K-mers algorithm-based unique sequence primer design method and system and storage medium

Abstract

The invention relates to the technical field of primer design, in particular to a unique sequence primer design method and system based on a k-mers algorithm and a storage medium. The method comprises the following steps: acquiring to-be-monitored species information, and obtaining a non-tolerant group, a tolerant group and a reference group according to the monitored species information; wherein the non-tolerant group is a whole mitochondrial genome sequence of the interfering species; the reference group is a whole mitochondrial genome sequence of the species to be monitored; the tolerance group is a complete mitochondrial genome sequence of other species of the species to be monitored; setting parameters with reference to the group; intercepting the non-tolerance group, the tolerance group and the reference group according to the length of the k-mers to obtain a non-tolerance group k-mers fragment, a tolerance group k-mers fragment and a reference group k-mers fragment; comparing to obtain a unique region sequence; other species whole mitochondrial genome sequences of a species to be monitored are set as a tolerance group; therefore, when a specific species primer is designed, a basic group error possibly existing during sequencing of a single whole mitochondrial genome is reduced, and the specificity of design of a long fragment sequence primer for a monitored species is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of primer design, and more specifically, to a unique sequence primer design method, system and storage medium based on a k-mers algorithm. Background Art

[0002] At present, the study of microbial community composition and diversity generally follows the method of sample collection, DNA extraction, PCR amplification of target gene fragments, and high-throughput sequencing. High-throughput sequencing is a highly targeted method used to analyze gene variation in specific genomic regions and is an ideal method for discovering single nucleotide polymorphisms (SNPs). At present, the most commonly used and accurate primer design method is to perform similarity comparison on DNA sequences with high credibility. The same fragments of different sequences between species are the conserved regions of the gene, and the appropriate fragments are selected as primers in the conserved regions of the gene according to the length of the target fragment; however, as more and more known sequences are known, higher requirements are placed on sequence quality; therefore, an accurate new method is urgently needed to design primers to shorten the running time and save research costs.

[0003] The prior art discloses a primer design method and system based on a k-mer algorithm. The method comprises: constructing a functional gene nucleic acid sequence database, cutting the nucleic acid sequences in the database into k-mers respectively; selecting a number of k-mers according to the frequency of occurrence of the k-mers from high to low as primer candidate k-mers; merging the k-mers with overlap>x in the primer candidate k-mers, and then selecting a plurality of k-mers according to the frequency from high to low as preliminary primers in the merged primer candidate k-mers; searching for k-mers with a base difference from each preliminary primer in the k-mers with a coverage>1%, and merging the searched k-mers with the corresponding preliminary primers in the form of degenerate bases to obtain degenerate primers; performing basic information evaluation on the degenerate primers respectively and calculating the length of the amplification product after all the degenerate primers are paired, and screening the paired primers according to the basic information evaluation results and the length of the amplification product; however, the primers involved in the method often cannot reflect the uniqueness of the species, and the primers involved are not accurate enough. Summary of the invention

[0004] The purpose of the present invention is to disclose a more accurate unique sequence primer design method, system and storage medium based on the k-mers algorithm.

[0005] In order to achieve the above object, the present invention provides a unique sequence primer design method based on the k-mers algorithm, comprising:

[0006] S1: Obtain the information of the species to be monitored, and obtain the non-tolerant group, the tolerant group and the reference group according to the information of the monitored species; the non-tolerant group is the whole mitochondrial genome sequence of the interfering species; the reference group is the whole mitochondrial genome sequence of the species to be monitored; the tolerant group is the whole mitochondrial genome sequence of other species of the species to be monitored;

[0007] S2: Set parameters according to the species information to be monitored, non-tolerant group, tolerant group and reference group; parameters include the length of k-mers

[0008] S3: intercepting the non-tolerance group, tolerance group and reference group according to the length of k-mers to obtain k-mers fragments of the non-tolerance group, k-mers fragments of the tolerance group and k-mers fragments of the reference group;

[0009] S4: align the k-mers fragments of the non-tolerance group, the k-mers fragments of the tolerance group and the k-mers fragments of the reference group to obtain the unique region sequence;

[0010] S5: Design primers based on the unique region sequence.

[0011] Further, in step S1, the information of the species to be monitored is obtained, and the non-tolerance group, the tolerance group and the reference group are obtained according to the monitored species information, including: obtaining the information of the species to be monitored, querying the position of the species to be monitored on the phylogenetic tree according to the information of the species to be monitored, so as to determine the specific range that needs to be monitored, and the specific range includes at least one of the following: different species of the same genus, family and class as the species to be monitored, downloading the whole mitochondrial genome sequence of species in the species list within the specific range as the non-tolerance group, and then downloading the whole mitochondrial genome sequence of the monitored species as the reference group, and downloading the whole mitochondrial genome sequence of other species of the monitored species as the tolerance group.

[0012] Furthermore, the whole mitochondrial genome sequences of species in the species list of all species within the specific range are downloaded as the non-tolerance group, and then the whole mitochondrial genome sequences of the monitored species are downloaded as the reference group, and the whole mitochondrial genome sequences of other species of the monitored species are downloaded as the tolerance group, including: when downloading the whole mitochondrial genome sequences of species in the species list of all species within the specific range, the whole mitochondrial genome sequences of the monitored species, and the whole mitochondrial genome sequences of the monitored species, the bases except A, T, C, and G are ignored; when the input whole mitochondrial genome sequence is an RNA sequence, the base U is replaced by the base T.

[0013] Further, in step S2, the parameters include at least one of the following:

[0014] -r is the complete mitochondrial group sequence of the species to be monitored;

[0015] -i is the complete mitochondrial genome sequence of other species of the species to be monitored;

[0016] -o is the name of the complete mitochondrial genome file of a species that belongs to the same genus but is different from the species to be monitored;

[0017] -u is the unique ratio of sequences in the species to be monitored in the -o sequence

[0018] -m is the maximum k value ratio allowed in -o

[0019] -l is the minimum k value ratio allowed in -o

[0020] -p is the minimum value of k-mers that can be tolerated in the tolerance group

[0021] -k is the length of k value for each comparison

[0022] -s is to output the unique region with no less than the number of bases

[0023] -t means output unique regions starting with T base

[0024] -v is to output a tsv file containing the bases of each k value length identified in -o and their position in -o, value ratio, and whether they are unique

[0025] -c is to output a tsv file containing the bases of each k value length identified by -i and their position in -i, value ratio, and whether they are unique

[0026] Among them, -rIo is a necessary parameter, and other parameters have default values, but users can modify them according to the situation.

[0027] Furthermore, in step S3, the intercepted non-tolerant group k-mers fragments, tolerant group k-mers fragments and reference group k-mers fragments are stored in the computer memory using a two-dimensional hash linked list data structure.

[0028] Further, in step S4, an alignment is performed based on the k-mers fragment, the tolerance group k-mers fragment and the reference group k-mers fragment, including:

[0029] Compare all k-mers in the reference group and the tolerance group one by one, and calculate the percentage of the number of times each k-mer in the reference group appears in the tolerance group by dividing the counts of public k-mers by the number of all k-mers in the tolerance group, and determine whether it is greater than the input value of the -p parameter. If it is greater than p, it is determined that the requirement is met and the k-mers in the tolerance group are regarded as public and unique. The key and counts of each k-mer in the tolerance group are also recorded and stored in the hash table. Then calculate the frequency of each k-mer in each gene sequence in the tolerance group, and then compare the k-mers that meet the requirements in the tolerance group with all k-mers in -o, and repeat the above process.

[0030] Furthermore, the k-mers that meet the requirements in the tolerance group are compared with all k-mers in -o, including:

[0031] The k-mers that meet the requirements in the tolerance group and the k-mers fragments in the non-tolerance group are compared one by one. When the key-value pairs in the k-mers that meet the requirements in the tolerance group and the k-mers fragments in the non-tolerance group are equal, the corresponding counts are divided by the number of all k-mers in the non-tolerance group to calculate the ratio of the number of times each k-mer in the reference group appears in the reference group. When the k-mers in the reference group are found in the non-tolerance group, the program will record the initial position of each string of input sequences and the position and frequency of occurrence of the k-mers in the two-dimensional hash list in the non-tolerance group until all k-mers in the reference group are compared one by one with all k-mers in the reference group to obtain a unique region sequence.

[0032] Furthermore, in step S5, it includes:

[0033] When downloading the whole mitochondrial genome sequences of species in the species list of all species within the specific range, the whole mitochondrial genome sequences of monitored species, and the whole mitochondrial genome sequences of monitored species, bases other than A, T, C, and G are ignored; when the input whole mitochondrial genome sequence is an RNA sequence, base U is replaced by base T.

[0034] In addition, the present invention also provides a unique sequence primer design system based on the k-mers algorithm, including:

[0035] Input module: obtain the information of the species to be monitored, and obtain the non-tolerance group, tolerance group and reference group according to the information of the monitored species; the non-tolerance group is the whole mitochondrial genome sequence of the interfering species; the reference group is the whole mitochondrial genome sequence of the species to be monitored; the tolerance group is the whole mitochondrial genome sequence of other species of the species to be monitored;

[0036] Parameter module: set parameters according to the species information to be monitored, non-tolerance group, tolerance group and reference group; parameters include the length of k-mers;

[0037] Interception module: Intercept the non-tolerance group, tolerance group and reference group according to the length of k-mers to obtain k-mers fragments of the non-tolerance group, k-mers fragments of the tolerance group and k-mers fragments of the reference group;

[0038] Alignment module: Align the k-mers fragments of the non-tolerance group, the k-mers fragments of the tolerance group and the k-mers fragments of the reference group to obtain the unique region sequence;

[0039] Output module: Design primers based on unique region sequences.

[0040] In addition, the present invention also provides a unique sequence primer design storage medium based on the k-mers algorithm, on which a computer program is stored. When the computer program is executed by a processor, the unique sequence primer design method based on the k-mers algorithm is implemented.

[0041] Compared with the prior art, the technical solution of the present invention has the following beneficial effects:

[0042] The method obtains a non-tolerance group, a tolerance group and a reference group according to the monitored species information; wherein the non-tolerance group is the whole mitochondrial genome sequence of the interfering species; the reference group is the whole mitochondrial genome sequence of the species to be monitored; the tolerance group is the whole mitochondrial genome sequence of other species of the species to be monitored; and then compares the k-mers fragments of the non-tolerance group, the k-mers fragments of the tolerance group and the k-mers fragments of the reference group to obtain a unique region sequence; and sets the whole mitochondrial genome sequences of other species of the species to be monitored as the tolerance group; thereby reducing the base errors that may exist in the sequencing of a single whole mitochondrial genome when designing primers for specific species, and increasing the specificity of the design of primers for long fragment sequences of the monitored species. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] Figure 1 This is a flow chart of the unique sequence primer design method based on the k-mers algorithm described in Example 1;

[0044] Figure 2 The block diagram of the unique sequence primer design system based on the k-mers algorithm described in Example 3;

[0045] Figure 3 This is an interface diagram of Example 6 based on entering perl through a windows terminal and running a script;

[0046] Figure 4Interface diagram for reading and providing files and outputting results when the script described in Example 6 is running;

[0047] Figure 5 Schematic diagram of three pairs of primers based on different primer amplification efficiencies described in Example 6;

[0048] Figure 6 The unique area .fa file result graph output by the program described in Example 6;

[0049] Figure 7 The process of comparing reference and ingroup one by one and the resulting diagram of the position of each k in the ingroup when k=25 as described in Example 6;

[0050] Figure 8 The location, uniqueness and percentage information result diagram of each kmers in the outgroup described in Example 6;

[0051] Fig. 9 The figure is a result diagram of the ratio of unique and non-unique regions in the whole mitochondrial genome sequence of the Oriental mayfly described in Example 6, and the position of each unique and non-unique region in the whole mitochondrial genome; DETAILED DESCRIPTION

[0052] The drawings are for illustrative purposes only and should not be construed as limiting the present patent;

[0053] The technical solution of the present invention is further described below in conjunction with the accompanying drawings and embodiments.

[0054] Embodiment 1:

[0055] The present invention provides Figure 1 The unique sequence primer design method based on the k-mers algorithm shown includes:

[0056] S1: Obtain the information of the species to be monitored, and obtain the non-tolerant group, the tolerant group and the reference group according to the information of the monitored species; the non-tolerant group is the whole mitochondrial genome sequence of the interfering species; the reference group is the whole mitochondrial genome sequence of the species to be monitored; the tolerant group is the whole mitochondrial genome sequence of other species of the species to be monitored;

[0057] S2: Set parameters according to the information of the species to be monitored, the non-tolerant group, the tolerant group, and the reference group; the parameters include the length of k-mers;

[0058] S3: intercepting the non-tolerance group, tolerance group and reference group according to the length of k-mers to obtain k-mers fragments of the non-tolerance group, k-mers fragments of the tolerance group and k-mers fragments of the reference group;

[0059] S4: align the k-mers fragments of the non-tolerance group, the k-mers fragments of the tolerance group and the k-mers fragments of the reference group to obtain the unique region sequence;

[0060] S5: Design primers based on the unique region sequence.

[0061] In this embodiment, a non-tolerance group, a tolerance group and a reference group are obtained according to the monitored species information; wherein the non-tolerance group is the whole mitochondrial genome sequence of the interfering species; the reference group is the whole mitochondrial genome sequence of the species to be monitored; the tolerance group is the whole mitochondrial genome sequence of other species of the species to be monitored; and then the k-mers fragments of the non-tolerance group, the k-mers fragments of the tolerance group and the k-mers fragments of the reference group are compared to obtain a unique region sequence; the whole mitochondrial genome sequences of other species of the species to be monitored are set as the tolerance group; thereby, when designing primers for specific species, the base errors that may exist in the sequencing of a single whole mitochondrial genome are reduced, and the specificity of the primer design for the long fragment sequence of the monitored species is increased.

[0062] In step S1, the information of the species to be monitored is obtained, and the non-tolerance group, the tolerance group and the reference group are obtained according to the monitored species information, including: obtaining the information of the species to be monitored, querying the position of the species to be monitored on the phylogenetic tree according to the information of the species to be monitored, so as to determine the specific range that needs to be monitored, and the specific range includes at least one of the following: different species of the same genus, family and class as the species to be monitored, downloading the whole mitochondrial genome sequence of species in the species list within the specific range as the non-tolerance group, downloading the whole mitochondrial genome sequence of the monitored species as the reference group, and downloading the whole mitochondrial genome sequence of other species of the monitored species as the tolerance group.

[0063] Download the whole mitochondrial genome sequences of species in the species list within the specific range as the non-tolerance group, then download the whole mitochondrial genome sequences of the monitored species as the reference group, and download the whole mitochondrial genome sequences of other species of the monitored species as the tolerance group, including: when downloading the whole mitochondrial genome sequences of species in the species list within the specific range, the whole mitochondrial genome sequences of the monitored species, and the whole mitochondrial genome sequences of the monitored species, the bases except A, T, C, and G are ignored; when the input whole mitochondrial genome sequence is an RNA sequence, the base U is replaced by the base T.

[0064] In step S2, the parameters include at least one of the following:

[0065] -r is the complete mitochondrial group sequence of the species to be monitored;

[0066] -i is the complete mitochondrial genome sequence of other species of the species to be monitored;

[0067] -o is the name of the complete mitochondrial genome file of a species that belongs to the same genus but is different from the species to be monitored;

[0068] -u is the unique ratio of sequences in the species to be monitored in the -o sequence

[0069] -m is the maximum k value ratio allowed in -o

[0070] -l is the minimum k value ratio allowed in -o

[0071] -p is the minimum value of k-mers that can be tolerated in the tolerance group

[0072] -k is the length of k value for each comparison

[0073] -s is to output the unique region with no less than the number of bases

[0074] -t means output unique regions starting with T base

[0075] -v is to output a tsv file containing the bases of each k value length identified in -o and their position in -o, value ratio, and whether they are unique

[0076] -c is to output a tsv file containing the bases of each k value length identified by -i and their position in -i, value ratio, and whether they are unique

[0077] In step S3, the intercepted non-tolerant group k-mers fragments, tolerant group k-mers fragments and reference group k-mers fragments are stored in the computer memory using a two-dimensional hash linked list data structure.

[0078] In step S4, an alignment is performed based on the k-mers fragment, the tolerance group k-mers fragment, and the reference group k-mers fragment, including:

[0079] Compare all k-mers in the reference group and the tolerance group one by one, calculate the percentage of the number of times each k-mer in the reference group appears in the tolerance group by dividing the counts of public k-mers by the number of all k-mers in the tolerance group, and determine whether it is greater than the input value of the -p parameter. If it is greater than p, it is determined that the requirement is met and the k-mers in the tolerance group are regarded as public and unique. The key and counts of each k-mer in the tolerance group are also recorded and stored in the hash table. Then calculate the frequency of each k-mer in each gene sequence in the tolerance group, and then compare the k-mers that meet the requirements in the tolerance group with all k-mers in the non-tolerance group, and repeat the above process.

[0080] Compare the k-mers in the tolerance group that meet the requirements with all k-mers in the non-tolerance group, including:

[0081] The k-mers that meet the requirements in the tolerance group and the k-mers fragments in the non-tolerance group are compared one by one. When the key-value pairs in the k-mers that meet the requirements in the tolerance group and the k-mers fragments in the non-tolerance group are equal, the corresponding counts are divided by the number of all k-mers in the non-tolerance group to calculate the ratio of the number of times each k-mer in the reference group appears in the reference group. When the k-mers in the reference group are found in the non-tolerance group, the program will record the initial position of each string of input sequences and the position and frequency of occurrence of the k-mers in the two-dimensional hash list in the non-tolerance group until all k-mers in the reference group are compared one by one with all k-mers in the reference group to obtain a unique region sequence.

[0082] In step S5, it includes:

[0083] When downloading the whole mitochondrial genome sequences of species in the species list of all species within the specific range, the whole mitochondrial genome sequences of monitored species, and the whole mitochondrial genome sequences of monitored species, bases other than A, T, C, and G are ignored; when the input whole mitochondrial genome sequence is an RNA sequence, base U is replaced by base T.

[0084] In this embodiment, a non-tolerance group, a tolerance group and a reference group are obtained according to the monitored species information; wherein the non-tolerance group is the whole mitochondrial genome sequence of the interfering species; the reference group is the whole mitochondrial genome sequence of the species to be monitored; the tolerance group is the whole mitochondrial genome sequence of other species of the species to be monitored; and then the k-mers fragments of the non-tolerance group, the k-mers fragments of the tolerance group and the k-mers fragments of the reference group are compared to obtain a unique region sequence; the whole mitochondrial genome sequences of other species of the species to be monitored are set as the tolerance group; thereby, when designing primers for specific species, the base errors that may exist in the sequencing of a single whole mitochondrial genome are reduced, and the specificity of the primer design for the long fragment sequence of the monitored species is increased.

[0085] Embodiment three:

[0086] This embodiment provides Figure 2 The unique sequence primer design system based on the k-mers algorithm shown includes:

[0087] Input module: obtain the information of the species to be monitored, and obtain the non-tolerance group, tolerance group and reference group according to the information of the monitored species; the non-tolerance group is the whole mitochondrial genome sequence of the interfering species; the reference group is the whole mitochondrial genome sequence of the species to be monitored; the tolerance group is the whole mitochondrial genome sequence of other species of the species to be monitored;

[0088] Parameter module: set parameters according to the species information to be monitored, non-tolerance group, tolerance group and reference group; parameters include the length of k-mers;

[0089] Interception module: Intercept the non-tolerance group, tolerance group and reference group according to the length of k-mers to obtain k-mers fragments of the non-tolerance group, k-mers fragments of the tolerance group and k-mers fragments of the reference group;

[0090] Alignment module: Align the k-mers fragments of the non-tolerance group, the k-mers fragments of the tolerance group and the k-mers fragments of the reference group to obtain the unique region sequence;

[0091] Output module: Design primers based on unique region sequences.

[0092] In this embodiment, a non-tolerance group, a tolerance group and a reference group are obtained according to the monitored species information; wherein the non-tolerance group is the whole mitochondrial genome sequence of the interfering species; the reference group is the whole mitochondrial genome sequence of the species to be monitored; the tolerance group is the whole mitochondrial genome sequence of other species of the species to be monitored; and then the k-mers fragments of the non-tolerance group, the k-mers fragments of the tolerance group and the k-mers fragments of the reference group are compared to obtain a unique region sequence; the whole mitochondrial genome sequences of other species of the species to be monitored are set as the tolerance group; thereby, when designing primers for specific species, the base errors that may exist in the sequencing of a single whole mitochondrial genome are reduced, and the specificity of the primer design for the long fragment sequence of the monitored species is increased.

[0093] Embodiment 4:

[0094] This embodiment provides a unique sequence primer design storage medium based on the k-mers algorithm, on which a computer program is stored. When the computer program is executed by a processor, the unique sequence primer design method based on the k-mers algorithm is implemented.

[0095] In this embodiment, a non-tolerance group, a tolerance group and a reference group are obtained according to the monitored species information; wherein the non-tolerance group is the whole mitochondrial genome sequence of the interfering species; the reference group is the whole mitochondrial genome sequence of the species to be monitored; the tolerance group is the whole mitochondrial genome sequence of other species of the species to be monitored; and then the k-mers fragments of the non-tolerance group, the k-mers fragments of the tolerance group and the k-mers fragments of the reference group are compared to obtain a unique region sequence; the whole mitochondrial genome sequences of other species of the species to be monitored are set as the tolerance group; thereby, when designing primers for specific species, the base errors that may exist in the sequencing of a single whole mitochondrial genome are reduced, and the specificity of the primer design for the long fragment sequence of the monitored species is increased.

[0096] Embodiment five:

[0097] This example needs to be run on a computer with strawberry perl configured in the environment. First, enter perl through the windows terminal and run the script. The interface is as follows Figure 3 As shown, the interface for reading provided files and outputting results when the script is running is as follows Figure 4 Shown

[0098] First, the user needs to query the position of the specific monitoring species on the phylogenetic tree to determine the specific range that needs to be monitored (such as different species in the same genus, family or class), and obtain a list of all species within the specific monitoring range as much as possible. According to the species list, it is recommended to download the whole mitochondrial genome sequence .fasta files of these species as the outgroup group (non-tolerance group), and then download the whole mitochondrial genome sequence .fasta format sequence file of the monitored species as the reference group (reference group). If the monitored species has multiple whole mitochondrial genome .fasta format sequence files, they can be downloaded and sorted as the ingroup group (tolerance group). Enter the windows terminal to open the file directory program script, put all the downloaded .fasta format sequence files in the same directory, enter the parameters required by the program in the terminal (see the parameter description for details), and you can quickly get the generated results. Based on this, the user must determine the Latin name of the species to be monitored, obtain its morphological classification discipline, genus and preferably a complete whole mitochondrial genome sequence. When the RNA sequence is entered, the base U will be automatically replaced with T.

[0099] Embodiment six:

[0100] Using NCBI sequence number > NC_012645.1Ephemera orientalis mitochondrion, complete genome as reference and ingroup, outgroup is a taxonomic group species of the same genus but different species as Ephemera orientalis. The following are the unique regions output by the program:

[0101] >NC_012645.1region241-624_size384_propspcIN100.0_propunivsOUT100.0_avgOUTentries0.0

[0102] CCCTTTTCTAATTTTATTAAATCCGTCGCGACTTTTATTTTTAATTACCCTTATTTTAGGAACTTTATTTTCAATCTCTGCTTCATCTTGATTTGGAGCTT GAGCAGGTTTAGAAATTAATTTACTTTCTTTTATCCCACTTATATCCCAAAATAATAAATTTTCTGCTGAAGCCGCTTTAAAATATTTTCTAGTACAAGCCCTTGCCTCTTCTATTTTATTATTCGCAGTTCTAATATTGTATTCTTTACATTCTATATTAATTTCTTTGGATTCTATTATTGACCCTAGATTAATTCTAAACACAGCCTTATTAATTAAATTAGGAGGAGCACCATTCCATTTCTGATTCCCAGGAGTAATGGAAGGACTTAATTGGTCTTG

[0103] >NC_012645.1region628-961_size334_propspcIN100.0_propunivsOUT100.0_avgOUTentries0.0

[0104] TATTATTTTAATAACTTGACAAAAGATGGCTCCTATAATACTATTATCCTACACTATTTATTTAAATACATTTTATACTTTTGTAATTATTTCTTCAGTTATAGCTGGATCGTTAGGAGGTTTTAACCAAACCTCACTACGTAAAATCATAGCTTATTCTTCTATTAATCACTTAGGGTGGATGGTAGCTTCTATTATTTTAGGAGATTTATTTTGGTTTATATATTTCCTATTTTATTCCTTTCTTTCTATCACTACTATTATTTTATTTAGTCAATTTAATTTAACTCATTTATACCAAATTTATTCTTCCTCATTTCATTCGCCTGCCATT

[0105] >NC_012645.1region988-1132_size145_propspcIN100.0_propunivsOUT100.0_avgOUTentries0.0

[0106] ATCATTAGGAGGATTACCTCCATTCCTAGGATTTCTCCCGAAATGAATTATTATTAATGGTTTAGTTATAAGAAATAATTACTTTACAATTACTGTTATAGTAATTATAACCTTAGTAACTTTATTTCTATCTGCGACTAACA

[0107] >NC_012645.1region1141-1284_size144_propspcIN100.0_propunivsOUT100.0_avgOUTentries0.0

[0108] TTTACTTTTAACCCATAGTGAACCAAAATGATTAAATCCTTCTACAACACTTTCTCCACTACTATTAATTTTAGTGACCTTATCTATTTTAGGATTATTATTAAGCCCTCTTCTGTTTGTAATTCTTTAAGGCTTTATGTTAAT

[0109] >NC_012645.1region2822-2948_size127_propspcIN100.0_propunivsOUT100.0_avgOUTentries0.0

[0110] TGGATCAACAATTCTTTTGTAGGTGTTCTTTTCTTAGTTTTCATTGTTTGGGAAGCTTTTGTTAGACACCGACAAGTAGCTTTCCCTCTTCAAATAACTTCTTCTGTTGAATGATTTCATAGCTTA

[0111] >NC_012645.1region3097-3226_size130_propspcIN100.0_propunivsOUT100.0_avgOUTentries0.0

[0112] AGTAATTCACCCTTAATAGAACAACTTACATTCTTCCATGACCACACGCTTCTTATTTTAGTAATAATTACAACTTTAGTAGGATACTTAATAATTTATACTATTCTTTAATAACTACACAAACCGATTCC

[0113] >NC_012645.1region3237-3366_size130_propspcIN100.0_propunivsOUT100.0_avgOUTentries0.0

[0114] CCAAACAATTGAAATTATCTGAACGATTCTACCCGCAATCACCTTGATTTTTATTGCTCTACCTTCTTTACGTCTACTTTACTTACTAGATGAAGTTAGAGATCCCTCCCTCACTCTTAAAACTATTGGG

[0115] >NC_012645.1region3417-3588_size172_propspcIN100.0_propunivsOUT100.0_avgOUTentries0.0

[0116] TGATTCTTATATAATCCCTTCAACAGAATTAGAGTTAGGAAATTTCCGACTTCTAGAAGTAGATAACCACGCAGTATTACCCATAAATACTCAAATCCGAGTACTTATTACAGCAGCAGATGTTTTACATTCATGAGCAGTTCCTAGCTTAGGTGTTAAGGTAGATGCTACT

[0117] >NC_012645.1region4091-4268_size178_propspcIN100.0_propunivsOUT100.0_avgOUTentries0.0

[0118] TCTATCTTTAAATTGATTAAGTACATTCCTAGGAATTCTACTAATTCCTCTCTCATTCTGACTTTTACCTTCCCGATATTCCCTCCTATGAAATAAAATTCTTTCTACTTTACATAAAGAATTTTCAACTCTTTTAGGACCCACTAGACACCCTGGAAGATCATTTATTTTTATTTCC

[0119] >NC_012645.1region4370-4520_size151_propspcIN100.0_propunivsOUT100.0_avgOUTentries0.0

[0120] ATGACTTAGATTTATACTTTATGGATGAATTAATCACACACAACATATATTTGCCCATCTTGTTCCTCAAGGGACTCCTCCAGTTCTAATACCTTTTATGGTTTGTATTGAAACTATTAGAAACGTAATCCGTCCTGGTACATTAGCAGTA

[0121] >NC_012645.1region4532-4635_size104_propspcIN100.0_propunivsOUT100.0_avgOUTentries0.0

[0122] TAATATAATTGCAGGCCATTTATTGATAACTCTTCTCGGAAATACCGG ACCAAGCTTATCTTTAACTATCCTTTCCCTATTAATTATAGGACAAATTGCTCTCC

[0123] >NC_012645.1region4699-4810_size112_propspcIN100.0_propunivsOUT100.0_avgOUTentries0.0

[0124] ATTCTAGTGAAGTAAACTAATGTCCACACATAGTAATCACCCATACCACCTAGTTGACCAAAGACCTTGACCTTTAACTGGAGCCATTGGAGCAATAACAACCTTATGTGGG

[0125] >NC_012645.1region4996-5245_size250_propspcIN100.0_propunivsOUT100.0_avgOUTentries0.0

[0126] TTTCTTTGTATCCTTCTTTTGAGCTTTCTTCCATAGTAGACTAGCACCTACTGTAGAATTAGGAGCTATTTGACCACCAACAGGTATTTCTCCCTTCAACCCATTACAAATTCCCCTTCTAAATACAGCAATTTTACTAGCATCAGGAGTCACAGTTACATGAGCCCATCATAGCCTTATAGAAAGTAACCACACCCAAGGCCTACAAGGATTATTTTTCACAGTTATTTTAGGAGTTTACTTCACTATC

[0127] >NC_012645.1region5275-5410_size136_propspcIN100.0_propunivsOUT100.0_avgOUTentries0.0

[0128] ATTTACTATTGCAGACGCTGTTTATGGATCAACATTCTTTATGGCTACCGGTTTCCACGGACTACATGTTATTATTGGTACTACATTCTTAATAGTTTGTTTAGTACGTCATTACTTAGAACACTTCTCCCCAAAC

[0129] >NC_012645.1region5545-5683_size139_propspcIN100.0_propunivsOUT100.0_avgOUTentries0.0

[0130] TTGGCTTCCAACCAGAAGGTTTGAAATTTCAAGATAAGTAATTATTATAATTTTCTCTATAACTATTATTTTAATATTGATTACATTAATTGTTATAATTTTAGCTAGACTTCTTTCTAAAAAATCAATCATTGACCGT

[0131] >NC_012645.1region5704-5893_size190_propspcIN100.0_propunivsOUT100.0_avgOUTentries0.0

[0132] ATGTGGATTTGACCCTAAATCCTCTTCACGACTTCCTTTTTCCCTTCGATTTTTCCTTATCGCAGTAATTTTCTTAATCTTTGATGTAGAAATTGCTTTGCTGCTTCCCCTTATTATTTTATTTACCGTTTCTTCAATAACTTTTTGATTTTATATTGGTAGATTCTTTATTTTAATCCTTCTTTTAGGT

[0133] >NC_012645.1region6282-6408_size127_propspcIN100.0_propunivsOUT100.0_avgOUTentries0.0

[0134] CTTAGGTTTTATAAATGTTCAAAGGTAAACTACCTCCCTAGCATCTTCAATGCTATGCTCTAATTATAAGCTATTTAAACATAAATTAATAAATATAAATATAAATACTAACCAAAACACAAAAGTT

[0135] >NC_012645.1region6411-6603_size193_propspcIN100.0_propunivsOUT100.0_avgOUTentries0.0

[0136] TAAATAAATTTTCAAATTATTATTTTGTAAAGCTTGTCTAATTTGAGATAATTTGAGTAATGAAAAATAAATACCTTGACCACCTAAATTTTCACTTCAACCTTGATCTATTCTCTTAATAAGACAAGACCCTCTGATTAAAGGACCTCTTCTAACTCCATATGTAGAGATATAAGGTATAAACCATATAGAT

[0137] >NC_012645.1region6657-6827_size171_propspcIN100.0_propunivsOUT100.0_avgOUTentries0.0

[0138] TCTTAATTGATTTATTTGATAACCAACCCAACCTCCTAAAATACTTACAAAGCTAAAGTTTTTAAATAGAAGGGTAAACAAACCATAGAAGGAGTGAAATAATACTCAACTTATAATTCTACCACCAATCACTGATATAATTAACAAACCACTTACCTTTAAG

[0139] >NC_012645.1region7293-7407_size115_propspcIN100.0_propunivsOUT100.0_avgOUTentries0.0

[0140] TTCAAAATTAGCCCCTAAACCTGCCATAAATATTGTAAGACCTGAAATTAAAAGTAACCAATCTCTAATCCAAGTAAATCTAATTGCAGGACTAAACGAACTAATAAACC

[0141] >NC_012645.1region7791-7905_size115_propspcIN100.0_propunivsOUT100.0_avgOUTentries0.0

[0142] TATAGAAGTAACAAATTAATACCAAATAAAAGCGATTAATATTATCCCCACTTATATTCTTTTTCTATAATAGATCACCAAAGAAGAAATTAAAACAAATCTC

[0143] >NC_012645.1region7911-8113_size203_propspcIN100.0_propunivsOUT100.0_avgOUTentries0.0

[0144] AATTAAAGATATTCAATCTAATAACAAAGTTATAACAATTCCAGTTCT ATGTAAATTTACTACTCCATTCCAATAAAATAGTATATTCACTTAATAAAATAAACCCCAGTCCAAAATAAAATAACTTAACTACCCAAAATACTAAACTAAAACAATTTGATACTCCCAACATTAGGCCTAAAATAAG

[0145] >NC_012645.1region8541-8667_size127_propspcIN100.0_propunivsOUT100.0_avgOUTentries0.0

[0146] AATATTAGTTAAACAAAATAAACCTGAAGAACACAATCCATGTGCAATTTAAAGTATAAGCACCATACTCCTCAATAAGTCAATGTTATTAAACCACCTAAAACTAATCCCTATGTGAGCTACT

[0147] >NC_012645.1region9306-9479_size174_propspcIN100.0_propunivsOUT100.0_avgOUTentries0.0

[0148] AAAACTTAACAAAATTAAACCAAAAGAAAGCATCAACCCAAAAATCTTACACCATAAACAACCAGAAATTACCCACTATTATAAACATAAAAGCCAAATATAATATTCAATTAATTAATGTCATCCTGTTTTCATAAAACTAAGGGGATCAAACTAAA

[0149] >NC_012645.1region9668-9786_size119_propspcIN100.0_propunivsOUT100.0_avgOUTentries0.0

[0150] AAGAGATAATACAATAAATTCTAATCTTAACAAAGTAGCAAGTAAATGTTTACGACTAGAAACAAATACAAAAACACCCAACATAAACAAAATTATTATTCTTAATAACCAAAATAGTT

[0151] >NC_012645.1region9956-10057_size102_propspcIN100.0_propunivsOUT100.0_avgOUTentries0.0

[0152] TTTTAAGATAGGACTTACATTTTGTTTTATAAAACATCCTCTTGCCATAGGTTTAATTTTACTCGTACAAACTACTTACATTTCAGTATTTTCAGGACTAT

[0153] >NC_012645.1region10095-10377_size283_propspcIN100.0_propunivsOUT100.0_avgOUTentries0.0

[0154] AGTATTCCTAGGAGGAATATTAGTATTATTCATTTATGTAACTAGTTTAGCATCAAATGAAATGTTTTCCTTATCATCAAAAACACTAATTTGCATATTTATTTCATTAATAATACTCCTAACCCTAACTATCTTCTTATATGACCCTGTA ACTTGAACCTTACCAACAACATTACTCAATGAAATATCATCCATTATTAATGATTTTAATTTAACAGACTATTTATTTAAACTTTATAATACACTATCATCTATTATTACTATATTGTTAATTTCCTATCTT

[0155] >NC_012645.1region10380-10572_size193_propspcIN100.0_propunivsOUT100.0_avgOUTentries0.0

[0156] CCTAACCTTAGTAATTGTAGTTTCAATTACAAACATTAATGAAGGACCTTTACGATCATCAACTAATTAATGTTTAAACCTATACGACTACACCACCCACTATTTAAATTGCTAACACGCATTAGTAGATTTGCTCCATCAAATATCTCAACATGATGAATTTGGCTCCTTACTCAACATTAATTTGAATTTGGCTCCTTACTGACTTACTA

[0157] >NC_012645.1region10671-10773_size103_propspcIN100.0_propunivsOUT100.0_avgOUTentries0.0

[0158] TGTAAATTATGGTTGATTATTACGTACACTACACGCCAATGGAGCATTCTTCTTTATCTGTATTTATCTTCACGTTGGTCGAGGAATATTATGGTTCA

[0159] >NC_012645.1region10950-11053_size104_propspcIN100.0_propunivsOUT100.0_avgOUTentries0.0

[0160] AGGAGGATTTGCAGTAGATAACGCTACTTTAACCCGTTTCTTTACATTTCATTTTGCTTCCTTTAGTTGCAGGTGCTACTCTAATTCATCTCTTCTATTTC

[0161] >NC_012645.1region11305-11475_size171_propspcIN100.0_propunivsOUT100.0_avgOUTentries0.0

[0162] ATCCCAAATAAGCTAGGAGGTGTAATTGCCCTAGTTTTATCTATCGCTATTCTTTTTTTTACCATTCACTAAAAGTAAATTCCGAGGATTAGAATTTTATCCAATCAACCAACTAATTTTTGATCTTTATTAGGCTACTCTTTTACTTACATGAATTTGGAGCA

[0163] >NC_012645.1region13305-13457_size153_propspcIN100.0_propunivsOUT100.0_avgOUTentries0.0

[0164] AT

[0165] >NC_012645.1region13494-13611_size118_propspcIN100.0_propunivsOUT100.0_avgOUTentries0.0

[0166] CTAACTTCCAAGCTTACAAACTTATTTTATAAAATTATTTAGAAATTCATAGAGCTTATCCCCTATAAATTTAGCATTATACTAAAACATAACCTTTTAAAAAATTGTTTCTAATAAC

[0167] >NC_012645.1region13768-13961_size194_propspcIN100.0_propunivsOUT100.0_avgOUTentries0.0

[0168] TAAACCCTGATACAAAGGTACAGTAATTAACCTACTTTTAATAATTCATTATTTCAACTATTTCATTAATCCCTTACAGTACATTTTACAAATATTTATCCTATATACTATACTAAAAACTAAAACATATTATATTAATTTATAAATTAAATATAAATAACTAAATTAAAACAAAACTTTTTCAAAACAATCGT

[0169] >NC_012645.1region14459-14597_size139_propspcIN100.0_propunivsOUT100.0_avgOUTentries0.0

[0170] GGGTATCTAATCCTAGTTTATTAACTAATTTTCTTAGCTTCACCTAATTAATAAAAGTTCATCTAATATTTTAAATTTCACCTAACAACAATATTATTTAATTAACTCTATAAAAACATAAATTAACTACAACTAAA

[0171] >NC_012645.1region14635-14786_size152_propspcIN100.0_propunivsOUT100.0_avgOUTentries0.0

[0172] GGCACAAATTTTACCAGAACTATATAATTTACTAAATCCAATTTACATTGATATTTAATGTAAAATACTGCGCCTAAATTAATAAAATCTTTAAGAACTATTTATATTCACGCTAAAAACTTACATGTAAAATAATTATAAAAAAGTAACAT

[0173] >NC_012645.1region14790-14917_size128_propspcIN100.0_propunivsOUT100.0_avgOUTentries0.0

[0174] CCAGAATAAAACTTTTCTATTTAAAAAATTTTATAAGGTTCTATACTAAACCACAGTATAAAACATTAAATAAATTACATATTTAAATTATTATTTTATAATTAAATAAAATTAAATTATAAATAACT

[0175] >NC_012645.1region14920-15138_size219_propspcIN100.0_propunivsOUT100.0_avgOUTentries0.0

[0176] AATAAATTTATATATATATATATACCATCACATAAAAATTAATAAATACGTGGGATTTTTACCCCTTTTCTAATTTTATTAAATAAACTCACACTATATACAATACTTTTATATACCATTACCTATATTTTAACTATATATATACTTATATATATATATTCTTAACACATAACCTCTTATTATTTATCCTATTATATAATTATAGCCATATTATTATATT

[0177] >NC_012645.1region15181-16438_size1258_propspcIN100.0_propunivsOUT100.0_avgOUTentries0.0

[0178]

[0179]

[0180] Primers were designed using primerDesigner. Some primer information is as follows:

[0181] Finally, the DECIPHER package of R language was used to write insilicoPCR to test the amplification efficiency and specificity of primers. The three pairs of primers with different amplification efficiencies are as follows Figure 5 As shown;

[0182] Taking the Oriental Mayfly as an example, the unique area .fa file output by the program is as follows Figure 6 As shown;

[0183] When k=25 is set, the process of comparing reference and ingroup one by one and the position of each k in ingroup are as follows Figure 7 As shown;

[0184] The location, uniqueness and percentage information of each kmers in outgroup are as follows Figure 8 As shown;

[0185] Taking the Oriental mayfly as an example, the ratio of unique and non-unique regions in the whole mitochondrial genome sequence and the position of each unique and non-unique region in the whole mitochondrial genome are as follows: Fig. 9 As shown;

[0186] Obviously, the above embodiments of the present invention are merely examples for clearly illustrating the present invention, and are not intended to limit the embodiments of the present invention. For those skilled in the art, other different forms of changes or modifications can be made based on the above description. It is not necessary and impossible to list all the embodiments here. Any modifications, equivalent substitutions and improvements made within the spirit and principles of the present invention should be included in the protection scope of the claims of the present invention.

Claims

1. A unique sequence primer design method based on k-mers algorithm, characterized in that: include: S1: Obtain the information of the species to be monitored, and obtain the non-tolerant group, the tolerant group and the reference group according to the information of the monitored species; the non-tolerant group is the whole mitochondrial genome sequence of the interfering species; the reference group is the whole mitochondrial genome sequence of the species to be monitored; the tolerant group is the whole mitochondrial genome sequence of other species of the species to be monitored; S2: Set parameters according to the information of the species to be monitored, the non-tolerant group, the tolerant group, and the reference group; the parameters include the length of k-mers; S3: intercepting the non-tolerance group, tolerance group and reference group according to the length of k-mers to obtain k-mers fragments of the non-tolerance group, k-mers fragments of the tolerance group and k-mers fragments of the reference group; S4: align the k-mers fragments of the non-tolerance group, the k-mers fragments of the tolerance group and the k-mers fragments of the reference group to obtain the unique region sequence; S5: Design primers based on the unique region sequence.

2. The unique sequence primer design method based on the k-mers algorithm according to claim 1, characterized in that: In step S1, the information of the species to be monitored is obtained, and the non-tolerance group, the tolerance group and the reference group are obtained according to the monitored species information, including: obtaining the information of the species to be monitored, querying the position of the species to be monitored on the phylogenetic tree according to the information of the species to be monitored, so as to determine the specific range that needs to be monitored, and the specific range includes at least one of the following: different species of the same genus, family and class as the species to be monitored, downloading the whole mitochondrial genome sequence of species in the species list within the specific range as the non-tolerance group, downloading the whole mitochondrial genome sequence of the monitored species as the reference group, and downloading the whole mitochondrial genome sequence of other species of the monitored species as the tolerance group.

3. The unique sequence primer design method based on k-mers algorithm according to claim 2, characterized in that: Download the whole mitochondrial genome sequences of species in the species list within the specific range as the non-tolerance group, then download the whole mitochondrial genome sequences of the monitored species as the reference group, and download the whole mitochondrial genome sequences of other species of the monitored species as the tolerance group, including: when downloading the whole mitochondrial genome sequences of species in the species list within the specific range, the whole mitochondrial genome sequences of the monitored species, and the whole mitochondrial genome sequences of the monitored species, the bases except A, T, C, and G are ignored; when the input whole mitochondrial genome sequence is an RNA sequence, the base U is replaced by the base T.

4. The unique sequence primer design method based on the k-mers algorithm according to claim 1, characterized in that: In step S2, the parameters include at least one of the following: -r is the complete mitochondrial group sequence of the species to be monitored; -i is the complete mitochondrial genome sequence of other species of the species to be monitored; -o is the name of the complete mitochondrial genome file of a species that belongs to the same genus but is different from the species to be monitored; -u is the unique ratio of sequences in the species to be monitored in the -o sequences; -m is the maximum k value ratio allowed in -o; -l is the minimum k value ratio allowed in -o; -p is the minimum value of k-mers that can be tolerated in the tolerance group; -k is the length of k value compared one by one each time; -s means outputting the unique regions with no less than the number of bases; -t means the output unique region starts with T base; -v is to output a tsv file containing the bases of each k value length identified in -o and their position in -o, value ratio, and whether they are unique; -c outputs a tsv file containing the bases of each k value length identified by -i and their position in -i, value ratio, and whether they are unique.

5. The unique sequence primer design method based on k-mers algorithm according to claim 1, characterized in that: In step S3, the intercepted non-tolerant group k-mers fragments, tolerant group k-mers fragments and reference group k-mers fragments are stored in the computer memory using a two-dimensional hash linked list data structure.

6. The unique sequence primer design method based on k-mers algorithm according to claim 4, characterized in that: In step S4, an alignment is performed based on the k-mers fragment, the tolerance group k-mers fragment, and the reference group k-mers fragment, including: Compare all k-mers in the reference group and the tolerance group one by one, and calculate the percentage of the number of times each k-mer in the reference group appears in the tolerance group by dividing the counts of public k-mers by the number of all k-mers in the tolerance group, and determine whether it is greater than the input value of the -p parameter. If it is greater than p, it is determined that the requirement is met and the k-mers in the tolerance group are regarded as public and unique. The key and counts of each k-mer in the tolerance group are also recorded and stored in the hash table. The frequency of each k-mer in each gene sequence in the tolerance group is calculated, and the k-mers that meet the requirements in the tolerance group are compared with all k-mers in -o, and the above process is repeated.

7. The unique sequence primer design method based on k-mers algorithm according to claim 6, characterized in that: Compare the k-mers in the tolerance group that satisfy the requirement with all k-mers in -o, including: The k-mers that meet the requirements in the tolerance group and the k-mers fragments in the non-tolerance group are compared one by one. When the key-value pairs in the k-mers that meet the requirements in the tolerance group and the k-mers fragments in the non-tolerance group are equal, the corresponding counts are divided by the number of all k-mers in the non-tolerance group to calculate the ratio of the number of times each k-mer in the reference group appears in the reference group. When the k-mers in the reference group are found in the non-tolerance group, the program will record the initial position of each string of input sequences and the position and frequency of occurrence of the k-mers in the two-dimensional hash list in the non-tolerance group until all k-mers in the reference group are compared one by one with all k-mers in the reference group to obtain a unique region sequence.

8. The unique sequence primer design method based on k-mers algorithm according to claim 3, characterized in that: In step S5, it includes: When downloading the whole mitochondrial genome sequences of species in the species list of all species within the specific range, the whole mitochondrial genome sequences of monitored species, and the whole mitochondrial genome sequences of monitored species, bases other than A, T, C, and G are ignored; when the input whole mitochondrial genome sequence is an RNA sequence, base U is replaced by base T.

9. A unique sequence primer design system based on the k-mers algorithm, characterized in that: include: Input module: obtain the information of the species to be monitored, and obtain the non-tolerance group, tolerance group and reference group according to the information of the monitored species; the non-tolerance group is the whole mitochondrial genome sequence of the interfering species; the reference group is the whole mitochondrial genome sequence of the species to be monitored; the tolerance group is the whole mitochondrial genome sequence of other species of the species to be monitored; Parameter module: set parameters according to the species information to be monitored, non-tolerance group, tolerance group and reference group; parameters include the length of k-mers; Interception module: Intercept the non-tolerance group, tolerance group and reference group according to the length of k-mers to obtain k-mers fragments of the non-tolerance group, k-mers fragments of the tolerance group and k-mers fragments of the reference group; Alignment module: Align the k-mers fragments of the non-tolerance group, the k-mers fragments of the tolerance group and the k-mers fragments of the reference group to obtain the unique region sequence; Output module: Design primers based on unique region sequences.

10. A storage medium for designing unique sequence primers based on a k-mers algorithm, characterized in that: A computer program is stored thereon, and when the computer program is executed by a processor, the unique sequence primer design method based on the k-mers algorithm described in any one of claims 1 to 8 is implemented.

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