Pantogenomic typing method for plectropomus leopardus based on low-cost DNA extraction

Abstract

The invention relates to the field of genetic typing, and discloses a plectropomus leopardus generic genome typing method based on low-cost DNA extraction, which comprises the following steps: carrying out DNA sampling extraction on plectropomus leopardus to construct a re-sequencing library, processing DNA data of all high-depth groups in the re-sequencing library by using Shape software, constructing a haplotype database, and carrying out genotyping on the haplotype database. And performing genotype filling on the low-depth sequencing individuals to obtain haplotypes and genotypes of the low-depth sequencing individuals, and establishing a generic genome IBD cluster typing technology. And finally, generating an individual-level report of the target plectropomus leopardus. According to the invention, a lossless, simple and low-cost DNA extraction technology for the plectropomus leopardus can be established, large-scale sample application is realized, and the purpose of generic genome typing of the plectropomus leopardus is realized.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of genotyping, in particular a pan-genome genotyping method of Epinephelus latifasciatus based on low-cost DNA extraction. BACKGROUND

[0002] Epinephelus latifasciatus, commonly known as East Starbass, is a high-end edible fish. It has characteristics such as slow growth and susceptibility to iridovirus, which can easily affect market prices. The core concept of pan-genome genotyping includes that pan-genome refers to the sum of the genomes of all individuals of a species, including the core genome (genes shared by all individuals) and the variable genome (genes specific to some individuals). Genotyping is to identify the specific genetic combination of alleles. Compared with traditional genotyping, pan-genome genotyping has the purposes of greatly improving coverage sites, discovering rare variations, and reducing costs.

[0003] The scientific purpose of genotyping is to explain the geographical population differentiation of Epinephelus latifasciatus and mine disease resistance, growth, body color genes, etc. through IBD cluster division. The industrial advantages include cost control and phenotype integration, and improved survival rate. The technology is not only an upgrade of genotyping method, but also a core engine to promote aquaculture into the era of precision, low cost and high throughput. At the same time, a non-destructive, simple and low-cost DNA extraction technology for Epinephelus latifasciatus is established, realizing the application of large-scale samples. SUMMARY

[0004] The present application overcomes the shortcomings of the prior art and provides a pan-genome genotyping method of Epinephelus latifasciatus based on low-cost DNA extraction.

[0005] To achieve the above purpose, the technical scheme adopted by the present application is as follows:

[0006] The present application provides a pan-genome genotyping method of Epinephelus latifasciatus based on low-cost DNA extraction in the first aspect, comprising the following steps:

[0007] DNA sampling and extraction are performed on Epinephelus latifasciatus, and a re-sequencing library is constructed based on the DNA data obtained by sampling;

[0008] Haplotype DNA database construction is performed on the DNA data of the high-depth group in the re-sequencing library, and genotype filling is performed on the DNA data of the low-depth group after the haplotype database construction to obtain a target haplotype DNA database;

[0009] Based on the target haplotype DNA database, pan-genome IBD cluster genotyping is performed on the target Epinephelus latifasciatus, and the cluster characteristics are labeled;

[0010] The individual-level report of the target Ptereleotris punctata is generated in combination with the IBD cluster typing processing result of the pan-genome of the target Ptereleotris punctata, and the target Ptereleotris punctata is resequenced to verify the consistency of the typing.

[0011] Further, in a preferred embodiment of the present application, the DNA of the target Ptereleotris punctata is sampled and extracted, and a resequencing library is constructed based on the DNA data obtained by sampling, specifically:

[0012] A Ptereleotris punctata requiring DNA extraction is obtained, and is labeled as a target Ptereleotris punctata. The target Ptereleotris punctata is introduced into a big data network, and a drug that can anesthetize the target Ptereleotris punctata is searched in the big data network. A dose of the corresponding drug that does not cause death to the target Ptereleotris punctata is searched and outputted, so that the target Ptereleotris punctata is in an anesthetized state.

[0013] The tail fin tissue of the target Ptereleotris punctata in the anesthetized state is cut, and the target Ptereleotris punctata tail fin tissue is obtained. The target Ptereleotris punctata tail fin tissue is placed in a centrifuge tube, a lysis buffer is added to the centrifuge tube, and the target Ptereleotris punctata tail fin tissue is subjected to water bath treatment in the centrifuge tube.

[0014] After water bath treatment, the lysis Ptereleotris punctata tail fin tissue is obtained. The volume of the lysis Ptereleotris punctata tail fin tissue is determined, and an equal volume of isopropyl alcohol is added to the centrifuge tube for impurity removal, and the supernatant of the lysis Ptereleotris punctata tail fin tissue is obtained.

[0015] Isopropyl alcohol is added to the supernatant of the lysis Ptereleotris punctata tail fin tissue, and centrifugal treatment is performed in the centrifuge tube. The precipitate is collected, wherein the precipitate is the DNA precipitate of the Ptereleotris punctata.

[0016] The precipitate is washed by ethanol, and the washed precipitate is dried to obtain dry precipitate. The dry precipitate is dissolved in TE buffer, and the concentration of the dry precipitate in the TE buffer is monitored by a spectrophotometer to obtain the DNA concentration of the target Ptereleotris punctata.

[0017] A resequencing library is constructed in combination with the DNA concentration of the target Ptereleotris punctata.

[0018] Further, in a preferred embodiment of the present application, the resequencing library is constructed in combination with the DNA concentration of the target Ptereleotris punctata, specifically:

[0019] The dry precipitate is subjected to cyclic ultrasonic fragmentation treatment by a focused ultrasound instrument, and the standard time of the cyclic ultrasonic fragmentation treatment is determined in combination with the DNA concentration of the target Ptereleotris punctata.

[0020] When the time of the cyclic ultrasonic fragmentation treatment is equal to the standard time of the cyclic ultrasonic fragmentation treatment, the dry precipitate cyclic ultrasonic fragmentation treatment is stopped, and the DNA fragments of the Ptereleotris punctatum to be treated are obtained;

[0021] The DNA fragments of the Ptereleotris punctatum to be treated are subjected to exponential amplification, and after the exponential amplification, the DNA fragments of the Ptereleotris punctatum to be treated are subjected to magnetic bead double-screen purification treatment, wherein the magnetic bead double-screen purification treatment is that magnetic beads used for removing DNA fragments with a size greater than a predetermined value in the DNA fragments of the Ptereleotris punctatum to be treated are added, and the DNA fragments of the Ptereleotris punctatum to be treated with a size maintained within the predetermined value are retained by the target magnetic beads, and target DNA fragments of the Ptereleotris punctatum are obtained;

[0022] Based on the target DNA fragments of the Ptereleotris punctatum, and in combination with the DNA concentration of the target Ptereleotris punctatum, a resequencing library is constructed, and the resequencing library is a double-strategy library, including high-depth group DNA data and low-depth group DNA data;

[0023] The resequencing library construction method is that a DNA sample blank library is introduced into a big data network, and the target DNA fragments of the Ptereleotris punctatum and the DNA concentration of the target Ptereleotris punctatum are introduced into the DNA sample blank library, and the library is classified according to the size of the target DNA fragments of the Ptereleotris punctatum and the corresponding concentration, and the resequencing library is obtained.

[0024] The difference between the high-depth group DNA data and the low-depth group DNA data is that the fragment size and the fragment concentration of the target DNA fragments of the Ptereleotris punctatum in different libraries are different.

[0025] Further, in a preferred embodiment of the present application, the high-depth group DNA data in the resequencing library is subjected to haplotype DNA database construction, and after the haplotype database is constructed, the low-depth group DNA data is subjected to genotype filling, and the target haplotype DNA database is obtained, specifically:

[0026] In the resequencing library, the high-depth group DNA data is designated as high-depth DNA data, and the low-depth group DNA data is designated as low-depth DNA data.

[0027] Based on the big data network, a reference genome of the Ptereleotris punctatum is retrieved, and the high-depth DNA data is compared with the reference genome of the Ptereleotris punctatum, and a DNA sequence alignment file is outputted.

[0028] In combination with the DNA sequence alignment file, all high-depth DNA data is subjected to variation site screening, and high-depth DNA data with variation sites is determined, and all high-depth DNA data with variation sites is subjected to variation information merging.

[0029] Filter all high-depth DNA data based on the variation information obtained by merging to obtain qualified high-depth DNA data;

[0030] Introduce Shapet software, and input the qualified high-depth DNA data into the Shapet software to perform Markov chain Monte Carlo iteration optimization, wherein the Markov chain Monte Carlo iteration optimization is to determine haplotype linkage relationship of different chromosomes on the qualified high-depth DNA data, and a phased result of the qualified high-depth DNA data is obtained;

[0031] According to the phased result of the qualified high-depth DNA data, the qualified high-depth DNA data is integrated to obtain a haplotype DNA database, and the low-depth DNA data is imported into the haplotype DNA database for sample alignment;

[0032] The similarity between the low-depth DNA data and the aligned qualified high-depth DNA data is calculated, and if the similarity is greater than a preset value, the low-depth DNA data is directly replaced by the corresponding qualified high-depth DNA data;

[0033] If the similarity is not greater than the preset value, the missing genotype of the low-depth DNA data compared with the aligned qualified high-depth DNA data is calculated, the low-depth DNA data is filled and iteratively optimized, and an optimized haplotype DNA database is output, which is labeled as a target haplotype DNA database.

[0034] Further, in a preferred embodiment of the present application, based on the target haplotype DNA database, the target leopard gill-spine bass is subjected to pan-genomic IBD cluster typing processing and cluster characteristics are labeled, and the specific steps are as follows:

[0035] Introduce IBIS software, and connect the IBIS software with the target haplotype DNA database, and through the IBIS software, monitor the homologous fragments in the filled genotype data in the target haplotype DNA database;

[0036] The filled genotype data in the target haplotype DNA database includes the qualified high-depth DNA data and the iteratively optimized low-depth DNA data;

[0037] Determine the homologous fragments shared between the filled genotype data, and label them as IBD fragments, and in the IBIS software, based on the total length and the number of fragments of the IBD fragments, construct an IBD fragment sharing matrix, and in the IBD fragment sharing matrix, the IBD fragments are classified by hierarchical classification method;

[0038] The hierarchical classification method is to convert the IBD fragment sharing matrix into a genetic distance matrix, and iteratively combine the closest IBD fragments in the genetic distance matrix, so that a new cluster IBD fragment is obtained each time, and the average distance between different cluster IBD fragments is updated in real time during the iterative combination process.

[0039] According to the average distance between the cluster IBD fragments, the distance variance rate between the cluster IBD fragments is calculated in real time, and a variance rate curve is drawn, the variance rate curve is analyzed, a standard decline rate is preset, when the decline rate of the variance in the variance rate curve is greater than the standard decline rate, the corresponding point in the variance rate curve is selected as an inflection point, and the optimal cluster number of the IBD fragment is determined based on the inflection point, and is marked as the target cluster number.

[0040] The allele frequency spectrum of different cluster IBD fragments is obtained, which is used to compare the SNP sites of different cluster IBD fragments, and the genomic function of different cluster IBD fragments is determined according to the difference of the SNP sites of the cluster IBD fragments.

[0041] Based on the genomic function of different cluster IBD fragments, the cluster characteristics of different cluster IBD fragments are labeled, wherein the cluster characteristics of different cluster IBD fragments represent the cluster characteristics of the target leopard grouper.

[0042] Further, in a preferred embodiment of the present application, the pan-genome IBD cluster typing processing result of the target leopard grouper is combined to generate an individual-level report of the target leopard grouper, and the target leopard grouper is resequenced to verify the consistency of the typing, specifically:

[0043] According to the cluster characteristics of the target leopard grouper, the genomic function of the corresponding cluster IBD fragment, and the filled genotype data of the target leopard grouper in the target haplotype DNA database, an individual-level report of the target leopard grouper is generated;

[0044] A commercial kit is obtained, and the DNA sample of the target leopard grouper is extracted through the commercial kit, and resequencing processing is performed after the DNA sample is extracted;

[0045] The resequencing processing is used to verify the pan-genome IBD cluster typing processing result of the target leopard grouper.

[0046] If the similarity between the cluster characteristics of the target leopard grouper obtained by the resequencing processing and the cluster characteristics of the target leopard grouper obtained by the pan-genome IBD cluster typing processing is greater than a preset value, the individual-level report of the target leopard grouper is divided into qualified;

[0047] Otherwise, the target leopard bristletooth is subjected to secondary pan-genome IBD cluster typing processing.

[0048] The second aspect of the present application also provides a leopard bristletooth pan-genome typing system based on low-cost DNA extraction, which comprises a memory and a processor, the memory stores a leopard bristletooth pan-genome typing method, and the leopard bristletooth pan-genome typing method is executed by the processor to achieve the following steps:

[0049] DNA sampling and extraction are performed on the leopard bristletooth, and a re-sequencing library is constructed based on the DNA data obtained by sampling;

[0050] Haplotype DNA database construction is performed on the high-depth group of DNA data in the re-sequencing library, and genotype filling is performed on the low-depth group of DNA data after the haplotype database construction to obtain a target haplotype DNA database;

[0051] Based on the target haplotype DNA database, the target leopard bristletooth is subjected to pan-genome IBD cluster typing processing, and the cluster characteristics are labeled;

[0052] Combined with the pan-genome IBD cluster typing processing result of the target leopard bristletooth, an individual-level report of the target leopard bristletooth is generated, and the target leopard bristletooth is re-sequenced to verify the consistency of the typing.

[0053] The present application solves the technical defects in the background art, and has the following beneficial effects: DNA sampling and extraction are performed on the leopard bristletooth for constructing a re-sequencing library, the re-sequencing library uses Shapet software to process all high-depth group DNA data, construct a haplotype database, and fill in the genotype of low-depth sequencing individuals, obtain the haplotype and genotype of each low-depth sequencing individual, and establish a pan-genome IBD cluster typing technology. Finally, an individual-level report of the target leopard bristletooth is generated. The present application can establish a non-destructive, simple and low-cost DNA extraction technology for leopard bristletooth, realize the application of large-scale samples, and achieve the purpose of pan-genome typing of leopard bristletooth. BRIEF DESCRIPTION OF DRAWINGS

[0054] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the following will briefly introduce the drawings needed to be used in the embodiments or prior art description. Obviously, the drawings in the following description are only some embodiments of the present application, and those skilled in the art can obtain other drawings of other embodiments according to these drawings without any creative effort.

[0055] Figure 1 A flowchart of a leopard bristletooth pan-genome typing method based on low-cost DNA extraction is shown.

[0056] Figure 2 A method flow chart for constructing a resequencing library is shown.

[0057] Figure 3 A program view of a leopard grouper pangenome typing system based on low-cost DNA extraction is shown. DETAILED DESCRIPTION

[0058] In order to enable a clearer understanding of the above-mentioned purposes, features and advantages of the present application, the present application will be further described in detail below in conjunction with the accompanying drawings and specific embodiments. It should be noted that the embodiments of the present application and the features in the embodiments can be combined with each other without conflict.

[0059] In the following description, a large number of specific details are set forth in order to facilitate a thorough understanding of the present application, however, the present application can also be implemented in other ways different from those described herein, and therefore, the scope of protection of the present application is not limited by the specific embodiments disclosed below.

[0060] Figure 1 A flow chart of a leopard grouper pangenome typing method based on low-cost DNA extraction is shown, including the following steps:

[0061] S102: DNA sampling and extraction is performed on the leopard grouper, and based on the DNA data obtained by sampling, a resequencing library is constructed;

[0062] S104: haplotype DNA database construction is performed on the DNA data of the high-depth group in the resequencing library, and after the haplotype database construction, genotype filling is performed on the DNA data of the low-depth group, to obtain a target haplotype DNA database;

[0063] S106: based on the target haplotype DNA database, pangenome IBD cluster typing processing is performed on the target leopard grouper, and cluster characteristics are labeled;

[0064] S108: combined with the pangenome IBD cluster typing processing result of the target leopard grouper, an individual-level report of the target leopard grouper is generated, and the target leopard grouper is resequenced to verify the consistency of the typing.

[0065] Further, in a preferred embodiment of the present application, the haplotype DNA database construction is performed on the DNA data of the high-depth group in the resequencing library, and after the haplotype database construction, genotype filling is performed on the DNA data of the low-depth group, to obtain a target haplotype DNA database, specifically:

[0066] In the resequencing library, the DNA data in the high-depth group is labeled as high-depth DNA data, and the DNA data in the low-depth group is labeled as low-depth DNA data;

[0067] Based on the big data network, the reference genome of the leopard pufferfish is retrieved, and the high-depth DNA data is compared with the reference genome of the leopard pufferfish, and a DNA sequence alignment file is output;

[0068] Combined with the DNA sequence alignment file, all high-depth DNA data is screened for variant sites, high-depth DNA data with variant sites is determined, and all high-depth DNA data with variant sites is combined for variant information;

[0069] Based on the combined variant information of the high-depth DNA data, all high-depth DNA data is filtered to obtain qualified high-depth DNA data;

[0070] Introduce Shapet software, input the qualified high-depth DNA data into the Shapet software for Markov chain Monte Carlo iteration optimization, wherein the Markov chain Monte Carlo iteration optimization is to determine the haplotype linkage relationship of different chromosomes of the qualified high-depth DNA data, and obtain the phased results of the qualified high-depth DNA data;

[0071] According to the phased results of the qualified high-depth DNA data, the qualified high-depth DNA data is integrated to obtain a haplotype DNA database, and the low-depth DNA data is imported into the haplotype DNA database for sample alignment;

[0072] Calculate the similarity between the low-depth DNA data and the aligned qualified high-depth DNA data, if the similarity is greater than a preset value, the low-depth DNA data is directly replaced by the corresponding qualified high-depth DNA data;

[0073] If the similarity is not greater than the preset value, calculate the missing genotype of the low-depth DNA data compared with the aligned qualified high-depth DNA data, fill and iteratively optimize the low-depth DNA data, and output the optimized haplotype DNA database, which is labeled as the target haplotype DNA database.

[0074] It should be noted that high-depth DNA data has lower quality variation, lower deletion rate, lower loss rate, and more reliable coverage than low-depth DNA data. First, the high-depth DNA data needs to be monitored and filtered, and then compared with the reference genome of the leopard pufferfish to determine the presence of variation sites in the high-depth DNA data, and the variation information of all high-depth DNA data is combined to perform population joint typing. The purpose is to filter low-quality DNA sites, including depth, quality value, and low deletion rate sites, to obtain qualified high-depth DNA data. The haplotype database is constructed by combining qualified high-depth DNA data, and the haplotype phasing of qualified high-depth DNA data is performed. Shape software is a software tool for haplotype phasing, which is used to divide qualified high-depth DNA data into continuous blocks and optimize through Markov chain Monte Carlo iteration to determine the haplotype linkage relationship of adjacent SNPs on each chromosome, that is, to determine the linkage relationship of different sites on DNA data. The haplotype DNA database is obtained by combining all phased results, and the low-depth DNA data is imported into the haplotype DNA database for sample alignment. The purpose is to facilitate the calculation of the haplotype matching probability of the next low-depth DNA data. The haplotype matching probability is the similarity between the low-depth DNA data and the aligned qualified high-depth DNA data. The greater the similarity, the more similar the low-depth DNA data is to a certain high-depth DNA data. In order to ensure the filling processing of low-depth DNA data, the same genotype is directly assigned. If the similarity is insufficient, the missing genotype of the low-depth DNA data compared with the aligned qualified high-depth DNA data is calculated, and the low-depth DNA data is filled and iteratively optimized, that is, the low-depth DNA data is processed to make it similar to the high-depth DNA data, and all DNA data is ensured to be high-depth DNA data. The target haplotype DNA database is obtained.

[0075] Further, in a preferred embodiment of the present application, based on the target haplotype DNA database, the target leopard pufferfish is subjected to pan-genomic IBD cluster typing processing and cluster characteristics are labeled, specifically:

[0076] IBIS software is introduced, and the IBIS software is connected with the target haplotype DNA database, and through the IBIS software, homologous fragment monitoring is performed on the filled genotype data in the target haplotype DNA database.

[0077] Among them, the filled genotype data in the target haplotype DNA database includes qualified high-depth DNA data and iteratively optimized low-depth DNA data.

[0078] Determine the homologous fragments shared between the filled genotype data, labeled as IBD fragments, construct an IBD fragment sharing matrix in the IBIS software based on the total length of the IBD fragments and the number of fragments, and cluster the IBD fragments in the IBD fragment sharing matrix by hierarchical clustering method;

[0079] Among them, the hierarchical clustering method is to convert the IBD fragment sharing matrix into a genetic distance matrix, and iteratively merge the closest IBD fragments in the genetic distance matrix, and each merging obtains a new cluster IBD fragment, and the average distance between different cluster IBD fragments is updated in real time during the iterative merging process;

[0080] According to the average distance between the cluster IBD fragments, the distance variance rate between the cluster IBD fragments is calculated in real time, and a variance rate curve is drawn, the variance rate curve is analyzed, and when the descending rate of the variance in the variance rate curve is greater than the standard descending rate, the corresponding point in the variance rate curve is selected as the inflection point, and the optimal cluster number of the IBD fragments is determined based on the inflection point, and is labeled as the target cluster number;

[0081] Obtain the allele frequency spectrum of different cluster IBD fragments, which is used to compare the SNP sites of different cluster IBD fragments, and determine the genomic function of different cluster IBD fragments according to the differences of the SNP sites of the cluster IBD fragments;

[0082] Based on the genomic function of different cluster IBD fragments, the cluster characteristics of different cluster IBD fragments are labeled, and the cluster characteristics of different cluster IBD fragments represent the cluster characteristics of the target leopard plectrypoma.

[0083] It should be noted that the IBIS software is used to scan the genomes between each pair of data individuals in the target haplotype DNA database, identify the completely same haplotype fragments, i.e. homologous fragments, also known as IBD fragments, and the IBD fragments are in pairs. Construct an IBD fragment sharing matrix, and cluster the IBD fragments in the IBD fragment sharing matrix by hierarchical clustering method, the purpose is to quantify the genetic sharing degree, and provide conditions for the pan-genomic typing of leopard plectrypoma. The hierarchical clustering method clusters different DNA fragment individuals, wherein the fragments in the cluster are genetically similar fragments, which are also in the same gene cluster after pan-genomic typing. Each cluster contains several gene fragments of the same type. Obtain the allele frequency spectrum of different cluster IBD fragments, which is used to compare the SNP sites of different cluster IBD fragments, i.e. to locate the same genomic function, and some cluster IBD fragments may be disease resistance related genes, and some may be growth regulation genes, etc.

[0084] Further, in a preferred embodiment of the present application, the pan-genome IBD cluster typing processing result of the target Ptereleotris punctatum is combined to generate an individual-level report of the target Ptereleotris punctatum, and the target Ptereleotris punctatum is resequenced to verify the consistency of the typing, specifically:

[0085] According to the cluster characteristics of the target Ptereleotris punctatum, the genomic function of the corresponding cluster IBD fragment, and the filled genotype data of the target Ptereleotris punctatum in the target haplotype DNA database, an individual-level report of the target Ptereleotris punctatum is generated;

[0086] A commercial kit is obtained, and DNA sample extraction is performed on the target Ptereleotris punctatum by using the commercial kit, and resequencing processing is performed after the DNA sample extraction;

[0087] The resequencing processing is used to verify the pan-genome IBD cluster typing processing result of the target Ptereleotris punctatum;

[0088] If the similarity between the cluster characteristics of the target Ptereleotris punctatum obtained by the resequencing processing and the cluster characteristics of the target Ptereleotris punctatum obtained by the pan-genome IBD cluster typing processing is greater than a preset value, the individual-level report of the target Ptereleotris punctatum is divided into qualified;

[0089] Otherwise, the target Ptereleotris punctatum is subjected to secondary pan-genome IBD cluster typing processing.

[0090] It should be noted that the purpose of generating the individual-level report of the target Ptereleotris punctatum is to provide a reference for the staff analyzing the genes, but it is also necessary to ensure whether the individual-level report of the target Ptereleotris punctatum is accurate. By using the sampling analysis monitoring of the commercial kit with high cost, it can be judged whether the pan-genome IBD cluster typing processing result of the target Ptereleotris punctatum is accurate. If it is not accurate, the pan-genome IBD cluster typing processing needs to be performed again.

[0091] Figure 2 A method flowchart for constructing a resequencing library is shown, which includes the following steps:

[0092] S202: DNA sampling and extraction are performed on the Ptereleotris punctatum, and a resequencing library is constructed based on the DNA data obtained by sampling;

[0093] S204: The resequencing library is constructed in combination with the DNA concentration of the target Ptereleotris punctatum.

[0094] Further, in a preferred embodiment of the present application, the DNA sampling and extraction are performed on the Ptereleotris punctatum, and a resequencing library is constructed based on the DNA data obtained by sampling, specifically:

[0095] A leopard catfish that needs to be subjected to DNA extraction is acquired, and is calibrated as a target leopard catfish, and is introduced into a big data network, in which a drug that can be used to anesthetize the target leopard catfish is searched, and a dose of the corresponding drug that does not cause death to the target leopard catfish is searched and output, so that the target leopard catfish is in an anesthetized state;

[0096] Tail fin tissue of the target leopard catfish in the anesthetized state is cut, and target leopard catfish tail fin tissue is obtained, and the target leopard catfish tail fin tissue is placed in a centrifuge tube, a lysis buffer is added to the centrifuge tube, and the target leopard catfish tail fin tissue is subjected to water bath treatment in the centrifuge tube.

[0097] After water bath treatment, the lysis leopard catfish tail fin tissue is obtained, the volume of the lysis leopard catfish tail fin tissue is determined, and an equal volume of isopropyl alcohol is added to the centrifuge tube for impurity removal, and the supernatant of the lysis leopard catfish tail fin tissue is obtained.

[0098] Isopropyl alcohol is added to the supernatant of the lysis leopard catfish tail fin tissue, and centrifugal treatment is performed in the centrifuge tube, and the precipitate is collected, wherein the precipitate is the DNA precipitate of the leopard catfish.

[0099] The precipitate is washed by ethanol, and the washed precipitate is dried to obtain dry precipitate, and the dry precipitate is dissolved in TE buffer, and the concentration of the dry precipitate in the TE buffer is monitored by a spectrophotometer to obtain the DNA concentration of the target leopard catfish.

[0100] In combination with the DNA concentration of the target leopard catfish, a resequencing library is constructed.

[0101] It should be noted that the leopard catfish needs to be anesthetized before DNA extraction, and non-lethal anesthesia is required during the anesthesia process, so as to ensure the activity of the leopard catfish and facilitate the pan-genomic typing. The tail fin tissue of the target leopard catfish is cut for pretreatment, and the target is to fully lyse it in a low-cost lysis buffer. After lysis by the lysis buffer, isopropyl alcohol and isopropyl alcohol are added to the centrifuge tube for a period of time, and the precipitate is collected. The precipitate is the DNA precipitate, and the DNA low-cost sampling purpose can be achieved by washing and dissolving the precipitate. The precipitate is washed by ethanol, and finally the DNA concentration is checked by a spectrophotometer.

[0102] Further, in one preferred embodiment of the present application, in combination with the DNA concentration of the target leopard catfish, a resequencing library is constructed, specifically:

[0103] The dry precipitate is subjected to cyclic ultrasonic fragmentation treatment by a focused ultrasound instrument, and the standard treatment time for cyclic ultrasonic fragmentation is determined according to the DNA concentration of the target Plectrypops leopardus.

[0104] When the time for cyclic ultrasonic fragmentation treatment is equal to the standard treatment time for cyclic ultrasonic fragmentation, the cyclic ultrasonic fragmentation treatment of the dry precipitate is stopped, and the DNA fragments of the Plectrypops leopardus to be treated are obtained.

[0105] The DNA fragments of the Plectrypops leopardus to be treated are subjected to exponential amplification, and the DNA fragments of the Plectrypops leopardus to be treated are subjected to magnetic bead double-screen purification treatment after exponential amplification, wherein the magnetic bead double-screen purification treatment is to add magnetic beads for removing DNA fragments of the Plectrypops leopardus to be treated with a size greater than a predetermined value, and the target magnetic beads are calibrated, and the DNA fragments of the Plectrypops leopardus to be treated with a size maintained within the predetermined value are retained by the target magnetic beads, and the target DNA fragments of the Plectrypops leopardus are obtained.

[0106] Based on the target DNA fragments of the Plectrypops leopardus, and in combination with the DNA concentration of the target Plectrypops leopardus, a resequencing library is constructed, which is a double-strategy library including high-depth group DNA data and low-depth group DNA data.

[0107] The resequencing library construction method is to introduce a DNA sample blank library into a big data network, and to import the target DNA fragments of the Plectrypops leopardus and the DNA concentration of the target Plectrypops leopardus into the DNA sample blank library, and to classify the library according to the size of the target DNA fragments of the Plectrypops leopardus and the corresponding concentration, and to obtain the resequencing library.

[0108] The difference between the high-depth group DNA data and the low-depth group DNA data is that the fragment size and the fragment concentration of the target DNA fragments of the Plectrypops leopardus in different libraries are different.

[0109] It should be noted that before the construction of the re-sequencing library, the dry precipitate needs to be subjected to ultrasonic fragmentation treatment, and the time for ultrasonic fragmentation treatment is different for different concentrations. After obtaining the DNA fragments of the Ptereleotris lunulata to be treated, in order to ensure the enrichment of the library, that is, to enrich the diversity of DNA data in the library, the DNA fragments of the Ptereleotris lunulata to be treated need to be subjected to exponential amplification, and after the exponential amplification, the DNA fragments of the Ptereleotris lunulata to be treated are subjected to magnetic bead double-screen purification treatment. The magnetic bead double-screen spring flower includes first purification and secondary screening. The first purification is to add magnetic beads to remove DNA data with a fragment size greater than a predetermined value. The secondary screening is to recover the target fragments from the supernatant, that is, to recover the DNA fragments of the Ptereleotris lunulata to be treated with a fragment size maintained within a predetermined value, to obtain target DNA fragments of the Ptereleotris lunulata. Finally, the target DNA fragments of the Ptereleotris lunulata and the DNA concentration of the target Ptereleotris lunulata are combined to construct a re-sequencing library, which is used for the following Ptereleotris lunulata pan-genome typing.

[0110] As shown in Figure 3 The second aspect of the present application also provides a Ptereleotris lunulata pan-genome typing system based on low-cost DNA extraction, which comprises a memory 31 and a processor 32. The memory 31 stores a Ptereleotris lunulata pan-genome typing method. When the Ptereleotris lunulata pan-genome typing method is executed by the processor 32, the following steps are implemented:

[0111] DNA sampling and extraction are performed on the Ptereleotris lunulata, and a re-sequencing library is constructed based on the DNA data obtained by sampling;

[0112] A haplotype DNA database is constructed from the DNA data in the high-depth group in the re-sequencing library, and after the construction of the haplotype database, the DNA data in the low-depth group is subjected to genotype filling to obtain a target haplotype DNA database;

[0113] Based on the target haplotype DNA database, the Ptereleotris lunulata is subjected to pan-genome IBD cluster typing processing, and the cluster characteristics are labeled;

[0114] Based on the pan-genome IBD cluster typing processing result of the target Ptereleotris lunulata, an individual-level report of the target Ptereleotris lunulata is generated, and the target Ptereleotris lunulata is subjected to re-sequencing to verify the consistency of the typing.

[0115] The above is only a specific embodiment of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art can easily think of changes or replacements within the technical scope disclosed by the present application, which should be covered within the protection scope of the present application. Therefore, the protection scope of the present application should be subject to the protection scope of the claims.

Claims

1. A method for genotyping of the Ptereleotris heteroptera metagenome based on low-cost DNA extraction, characterized by, The method comprises the following steps: DNA sampling and extraction are performed on the leopard bristletooth, and a resequencing library is constructed based on the obtained DNA data; A haplotype DNA database is constructed based on the high-depth group of DNA data in the resequencing library, and genotype filling is performed on the low-depth group of DNA data after the construction of the haplotype database to obtain a target haplotype DNA database; Based on the target haplotype DNA database, the target leopard bristletooth is subjected to pan-genomic IBD cluster typing processing and cluster characteristics are labeled; An individual-level report of the target leopard bristletooth is generated based on the pan-genomic IBD cluster typing processing result of the target leopard bristletooth, and the target leopard bristletooth is resequenced to verify the consistency of the typing.

2. The low-cost DNA extraction based Ctenochaetus strigosus pan-genomic genotyping method according to claim 1, characterized in that, The DNA sampling and extraction are performed on the leopard bristletooth, and a resequencing library is constructed based on the obtained DNA data, specifically as follows: A leopard bristletooth requiring DNA extraction is obtained, and is designated as a target leopard bristletooth. The target leopard bristletooth is introduced into a big data network, and a drug capable of anesthetizing the target leopard bristletooth is searched in the big data network. The dosage of the drug is searched, which will not cause death of the target leopard bristletooth, and is outputted, so that the target leopard bristletooth is in an anesthetized state. Tail fin tissue of the target leopard bristletooth is cut off, and the tail fin tissue of the target leopard bristletooth is obtained. The tail fin tissue of the target leopard bristletooth is placed in a centrifuge tube, a lysis buffer is added into the centrifuge tube, and the tail fin tissue of the target leopard bristletooth is subjected to water bath treatment in the centrifuge tube. After the water bath treatment, the tail fin tissue of the leopard bristletooth is lysed, the volume of the lysed tail fin tissue of the leopard bristletooth is determined, and an equal volume of isopropyl alcohol is added into the centrifuge tube for impurity removal, so that supernatant of the lysed tail fin tissue of the leopard bristletooth is obtained. Isopropyl alcohol is added into the supernatant of the lysed tail fin tissue of the leopard bristletooth, and centrifugal treatment is performed in the centrifuge tube. The precipitate is collected, wherein the precipitate is DNA precipitate of the leopard bristletooth. The precipitate is washed by ethanol, and the washed precipitate is subjected to drying treatment to obtain dried precipitate. The dried precipitate is dissolved in a TE buffer, and the concentration of the dried precipitate in the TE buffer is monitored by a spectrophotometer to obtain the DNA concentration of the target leopard bristletooth. The resequencing library is constructed based on the DNA concentration of the target leopard bristletooth.

3. The low-cost DNA extraction based C. leopardus pan-genomic genotyping method according to claim 2, characterized in that, The resequencing library is constructed based on the DNA concentration of the target leopard bristletooth, specifically as follows: The dried precipitate is subjected to cyclic ultrasonic fragmentation treatment by a focused ultrasonic instrument, and the standard time of the cyclic ultrasonic fragmentation treatment is determined based on the DNA concentration of the target leopard bristletooth. When the time of the cyclic ultrasonic fragmentation treatment is equal to the standard time of the cyclic ultrasonic fragmentation treatment, the cyclic ultrasonic fragmentation treatment of the dried precipitate is stopped, and DNA fragments of the leopard bristletooth to be treated are obtained. Exponentially amplify the DNA fragments of the to-be-processed Cephalopholis leopardus, and perform magnetic bead double-screen purification treatment on the DNA fragments of the to-be-processed Cephalopholis leopardus after the exponential amplification, wherein the magnetic bead double-screen purification treatment is that magnetic beads for removing DNA fragments with a size greater than a predetermined value in the DNA fragments of the to-be-processed Cephalopholis leopardus are added, the magnetic beads are calibrated as target magnetic beads, and the DNA fragments of the to-be-processed Cephalopholis leopardus with a size maintained within the predetermined value are retained through the target magnetic beads to obtain target DNA fragments of the Cephalopholis leopardus; Based on the target DNA fragments of the Cephalopholis leopardus and in combination with the DNA concentration of the target Cephalopholis leopardus, a resequencing library is constructed, and the resequencing library is a double-strategy library including high-depth group DNA data and low-depth group DNA data; The resequencing library is constructed by introducing a DNA sample blank library into a big data network, and introducing the target DNA fragments of the Cephalopholis leopardus and the DNA concentration of the target Cephalopholis leopardus into the DNA sample blank library, and classifying the library according to the size of the target DNA fragments of the Cephalopholis leopardus and the corresponding concentration size to obtain the resequencing library. The high-depth group DNA data and the low-depth group DNA data are different in that the sizes and concentrations of the target DNA fragments of the Cephalopholis leopardus in different libraries are different.

4. The low-cost DNA extraction based leopard grouper pan-genome typing method according to claim 1, characterized in that, The high-depth group DNA data in the resequencing library is used to construct a haplotype DNA database, and the low-depth group DNA data is used to fill in genotypes after the construction of the haplotype database to obtain a target haplotype DNA database, specifically as follows: In the resequencing library, the high-depth group DNA data is calibrated as high-depth DNA data, and the low-depth group DNA data is calibrated as low-depth DNA data. Based on a big data network, a reference genome of the Cephalopholis leopardus is searched, and the high-depth DNA data is compared with the reference genome of the Cephalopholis leopardus to output a DNA sequence alignment file. Based on the DNA sequence alignment file, all high-depth DNA data is screened for variation sites to determine high-depth DNA data with variation sites, and all high-depth DNA data with variation sites is combined for variation information. Based on the combined variation information of the high-depth DNA data, all high-depth DNA data is filtered to obtain qualified high-depth DNA data. The qualified high-depth DNA data is input into Shapet software for Markov chain Monte Carlo iteration optimization, wherein the Markov chain Monte Carlo iteration optimization is to determine the haplotype linkage relationship of different chromosomes of the qualified high-depth DNA data to obtain a phased result of the qualified high-depth DNA data. Based on the phased result of the qualified high-depth DNA data, the qualified high-depth DNA data is integrated to obtain a haplotype DNA database, and the low-depth DNA data is introduced into the haplotype DNA database for sample alignment. Calculate the similarity between the low-depth DNA data and the aligned qualified high-depth DNA data, and if the similarity is greater than a preset value, replace the low-depth DNA data directly with the corresponding qualified high-depth DNA data; If the similarity is not greater than the preset value, calculate the missing genotype of the low-depth DNA data compared with the aligned qualified high-depth DNA data, fill in the low-depth DNA data, and iteratively optimize, output the optimized haplotype DNA database, and label it as the target haplotype DNA database.

5. The low-cost DNA extraction based leopard grouper pan-genomic genotyping method according to claim 1, characterized in that, Based on the target haplotype DNA database, the target leopard pufferfish is subjected to pan-genomic IBD cluster typing processing and cluster characteristics are labeled, specifically: IBIS software is introduced, IBIS software is connected with target haplotype DNA database, and through IBIS software, homologous fragment monitoring is carried out on the filled genotype data in target haplotype DNA database; Among them, the filled genotype data in the target haplotype DNA database includes qualified high-depth DNA data and iteratively optimized low-depth DNA data; Determine the homologous fragments shared between the filled genotype data, and label them as IBD fragments. In the IBIS software, based on the total length and number of IBD fragments, an IBD fragment sharing matrix is constructed. In the IBD fragment sharing matrix, the IBD fragments are classified by hierarchical classification method; Among them, the hierarchical classification method is to convert the IBD fragment sharing matrix into a genetic distance matrix, and in the genetic distance matrix, the closest IBD fragments are iteratively combined, each combination obtains a new cluster IBD fragment, and the average distance between different cluster IBD fragments is updated in real time during the iteration and combination process; According to the average distance between the cluster IBD fragments, the distance variance rate between the cluster IBD fragments is calculated in real time, and the variance rate curve is drawn. Analyze the variance rate curve, and when the variance rate curve is greater than the standard rate of decline, select the corresponding point in the variance rate curve as the inflection point, and determine the optimal cluster number of IBD fragments based on the inflection point, and label it as the target cluster number; Obtain the allele frequency spectrum of different cluster IBD fragments, which is used to compare the SNP sites of different cluster IBD fragments, and determine the genomic function of different cluster IBD fragments according to the differences of the SNP sites of the cluster IBD fragments; Based on the genomic function of different cluster IBD fragments, the cluster characteristics of different cluster IBD fragments are labeled, and the cluster characteristics of different cluster IBD fragments represent the cluster characteristics of the target leopard pufferfish.

6. The low-cost DNA extraction based leopard grouper pan-genomic genotyping method according to claim 1, characterized in that, The individual-level report of the target leopard pufferfish is generated by combining the pan-genomic IBD cluster typing processing result of the target leopard pufferfish, and the target leopard pufferfish is resequenced to verify the consistency of the typing, specifically: According to the cluster characteristics of the target leopard grouper, the genomic function of the corresponding cluster IBD fragment, and the filled genotype data of the target leopard grouper in the target haplotype DNA database, an individual-level report of the target leopard grouper is generated; A commercial kit is obtained, and DNA sample extraction is performed on the target leopard grouper through the commercial kit, and resequencing processing is performed after the DNA sample extraction; The resequencing processing is used to verify the pan-genome IBD cluster typing processing result of the target leopard grouper; If the similarity between the cluster characteristics of the target leopard grouper obtained by the resequencing processing and the cluster characteristics of the target leopard grouper obtained by the pan-genome IBD cluster typing processing is greater than a preset value, the individual-level report of the target leopard grouper is divided into qualified; Otherwise, the target leopard grouper is subjected to secondary pan-genome IBD cluster typing processing.

7. A leopard coral grouper pan-genomic typing system based on low-cost DNA extraction, characterized by, The leopard grouper pan-genome typing system comprises a memory and a processor, and the memory stores a leopard grouper pan-genome typing method program. When the leopard grouper pan-genome typing method program is executed by the processor, the leopard grouper pan-genome typing method steps of any one of claims 1-6 are implemented.

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