Method and system for detecting DNA methylation based on imprint control regions

Abstract

The embodiment of the present application relates to the field of apparent detection technology, and discloses a DNA methylation detection method based on imprint control region, comprising: determining imprint position information of each imprint control region in a set range; comparing obtained sequencing data to reference genome sequence to obtain genome sequence with sequencing segment position information; screening sequencing segments falling into corresponding imprint control region according to imprint position information of each imprint control region and genome sequence with sequencing segment position information, and counting the number of sequencing segments falling into each imprint control region; respectively calculating entries of high-methylation and low-methylation sequencing segments in all sequencing segments, and judging the overall methylation level of the imprint control region. The DNA methylation detection method based on imprint control region in the embodiment of the present application can accurately judge the methylation level of the imprint control region through accurate sequencing data comparison and position information screening, and improve the accuracy of the detection result.

Description

Technical Field

[0001] This invention relates to the field of epigenetic detection technology, specifically to a method and system for detecting DNA methylation based on imprinted control regions. Background Technology

[0002] Currently, the pipeline for small molecule nucleic acid drugs is developing rapidly. Especially with the significant commercial success of mRNA vaccines, more small molecule nucleic acid drugs are under development—including innovative drugs such as mRNA vaccines and mRNA tumor vaccines that can improve disease prevention and treatment. There are numerous small molecule nucleic acid drug candidates, and drug developers aim to shorten the development-to-commercialization cycle. However, existing evaluation technologies overlook the potential harm caused by the instability of next-generation small molecule nucleic acid drugs to the genome, DNA methylome, and imprinted control regions (ICRs). Therefore, new safety evaluation technologies are needed to address this shortcoming.

[0003] Current drug toxicology effect assessment and safety evaluation technologies are mainly for protein drugs. Protein drugs primarily target proteins or mRNA, so current technologies mainly assess the toxicological effects of drugs molecularly by detecting transcriptomic or gene expression indicators (i.e., proteomics and metabolomics); there are no methods for evaluating the toxicological effects and safety of drugs based on genomic and epigenetic indicators, as well as the methylation status of imprinted control regions (ICRs). Summary of the Invention

[0004] To address the aforementioned deficiencies, this invention discloses a method for detecting DNA methylation based on imprinted control regions, which can accurately determine the extent to which imprinted control regions are affected by drugs, providing more precise detection results.

[0005] The first aspect of this invention discloses a method for detecting DNA methylation based on imprinted control regions, comprising: Determine the imprint location information for each imprint control area within the set range; The obtained sequencing data is aligned to a reference genome sequence to obtain a genome sequence with metric segment location information; Based on the imprinting location information of each imprinting control region and the genome sequence with sequencing segment location information, sequencing segments falling into the corresponding imprinting control region are screened out, and the number of sequencing segments falling into each imprinting control region is counted. Count the entries of highly methylated and lowly methylated sequencing segments in all sequencing segments separately to determine the overall methylation level of the imprinted control region; The overall methylation level of each imprinted control region is matched with a set alignment strategy to obtain the corresponding matching results, and the extent to which the DNA methylation modification of the corresponding imprinted control region is affected by the drug is determined based on the matching results.

[0006] As an optional implementation, in the first aspect of the present invention, the detection method further includes: Determine the sub-region location information of each gene promoter region within the specified range; The obtained sequencing data is aligned to a reference genome sequence to obtain a genome sequence with metric segment location information; Based on the imprinting location information of each gene promoter region and the genome sequence with sequencing segment location information, sequencing segments falling into the corresponding gene promoter regions are screened out, and the number of sequencing segments falling into each gene promoter region is counted. Count the entries of highly methylated and lowly methylated sequencing segments in all sequencing segments separately to determine the overall methylation level of the gene promoter region; The overall methylation level of each gene promoter region is matched with a set alignment strategy to obtain the corresponding matching results, and the extent to which the DNA methylation modification of the corresponding gene promoter region is affected by the drug is determined based on the matching results.

[0007] As an optional implementation, in a first aspect of the present invention, the gene promoter region includes TP53, PIK3CA, KMT2C, ARID1A, KMT2D, LRPIB, PTEN, RB1, FAT4, KRAS, Akt, Bax, FKHR / FoxO.PI3K, BC12, INPP4B, LKB1, PTEN, TSC1 / TSC2, Ab1, Cdk-2, cdk-4, HPV-E7, p15, p16.p57, Rb, AliroraA, HPV-E6, Mdm2, ARF, ATMVATR, BRCA1, Chk1, Chk2, DNA-PK, FANCSHIPK2, NBS1, 053, WT1, MUTYH, BLM, RECQL4, WRN, MMR, B-Raf, Fos / Jun.ILK, RaS, RTK, NF1, NF2, VHL, FH, SDH, Myc, BMPR, smad2 / 3, smad4, TGFBR, MEN1, HYMAI, B-catenin, RAR, soX, Wntl, APC, Axin, a-catenin, E-cadherin, Wnt5A, GPC3.TAL1, MLL, HOXS, MITF, EVI1, BCL6, HPC1, HRPT2, GRB10, IGFBP1, IGFBP3, H19, IGF2.KCNQ1, KCNQ10T1, CDKN1, CMEG3, DLK1, RTL1, MEG8, MEG9, DIO3, MKRN3, MAGEL2, NDN.SNURF, SNRPN, UBE3A, ATP10C, GNAS, MEST Any gene promoter region or a combination of different gene promoter regions.

[0008] As an optional implementation, in a first aspect of the present invention, the step of matching the overall methylation level of each imprinted control region with a set alignment strategy to obtain a corresponding matching result, and determining the extent to which the DNA methylation modification of the corresponding imprinted control region is affected by the drug based on the matching result, includes: The grayscale information of each imprint control region is obtained, and the corresponding comparison benchmark threshold is determined based on the grayscale information of each imprint control region and the theoretical methylation information of each imprint control region. The overall methylation level of each imprint control region is matched with the comparison benchmark threshold to obtain the corresponding comparison results. The extent to which the drug affects DNA methylation modification in the corresponding imprinted control region is determined based on the comparison results of each imprinted control region.

[0009] As an optional implementation, in a first aspect of the present invention, after determining the extent to which the DNA methylation modification of the corresponding imprinting control region is affected by the drug based on the matching result, the method further includes: Identify the imprinted control regions affected by the drug, and determine the primary impact of the corresponding imprinted control regions on cellular tumors based on the imprinted control regions affected by the drug and the established imprint-tumor mapping relationship; The secondary impact of the corresponding imprinting control regions on cell development was determined by comparing the imprinting control regions affected by the drug with the imprinting-development mapping relationship. Information on the first and second impact results is displayed.

[0010] As an optional implementation, in the first aspect of the present invention, the imprinting control region includes any one of the imprinting control regions selected from PLAGL1, GRB10, H19 / IGF2 (IC1), KVDMR1 (IC2), DLk1, SNURF (IC), NESP-AS / GNAS-AS1, GNAS-XLDNMTI, MEST, ZNF331, PEG3, IGFIR, PEG1O, DIRAS3, NAPIL5, FAM5OB, IGF2R, TRAPPC9 (PEG13)INPP5F, RB1, MCTS2P / HM13, BLCAP / NNAT, and L3MBTL1, or any combination of the above imprinting genes and imprinting control regions.

[0011] As an optional implementation, in the first aspect of the present invention, the detection method further includes: The first and second raw sequencing data, after data quality control, were compared with a pre-constructed reference genome, and the compared data were merged to obtain the first and second merged sequencing data; wherein, the first raw sequencing data is the sequencing data corresponding to the pre-drug cell genome library, and the second raw sequencing data is the sequencing data corresponding to the post-drug cell genome library. The first and second merged sequencing data are subjected to TC reduction operations to obtain first reduced sequencing data and second reduced sequencing data; the first and second reduced sequencing data are then compared with a pre-constructed reference genome to determine the first and second position information of each base sequence obtained by sequencing on the chromosome. The first merged sequencing data is spliced ​​according to the first position information to obtain the first chromosome set, and the second merged sequencing data is spliced ​​according to the second position information to obtain the second chromosome set. Comparative analysis of the first and second chromosome sets was performed to determine the chromosome copy number variation before and after medication. The methylation levels of the first and second pooled sequencing data were calculated based on the established methylation measurement model. The methylation difference value is determined based on the methylation levels corresponding to the first and second merged sequencing data. The obtained methylation difference value and chromosome copy number variation are then matched with the corresponding set standard logic. If the match is consistent, it is determined that the corresponding drug has a small impact on the epigenome; if the match is inconsistent, it is determined that the corresponding drug has a large impact on the epigenome.

[0012] A second aspect of this invention discloses a detection system for DNA methylation based on imprinting control regions, comprising: First position determination module: used to determine the position information of each mark control area within a set range; The second position determination module is used to align the obtained sequencing data to a reference genome sequence to obtain a genome sequence with metric segment position information. Statistics module: Used to filter sequencing segments that fall into the corresponding imprinted control regions based on the imprinted location information of each imprinted control region and the genome sequence with sequencing segment location information, and to count the number of sequencing segments that fall into each imprinted control region. Methylation calculation module: used to calculate the entries of highly methylated and lowly methylated sequencing segments in all sequencing segments separately, and determine the overall methylation level of the corresponding imprinted control regions; Matching module: Used to match the overall methylation level of each imprinted control region with the set matching strategy to obtain the corresponding matching results, and to determine the extent to which the DNA methylation modification of the corresponding imprinted control region is affected by the drug based on the matching results.

[0013] A third aspect of the present invention discloses an electronic device, comprising: a memory storing executable program code; a processor coupled to the memory; the processor calling the executable program code stored in the memory to execute the DNA methylation detection method based on imprinting control regions disclosed in the first aspect of the present invention.

[0014] A fourth aspect of the present invention discloses a computer-readable storage medium storing a computer program, wherein the computer program causes a computer to execute the DNA methylation detection method based on imprinting control regions disclosed in the first aspect of the present invention.

[0015] Compared with the prior art, the embodiments of the present invention have the following beneficial effects: The DNA methylation detection method based on imprinted control regions in this invention can accurately determine the methylation level of imprinted control regions through precise sequencing data alignment and location information screening, thus improving the accuracy of detection results. Statistical analysis of high-methylated and low-methylated sequencing segments enables quantitative analysis of the methylation level of imprinted control regions, contributing to a deeper understanding of the relationship between methylation modification and disease. Attached Figure Description

[0016] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0017] Figure 1 This is a schematic flowchart of the DNA methylation detection method based on imprinting control regions disclosed in an embodiment of the present invention; Figure 2 This is a schematic flowchart of the method for detecting DNA methylation in the gene promoter region disclosed in an embodiment of the present invention; Figure 3 This is a schematic diagram of the structure of a DNA methylation detection system based on imprinting control regions provided in an embodiment of the present invention; Figure 4 This is a schematic diagram of the structure of an electronic device provided in an embodiment of the present invention. Detailed Implementation

[0018] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0019] It should be noted that the terms "first," "second," "third," "fourth," etc., in the specification and claims of this invention are used to distinguish different objects, not to describe a specific order. The terms "comprising" and "having," and any variations thereof, in the embodiments of this invention are intended to cover non-exclusive inclusion. Exemplarily, a process, method, system, product, or device that includes a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to these processes, methods, products, or devices.

[0020] Existing drug toxicology effect assessment and safety evaluation technologies are mainly for protein drugs. Protein drugs primarily target proteins or mRNA; therefore, current technologies mainly assess drug toxicology effects molecularly by detecting transcriptomic or gene expression indicators (i.e., proteomics and metabolomics). There is no method for evaluating drug toxicology effects and safety based on genomic and epigenetic indicators, as well as the methylation status of imprinting control regions (ICRs). Therefore, this invention discloses a method, system, electronic device, and storage medium for detecting DNA methylation based on imprinting control regions. Through precise sequencing data alignment and location information screening, it can accurately determine the methylation level of imprinting control regions, improving the accuracy of detection results. Statistical analysis of high-methylated and low-methylated sequencing segments enables quantitative analysis of the methylation level of imprinting control regions, contributing to a deeper understanding of the relationship between methylation modification and disease.

[0021] Example 1 Please see Figure 1 , Figure 1 This is a flowchart illustrating the DNA methylation detection method based on imprinting control regions disclosed in this invention. The execution entity of the method described in this embodiment is an execution entity composed of software and / or hardware. This execution entity can receive relevant information via wired or / or wireless means and can send certain instructions. It may also have certain processing and storage functions. This execution entity can control multiple devices, such as remote physical servers or cloud servers and related software, or local hosts or servers and related software that perform related operations on devices located in a certain location. In some scenarios, it can also control multiple storage devices, which may be placed in the same location as the device or in different locations. Figure 1 As shown, the method for detecting DNA methylation based on imprinted control regions includes the following steps: S101: Determine the imprint location information of each imprint control area within the set range; S102: Align the obtained sequencing data to the reference genome sequence to obtain a genome sequence with metric segment location information; S103: Based on the imprinting location information of each imprinting control region and the genome sequence with sequencing segment location information, the sequencing segments falling into the corresponding imprinting control region are screened out, and the number of sequencing segments falling into each imprinting control region is counted. S104: Calculate the entries of highly methylated and lowly methylated sequencing segments in all sequencing segments respectively, and determine the overall methylation level of the imprinted control region; S105: Match the overall methylation level of each imprinted control region with the set alignment strategy to obtain the corresponding matching results, and determine the extent to which the DNA methylation modification of the corresponding imprinted control region is affected by the drug based on the matching results.

[0022] By determining the imprinting location information of each imprinting control region within a defined range, this method can precisely locate the DNA region to be analyzed. This helps reduce interference from non-target regions and improves detection accuracy. Aligning sequencing data to a reference genome sequence yields a genome sequence with metric segment location information. This step ensures comprehensive detection because it covers sequencing data from the entire target region. By selecting sequencing segments that fall into the corresponding imprinting control regions and counting their numbers, this method can quantify the DNA methylation status of each imprinting control region. This helps researchers understand the differences in methylation levels across different regions. By separately counting the entries of highly methylated and low-methylated sequencing segments, the overall methylation level of the imprinting control regions can be determined. This provides researchers with important information about the DNA methylation status. Matching the overall methylation level of each imprinting control region with a defined alignment strategy determines the extent to which DNA methylation modifications are affected by drugs. This step provides an important reference for drug development and efficacy evaluation, helping researchers understand the mechanisms by which drugs affect DNA methylation. Since DNA methylation plays a crucial role in many diseases, this method has potential applications in disease diagnosis, treatment, and prevention. By understanding changes in DNA methylation, researchers can better comprehend the pathogenesis of diseases, providing new ideas and methods for clinical treatment. This DNA methylation detection method based on imprinted control regions demonstrates excellent technical performance in terms of accuracy, comprehensiveness, quantitative analysis, methylation level assessment, drug impact evaluation, and clinical application.

[0023] Because mRNA and similar drugs have advantages such as shorter R&D / production cycles, lower costs, longer-lasting efficacy, and wider application areas, the development pipeline of small molecule nucleic acid drugs is developing rapidly. Especially with the successful commercialization of COVID-19 mRNA vaccines, more small molecule nucleic acid drugs are under development—including innovative drugs such as mRNA vaccines and mRNA tumor vaccines that can improve disease prevention and treatment. In summary, the next decade will see a large number of small molecule nucleic acid drug candidates, and drug developers hope to shorten the R&D-to-commercialization cycle. However, existing evaluation technologies overlook the potential harm caused by the instability of next-generation small molecule nucleic acid drugs to the genome, DNA methylome, and imprinted control regions (ICRs). Therefore, new safety evaluation technologies are needed to address this shortcoming.

[0024] More preferably, the detection method further includes: S106: Determine the sub-region location information of each gene promoter region within the specified range; S107: Align the obtained sequencing data to the reference genome sequence to obtain a genome sequence with metric segment location information; S108: Based on the imprinting location information of each gene promoter region and the genome sequence with sequencing segment location information, the sequencing segments falling into the corresponding gene promoter regions are screened out, and the number of sequencing segments falling into each gene promoter region is counted. S109: Calculate the entries of highly methylated and lowly methylated sequencing segments in all sequencing segments respectively, and determine the overall methylation level of the gene promoter region; S1010: Match the overall methylation level of each gene promoter region with the set alignment strategy to obtain the corresponding matching results, and determine the extent to which the DNA methylation modification of the corresponding gene promoter region is affected by the drug based on the matching results.

[0025] By identifying the subregional locations of individual gene promoter regions, this method can precisely analyze the DNA methylation status of gene transcription initiation regions. Gene promoter regions are crucial for transcriptional regulation, and their methylation status significantly impacts gene expression. The methylation level of gene promoter regions is typically closely correlated with gene expression levels. By analyzing the methylation status of these regions, researchers can gain a deeper understanding of the mechanisms of gene transcriptional regulation, thereby revealing the root causes of gene expression changes. By matching the overall methylation level of gene promoter regions with a predefined alignment strategy, the impact of drugs on the methylation status of gene promoter regions can be assessed. This helps researchers understand how drugs regulate gene expression by influencing DNA methylation, thus revealing the mechanisms of drug action. The methylation status of gene promoter regions plays a vital role in the occurrence and development of various diseases. Therefore, this method has broad application prospects in disease diagnosis, treatment, and prevention. By analyzing the methylation status of gene promoter regions, researchers can provide new strategies and methods for early disease diagnosis, personalized treatment, and drug efficacy evaluation. Combining the methylation analysis of imprinted control regions and gene promoter regions provides researchers with a comprehensive perspective to assess the function and role of DNA methylation in organisms. This helps to reveal the complexity and diversity of DNA methylation in biological processes.

[0026] Imprinted gene control region index detection: The changes in methylation levels of the 20 most thoroughly studied imprinted control regions (ICRs) represent the changes in methylation in specific regions under the influence of drugs. First, the locations of 20 imprinted control regions are determined in the program. Then, the number of reads falling into each imprinted control region is calculated, and the number of hypermethylated and hypomethylated reads among all reads is counted to determine the overall methylation level of the imprinted control region. Previous studies have found that the theoretical methylation level of the ICR in the imprinted control region of normal human cells is 50%. Based on research experience, we set the gray zone (acceptable measurement error) of normal imprinted control regions to ±30%. Therefore, the final determination interval for drug-induced high-risk variants in ICR methylation is set as "ICR methylation level <20%" or "ICR methylation level >80%". By comparing the differences in hypermethylation and hypomethylation in the imprinted control regions before and after drug administration according to this standard, the extent to which the DNA methylation modification of the imprinted gene region is affected by the drug can be determined. Based on the relationship between the ICR of each affected imprinted control region and tumors and development (Appendix: Notes on the relationship between ICR and tumors), the potential impact of the drug on tumors and developmental abnormalities of cells can be determined.

[0027] More preferably, the gene promoter region includes TP53, PIK3CA, KMT2C, ARID1A, KMT2D, LRPIB, PTEN, RB1, FAT4, KRAS, Akt, Bax, FKHR / FoxO.PI3K, BC12, INPP4B, LKB1, PTEN, TSC1 / TSC2, Ab1, Cdk-2, cdk-4, HPV-E7, p15, p16.p57, Rb, AliroraA, HPV-E6, Mdm2, ARF, ATMVATR, BRCA1, Chk1, Chk2, DNA-PK, FANCSHIPK2, NBS1, 053, WT1, MUTYH, BLM, RECQL4, WRN, MMR, B-Raf, Fos / Jun.ILK, RaS, RTK, NF1, NF2, VHL, FH, SDH, Myc, BMPR, smad2 / 3, smad4, TGFBR, MEN1, HYMAI, B-catenin, RAR, soX, Wntl, APC, Axin, a-catenin, E-cadherin, Wnt5A, GPC3.TAL1, MLL, HOXS, MITF, EVI1, BCL6, HPC1, HRPT2, GRB10, IGFBP1, IGFBP3, H19, IGF2.KCNQ1, KCNQ10T1, CDKN1, CMEG3, DLK1, RTL1, MEG8, MEG9, DIO3, MKRN3, MAGEL2, NDN.SNURF, SNRPN, UBE3A, ATP10C, GNAS, MEST Any gene promoter region or a combination of different gene promoter regions.

[0028] The genes listed above, such as TP53 and PIK3CA, play important roles in many cancers and other diseases. Analyzing the methylation status of the promoter regions of these genes can reveal their regulatory mechanisms in diseases, providing new insights for disease diagnosis, treatment, and prevention.

[0029] More preferably, the step of matching the overall methylation level of each imprinted control region with a set alignment strategy to obtain corresponding matching results, and determining the extent to which the DNA methylation modification of the corresponding imprinted control region is affected by the drug based on the matching results, includes: The grayscale information of each imprint control region is obtained, and the corresponding comparison benchmark threshold is determined based on the grayscale information of each imprint control region and the theoretical methylation information of each imprint control region. The overall methylation level of each imprint control region is matched with the comparison benchmark threshold to obtain the corresponding comparison results. The extent to which the drug affects DNA methylation modification in the corresponding imprinted control region is determined based on the comparison results of each imprinted control region.

[0030] The present invention addresses this issue by defining a threshold range for determining the risk of drug-induced ICR methylation mutations. Since the theoretical ICR methylation level in the imprinting control region of normal human cells is 50%, a gray zone (acceptable measurement error) of ±30% is defined. Therefore, when the ICR methylation level is below 20% or above 80%, a higher risk of methylation mutations is considered present.

[0031] This invention assesses the impact of drug administration on cells by analyzing changes in the methylation levels of imprinted gene control regions (ICRs) in two different cell groups before and after drug administration. The protected object comprises 20 imprinted control regions, and the changes in methylation levels in these regions before and after drug administration represent the changes in methylation in specific regions affected by the drug. First, the locations of the 20 imprinted control regions are determined in the program. Then, the number of reads falling into each imprinted control region is calculated, and the number of highly methylated and low-methylated reads among all reads is counted to determine the overall methylation level of the imprinted control region. This invention protects the methylation modification status of reads in imprinted gene regions previously obtained through analysis and comparison in normal cells. The average methylation level of imprinted control regions in normal cells should be between 20% and 80%. Therefore, the threshold for determining whether a drug causes abnormal methylation is (<20% or >80%): by comparing the proportion of hypermethylated and hypomethylated reads in the imprinted control region before and after drug administration based on this standard, the extent to which the epigenetic modification of the imprinted gene region is affected by the drug can be determined, and the potential impact on tumor and developmental abnormalities of cells can be determined based on the relationship between the imprinted control region and tumors and development.

[0032] This invention protects a method that progressively assesses the potential impact of a drug on human cells by analyzing changes in chromosomal aneuploidy, whole-genome DNA methylation values, and overall changes in imprinted gene control regions (ICRs) of two different groups of cells before and after drug administration.

[0033] More preferably, after determining the extent to which the DNA methylation modification of the corresponding imprinting control region is affected by the drug based on the matching result, the method further includes: Identify the imprinted control regions affected by the drug, and determine the primary impact of the corresponding imprinted control regions on cellular tumors based on the imprinted control regions affected by the drug and the established imprint-tumor mapping relationship; The secondary impact of the corresponding imprinting control regions on cell development was determined by comparing the imprinting control regions affected by the drug with the imprinting-development mapping relationship. Information on the first and second impact results is displayed.

[0034] Imprinted genes are a class of genes whose expression is influenced by parental origin during an organism's development, differing between paternal and maternal chromosomes. Imprinted genes play crucial roles in growth and development, significantly impacting processes such as cell proliferation, differentiation, and apoptosis. Abnormal expression of imprinted genes, such as loss of imprinting (LOI), may lead to tumorigenesis. This aberrant imprinting expression has been proven to be associated with increased tumor risk. For example, in mouse models, a widespread lack of imprinted genes is associated with increased tumor incidence. In humans, physical events and general imprinting disorders may lead to aberrant imprinting and increased tumor risk. This aberrant imprinting expression may be involved in the regulatory mechanisms of tumor cell growth, proliferation, and metastasis. Studies have shown that abnormal expression of certain imprinted genes in tumors may be related to tumor occurrence, development, and metastasis. Furthermore, some drugs or treatments may affect the therapeutic effects of tumors by regulating the expression of imprinted genes.

[0035] By identifying the relationship between ICRs and tumorigenesis and development, we aim to understand the role of each ICR in cell development and tumorigenesis. Particular attention is paid to ICRs closely associated with tumor suppression or key developmental stages, as changes in methylation in these regions can significantly impact cellular tumorigenesis and developmental abnormalities.

[0036] Tumor suppressor genes: If the affected ICR contains tumor suppressor genes and the methylation level is elevated (e.g., from normal levels to >80%), it may lead to the inactivation of tumor suppressor genes, increasing the risk of cell carcinogenesis. Proto-oncogenes: Conversely, if the methylation level of proto-oncogenes in the ICR is reduced (e.g., from normal levels to <20%), it may promote the expression of proto-oncogenes, similarly increasing the risk of cell carcinogenesis.

[0037] Key Developmental Genes: If the affected ICRs contain genes associated with critical stages of cell development, and their methylation levels change abnormally, it may affect the normal expression of these genes, leading to abnormal cell development. Imprinted Genes: Imprinted genes play an important role in cell development; changes in their methylation status may lead to imprint loss or abnormal expression, further affecting cell development. Degree of Impact: The potential impact of the drug on cell tumors and development is comprehensively assessed based on the number of affected ICRs, the degree of change in methylation levels, and the importance of its relationship to tumor / development. Risk Classification: Potential impacts can be classified into different categories such as high-risk, medium-risk, and low-risk to better guide drug development and clinical application. Individual Differences: Different individuals may respond differently to drugs; therefore, the impact of individual differences on methylation levels needs to be considered in practical applications. Multifactorial Effects: Cell tumors and developmental abnormalities may be influenced by multiple factors, including genetic and environmental factors; therefore, multiple factors need to be considered comprehensively when assessing the impact of drugs.

[0038] More preferably, the imprinting control region includes any one of the imprinting control regions of PLAGL1, GRB10, H19 / IGF2 (IC1), KVDMR1 (IC2), DLk1, SNURF (IC), NESP-AS / GNAS-AS1, GNAS-XLDNMTI, MEST, ZNF331, PEG3, IGFIR, PEG1O, DIRAS3, NAPIL5, FAM5OB, IGF2R, TRAPPC9 (PEG13)INPP5F, RB1, MCTS2P / HM13, BLCAP / NNAT, and L3MBTL1, or any combination of imprinting genes and imprinting control regions.

[0039] More preferably, the detection method further includes: The first and second raw sequencing data, after data quality control, were compared with a pre-constructed reference genome, and the compared data were merged to obtain the first and second merged sequencing data; wherein, the first raw sequencing data is the sequencing data corresponding to the pre-drug cell genome library, and the second raw sequencing data is the sequencing data corresponding to the post-drug cell genome library. The first and second merged sequencing data are subjected to TC reduction operations to obtain first reduced sequencing data and second reduced sequencing data; the first and second reduced sequencing data are then compared with a pre-constructed reference genome to determine the first and second position information of each base sequence obtained by sequencing on the chromosome. The first merged sequencing data is spliced ​​according to the first position information to obtain the first chromosome set, and the second merged sequencing data is spliced ​​according to the second position information to obtain the second chromosome set. Comparative analysis of the first and second chromosome sets was performed to determine the chromosome copy number variation before and after medication. The methylation levels of the first and second pooled sequencing data were calculated based on the established methylation measurement model. The methylation difference value is determined based on the methylation levels corresponding to the first and second merged sequencing data. The obtained methylation difference value and chromosome copy number variation are then matched with the corresponding set standard logic. If the match is consistent, it is determined that the corresponding drug has a small impact on the epigenome; if the match is inconsistent, it is determined that the corresponding drug has a large impact on the epigenome.

[0040] This invention discloses a detection and analysis method for evaluating the epigenetic safety of drugs. It can simultaneously obtain epigenomic indicators such as chromosomal copy number variation (CNV), whole-genome DNA methylation information accurate to single bases, and the 20 currently known imprinted gene control regions (ICRs) by testing ≥1 cell in a single test. Based on the epigenomic indicator data of normal cells before and after drug administration accumulated by this invention, preliminary standards for judging whether significant changes have occurred in the cell epigenomics have been established, and a detection and analysis method for evaluating the epigenomic safety of drugs (DEST) has been established, which helps to more comprehensively evaluate and predict the epigenomic toxicity of biomolecular drugs to human cells. Furthermore, this invention can obtain three different sets of epigenomic indicators—CNV, methylation level, and ICR—in a single test, thus greatly reducing the average cost per indicator.

[0041] The detection and analysis method for evaluating the epigenetic safety of drugs provided by this invention can simultaneously obtain epigenomic indicators such as chromosomal copy number variation (CNV), whole-genome DNA methylation information accurate to single bases, and multiple imprinted gene control regions (ICRs) from ≥1 cell in a single test. Based on the epigenomic indicator data of normal cells before and after drug administration accumulated by the protocol, a preliminary standard for judging whether significant changes have occurred in the cell epigenomics has been formed. Based on the parameters obtained above, a detection and analysis method for evaluating the epigenomic safety of drugs (DEST) has been established, which helps to more comprehensively evaluate and predict the epigenomic toxicity of biomolecular drugs to human cells. In addition, this invention can obtain three different sets of indicators—CNV, methylation level, and ICR—in a single test, thus greatly reducing the average cost per indicator.

[0042] Detailed implementation process: First, prepare the test cells for the drug: Select human bone marrow stem cells A as the test cells - culture for 1 day to obtain A1 cells → divide the A1 cells into two parts → continue to culture one part of A1 cells normally for 1 day to obtain 1000 A2 cells → treat the other part of A1 cells with the drug and culture for 1 day to obtain 1000 B2 cells → collect the 1000 normally cultured A2 cells → collect the 1000 B2 cells cultured for 1 day after drug administration.

[0043] Second, genomic DNA methylation library construction was performed on the cellular DNA before and after drug administration: 1000 cells from groups A2 and B2 before and after drug administration were taken respectively, placed in PCR tubes, and lysed for 2 hours with 5 μL of cell lysis buffer. DNA extraction was not required; the whole-genome DNA methylation library construction was performed directly according to the following procedure: 1) DNA fragmentation: Place the PCR sample tube on an ultrasonic disruptor to break down the DNA. Set the fragmentation parameters to 20 seconds of sonication followed by 20 seconds of pause, for a total fragmentation time of 8 minutes, with a 40% amplitude, to break the DNA into fragments of approximately 300-500 bp.

[0044] 2) End-repair with A: Add end-repair with A enzyme and end-repair with A buffer to the fragmented PCR tube, mix well, and incubate in a PCR instrument. PCR program settings: 20℃, 30 min; 65℃, 30 min; 4℃, ...

[0045] 3) Adding adapters: Add methylation adapters, ligase mixture, and reaction enhancer to the end-repair A-addition product, mix well, and incubate in a PCR instrument. PCR program settings: 20℃, 15min: 4℃, ...

[0046] 4) Purification of ligation products: Add magnetic beads to the ligation products, mix well, and let stand for 5 min; place the PCR tube in a magnetic rack, let stand for 2 min, and discard the liquid; add freshly prepared 80% ethanol to the tube, let stand for 30 s, and discard the liquid; add freshly prepared 80% ethanol to the tube, let stand for 30 s, discard the liquid, and then open the cap to air dry for 5 min; add elution buffer to the tube, mix well, and let stand for 5 min; place the PCR tube in a magnetic rack, let stand for 2 min, and transfer the liquid to a new PCR tube.

[0047] 5) TET2 oxidation: Add TET2 enzyme, reaction buffer, reaction enhancement solution and reaction supplement to the purified library on ice, vortex mix, add iron solution, vortex mix again and incubate at 37°C for 1 hour in a PCR instrument.

[0048] 6) Oxidation termination: Immediately after the reaction is complete, remove the PCR tube and place it on ice. Add the stop solution, mix, and then place it in the PCR instrument for incubation at 37°C for 30 minutes.

[0049] 7) Purification of oxidation products: Add magnetic beads to the oxidation products, mix well and let stand for 5 min; place the PCR tube in a magnetic rack, let stand for 2 min, and discard the liquid; add freshly prepared 80% ethanol to the tube, let stand for 30 s, and discard the liquid; add freshly prepared 80% ethanol to the tube, let stand for 30 s, discard the liquid and open the cap to air dry for 5 min; add elution buffer to the tube, mix well and let stand for 5 min; place the PCR tube in a magnetic rack, let stand for 2 min, and transfer the liquid to a new PCR tube.

[0050] 8) DNA denaturation: Add 0.1N NaOH to the PCR tube, then place the sample in a PCR instrument preheated to 50℃ and incubate for 10 minutes. After incubation, immediately place it on ice.

[0051] 9) Deamination reaction: Add deaminase, deamination buffer and reaction supplement to the PCR tube on ice, vortex to mix, and then incubate at 37°C for 3 hours in a PCR instrument.

[0052] 10) Purification of deamination products: Add magnetic beads to the deamination products, mix well and let stand for 5 min; place the PCR tube in a magnetic rack, let stand for 2 min, and discard the liquid; add freshly prepared 80% ethanol to the tube, let stand for 30 s, and discard the liquid; add freshly prepared 80% ethanol to the tube, let stand for 30 s, discard the liquid and open the cap to air dry for 5 min; add elution buffer to the tube, mix well and let stand for 5 min; place the PCR tube in a magnetic rack, let stand for 2 min, and transfer the liquid to a new PCR tube.

[0053] 11) PCR amplification: Add the amplification primer and PCR enzyme mixture to the PCR tube, mix well, and then place it in the PCR instrument for amplification. The PCR program is set as follows: 98°C, 45s; (98°C, 15s; 65°C, 30s; 72°C, 30s) x 15; 72°C, 1min; 4°C, ...

[0054] 12) Purification of amplification products: Add magnetic beads to the amplification products, mix well and let stand for 5 min; place the PCR tube in a magnetic rack, let stand for 2 min, and discard the liquid; add freshly prepared 80% ethanol to the tube, let stand for 30 s, and discard the liquid; add freshly prepared 80% ethanol to the tube, let stand for 30 s, discard the liquid and open the cap to air dry for 5 min; add elution buffer to the tube, mix well and let stand for 5 min; place the PCR tube in a magnetic rack, let stand for 2 min, and transfer the liquid to a new centrifuge tube.

[0055] 13) Library quality control: The library was quantified using a qPCR instrument, and the fragment size of the library was determined using an Agilent 2100. 14) Library sequencing: After the library passes quality control, the NGS sequencing platform is used to sequence the library.

[0056] The sequencing data was analyzed according to the following workflow: 1) Data quality control was performed on the raw sequencing data, removing adapter sequences and low-quality bases; 2) Genome alignment was then performed, and the aligned data were merged, removing PCR repetitive sequences; 3) Chromosomal copy number variation (CNV) index comparison analysis: The sequencing data of cells before and after drug administration were T-C reduced, and then compared and matched with the genome to determine the exact location of each base sequence obtained from sequencing on the chromosome. These sequences were then assembled into chromosomes, and the number of chromosomes in cells before and after drug administration was compared. The number of chromosome fragments in cells before and after drug administration was compared and analyzed, with a sliding window range of 1M each time to check whether the number of chromosome fragments had changed after drug administration. 4) Comparative analysis of methylation indicators: Because the unmethylated cytosine (C) was converted to T during library construction, when the obtained sequencing sequence is compared with the reference genome, it can be analyzed that if the standard reference genome is cytosine (C) at position A of the genome, and the base we measured is also cytosine (C), then the cytosine (C) of the cell at that position is methylated; if the standard reference genome is cytosine (C) at position B of the genome, and the base we measured is thymine (T), then the cytosine (C) of the cell at that position is not methylated.

[0057] The DNA methylation detection method based on imprinted control regions in this invention can accurately determine the methylation level of imprinted control regions through precise sequencing data alignment and location information screening, thus improving the accuracy of detection results. Statistical analysis of high-methylated and low-methylated sequencing segments enables quantitative analysis of the methylation level of imprinted control regions, contributing to a deeper understanding of the relationship between methylation modification and disease.

[0058] Example 2 Please see Figure 4 , Figure 4 This is a schematic diagram of the DNA methylation detection system based on imprinting control regions disclosed in an embodiment of the present invention. Figure 4 As shown, the DNA methylation detection system based on imprinted control regions may include: First position determination module 21: used to determine the imprint position information of each imprint control area within a set range; Second position determination module 22: used to align the obtained sequencing data to a reference genome sequence to obtain a genome sequence with metric segment position information; Statistical module 23: Used to screen sequencing segments that fall into the corresponding imprinted control regions based on the imprinted location information of each imprinted control region and the genome sequence with sequencing segment location information, and to count the number of sequencing segments that fall into each imprinted control region. Methylation calculation module 24: used to calculate the entries of highly methylated and lowly methylated sequencing segments in all sequencing segments respectively, and determine the overall methylation level of the corresponding imprinted control regions; Matching module 25: is used to match the overall methylation level of each imprinted control region with a set matching strategy to obtain the corresponding matching results, and to determine the extent to which the DNA methylation modification of the corresponding imprinted control region is affected by the drug based on the matching results.

[0059] The DNA methylation detection method based on imprinted control regions in this invention can accurately determine the methylation level of imprinted control regions through precise sequencing data alignment and location information screening, thus improving the accuracy of detection results. Statistical analysis of high-methylated and low-methylated sequencing segments enables quantitative analysis of the methylation level of imprinted control regions, contributing to a deeper understanding of the relationship between methylation modification and disease.

[0060] Example 3 Please see Figure 4 , Figure 4This is a schematic diagram of the structure of an electronic device disclosed in an embodiment of the present invention. The electronic device can be a computer, a server, etc. Of course, in certain cases, it can also be a mobile phone, tablet computer, monitoring terminal, or other smart device, as well as an image acquisition device with processing capabilities. Figure 4 As shown, the electronic device may include: Memory 510 storing executable program code; Processor 520 coupled to memory 510; The processor 520 calls the executable program code stored in the memory 510 to execute some or all of the steps in the DNA methylation detection method based on the imprinting control region in Embodiment 1.

[0061] This invention discloses a computer-readable storage medium storing a computer program that causes a computer to perform some or all of the steps in the DNA methylation detection method based on imprinting control regions described in Embodiment 1.

[0062] This invention also discloses a computer program product, wherein when the computer program product is run on a computer, the computer performs some or all of the steps in the DNA methylation detection method based on imprinting control regions in Embodiment 1.

[0063] This invention also discloses an application publishing platform, which is used to publish computer program products. When the computer program products are run on a computer, the computer performs some or all of the steps in the DNA methylation detection method based on imprinted control regions in Embodiment 1.

[0064] In various embodiments of the present invention, it should be understood that the sequence number of each process does not necessarily imply the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present invention.

[0065] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; they can be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0066] Furthermore, the functional units in the various embodiments of the present invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0067] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-accessible memory. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a memory and includes several requests to cause a computer device (which can be a personal computer, server, or network device, specifically a processor in the computer device) to execute some or all of the steps of the methods described in the various embodiments of the present invention.

[0068] In the embodiments provided by this invention, it should be understood that "B corresponding to A" means that B is associated with A, and B can be determined based on A. However, it should also be understood that determining B based on A does not mean determining B solely based on A; B can also be determined based on A and / or other information.

[0069] Those skilled in the art will understand that some or all of the steps in the various methods of the embodiments described can be implemented by a program instructing related hardware. This program can be stored in a computer-readable storage medium, including read-only memory (ROM), random access memory (RAM), programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), one-time programmable read-only memory (OTPROM), electrically-Erasable Programmable Read-Only Memory (EEPROM), compact disc read-only memory (CD-ROM) or other optical disc storage, disk storage, magnetic tape storage, or any other computer-readable medium capable of carrying or storing data.

[0070] The foregoing has provided a detailed description of the DNA methylation detection method, system, electronic device, and storage medium based on imprinted control regions disclosed in the embodiments of the present invention. Specific examples have been used to illustrate the principles and implementation methods of the present invention. The descriptions of the above embodiments are only for the purpose of helping to understand the method and core ideas of the present invention. At the same time, for those skilled in the art, there will be changes in specific implementation methods and application scope based on the ideas of the present invention. Therefore, the content of this specification should not be construed as a limitation of the present invention.

Claims

1. A method for detecting DNA methylation based on imprinted control regions, characterized in that, include: Determine the imprint location information for each imprint control area within the set range; The obtained sequencing data is aligned to a reference genome sequence to obtain a genome sequence with metric segment location information; Based on the imprinting location information of each imprinting control region and the genome sequence with sequencing segment location information, sequencing segments falling into the corresponding imprinting control region are screened out, and the number of sequencing segments falling into each imprinting control region is counted. Count the entries of highly methylated and lowly methylated sequencing segments in all sequencing segments separately to determine the overall methylation level of the imprinted control region; The overall methylation level of each imprinted control region is matched with a set alignment strategy to obtain corresponding matching results, and the extent to which the DNA methylation modification of the corresponding imprinted control region is affected by the drug is determined based on the matching results; the process of matching the overall methylation level of each imprinted control region with a set alignment strategy to obtain corresponding matching results, and determining the extent to which the DNA methylation modification of the corresponding imprinted control region is affected by the drug based on the matching results includes: The grayscale information of each imprint control region is obtained, and the corresponding comparison benchmark threshold is determined based on the grayscale information of each imprint control region and the theoretical methylation information of each imprint control region. The overall methylation level of each imprint control region is matched with the comparison benchmark threshold to obtain the corresponding comparison results. The extent to which the drug affects DNA methylation modification in the corresponding imprinted control region is determined based on the comparison results of each imprinted control region.

2. The method for detecting DNA methylation based on imprinted control regions as described in claim 1, characterized in that, The detection method further includes: Determine the sub-region location information of each gene promoter region within the specified range; The obtained sequencing data is aligned to a reference genome sequence to obtain a genome sequence with metric segment location information; Based on the imprinting location information of each gene promoter region and the genome sequence with sequencing segment location information, sequencing segments falling into the corresponding gene promoter regions are screened out, and the number of sequencing segments falling into each gene promoter region is counted. Count the entries of highly methylated and lowly methylated sequencing segments in all sequencing segments separately to determine the overall methylation level of the gene promoter region; The overall methylation level of each gene promoter region is matched with a set alignment strategy to obtain the corresponding matching results, and the extent to which the DNA methylation modification of the corresponding gene promoter region is affected by the drug is determined based on the matching results.

3. The method for detecting DNA methylation based on imprinted control regions as described in claim 1, characterized in that, The gene promoter region includes TP53, PIK3CA, KMT2C, ARID1A, KMT2D, LRPIB, PTEN, RB1, FAT4, KRAS, Akt, Bax, FKHR / FoxO.PI3K, BC12, INPP4B, LKB1, PTEN, TSC1 / TSC2, Ab1, Cdk-2, cdk-4, HPV-E7, p15, p16.p57, Rb, AliroraA, HPV-E6, Mdm2, ARF, ATMVATR, BRCA1, Chk1, Chk2, DNA-PK, FANCSHIPK2, NBS1, 053, WT1, MUTYH, BLM, RECQL4, WRN, MMR, B-Raf, Fos / Jun.ILK, RaS, RTK, NF1, NF2, VHL, FH, SDH, Myc, BMPR, smad2 / 3, smad4, TGFBR, MEN1, HYMAI, B-catenin, RAR, soX, Wntl, APC, Axin, a-catenin, E-cadherin, Wnt5A, GPC3.TAL1, MLL, HOXS, MITF, EVI1, BCL6, HPC1, HRPT2, GRB10, IGFBP1, IGFBP3, H19, IGF2.KCNQ1, KCNQ10T1, CDKN1, CMEG3, DLK1, RTL1, MEG8, MEG9, DIO3, MKRN3, MAGEL2, NDN.SNURF, SNRPN, UBE3A, ATP10C, GNAS, MEST Any gene promoter region or a combination of different gene promoter regions.

4. The method for detecting DNA methylation based on imprinted control regions as described in claim 1, characterized in that, After determining the extent to which the drug affects the DNA methylation modification of the corresponding imprinted control region based on the matching results, the method further includes: Identify the imprinted control regions affected by the drug, and determine the primary impact of the corresponding imprinted control regions on cellular tumors based on the imprinted control regions affected by the drug and the established imprint-tumor mapping relationship; The secondary impact of the corresponding imprinting control regions on cell development was determined by comparing the imprinting control regions affected by the drug with the imprinting-development mapping relationship. Information on the first and second impact results is displayed.

5. The method for detecting DNA methylation based on imprinted control regions as described in claim 1, characterized in that, The imprinting control region includes any one of the imprinting control regions of PLAGL1, GRB10, H19 / IGF2(IC1), KVDMR1(IC2), DLk1, SNURF (IC), NESP-AS / GNAS-AS1, GNAS-XLDNMTI, MEST, ZNF331, PEG3, IGFIR, PEG1O, DIRAS3, NAPIL5, FAM5OB, IGF2R, TRAPPC9(PEG13)INPP5F, RB1, MCTS2P / HM13, BLCAP / NNAT, and L3MBTL1, or any combination of imprinting genes and imprinting control regions.

6. The method for detecting DNA methylation based on imprinted control regions as described in claim 1, characterized in that, The detection method further includes: The first and second raw sequencing data, after data quality control, were compared with a pre-constructed reference genome, and the compared data were merged to obtain the first and second merged sequencing data; wherein, the first raw sequencing data is the sequencing data corresponding to the pre-drug cell genome library, and the second raw sequencing data is the sequencing data corresponding to the post-drug cell genome library. The first and second merged sequencing data are subjected to TC reduction operations to obtain first reduced sequencing data and second reduced sequencing data; the first and second reduced sequencing data are then compared with a pre-constructed reference genome to determine the first and second position information of each base sequence obtained by sequencing on the chromosome. The first merged sequencing data is spliced ​​according to the first position information to obtain the first chromosome set, and the second merged sequencing data is spliced ​​according to the second position information to obtain the second chromosome set. Comparative analysis of the first and second chromosome sets was performed to determine the chromosome copy number variation before and after medication. The methylation levels of the first and second pooled sequencing data were calculated based on the established methylation measurement model. The methylation difference value is determined based on the methylation levels corresponding to the first and second merged sequencing data. The obtained methylation difference value and chromosome copy number variation are then matched with the corresponding set standard logic. If the match is consistent, it is determined that the corresponding drug has a small impact on the epigenome; if the match is inconsistent, it is determined that the corresponding drug has a large impact on the epigenome.

7. A detection system for DNA methylation based on imprinted control regions, characterized in that, include: First position determination module: used to determine the position information of each mark control area within a set range; The second position determination module is used to align the obtained sequencing data to a reference genome sequence to obtain a genome sequence with metric segment position information. Statistics module: Used to filter sequencing segments that fall into the corresponding imprinted control regions based on the imprinted location information of each imprinted control region and the genome sequence with sequencing segment location information, and to count the number of sequencing segments that fall into each imprinted control region. Methylation calculation module: used to calculate the entries of highly methylated and lowly methylated sequencing segments in all sequencing segments separately, and determine the overall methylation level of the corresponding imprinted control regions; The matching module is used to match the overall methylation level of each imprinted control region with a set alignment strategy to obtain corresponding matching results, and to determine the extent to which the DNA methylation modification of the corresponding imprinted control region is affected by the drug based on the matching results. The process of matching the overall methylation level of each imprinted control region with a set alignment strategy to obtain corresponding matching results, and determining the extent to which the DNA methylation modification of the corresponding imprinted control region is affected by the drug based on the matching results, includes: The grayscale information of each imprint control region is obtained, and the corresponding comparison benchmark threshold is determined based on the grayscale information of each imprint control region and the theoretical methylation information of each imprint control region. The overall methylation level of each imprint control region is matched with the comparison benchmark threshold to obtain the corresponding comparison results. The extent to which the drug affects DNA methylation modification in the corresponding imprinted control region is determined based on the comparison results of each imprinted control region.

8. An electronic device, characterized in that, include: Memory containing executable program code; A processor coupled to the memory; The processor calls the executable program code stored in the memory to execute the DNA methylation detection method based on imprinting control regions as described in any one of claims 1 to 6.

9. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program, wherein the computer program causes a computer to perform the DNA methylation detection method based on imprinted control regions as described in any one of claims 1 to 6.

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