102 results about "CpG site" patented technology

The invention discloses a biomarker combination for predicting calendar age, a model and application of the biomarker combination. 57 kinds of DNA methylated CpG sites screened from many elderly subjects are creatively introduced, through multiple detection and large-scale parallel DNA sequencing, operation is easy, the result is highly repeatable, and the age prediction model constructed based on the method is good in stability and accuracy and high in sensitivity and has good application prospects. Calendar age can be predicted from trace blood samples associated with forensic cases.

Systems and method as described herein may determine and use methylation levels associated with various tissues and samples. For example, a method may include receiving sequence reads including methylation statuses at sites of cell-free DNA molecules. The method may further include aligning the sequence reads to N sets of one or more CpG sites or genes. Then, for each set of the N sets of one or more CpG sites or genes, the method may include identifying a group of sequence reads aligning to the set of one or more CpG sites or genes and determining a methylation level using the methylation statuses of the group of sequence reads.

The invention provides a biomarker, a kit and a method for predicting the aging-related physiological age of a mouse, the biomarker comprises a plurality of CpG sites with different methylation levels, and the position information of the CpG sites is as follows: chr10: 122698929, chr11: 22600252, chr12: 86422875, chr13: 49379202, chr14: 55116926, chr15: 86222032, chr16: 87766091, chr17: 55971541, chr1: 109982829 and the like. The method can solve the problem of high cost of detecting the physiological age of the mouse through methylation level in the prior art, and is suitable for the field of animal age detection.

The invention relates to the technical field of bioinformatics, in particular to a method for identifying an abnormally hypermethylated region in cancer methylation data. The method comprises the following steps: acquiring whole genome methylation sequencing data of a sample to be detected and genome conserved sequence data of primate species; performing density analysis based on a progressive hierarchical scanning strategy on the CpG loci according to the whole genome methylation sequencing data to obtain CpG enriched region data; performing distance calculation including short-range, medium-range and long-range on the genome conservative sequence data, and performing weighted correction on a calculation result according to the CpG enrichment region data to obtain region conservative score data. According to the method, through unsupervised clustering, self-adaptive threshold setting and multi-scale feature extraction, high methylation regions with high regulation and control effects in different cancer types can be more accurately captured.

Disclosed are methods of preparing a composition of non-naturally occurring DNA, comprising: (a) extracting DNA from a sample of a subject; (b) contacting the extracted DNA or its derivative with a panel of oligonucleotide probes designed to hybridize to a plurality of preselected genomic regions, thereby generating selected DNA, wherein at least 50% of the preselected genomic regions are CpG regions that each comprises at least 3 CpG sites and a CpG density of at least 0.02 CpG / bp, wherein the preselected genomic regions cover 10-500 Mb of sequence space in human genome, wherein the extracted DNA or its derivative or the selected DNA or its derivative is further treated with an agent or a combination of agents that discriminates between methylated and unmethylated cytosines; and (c) performing high-throughput sequencing on the selected DNA or its derivative and generating sequencing reads.

The present application relates to a method and system for inferring the age of an individual from semen or a semen stain, and a methylation detection kit, which comprises the following steps: firstly, extracting the genomic DNA of the semen or semen stain of the individual; secondly, performing bisulfite treatment on the genomic DNA; thirdly, selecting a plurality of sites in the CpG sites in the genomic DNA and amplifying the selected CpG sites to obtain the methylation rate of the selected CpG sites; and finally, performing regression analysis on the methylation rate of the selected CpG sites and the age of the individual to construct a regression model for inferring the age of an unknown individual from semen or a semen stain. The average absolute error of the present application reaches 1.68 to 4.44 years.

The present application relates to the technical field of bioinformatics, and particularly relates to a method for constructing a biological age prediction model based on DNA methylation. The method comprises the following steps: obtaining whole genome methylation sequencing data of a human peripheral blood sample; classifying cell subpopulations of the human peripheral blood sample, and performing single-cell RNA sequencing processing on each cell subpopulation to obtain single-cell sequencing data including lymphocytes, neutrophils and monocytes; performing tissue-specific analysis on CpG sites within a range of 2000 base pairs upstream and downstream of each cell subpopulation-specific transcription factor binding site according to the single-cell sequencing data and the whole genome methylation sequencing data to obtain candidate marker site data. The present application can provide strong support for early detection of accelerated aging, prediction of related disease risks and guidance of precision medicine.

The present invention relates to a tetracyclic compound and a use thereof. Specifically, the present invention provides a use of a compound of formula I, or an optical isomer, a racemate, a solvate, a pharmaceutically acceptable salt, or a deuterated compound thereof in the preparation of a composition or a formulation for preventing and / or treating tumors. The compound of the present invention has an excellent precise treatment effect on tumors with low or no expression and low or no activity of mitochondrial membrane permeability pores, low or no expression and low or no activity of recombinant peptidylprolyl isomerase F, low or no expression of NNMT gene, high expression of DNA methylases, high expression of UHRF 1, a high methylation level at a nucleotide site of the NNMT gene, and / or a high methylation level at a DNA CpG site of a NNMT gene region.

The present invention provides a device and a method capable of constructing a model that has high prediction accuracy and is suitable for a specific group from a small number of DNA methylation data items obtained from the specific group while reducing the number of samples required for model construction. A biological age measurement device 1 according to the present invention measures the biological age on the basis of the DNA methylation level. By using, as an explanatory variable matrix (n×p matrix (p≤q)), first explanatory variable information based on DNA methylation information in CpG sites at q points included in DNA of each sample of a first population composed of n samples, and using, as an objective variable vector (n-dimensional), first objective variable information based on biological age information of the n samples, the biological age measurement device 1 performs transfer learning on the basis of a biological age measurement model estimated by a second population different from the first population, and outputs the learning result as a trained biological age measurement model.

The present invention is related to a method of determining suitability of at least one Chinese Hamster Ovary (CHO) test cell line for optimal heterologous protein production, the method comprising:(a) determining a test methylation profile from genomic material obtained from the CHO test cell line; and(b) comparing the test methylation profile obtained from (a) with a reference methylation profile, wherein the reference methylation profile comprises the methylation status of more than one CpG site from at least one CHO reference cell line that displays at least one phenotype of interest for optimal heterologous protein production,wherein a significant similarity in the test methylation profile of (a) compared to the reference methylation profile, is indicative of the CHO test cell line being suitable for optimal heterologous protein production and wherein the test methylation profile and reference methylation profile are from CpG sites from the CHO cell genome and are determined using DNA methylation-bead-based array.

The invention belongs to the technical field of information analysis, and particularly relates to a whole genome methylation region splitting method based on a co-methylation state of adjacent CpG loci. On the basis of whole genome methylation sequencing data, methylation regions are split within a whole genome range according to the co-methylation state of adjacent CpG sites, more methylation region information is provided for diagnosis of diseases such as cancers, and the effect of improving the methylation signal-to-noise ratio of the diseases such as the cancers is achieved.

The invention relates to the technical field of judicial expertise, in particular to a segmented blood DNA methylation age prediction method and system based on an SVR model, and the method comprises the steps: collecting a DNA sample of a to-be-evaluated object; measuring the methylation level of a predetermined CpG site on the DNA sample to obtain a methylation level parameter; and predicting the age of the to-be-evaluated object according to the methylation level parameter. In order to solve the problem that the prediction error of a prediction method in the prior art is obviously increased along with the increase of age groups, in the scheme, firstly, the age interval of a to-be-evaluated object is predicted, then a prediction model on the corresponding interval is called in each age interval, and effective point locations screened out in the regression analysis process are combined, so that the prediction accuracy of the to-be-evaluated object is improved. The age of the to-be-evaluated object is accurately predicted, and the influence of the age interval on the age prediction error is improved.

The present invention relates to a method for assessing the prognosis or risk stratification of liver cancer by using a clinical specimen mixed with a normal tissue, wherein at least one CpG site that shows a low methylation level in normal and blood tissues but a high methylation level in only a cancer tissue is measured for methylation level.

A multi-modal pan-cancer early prediction method is disclosed, comprising: collecting cfDNA samples of i cancer populations and healthy populations respectively and extracting methylation data; merging CpG sites based on the methylation data to obtain multiple methylation intervals, screening multiple candidate marker intervals from the multiple methylation intervals, and further screening the multiple candidate marker intervals; training a first prediction model using the multiple candidate marker intervals, training a second prediction model based on the fragmentation characteristics of the chromosomes extracted from the reference genome, and training a third prediction model by extracting the methylation entropy characteristics of the chromosomes; training a multi-modal pan-cancer early prediction model through the cancer population prediction values of the first prediction model, the second prediction model and the third prediction model, which can provide precise joint early screening for lung cancer, intestinal cancer, gastric cancer, liver cancer, esophageal cancer, thyroid cancer and ovarian cancer.

Systems and methods of identifying methylation patterns discriminating or indicating a cancer condition are provided. First and second datasets are obtained. Each dataset comprises a plurality of fragment methylation patterns determined by methylation sequencing of nucleic acids obtained from a first or second set of subjects and comprising a methylation state of each CpG site in a corresponding plurality of CpG sites. Each plurality of subjects has a respective first or second state of the cancer condition. First and second interval maps are generated for each respective dataset, each comprising a plurality of nodes characterized by a start methylation site, an end methylation site, a representation of each different fragment methylation pattern and a count of fragments. The first and second interval maps are scanned for qualifying methylation patterns within a predetermined range of CpG sites, satisfying one or more selection criteria, thereby identifying methylation patterns discriminating a cancer condition.

The application provides a cancer primary focus tracing method, device, system and storage medium, and relates to the technical field of cancer tracing. The cancer primary focus tracing method comprises the following steps: acquiring sample tissue data, giving each cancer sample a primary focus label through a methylation chip; determining candidate CpG sites; and constructing a cancer tracing classifier. The application realizes the technology of tracing multiple cancers by using DNA methylation biological characteristics and machine learning methods, and has the following characteristics: due to the high stability of DNA molecules, cancer information is relatively completely retained, so that sample storage and transportation are more convenient; the cancers targeted by the application have a wide coverage range and include general common tumors; cancer-specific CpG sites have a wide coverage; through analysis of the cancer-specific sites, the interference of normal tissues is excluded, so that the accuracy and application range of the classifier are improved; and the high-precision classifier makes the cancer diagnosis process simpler, more accurate and more efficient.

Systems and method as described herein may determine and use methylation levels associated with various tissues and samples. For example, a method may include receiving sequence reads including methylation statuses at sites of cell-free DNA molecules. The method may further include aligning the sequence reads to N sets of one or more CpG sites or genes. Then, for each set of the N sets of one or more CpG sites or genes, the method may include identifying a group of sequence reads aligning to the set of one or more CpG sites or genes and determining a methylation level using the methylation statuses of the group of sequence reads.

The present invention belongs to, but is not limited to, the field of biotechnology, and discloses a method and system for predicting DNA methylation age based on the uniAge model, comprising the following steps: screening out CpG sites that can be covered by both RRBS and methylation chips; using DNAme chip data of human peripheral blood to screen sites and train a prediction model for age in the common CpG sites; correcting the DNAme level obtained from sequencing data to align with the chip data, or separately fitting model coefficients on the sequencing data using the screened CpG sites. The present invention predicts an individual's age using the DNAme levels of several CpG sites in peripheral blood; and trains an age prediction model that is applicable to both methylation chip data and sequencing data.

Systems and methods for diagnosing a disease, a condition, or a characteristic in a subject are provided. In one such method, a future severity of an infection or inflammatory disease in a subject afflicted with the infection or inflammatory disease is predicted by obtaining a plurality of methylation levels. Each respective methylation level in the plurality of methylation levels represents a corresponding methylation level at a CpG site at a corresponding genetic locus in a plurality of genetic loci in a biological sample obtained from the subject. The plurality of methylation levels are inputted into a model comprising a plurality of parameters, where the model applies the plurality of parameters to the plurality of methylation levels to generate as output from the model an indication as to future severity of an infection or inflammatory disease in the subject.

The present invention discloses an application of a reagent for detecting the methylation level of molecular markers in the preparation of a reagent product for detecting primary hepatocellular carcinoma, belonging to the technical field of gene detection. This solution can identify whether the patient from whom the sample is derived is a patient with primary hepatocellular carcinoma by detecting the methylation level of CpG sites in the region of chr17: 30970241-30970741. If the target sample is from a patient with primary hepatocellular carcinoma, the CpG sites in the above region are at a high methylation level; if the target sample is from a healthy person or a patient with a benign liver disease (such as cirrhosis, hepatitis, etc.), the CpG sites in the above region are at a low methylation level. The CpG sites in this region can be used to distinguish between samples from patients with primary hepatocellular carcinoma and samples from healthy people, as well as between samples from patients with primary hepatocellular carcinoma and samples from patients with benign diseases (such as cirrhosis, hepatitis, etc.).

The invention provides a gene methylation marker screening method, a kit, a storage medium and a system, and belongs to the technical field of gene detection.The gene methylation marker screening method comprises the steps that methylation chip sequencing data conforming to known typing of adult diffuse glioma is collected; aiming at a selected subtype, comparing methylation level differences of a CpG site in the subtype and other subtypes and contrasting brain tissues, and screening out a marker with a high median methylation level in a subtype sample; and according to the distinguishing contribution degree of each methylation marker in the random forest model to the classification result, carrying out importance evaluation on the marker, and screening out the key methylation marker having positive contribution to the classification result. On the basis of 11 methylation markers, an NGS detection method is adopted for typing the diffuse glioma of the adult, so that the problems that multiple molecular detection results in multiple omics need to be integrated in the conventional typing method, or the typing cost is high and the time period is long when a methylation chip is used for typing are solved.

The present invention relates to an in vitro method for predicting the chronological age of a test Chinese Hamster Ovary (CHO) cell or population of test CHO cells, the method comprising the steps of: (a) determining the test methylation level of a set of specific CpG sites from genomic material obtained from the test CHO cell or from the population of test CHO cells from a CHO cell line using a DNA-methylation bead-based array; (b) comparing the test methylation level determined from step (a) with a reference methylation level of the same set of specific CpG sites from an age-correlated reference sample, thereby establishing the epigenetic age and predicting the chronological age of the test CHO cell or the population of test CHO cells wherein the set of specific CpG sites comprises at least 10%, preferably 30%, more preferably 50% of the CpG sites indicated in Table 1.

A method of identifying oxidative stress caused by ageing and / or ultraviolet (UV) light exposure in a test cell. The method includes determining the methylation status of at least one CpG site in Protein Tyrosine Phosphatase Receptor Type N2 (PTPRN2), and / or the regulatory region of PTPRN2 in a DNA sample obtained from the test cell, and comparing the methylation status of the CpG site of PTPRN2 with that of a control without oxidative stress caused by ageing and / or UV light exposure. A difference in the methylation status of the CpG site of PTPRN2, and / or the regulatory region of PTPRN2 in the test cell compared to the CpG site in the control is indicative of the test cell having oxidative stress caused by exposure of the cell to UV light and / or ageing.

The present invention relates generally to methods of screening for rheumatoid arthritis, as well as kits for screening for rheumatoid arthritis. More particularly, the invention relates to a method of screening for rheumatoid arthritis in a subject, the method comprising using methylation levels of CpG sites in DNA from a biological sample obtained from the subject in order to screen for rheumatoid arthritis in the subject, wherein said methylation levels are used to provide an indication of the presence or absence of rheumatoid arthritis in the subject.

The invention relates to the technical field of molecular biology, in particular to a methylation marker for Down's syndrome diagnosis. The invention particularly relates to application of a detection reagent for detecting the methylation level of a CpG site of a nucleic acid marker in preparation of a Down's syndrome diagnostic kit. The nucleic acid marker comprises a) an SIM2 gene segment as shown in SEQ ID NO: 1 or a polynucleotide segment complementary to the SIM2 gene segment, and / or b) a CRYBG1 gene segment as shown in SEQ ID NO: 2 or a polynucleotide segment complementary to the CRYBG1 gene segment.

A method for screening a cell-free DNA marker, a DNA marker and the use thereof. The method for screening the cell-free DNA marker comprises: collecting a verified positive experimental sample and a control group sample; performing nucleotide sequencing on the positive experimental sample and the control group sample by means of a methylation sequencing method, wherein the sequencing method follows: segmenting CpG sites; and determining, according to whether average methylation quantification values of the segmented positive sample and control sample at the CpG sites meet specific criteria, whether the CpG sites can become candidate markers. Samples are obtained in a non-invasive manner, the screened markers have a high tolerance to detection noise, and the signal of the control group is clean. The detection features high sensitivity and strong anti-interference capability, and the accuracy of a single marker is not required. The reproducibility is high, which is suitable for large-scale popularization.

The invention relates to the technical field of biological information, in particular to a methylation sequencing data processing method and system. The method comprises the following steps: acquiring local sequence characteristic data of a DNA sample, wherein the local sequence characteristic data comprises GC content data of 20 basic groups before and after each CpG site, ion concentration data and environment temperature data; performing conformation state prediction on the DNA molecules according to the local sequence characteristic data to obtain thermodynamic parameter matrix data containing melting energy, base accumulation energy and ion acting force; on the basis of the Brown kinetics theory, a motion track model of DNA molecules under thermal disturbance is constructed according to thermodynamic parameter matrix data, and conformation state transition data of all CpG sites are obtained. The sequencing deviation is simulated and corrected through Brown dynamics according to DNA sequence characteristics and thermodynamic parameters, so that the accuracy of methylation sequencing data is improved.

The invention discloses a stem cell culture generation identification method based on an epigenetics clock. Belongs to the field of biotechnology and molecular biology, and designs a specific multiple PCR primer pool and establishes a high-precision generation prediction model by screening eight CpG sites highly related to stem cell replicative senescence. The method comprises the following steps: firstly, carrying out hydrosulfite conversion on sample DNA (Deoxyribonucleic Acid), carrying out targeted amplification by adopting a primer group with an optimized ratio, calculating a methylation level through high-throughput sequencing, and substituting into a formula to output a result. The model has small mean absolute error and is significantly related to aging function indexes. Compared with traditional chip detection, the cost is reduced, the detection period is shortened, and the method is suitable for release inspection of stem cell treatment products, anti-aging drug screening and cell bank quality management.

A recombinant prion protein (PRNP) gene-specific epigenetic editor is disclosed, comprising an unmethylated H3K4meO peptide, a DNMT3 methyltransferase-binding domain, and a PRNP gene-specific DNA binding domain. Expression of the epigenetic editor is non-toxic, and effective at silencing prion gene (PRNP) expression through DNA methylation (DNAme) at CpG sites within the PRNP promoter region. The PRNP-specific epigenetic editor should provide an AAV gene therapy approach for the treatment of prion diseases.

The present application relates to the field of DNA methylation modification detection, and particularly relates to nucleic acid sequence molecules and DNA methylation detection methods. The nucleic acid sequence molecules comprise at least a probe sequence, the probe sequence comprises at least one CpG site, at least one of which is a to-be-detected CpG site; the probe sequence comprises a methylation probe sequence and a non-methylation probe sequence, and the two probe sequences are modified with different fluorescent groups; and the probe sequence at least meets one of the following conditions: i) within the region of the to-be-detected CpG site and the 2 nt upstream and downstream of the to-be-detected CpG site, the overall GC content of the methylation probe is not more than 50%; ii) within the region of the to-be-detected CpG site and the 2 nt upstream and downstream of the to-be-detected CpG site, the overall GC content of the methylation probe is more than 50%, and the to-be-detected CpG site in the probe sequence is modified with LNA. The method of the present application can significantly improve the specificity and sensitivity of CpG site methylation detection.