A DNA encoding method, terminal device and storage medium satisfying biological condition constraints

Abstract

A DNA encoding method that satisfies biological condition constraints, comprising: constructing a circular coset S according to given parameter information a ; According to the circular coset S a Construct a polynomial #imgabs0#; select the vector space V formed by the partial polynomial d :It further includes selecting a set of Hamming distances d that satisfy max{S a}≤d for all cyclotomic cosets S a The corresponding polynomials #imgabs1#, use these polynomials to form the vector space #imgabs2# on F4; the vector space V d The polynomials in are mapped into codewords; codewords that meet biological constraints are selected from the codewords to generate a final codebook, and the final codebook satisfies: the edit distance between any two codewords is at least d e ≤d, where the code can correct #imgabs3# editing errors. The present invention is a novel DNA encoding method that can correct multiple editing errors (insertion, deletion or substitution) and satisfy biological constraints (including but not limited to GC global balance and local balance, run constraint and hairpin constraint).

Description

Technical Field

[0001] The present application belongs to the field of data storage technology, and in particular, relates to a DNA encoding method, terminal and computer-readable storage medium that meet biological condition constraints, and in particular, relates to a new type of DNA encoding method, terminal device and storage medium that can correct multiple editing errors (insertion, deletion or replacement) and meet biological constraints (including GC global balance and local balance, run constraints and card issuance constraints). Background Art

[0002] In an era of explosive digital data growth, DNA is being explored as a next-generation molecular storage medium. Data can be encoded in vitro by using four natural nucleotides (A, T, G, and C), synthesizing data in DNA molecules, and retrieving data from DNA by sequencing. DNA data storage achieves extremely high data density due to the manipulation of molecules at the atomic level. DNA materials are very stable both in liquids and at relatively high temperatures, providing high durability (high retention) compared to many existing media materials. Data in DNA can be easily produced in hundreds of millions of copies by simple PCR reactions while maintaining low energy. DNA data retrieval has greatly benefited from the revolution in sequencing technology, including Illumina Next Generation Sequencing (NGS) and Nanopore 3. RD produces sequencing that can rapidly sequence human and other genomes at ever-decreasing prices.

[0003] However, current strategies for DNA data storage also face challenges. The storage of any dataset requires the template-free synthesis of specific long DNA molecules by chemical or enzymatic methods, which is still very expensive, time-consuming, labor-intensive and error-prone. The synthesized DNA can no longer be used to store other datasets, further increasing the storage cost. For data retrieval, synthesis-based Illumina sequencing must cut long data DNA molecules into short fragments (<300 bases) to maintain a low error rate (<0.1%), and complex post-sequencing bioinformatics analysis is required to assemble the fragmented data. For these reasons, efforts have been made to write data into universal DNA sequences including natural DNA. There are still many unresolved issues in the research of its practical application. One of the major advantages of DNA as a storage medium is the stability of DNA molecules, which can be preserved for up to a hundred years without human intervention.

[0004] In the DNA storage model where DNA is used as the storage medium, the original data is converted into a DNA sequence consisting of four bases, A, T, C, and G, and is stored in a DNA pool after DNA synthesis. When reading data, it is necessary to select a DNA sequence from the DNA pool for sequencing and convert it into binary data for reading. Editing errors may occur during the synthesis, storage, and sequencing of DNA sequences, i.e., insertion, deletion, or replacement of bases. DNA storage coding technology introduces appropriate redundancy through coding to resist editing errors and ensure the reliability of stored data. However, existing DNA coding technology cannot meet biological constraints including GC global and local balance, run constraints, card issuance constraints, and error correction capabilities, which greatly affects the efficiency of DNA storage. Summary of the invention

[0005] The purpose of the present invention is to provide a DNA encoding method, electronic device and storage medium that meet biological constraints (including GC global balance and local balance, run constraints and card-issuing constraints), which can solve the technical problem that the prior art cannot meet GC global balance and local balance, run constraints, card-issuing constraints and error correction capabilities, including at least one of but not limited to the above-mentioned biological condition constraints, which greatly affects the DNA storage efficiency.

[0006] In a first aspect, this embodiment provides a DNA encoding method that satisfies biological condition constraints, including:

[0007] Construct the cyclotomic coset S according to the given parameter information a ;

[0008] According to the circular coset S a Construct a polynomial ;

[0009] Choose a vector space V spanned by some polynomials d :It further includes selecting a set of Hamming distances d that satisfy max{S a}≤d for all cyclotomic cosets S a The corresponding polynomial , use these polynomials to form the vector space on F4 ;

[0010] The vector space V d The polynomials in are mapped into codewords;

[0011] Codewords that meet the biological constraints are selected from the codewords to generate a final codebook, wherein the final codebook satisfies: the edit distance between any two codewords is at least d e ≤d, where the code can correct An editing error.

[0012] Screening the codewords that meet the biological constraints as candidate codewords further includes: selecting codewords that meet at least one or more biological condition constraints including GC-global balance, GC-local balance, run constraint, and card-issuing constraint.

[0013] The GC-globally balanced codeword is a codeword that satisfies the following conditions: for any small real number ∈ ≥ 0, and the DNA sequence , the GC content of S satisfies , k1 is a preset constant less than 1. When K1 is 0.5, the global GC content ratio satisfies: , that is, the codeword satisfies the biological condition constraints of global balance.

[0014] The GC-local balance is to select codewords that satisfy the following conditions: for any small real number , and DNA sequences , and integers , if for any length of S DNA sequence fragment , , both The GC content meets , then S is said to satisfy Local balance, K2 is a preset constant less than 1; when K2 is 0.5, GC-local balance is to select a codeword that satisfies the following conditions: for any small real number , and DNA sequences , and integers , if for any length of S DNA sequence fragment , , both GC content meets , then S is said to satisfy Local balance.

[0015] The run constraint is to select codewords that meet the following conditions: 1) The same base does not appear more than 3 times in a row; 2) Any 2-length subsequence does not appear more than 2 times in a row; 3) Any 3-length subsequence does not appear more than 2 times in a row.

[0016] The card issuance constraint is to select codewords that satisfy the following condition: the reverse complementary length of any subsequence with an interval greater than 2 does not exceed 5.

[0017] Compared with the prior art, the present invention has the following advantages:

[0018] First, the present invention constructs a code that meets certain distance requirements (such as the edit distance between any two code words is at least d e ≤d, where the code can correct editing errors), greatly reducing the search space, and specific filtering rules can be used for further screening to improve efficiency.

[0019] Secondly, a series of cyclotomic cosets are first constructed, and then a part is selected from them to construct a polynomial, so as to form a vector space, and finally the mapping from the vector space to the code C is completed. In addition, it can be configured to meet at least one biological constraint: selecting codewords that meet the biological constraint from the codewords as candidate codewords further includes: selecting codewords that meet at least one or more biological condition constraints including GC-global balance, GC-local balance, run constraint, and card-issuing constraint, and in particular, when the codewords meet these biological condition constraints, the optimization effect is good. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] Figure 1 The principle flow chart of the DNA storage coding optimization method that meets biological condition constraints of the present invention;

[0021] Figure 2 The present invention is a flowchart of an example of a DNA storage coding optimization method that meets biological condition constraints. DETAILED DESCRIPTION

[0022] In the following description, specific details such as specific system structures, technologies, etc. are provided for the purpose of illustration rather than limitation, so as to provide a thorough understanding of the embodiments of the present application. However, it should be clear to those skilled in the art that the present application may also be implemented in other embodiments without these specific details. In other cases, detailed descriptions of well-known systems, devices, circuits, and methods are omitted to prevent unnecessary details from obstructing the description of the present application.

[0023] It should be understood that when used in the present specification and the appended claims, the term "comprising" indicates the presence of described features, integers, steps, operations, elements and / or components, but does not exclude the presence or addition of one or more other features, integers, steps, operations, elements, components and / or combinations thereof.

[0024] It should also be understood that the term “and / or” used in the specification and appended claims refers to any and all possible combinations of one or more of the associated listed items, and includes these combinations.

[0025] As used in the specification and appended claims of this application, the term "if" can be interpreted as "when" or "uponce" or "in response to determining" or "in response to detecting", depending on the context. Similarly, the phrase "if it is determined" or "if [described condition or event] is detected" can be interpreted as meaning "uponce it is determined" or "in response to determining" or "uponce [described condition or event] is detected" or "in response to detecting [described condition or event]", depending on the context.

[0026] References to "one embodiment" or "some embodiments" etc. described in the specification of this application mean that one or more embodiments of the present application include specific features, structures or characteristics described in conjunction with the embodiment. Therefore, the statements "in one embodiment", "in some embodiments", "in some other embodiments", "in some other embodiments", etc. that appear in different places in this specification do not necessarily refer to the same embodiment, but mean "one or more but not all embodiments", unless otherwise specifically emphasized in other ways. The terms "including", "comprising", "having" and their variations all mean "including but not limited to", unless otherwise specifically emphasized in other ways.

[0027] With the widespread application of digital information and the rapid development of big data science, the information data generated by people every day is growing exponentially, and the existing traditional storage media have gradually failed to meet the demand. As a new type of storage medium, DNA molecular chain has attracted widespread attention due to its advantages such as high storage density, long preservation time, low maintenance cost and strong stability.

[0028] At present, research on DNA storage is more focused on improving storage efficiency through efficient encoding, decoding and improving fault tolerance, thereby reducing the cost of synthetic sequencing; and on DNA-based storage media, more emphasis is placed on the exploration of theory and material structure.

[0029] The general process of DNA storage is to encode digital data into a DNA base sequence, synthesize DNA according to the encoded base sequence, and store it in a storage medium inside or outside the body. Among them, the synthesis of DNA can be achieved by writing a nucleotide base sequence through a synthesizer, and then stored in a pooled liquid as a medium. When reading data, it can be read and sequenced by a sequencer, and the data can be restored through subsequent decoding processing.

[0030] First Example

[0031] The principle of the DNA storage coding optimization method that meets biological condition constraints of the present invention is as follows: S1: constructing a circular coset according to given parameters; S2: constructing a polynomial according to the circular coset; S3: selecting a vector space formed by a partial polynomial; S4: mapping the polynomial in the vector space into a codeword; S5: screening the codewords that meet the biological constraints and the edit distance constraints from the codewords to generate the final codebook. According to the given parameters, the selection of a vector space formed by a partial polynomial is specifically to construct a polynomial that meets the conditions through the edit distance, thereby forming a vector space, and finally completing the mapping from the vector space to the code C. In addition, the code C can be configured to meet the need to meet one or some biological constraints.

[0032] The following is a detailed implementation process (see Figure 1 ).

[0033] Step S210: construct a circular coset according to given parameters.

[0034] The construction is specifically as follows: let n be an even number, and m be the smallest positive integer such that For Z n-1 For any element a in a for .

[0035] Cyclic coset S a It has the following properties: .

[0036] Cyclic coset S a It has the following properties: .

[0037] Step S220: construct a polynomial based on the cyclotomic coset.

[0038] The specific construction is: , select The maximal linear group on F4 can be obtained from S a structure A polynomial on : For the same cyclotomic coset S a Of all the constructed polynomials, select the linearly independent parts as the construction results.

[0039] Polynomial It has the following properties: The number of terms in its polynomial is .

[0040] The construction result has the following properties: .

[0041] Step S230: Select a partial circular coset according to given parameters, and use the polynomial constructed from it to span the subspace.

[0042] The specific construction is: select the Hamming distance d, select the a}≤d for all cyclotomic cosets S a The corresponding polynomial . Use these polynomials to construct the vector space F4 .

[0043] Vector space V d It has the following properties: The specific proof is as follows: Consider all Z without counting repetitions n-1 Cyclotomic Cosets , i.e. the cyclotomic coset , obviously when a>nd, the circular coset S a The selection requirements are not met, so .

[0044] Step S240: transform the vector space V d The polynomials in the tool are mapped to codewords on F4.

[0045] The structure is specifically as follows: All elements in , for V d Any polynomial and its linear combination in , the corresponding codeword is , get the code .

[0046] The codeword has the following properties: the code length is an even number n, let m be the smallest positive integer such that .

[0047] Code C has the following property: all its codewords belong to F4. The specific proof is as follows: Consider , so code C is on F4.

[0048] The code C has the following properties: the code C Hamming distance ≥ d, the code can correct Hamming error. The specific proof is as follows: Since the polynomial Its highest term satisfies the property , so it is in There are at most nd zeros in At most nd bits are 0, so the Hamming distance of code C ≥ d.

[0049] Code C has the following properties: Code C dimension The specific proof is as follows: ,and , so .

[0050] Step S250: Filter codewords that meet biological constraints from the codewords of code C. The present invention is a novel DNA encoding method that can correct multiple editing errors (insertion, deletion or substitution) and meet biological constraints (including but not limited to GC global balance and local balance, run constraint and hairpin constraint). GC global balance and local balance, run constraint and hairpin constraint can meet one or more of the biological constraints. In the embodiment, only the corresponding parameters are cited for explanation and display.

[0051] The biological constraint refers to one or several of GC-global balance, GC-local balance, run constraint, and hairpin constraint, and may not be limited to these biological constraints.

[0052] GC-Globally balanced codewords are selected to satisfy the following conditions: for any small real number , and DNA sequences , the GC content of S satisfies , k1 is a preset constant less than 1. When K1 is 0.5, the global GC content ratio satisfies: , that is, the codeword satisfies the biological condition constraints of global balance.

[0053] GC-local balance is to choose a codeword that satisfies the following conditions: for any small real number , and DNA sequences , and integers , if for any length of S DNA sequence fragment , , both The GC content meets , then S is said to satisfy Local equilibrium, K2 is a preset constant less than 1; when K2 is 0.5, GC-local equilibrium means: for any small real number , and DNA sequences , and integers If any length of S is DNA sequence fragment , , both The GC content meets , then S is said to satisfy Local balance.

[0054] The run constraint means: 1) the same base cannot appear consecutively more than 3 times; 2) any 2-length subsequence cannot appear consecutively more than 2 times; 3) any 3-length subsequence cannot appear consecutively more than 2 times. The above parameters of 3, 2, etc. are just examples.

[0055] The card issuance constraint means that the reverse complementary length of any subsequence with an interval exceeding 2 does not exceed 5. The above parameters of 5, 2, etc. are only examples.

[0056] Complementarity means that two bases form base pairs such as AT and CG.

[0057] Reverse complement refers to: and Complementary, and Complementary, and Complementary... .

[0058] Intervals greater than 2 means .

[0059] Step S260: Select a group from the above final candidate codewords according to the selection algorithm to form the final codebook.

[0060] The final codebook satisfies the following properties: the edit distance between any two codewords is at least d e ≤d, where the code can correct An editing error.

[0061] The selection algorithm may specifically include:

[0062] 1) Randomly select a candidate codeword that has not been selected and mark it. If the codebook is empty at this time, put it directly into the codebook; if the codebook is not empty at this time, calculate the edit distance between it and all existing codewords in the codebook. If all of them are not less than d e , then put it into the codebook; if there is an existing codeword with an edit distance of no more than d e , then discard the codeword.

[0063] 2) If there are still candidate codewords that have not been selected, execute 1); if all candidate codewords have been selected, execute 3).

[0064] 3) If the current codebook is the first codebook, or the current codebook size is larger than the final codebook size, the final codebook is updated to the current codebook.

[0065] 4) Repeat the above process L times (pre-agreed number of times) and output the final codebook.

[0066] Application Examples

[0067] like Figure 2 As shown, this embodiment relates to a DNA encoding method capable of correcting multiple editing errors while satisfying the global GC content in The local GC content is between Between, travel constraints, card issuance constraints and other properties. It includes the following steps:

[0068] Given loop parameter L=100; encoding parameter , that is, considering a codeword with a code length of 16 and an edit distance of 7, the code can correct 3 Hamming errors / edit errors; the GC ratio parameter , that is, the global GC ratio satisfies: [0.4, 0.6], and the local GC ratio satisfies: the GC ratio of any 8-length subsequence is [0.25, 0.75]. For example, the above run constraints: "1) The number of consecutive occurrences of the same base does not exceed 3; 2) The number of consecutive occurrences of any 2-length subsequence does not exceed 2; 3) The number of consecutive occurrences of any 3-length subsequence does not exceed 2.", the hairpin constraint: "The reverse complementary length of any subsequence with an interval of more than 2 does not exceed 5". Step 1) Construct a circular coset based on the given parameters: .

[0069] Step 2) Consider the cyclotomic coset , from which linearly independent polynomials are constructed, including:

[0070] 2.1) Selection A set of bases on F4 .

[0071] 2.2) .

[0072] 2.3) .

[0073] 2.4) .

[0074] 2.5) .

[0075] 2.6) .

[0076] Step 3) Expand the obtained polynomial into a vector space on F4 .

[0077] Step 4) Mapping the polynomial in the vector space V7 to a codeword on F4, specifically including:

[0078] 4.1) Selection All elements in .

[0079] 4.2) Construction code .

[0080] Step 5) Select codewords satisfying biological constraints from code C as candidate codewords.

[0081] Step 6) Select a set of codewords from the candidate codewords as the final codebook, specifically including:

[0082] 6.1) Randomly select a codeword that has not been selected from the final candidate codewords and mark it.

[0083] 6.2) Determine whether the codebook is empty. If so, execute 6.4); if not, execute 6.3).

[0084] 6.3) Determine whether the edit distance between the codeword and the existing codewords in the codebook is not less than 7. If so, execute 6.4); if not, execute 6.1).

[0085] 6.4) Add the codeword to the codebook.

[0086] 6.5) Determine whether all code words have been selected. If so, execute 6.6); if not, execute 6.1).

[0087] 6.6) If the current codebook is the first codebook, execute 6.8); if the current codebook is not the first codebook, execute 6.7).

[0088] 6.7) If the current codebook size is larger than the final codebook size, execute 6.8); if the current codebook size does not exceed the final codebook size, execute 6.9).

[0089] 6.8) Update the final codebook to the current codebook.

[0090] 6.9) Determine the number of times 6.9) has been executed. If it is less than 100, clear all marks, reset the codebook, and execute 7.1); if it is the 100th time, output the final codebook.

[0091] Step 7) Get the final codebook with a codebook size of 597.

[0092] Second embodiment

[0093] The structure of a terminal device provided in an embodiment of the present application. The terminal device of this embodiment includes: at least one processor, a memory, and a computer program stored in the memory and executable on the at least one processor, and the processor implements the steps in any of the above-mentioned method embodiments when executing the computer program.

[0094] The terminal device may be a computing device such as a desktop computer, a notebook, a PDA, and a cloud server. The terminal device may include, but is not limited to, a processor and a memory. Those skilled in the art will appreciate that the terminal may have more or fewer components, or a combination of certain components, or different components, for example, it may also include input and output devices, network access devices, etc. The processor may be a central processing unit (CPU), and the processor may also be other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gates or transistor logic devices, discrete hardware components, etc. The general-purpose processor may be a microprocessor or the processor may also be any conventional processor, etc.

[0095] In some embodiments, the memory may be an internal storage unit of the terminal device, such as a hard disk or memory of the terminal device. In other embodiments, the memory may also be an external storage device of the terminal device, such as a plug-in hard disk, a smart memory card (Smart Media Card, SMC), a secure digital (Secure Digital, SD) card, a flash card (Flash Card), etc. equipped on the terminal device. Further, the memory may also include both an internal storage unit of the terminal device and an external storage device. The memory is used to store an operating system, an application program, a boot loader (BootLoader), data, and other programs, such as the program code of the computer program, etc. The memory may also be used to temporarily store data that has been output or is to be output.

[0096] The present application also provides a computer-readable storage medium storing a computer program, which can implement the steps in the above-mentioned method embodiments when the computer program is executed by a processor. The present application also provides a computer program product, which can implement the steps in the above-mentioned method embodiments when the computer program product is executed on a mobile terminal.

[0097] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the present application implements all or part of the processes in the above-mentioned embodiment method, which can be completed by instructing the relevant hardware through a computer program. The computer program can be stored in a computer-readable storage medium, and the computer program can implement the steps of the above-mentioned various method embodiments when executed by the processor. Among them, the computer program includes computer program code, and the computer program code can be in source code form, object code form, executable file or some intermediate form. The computer-readable medium can at least include: any entity or device that can carry the computer program code to the camera / terminal device, recording medium, computer memory, read-only memory (ROM, Read-Only Memory), random access memory (RAM, RandomAccess Memory), electric carrier signal, telecommunication signal and software distribution medium. For example, a USB flash drive, a mobile hard disk, a disk or an optical disk. In some jurisdictions, according to legislation and patent practice, computer-readable media cannot be electric carrier signals and telecommunication signals.

[0098] In the above embodiments, the description of each embodiment has its own emphasis. For the part not described or recorded in detail in one embodiment, reference can be made to the relevant description of other embodiments. The DNA module of the present invention mainly refers to deoxyribonucleic acid (DNA).

[0099] Those of ordinary skill in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of this application.

[0100] In the embodiments provided in the present application, it should be understood that the disclosed devices / network equipment and methods can be implemented in other ways. For example, the device / network equipment embodiments described above are merely schematic. For example, the division of the modules or units is only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0101] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

Claims

1. A DNA encoding method that meets biological condition constraints, characterized in that: include: Construct a cyclotomic coset based on the given parameter information ; According to the cyclotomic coset Construct a polynomial ; Choose a vector space spanned by some polynomials :It further includes the Hamming distance according to the setting Choose to meet All cyclotomic cosets of The corresponding polynomial , these polynomials are used to form Upper vector space ; The vector space The polynomials in are mapped into codewords; Codewords that meet the biological constraints are selected from the codewords to generate a final codebook, wherein the final codebook satisfies: the edit distance between any two codewords is at least , where the code can correct An editing error; Among them, the circular coset is constructed according to the given parameter information Further including: Any element , whose corresponding cyclotomic coset for , is an even number, is the smallest positive integer, -1; According to the cyclotomic coset Construct a polynomial Further including: make , select exist The maximal linear group on structure A polynomial on : , for the same cyclotomic coset Of all the constructed polynomials, select the linearly independent parts as the construction results; The vector space The polynomial in is mapped into codewords further including: Select All elements in ,for Any polynomial and its linear combination in , the corresponding codeword is , get the code .

2. The DNA encoding method satisfying biological condition constraints as claimed in claim 1, characterized in that: Circular cosets It has the following properties: and ,and .

3. The DNA encoding method satisfying biological condition constraints as claimed in claim 1, characterized in that: Selecting codewords that meet biological constraints from the codewords to generate a final codebook further includes: Selecting code words that meet biological constraints from the code words as candidate code words; A group is selected from the candidate code words according to a selection algorithm to form a final codebook.

4. The DNA encoding method satisfying biological condition constraints as claimed in claim 3, characterized in that: Screening the codewords that meet the biological constraints as candidate codewords further includes: selecting codewords that meet at least one of the biological condition constraints including GC-global balance, GC-local balance, run constraint, and card-issuing constraint.

5. The DNA encoding method satisfying biological condition constraints as claimed in claim 4, characterized in that: The GC-global balanced codeword is a codeword that satisfies the following conditions: for any small real number , and DNA sequences , The GC content meets , k1 is a preset constant less than 1.

6. The DNA encoding method satisfying biological condition constraints as claimed in claim 4, characterized in that: The GC-local balance is to select codewords that satisfy the following conditions: for any small real number , and DNA sequences , and integers , if The arbitrary length of DNA sequence fragment , , both The GC content meets , then it is called Meet GC- -Local balance, K2 is a preset constant less than 1.

7. The DNA encoding method satisfying biological condition constraints as claimed in claim 4, characterized in that: The run constraint is to select codewords that meet the following conditions: 1) The number of consecutive occurrences of the same base does not exceed ; 2) Any The longest subsequence appears no more than ; 3) Any The longest subsequence appears no more than .

8. The DNA encoding method satisfying biological condition constraints as claimed in claim 4, characterized in that: The card issuance constraint is to select code words that meet the following conditions: any interval exceeding The reverse complement length of the subsequence does not exceed .

9. The DNA encoding method satisfying biological condition constraints as claimed in claim 3, characterized in that: Selecting a group of candidate codewords according to a selection algorithm as a final codebook further comprises: S1: Randomly select a candidate codeword that has not been selected and mark it. If the codebook is empty at this time, put it directly into the codebook; if the codebook is not empty at this time, calculate the edit distance between it and all existing codewords in the codebook. If all are not less than , then put it into the codebook; if there is an existing codeword with an edit distance of no more than , then discard the codeword; S2: If there are still candidate codewords that have not been selected, execute S1; if all the candidate codewords have been selected, execute S3; S3: If the current codebook is the first codebook, or the current codebook size is larger than the final codebook size, the final codebook is updated to the current codebook; S4: Repeat the above process for a preset number of times and output the final codebook.

10. A terminal device, characterized in that: include: A memory and a processor, wherein the memory stores a computer program, and the processor implements the method according to any one of claims 1 to 9 when executing the computer program.

11. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer instructions, and when the computer instructions are executed on an electronic device, the electronic device executes the method according to any one of claims 1 to 9.

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