12 results about "Heteroplasmy" patented technology

Microscopy imaging that allows for multiple mRNAs, proteins and metabolites to be spatially resolved at a subcellular level provides valuable molecular information which is a crucial factor for understanding tissue heterogeneity as for example within the tumor micro environment. The current invention describes a method (High Density-SUMI-Seq) which combines the use of Spatial Unique Molecular Identifier in situ localization and identification (by in situ sequencing or sequential fluorescence hybridization) of rolonies derived from rolling circle amplification of circular oligonucleotides and in vitro sequencing of target amplified RNA or DNA in combination with SUMI identification at a subcellular level with no optical diffraction limitation in the amount of amplified target information that can be analyzed per cell. Apart from amplified RNA or DNA, the High Density-SUMI-Seq method can also be applied using linear oligonucleotides to spatially resolve proteins and metabolites to provide multiomics results.

The application discloses a Holstein cow breeding probe combination, a gene chip, a kit and application, the probe combination can detect 140290 SNP sites based on the reference genome ARS-UCD1.2. The site detected by the Holstein cow breeding probe combination is obtained from 77887 sites after further screening based on 4600 Holstein cow genome sequencing data, in combination with 62387 SNP sites related to yield, reproduction and body shape and 16 defect-related SNP sites, and can effectively reflect the structural heterogeneity of the genome itself. The site detected by the Holstein cow breeding probe combination has high polymorphism information content, and fully covers high polymorphism sites. Meanwhile, the interpolation accuracy is high, the genotyping consistency is equivalent to that of a high-density chip, the cost is significantly lower, and the economy is better, and the application provides an independent technical tool for efficient and accurate genome breeding of Holstein cows.

The application discloses a lung cancer gene mutation prediction method based on unsupervised clustering double-stage attention multi-instance learning, and relates to the technical field of pathological image analysis and gene detection. H&E staining pathological whole section images of non-small cell lung cancer patients and corresponding gene mutation data are collected to construct a data set; the images are preprocessed by using the OTSU method, segmented into blocks and high-dimensional feature vectors are extracted; the block features are grouped into cluster feature sets through unsupervised clustering; a double-stage attention mechanism composed of intra-cluster and inter-cluster is used to hierarchically aggregate and generate global features; finally, a classification model is used to output mutation positive / negative prediction results. The application groups the features through unsupervised clustering and structures the features, combines double-stage attention to strengthen key information, does not need complex manual annotation, adapts to various driver gene mutation prediction requirements, effectively deals with tumor heterogeneity and feature sparsity, improves prediction accuracy and generalization ability, and provides low-cost and efficient targeted therapy preliminary screening technical support for clinics.

Techniques for identifying a tumor heterogeneity of a subject are described. In an example method, sequence read data of a sample obtained from the subject is identified. The sequence read data is indicative of endpoint positions of nucleic acid molecules in the sample. The example method further comprises determining endpoint positions of the nucleic acid molecules, generating input features based on the endpoint positions of the nucleic acid molecules, and classifying, using a classifier, the tumor heterogeneity of the subject based on the input features.

Compositions and methods discussed herein provide for treatment or prevention of a disease or disorder, or its symptoms, using a modified herpes simplex virus (mHSV) vector comprising at least two transgenes, wherein at least a first transgene encoding a gene-editing system, gene-deletion system, or bridge-editing system is expressed to knock out or delete an endogenous target gene and at least a second transgene encoding a corrected copy of the endogenous targeted gene, wherein the gene product of the second transgene replaces the gene product of the endogenous target gene.

The application discloses a gene marker combination for evaluating HLH risk and use thereof, and belongs to the technical field of gene detection. The gene marker combination is obtained by whole genome association analysis of whole exome sequencing, covers more extensive genetic information, solves the narrowness of the prior art, and provides more comprehensive analysis of the polygenic heterogeneity of HLH. Moreover, the cumulative effect of alleles is comprehensively considered, the genetic susceptibility characteristics of an individual to HLH can be more accurately reflected, and the sensitivity and specificity of gene detection can be improved.

This invention discloses a gene composition, kit, and application for early diagnosis of renal cell carcinoma, relating to the field of molecular diagnostic technology. The gene composition consists of the PLIN2 gene, SLC25A25 gene, PITX1 gene, and SOX1 gene. The differential methylation site of the PLIN2 gene is cg13990947, the differential methylation site of the SLC25A25 gene is cg14294859, the differential methylation site of the PITX1 gene is cg02037307, and the differential methylation site of the SOX1 gene is cg1. 6705627; This invention, by screening four genes (PLIN2, SLC25A25, PITX1, and SOX1) and specific methylation site combinations, can accurately identify two major subtypes of renal cell carcinoma—clear cell and papillary renal cell carcinoma—compared to single-gene detection. The methylation difference between cancerous and normal tissues, Δβ-value, is greater than 0.2, solving the problem of heterogeneous renal cell carcinoma detection. The optimized urine free DNA lysis buffer and bisulfite conversion system improve the nucleic acid extraction and conversion rates. Combined with dedicated methylation-specific primers and probes, it enables non-invasive detection of urine samples.

This invention discloses a multi-omics joint detection method in the field of microbiology and fermentation technology for Baijiu brewing to analyze regional heterogeneity of high-temperature Daqu (fermentation starter). Taking high-temperature Daqu from different production areas and strata as examples, it integrates physicochemical enzyme activity assays, electronic sensory analysis, volatileomics, microbial amplicon sequencing, metagenomics, and metagenomic assembly technologies to systematically characterize the differences in physicochemical properties, sensory flavors, microbial communities, and metabolic functions of samples. It establishes a correlation model of "phenotype, flavor, microbial community, function, and strain," clarifying the impact of production area and stratum on Daqu quality and elucidating the mechanism of regional heterogeneity formation in high-temperature Daqu. This invention elevates the analytical depth from the genus level to the species and genome level, accurately locating core functional strains. It solves the problems of traditional methods having single detection dimensions, shallow analytical depth, and unclear functional attribution, providing scientific methods and theoretical support for improving the quality of high-temperature Daqu in Maotai-flavor Baijiu and enhancing the flavor of non-core production areas.

The invention relates to the technical field of image analysis, in particular to a multi-modal fusion glioma intelligent prognosis prediction method and system, and the method comprises the steps: collecting multi-modal data, respectively extracting omics features, constructing a multi-modal fusion depth model, obtaining high and low risk groups, and respectively carrying out difference analysis from multiple omics dimensions, screening out a gene set which is remarkably and highly expressed in the high-risk group, obtaining an intersection of each group of study difference analysis results, preliminarily screening out candidate genes, carrying out inter-study correlation analysis, and screening out intersection genes; introducing the intersection genes into a public database, and screening out genes which are remarkably and highly expressed in GBM to obtain candidate genes; and respectively introducing the candidate genes into a plurality of public databases, and finally identifying potential treatment targets related to the high-risk group. According to the method, the accuracy, the interpretability and the clinical transformation potential of GBM patient layering are comprehensively improved by constructing the multi-modal fusion depth model and combining heterogeneity mechanism analysis and target screening verification.

The application belongs to the technical field of biomedical data analysis and spatial omics data processing, and particularly relates to a disease target network construction method fusing pathological images and spatial transcriptome. Based on automatic or manual definition of a region of interest according to pathological characteristics, single-cell data and spatial transcriptome data are integrated; the spatial enrichment degree of different cell types and genes is quantitatively scored; and finally, a spatial co-localization network of genes and cells is constructed in the region of interest. The method can be compatible with various pathological imaging methods, and is suitable for irregularly shaped and significantly spatially heterogeneous disease tissues, overcoming the limitations of traditional spatial analysis methods guided by transcriptome characteristics in disease region positioning, and realizing systematic analysis from spatial pathology positioning to cell, gene and molecular correlation levels. The method is suitable for spatial mechanism research of complex diseases such as cardiovascular diseases, tumors and neurodegenerative diseases, and has high biological interpretation value and practical application significance.

The present invention, in the field of bioengineering and biotechnology, relates to a method for preparing a recombinant antibody with a unique glycan profile produced by a genome-edited CHO host cell. Specifically, according to a method of the present invention, the TALEN technology is used to edit the FUT8 gene in CHO cells that have been adapted for serum-free suspension growth. The edited CHO host cells can produce recombinant antibodies with a unique glycan profile. The unique glycan profile can be characterized by non-fucosylated N-linked oligosaccharide chains of the antibodies, extremely low N-glycosylation heterogeneity and uniform carbohydrate chains. The antibody prepared by the method of the invention exhibit significantly increased ADCC and greater stability.