Design of a panel for targeted capture sequencing of thalassemia gene mutations and its application in detection of thalassemia gene mutations

Abstract

The application belongs to the technical field of gene detection and high-throughput sequencing, and particularly relates to a design of a thalassemia gene mutation targeted capture sequencing panel and application thereof in thalassemia gene mutation detection. The application integrates multi-source databases, high-frequency SNP skeletons and structural variation breakpoints, designs a probe combination covering the coding region, the regulatory region and the SV hotspot region of the alpha / beta globin gene cluster, and covers about 160 kb. Based on the targeted capture sequencing method of the panel, gDNA is used as a sample, various sequencing platforms are compatible, various mutations can be detected at one time with high depth, and SNP regulatory sites and splicing regions are comprehensively covered. The method has high sensitivity and strong universality, and can realize one-stop closed-loop analysis from sequencing to reporting by cooperating with a local analysis system, and is suitable for thalassemia genetic screening and research application.

Description

Technical Field

[0001] This invention belongs to the field of gene detection and high-throughput sequencing technology, specifically relating to the design of a targeted capture sequencing panel for thalassemia gene mutations and its application in the detection of thalassemia gene mutations. Background Technology

[0002] Thalassemia is an autosomal recessive genetic disorder caused by mutations in globin genes, leading to an imbalance in the synthesis of hemoglobin subunits. Clinically, it is mainly divided into α-thalassemia and β-thalassemia based on the type of globin chain affected. α-thalassemia is mostly caused by large deletions (such as -SEA, -α3.7, -α4.2, etc.) or point mutations (such as Hb CS, Hb QS, etc.) in the α-globin gene cluster; β-thalassemia mainly involves point mutations and small deletions (such as CD41 / 42, IVS-II-654, -28, etc.) in the HBB gene. Currently, there is no effective cure for this disease. Carrier screening and prenatal diagnosis to prevent the birth of severely affected children remain the internationally recognized preferred prevention and control strategy.

[0003] Traditional detection methods such as Gap-PCR, PCR-RDB, and Sanger sequencing have played an important role in clinical applications, but they still have limitations such as low throughput, limited detection range, and difficulty in identifying rare or novel variants. In recent years, the rapid development of next-generation sequencing (NGS) technology, especially the targeted enrichment strategy based on hybridization capture, has provided a new technical pathway for the precise molecular diagnosis of thalassemia. This method can perform high-depth sequencing of the whole coding regions, regulatory regions, and known structural variant breakpoint regions of multiple related genes, enabling the simultaneous detection of single nucleotide variants (SNVs), insertions and deletions (Indels), copy number variations (CNVs), and complex structural variations.

[0004] However, traditional panel designs often rely on a single reference genome or a limited mutation database, easily overlooking rare but clinically significant variants. Furthermore, for the molecular diagnosis of thalassemia, there is a lack of a systematically validated, standardized gDNA targeted capture sequencing workflow suitable for routine clinical laboratory use, as well as a lack of supporting localized bioinformatics analysis and reporting systems. This hinders the achievement of closed-loop management from sample processing to report generation, severely restricting the translation of advanced sequencing technologies into clinical testing. Therefore, establishing a thalassemia gene detection solution capable of comprehensively covering the core regions of the globin gene cluster in a single test, simultaneously detecting multiple variant types, possessing high throughput and a standardized workflow, and equipped with a localized analysis system has become an urgent technical challenge. Summary of the Invention

[0005] The purpose of this invention is to provide a design for a targeted capture sequencing panel for thalassemia gene mutations and its application in the detection of thalassemia gene mutations. The panel covers a 160-300 kb genomic region and can simultaneously detect multiple mutation types such as single nucleotide variants, insertions and deletions, and structural variants, achieving "one-time capture and comprehensive detection". It also has high sensitivity, strong specificity, and reliable results.

[0006] This invention provides a method for designing a targeted capture sequencing panel for thalassemia gene detection, comprising the following steps: S1: Construct a multi-level target database, which includes four layers of data sources as shown in S11 to S14; S11: Identify core target regions based on human hemoglobin-related genes and distal regulatory elements annotated by the GENCODE and ENCODE projects. S12: Systematically review the pathogenic variants of thalassemia reported in literature, including HbVar, ClinVar, LOVD, and others. Collect the types and coordinate information of confirmed pathogenic variants. The types of pathogenic variants include small fragment variants and structural variants. The small fragment variants include single nucleotide variants and insertions / deletions. The structural variants include large fragment deletions, large fragment duplications, and gene fusion events. S13: Integrate gnomAD, 1000 Genomes Project and ChinaMAP databases to screen for high heterozygous SNP sites with MAF>5% in the α-globin gene cluster and β-globin gene cluster and the flanking regions of the above two, as backbone markers for haplotype analysis; S14: Collect the precise breakpoint coordinates of thalassemia-related variants and construct a structural variant breakpoint database. The thalassemia-related variants include large fragment deletions, large fragment duplications, and gene fusion events. S2: Based on the multi-level target database constructed in S1, the steps of constructing a high-density SNP backbone, covering known structural variation breakpoints, and enriching polymorphic sites are performed to design a probe set covering the target region; the probe set covers the coding region, regulatory region, splicing site, non-coding regulatory SNP site, and known structural variation breakpoint region of the α-globin gene cluster and β-globin gene cluster.

[0007] Preferably, the non-coding regulatory SNP sites are non-coding regulatory SNP sites obtained based on HaploReg and RegulomeDB annotations that affect the expression of α-globin gene clusters and β-globin gene clusters.

[0008] Preferably, the non-coding modulated SNPs include rs6732518, rs6738440, rs9402685, rs10189857, rs7606173, rs11759553, rs6545816, rs10184550, rs35959442, rs1427407, rs28384513, rs4895440, rs7599488, and rs6904897. rs4895441, rs766432, rs9376090, rs9402686, rs11886868, rs66650371, rs9494142, rs4671393, rs7776054, rs1320963, rs7557939, rs9399137, rs6934903, rs6706648, rs9389268, and rs6929404.

[0009] Preferably, the high-density SNP backbone construction step includes: based on 1000 GenomesProject data of the Chinese population, screening out high heterozygous SNP sites with an average interval of less than 500 bp within the α-globin gene cluster and β-globin gene cluster to form an SNP tag system; the MAF of the high heterozygous SNP sites is between 0.25 and 0.75.

[0010] Preferably, the high-density SNP backbone is used for copy number variation analysis and linkage haplotype analysis; In the copy number variation analysis, the full-region dose spectrum is constructed by calculating the ratio of sequencing depth to reference depth for each SNP site, and at least one of the following two analyses is performed: (1) determining the precise breakpoint boundary of deletion variants; (2) determining the heterozygous / homozygous status of all variant sites. In the linked haplotype analysis, haplotype classification is performed using genotype information from SNP loci.

[0011] Preferably, the high-density SNP backbone construction step further optimizes the probe group's step-by-step design in high GC regions and repetitive sequence regions through an iterative masking algorithm; after the step-by-step design optimization, the coefficient of variation of the coverage of the SNP backbone region is less than 0.3.

[0012] Preferably, the structural variation breakpoint database includes the precise breakpoint coordinates of -SEA, -α3.7, -α4.2, HKαα, Thaideletion, Filipino deletion, and HPFH deletion of the β-globin gene cluster.

[0013] Preferably, the step of covering known structural variation breakpoints includes: designing probes that cover the classic breakpoint and a 2 kb range upstream and downstream of the breakpoint.

[0014] Preferably, the probe is 100-140 nt in length; the probe set covers a 160-300 kb genomic region, and the number of probes is 1000-2000.

[0015] Preferably, the design method further includes updating the targeted capture sequencing panel; and supplementing probes when new thalassemia pathogenic variants or high-information SNPs are reported.

[0016] The present invention also provides a targeted capture sequencing panel for thalassemia gene detection, which is obtained using the design method described above.

[0017] The present invention also provides a panel for genetic disease gene detection, including the targeted capture sequencing panel for thalassemia gene detection described in the above technical solution and a customized panel for other genetic disease gene detection.

[0018] The present invention also provides the application of the targeted capture sequencing panel or the panel described in the above technical solution in the preparation of products for thalassemia detection.

[0019] This invention also provides a kit for thalassemia gene detection, comprising the targeted capture sequencing panel and sequencing reagents described in the above technical solution; the sequencing-related reagents include one or more of hybridization capture system buffers, sequencing platform adapters, and amplification primers.

[0020] This invention also provides a thalassemia gene detection system, comprising a sample processing module, a library construction module, a hybridization capture module, a high-throughput sequencing module, and a result output module: The sample processing module is used to process the sample to be tested; the processing of the sample to be tested includes extracting genomic DNA from the sample to be tested; The library construction module is connected to the sample processing module and is used to construct a genomic library based on the genomic DNA. The hybridization capture module is connected to the library construction module and is used to enrich the target region DNA fragment; the method for enriching the target region DNA fragment includes: using the targeted capture sequencing panel described in the above technical solution to hybridize and capture the genomic DNA to obtain the target region DNA fragment; The high-throughput sequencing module is connected to the hybridization capture module and is used to acquire high-throughput sequencing data of the sample to be tested; the acquisition steps include: performing high-throughput sequencing on the DNA fragment of the target region to obtain high-throughput sequencing data; The result output module is connected to most high-throughput sequencing modules to obtain the thalassemia gene detection results in the sample to be tested; the acquisition steps include: performing bioinformatics analysis on the high-throughput sequencing data to identify single nucleotide variants, insertions and deletions and structural variants, the structural variants including copy number variants, large fragment deletions / duplications and gene fusions, and outputting the variant site detection results.

[0021] This invention also provides a method for detecting thalassemia genes, comprising the following steps: 1) Extract genomic DNA from the sample to be tested; 2) Construct a genomic library based on the genomic DNA; 3) The genomic library is hybridized and captured using the targeted capture sequencing panel described in the above technical solution to obtain DNA fragments in the target region; 4) Perform high-throughput sequencing on the DNA fragment in the target region to obtain high-throughput sequencing data; 5) Perform bioinformatics analysis on the high-throughput sequencing data to identify single nucleotide variants (SNVs), insertions / deletions (Indels), and structural variants (SVs). The structural variants include copy number variants (CNVs), large fragment deletions / duplications, and gene fusions. Output the variant site detection results.

[0022] Beneficial effects: This invention provides a method for designing a targeted capture sequencing panel for thalassemia gene detection. The design incorporates innovative strategies such as multi-source database integration, high-frequency SNP backbone construction, and precise capture of structural variant endpoints, resulting in a probe combination capable of covering approximately 160 kb of the genome. Based on this panel and targeted capture sequencing technology, high-depth sequencing can be performed simultaneously on the coding regions, regulatory regions, splicing sites, non-coding regulatory SNP sites, and known structural variant breakpoint regions of the α-globin and β-globin gene clusters in thalassemia. This enables comprehensive detection of various variant types, including single nucleotide variants, insertions / deletions, and structural variations, with high sensitivity, strong specificity, and reliable results.

[0023] Based on the aforementioned panel, this invention also provides a method for thalassemia gene detection. This method uses gDNA as the detection sample, is based on the Illumina platform (compatible with MGI), and is suitable for genetic disease screening and diagnosis in medical institutions and research units at all levels, exhibiting strong universality. Combined with existing high-throughput sequencing analysis systems, it enables localized closed-loop analysis from sequencing data to variant interpretation. Data analysis is fully controllable, results are available in real time, and personalized report generation is supported, significantly improving the comprehensiveness, sensitivity, and interpretability of thalassemia gene detection. Detailed Implementation

[0024] This invention provides a method for designing a targeted capture sequencing panel for thalassemia gene detection, comprising the following steps: S1: Construct a multi-level target database, which includes four layers of data sources as shown in S11 to S14; S11: Identify core target regions based on human hemoglobin-related genes and distal regulatory elements annotated by the GENCODE and ENCODE projects. S12: Systematically review the pathogenic variants of thalassemia reported in literature, including HbVar, ClinVar, LOVD, and others. Collect the types and coordinate information of confirmed pathogenic variants. The types of pathogenic variants include small fragment variants and structural variants. The small fragment variants include single nucleotide variants and insertions / deletions. The structural variants include large fragment deletions, large fragment duplications, and gene fusion events. S13: Integrate gnomAD, 1000 Genomes Project and ChinaMAP databases to screen for high heterozygous SNP sites with MAF>5% in the α-globin gene cluster and β-globin gene cluster and the flanking regions of the above two, as backbone markers for haplotype analysis; S14: Collect the precise breakpoint coordinates of thalassemia-related variants and construct a structural variant breakpoint database. The thalassemia-related variants include large fragment deletions, large fragment duplications, and gene fusion events. S2: Based on the multi-level target database constructed in S1, the steps of constructing a high-density SNP backbone, covering known structural variation breakpoints, and enriching polymorphic sites are performed to design a probe set covering the target region; the probe set covers the coding region, regulatory region, splicing site, non-coding regulatory SNP site, and known structural variation breakpoint region of the α-globin gene cluster and β-globin gene cluster.

[0025] This invention constructs a multi-level target database, which includes four layers of data sources.

[0026] This invention, based on human hemoglobin-related genes and distal regulatory elements annotated by the GENCODE and ENCODE projects, identifies core target regions and forms a first-layer data source covering human hemoglobin genes and regulatory elements. As one implementation, the distal regulatory elements described in this invention can be, but are not limited to, the major enhancer (HS-40) of the α-globin gene cluster and / or the control region of the β-globin locus (β-LCR).

[0027] This invention systematically reviews HbVar, ClinVar, LOVD, and other literature-reported pathogenic variants of thalassemia, collecting the types and coordinate information of confirmed pathogenic variants to form a second layer of data source covering known pathogenic variants of human hemoglobin. The pathogenic variants described in this invention can be small fragment variants or structural variants; small fragment variants include single nucleotide variants (SNVs) and insertions / deletions (Indels), while structural variants include large fragment deletions, large fragment duplications, and gene fusion events. In this invention, the number of literature-reported thalassemia pathogenic variants is greater than 2000, and these 2000+ known thalassemia pathogenic variants are publicly available and relatively well-known in the art.

[0028] This invention integrates the gnomAD, 1000 Genomes Project, and ChinaMAP databases to screen for high heterozygous SNP sites with MAF>5% in the α-globin gene cluster and β-globin gene cluster, as well as in the flanking regions of the above two, as backbone markers for haplotype analysis, thus forming a third layer of data source covering population polymorphism information.

[0029] This invention collects precise breakpoint coordinates of thalassemia-related variants to construct a structural variant breakpoint database, thus forming a fourth-layer data source covering structural variant breakpoints of thalassemia genes. The thalassemia-related variants described in this invention include large deletions, large duplications, and gene fusion events. As one implementation, the structural variant breakpoint database of this invention contains more than 50 precise breakpoint coordinates for thalassemia-related variants, specifically including but not limited to precise breakpoint coordinates for --SEA, -α3.7, -α4.2, HKαα, Thai deletion, Filipino deletion, and HPFH deletion of the β-globin gene cluster.

[0030] As one implementation, the target database of the present invention further includes knowledge-driven region expansion; that is, non-coding regulatory SNP sites obtained by annotating the expression of α-globin gene clusters and β-globin gene clusters based on HaploReg and RegulomeDB are incorporated into the multi-level target database. As one implementation, the non-coding regulatory SNPs of the present invention include rs6732518, rs6738440, rs9402685, rs10189857, rs7606173, rs11759553, rs6545816, rs10184550, rs35959442, rs1427407, rs28384513, rs4895440, rs7599488, and rs6904. 897, rs4895441, rs766432, rs9376090, rs9402686, rs11886868, rs66650371, rs9494142, rs4671393, rs7776054, rs1320963, rs7557939, rs9399137, rs6934903, rs6706648, rs9389268, and rs6929404. These loci can be used not only for the study of thalassemia phenotypic modifiers but also to provide genetic markers for assessing the potential response to fetal hemoglobin-inducing therapies (such as hydroxyurea).

[0031] After obtaining the multi-level target database, the present invention performs the following steps: high-density SNP backbone construction, known structural variation breakpoint coverage, and polymorphic site enrichment, and designs probe sets to cover the target region.

[0032] In one implementation, the high-density SNP backbone construction step of the present invention includes: based on 1000 Genomes Project data of the Chinese population, screening for high heterozygous SNP sites with an average interval of less than 500 bp within the α-globin gene cluster and β-globin gene cluster, forming an SNP tag system; the MAF of the high heterozygous SNP sites is between 0.25 and 0.75. The probe set design of the present invention covers the α-globin gene cluster located at nucleotides 10,000 to 300,000 on chromosome 16 (NC_000016.9) in the human reference genome GRCh37 or hg19 version; and covers the β-globin gene cluster located at approximately nucleotides 5,000,000 to 5,500,000 on chromosome 11 (NC_000011.9) in the human reference genome GRCh37 or hg19 version. Based on the above steps, a dense labeling system can be formed. These SNPs have a high information content in the population and can effectively distinguish different haplotypes.

[0033] As one implementation method, the high-density SNP backbone of the present invention can be used for both copy number variation analysis and linkage haplotype analysis. In the copy number variation analysis, a full-region dose spectrum is constructed by calculating the ratio of sequencing depth to reference depth for each SNP site, and at least one of the following two analyses is performed: (1) determining the precise breakpoint boundary of deletion variants; (2) determining the heterozygous / homozygous status of all variant sites. In the linkage haplotype analysis, haplotype classification is performed using the genotype information of SNP sites.

[0034] As one implementation method, the high-density SNP backbone construction step of the present invention also achieves step-by-step design optimization of probe sets in high GC regions and repetitive sequence regions through an iterative masking algorithm; after the step-by-step design optimization, the coefficient of variation of coverage of SNP backbone regions is less than 0.3, avoiding dose analysis bias caused by differences in probe hybridization efficiency.

[0035] In this invention, the core idea of ​​the iterative masking algorithm is to dynamically adjust the probe coverage strategy for a specific region through multiple iterations during the design process, gradually "masking" unqualified or already fully covered regions until the overall design meets the uniformity index. In a specific embodiment, the steps of the iterative masking algorithm are as follows: 1) First, high-density probe deployment is performed in the target region, and all known problem regions are filtered out using masking technology, such as probes containing repeating sequences like Alu or with extreme GC content (>70% or <30%). 2) For the initially screened probes, their length is adjusted or modifications are introduced to make the unwinding temperature of all probes as consistent as possible. This step is to overcome the problem of excessively strong probe binding in high-GC regions and excessively weak binding in low-GC regions. 3) After the initial design, probe walking is initiated for the remaining "empty windows" (e.g., all high GC region probes are filtered out): starting with the valid probes at the edge of the empty window, a series of new probes are generated by translating with a very small step size (e.g., 1-2 bp); the new probes immediately enter the screening pipeline, and if they are qualified, they are included in the design, and the sequence is then "masked," stopping the walking process; if they are not qualified, the walking process continues. Step 3) is the key to the "iterative masking algorithm."

[0036] As one implementation, the known structural variation breakpoint coverage step of the present invention includes: designing probes that cover the classic breakpoint and a 2 kb range upstream and downstream of the breakpoint; so that even if recombination occurs outside the classic breakpoint, it can still be effectively captured by split-reads or soft-clipped reads.

[0037] In one implementation, the probes of this invention are 100-140 nt in length, and more specifically, 120 nt. Probes of this length are compatible with both short-read sequencing platforms such as Illumina and MGI, and long-read sequencing platforms such as Oxford Nanopore (ONT) and PacBio, ensuring cross-platform data comparability during hybridization capture. In another implementation, the probe set of this invention covers approximately 160 kb of genomic region, with 1000-2000 probes, and more specifically, 1200-1500 probes. For example, the panel designed in this embodiment contains 1354 probes.

[0038] As one implementation method, the design method of this invention further includes updating the targeted capture sequencing panel; when new thalassemia pathogenic variants or high-information SNPs are reported, probes are added to maintain the timeliness of the panel. For example, in a specific embodiment, this invention can periodically search public databases such as HbVar, ClinVar, LOVD, and literature reports on thalassemia mutation profiles for newly emerging mutations. If a new mutation is not covered by the previously designed probe range, this invention can supplement the probe design according to the probe design method described above, and periodically and promptly upgrade the panel's detection range to ensure that the panel can adapt to the latest mutation types and prevent missed detections.

[0039] This invention also provides a targeted capture sequencing panel for thalassemia gene detection, obtained using the design method described above. The targeted capture sequencing panel obtained through the above design method not only achieves comprehensive and accurate detection of thalassemia-related variants, but also provides strong technical support for haplotype analysis, non-invasive prenatal diagnosis, and expression regulation research.

[0040] This invention also provides a panel for genetic disease gene detection, including the targeted capture sequencing panel for thalassemia gene detection described in the above technical solution and a customized panel for other genetic disease gene detection. That is, the core probe set of this application can not only be used alone, but can also be mixed with other customized panels (such as other genetic disease gene panels) in proportion to support the joint detection of multiple diseases.

[0041] This invention also provides the application of the targeted capture sequencing panel or the panel described in the above-described technical solutions in the preparation of products for thalassemia detection. As one embodiment, the product of this invention includes a reagent kit or a detection system.

[0042] This invention also provides a kit for thalassemia gene detection, comprising the targeted capture sequencing panel and sequencing reagents described in the above technical solution; the sequencing-related reagents include one or more of hybridization capture system buffer, sequencing platform adapter, and amplification primers. As in an embodiment of this invention, the hybridization capture system buffer may be NadPrep. ® The hybrid capture system can further be used for NadPrep ® NanoBlockers and NadPrep ® Amplification Primer Mix II; NadPrep ® NanoBlockers are compatible with single-ended or dual-ended indices on the MGI platform, and also with the Illumina platform; the NadPrep... ® Amplification Primer Mix II is compatible with different sequencing platforms.

[0043] This invention also provides a thalassemia gene detection system, comprising a sample processing module, a library construction module, a hybridization capture module, a high-throughput sequencing module, and a result output module: The sample processing module is used to process the sample to be tested; the processing of the sample to be tested includes extracting genomic DNA from the sample to be tested; The library construction module is connected to the sample processing module and is used to construct a genomic library based on the genomic DNA. The hybridization capture module is connected to the library construction module and is used to enrich the target region DNA fragment; the method for enriching the target region DNA fragment includes: using the targeted capture sequencing panel described in the above technical solution to hybridize and capture the genomic DNA to obtain the target region DNA fragment; The high-throughput sequencing module is connected to the hybridization capture module and is used to acquire high-throughput sequencing data of the sample to be tested; the acquisition steps include: performing high-throughput sequencing on the DNA fragment of the target region to obtain high-throughput sequencing data; The result output module is connected to most high-throughput sequencing modules to obtain the thalassemia gene detection results in the sample to be tested; the acquisition steps include: performing bioinformatics analysis on the high-throughput sequencing data to identify single nucleotide variants, insertions and deletions and structural variants, the structural variants including copy number variants, large fragment deletions / duplications and gene fusions, and outputting the variant site detection results.

[0044] As one implementation method, the bioinformatics analysis described in this invention uses the localized data analysis visualization and interactive system and method disclosed in Chinese Patent ZL202310154719.X for analysis.

[0045] This invention also provides a method for detecting thalassemia genes, comprising the following steps: 1) Extract genomic DNA from the sample to be tested; 2) Construct a genomic library based on the genomic DNA; 3) The genomic library is hybridized and captured using the targeted capture sequencing panel described in the above technical solution to obtain DNA fragments in the target region; 4) Perform high-throughput sequencing on the DNA fragment in the target region to obtain high-throughput sequencing data; 5) Perform bioinformatics analysis on the high-throughput sequencing data to identify single nucleotide variants (SNVs), insertions / deletions (Indels), and structural variants (SVs). The structural variants include copy number variants (CNVs), large fragment deletions / duplications, and gene fusions. Output the variant site detection results.

[0046] As one implementation method, the bioinformatics analysis described in this invention uses the localized data analysis visualization and interactive system and method disclosed in Chinese Patent ZL202310154719.X for analysis.

[0047] To further illustrate the present invention, the technical solutions provided by the present invention will be described in detail below with reference to the embodiments, but they should not be construed as limiting the scope of protection of the present invention.

[0048] Example 1 A method for designing a targeted capture sequencing panel for thalassemia gene detection, comprising the following steps: 1. Construct a multi-level target database, specifically including the following steps: 1) Based on GENCODE v38 and the hemoglobin gene and distal regulatory elements (such as HS-40 and LCR) annotated by the ENCODE project, the core target region was determined.

[0049] 2) A systematic review of more than 2,000 confirmed pathogenic variants reported in HbVar (a database for hemoglobinopathies), ClinVar, LOVD, and Chinese literature on thalassemia mutation spectrum, covering various types such as SNV, Indel, deletion, insertion, and fusion.

[0050] 3) Integrate gnomAD v3.1 (East Asian population subset), 1000 Genomes Project (East Asian and Southern Chinese populations) and ChinaMAP databases to screen for high heterozygous SNP sites with MAF>5% in α- and β-globin gene clusters and their flanking regions as backbone markers for haplotype analysis.

[0051] 4) Collect precise breakpoint coordinates of more than 50 types of large fragment deletions, duplications and fusions related to thalassemia reported globally (such as --SEA, -α3.7, -α4.2, HKαα, Thai deletion, Filipino deletion, HPFH deletion of β-globin gene cluster, etc.) to construct a thalassemia structural variation breakpoint database.

[0052] 5) It not only covers gene coding regions and classical splicing sites, but also annotates non-coding regulatory SNPs that may affect expression (such as rs1427407 in the BCL11A enhancer region and rs9399137 in the HBS1L-MYB intergenic region) through HaploReg and RegulomeDB, and incorporates them into the design scope to achieve indirect detection of abnormal expression regulation.

[0053] 6) Dynamic updates and maintenance: The target database supports regular updates. When new pathogenic variants or high-information SNPs are reported, probes can be quickly evaluated and supplemented to maintain the timeliness of the panel.

[0054] 2. Construction of a high-density SNP backbone: haplotype tagging system 1) Population-specific SNP screening: Based on 1000g of data from the Chinese population, high heterozygous SNPs (MAFs) with an average interval of <500 bp (MAF between 0.25 and 0.75) were screened within the α-globin gene cluster (chr16: 10,000 ~ 300,000) and the β-globin gene cluster (chr11: 5,000,000 ~ 5,500,000) to form a dense tagging system. These SNPs are highly informative in the population and can effectively distinguish different haplotypes.

[0055] 2) Dual-purpose design: The same SNP probe can be used for both copy number variation analysis and linkage haplotype analysis. 2.1) Dosage analysis: By calculating the ratio of sequencing depth to reference depth for each SNP site, a dose spectrum of the entire region is constructed. This allows for the accurate determination of the boundary of deletion variants and heterozygous / homozygous status through step changes in upstream and downstream SNP doses, even if the breakpoint is not captured.

[0056] 2.2) Algorithm-optimized probe design: An iterative masking algorithm is used to optimize probe walking in high GC regions and repetitive sequence regions (such as Alu repeats in the α-globin gene cluster) to ensure uniform coverage of SNP backbone regions (coverage variation coefficient <0.3) and avoid dose analysis bias caused by differences in probe hybridization efficiency.

[0057] 3. Coverage of known structural variation breakpoints: Precise design based on recombination hotspots 3.1) Refinement of recombination hotspots: In the analysis of recombination hotspots in the Chinese population, probes covering a 2kb range upstream and downstream of the breakpoint were added, so that even if recombination occurs outside the classic breakpoint, it can still be effectively captured by split-reads or soft-clipped reads.

[0058] 3.2) Long Fragment Compatibility: All structural variation probes are designed to be 120 nt, which can be used on both short read (Illumina / MGI) and long read (ONT / PacBio) sequencing platforms in hybridization capture, ensuring cross-platform data comparability.

[0059] 4. Enrichment of polymorphic sites: SNPs related to expression regulation and drug response Thirty functionally validated non-coding region polymorphism sites were included, as follows: rs6732518, rs6738440, rs9402685, rs10189857, rs7606173, rs11759553, rs6545816, rs10184550, rs35959442, rs1427407, rs28384513, rs4895440, rs7599488, and rs690. 4897, rs4895441, rs766432, rs9376090, rs9402686, rs11886868, rs66650371, rs9494142, rs4671393, rs7776054, rs1320963, rs7557939, rs9399137, rs6934903, rs6706648, rs9389268, and rs6929404.

[0060] 5. Probe Synthesis and Panel Assembly The probes designed based on the above steps are synthesized and assembled to obtain the final panel.

[0061] Example 2 A method for detecting thalassemia genes based on targeted capture sequencing technology is proposed. The experimental procedure consists of sample collection and gDNA extraction, library construction, hybridization capture, sequencing, and data analysis.

[0062] The following steps are described primarily using the Illumina sequencing platform, but they should not be considered as the entire scope of protection of this invention.

[0063] 1. Sample collection and gDNA extraction 1.1 Sample Collection Collect 2-4 mL of peripheral venous blood from the subject and place it in an EDTA anticoagulant tube. It can be stored at 4°C for a short period or at -20°C for a long period.

[0064] 1.2 g DNA extraction Using a commercially available genomic DNA extraction kit (such as the QIAGEN DNeasy Blood & Tissue Kit), follow the instructions. After extraction, DNA concentration was accurately determined using a Qubit 3.0 microscope, and purity was assessed using Nanodrop (A260 / A280 between 1.8 and 2.0, A260 / A230 > 1.5). Agarose gel electrophoresis was used to confirm DNA integrity (no significant degradation).

[0065] 1.3 Input Requirements The recommended starting gDNA for each sample for library construction is 100-200 ng; if the total sample size is insufficient, all gDNA can be used, but the actual amount used must be recorded.

[0066] 2. Library Construction 2.1 Main Instruments and Reagents Main instruments: PCR gene amplification instrument (with hot cap), Qubit 3.0 fluorescence quantitative instrument, small centrifuge, pipette, vortex mixer, magnetic rack (suitable for 0.2 mL PCR tubes), vacuum concentrator (optional), electrophoresis apparatus (for agarose gel electrophoresis).

[0067] Main reagent: NadPrep ® NEM Fragment Module, NadPrep ® DNA Library PreparationModule v2, NadPrep ® Universal Stubby Adapter (UDI) Module, NadPrep ® SP Beads, TESolution, KOD FX Neo (Toyobo), anhydrous ethanol, and Nuclease Free Water.

[0068] 2.2 Operating Procedures: 1) gDNA fragmentation (enzyme digestion method) A 20 μL reaction system was prepared on ice, as shown in Table 1.

[0069] Table 1. Systems for gDNA fragmentation using enzyme digestion method

[0070] After mixing the gDNA and related reagents according to the system in Table 1, incubate the mixture in a PCR instrument at 37°C for 15 min. Immediately after the reaction, place the mixture on ice, add 5 μL of Stop Solution, mix gently, and then add 25 μL of Nuclease Free Water to obtain 50 μL of reaction solution.

[0071] 2) Fragmentation product purification and fragment screening (dual selection method) (1) Add 50 μL of NadPrep to the above 50 μL reaction solution. ® (1) Spice beads, mix well, and incubate at room temperature for 5 min. (2) Adsorb on a magnetic rack, discard the supernatant; add 150 μL of 80% ethanol to wash the magnetic beads twice. (3) Add 100 μL of 10 mM Tris-HCl (pH 8.0) to resuspend the magnetic beads, add 56 μL of screening buffer (0.75 M NaCl, 20% PEG 8000), mix gently, and incubate at room temperature for 5 min. This step can remove small fragments <300 bp. (4) Adsorb on a magnetic rack, discard the supernatant, and wash twice with 150 μL of 80% ethanol. (5) Add 20 μL of TE Solution to resuspend the magnetic beads, incubate at 25℃ for 2 min, and transfer the supernatant to a new tube on a magnetic rack. (6) Analyze the fragmented products using 0.8% agarose gel electrophoresis. They should be diffuse, with the main peak at approximately 300~500 bp.

[0072] 3) End repair and A-tail addition Take all the fragmented purified product (approximately 20 μL) and prepare the following system according to Table 2 (final volume 50 μL): Table 2 End-of-line repair and A-tailing system

[0073] Place the prepared system in a PCR instrument and run the reaction according to the following program to obtain 50 μL of product. The PCR program is: 25℃ 20 min → 65℃ 20 min → 10℃ incubation.

[0074] 4) Connector connection Add the reagents listed in Table 3 to the 50 μL product obtained in step 3), and then place the resulting mixture in a PCR instrument and run the reaction according to the PCR program of 20℃ for 15 min → 4℃ to obtain the ligation product.

[0075] Table 3. Reagents related to connector connection

[0076] 5) Purification of ligation products (1) Add 40 μL of NadPrep to the ligation product. ® (1) Spice beads, mix well, and incubate at 25°C for 5 min. (2) Adsorb onto a magnetic rack, discard the supernatant; wash twice with 150 μL of 80% ethanol. (3) Add 100 μL of Tris-HCl to resuspend the magnetic beads, add 47 μL of selection buffer, mix well, and incubate for 5 min (double selection). (4) Adsorb onto a magnetic rack, discard the supernatant; wash twice with 150 μL of 80% ethanol. (5) Add 47 μL of amplification system (without primers) to the magnetic beads. The amplification system is shown in Table 4.

[0077] Table 4. Ligation product purification and amplification system

[0078] Mix gently, incubate at 25°C for 2 min, and transfer the supernatant to a new PCR tube after magnetic adsorption.

[0079] 6) PCR amplification of enriched libraries Add 3 μL NadPrep to the supernatant ® The PCR amplification procedure for Universal UDI-Index Primer Mix is ​​shown in Table 5.

[0080] Table 5 PCR amplification program

[0081] Purification of amplified products: Add 50 μL of SP Beads, mix and incubate, wash twice with 150 μL of 80% ethanol, and finally elute with 50 μL of TE Solution.

[0082] 7) Document Quality Control (1) Use Qubit 3.0 to quantify the library concentration. (2) Use 0.8% agarose gel electrophoresis or Agilent 2100 to analyze the distribution of library fragments. The main peak of a qualified library should be between 350 and 500 bp, without large fragment tails.

[0083] 3. Targeted enrichment (hybrid capture) Using NadPrep ® The experiment was performed using ES Hybrid Capture Reagents v2 (rapid hybridization reagent) and HGBP Panel v1.0 obtained according to the design method in Example 1.

[0084] 3.1 Library Mixing and Drying For each sample, use 500 ng of the constructed library (if less than 500 ng, use the entire amount), along with 5 μL HumanCot DNA and 2 μL NadPrep. ® NanoBlockers (for Illumina ® Mix. Add the mixture to a 0.2 mL PCR tube and dry it completely in a preheated 60°C vacuum concentrator. Alternatively, use the magnetic bead concentration method (see Appendix).

[0085] 3.2 Preparation of hybridization reaction solution and hybridization Prepare hybridization solutions for each reaction (calculate in advance and prepare 10% extra), as shown in Table 6.

[0086] Table 6 Hybridization solution system

[0087] Dissolve the dried library in 17 μL of the above hybridization solution, gently aspirate and incubate at 25°C for 10 min. Then perform hybridization in a PCR instrument, as shown in Table 7.

[0088] Table 7 PCR instrument hybridization program (heated lid 100℃)

[0089] Note: Extending the hybridization time may reduce the reaction volume due to evaporation. It is recommended to perform an evaporation test on the PCR instrument before hybridization. If evaporation occurs, add 10 μL of Sealing Oil to prevent volatilization.

[0090] 3.3 Magnetic Bead Capture and Elution Magnetic bead preparation: Take 50 μL of Streptavidin Beads II for each hybridization reaction (equilibrate at room temperature for ≥30 min before use, and vortex mix for 15 sec). Adsorb the beads onto a magnetic rack, discard the supernatant, wash twice with 100 μL of room temperature ES Wash Buffer II, and finally resuspend in 100 μL of room temperature ES Wash Buffer II. Keep warm at 65°C for later use.

[0091] Capture: After the hybridization program enters the 65℃ incubation stage, add the magnetic bead suspension to the hybridization reaction solution and gently mix by blowing and aspirating at least 10 times. Incubate at room temperature for 20 min (1500 rpm) on a vortex mixer. After incubation, place on a magnetic rack and let stand for 1 min, then discard the supernatant (remove as much as possible).

[0092] Hot elution: (1) Add 150 μL of ES Wash Buffer II preheated to 65℃, mix by pipetting more than 10 times, and transfer all liquid to a new PCR tube (Note: Replacing the PCR tube can reduce non-specific capture and increase the target rate, and cannot be omitted). (2) Incubate at 65℃ for 5 min, magnetic rack adsorption for 30 sec, and discard the supernatant. Repeat this step twice (a total of 3 hot elutions). (3) Add 200 μL of room temperature 80% ethanol along the tube wall on the magnetic rack, being careful not to disturb the magnetic beads, let stand for 30 sec, and discard the supernatant. (4) Centrifuge briefly, and remove the residual ethanol with a 10 μL pipette tip. Open the lid and dry at room temperature for 1~2 min until matte (do not over-dry). (5) Add 22.5 μL of Nuclease Free Water to resuspend the magnetic beads (including the magnetic beads, do not discard them), and proceed to the next step of amplification with the magnetic beads.

[0093] 3.4 Post-capture library amplification Prepare the amplification system (total 50 μL) as shown in Table 8, and perform amplification according to the PCR procedure described in Table 9 to obtain the library amplification product.

[0094] Table 8 Amplification System

[0095] Table 9 PCR program (heated lid 105℃)

[0096] Table 10 Reference number of amplification cycles (HGBP Panel approximately 160 kb, falling into the 1 Kb-50 Kb range).

[0097] After amplification, the supernatant was transferred to a new tube by magnetic rack adsorption, 60 μL of SP Beads was added for purification, and the tube was washed twice with 150 μL of 80% ethanol. Finally, the tube was eluted with 20 μL of TE Solution.

[0098] 3.5 Capture Library Quality Control Quantification was performed using Qubit 3.0, and library fragments were analyzed using Qsep100 or Agilent 2100 (the main peak should show no significant change). Safe pause point: The purified capture library can be stored at -25 to -15°C for one week.

[0099] 4. Sequencing Dilute the enriched library to an appropriate concentration and perform paired-end 150 bp sequencing on an Illumina NovaSeq 6000 (or other PE150 platform) using a sequencing service provider or your own sequencer. The target raw sequencing depth for each sample should be no less than 500× (probe coverage area), and above 1000× is recommended to ensure the accuracy of low-frequency variants and CNV analysis.

[0100] 5. Data Analysis The obtained sequencing data were analyzed using the thalassemia high-throughput sequencing analysis system (the localized data analysis visualization and interactive system and methods disclosed in ZL202310154719.X) to perform variant analysis and generate interpretation reports.

[0101] 6. Precautions (1) All reagent operations should be performed in a laminar flow hood to prevent cross-contamination of nucleic acids. Strictly separate the clean area and contaminated area of ​​the experimental workbench to ensure that the actions of inserting and picking up pipette tips, adding samples, and discarding pipette tips are unidirectional.

[0102] (2) If crystals appear in the hybridization capture reagent (ES Hyb Mix, ES Wash Buffer II), it must be heated to 50°C to completely dissolve and mixed by inversion before use. If it is to be aliquoted for use / storage, the original tube / bottle must be heated until the crystals are completely dissolved before aliquoting. Do not aliquot directly.

[0103] (3) Streptavidin Beads II should be equilibrated at room temperature for at least 30 minutes before use and thoroughly mixed by vortexing.

[0104] (4) Changing the PCR tube during the elution process is a key step to ensure the hit rate and should not be omitted. If using 8-tube strips with separate caps, the caps should be replaced at the same time as the PCR tubes.

[0105] (5) The number of amplification cycles after capture should be strictly based on the recommended table according to the actual panel size and the number of hybridization libraries to avoid over-amplification and the generation of non-specific products.

[0106] (6) Before opening the PCR tube cap, centrifuge briefly to ensure that all liquid is placed at the bottom of the PCR tube to avoid cross-contamination.

[0107] (7) Disinfect the experimental area with a disinfectant solution containing 0.5% hypochlorous acid after the experiment.

[0108] 7. Appendix Magnetic bead concentration method (optional, as an alternative to vacuum concentration) When a vacuum concentrator is unavailable, magnetic bead concentration can be used for pre-hybridization library drying. (1) Add the mixed library (500 ng), 5 μL Human Cot DNA, and 2 μL NanoBlockers to 50 μL with Nuclease Free Water.

[0109] (2) Add 90 μL NadPrep® SP Beads (1.8 times the volume), mix well, and incubate at room temperature for 10 min.

[0110] (3) The supernatant was removed by magnetic rack adsorption, and the product was washed twice with 80% ethanol and dried until matte.

[0111] (4) Add 17 μL of hybridization reaction solution (13 μL of ES Hyb Mix + 4 μL of HGBP Panel) to resuspend the magnetic beads, incubate at room temperature for 5 min, transfer the supernatant to a new PCR tube using a magnetic rack, and continue the hybridization program.

[0112] Note: The magnetic bead concentration method requires additional purchase of reagents such as magnetic beads and Human CotDNA due to the increased reaction volume compared to the vacuum concentration method. Furthermore, the magnetic bead concentration method may result in slightly lower capture library yields due to variations in purification and recovery efficiency.

[0113] Example 2 According to the detection method in Example 2, the panel was validated using 100 known thalassemia genotypes of Jingliang Technology standard products (as shown in Table 11). The panel designed according to the design method in Example 1 had an accuracy of 100% in detecting heterozygous deletions of -SEA, -α3.7, and -α4.2, and could clearly distinguish between homozygous deletions and heterozygous deletions.

[0114] Table 11. Thalassemia detection results in 100 standard samples.

[0115] Example 3 Genetic testing was performed on 250 patients diagnosed with thalassemia according to the detection method in Example 2. The detection results of α-thalassemia with gene mutations in the 250 clinical samples are shown in Table 12, and the detection results of β-thalassemia with gene mutations are shown in Table 13.

[0116] Table 12. Detection of α-thalassemia in 250 clinical samples

[0117] Table 13. Detection of β-thalassemia in 250 clinical samples

[0118] Therefore, the detection rate for α-thalassemia samples was 100% for 83 cases of -SEA heterozygous deletion, 29 cases of -α3.7 heterozygous deletion, 1 case of -α3.7 homozygous deletion, 20 cases of -α4.2 heterozygous deletion, and 1 case of -α4.2 homozygous deletion. For β-thalassemia samples, the detection rate was also 100% for 1 case of SEA-HPFH heterozygous deletion, 34 cases of Codons 41 / 42 (-TTCT) heterozygous mutation, 28 cases of Codon 17 (A->T) heterozygous mutation, 22 cases of IVS-II-654 (C->T) heterozygous mutation, 17 cases of -28 (A->G) beta+ heterozygous mutation, 14 cases of CD 71 / 72 (+A) heterozygous mutation, 12 cases of Hb E heterozygous mutation, and 2 cases of IVS-I-1 (G->T) heterozygous mutation. Therefore, it can be seen that the present invention can achieve a 100% detection rate for the most common mutation in thalassemia (accounting for more than 95% of thalassemia patients).

[0119] Example 4 A panel for detecting multiple genetic disease genes is provided, which replaces the thalassemia detection portion of the NBGS Premium Panel v1.0 (Genetic Detection Kit for 282 Known Pathogenic Genes Related to 311 Clinically Significant and Operable Genetic Diseases) (Cat # 1001991 (96 rxn) / 1001992 (16 rxn)) developed by the applicant Nanodigmbio with the HGBP Panel v1.0 (Cat # 1001961 (96 rxn) / 1001962 (16 rxn)) obtained according to the design method in Example 1. This achieves more comprehensive target coverage for thalassemia while providing a panel for detecting multiple genetic disease genes.

[0120] From the above embodiments, it can be concluded that the present invention establishes a standardized, efficient, and clinically applicable gDNA targeted capture sequencing process, and is equipped with a localized bioinformatics analysis system to achieve closed-loop management from sample to report.

[0121] Although the above embodiments have provided a detailed description of the present invention, they are only some embodiments of the present invention, and not all embodiments. People can obtain other embodiments based on these embodiments without creative effort, and these embodiments all fall within the protection scope of the present invention.

Claims

1. A method for designing a targeted capture sequencing panel for thalassemia gene detection, characterized in that, Includes the following steps: S1: Construct a multi-level target database, which includes four layers of data sources as shown in S11 to S14; S11: Identify core target regions based on human hemoglobin-related genes and distal regulatory elements annotated by the GENCODE and ENCODE projects. S12: Systematically review the pathogenic variants of thalassemia reported in literature, including HbVar, ClinVar, LOVD, and others. Collect the types and coordinate information of confirmed pathogenic variants. The types of pathogenic variants include small fragment variants and structural variants. The small fragment variants include single nucleotide variants and insertions / deletions. The structural variants include large fragment deletions, large fragment duplications, and gene fusion events. S13: Integrate gnomAD, 1000 Genomes Project and ChinaMAP databases to screen for high heterozygous SNP sites with MAF>5% in the α-globin gene cluster and β-globin gene cluster and the flanking regions of the above two, as backbone markers for haplotype analysis; S14: Collect the precise breakpoint coordinates of thalassemia-related variants and construct a structural variant breakpoint database. The thalassemia-related variants include large fragment deletions, large fragment duplications, and gene fusion events. S2: Based on the multi-level target database constructed in S1, the steps of constructing a high-density SNP backbone, covering known structural variation breakpoints, and enriching polymorphic sites are performed to design a probe set covering the target region. The probe set covers the coding regions, regulatory regions, splicing sites, non-coding regulatory SNP sites, and known structural variation breakpoint regions of the α-globin and β-globin gene clusters.

2. The design method according to claim 1, characterized in that, The non-coding regulatory SNP sites are non-coding regulatory SNP sites obtained based on HaploReg and RegulomeDB annotations that affect the expression of α-globin gene clusters and β-globin gene clusters.

3. The design method according to claim 2, characterized in that, The non-coding modulating SNPs include rs6732518, rs6738440, rs9402685, rs10189857, rs7606173, rs11759553, rs6545816, rs10184550, rs35959442, rs1427407, rs28384513, rs4895440, rs7599488, rs6904897, rs 4895441, rs766432, rs9376090, rs9402686, rs11886868, rs66650371, rs9494142, rs4671393, rs7776054, rs1320963, rs7557939, rs9399137, rs6934903, rs6706648, rs9389268, and rs6929404.

4. The design method according to claim 1, characterized in that, The steps for constructing the high-density SNP backbone include: based on 1000 Genomes Project data of the Chinese population, screening out high heterozygous SNP sites with an average interval of less than 500 bp within the α-globin gene cluster and β-globin gene cluster to form an SNP tag system; the MAF of the high heterozygous SNP sites is between 0.25 and 0.

75.

5. The design method according to claim 4, characterized in that, The high-density SNP backbone is used for copy number variation analysis and linkage haplotype analysis. In the copy number variation analysis, the full-region dose spectrum is constructed by calculating the ratio of sequencing depth to reference depth for each SNP site, and at least one of the following two analyses is performed: (1) determining the precise breakpoint boundary of deletion variants; (2) determining the heterozygous / homozygous status of all variant sites. In the linked haplotype analysis, haplotype classification is performed using genotype information from SNP loci.

6. The design method according to claim 4, characterized in that, The high-density SNP backbone construction step also achieves step-by-step design optimization of the probe group in high GC region and repetitive sequence region through iterative masking algorithm; after the step-by-step design optimization, the coverage variation coefficient of the SNP backbone region is less than 0.

3.

7. The design method according to claim 1, characterized in that, The structural variation breakpoint database includes the precise breakpoint coordinates for -SEA, -α3.7, -α4.2, HKαα, Thai deletion, Filipino deletion, and HPFH deletion of the β-globin gene cluster.

8. The design method according to claim 1 or 7, characterized in that, The steps for covering known structural variation breakpoints include: designing probes that cover the classic breakpoint and a 2 kb range upstream and downstream of the breakpoint.

9. The design method according to claim 1, characterized in that, The probes are 100-140 nt in length; the probe set covers a 160-300 kb genomic region and contains 1000-2000 probes.

10. The design method according to claim 1, characterized in that, The design method also includes updating the targeted capture sequencing panel and supplementing probes when new thalassemia pathogenic variants or high-information SNPs are reported.

11. A targeted capture sequencing panel for thalassemia gene detection, characterized in that, Obtained by using the design method described in any one of claims 1 to 10.

12. A panel for detecting genes in hereditary diseases, characterized in that, This includes the targeted capture sequencing panel for thalassemia gene detection as described in claim 11 and a custom panel for gene detection of other genetic diseases.

13. The use of the targeted capture sequencing panel of claim 11 or the panel of claim 12 in the preparation of a product for thalassemia detection.

14. A kit for thalassemia gene detection, characterized in that, It includes the targeted capture sequencing panel and sequencing reagents as described in claim 11; the sequencing-related reagents include one or more of hybridization capture system buffers, sequencing platform adapters, and amplification primers.

15. A gene detection system for thalassemia, characterized in that, It includes a sample processing module, a library construction module, a hybridization capture module, a high-throughput sequencing module, and a results output module. The sample processing module is used to process the sample to be tested; the processing of the sample to be tested includes extracting genomic DNA from the sample to be tested; The library construction module is connected to the sample processing module and is used to construct a genomic library based on the genomic DNA. The hybridization capture module is connected to the library construction module and is used to enrich DNA fragments in the target region. The method for enriching target region DNA fragments includes: using the targeted capture sequencing panel of claim 11 to hybridize and capture the genomic DNA to obtain target region DNA fragments; The high-throughput sequencing module is connected to the hybridization capture module and is used to acquire high-throughput sequencing data of the sample to be tested; the acquisition steps include: performing high-throughput sequencing on the DNA fragment of the target region to obtain high-throughput sequencing data; The result output module is connected to most high-throughput sequencing modules to obtain the thalassemia gene detection results in the sample to be tested; the acquisition steps include: performing bioinformatics analysis on the high-throughput sequencing data to identify single nucleotide variants, insertions and deletions and structural variants, the structural variants including copy number variants, large fragment deletions / duplications and gene fusions, and outputting the variant site detection results.

16. A method for detecting thalassemia genes, characterized in that, Includes the following steps: 1) Extract genomic DNA from the sample to be tested; 2) Construct a genomic library based on the genomic DNA; 3) The genomic library is hybridized and captured using the targeted capture sequencing panel as described in claim 11 to obtain the target region DNA fragment; 4) Perform high-throughput sequencing on the DNA fragment in the target region to obtain high-throughput sequencing data; 5) Perform bioinformatics analysis on the high-throughput sequencing data to identify single nucleotide variants, insertions / deletions, and structural variants, including copy number variations, large fragment deletions / duplications, and gene fusions, and output the variant site detection results.

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