141 results about "Sequence comparison" patented technology

The invention belongs to the technical field of allele typing, and discloses a gene haplotype typing method and device based on sequencing data and a medium, and the method comprises the following steps: obtaining to-be-detected gene sequencing data from a to-be-detected sample; splitting the sequencing data into genes according to a reference sequence, and performing variation information detection and variation information filtering; after sequence splitting is carried out on the basis of the sequence obtained after variation information filtering, the haplotype sequence obtained after sequence splitting is corrected, and a to-be-detected gene haplotype typing result of the to-be-detected sample is obtained. According to the method, complex calculation is simplified by adopting a mode of firstly splitting sequences into genes, the method does not completely depend on sequence comparison results, and similar typing is finally evaluated by adopting a mode of combining comparison with backtracking variation information scoring, so that typing difference information can be effectively refined, and interference of sequencing data noise on the results is reduced; and a haplotype result is verified for multiple times by adopting a primary typing and correction mode, so that the result accuracy is higher.

The invention belongs to the field of molecular biological identification, and particularly relates to a specific SNP (Single Nucleotide Polymorphism) site combination for identifying a Wuzhishan pig variety and application. The specific SNP site combination for identifying the Wuzhishan pig variety comprises 77 SNP sites, and the physical positions of the SNP sites are determined by sequence comparison based on a pig reference genome Sscrofa11.1. The specific SNP site combination is screened based on a method of combining whole genome association analysis with selection signal analysis so as to ensure the accuracy of site selection. The selected specific SNP site combination can rapidly realize accurate identification of the Wuzhishan pig variety on the gene level, and has significant application value in the aspects of genetic resource accurate protection and variety utilization of Hainan Wuzhishan pigs.

The invention provides an enzyme modification method based on artificial intelligence. The enzyme modification method comprises the following steps: training an AlphaFold2 model to obtain a glycosyltransferase tertiary structure prediction model; performing multi-sequence comparison on the protein and nucleic acid sequence database and the non-redundant protein feature sequence database based on the active point location recognition model to obtain a comparison result; initializing a matrix of which the length is equal to that of a comparison result, so as to construct a PSSM matrix and screen out potential mutation sites; according to the screened potential mutation sites, constructing an initial mutation library to form a virtual screening mutation library; performing structure reconstruction on the sequence in the virtual screening mutation library based on a glycosyl transferase tertiary structure prediction model so as to predict the glycosyl transferase tertiary structure and perform molecular docking and dynamic simulation on the glycosyl transferase tertiary structure; the method is used for analyzing binding pockets of proteins and ligands and determining dynamic interaction of amino acid residues and ligands in the binding pockets, and the contact number of each amino acid residue and the ligands is used for modifying the tertiary structure of the glycosyltransferase.

The invention belongs to the technical field of molecular markers, and particularly relates to an anti-disease gene of corn grain rot, a molecular marker and application. The nucleotide sequence of the gene ZmRLK2 is as shown in SEQ ID NO. 1. According to the invention, the corn grain rot resistance candidate gene ZmRLK2 is obtained by carrying out correlation analysis on a whole genome of the corn grain rot and screening SNP marker sites. Sequence comparison of the gene finds that two allele types exist in a natural material, and molecular markers are developed for variation of the allele. The method is not influenced by tissue types, development stages, environmental factors and the like, the molecular marker technology is simple, rapid and easy to automation, the inoculation and identification cost is greatly saved, and the method can be used for corn molecular breeding.

The invention discloses a molecular biological method capable of simultaneously detecting duck-derived and goose-derived components and application of the molecular biological method, after genome DNA of a sample to be detected is subjected to PCR amplification and capillary electrophoresis through primers shown in SEQ ID NO.1 and SEQ ID NO.2, sequence comparison is carried out, when the peak value is 999bp, it is indicated that the sample contains the duck-derived component, and when the peak value is 992bp, it is indicated that the sample contains the goose-derived component, and when the peak value is 992bp, it is indicated that the sample contains the goose-derived component, it is indicated that the sample contains the duck-derived component. When the peak values are 999bp and 992bp, the duck-derived component and the goose-derived component are contained at the same time. The detection kit developed on the basis of the method can generate considerable economic benefits and good social values.

The invention discloses a pattern recognition method and device for medical gene sequencing data, and belongs to the technical field of data processing.The method comprises the steps that a target gene sequence obtained through sequencing is preprocessed, a self-adaptive scoring matrix is constructed, and site scores are dynamically adjusted through neural network training; by means of the self-adaptive scoring matrix, a sliding window is adopted to scan sequence differences, and a Gaussian mixture model is combined for analysis, and a variation region information file is generated; reading a variation region information file, constructing a base conversion matrix for sequence comparison, and generating a variation classification result by analyzing a comparison path; and based on a variation classification result, performing standardization processing on the variation region feature vector, and generating a mutation mode type through an improved clustering algorithm. Through the scheme of the invention, the filtering quality of the sequence data can be improved, and the capability of processing a complex variation mode is enhanced.

The invention provides a method for predicting binding affinity of human leukocyte antigen I-type molecules and peptide fragments, and a construction method of the method comprises the following steps: acquiring antigen binding site residues of the human leukocyte antigen I-type molecules, and extracting antigen binding region sequences of the human leukocyte antigen I-type molecules through secondary multi-sequence alignment; respectively generating a human leukocyte antigen class I molecule coding matrix and a peptide fragment coding matrix based on the paired human leukocyte antigen class I molecule-peptide fragment; and then constructing a model of a convolutional neural network to quantify the binding affinity score of the human leukocyte antigen class I molecule and the peptide fragment. The invention develops a method for predicting binding affinity of human leukocyte antigen class I molecules and peptide fragments based on a convolutional neural network by combining physicochemical characteristics of amino acids, complementary epitope sequences of the human leukocyte antigen class I molecules and an interaction relationship among the sequences.

The invention provides a protein language model pre-training and protein mutation method and related products. According to one specific embodiment of the protein language model pre-training method, a sample protein data set is obtained; generating a multi-sequence alignment probability distribution sequence corresponding to the sample protein data according to the amino acid residue probability distribution of multiple sequences in each sample protein data alignment at each site; the sample protein sequence in each sample protein data and the corresponding multi-sequence comparison probability distribution sequence and structure sequence are sequentially connected in series in the forward direction or the reverse direction, and a multi-modal sequence corresponding to the corresponding sample protein data is generated; and finally, performing autoregression pre-training on the protein language model based on the multi-modal sequence corresponding to each sample protein data to obtain a pre-trained protein language model. Namely, the prediction performance of the model is improved by introducing a multi-sequence comparison probability distribution sequence as an independent intermediate reasoning mode and thinking chains in two directions.

A system for dynamic sequence alignment and causal analysis in business mining, consisting of a data acquisition unit configured to capture real-time event logs from multiple enterprise systems via communication interfaces, wherein the data acquisition unit includes a variety of communication interfaces, including Ethernet ports, fiber optic interfaces, and wireless transceivers, enabling data acquisition from both local and remote enterprise systems, and wherein the unit is capable of processing multiple data streams simultaneously via parallel data acquisition channels; a preprocessing unit configured to normalize and transform the captured event logs using signal processors and real-time data converters; a sequence alignment processing unit configured with a central processing unit (CPU), a graphics processing unit (GPU) and a field-programmable gate array (FPGA) to dynamically align sequences of business events using machine learning; a causal inference processing unit configured with multiple central processing units (CPUs) and neural network accelerators to analyze the aligned sequences and infer causal relationships between business events; a visualization unit configured to display the aligned sequences and results of the causal analysis on user interface devices; and a data storage unit configured with solid-state drives (SSDs) and a redundant array of independent disks (RAID) to store event logs, aligned sequences, and causal analysis data.

The invention discloses a host exogenous nucleic acid identification method based on a high-throughput sequencing technology. The method comprises the following steps: acquiring sequencing data of a to-be-detected sample; filtering the sequencing data twice by using a host reference genome database to remove a host sequence; species classification is performed on the sequencing data after host filtering, and interference of homologous species sequences is reduced; performing sequence comparison by utilizing an identified species reference genome to obtain an accurate species sequence; low-complexity sequence removal is carried out on the compared sequences, so that the influence of sequence preference is reduced; and carrying out secondary comparison on the species reference genome by using BLAST or comparing the species reference genome to an NT library. By applying the method, the exogenous nucleic acid sequences of different host samples can be accurately and specifically identified, and effective analysis of biomass samples of high-host background and low-exogenous species is realized.

The invention relates to a probe design of a high-throughput single cell space transcriptome based on multi-round imaging coding. The invention provides a design method of a readout probe for a high-throughput single-cell space transcriptome, which is simultaneously suitable for more than two species tissues, and comprises the following steps: generating a candidate DNA sequence library with a sequence length of n, filtering out a sequence capable of being compared to a genome of a target species, filtering out a candidate DNA probe containing a short sequence appearing on the genome for more than one time, and obtaining a read-out probe for the high-throughput single-cell space transcriptome. The method comprises the steps of filtering candidate DNA probes capable of being compared to transcriptomes of target species through local BLAST, repeating the steps S20-S40 for all target species, performing probe internal mutual binding screening through the local BLAST, performing probe secondary structure inspection and probe internal mutual binding inspection through two-sequence comparison, performing online BLAST inspection on the probes, and determining the target species according to the BLAST. The final DNA probe sequence is obtained.

The invention relates to the technical field of information retrieval, in particular to an academic supply and demand dynamic sensing method and system based on space-time big data, and the method comprises the following steps: obtaining the path length of a source and a target college, screening migration direction stable labels, recognizing a trend consistent region, evaluating the local transfer capacity, and fusing a high-frequency path region. And extracting behavior track data, performing sequence comparison on the associated nodes, and generating a prediction chain space offset mark set. According to the method, space label units with stable migration characteristics are effectively distinguished by processing enrollment information and population migration trends and constructing a path length filtering and direction section repeating mechanism, and supply and demand migration origin areas are accurately locked in combination with change trends reflected by continuous direction consistency; spatial aggregation judgment is enhanced through a statistical means of a neighborhood capacity proportion and path intersection frequency, the sensitivity and dynamic response capability of a spatial prediction structure are improved, and active sensing and intervention prompting of a supply and demand change trend under multiple space-time dimensions are realized.

The invention discloses a group of shark nano antibodies targeting infectious subcutaneous and hematopoietic necrosis viruses of prawns and a preparation method of the shark nano antibodies. The amino acid sequence of the nano antibodies is any one amino acid sequence selected from SEQ ID NO.8-14, and the nano antibodies can be used for detecting cp, nsp1 and nsp2 antigen proteins of the infectious subcutaneous and hematopoietic necrosis viruses. The preparation or screening method of the nano antibody comprises the following steps: A, expression and purification of cp, nsp1 and nsp2 antigen proteins; b, constructing a shark natural library and / or a shark immune library; c, assisting in phage rescue, and purifying to obtain a phage library; d, panning a phage library of anti-cp, anti-nsp1 and anti-nsp2 antigen proteins; and E, carrying out phage-ELISA identification and sequencing, and carrying out sequence comparison on the cp nano antibody, the nsp1 nano antibody and the nsp2 nano antibody with different CDR3 region sequences. The nano antibody provided by the invention can specifically recognize infectious subcutaneous and hematopoietic necrosis viruses, can detect whether aquaculture animals and aquaculture feeds in aquaculture water are polluted by viruses or not, and realizes rapid detection.

The invention provides a disease marker epitope prediction and antibody screening method, which belongs to the technical field of disease markers, and comprises the following steps: firstly, establishing a training data set containing a known antigen-antibody compound structure and disease tissue expression data; and obtaining target protein sequence information through liquid chromatography-mass spectrometry analysis and carrying out sequence comparison. And then a deep convolutional neural network is utilized to extract sequence features, and surface exposure sites are identified by combining secondary structure prediction and solvent accessibility analysis. After the features are integrated with sequence evolution conservative properties, a prediction model is constructed by using a random forest classifier. The method comprises the following steps: carrying out molecular dynamics simulation on a prediction result, screening first 10% of candidate sequences through a comprehensive scoring function and K-means clustering, and finally determining an antigen epitope sequence with the strongest binding activity through verification of an antigen chip and a fluorescence labeled antibody system, so that the technical problem that specific antigen epitopes are difficult to accurately predict and recognize in the prior art is solved.

The invention discloses the field of molecular detection technology, and specifically relates to a liquid phase chip and a design method and application for beef cattle pedigree identification, wherein the genotyping object of the liquid phase chip includes 16690 SNP sites, and the liquid phase chip includes a set of nucleotide probes for detecting the 16690 SNP sites, and the physical positions of the 16690 SNP sites are determined based on the whole genome sequence alignment of the Hereford cattle reference genome; the version number of the whole genome sequence of the Hereford cattle reference genome is GCF_002263795.3; the 16690 SNP sites are shown in s00001-s16690 in Table 1; beef cattle include the following varieties: Angus cattle, Chinese grassland red cattle, Hereford cattle, Red Angus cattle, Simmental cattle, Limousin cattle, Yanbian cattle, Mongolian cattle and Yanhuang cattle. The liquid phase chip of the present invention can realize pedigree identification of beef cattle.

The invention discloses a somatic mutation recognition method and system based on a residual network in combination with a channel attention mechanism, and the method comprises the steps: scanning a sequence comparison result of a tumor sample and a paired normal sample, and constructing a multi-channel feature matrix representation; a somatic mutation recognition model combining a residual network (ResNeXt) and a channel attention mechanism (SE module) is constructed, verification and fine tuning are performed by using a test set, and then the somatic mutation recognition model which is excellent in performance and suitable for resource-constrained environment deployment is obtained. The invention provides a new hybrid neural network, the network fully utilizes sequence comparison result information of a tumor sample and a paired normal sample, somatic mutation information can be extracted and learned more effectively, and mutation recognition accuracy is improved.

A protein multi-conformation prediction method based on flexible residue probability distribution comprises the following steps: firstly, expanding a self-constructed protein data set by utilizing an ATLAS molecular dynamics simulation database so as to enhance the capturing capability of a model on protein dynamic information; secondly, extracting multi-sequence comparison features and structural features of the protein, and inputting the features into a deep learning network based on a residual network module for training; on this basis, a protein flexible residue probability graph is further generated, dynamic behaviors and conformation change information of the protein are fully mined, then the flexible residue probability graph is used for guiding multi-sequence alignment MSA mask operation, MSA of masks in different areas at different depths is constructed and input into an AlphaFold2 model, and finally the protein multi-conformation structure is generated. According to the method, the efficiency and precision of protein multi-conformation prediction are remarkably improved, and a more efficient and accurate solution is provided for protein multi-conformation prediction.

The invention belongs to the technical field of molecular biology, and particularly discloses a primer capable of identifying five acer species at the same time and application of the primer, the primer comprises AcerTS-F: CGGAACTAGTCGGATGGAGT; the invention relates to a method for preparing an Ac < S-R >: GAAGCAGTTCGAGACAACCG; respectively extracting total DNA (deoxyribonucleic acid) of acer palmatum, acer mono, acer ginnala, acer tegmentosum and acer mogmentosum plants; carrying out PCR (Polymerase Chain Reaction) amplification on the total DNA (Deoxyribose Nucleic Acid) of each species by using the AcerTS-F and the AcerTS-R; after PCR products are sequenced, sequence comparison is carried out, five acer species including acer northeast, acer mono, acer ginnala, acer tegmentosum and acer mogmentosum can be identified at the same time, and precious genetic resources are provided for genetic diversity, phylogenetic evolution and taxonomy research of the acer species.

The invention provides a method for predicting the interaction relevance between ncRNA (non-coding ribonucleic acid) and protein based on MLP-Mixer. The method comprises the following steps: firstly, coding a protein / ncRNA sequence by combining a k-mer method; inputting the sequence features into a hybrid network combined with an MLP-Mixer network so as to extract the sequence features; and finally, simulating interaction between nucleotide and amino acid through a double-sequence comparison attention module, and outputting the interaction to a classification part for classification. According to the method, the first-level sequence features, the second-level structure sequence features and the third-level structure features are comprehensively considered, a multi-layer perceptron mixer module is introduced and is combined with the convolutional neural network and the bidirectional long-short-term memory network, and therefore the long-distance dependency between the features recognized by the CNN can be captured. Meanwhile, complex interaction between nucleotide and amino acid is simulated through a double-sequence comparison attention module, so that fine correlation between ncRNA and a protein sequence is explored.

The application of the primer for detecting the anti-disease gene of the Eriocheir sinensis in identifying the disease resistance of the parent of the Eriocheir sinensis comprises the following steps: (1) respectively extracting RNA (Ribonucleic Acid) of the Eriocheir sinensis, and carrying out reverse transcription to obtain cDNA (Complementary Deoxyribonucleic Acid) of the Eriocheir sinensis; (2) designing a primer combination according to the sequence of the lysozyme gene of the eriocheir sinensis and the sequence of the C-type lectin 4 gene, performing PCR amplification on the cDNA sample of the eriocheir sinensis by utilizing the primer combination to obtain a target fragment, and detecting and confirming that the target fragment is amplified by utilizing agarose gel electrophoresis; (3) obtaining a cDNA sequence by a first-generation sequencing means, carrying out sequence comparison, identifying SNP sites in gene coding regions of the lysozyme gene and the C-type lectin 4 gene, and analyzing the two genes and a combination thereof; and comparing the differences of the disease resistance of the genotypes, and screening to obtain the genotype with the strongest disease resistance and the combined marker primer thereof.

The invention relates to the technical field of virus gene variation detection, in particular to a multi-sequence alignment method for virus gene variation detection, and the method comprises the following steps: collecting a to-be-detected virus gene sequence and a plurality of virus gene alignment sequences; based on an initial preset vacancy penalty score, adopting a multi-sequence alignment algorithm to obtain an initial score matrix between the virus gene sequence and any virus gene alignment sequence; in the backtracking process of the initial score matrix, vacancy score penalty correction results of different positions are dynamically calculated; and correcting the initial score matrix based on vacancy penalty correction results of the virus gene sequence and any virus gene alignment sequence at different positions in the backtracking process, and substituting the correction results into a multi-sequence alignment algorithm to carry out multi-sequence alignment on the virus genes. The invention aims to improve the accuracy of a final comparison result.

The invention provides an SNP (Single Nucleotide Polymorphism) molecular marker combination for pepper genotyping, the SNP molecular marker combination comprises 30462 SNP molecular markers, the physical positions of the 30462 SNP molecular markers are determined based on pepper Hot1 genome sequence comparison, and the specific SNP molecular marker condition is shown in the specification table 1. The number of liquid phase probe capture sites corresponding to the SNP marker is large, the capture rate is high, the capture efficiency of a CC group is 90% or above, the capture efficiency of a non-CC group CA and a non-CC group CF is 79% or above, and the capture efficiency of a CP group is about 51%. The genetic background difference between the CP group and the sequencing group is large, but the CP group can capture about 15k markers and can also complete genetic background evaluation, and the sequencing depth is more than 7X. Overall, genetic background evaluation can be completed by capturing the marker number.

The invention discloses a method for microfluidic high-throughput screening of AKK bacteria. The method comprises the following steps: 1) preparing a microfluidic chip; 2) collecting fresh excrement of healthy volunteers, diluting, and adding a fluorescence labeled antibody to obtain a dispersion phase; and (3) preparing liquid drops by taking paraffin oil and Span-80 as a mobile phase, enabling the liquid drops to enter a liquid drop culture tank through an S-shaped liquid drop circulation channel, culturing, introducing the mobile phase, introducing the liquid drops in the liquid drop culture tank into a liquid drop collection tank, taking out, detecting a fluorescence signal, culturing the liquid drops with the fluorescence signal on the improved brain heart infusion broth solid culture medium, and obtaining the brain heart infusion broth. Obtaining a to-be-identified strain; 4, the strain to be identified serves as a template, PCR amplification is conducted, sequencing is conducted on an amplification product, BLAST sequence comparison is conducted on a sequencing result on an NCBI website, and the target strain AKK bacterium is screened out. The method has the advantages of being high in throughput, simple in experimental process and high in specificity, and the screening efficiency of the AKK bacterium can be improved.

The invention belongs to the field of biological medicine, and relates to a detection reagent based on a nasopharyngeal carcinoma related TCR sequence and application of the detection reagent. The invention provides a storage assembly for storing data, the storage assembly stores instructions for diagnosing an individual suspected to suffer from nasopharynx cancer, receives input individual data, and the individual data comprises obtained sequences of TCR libraries in biological samples of the individual and obtained TCR library sequence information of the individual; analyzing TCR library sequence information of the individual and reference CDR3 beta amino acid sequence comparison information to obtain a TCR clone number completely matched with the reference CDR3 beta amino acid sequence, and obtaining a TCR score according to the obtained TCR clone number completely matched with the reference CDR3 beta amino acid sequence; and on the basis of the TCR score, outputting diagnosis information about whether the individual suffers from nasopharynx cancer or not. The storage assembly for storing data can be used to obtain a diagnostic system for diagnosing an individual suspected of having nasopharynx cancer. The diagnosis system disclosed by the invention can be applied to screening of high-risk groups with nasopharyngeal carcinoma, early diagnosis and treatment of nasopharyngeal carcinoma, evaluation of clinical prognosis and development of a new immunotherapy strategy.

The invention provides an SNP (Single Nucleotide Polymorphism) site combination, a molecular probe combination, a zucchini whole genome gene chip and application thereof, the SNP site combination comprises at least one SNP site in a table 1, and physical position information of the SNP site in the table 1 is determined based on a zucchini reference genome 22S20 or genome sequence comparison of an updated version of the zucchini reference genome 22S20. Specifically, the invention provides a zucchini whole genome 10K liquid-phase gene chip and application thereof. By adopting the zucchini whole genome 10K liquid-phase gene chip disclosed by the invention, high-depth re-sequencing can be carried out on target sites of zucchini, and accurate detection of genotypes of SNP (Single Nucleotide Polymorphism) sites is realized. Meanwhile, the zucchini whole genome 10K liquid-phase gene chip has the advantages of low cost and high efficiency, is beneficial to accelerating the breeding process of zucchini, and provides powerful technical support for development and utilization of zucchini germplasm resources.

The application relates to a detection method of anti-preS1 antibody, an anti-preS1 antibody detection kit and application, the application carries out multi-sequence comparison and conservation analysis on preS1 sequences of different genotypes (A, B, C, D and CD mixed type) of HBV, takes type A (AB697487.1), type C (FJ032351.1) and type D (LC519808.1) as reference sequences, based on the sequence consistency standard of 85% of full length and 90% of the key region of functional antibody binding, a highly conservative preS1 full-length antigen sequence is systematically screened out in natural variation, the sequence can cover antigen variation of A-D type HBV, and the sequence is taken as a coating antigen to establish an indirect ELISA detection system, a good linear relationship is presented in the range of 4.88-625 ng / mL, and the Cut-off value is 33.6 ng / mL; clinical verification shows that the method can effectively distinguish chronic hepatitis B patients from healthy control groups, compared with detection methods based on partial fragments or overlapping short fragments, the false negative rate can be significantly reduced, and the method is suitable for HBV infection immune state evaluation, anti-virus curative effect monitoring and prognosis analysis.

The invention discloses a monoclonal antibody in broad-spectrum combination with multi-branch H5Nx subtype avian influenza virus HA protein and application of the monoclonal antibody. The monoclonal antibody is named as 1G10, belongs to an IgG1 subclass and comprises a heavy chain variable region and a light chain variable region, the heavy chain variable region comprises VHCDR1, VHCDR2 and VHCDR3 of which the amino acid sequences are respectively shown as SEQ ID NO.5-7, and the light chain variable region comprises VLCDR1, VLCDR2 and VLCDR3 of which the amino acid sequences are respectively shown as SEQ ID NO.8-10. The monoclonal antibody can specifically recognize the HA protein in an indirect immunofluorescence test, a protein immunoblotting test and a neutralization test. Besides, the monoclonal antibody can be subjected to a specific hemagglutination inhibition reaction with H5Nx subtype avian influenza viruses such as H5N1, H5N6, H5N8 and the like of different HA gene evolution branches such as 2.3. 2.1 d, 2.3. 4.4 b, 2.3. 4.4 d and the like, which indicates that the epitope recognized by the 1G10 monoclonal antibody is a broad-spectrum neutralizing epitope of the H5 subtype avian influenza viruses. Through a chick embryo immune escape test and sequence alignment, the neutralizing antigen epitope identified by the 1G10 monoclonal antibody is screened and contains 170th and 231th amino acid sites of HA protein, and the mutation of the neutralizing antigen epitope significantly influences antigenicity.

The invention provides an SNP (Single Nucleotide Polymorphism) site and method for identifying the trehalose content of a tetraploid potato tuber and application, the physical position of the SNP site is determined on the basis of sequence comparison of a chromosome 12 of a tetraploid potato'Qing potato No.9 'reference genome, and the SNP site comprises: an A2 haplotype SNP single nucleotide polymorphism site snp: 35849480, the polymorphism being A / G; the SNP single nucleotide polymorphism site snp of the A3 haplotype is 55777825, and the polymorphism is T / G; the SNP single nucleotide polymorphism site snp of the A4 haplotype is 46535012, and the polymorphism is A / G; the SNP single nucleotide polymorphic site snp of the A4 haplotype is 46568448, and the polymorphism is A / T. The invention provides an important molecular tool for efficient identification and genetic improvement of the trehalose content of the tetraploid potatoes.

The present invention belongs to the field of molecular biological identification, and specifically relates to a specific SNP site combination and application for identifying Tunchang pig breeds. The specific SNP site combination for identifying Tunchang pig breeds includes 62 SNP sites, and the physical location is based on the reference genome of the pig. Sscrofa11 .1 The specific SNP locus combination was screened based on the whole genome association analysis combined with the selection signal analysis method to ensure the accuracy of the locus selection. The selected specific SNP locus combination can quickly realize the accurate identification of the Tunchang pig breed at the gene level, and has significant application value in the accurate protection of the genetic resources and breed utilization of the Tunchang pig in Hainan.

The invention belongs to the technical field of biological detection, and relates to a bacterium 16s rDNA full-length RAA detection kit and a method for identifying bacteria by using the same. The kit comprises a primer pair for RAA amplification of bacterium 16srDNA full length, the sequence of an upstream primer of the primer pair is as shown in SEQ ID NO: 1, and the sequence of a downstream primer of the primer pair is as shown in SEQ ID NO: 2. According to the bacteria 16s rDNA full-length RAA detection kit and the method for identifying the bacteria by using the same, high-specificity, high-sensitivity and high-stability RAA amplification can be performed on the 16s rDNA full lengths of various bacteria in a sample to be detected, and amplification products are easier to quickly and accurately determine the species of the bacteria in the sample to be detected through sequencing and sequence comparison.