Genetic marker detection system containing 68 high-performance autosomal haplotypes and application

Abstract

The invention provides a genetic marker detection system containing 68 high-performance autosomal haplotypes and application, and relates to the field of forensic identification. The detection system is formed by combining 68 amplification primer pairs after amplification, and the sequences of the amplification primers are as shown in SEQ ID No. 1 to SEQ ID No. 136. The invention also provides a method for identifying the genetic relationship, which comprises the following steps: S1, collecting a sample, extracting DNA (Deoxyribonucleic Acid), and obtaining a corresponding original sequencing result; s2, comparing an original sequencing result with a human reference genome hg38, and screening to obtain a genetic typing of each MiniHap gene locus; and S3, calculating the likelihood ratio of the specific genetic relationship between the sample pairs, and judging whether the sample pairs have the genetic relationship or not. According to the invention, a haplotype panel containing 68 human MiniHaps gene loci is constructed, and by combining multiple PCR and nanopore sequencing, very high personal identification and genetic relationship identification system efficiency can be achieved, and genetic relationship identification within third level is expected to be realized.

Description

Technical Field

[0001] This invention relates to the field of forensic identification, and more specifically, to a genetic marker detection system containing 68 high-efficiency autosomal haplotypes and its application. Background Technology

[0002] Kinship identification is one of the most important tasks in forensic judicial appraisal practice. It is crucial not only in paternity testing but also widely applied in judicial and civil fields such as criminal investigation, missing persons tracing, identification of disaster victims, and inheritance disputes. With evolving societal needs, accurate identification of complex kinship relationships (such as third-degree kinship) has become a key challenge in this field.

[0003] Currently, short tandem repeat (STR) analysis based on capillary electrophoresis is the gold standard for kinship identification. While its high polymorphism provides a powerful ability to identify first-degree relatives, STR technology itself has many limitations. For example, stutter artifacts, a high mutation rate, and a limited number of available loci all pose significant challenges to the accurate identification of distant relatives. SNPs have advantages such as low mutation rates, wide distribution in the genome, and a large number of loci, making them particularly suitable for degraded samples and distant kinship analysis. However, SNPs themselves are biallelic, with relatively low polymorphic information content. Typically, tens of thousands of loci need to be detected together to achieve sufficient discriminative power, which poses significant challenges to detection costs and data analysis.

[0004] Microhaplotypes are defined as short DNA sequences in the genome, typically less than 300 bp in length, containing two or more tightly linked SNPs. These SNPs collectively constitute a haplotype with multiple alleles. MH markers offer several significant advantages, such as absence of stutter artifacts, low mutation rate, and high polymorphism. These advantages enhance individual identification, kinship analysis, mixture deconvolution, and ancestor prediction capabilities. Building upon the foundation of microhaplotype research, some researchers have further proposed novel markers with even higher polymorphism—MiniHaps. These markers are defined as DNA fragments less than 800 bp in length containing at least five tightly linked SNPs. Compared to traditional MH, MiniHaps exhibit significantly higher allele diversity due to the inclusion of more SNPs, with an average effective allele count exceeding 12, demonstrating discriminative ability comparable to or even superior to STRs.

[0005] Current massively parallel sequencing (MPS) platforms only allow sequencing of relatively short reads (<400 bp), which is not suitable for the length of MiniHaps. Therefore, a new approach is needed that can sequence longer reads. Summary of the Invention

[0006] The purpose of this invention is to provide a genetic marker detection system containing 68 high-performance autosomal haplotypes and its application. It obtains genotyping results for 68 MiniHaps loci by specifically amplifying primer pairs of 68 human MiniHaps loci genetic markers in the same system. In addition, the primer pairs do not interfere with each other, which can meet the requirements of multiplex PCR. It also has high efficiency in individual identification and kinship identification, and is expected to solve the problem of kinship identification within three degrees.

[0007] The technical problem solved by this invention is achieved by the following technical solution.

[0008] In a first aspect, embodiments of this application provide a genetic marker detection system containing 68 high-performance autosomal haplotypes, which is composed of 68 amplification primer pairs after amplification, and the sequences of the amplification primers are shown in SEQ ID No.1-SEQ ID No.136.

[0009] Secondly, embodiments of this application provide a forensic identification kit that uses the aforementioned amplification primer pair.

[0010] Thirdly, embodiments of this application provide a method for identifying kinship, which employs the aforementioned forensic identification kit and includes the following steps: S1: Collect samples, extract DNA, and obtain the corresponding raw sequencing results; S2: The original sequencing results are compared with the human reference genome hg38 to screen and obtain the genotypes of each MiniHap locus; S3: Calculate the likelihood of a specific kinship between sample pairs and determine whether they are related.

[0011] Furthermore, step S1 also includes performing multiplex PCR amplification on the extracted DNA and purifying the PCR product.

[0012] Furthermore, in step S2, the screening includes filtering out alleles with a minor allele and major allele read count ratio of less than 0.1 and loci with an average sequencing depth of less than 100×.

[0013] Fourthly, embodiments of this application provide the application of the genetic marker detection system containing 68 high-performance autosomal haplotypes in individual identification or kinship determination.

[0014] Compared with the prior art, the embodiments of the present invention have at least the following advantages or beneficial effects: 1. This invention screened 68 primer pairs for human MiniHaps loci genetic markers and constructed a MiniHaps system, which can be specifically amplified in the same system and the primer pairs do not interfere with each other, thus meeting the requirements of multiplex PCR. 2. The MiniHaps system constructed in this invention contains multiple SNPs with longer locus lengths (0-800bp), higher haplotype polymorphism, and high efficiency of the kinship identification system; 3. This invention combines the advantages of long reads in third-generation sequencing technology, enabling direct acquisition of highly polymorphic long-fragment haplotypes, which significantly improves the efficiency of kinship identification. Attached Figure Description

[0015] To more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings used in the embodiments will be briefly introduced below. It should be understood that the following drawings only show some embodiments of the present invention and should not be regarded as a limitation of the scope. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort.

[0016] Figure 1 This is a schematic diagram of the overall sequencing process of the detection system in Embodiment 3 of the present invention; Figure 2 This is a schematic diagram illustrating the kinship of the samples in Embodiment 3 of the present invention; Figure 3 This is a schematic diagram of the sample sequencing performance in Example 3 of the present invention; Figure 4 This is a likelihood ratio distribution diagram of true kinship pairs and unrelated individual pairs in Embodiment 3 of the present invention; Figure 5 This is a likelihood ratio distribution diagram of simulated sample kinship pairs and unrelated individual pairs in Embodiment 4 of the present invention. Detailed Implementation

[0017] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below. Where specific conditions are not specified in the embodiments, conventional conditions or conditions recommended by the manufacturer shall apply. Reagents or instruments whose manufacturers are not specified are all conventional products that can be purchased commercially.

[0018] It should be noted that, unless otherwise specified, the embodiments and features described in this application can be combined with each other. The present invention will now be described in detail with reference to specific embodiments.

[0019] Example 1 This embodiment provides a detailed method for constructing a genetic marker detection system containing 68 high-performance autosomal haplotypes, including the following steps: Step 1: SNP loci were screened from the 1000 Genomes Project (1kGP). The screened loci met Hardy-Weinberg equilibrium, i.e., p > 0.05. InDel loci were excluded, and only dia allele SNP loci were retained, with a minor allele frequency (MAF) greater than 0.1. Haplotype assembly was then performed, arranging all possible SNP combinations within an 800 bp range to form MiniHaps loci. The effective allele count (Ae) was calculated based on the frequency of each MiniHaps locus allele in the Southern Chinese (CHS) and Han Chinese in Beijing (CHB) populations of the 1kGP.

[0020] Ae is calculated as follows:

[0021] Where n represents the total number of alleles at the microhaplotype locus; pi represents the frequency of the i-th allele in the population.

[0022] Step 2: Further screen the assembled MiniHaps sites according to the following criteria to select MiniHaps sites that meet the purpose of this embodiment: ①MiniHaps are ≤800bp in length, contain ≥5 SNPs, and have an Ae value ≥12 in the CHS and CHB populations of the 1000 Genomes Association. ② When there is an overlapping region between MiniHaps sites, the site with the largest Ae and the shortest fragment length among the overlapping MiniHaps sites is retained. In order to reduce the possibility of linkage, the physical distance between gene loci on the same chromosome is greater than 10Mb. ③ The CHS and CHB populations satisfy Hardy-Weinberg equilibrium and there is no linkage disequilibrium; ④ View the sequence features within ±200 bp upstream and downstream of the microhaps location on the UCSC browser, remove recombination hotspots, and eliminate microhaps loci with long poly structures, repeat regions, or indels; this step initially screened out 79 MiniHaps sites.

[0023] Step 3: Based on the selected sites, primers were designed for each site using the hg38 pair. Multiple specific primers were designed flanking the ROI site based on thermodynamic stability; the amplicon ranged from 600-1271 bp, with 100% coverage. Primer evaluation software was used to assess primer dimerization and non-specific amplification. The designed and synthesized primers were validated by agarose gel electrophoresis single amplification, and primers with poor detection performance were evaluated and replaced. Then, multiplex amplification and sequencing were performed. After sequencing, MiniHaps sites that could not be stably detected, had excessively low total sequencing reads, or showed significant differences in allele sequencing reads among heterozygous individuals were excluded. 68 sites that could be stably amplified and sequenced, along with 136 effective primer sequences, were retained, forming the MiniHaps multiplex system. Specific information on the 68 MiniHaps sites is shown in Table 1, and the 136 effective primer sequences are shown in Table 2.

[0024] Table 1 Information on 68 MiniHaps sites

[0025] Table 2 Primers corresponding to the loci

[0026] In Table 2, "A, T, C, G, U" in the primer sequences represent the bases of the nucleic acid. "A" represents adenine, "T" represents thymine, "C" represents cytosine, and "G" represents guanine. "0" in the primer direction indicates a forward primer, used to amplify the sense strand of the target sequence. "1" indicates a reverse primer, used to amplify the antisense strand of the target sequence. The forward primer for detecting position 1 in sequence number SEQ ID NO. 1 is numbered SEQ ID NO. 2, and the reverse primer is numbered SEQ ID NO. 136.

[0027] Example 2 This embodiment calculates the system efficiency of a genetic marker detection system containing 68 high-performance autosomal haplotypes constructed in Example 1, including the following steps: 1. Obtain the frequencies of the 1000 Genomes Project in the Southern Chinese (CHS) and Han Chinese in Beijing (CHB) populations.

[0028] 2. Calculate the matching probability (MP) and the probability of non-parent exclusion (PE) for a single locus using frequency. The formula for calculating a single locus can be expressed as:

[0029] in, Indicates the number of alleles at a locus; Indicates the first The frequency of each allele in the population.

[0030]

[0031] in, This indicates the total number of alleles at this microhaplotype locus. pi , p j This represents the frequency of the i-th and j-th alleles in the population.

[0032] 3. Calculate the cumulative matching probability (CMP) and cumulative non-parent exclusion probability (CPE) for panels containing multiple loci. Calculation formula: ;

[0034] in, This indicates the total number of microhaplotype sites contained in the panel. This represents the probability of a random match at the i-th position. This represents the probability of a random match at the i-th position.

[0035] The experimental results are shown in Table 3: Table 3 System efficacy of the 68 MiniHaps loci detection system

[0036] It can be seen that the cumulative matching probability of this detection system is extremely small and the cumulative non-father exclusion probability is close to 1, which confirms that it can solve problems such as identity determination, parentage testing, and grandparent-grandchild identification.

[0037] Based on this conclusion, those skilled in the art can develop a genetic marker detection system containing 68 high-performance autosomal haplotypes into a locus kit, which can then be used by forensic experts to solve problems such as identity verification, parentage testing, and grandparent-grandchild identification.

[0038] Example 3 This embodiment further details a method for identifying kinship, which employs a genetic marker detection system containing 68 high-performance autosomal haplotypes as described in Example 1. The entire sequencing and genotyping process is as follows: Figure 1 As shown. First, an experimental analysis was conducted on one related family lineage with informed consent. The family lineage consisted of 32 members (all Han Chinese), and the kinship details are as follows. Figure 2 As shown, the family lineage contains 290 pairs of related individuals and 206 pairs of unrelated individuals, including 34 pairs of first-degree related individuals, 40 pairs of second-degree related individuals, and 41 pairs of third-degree related individuals.

[0039] The methods for determining kinship include the following steps: S1: Collect venous blood samples from each member, extract DNA using the salting-out method to obtain the test samples. 9947A genomic DNA and nuclease-free water were used as positive and template-free negative controls, respectively. Then, using the extracted DNA as a template, multiplex PCR amplification was performed. The PCR amplification system included the following reagents and quantities:

[0040] PCR amplification reaction procedure:

[0041] The PCR products were then purified using magnetic beads to remove unligated adapters, primers, and other impurities. Qubit-based quantification was performed to ensure the library quality and concentration met sequencing requirements.

[0042] After quantification, sequencing was performed on the PromethION 2 Solo nanopore sequencer platform. Sequencing libraries were prepared using the Native Barcoding Kit 96 V14 (catalog number SQK-NBD114.96) according to the manufacturer's instructions. The prepared libraries were loaded into a PromethION R10.4.1 sequencing chip, and sequencing was performed using Kit 14 chemical reagents under the control of MinKNOW v23.07.8 software, yielding raw data in POD5 format. Base identification of the raw data was performed using Dorado base identification software (version 0.5.1) with the highly accurate model dna_r10.4.1_e8.2_400bps_sup@v4.2.0. The obtained FASTQ data were quality assessed using NanoStat software, and sequencing adapters were removed using Porechop software.

[0043] S2. The sequences in the FASTQ files obtained from sequencing were compared with the human reference genome hg38. Alleles with a read ratio of less than 0.1 for both minor and major alleles, as well as loci with an average sequencing depth of less than 100×, were filtered out to obtain the genotypes of each MiniHap locus for each member. The sequencing results of 32 individuals are as follows: Figure 3 As shown, the 68 sites selected in this invention have good sequencing performance.

[0044] S3. Calculate the likelihood of a specific kinship between sample pairs using the ITO method. Allelic frequencies used for kinship identification are calculated based on the genotypes and haplotypes of 208 unrelated Chinese individuals from the 1000 Genomes Project. For any two samples to be identified, if the cumulative kinship index is ≤10... t1（ If the lower limit is t1), it is determined to be an irrelevant individual; if the cumulative kinship index is ≥10 t2（ If the upper limit t2 is reached, the corresponding kinship is determined; if it is between t1 and t2, the sample cannot be identified. Experimental results are shown in Table 4 and... Figure 4 As shown.

[0045] Table 4. Results of identification of specific kinship between sample pairs

[0046] Combined with Table 4, Figure 4 and Figure 2 It can be seen that: First-degree kinship (full siblings): 34 kinship samples formed 23 parent-child pairs, 11 of which were full siblings. All MiniHaps loci observed in the 23 genuine parent-child pairs conformed to Mendelian laws of inheritance. The logarithmic distribution of the 11 full sibling samples...10 The likelihood distributions of LR and irrelevant individual pairs have no overlapping area. Using 3 and -3 as the decision thresholds, all full-sib samples can be correctly identified as full siblings. That is, a genetic marker detection system containing 68 high-efficiency autosomal haplotypes has 100% effectiveness in first-degree kinship analysis.

[0047] Second-degree kinship (second-degree kinship pairs): logarithmic value of 40 pairs of second-degree kinship samples 10 The overlap area between the LR values ​​and the likelihood distributions of irrelevant individual pairs is 0. Using 3 and -3 as the determination thresholds, all second-degree related samples can be correctly determined as second-degree related. The effectiveness of the detection system is 100%.

[0048] Third-degree kinship (third-degree kinship pairs): The overlap area between the log10LR values ​​of 41 third-degree kinship samples and the likelihood distributions of unrelated individual pairs was 2.42%. Using 1 and -1 as thresholds, the effectiveness of the detection system was 92.31%; using 2 and -2 as thresholds, the effectiveness was 80.57%; and using 3 and -3 as thresholds, the effectiveness was 58.70%.

[0049] Example 4 This embodiment further verifies the identification efficacy of the genetic marker detection system containing 68 high-performance autosomal haplotypes described in Example 1 through high-frequency simulation testing. The method is largely the same as in Example 3, including the following steps: Python software was used to simulate different levels of kinship. The simulation count for each level was set to 10,000, resulting in 10,000 pairs of samples. The simulations differentiated between 10,000 first-degree kinship pairs and 10,000 unrelated individual pairs; 10,000 second-degree kinship pairs and 10,000 unrelated individual pairs; and 10,000 third-degree kinship pairs and 10,000 unrelated individual pairs. The kinship index of the simulated samples was calculated using the ITO method, and allele frequencies were calculated based on the genotypes and haplotypes of 208 unrelated individuals from the 1000 Genomes Project in China. The kinship determination threshold was the same as in Example 3. The experimental results are shown in Table 5. Figure 5 As shown.

[0050] Table 5. Results of kinship identification in simulated family samples

[0051] From Table 5 and Figure 5 It can be seen that: First-degree kinship (full sibling pairs): logarithm of 10,000 full sibling pairs 10The likelihood distributions of LR and irrelevant individual pairs have no overlapping area. Using 3 and -3 as the decision thresholds, all full-sib samples can be correctly identified as full siblings. That is, a genetic marker detection system containing 68 high-efficiency autosomal haplotypes has 100% effectiveness in simulated first-degree kinship analysis.

[0052] Second-degree kinship (second-degree kinship pairs): logarithmic value of 10,000 pairs of second-degree kinship samples. 10 The overlap area between the LR value and the likelihood distribution of irrelevant individual pairs is 0. Using 3 and -3 as the judgment thresholds, the effectiveness of the detection system is 99.89%.

[0053] Third-degree kinship (third-degree kinship pairs): The overlap area between the log10LR values ​​of 10,000 third-degree kinship pairs and the likelihood distribution of unrelated individual pairs is 1.42%. Using 1 and -1 as thresholds, the effectiveness of the detection system is 95.19%; using 2 and -2 as thresholds, the effectiveness is 86.56%; and using 3 and -3 as thresholds, the effectiveness is 69.86%.

[0054] Based on the conclusions of this embodiment and Embodiment 3, it is clear that the genetic marker detection system containing 68 high-efficiency autosomal haplotypes provided in Embodiment 1 is fully applicable to individual identification or kinship determination. Those skilled in the art can apply it according to actual circumstances.

[0055] In summary, this invention provides a genetic marker detection system containing 68 high-performance autosomal haplotypes and its application. It screens primer pairs for 68 human MiniHaps loci genetic markers, constructs a MiniHaps system, which enables specific amplification within the same system, and the primer pairs do not interfere with each other, thus meeting the requirements of multiplex PCR. The MiniHaps system constructed in this invention contains multiple SNPs with longer locus lengths (0-800bp), higher haplotype polymorphism, and high efficiency of the kinship identification system; This invention combines the advantages of long reads in third-generation sequencing technology to directly obtain highly polymorphic long-fragment haplotypes, significantly improving the efficiency of kinship identification.

[0056] The embodiments described above are some, but not all, embodiments of the present invention. The detailed description of the embodiments of the present invention is not intended to limit the scope of the claimed invention, but merely to illustrate selected embodiments. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without inventive effort are within the scope of protection of the present invention.

Claims

1. A genetic marker detection system containing 68 high-performance autosomal haplotypes, characterized in that, It is composed of 68 amplification primer pairs combined after amplification, and the sequences of the amplification primers are shown in SEQ ID No.1-SEQ ID No.

136.

2. A reagent kit for forensic identification, characterized in that, The amplification primer pair as described in claim 1 was used.

3. A method for identifying kinship using the forensic identification kit as described in claim 2, characterized in that, Includes the following steps: S1: Collect samples, extract DNA, and obtain the corresponding raw sequencing results; S2: The original sequencing results are compared with the human reference genome hg38 to screen and obtain the genotypes of each MiniHap locus; S3: Calculate the likelihood of a specific kinship between sample pairs and determine whether they are related.

4. The method for identifying kinship according to claim 3, characterized in that, Step S1 also includes performing multiplex PCR amplification on the extracted DNA and purifying the PCR product.

5. The method for identifying kinship according to claim 3, characterized in that, In step S2, the screening includes filtering out alleles with a minor allele and major allele read count ratio of less than 0.1 and loci with an average sequencing depth of less than 100×.

6. The application of the genetic marker detection system containing 68 high-efficiency autosomal haplotypes as described in claim 1 in individual identification or kinship identification.

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