sodium acetate solution (pH 4.3)

[0121] Take 4M acetic acid aqueous solution and titrate it with 5M NaOH aqueous solution to pH 4.3 to obtain sodium acetate solution (pH 4.3). Store at 4°C.

[0122] 3. Pretreatment using method 1

[0123] The samples to be processed are the negative control sample and the positive control sample prepared in step 1.

[0124] 1. Prepare the oxidation reaction system in a PCR tube, incubate at 30°C for 80 min, then add 1 μL of proteinase K solution to the PCR tube and incubate at 50°C for 1 h.

[0125] Oxidation reaction system (50 μL): 15 μL TET2 Buffer 1, 3.3 μL Fe 2+ Solution 1, 4 μL recombinant human TET2 protein solution, sample to be processed (DNA content 100 ng), add water to 50 μL.

[0126] 2. After completing step 1, purify with 1.8× magnetic beads and then elute with 20 μL of nuclease-free water to obtain the product solution.

[0127] 3. Prepare the oxidation reaction system in a PCR tube, incubate at 30°C for 80 min, then add 1 μL of proteinase K solution to the PCR tube and incubate at 50°C for 1 h.

[0128] Oxidation reaction system (50 μL): 15 μL TET2 Buffer 1, 3.3 μL Fe 2+ Solution 1, 4 μL recombinant human TET2 protein solution, 20 μL product solution obtained in step 2, add water to 50 μL.

[0129] 4. After completing step 3, purify with 1.8× magnetic beads and then elute with 35 μL of nuclease-free water to obtain the product solution.

[0130] 5. Prepare the reduction reaction system in a PCR tube and react at 37°C and 850 rpm for 16 hours.

[0131] Reduction reaction system (50 μL): 5 μL pyridine borane complex solution, 10 μL sodium acetate solution (pH 4.3), 35 μL product solution obtained in step 4.

[0132] 6. After completing step 5, use the Oligo Clean & Concentrator kit to purify the DNA (follow the instructions) to obtain 15 μL of product solution.

[0133] 4. Preprocessing using Method 2

[0134] TET2 kit: Ibotek, catalog number RK20557. The TET2 kit provides the following components: TET2 (component catalog number RM20540), TET2 Reaction Buffer (component catalog number RM20815), TET2 Reaction Enhancer (component catalog number RM20816), 100 mM DTT (component catalog number RM20117), and Fe(II) Solution (component catalog number RM20817).

[0135] The samples to be processed are the negative control sample and the positive control sample prepared in step 1.

[0136] 1. Take 300 μL of TET2 Reaction Buffer and add it to TET2 Reaction Enhancer to obtain TET2 Buffer. Mix thoroughly to dissolve, centrifuge briefly, and place on ice for later use.

[0137] 2. Take 1 μL of Fe(II)Solution and add it to 1249 μL of water to obtain Fe(II)Solution dilution. Vortex mix and centrifuge briefly. Protect from light and place on ice until ready for use.

[0138] 3. Prepare the oxidation reaction system in a PCR tube, then place the PCR tube on a PCR instrument with a heated lid at 50°C and incubate at 37°C for 1 hour. Then add 1 μL of proteinase K solution to the PCR tube and incubate at 50°C for 1 hour.

[0139] Oxidation reaction system (50 μL): 10 μL TET2 Buffer, 1 μL 100 mM DTT, 4 μL TET2, 5 μL Fe(II)Solution diluent, sample to be processed (DNA content 100 ng), add water to 50 μL.

[0140] 4. After completing step 3, purify with 1.8× magnetic beads and then elute with 35 μL of nuclease-free water to obtain the product solution.

[0141] 5. Same as step 5 in step 3.

[0142] 6. Same as step 6 in step 3.

[0143] 5. Use method 3 for pretreatment

[0144] Recombinant Ten-Eleven Translocase 2.0 Kit: Yisheng Company, catalog number 12212ES24. The components of the recombinant TET enzyme 2.0 kit are as follows: eTET2.0 Reaction Buffer (component number 12212-A), eTET2.0 Enzyme mix (component number 12212-B), 125×Fe 2+ Solution (component number 12212-C), Termination Buffer (component number 12212-D), Termination Enzyme (component number 12212-E), Conversion Reagent (component number 12212-F), Conversion Enhancer (component number 12212-G), Neutralizer (component number 12212-H).

[0145] The samples to be processed are the negative control sample and the positive control sample prepared in step 1.

[0146] 1. Take 1 μL 125×Fe 2+ Solution, add 124 μL of water to obtain 1×Fe 2+ Solution, vortex mix, centrifuge briefly, and place on ice in the dark until ready for use.

[0147] 2. Prepare the oxidation reaction system in a PCR tube, then place the PCR tube on a PCR instrument, set the heated lid to 60°C, and incubate at 37°C for 2 hours.

[0148] Oxidation reaction system (25 μL): 1.9 μL eTET2.0 Reaction Buffer, 6 μL eTET2.0 Enzymemix, 0.9 μL 1×Fe 2+ Solution: Sample to be processed (DNA content 100 ng), add water to 25 μL.

[0149] 3. After completing step 2, add 1 μL Termination Buffer and 1 μL Termination Enzyme to the PCR tube, then place the PCR tube in a PCR instrument with a heated lid at 60°C and incubate at 50°C for 30 min.

[0150] 4. After completing step 3, add 9 μL Conversion Reagent and 2 μL Conversion Enhancer to the PCR tube, then place the PCR tube in a thermal cycler with a heated lid at 60°C and incubate at 37°C for 16 h.

[0151] 5. After completing step 4, add 34 μL Neutralizer to the PCR tube and mix thoroughly by pipetting.

[0152] 6. After completing step 5, use the Oligo Clean & Concentrator kit to purify the DNA (follow the instructions) to obtain 15 μL of product solution.

[0153] 6. Comparison of the effects of different pretreatment methods

[0154] The test samples were: the product solution prepared in step three of the negative control sample, the product solution prepared in step three of the positive control sample, the product solution prepared in step four of the negative control sample, the product solution prepared in step four of the positive control sample, the product solution prepared in step five of the negative control sample, and the product solution prepared in step five of the positive control sample.

[0155] The test sample was amplified by PCR using the primer pair consisting of primers F0 and R0, followed by digestion with HpaII restriction endonuclease (following the manufacturer's instructions). The digestion product was analyzed on a 2100 bioanalyzer using an Agilent DNA 1000 kit (following the manufacturer's instructions).

[0156] See the schematic diagram of the detection principle Figure 2 .

[0157] The product solution prepared in step 3 is used as an exemplary test sample. Figure 3 The product solution prepared in step 4 is used as the sample for the exemplary results. Figure 4 The product solution prepared in step 5 is used as the sample for the exemplary results. Figure 5 . Figures 3 to 5Middle: Panel a corresponds to the negative control sample, and panel b corresponds to the positive control sample; 15 corresponds to the 15-nucleotide internal standard, and 1500 corresponds to the 1500-nucleotide internal standard; arrows indicate the target peaks. When the product solution prepared in step 3 of the negative control sample, the product solution prepared in step 4 of the negative control sample, and the product solution prepared in step 5 of the negative control sample were used as test samples, two fragment peaks were displayed (consistent with the expected sizes of the two fragments after enzyme digestion). When the product solution prepared in step 3 of the positive control sample was used as a test sample, two fragment peaks were displayed (consistent with the expected sizes of the two fragments after enzyme digestion), indicating that the pretreatment using method 1 did not effectively achieve the conversion of 5mC to T. When the product solution prepared in step 4 of the positive control sample was used as a test sample, two fragment peaks were displayed (consistent with the expected sizes of the two fragments after enzyme digestion), indicating that the pretreatment using method 2 did not effectively achieve the conversion of 5mC to T. When the product solution prepared in step 5 of the positive control sample was used as a test sample, one fragment peak was shown (consistent with the expected size of the fragment that had not been cleaved by enzymes), indicating that the pretreatment using method 3 can effectively achieve the conversion of 5mC to T.

[0158] Example 2: Screening and integration of genetic markers and optimization of integrated detection systems

[0159] SNPs used in forensic science primarily include individual identification SNPs, pedigree information SNPs, ancestry information SNPs, and phenotypic information SNPs. Currently, individual identification remains a primary challenge in forensic medicine, but due to the low polymorphism of SNPs, a small number of SNPs cannot meet the needs of individual identification. DNA methylation molecular markers have important applications in disease prediction, body fluid identification, age estimation, identification of identical twins, identification of fabricated DNA evidence, and lifestyle prediction. In this study, age-related and body fluid-specific DNA methylation molecular markers were selected as candidates for an integrated detection system. It is noteworthy that base methylation does not alter the primary structure of DNA. However, methylated Cs are converted to DHUs after pretreatment and subsequently recognized as Ts during PCR amplification. This conversion converts base methylation differences within the DNA sequence into sequence-level differences, potentially affecting the accurate typing of SNP genetic markers in integrated testing. Therefore, when selecting sites, it is important to exclude SNP loci that may form CpGs with adjacent bases to ensure accurate typing of the screening markers in subsequent testing results.

[0160] The test samples involved in this example are: 5 peripheral blood samples, collected from 5 healthy individuals (aged 21, 39, 61, 83, and 72, respectively, and named PB1, PB2, PB3, PB4, and PB5); 2 semen samples (named SE1 and SE2), collected from 2 healthy male individuals; 1 saliva sample (named SA1), collected from 1 healthy individual; 2 vaginal fluid samples (named VF1 and VF2), collected from 2 healthy women (premenstrual period) using clean cotton swabs; and 1 menstrual blood sample (named MB1), collected from 2 days before menstruation using clean sanitary napkins from a healthy woman. SA1, VF1, and PB1 were obtained from the same individual.

[0161] 1. Screening Markers

[0162] We screened 448 SNPs previously identified by our research team according to the following criteria: ① Excluding SNPs whose alleles contained a C and whose subsequent base was a G in the dbSNP database; ② Excluding SNPs whose alleles contained a G and whose preceding base was a C in the dbSNP database; ③ Excluding SNPs with a minor allele frequency (MAF) ≤ 0.2; and ④ Excluding SNPs whose primer sequences contained a CpG. This screening resulted in 55 SNP markers (50 autosomal SNPs and 5 X-chromosome SNPs). Information on these 55 SNP markers is shown in Table 1.

[0163] Table 1

[0164] SNP chromosome physical location Polymorphic Types MAF value SNP chromosome physical location Polymorphic Types MAF value rs10914803 chr1 33888047 A / G 0.4036 rs944662 chr9 75232377 C / G / A 0.4511 rs10888979 chr1 56545039 A / T 0.3689 rs826472 chr10 2364437 A / C / T 0.2183 rs4847034 chr1 105175009 A / G / T 0.4792 rs3780962 chr10 17151347 A / G 0.4539 rs6687760 chr1 116971712 A / G 0.4182 rs2435344 chr10 43090426 C / T 0.4500 rs1413212 chr1 242643495 A / C / T 0.4574 rs7911308 chr10 122786140 A / C 0.3688 rs798443 chr2 7828144 A / G / T 0.4016 rs6591147 chr11 106042257 A / C / T 0.4155 rs918331 chr2 56758052 C / T 0.3156 rs1863370 chr11 128172128 G / A 0.3913 rs2053911 chr2 118786793 A / G 0.3741 rs7962675 chr12 23980549 A / G 0.4559 rs2033849 chr2 153170480 G / A 0.4397 rs2920816 chr12 40469250 A / G 0.3370 rs13019672 chr2 191657187 A / G 0.3415 rs2730648 chr12 51143413 C / T 0.3865 rs13034774 chr2 229053092 A / C 0.4928 rs6581429 chr12 61763114 A / C 0.4835 rs9809528 chr3 209075 A / C / G 0.4711 rs7980449 chr12 69179039 A / T 0.3897 rs34309901 chr3 94002939 C / T 0.4362 rs959897 chr12 92426976 T / C 0.3782 rs10034991 chr4 21003628 C / T 0.4824 rs7979370 chr12 101974612 G / T 0.4539 rs279844 chr4 46327638 A / T 0.4854 rs11617748 chr13 30648733 G / T 0.4894 rs4484354 chr4 65664064 A / T 0.4823 rs1413577 chr13 66415752 A / T 0.4926 rs1487052 chr4 111199584 C / T 0.3085 rs430046 chr16 77983154 C / G / T 0.3440 rs1156358 chr5 26907764 A / G 0.4496 rs4796362 chr17 6908210 A / G / T 0.4352 rs158803 chr5 36911514 A / G / T 0.4638 rs1493232 chr18 1127985 A / C 0.3705 rs10057763 chr5 56149217 G / T 0.2016 rs576261 chr19 39069167 A / C 0.4071 rs2235254 chr6 27455015 A / G 0.4220 rs4813947 chr20 10879475 A / G 0.2597 rs6933870 chr6 53533172 C / G 0.4504 rs12480506 chr20 16260771 A / G 0.3556 rs7767965 chr6 86187358 A / G 0.4256 rs6639398 chrX 5223258 A / G 0.4125 rs1358856 chr6 123573833 A / C 0.4301 rs7060326 chrX 42739000 C / T 0.4906 rs2503107 chr6 127142231 A / C 0.4366 rs5915052 chrX 57488707 A / G / T 0.2913 rs2272998 chr6 148440320 C / G / T 0.3732 rs4826248 chrX 78116778 C / T 0.2642 rs11779605 chr8 73304933 C / T 0.3451 rs6649211 chrX 121340866 A / C 0.4875 rs6473257 chr8 80979127 A / C 0.4113

[0165] Existing DNA methylation markers were screened based on the following criteria: ① age-related or body fluid-specific; ② a well-established age-inference model for age-related methylation marker combinations; and ③ body fluid-specific methylation sites exhibiting hypermethylation in peripheral blood, saliva, semen, vaginal fluid, and menstrual blood. Nine body fluid-specific DNA methylation markers and five age-related DNA methylation markers were identified. Information on these DNA methylation markers is provided in Table 2.

[0166] Table 2

[0167]

[0168] 2. Design primers and verify specificity

[0169] Primer pairs were designed to detect individual SNP genetic markers and DNA methylation markers. (The two menstrual blood-specific DNA methylation markers, CpG12 and CpG13, were located on the same amplicon because their physical locations differ by only 22 bp.) Using hg38 as the reference genome, the minimum Tm required between the primers' expected binding sites was 50°C. Base mismatches were not permitted at the 3' end of the primers, and the amplification product length ranged from 100 to 400 bp. The specificity of each primer pair was verified by agarose gel electrophoresis using 2800 M as the template.

[0170] 3. Design an integrated testing system and optimize it through performance verification

[0171] Eight test samples were set up, namely: PB1, PB2, PB3, PB4, SE1, VF1, SA1, and MB1.

[0172] The total DNA of the test sample was used as the sample to be processed and pretreated according to the method of step 5 of Example 1 to obtain a product solution. The product solution obtained by pretreatment was used as the template solution, and a primer combination (the primer combination was composed of the primer pairs obtained in step 2) was used for multiple PCR amplification, and then purified using 0.8× magnetic beads to obtain a purified product solution (20 μL). The purified product solution was taken for library construction and high-throughput sequencing. The original sequencing results were obtained and data analysis was performed.

[0173] SNPTyper software was used to obtain sequencing depth and typing results for 55 SNP genetic markers. The average sequencing depth for the eight samples was 8180±9891×. The sequencing depths for rs6687760, rs1487052, rs9809528, and rs2235254 were all below 100× in all eight samples, with average sequencing depths of 24±13×, 29±12×, 60±30×, and 30±9×, respectively. The sequencing depths for rs10034991 in SA1, PB1, and PB2 were 44×, 38×, and 99×, respectively, with an average sequencing depth of 127±63× in all eight samples. The sequencing depth for rs1863370 in PB1 was 48×, with an average sequencing depth of 216±99× in all eight samples. The sequencing depths for rs1358856 were 49× and 64× in SA1 and PB1, respectively, with an average sequencing depth of 347±214× across the eight samples. The sequencing depths for rs1413212 were 68× and 75× in SA1 and PB1, respectively, with an average sequencing depth of 187±78× across the eight samples. No SNPs were identified for rs6687760 in PB1, but all 55 SNPs were identified in the remaining samples. The SNP typing results for SA1, VF1, and PB1 were consistent.

[0174] MHTyper software was used to determine the sequencing depth of 14 DNA methylation markers and calculate their methylation levels. The average sequencing depth for the eight samples was 10,939 ± 10,589 ×, with all sites exceeding 100 ×. CpG4 had the lowest average sequencing depth (1,310 ± 2,065 ×), while CpG14 had the highest average depth (30,898 ± 10,722 ×). Methylation levels at CpG1 decreased with age, while those at CpG2, CpG3, CpG4, and CpG5 increased. Methylation levels at the peripheral blood-specific methylation markers CpG6 and CpG7 were significantly higher in the four peripheral blood samples than at the other seven body fluid-specific methylation sites. Methylation levels at the semen-specific methylation markers CpG8 and CpG9 were significantly higher in semen than at the other seven body fluid-specific methylation sites. The methylation levels of vaginal fluid-specific methylation markers CpG10 and CpG11 were significantly higher in vaginal fluid samples than those of the other seven body fluid-specific methylation sites. The methylation levels of menstrual blood-specific methylation markers CpG12 and CpG13 were lower than those of CpG6, CpG7, and CpG11, but higher than those of the other four body fluid-specific methylation sites. The methylation level of the saliva-specific methylation marker CpG14 in saliva samples, like the methylation levels of the other eight body fluid-specific methylation sites, was below 0.05, indicating almost no methylation.

[0175] Based on the data analysis results, the integrated detection system was optimized according to the following principles: if the methylation level of the DNA methylation molecular marker in the corresponding body fluid is lower than or equal to the methylation level of other body fluid-specific methylation molecular markers, the body fluid-specific methylation molecular marker is deleted; if the trend of DNA methylation molecular marker changes with age is inconsistent with the reference literature, the age-related methylation marker is deleted; if the SNP genetic marker has no typing results or the sequencing depth is less than 100×, the concentration of the SNP genetic marker in the DNA primer mixture is increased. Optimization results: CpG12 and CpG13, whose DNA methylation levels in menstrual blood samples showed no significant difference from those in other body fluid-specific methylation markers, were deleted; CpG14, whose DNA methylation levels in saliva samples showed no significant difference from those in other body fluid-specific methylation markers, was deleted; the concentrations of eight SNP genetic markers, rs6687760, rs1487052, rs9809528, rs2235254, rs10034991, rs1863370, rs1358856, and rs1413212, which were not detected in eight samples and had a sequencing depth of less than 100×, in the multiplex amplification system were increased.

[0176] 4. Verification of the effectiveness of the optimized integrated detection system

[0177] Three test samples were set up, namely: PB5, SE2 and VF2.

[0178] 1. Take the test sample and extract DNA using the QIAamp DNA Investigator kit (follow the instructions) to obtain a DNA solution.

[0179] 2. Take the DNA solution obtained in step 1 and quantify it using the double-stranded DNA rapid quantification kit (follow the instructions) and the Qubit3.0 fluorometer.

[0180] 3. Take the DNA solution obtained in step 1 as the sample to be processed, and pre-treat it according to the method of step 5 of Example 1 to obtain a product solution.

[0181] 4. Perform multiplex PCR amplification to obtain amplified products.

[0182] Amplification reaction system (20 μL): 10 μL of KAPA HiFi HotStart Uracil + ReadyMix, primer combination solution, the product solution from step 3 (DNA content 1 ng), and water to 20 μL. KAPA HiFi HotStart Uracil + ReadyMix: KAPA Biosystems, catalog number KK2801.

[0183] The active ingredients provided by the primer composition solution are 142 primers (the 142 primers are shown in SEQ ID NO: 1 to SEQ ID NO: 142; see Tables 3 and 4). The concentrations of the primers in the amplification reaction system are shown in Tables 3 and 4 (working concentration refers to the concentration in the amplification reaction system).

[0184] Amplification reaction program: 98°C for 45 s; 98°C for 15 s, 60°C for 30 s, 72°C for 30 s, 28 cycles; 72°C for 1 min.

[0185] Table 3

[0186]

[0187]

[0188]

[0189] Table 4

[0190]

[0191]

[0192] 5. Take the amplified product obtained in step 4 and use 0.8× magnetic beads to purify the DNA to obtain the purified product of the amplified product.

[0193] 6. Library Construction

[0194] Take the purified product obtained in step 5 and use the TruSeq DNA PCR-Free High Throughput LibraryPrep Kit according to the instructions (the library preparation process includes: end repair, end repair product purification, A-tail ligation, Adapter ligation, and purification of the ligation product). Then, use the KAPA Library Quantification Kit to quantify the library and perform library normalization to obtain a library solution.

[0195] TruSeq DNA PCR-Free High Throughput Library Prep Kit: Illumina, product catalog number: 20015963. KAPA Library Quantification Kit: KAPA Biosystems, product catalog number: KK4824.

[0196] 7. High-throughput sequencing

[0197] Take the library solution prepared in step 6 and use the MiSeq v2 kit (300 cycles) on the MiSeq FGx TM Sequencing was performed using the Forensic Genome Analysis System (Illumina).

[0198] MiSeq v2 kit (300 cycles): Illumina, product catalog number MS-102-2002.

[0199] 8. Data Analysis

[0200] (1) Obtaining MiSeq FGx TM Paired-end FASTQ files generated by the Forensic Genomic Analysis System;

[0201] (2) The sequencing depth of the target CpG site was analyzed using MHTyper analysis software (https: / / github.com / wangle-ifs / MHTyper.git). If the sequencing depth of the target CpG position was greater than 50×, the marker was considered detected. The methylation level of the methylation site was equal to the sum of the number of reads with the bases TG and CA at the CpG position divided by the sum of the number of reads with the bases TG, CA, and CG at the CpG position, that is, (TG+CA) / (TG+CA+CG);

[0202] (3) Use SNPTyper analysis software (https: / / github.com / wangle-ifs / SNPTyper.git) to obtain the sequencing depth and typing results of the target SNP. If the sequencing depth of the SNP site is greater than 100×, the site is considered to be detected. For unbalanced SNP sites, the minor allele can be identified as an allele if the sequencing depth is greater than 10% of the total sequencing depth;

[0203] (4) SPSS software (v25) was used to perform statistical analysis on the average sequencing depth of the samples.

[0204] 9. Results

[0205] The average sequencing depth for all markers was greater than 1000×. The sequencing depth for SNPs in all three samples was greater than 100×, and the sequencing depth for DNA methylation markers was greater than 50×. The methylation levels of body fluid-specific methylation markers in their corresponding body fluids were significantly higher than those of other body fluid-specific methylation sites.

[0206] Example 3: Detecting samples using the optimized integrated detection system

[0207] The test samples involved in this embodiment are as follows:

[0208] The four peripheral blood samples (PB1, PB2, PB3, and PB4) in Example 2; 12 new peripheral blood samples (named PB6 to PB17), which were peripheral venous blood collected from 12 healthy individuals using EDTA anticoagulant tubes; 4 semen samples (named SE3 to SE6), which were fresh semen collected from 4 healthy male individuals; 4 vaginal secretion samples (named VF3 to VF6), which were vaginal secretions collected from 4 healthy women who were not in their menstrual period using clean cotton swabs; 1 oral sample (named BC1), which was oral epithelial cells collected from 1 healthy individual using a clean cotton swab;

[0209] WNS sample (Human WGA Non-Methylated DNA): Zymo Research, catalog number D5013-

[0210] 1. WMS sample (Human WGA Methylated DNA): Zymo Research, catalog number D5013-2.

[0211] 2800M.

[0212] Take each test sample and perform the operation according to steps 1 to 8 of step 4 of Example 2.

[0213] Example 4: Verification of the Detection Accuracy of SNP Genetic Markers

[0214] Obtain the result data for 2800M, PB6, and BC1 in Example 3. 2800M, PB6, and BC1 were all from male individuals. The sequencing depth for all SNP genetic markers in the three samples was greater than 100×, and the sequencing depth for DNA methylation molecular markers was greater than 50×.

[0215] Compare the consistency of the SNP typing results in the 2800M data with the SNP typing data in the 2800M provided by the standard "GB / T 44322-2024 Basic Quality Requirements for Forensic Science Next-Generation Sequencing Reagents." Compare the consistency of the SNP typing results in the PB6 and BC1 data with the corresponding SNP typing results in their respective whole-genome sequencing data.

[0216] The results are shown in Table 5. There are no reference typing results for rs2053911, rs1358856, and rs5915052 in the standard "GB / T 44322-2024 Basic Quality Requirements for Forensic Science Next-Generation Sequencing Reagents." The typing results for the remaining 52 SNP genetic markers were consistent with the typing results for the 2800M SNP genetic markers in the integrated test. The typing results for the 55 SNP genetic markers for PB6 and BC1 in the integrated test and whole-genome sequencing were consistent. The 55 SNP genetic markers were derived from 448 SNP loci previously screened by this research team based on the Han population in northern China. The average DP value of the 50 SNP genetic markers was calculated to be 0.6121, and the cumulative individual identification ability was 1-2.18×10 -21 .

[0217] Table 5

[0218]

[0219]

[0220]

[0221] Example 5: Verification of the Detection Accuracy of DNA Methylation Molecular Markers

[0222] Obtain the result data of the WMS sample and the result data of the WNS sample in Example 3.

[0223] In both WMS and WNS, the sequencing depth of SNP genetic markers was greater than 100×, and the sequencing depth of DNA methylation molecular markers was greater than 50×. Figure 6 As shown, the methylation levels of the 11 DNA methylation molecular markers in WMS were all greater than 0.8, with an average of 0.95, and the methylation levels in WNS were all less than 0.05, with an average of 0.01.

[0224] Example 6: Verification of the ability of DNA methylation molecular markers to identify body fluids

[0225] Obtain the result data for the five peripheral blood samples (PB7 to PB11) in Example 3, for a total of five peripheral blood sample result data. Obtain the result data for the SE2 sample in step 4 of Example 2 and the result data for the four semen samples (SE3 to SE6) in Example 3, for a total of five semen sample result data. Obtain the result data for the VF2 sample in step 4 of Example 2 and the result data for the four vaginal fluid samples (VF3 to VF6) in Example 3, for a total of five vaginal fluid result data.

[0226] The sequencing depth of SNP genetic markers in 15 samples was greater than 100×, and the sequencing depth of DNA methylation molecular markers was greater than 50×. Figure 7 As shown, in peripheral blood samples, the methylation levels of peripheral blood-specific methylation markers were statistically significantly different from those of other body fluid-specific methylation sites; in semen samples, the methylation levels of semen-specific methylation markers were statistically significantly different from those of other body fluid-specific methylation sites; and in vaginal fluid samples, the methylation levels of vaginal fluid-specific methylation markers were statistically significantly different from those of other body fluid-specific methylation sites. All three body fluid-specific methylation markers showed significant hypermethylation in their corresponding body fluids.

[0227] Table 6

[0228]

[0229] Example 7: Results of DNA methylation molecular marker age inference capability verification

[0230] Obtain the result data of the PB5 sample in step 4 of Example 2, the result data of the four peripheral blood samples (PB1, PB2, PB3, PB4) in Example 3, and the result data of the 12 peripheral blood samples (PB6 to PB17) in Example 3, for a total of 17 peripheral blood samples.

[0231] The age distribution of the providers of the 17 peripheral blood samples is shown in Table 7 .

[0232] Table 7

[0233]

[0234] The sequencing depth of SNP genetic markers in all samples was greater than 100×, and the sequencing depth of DNA methylation molecular markers was greater than 50×. Figure 8 As shown in Figures and , the methylation levels of the five age-related DNA methylation markers were all correlated with age. The methylation level of CpG1 was negatively correlated with age, while that of CpG2, CpG3, CpG4, and CpG5 was positively correlated with age. The methylation levels of CpG1, CpG2, and CpG5 were highly correlated with age, and the methylation levels of CpG3 and CpG4 were strongly correlated with age. Based on the actual age and methylation levels of 17 peripheral blood samples, a multivariate linear regression model for age prediction using the five age-related DNA methylation markers was constructed: 43.634-56.117×CpG1+73.395×CpG2+32.036×CpG3-2.782×CpG4+106.139×CpG5. The model was cross-validated 10 times using 17 samples. The average absolute error between the actual age and the predicted age was 3.99 years, and the root mean square error was 4.49 years. The correlation between the predicted age and the actual age is shown in Figure 2. Figure 9 As shown, the correlation coefficient is 0.986 (R 2 =0.972, P<0.01).

[0235] Table 8

[0236] DNA methylation molecular markers Correlation coefficient <![CDATA[R 2 ]]> P-value CpG1 -0.924 0.854 <0.01 CpG2 0.922 0.850 <0.01 CpG3 0.653 0.426 <0.01 CpG4 0.669 0.448 <0.01 CpG5 0.825 0.763 <0.01

[0237] The meanings of the degenerate bases involved in the primers in Tables 3 and 4 are shown in Table 9.

[0238] Table 9

[0239]

[0240]

[0241] The present invention has been described in detail above. It will be apparent to those skilled in the art that the present invention may be practiced over a wide range of parameters, concentrations, and conditions without departing from the spirit and scope of the present invention and without unnecessary experimentation. Although specific embodiments have been given herein, it should be understood that further modifications may be made to the present invention. In summary, this application is intended to encompass any variations, uses, or improvements to the present invention, including those made by conventional techniques known in the art that depart from the scope of the present invention. Applications of the essential features may be made within the scope of the following claims.

Claims

1. A primer composition, comprising 142 primers; the nucleotide sequences of the 142 primers are shown in SEQ ID NO: 1 to SEQ ID NO: 142, respectively.

2. Use of the primer combination according to claim 1 in preparing a kit.

3. A kit comprising the primer composition according to claim 1.

4. The method for preparing the kit according to claim 3, comprising the steps of: mixing and packaging all primers in the primer combination.

5. Use of the primer composition according to claim 1 or the kit according to claim 3, wherein: (a) Forensic medical examination; (b) Kinship identification.

6. Use of the primer composition according to claim 1 or the kit according to claim 3, wherein: (c) individual identification; (d) Identify the sample type; (e) Identify the age of the individual.

7. Use of the primer combination of claim 1 or the kit of claim 3 for identifying 55 human SNPs and 11 human methylation markers; The 55 human SNPs are as follows: rs10914803, rs10888979, rs4847034, rs6687760, rs1413212, rs798443, rs918331, rs2053911, rs2033849, rs13019672, rs13034774, rs9809528, rs3430 9901, rs10034991, rs279844, rs4484354, rs1487052, rs1156358, rs158803, rs1005 7763, rs2235254, rs6933870, rs7767965, rs1358856, rs2503107, rs2272998, rs1177 9605, rs6473257, rs944662, rs826472, rs3780962, rs2435344, rs7911308, rs65911 47. rs1863370, rs7962675, rs2920816, rs2730648, rs6581429, rs7980449, rs959897 , rs7979370, rs11617748, rs1413577, rs430046, rs4796362, rs1493232, rs576261, rs4813947, rs12480506, rs6639398, rs7060326, rs5915052, rs4826248, rs6649211; The 11 human methylation markers are as follows: CpG1, CpG2, CpG3, CpG4, CpG5, CpG6, CpG7, CpG8, CpG9, CpG10 and CpG11; the CpG1 is located at position 207823681 of chromosome 1; the CpG2 is located at position 105399282 of chromosome 2; the CpG3 is located at position 160450189 of chromosome 3; the CpG4 is located at position 11044628 of chromosome 6; the C pG5 is located at position 130734355 on chromosome 7; the CpG6 is located at position 3344275 on chromosome 19; the CpG7 is located at position 108562706 on chromosome 6; the CpG8 is located at position 219514322 on chromosome 2; the CpG9 is located at position 143943879 on chromosome 8; the CpG10 is located at position 27251959 on chromosome 7; and the CpG11 is located at position 53961752 on chromosome 12.

8. A method for identifying 55 SNPs and 11 methylation markers in a human test sample, comprising the following steps: (1) Take the test sample, extract DNA, and then perform pretreatment to convert the methylated C in the DNA into DHU; (2) using the product of step (1) as a template and the primer combination described in claim 1 to perform multiplex PCR amplification; (3) Purifying the amplified product of step (2) and then constructing the library; (4) The library constructed in step (3) is subjected to high-throughput sequencing to output the original sequencing results, and the genetic information of the 55 SNPs and 11 methylation markers of the test sample is obtained based on the original sequencing results.

9. A method for forensic identification of a test sample, comprising the following steps: (1) Take the test sample, extract DNA, and then perform pretreatment to convert the methylated C in the DNA into DHU; (2) using the product of step (1) as a template and the primer combination described in claim 1 to perform multiplex PCR amplification; (3) Purifying the amplified product of step (2) and then constructing the library; (4) Performing high-throughput sequencing on the library constructed in step (3), outputting the original sequencing results, and performing data analysis on the original sequencing results.

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