90 results about "Differential Methylation" patented technology

The invention provides an esophageal cancer marker screening method based on enzyme transfer method methylation sequencing, which comprises the following steps: S1, collecting esophageal early cancer and para-carcinoma tissue samples, and carrying out enzyme transfer method whole genome methylation sequencing; s2, integrating methylation data of esophageal cancer and para-carcinoma tissues in databases of TCGA, GEO, MethMarker DB and the like; s3, screening differential methylation sites, preferably sites which are hypermethylated in esophageal cancer but hypomethylated in samples such as leukocytes, so as to reduce plasma background interference; s4, obtaining a candidate marker combination based on an integrated methylation feature screening model of LASSO regression and a random forest algorithm; s5, constructing a classifier model based on the candidate marker combination, carrying out training and reasoning test on the model, and evaluating the prediction performance of the model; and S6, obtaining the esophageal cancer marker combination. According to the method, enzyme transfer sequencing and machine learning are combined, the marker prediction accuracy is remarkably improved, and a new reference is provided for clinical research of esophageal cancer.

The present disclosure includes a method of comprising (a) obtaining cell-free DNA (cfDNA) from a sample from a subject; (b) selectively enriching subsets of the cfDNA from (a) or derivatives therefrom having one or more target regions to obtain enriched DNA, wherein the target regions are differentially methylated in cancer; (c) sequencing the enriched DNA from (b) to obtain sequence reads; and (d) partitioning a plurality of the sequence reads into two or more groups based on their methylation status and determining the fragment length distribution of the sequence reads in at least one of the groups.

The present disclose provides a method for classifying a sample derived from a subject. The method may comprise obtaining a sample comprising nucleic acid molecules from the subject. The method can comprise assaying the nucleic acid molecules to generate a data set comprising methylation states of one or more genomic regions. The one or more genomic regions can comprise differentially methylation regions (DMRs). The method can comprise processing at least a portion of the data set to generate an output indicative of cancer in the subject. The portion of the data set can pertain to a set of DMRs specific to the subject.

The invention discloses a methylated biomarker for detecting esophageal cancer and application of the methylated biomarker. The invention provides a methylated biomarker, and the methylated biomarker comprises any one selected from the following differential methylated regions or any combination of the differential methylated regions: chr17: 49021947-49022096, chr19: 11998652-11998772, and the like. The invention also provides a method for preparing the methylated biomarker, and the methylated biomarker comprises any one selected from the following differential methylated regions: chr17: 49021947-49022096, chr19: 11998652-11998772, and the like. The methylated biomarker provided by the invention can be used for diagnosing esophageal cancer, and has good sensitivity, specificity and accuracy.

Low background regions (LBRs) refer to genomic regions comprising one or more CpG sites that are differentially methylated in cancer and non-cancer samples. Disclose methods involve identifying LBRs comprising one or more CpG sites whose methylation statuses sufficiently distinguish between samples that contain a presence of a cancer signature and samples that do not contain a presence of a cancer signature. LBRs enable improved detection of presence or absence of cancer signatures while using smaller samples and fewer consumable reagents.

The present disclosure provides for a method of treating fetal growth restriction in a fetus comprising obtaining a blood sample from a pregnant subject; isolating cell-free fetal DNA from the blood sample; testing the cell-free fetal DNA for a first DNA methylation level of 0.5800 or less in a group of genes, wherein the group of genes comprises the genes of any one of Tables 19-21, wherein the first DNA methylation level is calculated via an average of all differentially methylated islands of cytosine and guanine dinucleotides separated by only one phosphate in the 5' to 3' direction (5'-C-phosphate-G-3') (CpGIs) in differentially methylated regions (DMRs); and when the first DNA methylation level is 0.5800 or less, selecting a treatment from the following: monitoring the fetus during pregnancy of the pregnant subject, tracking movements of the fetus, admitting the pregnant subject to a hospital prior to going into labor, inducing early delivery of the fetus, performing an emergency Cesarean section on the pregnant subject, administering corticosteroids to the pregnant subject, or administering corticosteroids to the fetus upon birth. Other related methods are disclosed herein.

The invention discloses a sperm genome methylation detection method for safety evaluation of biological breeding crops by using primates and application, and relates to the technical field of safety evaluation of crops, the sperm genome methylation detection method comprises the following steps: dividing non-human primates into three groups, collecting sperms after long-term feeding, and extracting DNA (Deoxyribose Nucleic Acid); carrying out whole genome sequencing and quality control after bisulfite treatment; the epigenetic safety of crops is comprehensively evaluated by analyzing the methylation level of a whole genome and a functional region and functional enrichment of a differential methylation region and related genes thereof; according to the sperm genome methylation detection method for evaluating the safety of the biologically bred crops by utilizing the primates and the application, by utilizing a high-resolution WGBS technology, subtle epigenetic changes which are difficult to find by traditional toxicology can be detected, and the sperm genome methylation detection method has important significance in cross-generation reproduction effect evaluation, and has a wide application prospect. A food safety evaluation system can be perfected, and a more scientific and reliable safety interpretation basis can be established.

Low background regions (LBRs) refer to genomic regions comprising one or more CpG sites that are differentially methylated in cancer and non-cancer samples. Disclose methods involve identifying LBRs comprising one or more CpG sites whose methylation statuses sufficiently distinguish between samples that contain a presence of a cancer signature and samples that do not contain a presence of a cancer signature. LBRs enable improved detection of presence or absence of cancer signatures while using smaller samples and fewer consumable reagents.

The present invention relates to methods of determining the presence or absence of certain cancers in a human individual, as well as to related methods to determine the response to therapy against certain cancers in a human individual, in particular ovarian cancer in a woman. Such methods are based on the detection—from (eg cell-free) DNA of said human individual—of one or more methylated (or un-methylated) CpGs being associated with differentially methylated regions (DMRs) of the present invention; such as methylation (or un-methylation) at one or more or all of certain CpGs being associated with such DMRs. Accordingly, such methods have diagnostic, prognostic and / or predictive utility for detecting or managing certain cancers in women or men, in particular ovarian cancer in women. The present invention further relates to nucleic acids comprising certain sequences that may be detected during the method, or nucleic acids (such as probes and / or primers) that are useful to detect such sequences, as wells as compositions, kits, computer program products and other aspects that are useful for or related to the practice or application of such methods.

The invention relates to the technical field of methylation detection site detection, and particularly provides an early gastric cancer lymph node metastasis risk prediction method, system, application and medium, and the method comprises the following steps: obtaining a gastric cancer public data set containing a DNA methylation chip data set and an RNA sequencing data set, and carrying out sample screening, quality control and grouping processing to obtain eight quality control grouping samples; carrying out methylation and RNA difference analysis on the quality control grouped samples to obtain a related gene set of differential methylation sites and differential methylation regions and an RNA differential expression gene set; a gene set of differential methylation sites and an RNA differential expression gene set are integrated and screened to obtain eight target genes. The system comprises a sample acquisition module, a gene analysis module and a gene screening module. Target genes are analyzed and screened on the basis of database biological information, and methylation detection sites for histopathological specimens are screened in combination with lymph node metastasis positive and negative early gastric cancer histological sample verification.

The present application relates to a kind of sgRNA targeting Plagl1 gene DMR, epigenetic editing system and its application.Specifically, the present application provides sgRNA targeting Plagl1 gene differential methylation region, which forms epigenetic editing system with dCas9-Tet1-CD fusion protein.The system is loaded in injectable type light-cured silk fibroin hydrogel, the expression of Plagl1 gene in periosteum stem / progenitor cells is accurately activated by targeted demethylation modification, thereby promoting osteogenic differentiation.The present application combines epigenetic regulation with biomaterial delivery, and provides a safe, efficient new strategy for jaw bone defect regeneration and repair.

The invention provides target sections S6-1, S6-2 and S6-3 for identifying multiple cancer species and application of the target sections S6-1, S6-2 and S6-3. A group of unprecedented gene methylation sites are successfully identified through an innovative screening strategy and large-scale cross-cancer omics data analysis. The invention also comprises a detection reagent (such as a primer) and a kit for detecting the target segment of the genome. The methylation degrees of the target segment between a plurality of cancer tissues and para-carcinoma tissues have significant differences, so that the subject can be judged to belong to tumor high-risk groups. The cancer tissue and para-carcinoma tissue differential methylation state presented by the target segment can be widely applied to various different types of cancers.

Low background regions (LBRs) refer to genomic regions comprising one or more CpG sites that are differentially methylated in cancer and non-cancer samples. Disclose methods involve identifying LBRs comprising one or more CpG sites whose methylation statuses sufficiently distinguish between samples that contain a presence of a cancer signature and samples that do not contain a presence of a cancer signature. LBRs enable improved detection of presence or absence of cancer signatures while using smaller samples and fewer consumable reagents.

Digital amplification methods and kits provide the ability to estimate the fetal fraction of cfDNA in a maternal sample, such as plasma or serum, by analyzing target sites differentially methylated in fetal and maternal free DNA (cfDNA).

The present invention belongs to the field of computer technology and provides a method and system for predicting DNA methylation level profiles in conjunction with pathological phenotype characteristics. The training method includes obtaining a characteristic spectrum of cell nuclei in the tumor region of the digital pathology slide data based on digital pathology slide data; obtaining a methylation level matrix of all CpG sites based on the patient's original DNA methylation sequencing data; determining the clinical diagnostic stage of cancer tissue samples, normal tissue samples, and cancer patients based on the methylation level matrix of all CpG sites and the patient's clinical information, performing differential methylation CpG site analysis, and obtaining a tumor differential CpG site methylation level spectrum and a tumor stage differential CpG site methylation level spectrum; and training a generative model using the characteristic spectrum of cell nuclei in the tumor region of the digital pathology slide data as input and the differential CpG site methylation level spectrum of the tumor and the differential CpG site methylation level spectrum of the tumor as output.

It has been discovered that differential methylation in DNA can be used to distinguish between malignant and non-malignant skin lesions. Seven genes, 3 that are hypermethylated in melanoma, 1 that is hypermethylated in melanocytes and remains methylated in melanoma, and 3 that are hypermethylated in all tissues are provided as biomarkers. The panel demonstrates a 93% sensitivity, 97% specificity and an AUC of 95% in distinguishing between melanoma and benign lesions. Thus provided herein are melanoma biomarkers and methods of detecting them and using them to diagnose and guide treatment of subjects with the same, and monitor melanoma tumor dynamics during and after treatment.

The invention discloses a biological age assessment method and system based on full life cycle DNA methylation and application, and belongs to the technical field of bioinformatics. The method comprises the following steps: firstly, carrying out quality control and standardization treatment on obtained original DNA methylation data; then, screening differential methylation sites significantly related to calendar age as features; then, by taking calendar age as a target variable, constructing a regression model by adopting a LightGBM gradient lifting framework to obtain a methylated clock model; then, predicting the DNA methylation age of the individual by using the model, and calculating an epigenetic age acceleration value based on the deviation between the DNA methylation age and the calendar age; and finally, carrying out correlation analysis on the age acceleration value and health or physiological indexes of different life stages, so as to evaluate the biological aging state of the individual and predict related health risks. The method covers the whole life cycle, is suitable for Chinese population, and can provide an effective tool for clinical disease risk prediction, health management and anti-aging intervention effect evaluation.

The present disclosure includes a method comprising: (a) obtaining free DNA (cfDNA) from a sample from a subject; (b) selectively enriching a subset of the cfDNA or derivatives thereof from (a) having one or more target regions to obtain an enriched DNA, wherein the target regions are differentially methylated in cancer; (c) sequencing the enriched DNA from (b) to obtain a sequence read; and (d) dividing a plurality of said sequence reads into two or more groups based on the methylation status thereof, and determining the fragment length distribution of said sequence reads in at least one of said groups.

The invention relates to the technical field of gene classification, in particular to a longitudinal DNA methylation data-based classification method, which comprises the following steps of: taking collected longitudinal DNA methylation data as sample data, dividing a plurality of data profile matrixes by a time axis, and forming a methylation matrix according to context information of the data profile matrixes; extracting each key site in the methylation matrix by using the stage identifier of the sample data, and identifying the change trend of each key site according to the clustering trajectory of the key sites; based on the change trend of each key site, extracting each differential methylation region, taking each differential methylation region as input, outputting the expression type of each sample data by using the classification model, and calibrating a difference factor according to the data proportion of the expression type in each differential methylation region; according to the difference factor calibrated by each differential methylation region, identifying the execution screening classification of each difference factor; and the accuracy and efficiency of DNA methylation data classification are improved.

The present application relates to the technical field of medical detection, and particularly relates to a marker combination, a primer probe combination, a kit and application for detecting multiple subtypes of ovarian cancer and borderline ovarian tumors. The marker combination comprises at least 3 of the following differential methylation regions: a differential methylation region of IFFO1, a differential methylation region of TFAP2E-AS1, a differential methylation region of WNT6, and a differential methylation region of AC104801.1. The present application can comprehensively cover the detection of multiple subtypes of ovarian cancer and borderline ovarian tumors, is suitable for liquid biopsy, and has high sensitivity and high specificity.

The invention discloses a DNA methylation regulatory gene identification method related to formation of cold resistance of Brassica campestris L. and application of the DNA methylation regulatory gene identification method. The method belongs to the technical field of winter rape cold resistance epigenetic regulation mechanism analysis. According to the invention, a methylation sensitive amplification polymorphism technology is utilized, four Chinese cabbage type winter rape materials with large cold resistance difference after the same variety is domesticated in different breeding environments are selected as research objects, the change rule of DNA methylation after treatment at 4 DEG C for 24 hours and recovery growth for 2 days is analyzed, and finally differential methylation gene expression is verified by utilizing a qPCR technology. The invention provides a reference method for DNA methylation research of plants under adversity stress, and compared with other epimics research such as DNA methylation, the method is simple and convenient to operate and low in cost, does not need high-throughput sequencing, and only needs one-generation sequencing. The candidate gene identified by the invention provides a genetic basis for explaining a cold resistance evolution molecular mechanism of Brassica campestris L. and guiding cold resistance improvement of northern winter rapes.

The application belongs to the field of aquatic molecular breeding and epigenetic marker development, and particularly relates to a group of DNA methylation markers related to loss of Chinese mitten crab in summer extreme high temperature and application thereof in breeding. The methylation markers include 8 differentially methylated cytosine sites located on the reference genome ASM2467909v1, adjacent to LOC126983793 (ADCY9), LOC126997354 (UNC79), LOC126998428 (UBN1), LOC126997943 (IFT52), LOC126991093 (ACO2), LOC126986070, LOC127001126 and LOC126997895 respectively. Among them, the high temperature damage group shows high methylation at part of the sites, low methylation at part of the sites, and abnormal expression of the corresponding adjacent genes. The above markers can be used for molecular detection and assisted selection of heat tolerance, survival rate maintenance ability, large-size crab output stability and high temperature damage risk of Chinese mitten crab.

A method of assigning a parent to a haplotype, a sub-haplotype, or an allele associated with a haplotype. A chromosomal length haplotype of the genome is generated and a differential methylation status of at least one imprinted differential methylation region (iDMR) associated with each autosomal is determined. The differential methylation status of at least one iDMR is used to assign a parent for each chromosome length haplotype.

The present invention firstly discloses a gene methylation biomarker combination and a screening model for the screening of high-grade cervical lesions. By comparing differentially methylated positions (DMPs) in normal tissues and high-grade lesion tissues, and using the corresponding CpG islands as diagnostic biomarkers for research, the present invention screens out 12 optimal CpG islands with consistent characteristics through a random forest classifier, and establishes a screening model based on the CpG island level of cervical exfoliated cells. This model can perform risk assessment on patients with positive HPV and negative cytology, distinguish high-risk groups from low-risk groups, and recommend different follow-up or intervention measures clinically to achieve patient stratification and effectively improve the accuracy of cervical cancer screening; the screening model has the advantages of high sensitivity and specificity, and objective risk assessment results.

For various purposes, a nucleosome signal pattern using fragmentation at a location around a target site is provided. For example, a nucleosome signal pattern may be used to determine methylation levels of a target site (e.g., a CpG site). The signal may be associated with a nucleosome pattern of a cfDNA molecule within a genomic region that is differentially methylated in a target tissue type by having different methylation levels (or levels, e.g., as a pattern) relative to one or more other tissue types (e.g., blood cells). The nucleosome signal pattern can be compared to one or more reference patterns with known methylation levels. Another exemplary method may determine a lesion level in a subject. Another example may determine a proportional concentration of DNA for a particular tissue type.

The invention discloses a methylation marker identification method for free DNA (deoxyribonucleic acid), which comprises the following steps of: identifying three types of differential methylation regions of abnormal tissues relative to normal control tissues on the basis of the fragment methylation level of whole genome methylation sequencing data; based on the abnormal tissue M-DMR set and the normal control tissue-specific low-methylation region set, identifying a region set in which the tissue-specific low-methylation region is not changed in the abnormality generation process; on the basis of the abnormal tissue U-DMR set and other normal tissue specific low methylation region sets, identifying that a non-tissue specific high methylation region is converted into a region set similar to other normal tissue specific low methylation regions in the abnormality generation process; a set of aberrant DMRs, NT-DMRs, that fall within a non-tissue-specific region on the genome are identified. The novel and accurate methylation mark recognition method is provided, the methylation set area recognized through the method is highly related to the abnormal tissue, and tools and data support can be provided for recognition of the abnormal tissue.

The application discloses a methylation biomarker for diagnosing lung cancer and application thereof, and belongs to the technical field of biomedical detection. The methylation biomarker is composed of 16 differential methylation regions (DMRs), and specific differential methylation regions are shown in Table 2. The application also provides products and devices for diagnosing lung cancer based on the 16 differential methylation regions, and the lung cancer diagnosis has the advantages of high sensitivity and strong specificity, and has important application value for clinical lung cancer diagnosis.

The present invention belongs to the field of bio-pharmaceuticals. Disclosed are a differentially methylated region of an ADHFE1 gene, a detection primer, a probe, a kit, and use of the differentially methylated region in the detection of colorectal cancer or precancerous lesions of colorectal cancer and in the evaluation of prognostic risks of colorectal cancer patients. The differentially methylated region is chr8:67344198-67345563. The differentially methylated region of the present invention can be used for effectively detecting colorectal cancer or precancerous lesions of colorectal cancer, or for evaluating prognostic risks of colorectal cancer patients.

The present invention discloses a molecular typing method, device, computer-readable storage medium and product for medulloblastoma patients, relating to the field of medulloblastoma typing, the method comprising obtaining whole-genome sequencing data; the whole-genome sequencing data comprising: whole-genome sequencing data of normal cerebellum tissue and whole-genome sequencing data of tumor tissue of medulloblastoma patients; performing differential methylation region DMR analysis on the whole-genome cytosine report file of the whole-genome sequencing data; screening, principal component analysis and t-SNE analysis of the DMR analysis results; clustering the t-SNE result matrix using the kmeans clustering method; annotating copy number variation CNV according to the clustering results to obtain the molecular typing results of medulloblastoma patients. The present invention can accurately type medulloblastoma patients.

Methylation arrays and a method of diagnosing or treating a cancer in a subject using differential methylation levels. In one implementation, the method includes the steps of obtaining a cfDNA sample from a subject, probing the cfDNA sample with a plurality of CpG probes, and comparing information from the probed cfDNA sample to a methylation array. The methylation arrays are used to determine a differential methylation level at each of a plurality of limited CpG sites within the cfDNA sample. The plurality of limited CpG sites correspond to the plurality of CpG probes, and two or more of the CpG sites are located on chromosome (2), two or more are located on chromosome (6), and two or more are located on chromosome (16).