Screening method of susceptible SNP site target gene for AML diagnosis and application thereof

Abstract

The invention relates to the technical field of biology, and provides a screening method and application of susceptible SNP site target genes for AML diagnosis, and the method comprises the following steps: obtaining AML susceptible SNP sites, three-dimensional genome data and AML patient queue data; preprocessing the three-dimensional genome data to obtain a DNA interaction section; predicting a potential target gene regulated and controlled by the AML susceptible SNP locus according to the DNA interaction segment; according to potential target genes regulated by AML susceptible SNP sites, high-credibility transcriptional regulation target genes are screened, and a high-credibility target gene set is obtained; the transcriptional regulation activity of the SNP of the high-credibility target gene set is verified by applying an in-vitro cell experiment. According to the invention, understanding of a regulatory network between AML susceptible SNP and a target gene is expanded, and a new biomarker and a new drug target are provided.

Description

Technical Field

[0001] The present invention relates to the field of biotechnology, and in particular to a method for screening a susceptible SNP site target gene for AML diagnosis and an application thereof. Background Art

[0002] Acute myeloid leukemia (AML) is a hematological malignancy originating from bone marrow hematopoietic stem cells. It is characterized by excessive proliferation and differentiation blockage of bone marrow blasts, which leads to damage to normal hematopoietic function. Although some progress has been made in the treatment of AML in recent years, about 75% of newly diagnosed AML patients can achieve complete remission after 1-2 courses of induction chemotherapy, but relapse and drug resistance are still prominent, resulting in poor long-term prognosis of AML patients, with a 5-year overall survival rate of less than 50%. The high heterogeneity of the genome of AML patients is an important factor affecting relapse and drug resistance. This heterogeneity is not only reflected in the diversity of somatic gene mutations and gene fusions, but also involves a large number of genetic variations, especially single nucleotide polymorphisms (SNPs). With the widespread application of high-throughput sequencing technology, more and more studies have revealed the important role of genetic variation in the occurrence and development of AML. According to statistics, about 5%-10% of AML cases are related to susceptibility caused by genetic variation.

[0003] In recent years, researchers have identified more than 94 SNP sites associated with AML risk, treatment response or prognosis based on genome-wide association studies (GWAS). These AML susceptibility SNP sites can regulate gene expression by interacting with target genes, thereby affecting the occurrence, diagnosis and prognosis of AML patients. However, only a few of the molecular mechanisms of AML susceptibility SNP sites have been elucidated, and there are still a large number of susceptibility sites whose specific functions in AML etiology need to be explored. Accurately identifying the target genes of these SNP sites, especially those located in non-coding regions, is a major challenge currently faced. Existing SNP site target gene prediction methods mainly rely on linear distance, predicting the gene closest to the SNP site on the linear genome as its target gene. This method is limited to neighboring genes and fails to consider the possibility that SNP sites regulate distal genes through long-distance chromatin interactions, resulting in a significant limitation in the breadth of target gene identification and a high risk of false positives.

[0004] In recent years, the rapid development of three-dimensional genomics technology has enabled researchers to predict the target genes of disease-susceptible SNP sites by analyzing the spatial contact relationship between disease-susceptible SNP sites and genes. However, existing methods can only confirm that SNP sites and potential target genes have physical contact in spatial structure, and it is still unclear whether such physical contact can effectively change the transcription level of target genes in AML patient cohorts. This limitation leads to greater uncertainty in the analysis of the specific regulatory mechanism of SNP sites on their potential target genes by three-dimensional genomics methods, hindering our in-depth understanding of the function of disease-susceptible SNP sites. In addition, there is currently no research on the precise and systematic identification and analysis of the transcriptional regulatory targets and their functions of AML-susceptible SNP sites. Therefore, existing methods have problems such as high false positives in predicting SNP site target genes, inability to identify distal target genes, and inability to clarify the transcriptional regulatory relationship between SNP sites and target genes. Summary of the invention

[0005] The present invention aims to solve at least one of the technical problems existing in the related art. To this end, the present invention provides a screening method for a susceptible SNP site target gene for AML diagnosis and its application, which enables people to understand the regulatory network between AML susceptible SNP and target gene, and provides new biomarkers and drug targets.

[0006] The present invention provides a method for screening a susceptible SNP site target gene for AML diagnosis, comprising: S1: Obtain AML susceptibility SNP loci, three-dimensional genome data, and AML patient cohort data; S2: Preprocess the 3D genome data to obtain DNA interaction segments; S3: Prediction of potential target genes regulated by AML susceptibility SNP loci based on DNA interaction segments; S4: Screen high-confidence transcriptional regulatory target genes based on potential target genes and AML patient cohort data to obtain a high-confidence target gene set.

[0007] Furthermore, step S1 includes: S11: Collect the currently published AML susceptibility SNP sites; S12: Collect 3D genomic data from various myeloid cell lines, including Hi-C, ChIA-PET, and BL-Hi-C; S13: Collect AML patient cohort data, including genotype data and RNA-seq data of TCGA-LAML, TARGET-AML, and BeatAML cohorts.

[0008] Furthermore, step S2 includes: For ChIA-PET and BL-Hi-C data, the CHIAPET2 process was used to identify the information of the interaction between protein binding sites after linker sequence cutting, quality control, data alignment, and binding peak search. Based on the information of the interaction between protein binding sites, the DNA interaction segments were obtained. For Hi-C data, HICCUPS software was used to identify DNA interacting segments.

[0009] Furthermore, in step S3, Compare the positions of AML susceptibility SNP sites with DNA interaction segments identified in three-dimensional genomics data to determine the DNA segments containing the susceptibility SNP sites; Based on the interaction pairing relationship between DNA segments provided in the three-dimensional genome data, the DNA segments that interact with the DNA segments of the susceptible SNP sites are located, and the potential target genes regulated by the AML susceptible SNP sites are obtained.

[0010] Furthermore, the target genes are classified according to the interaction between the susceptible SNP sites and the target genes. The susceptible SNP site is located at one end of a pair of interacting DNA segments, while the other end overlaps with the promoter region of the gene. The gene in this positional relationship with the susceptible SNP site is defined as a type 1 target gene; The susceptible SNP site is located at one end of a pair of interacting DNA segments, while the other end overlaps with the gene body region of the gene. The gene in this positional relationship with the susceptible SNP site is defined as a type 2 target gene.

[0011] Furthermore, by comparing the bases at the SNP site with the alleles in the hg38 reference genome, when both chromosomes of the AML patient carry the reference allele at the SNP site, the AML patient has an AA genotype; when both chromosomes of the AML patient carry the reference allele and the mutant allele at the SNP site, respectively, the AML patient has an AB genotype; when both chromosomes of the AML patient carry the mutant allele at the SNP site, the AML patient has a BB genotype.

[0012] Further, step S4 includes, S41: construct a linear regression model of the target gene based on the genotype, broad factors that have a broad impact on mRNA expression, and the mRNA expression level of the target gene; S42: using the least squares method to calculate the regression coefficient between the genotype of the target gene linear regression model and the target gene mRNA expression level, and obtaining the regression coefficient between each genotype and the target gene mRNA expression level; S43: Based on the regression coefficient between the genotype and the target gene mRNA expression level, the t-test was used to calculate the statistic and obtain the P value of each genotype; S44: Fisher's method was used to calculate the P value of each genotype to obtain the joint P value; S45: Benjamini-Hochberg correction was performed on the joint P value to obtain the false discovery rate FDR; S46: According to the P value, the regression coefficient between the genotype and the target gene mRNA expression, and the false discovery rate FDR, three thresholds are set to filter the target gene set, and the target genes that meet the three thresholds at the same time are selected to obtain a high-confidence target gene set.

[0013] Further, step S45 includes: S451: sort all obtained joint P values ​​in ascending order and record the original position of each joint P value, S452: Calculate an adjusted value of each joint P value based on the sorted joint P values ​​and rankings, where the adjusted value of the joint P value is an FDR value; S453: Adjust the order of FDR values ​​so that the adjusted FDR values ​​meet the principle of monotonically decreasing; S454: Reversely map the adjusted FDR value to the original position of each joint P value, so that each joint P value matches the corresponding adjusted FDR value to obtain the false discovery rate FDR.

[0014] Furthermore, in S46, Threshold 1: P value < 0.05 in at least one patient cohort; Threshold 2: Multiple β The direction of the 1 value is the same, all positive or negative correlation; Threshold 3: false discovery rate FDR < 0.05.

[0015] An application of a method for screening a susceptible SNP site target gene for AML diagnosis, wherein the method for screening a susceptible SNP site target gene for AML diagnosis is the above-mentioned method for screening a susceptible SNP site target gene for AML diagnosis.

[0016] The above one or more technical solutions in the embodiments of the present invention have at least one of the following technical effects: The present invention provides a screening method for target genes of susceptible SNP sites for AML diagnosis and its application, which systematically integrates multi-dimensional omics data of AML-related cell lines and realizes comprehensive prediction of transcriptional regulatory target genes of AML susceptible SNP sites. Based on the AML patient cohort, the present invention verifies the high-confidence transcriptional regulatory target genes of AML susceptible SNP sites. It provides potential biomarkers and drug targets for the accurate diagnosis and treatment of AML.

[0017] The present invention reveals the various forms of target gene regulation by AML susceptibility SNP sites, effectively making up for the deficiency of predicting target genes of SNP sites based only on linear distance, and clarifies that these susceptibility sites can regulate the expression of distal targets through chromatin interactions, providing a theoretical basis for understanding the complex regulatory network between AML susceptibility SNPs and target genes.

[0018] Additional aspects and advantages of the present invention will be given in part in the following description and in part will be obvious from the following description, or will be learned through practice of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] In order to more clearly illustrate the technical solutions in the present invention or the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0020] Figure 1 It is a schematic diagram of a process for screening a susceptible SNP site target gene for AML diagnosis provided by the present invention.

[0021] Figure 2 The present invention provides a method for screening a susceptible SNP site target gene for AML diagnosis, which is an integrated view of the AML susceptible SNP rs187084 and its adjacent regions observed in HL-60 cells by IGV.

[0022] Figure 3 This is a method for screening target genes at susceptible SNP sites for AML diagnosis provided by the present invention, and is a graph showing the eQTL analysis results between rs187084 and the mRNA expression levels of the ITIH4 gene based on three AML patient cohorts, namely TCGA-LAML, TARGET-AML and BeatAML.

[0023] Figure 4The present invention provides a method for screening target genes at susceptible SNP sites for AML diagnosis provided by the present invention, and an in vitro cell dual fluorescence reporter experiment verifies the regulatory effect of SNP rs187084 on gene expression. DETAILED DESCRIPTION

[0024] In order to make the purpose, technical scheme and advantages of the present invention clearer, the technical scheme in the present invention will be clearly and completely described below. Obviously, the described embodiments are part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments in the present invention, all other embodiments obtained by ordinary technicians in the field without creative work are within the scope of protection of the present invention. The following embodiments are used to illustrate the present invention, but cannot be used to limit the scope of the present invention.

[0025] In the description of this specification, the description with reference to the terms "one embodiment", "some embodiments", "example", "specific example", or "some examples" etc. means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the embodiment of the present invention. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described may be combined in any one or more embodiments or examples in a suitable manner. In addition, those skilled in the art may combine and combine the different embodiments or examples described in this specification and the features of the different embodiments or examples, without contradiction.

[0026] Combine the following Figures 1 to 4 The present invention describes a method for screening a susceptible SNP site target gene for AML diagnosis and its application.

[0027] like Figure 1 As shown, a screening method for a susceptible SNP site target gene for AML diagnosis comprises: S1: Obtain AML susceptibility SNP loci, three-dimensional genome data, and AML patient cohort data; S11: Collect the currently published AML susceptibility SNP loci, a total of 94, which are all from literature reports and identified by genome-wide association analysis; S12: Collect 3D genomic data from various myeloid cell lines, derived from various technology types, including Hi-C, ChIA-PET, BL-Hi-C. All data are derived from the public database GEO, the DNA 3D genomics sequencing set released in the third phase of the ENCODE project, or published literature; S13: Collect AML patient cohort data, including genotype data and RNA-seq data of acute myeloid leukemia (TCGA-LAML), targeted acute myeloid leukemia (TARGET-AML), and BeatAML cohorts.

[0028] S2: Preprocess the 3D genome data to obtain DNA interaction segments; For ChIA-PET and BL-Hi-C data, the CHIAPET2 process was used. After the steps of linker sequence cutting, quality control, data alignment, and binding peak search, the interaction information between specific protein binding sites was identified for subsequent analysis. The specific parameters of the CHIAPET2 process were -m 1 -e 3 -k 2 -t 6 -l 12 -C 1. For Hi-C data, HICCUPS software was used to identify the interaction between different DNA segments. The specific parameters of the HICCUPS software were -k KR--cpu -m 1024 --threads 8 -r 5000,10000 --ignore_sparsity.

[0029] S3: Prediction of potential target genes regulated by AML susceptibility SNP loci based on DNA interaction segments; The potential transcriptional regulatory target genes of AML susceptibility SNP sites are predicted based on the interaction information between different DNA segments provided by genomic data. Specifically, the AML susceptibility SNP sites are first compared with the DNA interaction segments identified in the three-dimensional genomic data to determine the DNA segments containing the susceptible SNP sites. Then, based on the interaction pairing relationship between the DNA segments provided in the three-dimensional genomic data, the DNA segments that interact with the above-mentioned susceptible SNP sites are located, thereby inferring the potential target genes regulated by the susceptible SNP sites. According to the different ways in which the susceptible SNP sites interact with the target genes, the target genes are divided into the following two categories: There is an interaction between the susceptible SNP site and the promoter region of the gene. Specifically, the SNP is located at one end of a pair of interacting DNA segments, while the other end overlaps with the promoter region of the gene. The gene in this positional relationship with the susceptible SNP site is defined as a type 1 target gene; There is an interaction between the susceptible SNP site and the gene body region of the gene. Specifically, the SNP is located at one end of a pair of interacting DNA segments, and the other end overlaps with the gene body region of the gene. The gene in this positional relationship with the susceptible SNP site is defined as a type 2 target gene; In addition, if a target gene is identified as both a type 1 target gene and a type 2 target gene of an AML susceptibility SNP site, it is preferentially classified as a type 1 target gene. The present invention predicts 192 potential target genes for rs187084, including 93 type 1 target genes and 99 type 2 target genes. The prediction results of potential transcriptional regulatory target genes of rs187084 of the AML susceptibility SNP site based on three-dimensional genome data are shown in Table 1.

[0030] Table 1 Prediction results of potential transcriptional regulatory target genes of AML susceptibility SNP site rs187084 in three-dimensional genomic data S4: Screen high-confidence transcriptional regulatory target genes based on potential target genes regulated by AML susceptibility SNP sites and AML patient cohort data to obtain a high-confidence target gene set; Carry out expression quantitative trait loci (eQTL) analysis to compare the differences in the transcription levels of target genes in patients with different genotypes, and further clarify the impact of AML susceptibility SNP sites on target gene transcription. Considering that the effect of SNP on target genes is small and uneven sample size may cause deviations in statistical significance, different statistical test methods are combined on the basis of conventional eQTL analysis to optimize the effectiveness of eQTL verification; First, according to the differences in the patient's gene sequence at the SNP site, the patients were divided into three genotypes: AA, AB, and BB. By comparing the bases at the SNP site with the alleles in the hg38 reference genome, when both chromosomes of an AML patient carry the reference allele at the SNP site, they are classified as the AA genotype; when both chromosomes of an AML patient carry the reference allele and the mutant allele at the SNP site, they are classified as the AB genotype; when both chromosomes of an AML patient carry the mutant allele at the SNP site, they are classified as the BB genotype. S41: construct a linear regression model of the target gene based on the genotype, broad factors that have a broad impact on mRNA expression, and the mRNA expression level of the target gene; The genotype at the SNP site was used as the independent variable and the mRNA expression level of the target gene was used as the dependent variable to construct a linear regression model of the target gene. The calculation expression of the linear regression model of the target gene is: in, is the mRNA expression value of the target gene, For different genotypes of SNP sites, AA=0, AB=1, BB=2, is the regression coefficient between genotype and target gene mRNA expression, is a broad factor, is a random error, is the target gene mRNA expression value when both the SNP genotype and the broad factor are 0, is the regression coefficient between the broad factor and the target gene mRNA expression; In order to avoid the influence of different sample sources (such as gender, age, ancestry, etc.) on the identification of SNP genotypes and calculation of mRNA expression, broad factors that have a broad impact on mRNA expression were included in the regression model as covariates to remove their interference with the results; Broad factors include the sex, age, ethnic background and latent factors of the samples; latent factors refer to factors that are related to gene expression but cannot be directly measured, such as batch effects, environmental factors and technical noise. They were calculated using the R package PEER, and based on the number of samples in the three AML patient cohorts (150 ≤ N<250), 30 latent factors were calculated for each AML patient cohort and added as covariates to ensure the accuracy of the analysis; Ethnic background refers to the dimensionality reduction of SNP genotype data using principal component analysis (PCA), extracting the main variation components between samples, and selecting the first five principal components to add as covariates; The target gene linear regression model was used to evaluate the changing patterns of mRNA expression levels of target genes in patients with different genotypes; S42: using the least squares method to calculate the regression coefficient between the genotype of the target gene linear regression model and the target gene mRNA expression level, and obtaining the regression coefficient between each genotype and the target gene mRNA expression level; The regression coefficient between each genotype AA, AB, BB and the target gene mRNA expression level was calculated based on the target gene linear regression model; the impact of different genotypes (AA, AB, BB) on the expression level of the target gene was determined through the regression coefficient; a positive regression coefficient indicated that the genotype was associated with a higher target gene mRNA expression level, and a negative regression coefficient indicated that the genotype was associated with a lower target gene mRNA expression level; S43: Based on the regression coefficient between the genotype and the target gene mRNA expression level, the t-test was used to calculate the statistic and obtain the P value of each genotype; Through three AML patient cohorts, three target gene linear regression models were obtained. β 1. According to β 1 Calculate the two-tailed significance level P, according to distribution (degrees of freedom is the number of samples minus the number of model parameters), calculate value, The value calculation expression is: in, for β The standard error is 1, which measures the uncertainty of the estimate.

[0031] calculate The two-tailed significance level corresponding to the value is obtained to obtain the P value.

[0032] If the P value is less than the set significance threshold, the null hypothesis is rejected and it is considered that the association between the SNP and the target gene mRNA expression level is significant.

[0033] The P value is used to evaluate the statistical significance of the relationship. The P value and the FDR value after BH correction are used to evaluate whether the association between SNP and gene expression is significant. If the P value is less than the preset significance level (such as 0.05), it means that there is a significant association between the SNP genotype and the target gene expression.

[0034] Three β The 1 value represents the regression coefficient of SNP and target gene mRNA expression level in different patient cohorts, and the three P values ​​represent the statistical significance in different patient cohorts.

[0035] S44: Fisher's method was used to calculate the P value of each genotype to obtain the joint P value; In order to obtain a reliable SNP-target gene set and eliminate the impact of uneven sample size on statistical test significance, Fisher's method was used to calculate the above three P values ​​to obtain a joint P value: in, is the joint P value, For the The P value obtained from a single test is is the number of P values.

[0036] S45: Benjamini-Hochberg correction was performed on the joint P value to obtain the false discovery rate (FDR); In order to control the false positive rate in multiple hypothesis testing, the joint P value of type 1 target gene and type 2 target gene was corrected by Benjamini-Hochberg (BH). S451: sort all obtained joint P values ​​in ascending order and record the original position of each joint P value, S452: Calculate an adjusted value of each joint P value based on the sorted joint P values ​​and rankings, where the adjusted value of the joint P value is an FDR value; in, is the adjusted FDR value, After sorting joint P value, m is the total number of hypothesis tests, is the ranking position of the joint P value, S453: Adjust the order of FDR values ​​so that the adjusted FDR values ​​meet the principle of monotonically decreasing; If one adjusted FDR value is greater than the next adjusted FDR value, they are adjusted to the same value; S454: Reversely map the adjusted FDR value to the original position of each joint P value, so that each joint P value matches the corresponding adjusted FDR value to obtain the false discovery rate FDR.

[0037] S46: According to the P value, the regression coefficient between the genotype and the target gene mRNA expression, and the false discovery rate FDR, three thresholds are set to filter the target gene set, and the target genes that meet the three thresholds are selected to obtain a high-confidence target gene set; According to the performance of the target gene at the susceptible SNP site in different patient cohorts, three thresholds were set to filter the target gene set. Threshold 1: P value < 0.05 in at least one patient cohort; Threshold 2: Multiple β The direction of the 1 value is the same, all positive or negative correlation; Threshold 3: false discovery rate FDR < 0.05.

[0038] If the target gene meets the three criteria of threshold 1, threshold 2 and threshold 3 at the same time, it is a target gene with high confidence.

[0039] Use in vitro cell experiments to verify the transcriptional regulatory activity of SNPs in high-confidence target gene sets; The dual fluorescence reporter experiment was used to detect the regulatory function of SNP sites on genes. This experiment used the PGL3-REPORT vector, which contains a firefly luciferase reporter gene under the control of an SV40 promoter. In the multiple cloning site upstream of the promoter, 150bp of nucleotide sequences upstream and downstream of the screened wild-type and mutant SNP sites were inserted respectively, and the target plasmid was recombined and synthesized. At the same time, the Renilla luciferase plasmid pRL-CMV was used as an internal reference plasmid. The target plasmid and the internal reference plasmid were co-transfected into 293T cells for 24 hours, and the luciferase activity was determined using a dual fluorescence reporter detection kit. The effect of SNP on gene regulation was judged by the level of luciferase activity, such as Figure 4 shown.

[0040] The present invention successfully identified the highly reliable transcriptional regulatory target gene ITIH4 for the AML susceptibility SNP site rs187084, as shown in Table 2, the cross-validation results of rs187084-ITIH4 in three independent AML patient cohorts.

[0041] Table 2. Cross-validation results of rs187084-ITIH4 in three independent AML patient cohorts like Figure 2 As shown, rs187084 can physically contact the gene ITIH4 through long-range chromatin interactions in HL-60 cells, as observed by the Integrative Genomics Viewer (IGV).

[0042] Figure 2 The multi-omics data of chromosome 3 (Chr3) of HL-60 cell line in the region of 52,180 kb to 52,850 kb are shown in the figure. The horizontal axis represents the genomic coordinates, covering a range of 670 kb. The blue annotations represent the RefSeq gene annotations, indicating the locations of the key genes TLR9 and ITIH4 in the region; the red short line annotations represent the location of the SNP site rs187084; the purple arcs represent the chromatin loops formed by all the anchor peaks of rs187084 and their interacting anchor peaks in the region of 52,180 kb to 52,850 kb, and the dark purple arcs highlight the chromatin loops between the anchor peaks of rs187084 and the regulatory region of the ITIH4 gene; Figure 2The signal distribution and intensity of RNASeq (transcriptome sequencing), H3K27ac (enhancer mark), H3K4me3 (promoter mark), CTCF (chromatin structural protein) and RNA polymerase II (RNA Pol II phosphoS5) are displayed. [0-3676] shows the numerical range of RNASeq protein peak intensity, [0-300] shows the numerical range of H3K27ac protein peak intensity, [0-515] shows the numerical range of H3K4me3 protein peak intensity, [0-15] shows the numerical range of CTCF protein peak intensity, and [0-102] shows the numerical range of RNA polymerase II protein peak intensity. The larger the value, the stronger the signal.

[0043] like Figure 3 As shown, based on the three AML patient cohorts of TCGA-LAML, TARGET-AML and BeatAML, rs187084 can upregulate the mRNA expression of the ITIH4 gene.

[0044] like Figure 4 As shown, the results showed that the luciferase activity of mutant rs187084 was increased, indicating that mutant rs187084 in AML patients can regulate gene promoter expression, has enhancer activity, and affects the upregulation of oncogene expression.

[0045] A screening method for susceptibility SNP site target genes for AML diagnosis is used to screen AML susceptibility SNP site target genes, providing new biomarkers and drug targets for the precise diagnosis and treatment of AML.

[0046] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for screening a susceptible SNP site target gene for AML diagnosis, characterized in that: include: S1: Obtain AML susceptibility SNP loci, three-dimensional genome data, and AML patient cohort data; S2: Preprocess the 3D genome data to obtain DNA interaction segments; S3: Prediction of potential target genes regulated by AML susceptibility SNP loci based on DNA interaction segments; S4: Screen high-confidence transcriptional regulatory target genes based on potential target genes and AML patient cohort data to obtain a high-confidence target gene set.

2. The method for screening a susceptible SNP site target gene for AML diagnosis according to claim 1, characterized in that: The S1 step includes: S11: Collect the currently published AML susceptibility SNP sites; S12: Collect 3D genomic data from various myeloid cell lines, including Hi-C, ChIA-PET, and BL-Hi-C; S13: Collect AML patient cohort data, including genotype data and RNA-seq data of TCGA-LAML, TARGET-AML, and BeatAML cohorts.

3. The method for screening a susceptible SNP site target gene for AML diagnosis according to claim 2, characterized in that: The S2 step includes: For ChIA-PET and BL-Hi-C data, the CHIAPET2 process was used to identify the information of the interaction between protein binding sites after linker sequence cutting, quality control, data alignment, and binding peak search. Based on the information of the interaction between protein binding sites, the DNA interaction segments were obtained. For Hi-C data, HICCUPS software was used to identify DNA interacting segments.

4. The method for screening a susceptible SNP site target gene for AML diagnosis according to claim 1, characterized in that: In step S3, Compare the positions of AML susceptibility SNP sites with DNA interaction segments identified in three-dimensional genomics data to determine the DNA segments containing the susceptibility SNP sites; Based on the interaction pairing relationship between DNA segments provided in the three-dimensional genome data, the DNA segments that interact with the DNA segments of the susceptible SNP sites are located, and the potential target genes regulated by the AML susceptible SNP sites are obtained.

5. The method for screening a susceptible SNP site target gene for AML diagnosis according to claim 1, characterized in that: The target genes are classified according to the interaction between the susceptible SNP sites and the target genes. The susceptible SNP site is located at one end of a pair of interacting DNA segments, while the other end overlaps with the promoter region of the gene. The gene in this positional relationship with the susceptible SNP site is defined as a type 1 target gene; The susceptible SNP site is located at one end of a pair of interacting DNA segments, while the other end overlaps with the gene body region of the gene. The gene in this positional relationship with the susceptible SNP site is defined as a type 2 target gene.

6. The method for screening a susceptible SNP site target gene for AML diagnosis according to claim 1, characterized in that: Compare the bases at the SNP site with the alleles in the hg38 reference genome. When both chromosomes of an AML patient carry the reference allele at the SNP site, the AML patient has an AA genotype; when both chromosomes of an AML patient carry the reference allele and the mutant allele at the SNP site, the AML patient has an AB genotype; when both chromosomes of an AML patient carry the mutant allele at the SNP site, the AML patient has a BB genotype.

7. The method for screening a susceptible SNP site target gene for AML diagnosis according to claim 6, characterized in that: The S4 step includes: S41: construct a linear regression model of the target gene based on the genotype, broad factors that have a broad impact on mRNA expression, and the mRNA expression level of the target gene; S42: using the least squares method to calculate the regression coefficient between the genotype of the target gene linear regression model and the target gene mRNA expression level, and obtaining the regression coefficient between each genotype and the target gene mRNA expression level; S43: Based on the regression coefficient between the genotype and the target gene mRNA expression level, the t-test was used to calculate the statistic and obtain the P value of each genotype; S44: Fisher's method was used to calculate the P value of each genotype to obtain the joint P value; S45: Benjamini-Hochberg correction was performed on the joint P value to obtain the false discovery rate FDR; S46: According to the P value, the regression coefficient between the genotype and the target gene mRNA expression, and the false discovery rate FDR, three thresholds are set to filter the target gene set, and the target genes that meet the three thresholds at the same time are selected to obtain a high-confidence target gene set.

8. The method for screening a susceptible SNP site target gene for AML diagnosis according to claim 7, characterized in that: Step S45 includes: S451: sort all obtained joint P values ​​in ascending order and record the original position of each joint P value, S452: Calculate an adjusted value of each joint P value based on the sorted joint P values ​​and rankings, where the adjusted value of the joint P value is an FDR value; S453: Adjust the order of FDR values ​​so that the adjusted FDR values ​​meet the principle of monotonically decreasing; S454: Reversely map the adjusted FDR value to the original position of each joint P value, so that each joint P value matches the corresponding adjusted FDR value to obtain the false discovery rate FDR.

9. The method for screening a susceptible SNP site target gene for AML diagnosis according to claim 8, characterized in that: In S46, Threshold 1: P value < 0.05 in at least one patient cohort; Threshold 2: The direction of the regression coefficients between multiple genotypes and target gene mRNA expression is the same, all positively or negatively correlated; Threshold 3: False Discovery Rate FDR < 0.

05.

10. An application of a method for screening a susceptible SNP site target gene for AML diagnosis, characterized in that: The method for screening a susceptible SNP site target gene for AML diagnosis is the method for screening a susceptible SNP site target gene for AML diagnosis described in any one of claims 1-9.

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