244 results about "Whole genome sequencing" patented technology

A molecular marker related to body weight traits of Hu sheep and an application are provided. The whole genome sequencing of Hu sheep is carried out in the invention, the combination of QTL and GWAS is adopted, the candidate genes related to the weight traits are analyzed and the three molecular markers of MAP3K1, ABCB1, and MEF2C are selected as candidate genes for the weight traits of Hu sheep, and the two molecular markers of ANKRD55 and TRNAW-CCA-87 can be used as potential candidate genes for the weight traits of Hu sheep, these candidate genes can be used as molecular markers for application, the guidance of Hu sheep breeding will help to understand the genetic mechanism of weight traits of Hu sheep and further guide Hu sheep breeding.

The invention discloses application of a gene marker in early screening of esophagus, stomach and intestine multiple cancer species, an early screening model construction method and a detection device, and belongs to the technical field of early noninvasive detection of digestive tract tumors. By analyzing the whole genome characteristics of circulating free DNA in peripheral blood, a novel multi-cancer-species screening system is established. On the basis of low-depth whole genome sequencing data, molecular markers in three dimensions, namely a genome copy number variation mode, a DNA fragment distribution characteristic with a specific length and an epigenetics signal of a transcription initiation region, are emphatically detected. An advanced converter neural network architecture is adopted, and the model can efficiently capture complex feature association in a whole genome range through a specific self-attention mechanism. The model design particularly considers the particularity of genome data, introduces an adaptive position coding system, and accurately reflects the spatial distribution relationship of DNA fragments on chromosomes. Therefore, the system can still maintain excellent detection performance under extremely low sequencing depth.

The invention discloses a primer composition and application of the primer composition in detection of animal bifidobacterium subsp. Lactis HN019. According to the present invention, bifidobacterium animalis subsp. Lactis HN019 is adopted as an object, bacterial strain specific genetic markers are screened through whole genome sequencing and single nucleotide polymorphism analysis, and a fluorescent quantitative PCR technology is combined so as to obtain the efficient, specific and stable HN019 quantitative detection primer composition and the method thereof; through system verification, the method is suitable for an HN019 strain level detection technical framework in scientific research and industrial application scenes, and also provides key technical support for market supervision and industrial healthy development of probiotic foods.

The invention relates to the technical field of breeding methods, in particular to a precise breeding method based on single nucleotide polymorphism, which comprises the following steps: carrying out whole genome sequencing and screening SNP (Single Nucleotide Polymorphism) markers related to target traits; designing a genotype detection chip based on the SNP marker, and performing genotyping; constructing a genetic evaluation model and predicting a breeding value; designing a matching scheme based on the breeding value; performing performance verification on the offspring and continuously improving the breeding strategy. By integrating whole genome sequencing, transcriptome and metabolome data and combining bioinformatics and an artificial intelligence algorithm, efficient screening of functional SNPs related to complex characters is achieved, and the problems of multi-character collaborative improvement and insufficient environmental adaptability in a traditional method are effectively solved.

The invention provides a method for screening disease-related gene targets based on whole genome association analysis, and belongs to the technical field of disease genetic risk assessment, the method comprises the following steps: collecting and recording a sample information data set; performing whole genome sequencing on the samples to obtain SNP data, and combining the SNP data of all the samples to obtain a training data set; performing principal component analysis on the SNP matrix, and screening the top 10-30 SNPs as covariables of the model; and carrying out whole genome association analysis on the training data set and constructing a logistic regression model, and screening out the SNP related to the disease according to the P value. According to the method, confounding factors can be effectively controlled by adopting the logistic regression model and introducing covariables (such as age, gender and the number of weekly exercises), high-dimensional data are processed through a regularization method, and the risk of over-fitting is reduced. The method can also capture interaction between SNPs, and provides more accurate disease-related SNP recognition.

The invention discloses a forest tree genotype-environment interaction modeling method based on multi-modal deep learning, and relates to the technical field of forest tree breeding, the method comprises the following specific steps: multi-modal data acquisition: adopting a high-throughput phenotype platform, a whole genome sequencing technology and soil nutrient detection equipment to acquire multi-modal data; sNP locus genotype data, soil key physicochemical index environmental data and growth-related morphology and biomass parameter phenotype data of forest trees are collected respectively; forest genotype, environment and phenotype multi-modal data are collected through the system, the genotype-environment interaction algorithm and the phenotype prediction model are constructed after preprocessing and fusion, the model can accurately predict forest phenotypes, the breeding screening period is remarkably shortened, the breeding selection precision and efficiency are greatly improved, and the method is suitable for large-scale popularization and application. The method effectively solves the problem that a traditional breeding mode is short in time and efficiency, enables breeding work to respond to market demands and environmental changes more quickly and accurately, and provides powerful support for sustainable development of the forestry industry.

The invention discloses a genetic characteristic index quantitative evaluation method based on embryo genetic information processing and a computer program product, and particularly relates to the technical field of genetic information processing.The method comprises the steps that firstly, whole genome sequencing is conducted on an embryo sample, and pathogenic related mutations are screened through a variation recognition algorithm; then extracting variation points and structural features, and constructing vector description data; further generating two fixed value indexes of pathogenic load and structural stability as model input to calculate an embryo genetic health score; and finally, sorting is performed according to a scoring result, so that the embryo transplantation priority is determined, and scientific and accurate embryo optimization is realized. According to the method, comprehensive identification of embryo genetic states is realized through whole genome sequencing, a pathogenic load and structural stability double-index system is constructed, three-dimensional quality evaluation is realized, and the scientificity, accuracy and individualized clinical application capability of embryo screening are improved by combining a grading result and a family medical history calibration mechanism output by a grading model.

The invention discloses a colorectal cancer plasma circulating microbial marker, a reagent, a kit and application thereof, and belongs to the technical field of biomedical detection. The plasma circulating microbial marker for colorectal cancer comprises alternaria alternata, alophilous alophilous alophilous alophilous alophilous alophilous alophilous alophilous alophilous alophilous alophilous alophilous alophilous alophilous alophilous alophilous alophilous alophilous alophilous The colorectal cancer plasma circulating microbial marker can be used for early screening of colorectal cancer, has relatively high sensitivity and specificity, and remarkably improves the accuracy and reliability of detection; the limitation of traditional ctDNA detection is broken through, and the detection rate of early colorectal cancer is improved. The colorectal cancer plasma circulating microbial marker in a colorectal cancer plasma sample is detected through low-depth whole genome sequencing, the requirement for depth in an experiment is reduced, the cost can be greatly reduced while high sensitivity and specificity are guaranteed, and the method is more suitable for large-scale screening.

The invention discloses a method for screening a cancer specific cfDNA fragment feature combination in peripheral blood based on whole genome sequencing and application of the method. According to the method, multi-dimensional cfDNA fragment information is combined to screen characteristic indexes closely related to cancers, a brand-new index F-Index for evaluating fragment length distribution characteristics is provided, and obvious difference exists between a cancer sample and a healthy sample; in addition, motif characteristics of six basic groups at the tail end of a cfDNA fragment and distribution characteristics of the cfDNA fragment in a 10kb window on a genome are applied, a plurality of machine learning algorithms are applied, a series of cancer-specific molecular characteristic combinations are obtained through identification, and the cancer-specific molecular characteristic combinations are suitable for risk assessment and prediction of early cancers. The feature combination screened based on the method has excellent prediction performance in different classification models, and the judgment accuracy is high.

The present invention provides primers and methods for amplifying the entire genome of avian leukosis virus. The detection primer set for avian leukosis virus includes 18 pairs of amplification primers, the specific sequences of which are shown in SEQ ID NOs. 1 to 36. The detection primer set provided by the present invention can achieve relatively uniform coverage of avian leukosis virus, and in nanopore sequencing, 100% regional coverage of the genome is achieved. The method for preparing sequencing fragments of the entire genome of avian leukosis virus provided by the present invention is simple and easy to operate, with good amplification effect. Nanopore sequencing has the advantage of real-time analysis while sequencing, which can greatly shorten the detection time and can quickly identify and diagnose avian leukosis virus infection. At the same time, its entire genome sequence can be obtained. The obtained genome sequence can provide a scientific basis for virus tracing, pathogen mutation tracking, new strain identification and early warning, etc.

The invention discloses a copy number variation detection method, device and equipment based on low-depth whole genome sequencing and a storage medium, and relates to the technical field of medical data processing, the method comprises the following steps: performing sequencing quality control on sample gene data to obtain filtered gene data; performing data preprocessing on the filtered gene data through a dynamic negative reference library and a reference genome to obtain processed gene data and a dynamic Z test result; the dynamic negative reference library is determined according to the GC content of the contrast negative sample set; and performing improved copy number variation detection according to the processed gene data and the dynamic Z test result to obtain a copy number variation detection result. According to the method, sequencing quality control is carried out firstly, and data quality is guaranteed; and then data preprocessing is performed based on a dynamic negative reference library constructed in real time, and finally CNV detection is performed based on optimized processing gene data and a dynamic Z test result, so that systematic deviation is effectively reduced, and the detection reliability is improved.

The invention provides a non-lineage animal pairing evaluation method based on genome data, and belongs to the technical field of bioinformatics and protection genetics, the method comprises the following steps: firstly, obtaining whole genome sequencing data of all individuals in a population, and carrying out quality control to obtain a high-quality SNP site set; aiming at all possible male and female pairing combinations in the population, calculating an inter-parent genetic coefficient depKin, an inter-parent heterozygous difference ratio HDR and an inter-parent potential risk load index GRLI, and predicting a fixed proportion Proh of ROH of offspring; performing z-score standardization processing on the four genetic indexes: performing principal component analysis on standardized data, extracting the first two principal components PC1 and PC2, determining a weight according to a variance contribution rate, and calculating a pairing comprehensive score; and generating a pairing candidate recommendation list for each individual according to the comprehensive score, and screening a high-quality pairing scheme. The method disclosed by the invention can be completely independent of pedigree records, and genetic evaluation is directly carried out based on genome data.

The application provides a STR typing method applied to second-generation sequencing data, and relates to the technical field of biology.The method specifically comprises the following steps: customizing an STR locus configuration file; constructing a k-mer index library of a flanking sequence of the STR locus; extracting STR allele sequences from each READ of a sequence alignment file in combination with a CIGAR value and the k-mer index; constructing a PCR ghost peak model of the STR locus, and estimating parameters of the PCR ghost peak model by using a maximum likelihood estimation method; estimating candidate allele frequencies by using a second-generation sequencing sample data set; calculating posterior probabilities of all candidate alleles by using an allele set extracted from a given sequence alignment file, and inferring the most possible allele.The STR typing method has higher detection rate and typing accuracy, and has faster typing speed, and can be used for whole genome sequencing data, high-coverage targeted sequencing data or amplicon sequencing data.

The invention relates to a breeding method of Lingnan pigeons, belongs to the field of poultry genetic breeding, and mainly solves the problems of low growth speed and low meat yield of meat pigeons. The method comprises the following steps: firstly, selecting purebred male Shiqi pigeons and purebred female mimassa pigeons to establish a basic group, and naturally mating according to a male-female ratio of 1: 1 to obtain F1-generation hybrid pigeons; measuring the growth performance index and the reproductive performance index of the F1 generation, calculating the breeding index through an index selection method, and selecting and remaining the first 50% of individuals; mating the selected F1-generation male and female pigeons according to a ratio of 1: 1 to obtain an F2-generation, collecting gene samples of the F1-generation male and female pigeons, carrying out whole genome sequencing, and screening out core genes CTNNB1 and MYO9A for regulating and controlling the growth speed and the meat yield; f2-generation individuals conforming to target traits are selected and reserved based on genotypes for cross-crossing fixation to form two-line hybrid pigeons; and finally, carrying out three-way hybridization on the two-line male pigeons as male parents and American king pigeons as female parents to obtain commercial generation Lingnan pigeons. According to the method, the growth performance, the meat yield and the stress resistance of commercial generation pigeons are remarkably improved through combination of multi-generation hybrid advantage integration and a molecular breeding technology.

The invention discloses an X-chromosome specific molecular marker of micropterus salmoides and application of the X-chromosome specific molecular marker. On the basis of a whole genome sequencing technology, the X chromosome specific molecular marker of micropterus salmoides is obtained. Aiming at the molecular marker, the invention also provides a detection primer pair and a detection method of the molecular marker, and by detecting the molecular marker, rapid and accurate screening of YY supermale fish individuals can be realized to obtain a YY supermale fish population. The obtained YY super-male fish group and a proper female fish group are jointly fed and bred, and then the micropterus salmoides all-male fingerling can be obtained. If the YY super-male fish group and the YY pseudo-female fish group are jointly bred and bred, largemouth bass offspring which is all YY super-male fish can be obtained. Compared with a traditional all-male breeding method of the largemouth black bass, the all-male breeding method of the largemouth black bass is beneficial to simplifying all-male breeding steps of the largemouth black bass, shortening breeding time, and beneficial to cultivation of all-male largemouth black bass fingerlings and popularization of single-male breeding of the largemouth black bass.

The invention discloses panda-derived tryptophan-producing streptococcus non-lactolyticus C49 and application thereof, and belongs to the field of microorganisms, the strain is preserved in Guangdong Microbial Culture Collection Center, and the preservation number is GDMCC No: 67209. The strain has good acid-resistant and cholate-resistant characteristics, and can ensure that enough biomass passes through stress of a digestive tract environment; whole genome sequencing finds that C49 is significantly related to the pathway and module of tryptophan biosynthesis. Whole genome sequencing and in-vitro fermentation confirm that C49 has tryptophan biosynthesis capability, and in-vivo animal tests confirm that C49 has synthetic nerve conditioning capability. Therefore, as a probiotic feed additive, the streptococcus non-lactolyticus C49 has a good application prospect in the aspects of improving the feed value, improving the intestinal health of animals, enhancing the immunity of organisms and the like.

Methods for treating and / or assessing a subject having a symptomatic multiple myeloma or a precursor thereof, where the methods involve characterizing a plasma cell dyscrasia (e.g., monoclonal gammopathy of undetermined significance, smoldering multiple myeloma, multiple myeloma, plasma cell leukemia) in a biological sample from a subject as being high, medium, or low risk by assigning to the plasma cell dyscrasia a multiple myeloma (MM)-like score. The methods may involve sequencing DNA from the biological sample using whole-genome sequencing (WGS).

The invention relates to a disease-specific quantitative trait locus identification method based on multi-omics integration. The method comprises the following steps: acquiring variation sites of whole genome sequencing data of a target object, and molecular phenotypes and molecular abundance of molecular phenotype data; determining an association significance probability value of an association pair formed by the variation point and the molecular phenotype based on the variation point and the molecular abundance, and screening a first association pair from the association pair based on the association significance probability value and condition analysis; determining a consistent second association pair in the normal association pair and the disease association pair, and determining a third association pair with a disease interaction effect in the second association pair; calculating a first effect estimation value and a second effect estimation value of each third association pair; and based on the first effect estimation value and the second effect estimation value of the third correlation pair, determining a target correlation pair related to the Parkinson's disease, and taking the target correlation pair as the identified quantitative trait site. By adopting the method, the Parkinson's specific pathogenic heritable variation can be accurately identified.

The invention provides a cactus plant species identification method based on high-throughput sequencing data. A specific variation region in a cactus chloroplast genome is screened based on a high-throughput sequencing data system, and a standardized cactus plant species rapid identification process is developed by combining Pi value screening and specific variation region marking. Compared with a traditional DNA bar code fragment, the identification precision of the targeted specific variation region is remarkably improved, so that species with highly overlapped forms can be effectively distinguished, and the identification accuracy is improved. Meanwhile, the method greatly reduces the technical threshold and cost, PCR amplification is performed on the DNA of the sample to be detected by designing a specific primer of a targeted specific variation region, whole genome sequencing and assembly are avoided, the detection cost and detection period of a single sample are reduced, and the method is compatible with a conventional PCR platform and has high practicability. And on-site rapid detection of scenes such as a medicinal material market and a customs port becomes possible.

This invention provides a data storage method and system for tuberculosis detection, relating to the field of tuberculosis detection technology. The data storage method for tuberculosis detection includes the following steps: S1. Collecting whole-genome sequencing data of Mycobacterium tuberculosis, host serum IgG titer, and drug sensitivity test results; S2. Calculating genetic distance D based on a reverse evolution model to generate four-dimensional spatiotemporal coordinates (t, x, y); S3. Performing data partitioning and storage based on the drug target barrier value β; S4. Generating dynamic metadata using a host-pathogen dynamics model and compressing and storing it. This invention implements a dynamic storage entropy adjustment algorithm at the hardware and software collaborative level, continuously optimizing the matching efficiency of data compression and physical storage. This results in an intelligent data hub that can perceive the evolutionary pulse of pathogens and autonomously optimize resources, providing support for clinical tuberculosis prevention and control decisions with temporal depth, spatial correlation, and risk evolution.

This invention discloses a method for directed evolution of antibiotic-resistant Escherichia coli strains based on cytidine deaminase, belonging to the field of microbial directed evolution and genetic engineering technology. This method uses E. coli as the host, introducing a recombinant plasmid expressing an optimized double-stranded cytidine deaminase mutant. Utilizing the low toxicity and high mutagenicity of this mutant, continuous passage evolution is carried out under gradient concentrations of aminoglycoside antibiotics (kanamycin and streptomycin). Combined with whole-genome sequencing, molecular docking, and reverse genetics verification, the A145T missense mutation in the wcaE gene is identified as the core functional site. This invention overcomes the shortcomings of traditional spontaneous and chemical mutagenesis, which suffer from low efficiency and significant strain damage. The mutation type is controllable, the evolutionary cycle is short, and the obtained engineered strains can tolerate up to 300 mg / L kanamycin while exhibiting streptomycin cross-resistance, and the genetic stability of the tolerance trait is strong. This method is simple, highly reproducible, and suitable for industrial breeding of stress-resistant E. coli, and can be widely applied in antibiotic fermentation, industrial microbial culture, and other scenarios.

Embodiments of systems, methods, and compositions provided herein relate to assays for selectively controlling enzymatic reactions. Some embodiments relate to methods of inhibiting, reducing, or eliminating secondary DNA (such as mitochondrial DNA) sequencing reads from open chromatic sequencing, whole genome sequencing, or targeted sequencing.

The invention belongs to the technical field of medical software development, and particularly relates to a plateau newborn inherited metabolic disease screening system, a computer readable storage medium and application of the plateau newborn inherited metabolic disease screening system. According to the screening system, an altitude hierarchical multi-level reference value database based on a local healthy newborn queue is established, and the problem that the false positive rate of a plain area screening model in a plateau area is too high is solved by fitting an altitude metabolism marker reference median and a standard deviation curve. By designing a'biochemical primary screening-risk scoring-targeted sequencing automatic triggering 'three-level joint control data processing flow, targeted sequencing guided by a crowd specific pathogenic mutation library is started only when the biochemical risk is high, unnecessary whole genome sequencing is avoided, and the screening cost is remarkably reduced. The system can continuously iterate a reference curve and a risk threshold value according to definite diagnosis data, and closed-loop dynamic optimization from sample collection to report generation is achieved. The method has plateau adaptability, crowd specificity and cost controllability, and has a good clinical application prospect.

This disclosure relates to a technique for identifying tumor-specific mutations through integrated analysis of next-generation sequencing data using machine learning models. In certain embodiments, a computer implementation method is provided, comprising: generating sequence reads from one or more samples collected from the same patient; generating variant calling files by analyzing the sequence reads corresponding to each of the one or more samples; generating a list of candidate somatic variants by comparing the variant calling files; generating a score for each of the candidate somatic variants in the list of candidate somatic variants using a classification machine learning model, wherein the score is generated based on a plurality of classifications generated by the classification machine learning model; determining the ctDNA status for the patient based on the score, wherein the ctDNA status is either positive or negative; and generating a report providing the ctDNA status for the patient.

The present disclosure is in the field of low depth whole genome sequence and genetic sequencing. In particular, method of detecting contamination based on haplotype detection of the mitochondrial DNA.

The application discloses a method, device and storage medium for detecting mitochondrial-derived nuclear genome sequences. The method comprises the following steps: aligning whole genome sequencing data to a mitochondrial reference genome rCRS, retaining the reads aligned to the rCRS, aligning the reads to a reference sequence containing 23 pairs of chromosomes and the rCRS, removing non-unique alignment reads; extracting potential junction reads, clustering the junction reads within a distance of 50 bp according to the alignment positions, locating the coordinates and directions of the integrated mitochondrial DNA fragments, and the nuclear genome integration position; searching for inconsistent alignment read pairs within 100 bp upstream and downstream of a read cluster, and counting the number of the inconsistent alignment read pairs as support information for the existence of non-ref NUMTs. The application utilizes the alignment information of the junction reads, detects the non-ref NUMTs through local assembly and clustering, reduces the false positive rate, can obtain accurate breakpoint and fragment information, is simple to operate, and has low detection cost.

The invention discloses a primer group and method for human metapneumovirus whole genome sequencing and application. Two groups of specific primer pools are designed for the metapneumovirus, totally comprise 21 primers, can effectively amplify the metapneumovirus type A and the metapneumovirus type B, are high in sensitivity and suitable for multi-platform detection, and provide a new direction for detection, typing, traceability and evolutionary analysis of the metapneumovirus.

The invention relates to the technical field of bioinformatics and crop breeding, and particularly discloses a method, a device and equipment for predicting the close planting yield of brassica napus by using hypocotyl length based on a whole genome selection technology. The method is characterized by comprising the following steps: acquiring whole genome sequencing data of brassica napus germplasm; inputting the whole genome sequencing data into a target model; outputting hypocotyl length data of the brassica napus under a close planting condition through the target model; and according to the hypocotyl length data of the brassica napus under the close planting condition, obtaining a brassica napus germplasm yield potential sorting result. According to the method, whole genome selection and key morphological characters (hypocotyl length) under specific stress (close planting conditions) are combined for the first time, high-yield varieties suitable for close planting cultivation can be efficiently and accurately screened out without on-site close planting tests in the early stage of rape breeding, and the breeding efficiency is remarkably improved.

The invention relates to a primer set for whole genome sequencing of chlamydia psittaci, the primer set comprises a primer subset p1 and a primer subset p2, the primer subset p1 comprises primers with sequences as shown in SEQ ID NO: 1-240, and the primer subset p2 comprises primers with sequences as shown in SEQ ID NO: 241-480. The primer group disclosed by the invention not only can accurately obtain the whole genome sequence of chlamydia psittaci, but also is adaptive to the sequencing modes of all second-generation and third-generation sequencing platforms.

The present invention provides a method, device, and application for detecting tumor molecular typing based on low-depth whole-genome sequencing. The method comprises: independently dividing low-depth whole-genome sequencing data into non-fixed bin groups and fixed bin groups; using the copy numbers of the non-fixed bin groups and the fixed bin groups to calculate the average copy number and mutation region ratio of each group; establishing a scoring model based on the average copy number and mutation region ratio to determine the copy number variation type at each structural level of the chromosome, and then deriving the corresponding molecular typing; wherein the non-fixed bin group includes a first target region belonging to the exon and an anti-target region outside the exon; the fixed bin group includes a second target region of 1M in length and a third target region of 10K in length obtained by continuous division. In this way, the copy number variation type of the chromosome at different hierarchical structural positions is obtained, thereby achieving more accurate molecular typing detection of the size of tumor chromosomes at each level.