273 results about "Sequence alignment" patented technology

The invention belongs to the technical field of biological probiotic screening, and particularly relates to a probiotic screening method based on a convolutional neural network, which comprises the following steps: reading an original probiotic related DNA sequence file, matching the DNA sequence file by adopting a regular expression, removing all non-ATCG base characters to obtain a normalized DNA sequence, and screening the normalized DNA sequence; segmenting the screened DNA sequence by adopting a sliding window method to generate a k-mer fragment set; constructing a k-mer frequency vector according to the occurrence frequency of each k-mer fragment in the sequence; performing normalization processing on the k-mer frequency vector; inputting the k-mer frequency vector after normalization processing into the trained convolutional neural network to obtain a DNA sequence classification result; determining whether a strain corresponding to the sequence is a probiotic or not according to a DNA sequence classification result; according to the method, the k-mer frequency characteristics are extracted by adopting the sliding window, and the calculation complexity of a traditional sequence alignment method is reduced from O (n2) to O (n), so that the consumption of calculation resources is reduced.

The invention discloses an electric power infrastructure line operation behavior intelligent identification method, and belongs to the technical field of mode identification and data processing, and the method comprises the steps: constructing a heterogeneous space-time scene map, and carrying out the multi-modal structural perception of an operation site; segmenting the continuous behavior flow into behavior primitives in an unsupervised manner, and encoding the behavior primitives into observation sequences; analyzing the security operation regulations offline and compiling the security operation regulations into normal form behavior genomes; performing local sequence alignment on the observation sequence and the normal form genome to quantify behavior deviation; and identifying a jump critical point of the risk state based on the deviation disturbance and generating a structured early warning event. According to the method, a heterogeneous space-time scene map is constructed to fuse multi-modal perception data, an actual operation behavior is abstracted into an observation behavior primitive sequence, and the observation behavior primitive sequence and a normal form behavior genome compiled from a safety regulation are subjected to sequence alignment, so that behavior deviation can be quantified, a jump critical point of a risk state can be identified, and the accuracy of the risk state is improved. And accurate and foresight intelligent identification and early warning of operation behaviors are realized.

Compressing files is disclosed. An input file to be compressed is first aligned. Aligning the file includes splitting the file into sequences that can be aligned. When splitting the file into sequences or when performing subsequent recursive splitting, the splitting is based on a longest sequence match. The result is a compression matrix, where each row of the matrix corresponds to part of the file. A consensus sequence is determined from the compression matrix. Using the consensus sequence, pointer pairs are generated. Each pointer pair identifies a subsequence of the consensus matrix. The compressed file includes the pointer pairs and the consensus sequence.

The invention relates to the technical field of molecular detection, and particularly discloses a liquid chip for identifying opisthopapus taihangensis and Hebei province as well as a preparation method and application of the liquid chip. Genotyping sites of the liquid chip comprise 1140 SNP sites; the physical positions of the 1140 SNP loci are determined based on comparison of a whole genome sequence of a bovine reference genome, and the version number of the whole genome sequence of the bovine reference genome is ARSUCD 1.2; wherein the physical position information of the 1140 SNP loci is as shown in a table 1. The liquid chip can realize genetic typing of the opisthopapus taihangensis and the Hebei province cattle, has the advantage of high detection rate, and can obviously cluster the opisthopapus taihangensis and the Hebei province cattle into two classes when clustering analysis is carried out on the opisthopapus taihangensis and the Hebei province cattle, so that a marker combination of the liquid chip can represent whole genome re-sequencing genes, assists in distinguishing the opisthopapus taihangensis and the Hebei province cattle, and is high in accuracy and high in accuracy. Therefore, the variety identification of the opisthopapus taihangensis and the Hebei Hebei is realized.

The application discloses a kind of electric power infrastructure line operation behavior intelligent identification method, belong to pattern recognition and data processing technical field, it includes constructing heterogeneous space-time scene atlas to carry out multi-modal structured perception to operation site;Continuous behavior flow is unsupervised and is divided into behavior base element and is encoded as observation sequence;Offline analysis safety operation regulation and is compiled as paradigm behavior genome;Observation sequence and paradigm genome are locally sequenced to be aligned to quantify behavior deviation;The jump critical point of risk state is identified based on deviation disturbance, and structured early warning event is generated.The application constructs heterogeneous space-time scene atlas to fuse multi-modal perception data, abstracts actual operation behavior as observation behavior base element sequence, and carries out sequence alignment with paradigm behavior genome compiled from safety regulation, can quantify behavior deviation and identify the jump critical point of risk state, realize accurate, forward-looking intelligent identification and early warning to operation behavior.

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.

The invention discloses a method, a system and equipment for detecting internal tandem repeat and a storage medium, and the key points of the technical scheme are as follows: obtaining a first reference sequence according to at least one target exon sequence corresponding to a protooncogene, and obtaining a second reference sequence according to at least one target intron sequence corresponding to the protooncogene; comparing the sequencing data of the to-be-detected sample to the second reference sequence to obtain a first comparison result, extracting an uncompared sequence from the sequencing data according to the first comparison result, and comparing the uncompared sequence to the first reference sequence to obtain a second comparison result; and determining a first detection result according to the second comparison result and a first reference sequence, and performing false positive filtering on the first detection result to obtain a second detection result. According to the invention, false positive can be reduced so as to ensure the accuracy and reliability of subsequent analysis.

Provided are a Medicago sativa SNP molecular marker combination and a use thereof. The SNP molecular marker combination consists of 61351 SNP molecular markers. The physical positions of the 61351 SNP molecular markers are determined by sequence alignment on the basis of the Medicago sativa reference genome ZM-4 alfalfa genome. The SNP molecular markers have good site specificity, strong versatility, and high polymorphism and can effectively discriminate Medicago sativa germplasms from different sources. A Medicago sativa genome-wide liquid-phase gene chip is prepared from the SNP molecular markers, and can be used for genetic diversity assessment of Medicago sativa germplasm resources, genetic map construction and functional gene mapping, genome-wide association study, etc., providing an important tool and technical support for Medicago sativa molecular design breeding and variety authenticity identification, and achieving important significance for high-quality development of the alfalfa seed industry in China.

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 relates to the technical field of molecular detection, and particularly discloses a saline-alkaline tolerant soybean liquid phase chip and a design method and application thereof, and genetic typing sites of the saline-alkaline tolerant soybean liquid phase chip comprise 232 SNP sites and 2 Indel sites; the physical positions of the 232 SNP loci and the two Indel loci are determined based on the comparison of the whole genome sequence of the soybean reference genome, and the version number of the whole genome sequence of the soybean reference genome is Glycine max Wm82. A2. V1; wherein the 232 SNP loci and the 2 Indel loci are as shown in a table 1. The screened 232 SNP loci and 2 Indel loci can realize genetic typing of the saline-alkaline tolerant soybeans so as to realize saline-alkaline tolerant character identification of the soybeans, and can be used for soybean molecule assisted breeding to breed the saline-alkaline tolerant soybeans.

The invention discloses an SNP (Single Nucleotide Polymorphism) molecular marker related to disease resistance of ricefield eel and application of the SNP molecular marker, and relates to the technical field of molecular biology. The nucleotide sequence of the SNP molecular marker is as shown in SEQ ID NO.3, and SNP sites, namely G / A mutation and A / C mutation, exist at the 143rd and 413th basic groups of the SNP molecular marker. According to the invention, SNP loci in LamR genes in a ricefield eel group are screened out through sequence alignment, and genotyping is carried out on the SNP loci; and comparing the differences of the disease resistance of the genotypes, and screening to obtain the genotype with the strongest disease resistance, thereby providing an effective molecular marker for detecting the disease resistance of the ricefield eel. The SNP molecular marker provided by the invention is associated with the disease resistance of the ricefield eel, and provides effective technical support for breeding of disease-resistant ricefield eel varieties.

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 relates to an eDNA method for identifying bumblebee honeycombs in permafrost regions of Qinghai-Tibet Plateau. The eDNA method comprises the following steps: S1, positioning observation sample belts and arranging sampling points on the basis of multi-source data in combination with a Bayesian hierarchical model; s2, performing deep freezing and complete excavation on matrixes around and inside all the sampling points; s3, stratified sampling and anti-degradation treatment are carried out, and a spatial attribute database is established; s4, extracting and purifying eDNA (enhanced deoxyribonucleic acid); s5, determining a nest host based on PCR amplification, high-throughput sequencing and sequence comparative analysis; and S6, constructing a Bayesian hierarchical model in combination with biological information, and judging honeycomb characteristics. The method is simple, rapid and low in cost, not only is suitable for Qinghai-Tibet Plateau permafrost regions, has the core advantages of non-destructiveness and high sensitivity, but also is also suitable for underground insect nest identification research in other environment sensitive regions or regions difficult to physically explore in principle, and has wide application prospects. The method is especially suitable for monitoring rare, secret or difficult-to-approach organisms.

Various techniques for detecting visual similarity between DNS fully qualified domain names (FQDNs) are disclosed. In some embodiments, a system, process, and / or computer program product for detecting visual similarity between DNS FQDNs includes receiving a DNS data stream, wherein the DNS data stream includes a DNS query and a DNS response for resolution of the DNS query; performing extended sequence alignment for each of the set of FQDNs to identify potential malware FQDNs for one or more target FQDNs based on a visual similarity for each domain in the DNS data stream; and classifying the set of domains as malware FQDNs or benign FQDNs based on results of the extended sequence alignment.

The invention discloses a primer for diagnosis of early pregnancy of sows. The nucleotide sequence of the primer is shown as follows: SRY-O-F: 5 '-CAGCAAAATATTCTCGCCTTGG-3', and the nucleotide sequence of the primer is shown as follows. And SRY-O-R: 5 '-CATCCTCTCTCTACGC-3', and SRY-O-R: 5 '- SRY-I-F: 5 '-ATATTCTCGCCTTGGGG-3', SRY-I-F: 5 '- And SRY-I-R is 5 '-GCTTTCGGCTTCTGTA-3', and the formula is shown in the description. Two pairs of primers with high sensitivity and strong specificity are designed through comparative analysis of pig SRY gene sequences, fetal free DNA in peripheral blood of sows is used as a template, and the specificity and sensitivity of PCR are enhanced through amplification of the two pairs of primers. Through two rounds of PCR amplification, whether the sow is pregnant or not can be detected on the 18th day of pregnancy, and the accuracy of the detection result is extremely high and reaches 100%. Compared with the prior art that the ZFY gene is used for detecting the sows on the twentieth breeding day, the method has the advantages that the detection time can be advanced to the eighteenth breeding day, and the detection accuracy is greatly improved (100% vs 10%). According to the method, powerful technical support is provided for early and accurate identification of the non-pregnant sows, reduction of non-production days and feeding cost and smooth execution of a production plan.

The application relates to the technical field of gene chips, in particular to a SNP molecular marker combination of Pinus massoniana and application thereof. The SNP molecular marker combination is composed of 113,709 SNP molecular markers, wherein the physical position of the SNP molecular markers is determined by sequence alignment based on a reference genome Pinus.tabuliformis V1.0 of Pinus tabulaeformis. The application provides a whole genome chip of Pinus massoniana containing 113,709 SNP sites for the first time, and the chip has the advantages of high efficiency, low cost, good genetic stability and the like, and can be widely applied to different application scenarios such as identification of Pinus massoniana germplasm resources, genetic background analysis of breeding materials, gene positioning, whole genome association analysis, whole genome selection breeding and intelligent design breeding.

The invention provides a construction method, system and product of a false positive judgment model of a mutation site obtained by sequencing after enzyme digestion fragmentation and related application. Specifically, the false positive judgment model is constructed on the basis of a plurality of characteristic parameters associated with mutation sites obtained by enzyme digestion fragmentation sequencing; the characteristic parameters comprise scores obtained by performing reverse complementary sequence alignment on the front and back extension 30bp of the mutation site, the sequence proportion of 15 basic groups at the tail end of the mutation site, the Bayesian conditional probability of the extracted mutation site, and the KS test statistic of the extracted mutation site. Furthermore, the invention also provides a method for constructing the model by utilizing the crowd detection rate and the corresponding false positive. According to the method, the data characteristics of the false positive mutation sites are introduced by utilizing digestion fragmentation, so that the reliability of the digestion false positive mutation sites is objectively evaluated under the condition that high depth and large data volume are not needed, and the detection accuracy of the mutation sites can be remarkably improved.

The invention discloses a gene feature extraction method in gene data based on sequence search, and relates to the technical field of biological information. The problems that gene data is wide in source and diversified in format, data processing is extremely complex, data of different formats are difficult to integrate and analyze, and the accuracy and efficiency of feature extraction are affected are solved. According to the method, gene data are comprehensively preprocessed, low-quality and redundant parts are removed, reliable data quality is ensured, data distribution and data conversion are performed at the same time, high-similarity gene feature regions are accurately screened through sequence comparison, importance weights of gene features are determined by using clustering group features, key features are reasonably screened, and the accuracy of gene feature extraction is improved. Data dimensions are effectively reduced, the feature extraction efficiency and accuracy are improved, local and global features are fused to construct a comprehensive feature vector, the feature expression ability is enhanced, a screening result is verified by constructing a test data set, and the accuracy and reliability of the gene feature extraction method are continuously improved.

Disclosed herein are methods and systems for aligning sequence reads based on reduced sequence representations. The methods and systems may include receiving sequence reads generated from nucleic acids; encoding sequence reads with a reduced sequence representation, thereby generating transformed sequence reads; generating seeds from the transformed sequence reads; and matching the seeds, thereby aligning the transformed sequence reads. The methods and systems may improve alignment efficiency and accuracy, for example when used with sequence reads which include mutations or sequencing errors, such as in sequencing aided by mutagenesis (SAM) or long-read sequencing applications.

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 provides a goat whole genome SNP locus combination which is composed of 30000 SNP loci, the physical positions of the SNP loci are determined through sequence alignment based on a goat reference genome ARS1, and locus information is shown in a table 1 in the specification. The invention also provides a liquid phase chip relating to the SNP site combination and an application thereof. The liquid chip has the following advantages: the liquid chip supports flexible screening and updating of original sites, is low in detection cost, is more suitable for genotype screening and typing work of large-scale farms, and helps to improve the breeding efficiency; the liquid-phase chip is excellent in performance, high in average detection rate of SNP sites, stable in typing effect and high in gene consistency; the method can be accurately applied to multi-character breeding practice; according to the method, the integrity of whole genome detection is remarkably improved in design, the covered functional sites are more comprehensive, the marking density and the resolution ratio are higher, the universality is enhanced, and the method is suitable for germplasm resource improvement and protection work of various goats.

The invention provides an MHC presentation peptide fragment prediction method and system based on multi-modal deep learning. The method comprises the following steps: constructing a multi-species MHC-peptide fragment combination data set; carrying out single genotype analysis on the multi-allele MHC-peptide fragment data in the multi-species MHC-peptide fragment combination data set, and determining a unique MHC-peptide fragment corresponding relationship; performing multi-sequence alignment and feature alignment on the cross-species MHC sequences, and extracting core site information representing MHC molecular polymorphism by adopting a frequency weighted amino acid feature distance algorithm; and constructing a multi-modal deep learning model, integrating MHC sequence features and peptide fragment sequence features, and predicting the binding capacity of MHC molecules and peptide fragments. According to the method, the high-order interaction characteristics between the MHC and the antigen peptide fragment can be more comprehensively and effectively captured.

The invention belongs to the technical field of molecular biology, bioinformatics, sorghum genetics and whole-genome gene chips, and particularly relates to a sorghum whole-genome SNP molecular marker combination developed based on a targeted sequencing technology, a 10K liquid chip and application of the sorghum whole-genome SNP molecular marker combination and the 10K liquid chip. The SNP molecular marker combination comprises 10,000 SNP loci, and the specific information of the 10,000 SNP loci is as shown in a table 1; the physical positions of the 10000 SNP loci are determined by performing sequence alignment based on a reference genome of the wine red tassel sorghum variety HYZ-T2T with the version number of v1.0. A liquid chip developed based on the SNP molecular marker combination provided by the invention can be effectively applied to genetic diversity analysis, whole genome association analysis, genetic typing, molecular marker-assisted selective breeding, whole genome selective breeding and other applications of sorghum germplasm resources.

The invention discloses an SNP molecular marker combination related to disease resistance of ricefield eels and application of the SNP molecular marker combination, and relates to the technical field of molecular biology. The SNP molecular marker combination comprises the following molecular markers (1)-(3): (1) a molecular marker with a nucleotide sequence as shown in SEQ ID NO.7; (2) a molecular marker with a nucleotide sequence as shown in SEQ ID NO.8; and (3) a molecular marker with a nucleotide sequence as shown in SEQ ID NO.9. According to the invention, an SNP locus in a TLR7 gene in a monopterus albus group is screened through sequence alignment, and genotyping is carried out on the SNP locus; and comparing the differences of the disease resistance of the genotypes, and screening to obtain the genotype with the strongest disease resistance, thereby providing an effective molecular marker for detecting the disease resistance of the ricefield eel. The molecular marker combination provided by the invention is associated with the disease resistance of the monopterus albus, and provides effective technical support for breeding of disease-resistant monopterus albus varieties.

This invention provides a germline mutation detection method and system with a low false positive rate. The system is computer-executed and includes: first, performing a PCR repeat cluster consistency test on sequence alignment files generated from high-throughput sequencing reads, down-regulating the base count weights of inconsistent sites within the cluster; then, based on the sample-specific background error baseline, calculating the variation confidence index of each genomic site using an empirical Bayesian framework to obtain candidate single nucleotide variants (SNPs); obtaining candidate insertion / deletion variants through read clustering and physical verification of insertion fragment lengths; subsequently, performing a dual-engine cross-feedback iteration on the two candidate types until convergence, integrating and filtering, and outputting a structured mutation detection report. This invention significantly reduces the false positive rate of both SNPs and insertion / deletion variants while maintaining sensitivity, and improves the detection capability of complex insertion / deletion variants.

The application relates to the technical field of molecular detection, and particularly discloses a salt and alkali tolerant soybean liquid phase chip as well as a design method and application thereof. The genotyping sites of the salt and alkali tolerant soybean liquid phase chip include 232 SNP sites and two Indel sites. The physical positions of the 232 SNP sites and the two Indel sites are determined based on whole genome sequence alignment of a soybean reference genome. The version number of the whole genome sequence of the soybean reference genome is Glycine max Wm82.a2.v1. The 232 SNP sites and the two Indel sites are shown in Table 1. The 232 SNP sites and the two Indel sites screened by the application can realize genotyping of salt and alkali tolerant soybeans, and further realize soybean salt and alkali tolerance trait identification. The application can be used for soybean molecular assisted breeding, and salt and alkali tolerant soybeans can be bred.

Compressing files is disclosed. An DNA sequence to be compressed is first aligned. Aligning the DNA sequence includes splitting the DNA sequences into smaller sequences or portions that can be aligned. After the DNA sequence is spilt one or more time and aligned, a compression matrix is generated. Each row of the compression matrix corresponds to part of the DNA sequence. A consensus sequence is determined from the compression matrix. Using the consensus sequence, pointer pairs are generated. Each pointer pair identifies a subsequence of the consensus matrix. The compressed file includes the pointer pairs and the consensus sequence.

The invention relates to the technical field of animal genetic breeding, and provides a double-character genome selection platform based on local genetic correlation (LGC). The platform is composed of a phenotype data processing module, a genotype data processing module and a genome selection module (comprising a model selection sub-module and a parameter selection sub-module). The platform performs quality control, data normality test and correction on phenotypic data; performing quality control, sequence alignment, variation detection and genotype filling on the genotype data; and identifying whole genome local genetic correlation, checking the significance of LGC, selecting a model based on a whole genome LGC estimation result of a character pair and a corresponding P value, setting a corresponding model parameter threshold, and realizing section weighted double-character genome selection analysis. According to the method, the genetic evaluation accuracy of complex characters, especially low heritability characters, can be effectively improved, and an efficient and stable genome selection tool is provided for livestock and poultry breeding.

The present invention discloses a molecular marker combination and application for analyzing sheep breeds, relating to the field of biotechnology. The present invention provides 10,082 molecular markers capable of analyzing sheep, wherein the physical location information of the molecular markers is determined based on genome sequence alignment of the sheep reference genome Oar_rambouillet_v1.0. A molecular probe combination, a gene chip, and a kit prepared using the 10,082 SNP molecular markers can be used to perform genetic assessment on individual sheep, perform individual selection on sheep breeds that were difficult to measure in the early stages, shorten the generation interval, accelerate the breeding process, and thus save a large amount of breeding costs.

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.