159 results about "Methylation Site" patented technology

The invention provides a protein methylation site prediction method fusing quantum and region perception, which comprises the following steps: step 1, acquiring a protein sequence as a data source, and respectively constructing a training set and an independent test set; 2, constructing a multi-modal feature for each protein sequence by adopting a three-way nested scattering network, and fusing the multi-modal features to obtain an optimized fusion feature tensor; and step 3, inputting the optimized fusion feature tensor into a RaQMeNet network model, and performing a methylation site prediction task. The performance indexes of the method are greatly superior to those of the prior art, and the method has higher adaptability, stability and interpretability, can be widely applied to a plurality of bioinformatics and biological medicine related fields such as protein function annotation, disease mechanism research and drug target discovery, and has good application prospects and commercial values.

The invention discloses a method for predicting an RNA (Ribonucleic Acid) methylation site, which is based on a multi-modal feature fusion and semantic vector embedding technology and is used for remarkably improving the recognition precision of an m7G modification site. The method comprises the following steps: firstly, constructing an RNA sequence data set containing positive and negative samples, and dividing the RNA sequence data set into a training set and an independent test set according to a predetermined proportion; then, multi-modal features are extracted through One-hot coding (One-hot), nucleotide chemical property coding (NCP), electron-ion interaction potential coding (EIIP) and local nucleotide composition coding (ENAC), and context semantic information of a nucleotide sequence is obtained in combination with a DNA2Vec model; according to the model, a multi-modal feature fusion path (MRF) and a DNA2Vec embedding path are adopted, after feature dimension compression is carried out through a full connection layer, a Transform encoder is used for capturing a long-range dependency relationship, and a prediction probability is calculated through a Sigmoid activation function. In the optimization process, batch normalization, Dropout and Adam optimizers are adopted, and the binary cross entropy loss function is minimized. Finally, the performance of the model is evaluated through five-fold cross validation, and the generalization ability of the model is verified on an independent test set. According to the method, through multi-source feature fusion and hierarchical modeling, the analysis capability of sequence information is remarkably improved, and an accurate calculation tool is provided for RNA modification prediction.

The invention relates to the technical field of biology, in particular to an MSRE-RPA-CRISPR / Cas12a detection system aiming at a breast cancer methylation site and application of the MSRE-RPA-CRISPR / Cas12a detection system. The MSRE-RPA-CRISPR / Cas12a systems of the four breast cancer methylation sites are constructed and optimized, the visual detection method for the breast cancer methylation sites based on the MSRE-RPA-CRISPR / Cas12a systems is established, the detection method has the advantages of being high in sensitivity, high in specificity and short in detection time, does not depend on large-scale instruments and equipment, the result is visual and visual, and the method is suitable for large-scale popularization and application. The method is suitable for point-of-care testing (POCT).

The present invention discloses an in vitro method for obtaining DNA methylation biomarkers as exquisite DNA methylation positions in the human genome (i.e., CGIDs) that predict cervical cancer especially at as yet inaccessible early stages by examining progression of “categorical” DNA methylation alterations in three stages of premalignant lesions (cervical intraepithelial neoplasia (CIN)), progressing from CIN1 to CIN3. The present invention discloses combinations of CGIDs for detecting with high specificity and sensitivity cervical cancer by measuring their DNA methylation status and deriving a “methylation score”, which is useful as a biomarker for cervical cancer. Also disclosed are kits for predicting cervical cancer using such CGIDs using multiplexed next generation sequencing methylation assays, pyrosequencing assays and methylation specific PCR. The DNA methylation markers (CGIDs) described in the present invention are useful for cervical screening and early detection of cervical cancer by any person skilled in the art to detect cervical cancer.

The present invention relates to the field of gene detection, and particularly to a primer-probe combination, a kit and their applications for detecting the benign and malignant nature of pulmonary nodules. The primer-probe combination includes primer pairs and probes for detecting gene mutation sites and methylation sites, and can achieve simultaneous detection covering the EGFR L858R mutation site, the EGFR 19Del mutation site, and the methylation sites of the HOXA7, CCNA1, and ZNF808 genes at one time. Thus, the present invention is a simple, rapid and accurate combined detection scheme for DNA methylation and gene mutation to assist in differentiating the benign and malignant nature of pulmonary nodules; at the same time, the primer-probe combination can achieve rapid pre-cancer screening, and also has application values such as accurate medication guidance and prognosis and metastasis risk prediction.

The invention belongs to the technical field of bioinformatics and deep learning, and particularly relates to a DNA methylation site prediction method, system and device and an electronic medium, and the method comprises the following steps: respectively coding single bases in a DNA sequence into four molecular fingerprints, and constructing each base into a molecular map structure; performing high-order feature extraction on the four molecular fingerprints through a multi-layer perceptron to generate molecular fingerprint features; modeling the molecular graph structure by adopting a multi-head graph attention network, calculating and normalizing attention scores among nodes, carrying out weighted summation on neighbor node features, and carrying out multi-head attention fusion to generate molecular graph features; splicing the molecular fingerprint features and molecular map features, and inputting the spliced molecular fingerprint features and molecular map features into a deep convolution gated channel attention module to generate fused features; and obtaining a prediction probability of the fused features, and judging whether the features are methylation sites or not according to the prediction probability. According to the invention, the identification capability of methylation sites can be improved.

A method for detecting a methylated genomic locus is provided. In certain embodiments, the method comprises: a) treating a nucleic acid sample that contains both unmethylated and methylated copies of a genomic locus with an agent that modifies cytosine to uracil to produce a treated nucleic acid; b) amplifying a product from the treated nucleic acid using a first primer and a second primer, wherein the first primer hybridizes to a site in the locus that contain methylcytosines and the amplifying preferentially amplifies the methylated copies of the genomic locus, to produce an amplified sample; and c) detecting the presence of amplified methylated copies of the genomic locus in the amplified sample using a flap assay that employs an invasive oligonucleotide having a 3′ terminal G or C nucleotide that corresponds to a site of methylation in the genomic locus.

This invention discloses a method for constructing a gene methylation diagnostic model for differentiated thyroid cancer (PTC). The method includes the following steps: S1, obtaining a test sample; S2, extracting and storing DNA from the test sample; S3, performing methylation analysis; S4, establishing a diagnostic model based on DNA methylation, where the model shows that patients with cg03596178, cg06033721, cg06688989, cg07209244, cg07485775, cg14484681, cg19979108, and cg20943461 are more likely to experience disease progression and are considered risk factors; S5, cross-validating and evaluating the performance to obtain the gene methylation diagnostic model. This model, by detecting and statistically analyzing specific methylation sites, can differentiate patients with recurrent or metastatic characteristics in differentiated thyroid cancer. The relevant model can assist in the clinical diagnosis and follow-up of thyroid patients.

A method, apparatus, storage medium, and program product for tracing the source of disease-affected tissues or organs, the tracing method comprising: acquiring methylation data of multiple tissues or organs, wherein the methylation data of the tissues or organs are methylation data of healthy tissues or organs; establishing an average methylation rate matrix based on the methylation data of multiple tissues or organs, wherein the average methylation rate matrix includes the average methylation rate of each tissue or organ at multiple methylation sites or methylation regions; determining specific methylation sites or specific methylation regions based on the average methylation rate matrix; acquiring methylation data of a sample to be traced; and performing tracing based on the average methylation rate of multiple tissues or organs at the specific methylation sites or specific methylation regions and the methylation data of the sample to be traced.

The invention provides a DNA methylation biomarker for liver cancer detection and application of the DNA methylation biomarker, and belongs to the technical field of biology. The biomarker disclosed by the invention is selected from any one of the following methylation sites: cg13597025, cg00033450, cg20335273, cg06121113, cg27629428, cg02307184, cg15602112 and cg26472334, and the biomarker disclosed by the invention can be used for detecting the methylation sites of the cg13597025 and the cg00033450. The biomarker provided by the invention can be used for noninvasive detection of liver cancer, and has important significance for early screening of liver cancer.

The application belongs to the technical field of molecular biology and medicine, and discloses a methylation marker for detecting the benignity and malignancy of thyroid nodules and an application. 780 new methylation sites are identified, 273 tumor occurrence and development related genes are associated, and the Fc gamma R-mediated phagocytosis signal pathway is involved. The methylation marker for detecting the benignity and malignancy of thyroid nodules comprises multiple genes and multiple methylation sites. The methylation level of multiple genes and multiple sites is detected, the problem of low and unstable methylation signal of single gene or single site is overcome, and thus the sensitivity and specificity of detection are improved.

The invention discloses a novel gene participating in a DNA methylation pathway and application of the novel gene in plant epigenetic regulation. Experiments show that a hypermethylation site exists in an arabidopsis thaliana RMU1 gene promoter region, the methylation level of the arabidopsis thaliana RMU1 gene promoter region is obviously reduced under the background of an RdDM defective mutant, the transcriptional level of the arabidopsis thaliana RMU1 gene promoter region is obviously improved, and it is proved that expression of the arabidopsis thaliana RMU1 gene promoter region is regulated by After the RMU1 gene is mutated, the methylation level of the whole gene is obviously changed, the methylation levels of CHG and CHH sites of the rmu1 mutant in gene upstream and downstream 2kb regions, transposon upstream and downstream 2kb regions and transposon body regions are obviously higher than those of wild arabidopsis thaliana, and the phenomenon is not observed in a gene body region, so that the RMU1 participates in regulating and controlling the DNA methylation level. The arabidopsis thaliana RMU1 gene has important effects and application prospects in epigenetic editing tool development, epigenetic breeding and transposon domestication.

The invention relates to the technical field of colorectal cancer auxiliary detection, and particularly discloses a blood methylation site combination and a detection kit for early diagnosis of colorectal cancer, and the method comprises the following steps: providing a blood sample of a person to be detected for obtaining cfDNA; the cfDNA is subjected to bisulfite treatment, and the transformed DNA is obtained; amplifying the transformed DNA by using a multiplex fluorescence PCR (Polymerase Chain Reaction) method to obtain fluorescence signal data of each gene; calculating a Ct value of each gene based on the fluorescence signal data, comparing the Ct value with a preset Cut-off value, and judging whether the colorectal cancer exists or not; according to the present invention, the invasive operation of the colonoscope can be replaced, the screening can be completed through the blood sample, the patient compliance can be significantly improved, the method is suitable for the large-scale early screening, the trace tumor signal in the blood can be efficiently captured based on the methylation marker highly related to the colorectal cancer, and the accurate early canceration identification can be achieved.

The invention relates to a tumor-related DNA methylation marker combination, which is selected from at least one of the following: a target sequence as shown in SEQ ID NO: 1-SEQ ID NO: 10, a nucleic acid fragment with the length of at least 15 oligonucleotides or a complementary nucleic acid fragment thereof, and the nucleic acid fragment comprises at least one methylation site indicated by CG. The invention also relates to a detection kit for the methylation marker combination. According to the invention, the combination of the co-methylation states of a plurality of specific methylation regions is used for distinguishing and analyzing the occurrence of tumors, especially kidney cancer, the specific methylation combination has high sensitivity for distinguishing the occurrence of kidney cancer, and the detection method is simple, convenient and feasible. The primer pair combination of the kit overcomes the defect of false positive caused by detection mismatch of a single methylation site in the aspect of primer sequence design, and the interaction between a plurality of methylation biomarker primers and probe pair combinations is considered.

The present invention relates to a method of evaluating the effect of at least one test component of an animal feed on at least the performance and / or the overall health of a test animal consuming an animal feed having the test component, the method comprising the steps of: (a) determining a test methylation profile of one or more preselected methylation sites within the DNA of the test animal; (b) comparing the test methylation profile from (a) to at least one control methylation profile from a control animal consuming animal feed free of the test component belonging to the same biologic classification unit as the test animal; and wherein the results of (a) are used to determine the performance and / or overall health of the test animal; and (c) comparing the test methylation profile from (a) to (i) a first reference methylation profile from a control animal having good performance and / or overall health belonging to the same biologic classification unit as the test animal; and / or (ii) a second reference methylation profile derived from a control animal having poor performance and / or overall health, belonging to the same bioclassification unit as the test animal; and wherein a significant similarity of the test methylation profile of (a) compared to the control methylation profile indicates that the test component has no effect on the performance and / or overall health of the test animal; and wherein a significant difference in the test methylation profile of (a) compared to the control methylation profile indicates that the test component has an effect on the performance and / or overall health of the test animal; and wherein a significant similarity of the test methylation profile of (a) to the first reference methylation profile and / or a difference of the test methylation profile of (a) to the second reference methylation profile indicates that the test animal has good performance and / or overall health as a control cell; and / or wherein the difference in the test methylation profile of (a) compared to the first reference methylation profile and / or the significant similarity of the test methylation profile of (a) to the second reference methylation profile indicates that the test animal has poor performance and / or overall health as a control animal; and wherein the test animal is selected from livestock or poultry.

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 discloses a kind of based on DNA methylation's construction method of biological age prediction model, the application is downloaded from GEO data website, derived from Chinese population, contains calendar age data, whole blood sample 450k methylation chip data, by the method of elastic network combined bootstrap, 31 methylation sites of modeling candidate are screened, multiple linear regression, support vector machine, random forest and gradient boosting regression tree are used to carry out preliminary construction and evaluation of model, then further filter methylation sites using full subset regression, obtain methylation age prediction model based on 18 methylation sites.Finally, using any provincial team natural population data, methylation age prediction model is optimized, and finally the biological age prediction model based on 18 methylation sites is obtained.The model is suitable for Chinese population, the number of methylation sites contained is less, is not affected by blood cell components, and the prediction accuracy is good.

Compositions and methods for diagnosing epithelial ovarian cancer (EOC) and assessing the prognosis thereof are provided. Development of an artificial intelligence method named MethylBert and its use in the identification of methylation sites useful for the identification of EOC in free DNA obtained from serum or plasma are shown. A PCR-based method for the methylation status of the OV-1 site identified using the McthylBERT method can be used to screen EOC using free DNA obtained from a blood sample, and can be combined with the measurement of EOC-related tumor markers.

The application discloses a DNA methylation site marker for detecting hepatocellular carcinoma, a multiplex dPCR kit and a diagnostic model construction method. The DNA methylation site marker comprises cg02829688, cg13080379, cg03760839, cg10703826, cg12664119, cg16990168 and cg23371746 sites. The application designs a primer probe group for the above sites, constructs a multiplex dPCR kit of a double reaction system, realizes quantification of target DNA methylation sites, takes the methylation levels of the 7 sites as characteristic variables, adopts an XGBoost algorithm and / or an LR algorithm to construct a diagnostic model. Experimental verification shows that the model can effectively distinguish hepatocellular carcinoma patients from liver cirrhosis, chronic hepatitis B, metabolic dysfunction-related fatty liver disease patients and healthy individuals, especially shows good efficiency in auxiliary diagnosis of early hepatocellular carcinoma, and provides a new technical scheme for clinical diagnosis and screening of hepatocellular carcinoma.

This invention relates to the field of biotechnology, and in particular to a primer-probe combination for detecting methylation sites in cancer and its applications. This invention is the first to discover that abnormal methylation at specific sites of the TRIB3 gene is significantly associated with the occurrence and development of colorectal cancer, and abnormal methylation at specific sites of the MAPT gene is significantly associated with the occurrence and development of gastric cancer. This correlation has not been publicly reported in the prior art, possessing novelty and significant clinical application value. The primer-probe combination provided by this invention is used to detect the methylation status of the TRIB3 gene or the MAPT gene in a sample. Specifically, when the primer-probe combination is used to detect the methylation level at specific sites of the TRIB3 gene, it can be used for the auxiliary diagnosis, early screening, or risk assessment of colorectal cancer; when the primer-probe combination is used to detect the methylation level at specific sites of the MAPT gene, it can be used for the auxiliary diagnosis, early screening, or risk assessment of gastric cancer.

This invention provides an esophageal cancer diagnostic kit based on multi-gene methylation level detection. It detects the methylation status of esophageal cancer gene methylation sites, including ZNF154, RNF126, C2ORF27A, OTOP2, TM4SF19, and P16, thereby enabling early screening of esophageal cancer samples. Furthermore, this kit, combined with digital PCR, offers advantages such as absolute quantification, high batch-to-batch stability, and high sensitivity, accurately distinguishing the relationship between sample gene methylation and esophageal cancer. Simultaneously, it employs fluorescently labeled probes for genotyping, demonstrating high specificity and applicability to esophageal cancer patients at different stages. Therefore, it provides a convenient, rapid, and accurate detection method for early screening, diagnosis, and prognosis of esophageal cancer, possessing significant clinical value.

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.

The invention relates to a methylation site marker for assisting in early diagnosis of esophageal squamous cell carcinoma and application of the methylation site marker, and belongs to the technical field of biomedicine. The methylation site marker is one or a combination of human peripheral blood mononuclear cell methylation sites cg05064044, cg03395511 and cg21548813, and the nucleotide sequence of the methylation site marker is as shown in SEQ ID NO. 1-3. According to the present invention, the methylation chip detection results show that the methylation levels of the cg05064044, the cg03395511 and the cg21548813 in the peripheral blood mononuclear cells of the esophageal squamous cell carcinoma patient are significantly increased compared to the health control group; the methylation levels of cg05064044, cg03395511 and cg21548813 sites in PBMC of esophageal squamous cell carcinoma patients in a training queue and a verification queue are all obviously higher than those of a healthy control group through further analysis. Finally, through ROC curve analysis, it is determined that the three methylation sites cg05064044, cg03395511 and cg21548813 have good specificity and sensitivity, have high diagnosis efficiency when being independently or jointly used for esophageal squamous cell carcinoma diagnosis and can be used as potential molecular markers for esophageal squamous cell carcinoma diagnosis.

The invention discloses a methylation marker combination for detecting gastric cancer, a corresponding primer probe combination, a kit and application thereof. The methylation marker combination related to the gastric cancer comprises a CpG methylation site cg08630279 of a ZNF569 gene, a CpG methylation site cg24773720 of a GHR gene and a CpG methylation site cg20622089 of a CNR1 gene, wherein the CpG methylation site cg08630279 of the ZNF569 gene, the CpG methylation site cg24773720 of the GHR gene and the CpG methylation site The methylation levels of the ZNF569, GHR and CNR1 sites are related to gastric cancer staging, and the ZNF569, GHR and CNR1 sites can be used as high-specificity markers for early screening of gastric cancer. A primer probe combination for detecting the marker combination comprises specific upstream primers, downstream primers and probes aiming at methylation sites of all markers. The kit comprises a primer probe combination, and also comprises a positive control, a negative control and a quality control reagent. Three-site combined detection is adopted, the detection sensitivity in a gastric cancer blood sample reaches 91% or above, the specificity reaches up to 100%, the kit is used for auxiliary screening, detection or molecular analysis related to gastric cancer and precancerous lesions of the gastric cancer, and a technical scheme high in sensitivity, high in specificity and good in repeatability is provided for clinical detection.

A method of determining percentages of twelve blood cell subtypes in a blood specimen, includes steps of: (a) obtaining genomic DNA from the blood specimen of a human subject, (b) observing unmethylated CG loci, in the genomic DNA of the human subject, wherein said observing includes performing a bisulfate conversion process on the genomic DNA of the human subject so that cytosine residues in the genomic DNA of the human subject are transformed to uracil, while 5-methylcytosine residues in the genomic DNA of the human subject are not transformed to uracil, (c) comparing the unmethylated CG loci observed in (b) to unmethylated CG loci observed in genomic DNA collected from a reference group of human individuals and (d) correlating the unmethylated CG loci observed in (b) with the unmethylated CG loci observed in the reference group of human individuals to determine the percentage of the twelve blood cell subtypes in the blood specimen.

The invention relates to the technical field of biology, and discloses a multiplex fluorescent PCR detection system and application thereof, the multiplex fluorescent PCR detection system comprises 22 primer pairs, and primer sequences aiming at 22 sites are disclosed and are respectively used for simultaneously amplifying 15 detection sites and 7 internal reference sites. The multiplex fluorescent PCR detection system provided by the invention realizes effective detection of a plurality of methylation sites by combining capillary electrophoresis detection, performs high-sensitivity and specific detection on colorectal cancer by combining a corresponding detection method and a result judgment method, and has important clinical application value and wide market prospect.

The invention discloses a screening method of skeletal muscle senescence markers, clock construction and a kit, and belongs to the technical field of biomedical engineering. The method comprises the following steps: acquiring multi-modal biomarker data of an individual, wherein the multi-modal biomarker data comprises an inflammatory marker, a metabolic marker, a hormone marker and a muscle function marker; inputting the data into a trained skeletal muscle biological age prediction model to obtain skeletal muscle biological age (SMBA); based on the skeletal muscle biological age (SMBA), screening out a specific methylation site set related to the skeletal muscle senescence state from the methylation sites of the whole genome; constructing a methylation aging clock model by using methylation data of the site set; and finally, accurately predicting and evaluating the skeletal muscle senescence state of an individual by using the model. According to the invention, conversion from multi-modal clinical indexes to specific single-dimensional molecular markers is realized, and the constructed senescence clock model and derivative products can be used for personalized evaluation and early risk early warning of skeletal muscle senescence.

Provided are a method and a combination for one-tube simultaneous detection of tumor-specific gene mutation and methylation, and the use thereof. The method comprises searching a database to select mutation and methylation sites of a cancer driver gene and a cancer suppressor gene, synthesizing capture probes correspondingly paired with a target interval, performing hybrid capture on an amplification product of a sample treated with a restriction endonuclease by using a probe set comprising tumor-specific gene mutation and methylation capture probes, constructing a high-throughput sequencing library containing a target region, and performing high-throughput sequencing to obtain the sequence of a target fragment, so as to obtain the results of methylation, point mutations and indel variation of a cancer-associated gene. The provided method enables one-tube simultaneous detection of mutation and methylation states of a cancer-associated gene in one assay, requires a low content of a gene to be detected, can be used for methylation and mutation detection of a tumor-specific DNA, and has low detection costs and high efficiency.

The present invention discloses a method for predicting 2'-O-methylation sites in RNA based on ensemble learning, belonging to the technical field of bioinformatics. In view of the characteristics of RNA sequences, the present invention performs task-specific fine-tuning on the Promoter-BERT model, enabling it to more effectively capture the complex patterns of RNA sequences in specific tasks, thereby obtaining high-quality biological feature representations; the ANOVA technique is used to select the extracted features, eliminating redundant features and retaining the most influential features. In addition, traditional sequence features are combined with the embedded features obtained through the Word2Vec model to enhance the expressive power of the model; the prediction results of the lightweight gradient boosting machine and the deep learning model are combined, and a final prediction model is formed through a soft voting mechanism. This ensemble method not only improves the generalization ability of the model but also increases the stability of the prediction.

The invention discloses a methylated biomarker for diagnosing gastric cancer and application of the methylated biomarker. The invention provides a methylation biomarker for diagnosing gastric cancer, and the methylation biomarker comprises a methylation region which is equal to and / or complementary to at least one of target sequences as shown in SEQ ID NO.1-6 and fragments of the target sequences as shown in SEQ ID NO.1-6, and the methylation region comprises at least one methylation site indicated by CG. The methylated biomarker provided by the invention can be used for diagnosing gastric cancer, and has good sensitivity, specificity and accuracy.