71 results about "SNP genotyping" patented technology

The invention belongs to the technical field of sweet potato breeding, and provides an SNP marker related to sweet potato root color and anthocyanin content and application of the SNP marker, the SNP marker is located at the 25658800th site of a chromosome 10a of sweet potatoes, and the base polymorphism is A / T. When the SNP genotype of the sample to be detected is A / T, the content of anthocyanin in the tuberous roots is high, and the color is purple; when the SNP genotype is T / T, the content of anthocyanin in the tuberous roots is low, and the tuberous roots are non-purple in a large probability. According to the detection method and the kit provided by the invention, the efficiency of identifying the purple sweet potatoes by the developed SNP marker through sweet potato natural population phenotype identification and verification reaches 100%, the efficiency of identifying the non-purple sweet potatoes reaches 85.04%, the color of the sweet potato tuberous roots and the anthocyanin content can be rapidly and accurately detected, and the detection method and the kit have the advantages of being simple and convenient to operate, low in cost and the like, and have wide application prospects. The requirement of large-scale molecular marker-assisted selection can be met.

The invention provides a method for deducing the abundance of each family in a group based on mixed pool simplified genome sequencing, which comprises the following steps of: (1) establishing a parent 2b-rad library, and extracting SNP (Single Nucleotide Polymorphism) genotypes and sites by using a 2b-rad standard process; combining the SNP genotypes of the 2n parents into genotypes of n parent pairs according to a male parent and female parent relationship; comparing the genotypes of the parent pairs, and determining family specific tags; (2) extracting offspring individual tissues, mixing, and carrying out DNA extraction and 2b-rad library building sequencing on the mixed sample tissues; counting the sequencing depth of all the specific tag sites and calculating the secondary allele frequency of the specific tag of the mixed sample filial generation; and (3) calculating the proportion of each family in the offspring according to the sequencing depth of the specific tag site and the secondary allele frequency of the specific tag of the mixed offspring. According to the method, the overall feature distribution of the family can be accurately evaluated without sequencing each individual, so that the cost is greatly reduced.

The invention discloses an SNP (Single Nucleotide Polymorphism) marker-based rice disease resistance character whole genome association analysis method, which relates to the technical field of biology, and is characterized by comprising the following steps: selecting a representative genetic recombination population, carrying out high-density SNP genetic typing on the population, and combining recombination event positioning and linkage analysis to obtain the disease resistance character whole genome association analysis of rice. Obtaining genetic parameters reflecting recombination frequencies of different genome segments; on the basis of the obtained original genetic data, parent and offspring genotype information is further integrated, fine positioning and statistics are carried out on recombination breaking points, and a high-resolution genetic map is constructed. By constructing a high-resolution genetic map and combining feature engineering and machine learning, accurate identification and dynamic SNP encryption of a high-recombination region are realized, the marker coverage and associated signal capture capability of the region is enhanced, the functional site leak detection risk is reduced, and the detection efficiency is improved. The positioning accuracy and the molecular breeding application effect of the rice disease resistance character related candidate gene are improved.

This invention belongs to the field of biochip technology, specifically an erasable single nucleotide polymorphism (SNP) genotyping chip and its detection method. The erasable SNP genotyping chip provided by this invention is prepared using polystyrene microspheres, capture probes, and a silicon substrate. In the SNP recognition stage, it relies on a FEN1 enzyme-mediated invasive reaction. Based on the technical characteristics of this invasive reaction, downstream probes A and B are designed with self-protective hairpin structures, preventing false positive signals from hybridization with the capture probe even when added in excess, thus significantly improving detection specificity. The detection method of the erasable SNP genotyping chip provided by this invention overcomes the long-standing problem of high application costs caused by the single-use nature of solid-phase SNP gene detection chips.

The invention belongs to the technical field of aquatic product breeding, and particularly relates to a KASP molecular marker related to high temperature resistance character of patinopecten yessoensis and application of the KASP molecular marker in genetic breeding. On the basis of genome re-sequencing of 200 patinopecten yessoensis, a PySNP587919 locus obviously associated with the patinopecten yessoensis high-temperature-resistant character is screened by combining a whole genome SNP genotype and whole genome association analysis of the patinopecten yessoensis high-temperature-resistant character, and after the reliability of the locus is verified through Sanger sequencing, the locus is developed into a KASP marker, and the KASP marker can be used for identifying the high-temperature-resistant character of the patinopecten yessoensis and identifying the high-temperature-resistant character of the patinopecten yessoensis. The screening method can be used for screening the high-temperature-resistant comb shells. Furthermore, the invention also establishes a method for screening the high-temperature-resistant patinopecten yessoensis, and the method is efficient and accurate. Therefore, the technical scheme provided by the invention is suitable for molecular marker-assisted breeding work, rapid and effective screening of parents can be realized by typing the PySNP587919 site, and the breeding efficiency is improved.

The application discloses a method for screening superior parents of carp with high total content of polyunsaturated fatty acids. The method comprises obtaining training characteristic data and training target data, wherein the training characteristic data comprises SNP genotype information of training samples, and the training target data comprises total content information of polyunsaturated fatty acids of the training samples; training a ridge regression model by using the training characteristic data and the training target data to obtain a prediction model; obtaining SNP genotype information of a to-be-tested sample; obtaining a breeding value of the to-be-tested sample according to the SNP genotype information of the to-be-tested sample and the prediction model; and screening superior parents of carp with high total content of polyunsaturated fatty acids according to the breeding value. By the method, the breeding value of the to-be-tested sample can be directly obtained according to the SNP genotype information of the to-be-tested sample and the prediction model, and then the superior parents of carp with high content of polyunsaturated fatty acids can be screened from the to-be-tested sample, thereby providing excellent materials for new germplasm identification and breeding of carp.

The invention discloses an SNP phenotype prediction method based on deep learning, and relates to the technical field of data processing, and the method comprises the following steps: S1, obtaining SNP genotype data of a VCF file, and generating a double-character coding sequence; s2, constructing an SNP (Single Nucleotide Polymorphism) basic model; s3, based on the double-character coding sequence, training the SNP basic model; and S4, performing phenotype prediction by using the trained SNP basic model. According to the method, the pre-training thought of deep learning is utilized to directly perform SNP phenotype prediction, starting from genomic sequence features, the BERT architecture is further extended to the field of genomics, and a more direct and efficient calculation method is provided for phenotype prediction.

The invention provides a method for screening candidate genes and SNP (Single Nucleotide Polymorphism) loci related to residual feed intake of Sahu hybrid sheep, which is characterized by comprising the following steps: S1, collecting jugular vein blood samples of the Sahu hybrid sheep, and extracting genomic DNA (Deoxyribose Nucleic Acid) of the blood samples for quality detection; the method comprises the following steps: S1, extracting DNA, S2, carrying out whole genome re-sequencing on the extracted DNA and carrying out genotyping to obtain SNP genotype data, and S3, carrying out reference genome comparison, SNP detection and genotype quality control. And S4, carrying out whole genome association analysis on the residual feed intake character of the Sahu hybrid sheep to obtain a significant SNP site. The nucleotide sequence of the SNP site obviously related to the residual feed intake of the Sahu hybrid sheep, which is obtained by the method provided by the invention, is as shown in SEQ ID NO.1, the basic group R at the 51st site of the sequence is A or G, the gene mutation causes the nucleotide of the sequence to generate polymorphism, and when the marker is mutated into G, the Sahu hybrid sheep shows lower residual feed intake.

The invention discloses an SNP (Single Nucleotide Polymorphism) marker related to cane sugar components of sugarcanes. The inventor finds that genotypes at 47469846bp positions of a sugarcane chromosome 3 are highly related to sugarcane sucrose components, and researches find that the sucrose components of sugarcanes with 91.72% of SNP genotypes AA are all higher than 15.0%, the sucrose components of sugarcanes with 72.73% of SNP genotypes AG are all higher than 15.0%, the sucrose components of sugarcanes with 0.00% of SNP genotypes GG are all higher than 15.0%, and the sucrose components of sugarcanes with 0.00% of SNP genotypes GG are all higher than 15.0%. Therefore, the genotype at the position can be used as the SNP marker of the sucrose component of the sugarcane. By utilizing the discovery, the SNP marker is applied to the detection of the sucrose content of the sugarcane, and the cultivation of a high-sugar sugarcane variety is facilitated.

This invention provides a set of core molecular markers for peas developed based on KASP technology and its applications, belonging to the field of molecular detection technology. This invention utilizes KASP-based SNP markers, including 25 core SNP markers, which are evenly distributed across the seven chromosomes of the pea genome, with 3-4 SNP markers on each chromosome. Based on this set of core molecular markers for peas, high-throughput SNP genotyping detection can be performed on pea resources or varieties, enabling the identification and purity testing of commercial pea varieties; it can be used to construct pea fingerprint libraries; and it can be applied to the genetic diversity analysis of pea germplasm resources; it is low-cost and highly efficient.

This application relates to the technical field of biological gene detection, specifically disclosing a miniature pig SNP molecular marker combinatorial system and its application. The miniature pig SNP molecular marker combinatorial system disclosed in this application includes at least one of 221 SNP molecular markers. The physical locations of these 221 SNP molecular markers are determined based on sequence alignment during 10× coverage whole-genome sequencing of miniature pigs. The site information of the 221 SNP molecular markers is shown in Table 1. The miniature pig SNP molecular marker combinatorial system provided in this application is used for detecting SNP genotyping in miniature pigs and possesses novel, stable, cost-effective, and efficient properties.

The application discloses a kind of molecular breeding methods of apricot flower chicken for optimizing meat quality, it is related to molecular assisted selection, the method comprises: the index correlation analysis is carried out to the chicken of selected variety;Statistical meat quality trait target characteristic value is inconsistent with the first occurrence frequency ratio of the first selected chicken trait record data of variety in the index of feeding condition;Statistical meat quality trait target characteristic value is consistent with the second occurrence frequency ratio of the first selected chicken trait record data of variety in the index of feeding condition, the average of second occurrence frequency ratio is third occurrence frequency ratio;When the first occurrence frequency ratio or third occurrence frequency ratio is greater than or equal to occurrence frequency ratio threshold value, add variety chicken into SNP genotyping chicken;According to SNP genotyping variety chicken, apricot flower chicken molecular breeding is carried out.Solve the problem that the existing breeding method carries out genotyping detection to each variety of apricot flower chicken, determines the correlation of trait and genotype, selects variety and then optimizes apricot flower chicken meat quality, resulting in low efficiency.

The application discloses a SNP genotype coding method, comprising the following steps: obtaining genomic selection data and a genomic annotation file, wherein the data comprises SNP input data; the SNP input data comprises chromosome number and SNP position; sorting columns of a data table according to the chromosome number and the SNP position; preprocessing the data table to obtain SNP coding; extracting the genomic annotation file to obtain SNP type information; forming SNP columns in the data table at the SNP positions, traversing adjacent SNP columns, storing the SNP columns into channels, and completing the channels; and coding the filled SNP based on the SNP type information and the SNP coding to obtain a sample vector. The sample vector can be used as an input of a convolutional neural network, so that information contained in the genomic annotation file can be applied to deep learning.

The invention discloses a gene expression profile prediction method and device, electronic equipment and a storage medium, and relates to the technical field of artificial intelligence. Specific genetic variation and regulation region sequences in a peripheral blood sample are detected, and a standardized SNP genotype matrix and a regulation annotation vector are obtained; constructing a gene-pathway-disease-drug four-layer regulation and control network based on multi-source heterogeneous data, and determining a core node gene based on the constructed network; obtaining LD structure information and chromatin accessibility characteristics corresponding to the core node gene; and taking the standardized SNP genotype matrix corresponding to the core node gene, the regulation and control annotation vector, the LD structure information and chromatin accessibility characteristics as input of a pre-trained gene expression profile prediction model to obtain a gene expression profile prediction value of an individual corresponding to the peripheral blood sample in a specified brain region. Therefore, an accurate mapping relation between the blood gene expression data and the gene expression data of the targeted CNS tissue is established.

This invention discloses a SNP molecular marker, detection product, and application related to bull sperm motility based on the HSPB9 gene. These findings pertain to molecular biology technology. The SNP molecular marker is located at position 42255643 in the bovine genome, Chr19:42255643, and is polymorphic to either C or T. Research has found that the SNP genotype combination associated with high bull sperm motility is TT. By detecting the polymorphism at this SNP locus, bull sperm motility can be assessed, thereby assisting breeding efforts and providing reliable support for the production of high-quality offspring. This method offers advantages such as high reliability, high efficiency, and low cost.

The application discloses an application of a GhSCAR4 gene related to oil content and protein quality of Gossypium hirsutum L.The application provides a cDNA sequence SEQ ID NO.1 and a genome sequence SEQ ID NO.2 of the gene in tetraploid Gossypium hirsutum L.The gene is obtained by resequencing and whole genome association analysis of Gossypium hirsutum L.varieties, and is significantly related to oil content and protein content of cotton seeds.The gene is used for distinguishing high-quality and low-quality haplotypes by using whether methylation variation and SNP genotypes of the gene occur.The varieties population is classified according to the haplotypes, and statistical analysis is carried out in combination with quality traits, and it is also proved that the GhSCAR4 gene is significantly related to the oil content and protein content of cotton seeds.The above results show that the gene has important research value and application prospect in efficient identification of high-oil and high-protein cotton varieties, improvement of the oil content and protein content of cotton and cultivation of new cotton varieties with high oil content and high protein content.

This application provides a method, apparatus, and electronic device for evaluating the effectiveness of SNP genotyping based on silhouette coefficients, relating to the field of SNP genotyping technology, and alleviating the technical problems in evaluating the effectiveness of SNP genotyping. The method includes: acquiring endpoint fluorescence intensity data for a target SNP locus; performing clustering based on the endpoint fluorescence intensity data using a clustering algorithm to obtain a first clustering result; filtering samples in the first clustering result using individual silhouette coefficients and a preset silhouette coefficient threshold to obtain a sample filtering result; and clustering the sample filtering result using the clustering algorithm to obtain a second clustering result.

The invention discloses application of an NDUFS1 gene molecular marker influencing the death rate of duck sperms in duck genetic breeding, and belongs to the technical field of biology. According to the method, SNP genotyping is performed by using a sequencing technology, the NDUFS1 gene molecular marker remarkably related to the death rate of the sperms is obtained through whole genome association analysis and screening, the death rate of the sperms of the ducks can be efficiently and rapidly identified through the method, and a scientific basis is provided for early breeding of high-quality ducks.

This invention discloses molecular markers related to the number of ears per unit area in wheat and their applications. This invention belongs to the field of biotechnology, specifically relating to molecular markers related to the number of ears per unit area in wheat and their applications. The method for identifying or assisting in the identification of the number of ears per acre in wheat includes detecting the genotype of a SNP locus in the genome of the wheat to be tested, and identifying or assisting in the identification of the number of ears per acre based on the genotype. The SNP locus is a single SNP locus on wheat chromosome 4A, with nucleotide type G or T, and is the 51st nucleotide of sequence 4 in the sequence listing. The number of ears per acre in the tested wheat with the SNP genotype TT is higher or a candidate higher than that in the tested wheat with the SNP genotype GG. The identification method and its primer composition of this invention can be used in wheat breeding and have broad application prospects.

The invention discloses an optimal prediction system for selecting black carp growth traits based on a whole genome and a construction method and application thereof.The system is composed of an optimal GS statistical model GBLUP model and an optimal SNP genotype site set with the number of 12000, the construction method comprises the steps that genome re-sequencing and genetic typing are conducted on 499 black carps, and 237730 high-quality SNP sites are obtained; carrying out whole genome association analysis by combining the phenotypic data of the growth traits of the black carps to obtain 9 SNP genotype site sets; 80% of a black carp group is used as a training group, black carp growth character phenotype data, five GS statistical models and nine SNP genotype site set data are utilized to establish a black carp growth character GS prediction model, a black carp growth character optimal prediction system is obtained through verification and screening, and breeding values of growth characters in the black carp group are rapidly and accurately calculated. The early prediction of the growth traits of the black carps is realized, and the black carps with good growth potential are screened.

The present invention discloses a paternity testing method and system based on a liquid biochip, belonging to the field of gene detection and data analysis technology. The method comprises obtaining SNP genotype data of each individual in a dairy cow population, wherein the SNP genotype data is collected via a liquid biochip; performing a similarity comparison on any two individuals in the dairy cow population, and determining the similarity value of the two individuals at each SNP site based on the degree of similarity of the SNP genotypes of the two compared individuals at the same SNP site; obtaining a calculation weight based on the type of SNP genotype; obtaining a similarity coefficient based on the similarity value and calculation weight of the two individuals at each SNP site; and determining the parent-child relationship between the two individuals based on the similarity coefficient. The method can quickly and accurately identify the parent-child relationship between a large group of dairy cows, solving the problem that the prior art of dairy cow paternity testing is complicated and ineffective, which is not conducive to efficient identification of large groups.

The invention relates to a method for applying an AK4 gene molecular marker to duck high sperm curve rate early breeding, and belongs to the technical field of biology, SNP genetic typing is carried out by utilizing a sequencing technology, the AK4 gene molecular marker obviously related to sperm curve rate is obtained through whole genome association analysis and screening, and in breeding, according to a breeding target, the AK4 gene molecular marker is applied to duck high sperm curve rate early breeding. By eliminating G / A genotype and A / A genotype individuals and retaining G / G genotype individuals, the reproductive performance of the breeding ducks is improved, the artificial insemination efficiency is optimized, and the breeding progress is accelerated.

The application discloses a dyslipidemia risk prediction device and terminal equipment, method and storage medium, and relates to the technical field of medical detection equipment. The device comprises an acquisition module, a first processing module and a second processing module which are connected with each other. The first processing module is used for inputting SNP genotype data of a to-be-predicted object into a pre-constructed scoring model, obtaining a polygenic risk score, and inputting an actual age and a phenotype age into a pre-constructed age linear regression model after obtaining the phenotype age based on clinical biochemical marker data and the actual age of the to-be-predicted object, so as to obtain a phenotype age acceleration value. The second processing module is used for inputting the polygenic risk score, the phenotype age acceleration value and individual characteristic data into a pre-constructed integrated model, obtaining a prediction result set, and taking a mode of the prediction result set as a prediction result of the to-be-predicted object. The device can be used for more comprehensive and accurate prediction and can improve processing efficiency.

The invention discloses an efficient and accurate wheat parent matching method and system based on the distance between a core germplasm and a genome, and belongs to the technical field of cross breeding. The matching method comprises the following steps: acquiring whole genome SNP genotype data of a breeding population, constructing a core germplasm of which the sample size is smaller than that of an original population but the original genetic diversity is greater than or equal to 95%, analyzing the population genetic structure of the core germplasm, calculating the genome distance between individuals of the core germplasm, and selecting the whole genome SNP genotype data of the breeding population. And screening Top N combinations with maximum and minimum genome distances by taking parents from different genetic subgroups as a primary condition and taking an interval from the top quartile to the maximum value of the genome distance as a primary screening range, and outputting a recommended hybrid combination list. According to the method, quantitative indexes of the genetic population structure and the genome distance are innovatively coupled through an algorithm model, double screening of subpopulation complementation and distance optimization is achieved, decision logic is more scientific, and prediction accuracy is higher.

The invention belongs to the technical field of biological detection, and particularly relates to a probe-free multiple SNP (Single Nucleotide Polymorphism) typing method, a kit and application thereof. The invention provides a method for realizing multiple SNP (Single Nucleotide Polymorphism) typing without using a probe, and the method takes a melting temperature (Tm) as a discrimination index to distinguish different allele specific PCR (Polymerase Chain Reaction) products for adjusting the Tm through differential tailing so as to identify allele types of each SNP. Compared with an existing method, the reagent cost, the experiment time and the workload are greatly reduced, and meanwhile high accuracy and stability are kept. The method has the characteristics of high efficiency, expandability and economical efficiency, and is expected to play an important role in the fields of large-scale gene screening, crop breeding, clinical typing analysis and the like, so that the method has a good practical application value.

The invention discloses an SNP marker combination, a KASP primer combination and a kit for identifying zoysia japonica varieties and application of the SNP marker combination, the KASP primer combination and the kit, and belongs to the technical field of molecular biology. The SNP marker combination for identifying the zoysia japonica variety comprises 30 optimized SNP loci, can perform effective SNP genotyping on the zoysia japonica variety, can be used for analyzing the genetic background and genetic relationship of the zoysia japonica variety, and provides a scientific basis for identification and variety right protection of the zoysia japonica variety. The KASP primer combination with high specificity and good polymorphism is provided for SNP genetic typing of the zoysia japonica variety, can be used for developing a zoysia japonica variety SNP detection kit, and provides technical support for construction of a zoysia japonica variety DNA fingerprint spectrum.

The application belongs to the technical field of molecular marker assisted breeding, and particularly relates to a specific SNP molecular marker for rapidly identifying the genetic sex of Pelochelys cantonensis and application thereof, the SNP molecular marker is selected from at least one of JB_SNP1-3, is located at the 337th, 363rd and / or 392th base of the nucleotide sequence shown in SEQ ID NO. 3 and / or 4, and when being GG, CC and / or TT genotype respectively, the to-be-tested Pelochelys cantonensis individual is male, and when being GT, CA and / or TC genotype respectively, the to-be-tested Pelochelys cantonensis individual is female. The application provides an important molecular tool for the sex identification and sex determination mechanism research of Pelochelys cantonensis, can convert the judgment of the sex of Pelochelys cantonensis into the judgment of the SNP genotype, is favorable for the sex identification of Pelochelys cantonensis in the early growth stage, and has the advantages of rapidness and high efficiency, short sex detection period, large detection flux, small environmental factor interference, high accuracy and reliability of detection results and the like.

The application belongs to the field of plant development biology and crop molecular genetic breeding technology, and discloses a molecular marker closely linked to a major QTL site qLL.A02 for regulating the length of a rape rosette leaf and application thereof. A stable major QTL site qLL.A02 for regulating the length of a rape rosette leaf is identified through whole genome correlation analysis. A key SNP variation closely linked to qLL.A02 is identified through co-segregation analysis of a lead SNP genotype and a phenotype between populations, which is located at a SNP site at 9828644 bp of a chromosome A02 of a rape ZS11.v10 reference genome, and the G base variation genotype is a rosette leaf length dominant genotype, and is also highly related to leaf area and seedling stage biomass dominance. A KASP molecular marker developed for the variation can efficiently and accurately identify and explore excellent materials with leaf dominance in a rape germplasm resource population, and provides a key, reliable and efficient idea and method for rape variety improvement and molecular design breeding at the level of seedling stage nutrient growth.

The invention discloses a method and equipment for identifying HLA gene genetic variation based on NGS data and a storage medium. A sequence close to an individual HLA genotype sequence is obtained as a sample HLA gene reference sequence for accurate detection of an HLA SNP genotype, then detected SNP loci have comparability among individuals under a coordinate system through alignment, and the disease-susceptible HLA genetic SNP loci with high research and diagnosis values can be identified more accurately.

The invention discloses a method for identifying mulberry varieties by using AI-driven PCA and random forest combination, which comprises the following steps: firstly, obtaining mulberry seeds to be identified to construct a DNA library, and obtaining annotated SNP data through the steps of double-end sequencing, data preprocessing, comparison and the like; encoding the data, extracting a main SNP site in combination with PCA and singular value decomposition, training and screening out 225 core SNP sites through a machine learning algorithm, and constructing a variety prediction model; and finally, building a library for sequencing a to-be-identified sample, converting 225 SNP genotypes into effective codes, inputting the effective codes into a random forest algorithm for multiple predictions, and determining the variety type of the sample according to the predictions. The method can accurately and efficiently identify the mulberry variety.