31 results about "Nucleic acid methylation" patented technology

Provided are systems and methods for cell-free nucleic acid sequencing to assess a condition.Generally, cell-free nucleic acid samples are used to perform methyl sequencing, targeting specific regions associated with abnormal methylation.The methylation of cell-free nucleic acid molecules can be evaluated based on sequencing results.Various features can be derived from methylation evaluation and used in computational models to assess cell-free nucleic acid samples for a condition.

The present invention provides systems and methods for sequencing cell free nucleic acids to assess a condition. Generally, methylation sequencing for specific regions associated with aberrant methylation is performed using a cell free nucleic acid sample. Based on the results of the sequencing, methylation of the cell free nucleic acid molecule can be assessed. Various features may be derived from methylation assessment and used within a computational model to assess a cell free nucleic acid sample for a condition.

The present disclosure provides methods and systems for screening or detecting a colorectal cancer or following colorectal disease progression that may be applied to cell-free nucleic acids such as cell-free DNA. The method may use detection of methylation signals within a single sequencing read in identified genomic regions as input features to train a machine learning model and generate a classifier useful for stratifying populations of individuals. The method may comprise extracting DNA from a cell-free sample obtained from a subject, converting the DNA for methylation sequencing, generating sequencing reads, and detecting colon proliferative cell disorder-associated signals in the sequencing information and training a machine learning model to provide a discriminator capable of distinguishing groups in a subject population such as healthy, cancer or distinguishing disease subtype or stage. The method may be used for, e.g., predicting, prognosticating, and / or monitoring response to treatment, tumor load, relapse, or colorectal cancer development.

The disclosure relates to methods for determining the methylation profile of nucleic acids. The methods use base conversion methods in combination with methylation-based partitioning methods to resolve multiple types of methylation in a single workflow.

The present disclosure provides methods and systems for screening or detecting colorectal cancer or subsequent colorectal disease progression, which can be applied to cell-free nucleic acids, such as cell-free DNA. The methods can train a machine learning model using detection of methylation signals within single sequencing reads in identified genomic regions as input features, and generate a classifier suitable for stratifying a population of individuals. The methods can include extracting DNA from a cell-free sample obtained from a subject, transforming the DNA for methylation sequencing, generating sequencing reads, and detecting colon proliferative cell disorder related signals in the sequencing information, and training a machine learning model to provide a discriminator capable of distinguishing between groups such as healthy, cancer, etc. in a population of subjects, or distinguishing between disease subtypes or stages. The methods can be used, for example, to predict, prognosticate, and / or monitor response to treatment, tumor burden, recurrence, or progression of colorectal cancer.

Methods and systems provided herein address current limitations of bisulfite-based methylation sequencing by improving the quality and accuracy of nucleic acid methylation sequencing and uses thereof for detection of disease. Methods that include minimally-destructive conversion methods for methylation sequencing as well as specialized UMI adapters provide for improved quality of sequencing libraries and sequencing information. Greater accuracy and more complete methylation-state information permits higher quality feature generation for use in machine learning models and classifier generation.

The invention provides a construction method of a high-throughput sequencing library. The method comprises the following steps: carrying out nucleic acid interruption in a single-tube reaction chamber by adopting transposase with a universal joint, adding the universal joint, and then carrying out at least two rounds of ligation reactions in a branched-combination combination manner to introduce different tag combinations into genome fragments of each cell, thereby obtaining a sequencing library. The homogeneity of cell transposase breaking treatment is higher, the nucleic acid tag connection process is easier to operate, the cell flux covered by single sequencing is improved, the cost is lower, and the method is compatible with a single-cell multi-omics sequencing method.

Methods and systems provided herein address current limitations of bisulfite-based methylation sequencing by improving the quality and accuracy of nucleic acid methylation sequencing and uses thereof for detection of disease. Methods that include minimally-destructive conversion methods for methylation sequencing as well as specialized UMI adapters provide for improved quality of sequencing libraries and sequencing information. Greater accuracy and more complete methylation-state information permits higher quality feature generation for use in machine learning models and classifier generation.

The present disclosure is directed to an array comprising one or more capture sites, wherein the capture sites comprise one or more nucleic acid probes immobilized on a solid support, and wherein the nucleic acid probes comprise: (a) a first clustering adapter sequence and a second clustering adapter sequence; (b) a spatial barcode (SBC) sequence; (c) a sequencing adapter sequence; (d) a restriction enzyme recognition site (RS region); and (e) a random region (X region); and its use to spatially identifying nucleic acid methylation.

The utility model provides an integrated device for nucleic acid extraction and nucleic acid methylation, which comprises a bottom plate and a magnetic adsorption mechanism, and the magnetic adsorption mechanism comprises a magnetic adsorption assembly for adsorbing magnetic beads in a reaction tube and a driving assembly for driving the magnetic adsorption assembly to lift, the driving assembly comprises a lead screw in threaded connection with the magnetic attraction assembly and a rotary driving motor, an output rotating shaft of the rotary driving motor is in transmission connection with the driving end of the lead screw through a synchronous belt, and the rotating axis of the lead screw and the rotating axis of the output rotating shaft are arranged in parallel in a spaced mode. The lead screw and the rotary driving motor are projected on a vertical plane in the direction perpendicular to the output rotating shaft, and the axial length of the rotary driving motor is within the axial length range of the lead screw. The overall design height of the integrated device can be effectively reduced, and the structure of the device is more compact.

The invention includes improved methods and compositions for detecting methylation in nucleic acids. In particular, the disclosure is directed to methods of converting 5-hydroxymethylcytosine (5hmC) and / or 5-methylcytosine (5mC) to Thymine (T). In addition, the disclosure is also directed to methods of detecting 5hmC and / or 5mC in a sample.

The present disclosure provides methods and systems for detecting colorectal cancer by nucleic acid methylation analysis. In particular, the present disclosure provides methods and systems for screening or detecting colorectal cancer or subsequent colorectal disease progression, which can be applied to cell-free nucleic acids, such as cell-free DNA. The method may train a machine learning model using detection of methylation signals within a single sequencing read in an identified genomic region as an input feature and generate a classifier suitable for layering a population of individuals. The method may include extracting DNA from a cell-free sample obtained from a subject, transforming the DNA for methylation sequencing, generating a sequencing read, and detecting a colonic proliferative cell disorder related signal in sequencing information, and training a machine learning model to provide a discriminator, the discriminator is capable of differentiating groups, such as health, cancer, or differentiating disease subtypes or stages, in a population of subjects. The methods are useful, for example, in predicting, prognosing, and / or monitoring response to treatment, tumor load, recurrence, or progression of colorectal cancer.

A computer-implemented method for characterizing disease progression is provided. The computer-implemented method may include: receiving, at a computing device, a set of nucleic acid methylation data; receiving, at the computing device, a designation of one or more genomic regions; generating, using a processor of the computing device, a trajectory of disease progression; identifying, using the processor and within the set of nucleic acid methylation data, one or more temporal methylation features associated with progression along the trajectory; and mapping, using the processor, the one or more temporal methylation features to the one or more genomic regions.

The present disclosure is concerned with modified proteins, methods, compositions, and kits for mapping of methylation status of nucleic acids, including 5-methylcytosine and 5-hydroxymethyl cytosine (5hmC). The proteins selectively act on certain modified cytosines of target nucleic acids and include one or more substitution mutations that enhance the selectivity of the proteins for certain modified cytosines, enhance the stability of the proteins, or enhance both selectivity and stability. Also provided are compositions and kits that include one or more of the proteins and methods for using one or more of the proteins.

The invention discloses a medical data processing method and system and a medium. The method comprises the following steps: acquiring test data; inputting the test data into a trained methylation marker screening model to obtain a screening result, performing feature extraction on the test data, and performing classification by using a two-layer classifier to obtain the screening result; and based on the screening result, outputting the screening result to a user side for visual display. According to the method, DNA methylation data of normal tissues and cancer tissues and serum circulating nucleic acid methylation data of healthy people and cancer patients are combined, a methylation marker screening method is constructed from an alpha value, meanwhile, four data characteristics are developed from the alpha value and a beta value, an ensemble learning model is constructed from four data dimensions, and the methylation marker screening method is established. Therefore, the sensitivity and the specificity of cancer early screening are remarkably improved.

A method for discriminating a cancer state is provided. A first dataset is obtained for a plurality of subjects having a first cancer state. Each subject has a plurality of nucleic acid methylation fragments with methylation patterns comprising CpG site methylation states. An autoencoder including an encoder and decoder is trained by evaluating the error in the autoencoder reconstruction of the methylation pattern and nucleic acid sequence of each nucleic acid methylation fragment in the first dataset. A second dataset is obtained for a plurality of subjects having a second cancer state. A plurality of features is identified by inputting the methylation pattern and nucleic acid sequence of each nucleic acid methylation fragment in the second dataset into the trained autoencoder and computing a score determined by the autoencoder reconstruction of the methylation pattern. The plurality of features is used to train a supervised model that discriminates a cancer state.

The present disclosure is concerned with proteins, methods, compositions, and kits for mapping of methylation status of nucleic acids. In one embodiment, proteins are provided that selectively act on certain modified cytosines of target nucleic acids and converts them to thymine. Also provided are compositions and kits that include one or more of the proteins and methods for using one or more of the proteins.

The present disclosure is concerned with altered cytidine deaminases, methods, compositions, and kits for mapping of methylation status of nucleic acids. In one embodiment, altered cytidine deaminases are provided that selectively act on certain modified cytosines of target nucleic acids and converts them to thymidine. Also provided are compositions and kits that include one or more of the proteins and methods for using one or more of the proteins.

Disclosed herein are compositions for preparing a target nucleic acid molecule comprising one or more 5-formylcytosine bases or adducts of 5-formylcytosine. Also disclosed herein are methods of efficiently synthesizing a nucleic acid molecule comprising one or more 5-formylcytosine bases from a target nucleic acid molecule comprising one or more 5-hydroxymethylcytosine bases. The disclosure also provides methods of detecting epigenetic modifications in a target nucleic acid molecule, such as those characterized by the methylation of cytosine at position 5 (e.g., 5-methylcytosine, 5-hydroxymethylcytosine).

The present application relates to a method for detecting methylation status of a nucleic acid, comprising the steps of: treating a biological sample with an unmethylation-sensitive restriction enzyme; and performing a methylation-sensitive high-resolution melting (MS-HRM) analysis.

The present disclosure provides methods and systems for screening or detecting a colorectal cancer or following colorectal disease progression that may be applied to cell-free nucleic acids such as cell-free DNA. The method may use detection of methylation signals within a single sequencing read in identified genomic regions as input features to train a machine learning model and generate a classifier useful for stratifying populations of individuals. The method may comprise extracting DNA from a cell-free sample obtained from a subject, converting the DNA for methylation sequencing, generating sequencing reads, and detecting colon proliferative cell disorder-associated signals in the sequencing information and training a machine learning model to provide a discriminator capable of distinguishing groups in a subject population such as healthy, cancer or distinguishing disease subtype or stage. The method may be used for, e.g., predicting, prognosticating, and / or monitoring response to treatment, tumor load, relapse, or colorectal cancer development.

Provided are compositions and methods for modulating methylation and / or expression of one or more target nucleic acids in a cell. Also provided are methods of making the disclosed compositions and methods of treating a disease or condition associated with increased methylation of a target nucleic acid by administering a disclosed composition.

Methods and systems provided herein address current limitations of bisulfite-based methylation sequencing by improving the quality and accuracy of nucleic acid methylation sequencing and uses thereof for detection of disease. Methods that include minimally-destructive conversion methods for methylation sequencing as well as specialized UMI adapters provide for improved quality of sequencing libraries and sequencing information. Greater accuracy and more complete methylation-state information permits higher quality feature generation for use in machine learning models and classifier generation.

This disclosure provides compositions for use in the preparation of target nucleic acid molecules, comprising one or more 5-formylcytosine bases or adducts of 5-formylcytosine. Also disclosed herein is a method for efficiently synthesizing nucleic acid molecules comprising one or more 5-formylcytosine bases from target nucleic acid molecules comprising one or more 5-hydroxymethylcytosine bases. This disclosure also provides a method for detecting epigenetic modifications in target nucleic acid molecules, such as epigenetic modifications characterized by methylation of cytosine at position 5 (e.g., 5-methylcytosine; 5-hydroxymethylcytosine).

Systems and methods of the disclosure may include receiving, at a computing device, a first set of nucleic acid methylation data and a second set of nucleic acid methylation data, wherein the first set of nucleic acid methylation data is associated with a pre-treatment sample and wherein the second set of nucleic acid methylation data is associated with a post-treatment sample. The method may include comparing, using a processor of the computing device, a first feature set of the first set of nucleic acid methylation data against a second feature set of the second set of nucleic acid methylation data; determining, based on the comparing, at least one treatment affected feature in the second feature set of the second set of nucleic acid methylation data; and implementing, based on the determining, an exclusion process on the at least one treatment affected feature in the second feature set.

A method for discriminating a cancer state is provided. A first dataset is obtained for a plurality of subjects having a first cancer state. Each subject has a plurality of nucleic acid methylation fragments with methylation patterns comprising CpG site methylation states. An autoencoder including an encoder and decoder is trained by evaluating the error in the autoencoder reconstruction of the methylation pattern and nucleic acid sequence of each nucleic acid methylation fragment in the first dataset. A second dataset is obtained for a plurality of subjects having a second cancer state. A plurality of features is identified by inputting the methylation pattern and nucleic acid sequence of each nucleic acid methylation fragment in the second dataset into the trained autoencoder and computing a score determined by the autoencoder reconstruction of the methylation pattern. The plurality of features is used to train a supervised model that discriminates a cancer state.

Methods and systems provided herein address limitations in standard nucleic acid library preparation used in conjunction with methylation sequencing which can increase library yield, achieve more uniform library amplification yields, and reduce undesired PCR products thereby minimizing signal loss and reducing biases that can be introduced in standard library preparation methods as well as improve the quality and accuracy of nucleic acid methylation sequencing and uses thereof, for example, in detection of disease. More accurate and complete information regarding methylation state permits higher quality feature generation for use in machine learning models and classifier generation, and the uses thereof for detection of disease by improving the quality, sensitivity, and accuracy.

The invention discloses a trace nucleic acid methylation library building method of exosome DNA and application of the trace nucleic acid methylation library building method, and belongs to the technical field of biology. The method comprises the following steps: breaking exosome DNA by using symmetric single-linker Tn5 transposase, connecting a 5'end linker, and not carrying out notch completion; transforming the exosome DNA by using an enzyme method; connecting a 3'end joint; and amplifying the exosome DNA which is subjected to breaking, enzymatic conversion and joint connection, so as to obtain the methylation sequencing library. The method can be applied to methylation library establishment of trace DNA of exosomes from various sources including body fluid, cell culture, tissue and the like, and is also suitable for methylation library establishment of all trace long fragment DNA. According to the method, the defects that the library building efficiency of the traditional asymmetric joint Tn5 is only 50% and methylation deviation is introduced during gap completion are overcome. The symmetric single-linker transposase is connected with the single-linker, so that the method has high gene comparison rate and conversion rate, and has good development and application prospects.

The present invention relates to a method for diagnosing, monitoring the effect of a treatment, monitoring the progression of a disease, or screening for a compound for treating a cerebral creatine deficiency syndrome, said method comprising the steps of measuring the level of nucleic acid methylation in a biological sample, and comparing the measured level with a control nucleic acid methylation level. The present invention also relates to folate and derivatives thereof for use in the treatment of a cerebral creatine deficiency syndrome.

Systems and methods of the disclosure may include a computer-implemented method, the computer-implemented method may include: receiving, at a computing device, a set of nucleic acid methylation data; receiving, at the computing device, a designation of one or more genomic regions; identifying, using a process of the computing device and within the set of nucleic acid methylation data, one or more abnormal methylation features; and mapping, using the processor, the one or more abnormal methylation features to the one or more genomic regions. Other aspects are described and claimed.