61 results about "Genome wide analysis" patented technology

The invention discloses a lytic bacteriophage for preventing and controlling vibrio in an aquaculture environment. The bacteriophage vBValMR42H belongs to a muscle tail bacteriophage and is insensitive to chloroform, the capsid of the bacteriophage vBValMR42H is free of lipid substances, and the preservation number is GDMCC No: 67434-B1. The bacteriophage has the characteristics of high adsorption speed, short incubation period and high cracking amount, keeps high activity in a wide range of temperature (4-55 DEG C) and pH (2-11), and has strong environmental adaptability. Genome analysis shows that the bacteriophage does not contain virulence factors, antibiotic resistance genes and lyogen related genes, and is high in biological safety. Physical development analysis shows that the method can be divided into a new genus. The bacteriophage R42H has the advantages of high splitting efficiency, good environmental stability, strong specificity, gene safety and the like, and can be used as an ideal biological prevention and control agent for preventing and controlling vibrio alginolyticus diseases in aquaculture.

The invention discloses a citrus hybrid offspring authenticity identification method based on whole genome SNP (Single Nucleotide Polymorphism) analysis. According to the invention, a genome typing technology in a whole genome range is adopted, and a set of discrimination system capable of accurately identifying real hybrid offspring is established through high-density SNP (Single Nucleotide Polymorphism) marker analysis and an IBD (Identity by means of an algorithm. The method breaks through the limitation of a traditional method on hybrid filial generation identification, and provides reliable technical support for breeding practice.

In one embodiment, a method includes providing sequence information of a DNA sequence as an input to a neural network model, generating activations by convolutional filters of the neural network model based on the sequence information, wherein each convolutional filter is associated with a weight, identifying motifs from the DNA sequence based on the convolutional filters and their weights by the neural network model based on a regularization function configured to enable each convolutional filter to learn a distinct motif, generating a linear vector of attention scores for the motifs and identifying interactions between the motifs by attention layers of the neural network model based on the activations, determining motif instances and an associated syntax by the neural network model based on the linear vector of attention scores and the interactions, and generating predictions associated with genomic regulatory functions based on the motif instances and the associated syntax.

The application belongs to the technical field of biological information, and particularly relates to a method for locating ancestral haplotype genes for deep hybrid lines. In the application, the ancestral genotype of a sample to be analyzed is obtained, and then a genomic segment significantly associated with a phenotype is obtained. Then, whole genome analysis is performed. Compared with the prior art, the method for locating ancestral haplotype genes for deep hybrid lines can effectively reduce false positives, and can also be used for heterosis analysis, capture of dominant and epistatic effects between genetic markers and the like.

The present invention relates to the field of spatial epigenomic profiling. It concerns DNA arrays loaded with barcoded polynucleotides harboring a mosaic (MOS) sequence, methods and uses thereof enabling spatial epigenomic profiling.

Methods and systems for predicting the pathogenicity of variant sequences detected in a sample from a subject are described. The disclosed methods may comprise, for example, receiving sequence read data for a plurality of sequence reads obtained from a sample from a subject; identifying one or more variant sequences based on the sequence read data; providing a variant sequence from the one or more identified variant sequences as input to a trained machine learning model configured to determine a pathogenicity prediction score for the identified variant sequence based on the variant sequence and at least one of additional genomic profiling, demographic pathogenicity prediction score determined for the variant sequence identified in the sample from the subject.

The application discloses a kind of based on machine learning's genome analysis parallel optimization method and system, the method of the present application includes the input BAM file is cut into multiple same size file blocks;For each file block, extract file block characteristics, and input the file block characteristics into the pre-trained machine learning model to obtain the predicted running time of the file block;The predicted running time is in the front part file block is divided into smaller file block;File block is input into HaplotypeCaller in parallel to carry out variation detection;The variation detection result generated by HaplotypeCaller for each file block is merged and output.The present application is aimed at solving the problem of serious calculation tilt and low resource utilization caused by unclear calculation complexity before HaplotypeCaller runs, improving the efficiency of genome analysis, shortening the variation detection duration.

The invention discloses a genome analysis method for mining a potential natural strain repository of a drug-resistant gene tetX. According to the method, aiming at a database of a drug-resistant gene detection core, a plurality of representative databases (such as CARD, Resfinder and SARG) and drug-resistant gene sequences annotated in an NCBI public database are combined on the construction composition of the database; various types which are not included in but reported in the database at present are considered, so that the types and the quantity of corresponding drug-resistant gene databases (such as tetX genes) are greatly expanded; an optimized and integrated analysis strategy and a verification strategy are provided for mining and analyzing a potential natural strain repository of tetX drug-resistant genes.

The present invention provides methods, compositions and kits for using a transposase and a transposon end for generating extensive fragmentation and 5′-tagging of double-stranded target DNA in vitro, then using a DNA polymerase for generating 5′- and 3′-tagged single-stranded DNA fragments without performing a PCR amplification reaction, wherein the first tag on 5′-ends exhibits the sequence of the transferred transposon end and optionally, an additional arbitrary sequence, and the second tag on 3′-ends exhibits a different sequence from the sequence exhibited by the first tag. The method is useful for generating 5′- and 3′-tagged DNA fragments for use in a variety of processes, including processes for metagenomic analysis of DNA in environmental samples, copy number variation (CNV) analysis of DNA, and comparative genomic sequencing (CGS), including massively parallel DNA sequencing (so-called “next generation sequencing”).

The invention provides a digestive tract tumor course monitoring system. The system comprises a system control module, a first-stage detection module, a second-stage detection module, a third-stage detection module, a risk assessment module and an intervention decision module. The primary detection module is used for collecting tumor markers, images and clinical symptom data of a patient; the second-stage detection module is used for performing liquid biopsy, pathological biopsy and metabolic function evaluation on the first-stage positive patient; the third-stage detection module is used for carrying out micro-metastasis detection and immune microenvironment and genome analysis on a second-stage positive patient; the risk assessment module determines a patient risk level based on a detection result; the intervention decision module outputs intervention measures based on the risk level; the system control module manages and coordinates operation of all the modules. Each detection module automatically captures detection data by being connected with a hospital system, and judges an abnormal condition according to a set threshold value. According to the system, through a logic mechanism of grading detection and grading intervention, precise monitoring and early warning intervention on the disease course of the digestive tract tumor patient are realized.

The invention discloses a layered gel culture technology constructed by using environmental extracts, and belongs to the field of environmental microorganism culture. According to the technology, an environmental sample is separated into a particle phase and a liquid phase through water extraction, the particle phase and the liquid phase are respectively prepared into a lower-layer solid-phase matrix and an upper-layer gel phase with gel (preferably agar), a vertical nutrition / signal slow-release gradient is formed in a culture dish, and particle attachment sites are provided; and inoculating the environmental microorganisms on the upper layer or the surface for culture. Compared with nutrient agar or extremely simple water agar, the method has the advantages that more bacterial colonies and higher distinguishable form number can be obtained under the repeatable condition, and the community diversity and the OTU / ASV overlapping degree with an original sample are improved; rare / slow-growing groups can be stably separated, and subsequent 16S / metagenome analysis and agar block bacteriostasis primary screening are facilitated. Meanwhile, the invention provides a corresponding culture medium composition and a kit / prefabricated layered culture dish. According to the scheme, operation is easy and convenient, parameters can be standardized, and the method is suitable for isolated culture and ecological function research of environmental samples such as soil, sediments and low-solid water samples.

The disclosure relates to comprehensive genomic profiling (CGP) and to consensus-based classification techniques for determining genetically inferred ancestry from CGP of tumor DNA. Aspects are directed towards accessing reference and subject sequencing files and identifying genomic variants using a hybrid variant tool. The reference variant file is consolidated into a datastore formatted file that is queried to perform joint variant calling to generate a final reference variant file. The final reference variant file and the subject variant file are merged. On the merged variant file, principal component (PC) analysis is performed, and the PCs are used by a first and second classification process to generate a first and second ancestry call. The merged variant file is input into a third classification process to generate a third ancestry call. A consensus genetically inferred ancestry (GIA) call is predicted based on the first, the second, and the third ancestry calls.

The invention discloses a strain of Saccharobacterium tumefaciens and application thereof, and belongs to the field of microorganisms. According to the invention, a strain is separated and purified from leaves of Chuxiong saiai plant in Yunnan, and cell morphology observation, physiological and biochemical characteristic detection, cell chemical composition detection, and sequencing and comparison of genome DNA prove that the strain is a new species of the genus beach bacillus, and is named as beach bacillus saiai, and the strain is a new species of the genus beach bacillus and is named as beach bacillus saiai. Experiments and genome analysis prove that the strain has phosphorus solubilizing potential and can degrade PO4 < 3 + > generated by organophosphorus, so that the strain obtained by screening can be used for preparing reagents for degrading organophosphorus.

[Problem] To provide technology for assisting in making better use of personnel by utilizing the results of personality tests on other personnel. [Solution] An information processing device 1 is capable of performing personality estimation in various models using answer results from a questionnaire, image data obtained by imaging the face, image data obtained by imaging the upper body or the entire body, and genome analysis results as personal information for personality estimation. Regarding the personality of an arbitrary person among target people for whom the personality estimation was performed, a distribution identification unit 1C and a position calculation unit 1D postulate target people belonging to a group of target people which is postulated for said arbitrary person, for example an organization or a divided unit within an organization (e.g. a department), and calculate a relative position. Thereby, the personality of the arbitrary person can be understood as a relative position within the postulated group.

This invention provides a *Roseolariomoraxella salina* strain for saline-alkali soil improvement, with accession number CGMCC No. 36067. The *Roseolariomoraxella salina* strain provided by this invention exhibits significant comprehensive application advantages. This strain demonstrates excellent survival and growth capabilities under saline-alkali stress, effectively reducing salinity and alkalinity in saline-alkali soils and thus improving the saline-alkali environment. Whole-genome analysis shows that this strain carries multiple functional genes related to osmotic regulation and ion transport, providing a molecular basis for its salinity-reducing ability. Adding citric acid or betaine can further enhance its salinity-reducing performance, and its biomass is significantly increased after optimization of fermentation conditions. This strain shows promising application prospects in saline-alkali soil improvement and saline-alkali aquaculture environment management.

The invention relates to the technical field of gene engineering detection, and particularly discloses a gene detection system for promoting andrographolide synthesis based on a biosensor, a key gene ApDof29 for regulating and controlling andrographolide synthesis is determined through whole genome analysis, gene expression profile research and co-expression network analysis, the core regulation and control effect of ApDof29 is verified, and the gene detection system for promoting andrographolide synthesis based on the biosensor is used for promoting andrographolide synthesis. The invention also develops a real-time dynamic monitoring system, and realizes non-invasive monitoring of andrographolide content accumulation, biosynthesis rate and metabolic intermediate concentration change by utilizing the fusion of a specific response element and a reporter gene. Through comprehensive calculation processing of an accumulation abnormal coefficient, a synthesis rate abnormal coefficient and a concentration change abnormal coefficient, the regulation and control effect of ApDof29 is dynamically evaluated, and a scientific basis is provided for subsequent gene modification.

A copy number variation spectrum determination method performed by at least one processor is provided. The copy number variation spectrum determination method comprises the following steps: acquiring a whole genome analysis result related to a target sample collected from an object; on the basis of the acquired whole genome analysis result, a read depth related to the target sample is calculated for each of a plurality of predetermined bins on the genome (genome); correcting the depth of a sequencing fragment related to the target sample; and determining a copy number variation spectrum (profile) related to the target sample by using the corrected depth of the sequencing fragment, wherein the copy number variation spectrum (profile) is related to the target sample.

The invention discloses a specific target sequence, a primer pair and a kit for identifying fusarium species based on a time-precious method, application of the specific target sequence, the primer pair and the kit and a species identification method, and accurate identification of fusarium related species can be achieved based on species specific sequences obtained through analysis and screening of all genomes of fusarium. The species identification method disclosed by the invention is strong in specificity, high in sensitivity and multiple in detection technology, can realize rapid identification of species, has important significance in medicinal material fungal pollution detection and agricultural disease control, and has a wide application prospect.

The invention discloses a differential diagnosis and prognosis evaluation method for a pleural effusion microbiome based on metagenome sequencing and application, belongs to the technical field of bioinformatics, and discloses a method for analyzing the microbiome of a pleural effusion sample, and the method comprises the following steps: carrying out metagenome next-generation sequencing on an in-vitro pleural effusion sample to obtain a sequencing reading; performing bioinformatics analysis on the sequencing reading, and determining microorganism composition information of the pleural effusion sample based on a verification result; by establishing a unified mNGS experimental process and a parallel bioinformatics analysis path, two kinds of technical information of different dimensions, namely microbiome structural characteristics and host genome copy number variation (CNV), are synchronously output from single sequencing data, and the defect that microbiological analysis and genome analysis need to be carried out in batches in the prior art is overcome.

Methods are provided for analyzing genomic DNA where the genomic DNA is subject to in situ fragmentation, in situ transcription, complementary DNA synthesis and barcoding complementary DNA.

The invention relates to the field of gene data analysis, and provides a corn whole genome association analysis method, device and equipment and a readable storage medium, the method comprises the following steps: integrating a genotype data matrix and a phenotype data matrix of a corn sample to obtain a whole genome association analysis data matrix; training a convolutional neural network based on the whole genome association analysis data matrix; combining the trained convolutional neural network with the member contribution model to construct a whole genome association analysis model; and based on the whole genome association analysis model, obtaining an influence result of each gene locus of the to-be-analyzed corn on the corn phenotype. According to the corn whole genome correlation analysis method, the whole genome correlation analysis model is constructed through the combination of the convolutional neural network and the member contribution model, correlation analysis is performed on the corn whole genome, and the precision and efficiency of corn whole genome analysis are improved.

The invention relates to the field of biological medicine, and discloses an integrated genome analysis method based on low-depth sequencing, and the method comprises the following steps: obtaining whole genome low-depth sequencing data; after quality control and comparison, SNV, Indel and CNV are calculated; performing multi-dimensional function annotation by combining genome position, coding influence, splicing disturbance, conservative property, regulatory element and three-dimensional chromatin interaction; database information such as ClinVar and HGMD is integrated, and according to a phenotype-driven rule engine, a clinical interpretable report is generated according to the ACMG / AMP standard. According to the method, a complete analysis chain covering sequence variation detection, multi-dimensional function annotation, three-dimensional genome association, public database integration and phenotype driven interpretation is constructed, so that the fundamental defect that only an original variation list is output and a clinical action basis cannot be provided in traditional low-depth sequencing is overcome.

The invention provides an acceleration method and device for gene detection and electronic equipment, and relates to the field of biological information.The method mainly comprises the steps that a first variation data set and a second variation data set are obtained according to a first gene sample set; and obtaining a variation quality control model according to the second variation data set, and processing the first variation data set according to the variation quality control model to obtain a first variation detection result corresponding to the first variation data set. According to the technical scheme, the temporary interval information is utilized to divide the variation detection data into the first variation data set and the second variation data set, so that interval processing is directly oriented during subsequent application of quality control, and the speed-up calculation effect is achieved. Compared with the conventional method of re-splitting data and allocating tasks when quality control is applied, the method has the advantages that the time consumption of detection is reduced, and the analysis and calculation efficiency of the population genome is effectively improved.

The invention relates to the field of biological information, and discloses a gene library acquisition method for improving single cell amplification genome coverage. Aiming at the problem of insufficient single cell amplification genome coverage, the gene library acquisition method provides a strategy of composite library construction and optimized data integration, and comprises the following steps: constructing at least one original text library and one sub-library with different average fragment lengths for the same single cell sample, and sequencing; performing Barcode resolution and effective single cell identification on the sequencing data through a customizable sequence feature detection method; and further, according to the identification result of the effective single cell, identifying, collecting and merging all sequencing sequence data of the same single cell, generating an integrated sequence data set of the corresponding single cell, and obtaining gene library data of the single cell. The SAG coverage degree of the obtained gene library data is high, and the method has high reliability and application value when being used for genome analysis of the single cell downstream.

The invention relates to an Ectoine-producing halophilic bacterium as well as a screening method and application thereof, and belongs to the technical field of microorganisms. According to the Ectoin-producing halophilic bacteria disclosed by the invention, the Ectoin-producing halophilic bacteria are Vreelandelassp., and the Ectoin-producing halophilic bacteria are Ectoin-producing halophilic bacteria. The 16S rRNA of the Ectoin-producing halophilic bacteria has at least 90% of nucleotide sequence consistency with that of SEQ ID NO. 1; the Ectoin halophilic bacteria are used for expressing 2-aminobutyric acid acetyltransferase, 2-aminobutyric acid transaminase and Ectoin synthetase. Through an efficient screening method and deep genome analysis, the novel halophilic strain capable of synthesizing the Ectoine is successfully screened out, and the gene cluster for synthesizing the Ectoine is excavated, so that the production efficiency and yield of the Ectoine can be improved, a microbial resource library is enriched, and the genetic diversity is increased.

According to some embodiments of the present invention, an oral microbiome inspection system for early diagnosis of pet periodontal disease comprises: a genome analysis device configured to generate microbiome data on the basis of a specimen collected from the oral cavity of a pet to be inspected; and a processing device configured to generate abundance data, occurrence frequency data, and correlation data of the microbiome data on the basis of a list of microorganisms of interest in a pet standard database, generate health state data of the specimen by comparing the abundance data, the occurrence frequency data, and the correlation data with standard samples of the pet standard database, and generate an oral health report for the pet to be inspected, on the basis of the health state data.

Embodiments of this specification relate to methods for optimizing microbial strain combinations and predicting the growth state of said strains. A method for determining microbial strain combinations according to one embodiment of this specification for achieving the aforementioned objectives may include: obtaining genomic analysis information about a target microorganism; obtaining first metabolic information about each of a plurality of first microbial colonies containing the target microorganism; estimating first growth indicator information about each of the plurality of first microbial colonies using the genomic analysis information and metabolic information as input to a first model; and determining a strain combination based on at least one of the metabolic information and the growth indicator information.

A method for detecting de novo structural variations includes: a genome analysis apparatus extracting k-mer data of a target individual from genome sequencing data of a target individual. The method may include: extracting k-mer data of a target individual from genome sequencing data, comparing a reference-genome k-mer database—including parents' and pan-genome k-mers—with the target individual's k-mers to select target-individual-specific k-mers, determining target-individual-specific reads, identifying candidate de novo structural-variation regions, predicting discordant read pairs using a machine-learning model, selecting final de novo regions based on an estimated variant allele frequency, and generating a clinical report.

This invention belongs to the field of gene technology and discloses a bacterial strain B11 antagonistic to soft rot disease of Amorphophallus muelleri. Isolated from the rhizosphere soil of Amorphophallus muelleri, it was identified as the golden subspecies of *Pseudomonas aeruginosa*. This strain effectively inhibits the growth of the soft rot pathogen Pcc, reducing the incidence and disease index of soft rot in Amorphophallus muelleri. It also possesses the ability to dissolve organophosphates and produce siderophores, and exhibits broad-spectrum antagonistic activity against various fungal diseases of Amorphophallus muelleri, including white mold, leaf spot, and dry rot. Whole-genome analysis shows that the B11 genome is 6.77 Mb in size, with a GC content of 62.81%, encoding 5,964 genes, including gene clusters related to antibacterial activity such as phenazine, nitropyrrolizin, and siderophores. This strain has good development and application potential in the control of soft rot in Amorphophallus muelleri.

The invention discloses a CpG methylation single cell whole genome analysis method and related equipment based on sequencing reads, and the method comprises the following steps: obtaining to-be-analyzed single cell data, and carrying out methylation data sequencing read comparison on the to-be-analyzed single cell to obtain a methylation site statistical result; screening a methylation specific interval based on a random sampling strategy and the methylation Hamming distance of the sequencing read; calculating a Hamming distance matrix of every two to-be-analyzed single cell CpG sites according to a methylation site statistical result and a methylation specific interval, and performing initial clustering based on the Hamming distance matrix; and obtaining cell DNA methylation heterogeneity measurement according to an initial clustering result, extracting a cell type or state specific DNA methylation mode panorama, calculating the similarity between a read segment and each cell type according to a specific methylation mode, and calculating the proportion of cells from a mixed sample sequencing result. According to the embodiment of the invention, the cell methylation analysis efficiency and sensitivity can be improved. The method can be widely applied to the technical field of gene analysis.