357 results about "Variation (Genetics)" patented technology

Many areas of biomedical research depend on the analysis of uncommon variations in individual genes or transcripts. Here we describe a method that can quantify such variation at a scale and ease heretofore unattainable. Each DNA molecule in a collection of such molecules is converted into a single particle to which thousands of copies of DNA identical in sequence to the original are bound. This population of beads then corresponds to a one-to-one representation of the starting DNA molecules. Variation within the original population of DNA molecules can then be simply assessed by counting fluorescently-labeled particles via flow cytometry. Millions of individual DNA molecules can be assessed in this fashion with standard laboratory equipment. Moreover, specific variants can be isolated by flow sorting and employed for further experimentation. This approach can be used for the identification and quantification of rare mutations as well as to study variations in gene sequences or transcripts in specific populations or tissues.

The present invention provides assays systems and methods for detection of genetic variants in a sample, including copy number variation and single nucleotide polymorphisms. The invention preferably employs the technique of tandem ligation, i.e. the ligation of two or more fixed sequence oligonucleotides and one or more bridging oligonucleotides complementary to a region between the fixed sequence oligonucleotides.

Methods and uses for molecular tags are disclosed. Molecular tags may be attached to nucleic acid molecules. The attachment of the nucleic acid molecules prior to PCR amplification and sequencing improves the accuracy of genetic analysis and detection of genetic variations and diversity. Molecular tags may also be used for detection of drug-resistant variants. Methods for using molecular tags for determining and correcting PCR errors and/or sequencing error are also disclosed.

In one aspect, the invention provides a method of screening and, optionally, treatment of an individual suffering from an insulin resistance disorder by screening an individual in need of treatment for an insulin resistance disorder for one or more genetic variations indicating a predisposition to a response to an insulin sensitizer; and, optionally, administering or not administering an insulin sensitizer to the individual based on the results of the screening. The insulin sensitizer for which the individual is screened and the insulin sensitizer that is administered or not administered may be the same or different. In another aspect, the invention provides methods comprising identifying one or more genetic variations, e.g., one or more single nucleotide polymorphisms, that at least partly differentiate between a subset of a plurality of individuals who experience a response when administered an insulin sensitizer, and a subset of said plurality of individuals who do not experience a response when administered the insulin sensitizer. The invention also provides nucleic acids, polypeptides, antibodies, kits, and business methods associated with these screening and association methods.

The invention provides a comprehensive, rapid, unbiased, and accurate method for identifying and/or discovering disease-associated genetic variations, e.g., disease-associated variations. The present invention further provides novel disease-associated genetic variations for use as genetic markers of disease, e.g., cancer. The invention further provides methods for assessing an individual's risk for developing a disease, e.g., cancer, by detecting the presence the novel disease-associated genetic variations of the invention.

Various embodiments of the presently described invention provide a method for evaluating correlations between genetic variations and clinical information. The method includes normalizing one or more of genotypic data and clinical data associated with each of a plurality of patients in a population of patients, receiving one or more clinical conditions from a user, selecting a subset of patients from the population based on the clinical conditions, and determining one or more correlations between at least one of the clinical conditions and one or more of the genotypic and clinical data for the patient subset.

The reconstruction of genetic networks in mammalian systems is one of the primary goals in biological research, especially as such reconstructions relate to elucidating not only common, polygenic human disease, but living systems more generally. The present invention provides novel gene network reconstruction algorithms that utilize naturally occurring genetic variations as a source of perturbations to elucidate the networks. The algorithms incorporate relative transcript abundance and genotypic data from segregating populations by employing a generalized scoring function of maximum likelihood commonly used in Bayesian network reconstruction problems. The utility of these novel algorithms can be demonstrated via application to gene expression data from a segregating mouse population. The network derived from such data using the novel network reconstruction algorithm is able to capture causal associations between genes that result in increased predictive power, compared to more classically reconstructed networks derived from the same data.

A database of genetic variations is analyzed to produce a haplotype map of the genome for strains of a single species. A computational method is used to rapidly map complex phenotypes onto the haplotype blocks within the haplotype map. The specific genetic locus regulating three different biologically important phenotypic traits in mice is identified using these systems and methods.

The invention discloses an industrial control protocol vulnerability mining system based on a fuzzy test. The system comprises a protocol analyzing module, a data construction module, a genetic variation module, a session management module, an agent module, a drive module and an auxiliary tool module; the genetic variation module, the session management module and the agent module are connected with the drive module; the protocol analyzing module is connected with the data construction module and then is connected with the genetic variation module; and the drive module is used for connecting a test target. According to the system, the conditions of the tested target can be learned and analyzed; related data such as test scripts and a test case are specifically constructed according to the analyzed information; the hit rate of the test case is increased through analyzing the tested target; in a test process, the generation method or variation direction of the test case is adjusted specifically according to the information such as the current state of the tested target and the feedback of the test case; the vulnerability mining efficiency is improved through an efficient adjusting algorithm; and moreover, the system adaptation is increased.

The present invention is in the field of nucleic acid-based genetic analysis. More particularly, it discloses novel insights into the overall structure of genetic variation in all living species. The structure can be revealed with the use of any data set of genetic variants from a particular locus. The invention is useful to define the subset of variations that are most suited as genetic markers to search for correlations with certain phenotypic traits. Additionally, the insights are useful for the development of algorithms and computer programs that convert genotype data into the constituent haplotypes that are laborious and costly to derive in an experimental way. The invention is useful in areas such as (i) genome-wide association studies, (ii) clinical in vitro diagnosis, (iii) plant and animal breeding, (iv) the identification of micro-organisms.

The present invention discloses methods for combining data on genetic variations and phenotypes of individuals to predict a phenotype-of-interest. The present invention also discloses kits that can be used to determine if an individual has or does not have a phenotype-of-interest. The kit can include at least one diagnostic tool and written instructions.

Computationally-efficient techniques facilitate secure crowdsourcing of genomic and phenotypic data, e.g., for large-scale association studies. In one embodiment, a method begins by receiving, via a secret sharing protocol, genomic and phenotypic data of individual study participants. Another data set, comprising results of pre-computation over random number data, e.g., mutually independent and uniformly-distributed random numbers and results of calculations over those random numbers, is also received via secret sharing. A secure computation then is executed against the secretly-shared genomic and phenotypic data, using the secretly-shared results of the pre-computation over random number data, to generate a set of genome-wide association study (GWAS) statistics. For increased computational efficiency, at least a part of the computation is executed over dimensionality-reduced genomic data. The resulting GWAS statistics are then used to identify genetic variants that are statistically-correlated with a phenotype of interest.

Dual nucleic acid probes with resonance energy transfer moieties are provided. In particular, fluorescent or luminescent resonance energy transfer moieties are provided on hairpin stem-loop molecular beacon probes that hybridize sufficiently near each other on a subject nucleic acid, e.g. mRNA, to generate an observable interaction. The invention also provides lanthanide chelate luminescent resonance energy transfer moieties on linear and stem-loop probes that hybridize sufficiently near each other on a subject nucleic acid to generate an observable interaction. The invention thereby provides detectable signals for rapid, specific and sensitive hybridization determination in vivo. The probes are used in methods of detection of nucleic acid target hybridization for the identification and quantification of tissue and cell-specific gene expression levels, including response to external stimuli, such as drug candidates, and genetic variations associated with disease, such as cancer.

The invention discloses a method and a system for intelligently interpreting and reporting the genetic variation of a single gene disease, which can automatically analyze the genetic variation resultbased on the original sequence data of a gene of a patient, and provide a professional genetic variation analysis report, thereby improving the diagnosis and treatment efficiency of the genetic variation. The method comprises the following steps of: gene sequence data is acquired and attribute marking is performed on the gene sequence data; sequence alignment of each set of gene sequence data withhuman reference genome is performed to obtain corresponding amount of alignment data; based on the length information of genetic variation, the variation type is identified, and the variation function is predicted based on the position information and base change information of genetic variation. According to the identification results of each genetic variation type, the gene and population frequencies of genetic variation were annotated, and the family genetic pattern was judged when the family detection mode was used. The system comprises the method proposed in the technical proposal.

The invention discloses a method for solving flexible job shop scheduling based on a hybrid whale swarm algorithm, and the method comprises the steps: firstly defining the coding mode of flexible jobshop scheduling as two-stage random key coding, and then carrying out the mapping conversion through employing a conversion mechanism; Defining the shortest total processing time for solving the fitness function as an optimization target; Secondly, initializing parameters and whale population in the flexible job shop scheduling problem by adopting a whale group algorithm, wherein initialization isdivided into a sorting scheme of a random generation process and a genetic variation mode of an improved genetic algorithm to generate a better machine distribution scheme corresponding to the sorting scheme of the process, and then a better initial population is generated; Calculating the fitness value of each scheduling scheme, and finding and reserving the best scheduling solution; And finally, outputting the optimal scheduling solution and the corresponding fitness function value to obtain a solved optimal scheduling scheme, and solving the problems of low solution precision and low convergence rate in the existing flexible job shop scheduling problem.

The invention relates to a cotton breeding method. In the method, a combination part of genetic variation generated by cotton graft is used as an explant for inducing to culture callus; the cultured callus is subjected to propagation, subculturing and differentiated culture to obtain cotton seedlings; and after hardening off, the cotton seedlings are grafted for transplantation or directly transplanted. The cotton breeding method has the advantages that: by utilizing graft to create genetic variation, the method not only improves plant quality, yield, stress resistance, and the like, but also obtains distant variation which cannot be obtained through sexual hybridization, and has simple operation, high seed selection efficiency and low cost; the method provides a novel cotton transgenic means and can transfer target gene to a breed to be improved to generate a variation type combining the merits of parental stock and cion parents; and the creation of genetic variation by utilizing graft can be taken as a supplementary means of general breeding and modern gene engineering breeding and is an important breeding means with broad prospects.

The invention provides methods, apparatuses, and compositions for high- throughput amplification sequencing of specific target sequences in one or more samples. In some aspects, barcode-tagged polynucleotides are sequenced simultaneously and sample sources are identified on the basis of barcode sequences. In some aspects, sequencing data are used to determine one or more genotypes at one or more loci comprising a causal genetic variant. In some aspects, systems and methods of detecting genetic variation are provided.

The invention discloses infective clone for porcine circovirus type 1 and rescued virus and application thereof. Two genomes of the porcine circovirus type 1 are connected in cis and inserted into a vector to construct and obtain an infective molecular clone. A Sal I enzyme cutting site as a molecular target is inserted in the infective molecular clone. A rescued recombinant virus (PCV1/G strains) carries a molecular marker, and the preservation number of the rescued recombinant virus is CGMCC NO.2658. An antigen of the recombinant virus is only reacted with a univalent specific antibody of PCV1/Cap protein, but has no cross with an antibody against PCV2/Cap protein. The recombinant virus and a parental virus are identified by combination of PCR and RFLP. The virus strain cultured in vitro has stable propagation property and high virus titer, and the rescued virus strain can be used for detecting the antibody of the virus. The invention lays a foundation for research such as genesis and evolution, genetic variation rule, molecular differential diagnosis, and the like for porcine circovirus in future.

The present invention is directed to compositions and methods for producing a dominant high-amylopectin starch trait in cereal grain and methods for screening grain for genetic variation in hydrolysis and fermentation time.

The physiological regulation of intake, growth and energy partitioning in animals is under the control of multiple genes, which may be important candidates for unraveling the genetic variation in economically relevant traits in beef production. The present invention relates to the identification of single nucleotide polymorphisms (SNPs) within the bovine gene encoding mitochondrial transcription factor A (“TFAM”) and their associations with economically relevant traits in beef production. The invention further encompasses methods and systems, including network-based processes, to manage the SNP data and other data relating to specific animals and herds of animals, veterinarian care, diagnostic and quality control data and management of livestock which, based on genotyping, have predictable meat quality traits, husbandry conditions, animal welfare, food safety information, audit of existing processes and data from field locations.