A quality control program analysis method for third-generation sequencing

Abstract

The present invention provides a quality control analysis method for third-generation sequencing, which includes performing raw sequencing on the extracted gene sequence to obtain a POD5 text of the initial data. The POD5 text is then converted into a FASTQ file, and adapter data is removed. Quality assessment is then performed to obtain read data. The read data is then aligned and analyzed with the target base sequence of theoretical length, impurities are filtered, and finally, visual detection results are obtained. The present invention also provides a gene extraction method, which forms a highly optimized and reliable bioinformatics analysis process from raw data acquisition, preprocessing, quality assessment, alignment analysis, to final report generation.

Description

Technical Field

[0001] The present invention relates to the field of computer processing technology, and in particular to a quality control program analysis method for third-generation sequencing. Background Art

[0002] Adeno-associated virus (AAV) vectors are single-stranded, non-enveloped DNA vectors belonging to the helper virus-dependent parvovirus B19 family. AAV replication in a host requires the assistance of host cells or other viruses, such as adenoviruses and herpes viruses, hence the name adeno-associated virus. The AAV genome is a linear, single-stranded, positive- or negative-strand DNA sequence approximately 4,700 nucleotides in length. The AAV genome contains two open reading frames, rep and cap, flanked by terminal repeats (ITRs).

[0003] Wild-type adeno-associated viruses exist naturally, but experimental AAV vectors are artificially modified plasmids based on wild-type adeno-associated viruses, hence the name recombinant adeno-associated virus (rAAV). Unless otherwise specified, the abbreviation AAV generally refers to modified AAV vectors. RAVs are widely used in biology for gene delivery and direct production of plasmid DNA vaccines. They also serve as the basis for packaging viral vectors in gene and cell therapies. Therefore, accurate plasmid sequencing is essential for producing high-quality viral vectors and other clinical therapeutic products.

[0004] Sanger sequencing, also known as first-generation sequencing technology, serves as the gold standard for sequencing and has driven the creation of a "working map" of the human genome. However, Sanger sequencing relies on pure consensus sequence templates and cannot simultaneously sequence and quantify mixed sequences. Therefore, it is not suitable for high-throughput, large-scale sequencing, nor can it quantitatively analyze each sequence in a mixed sequence. The low throughput and high cost of Sanger sequencing have limited its further large-scale application. With the rise of next-generation high-throughput sequencing technology, also known as second-generation sequencing technology, it has been widely used in basic research and clinical diagnosis and treatment due to its high throughput and low cost. Although second-generation sequencing effectively solves the problem of high-throughput simultaneous sequencing and quantitative analysis of mixed sequences, its read length is short (tens to hundreds of bases). A single read length often cannot cover the length of a single sequence in the sample. Multiple read sequences need to be spliced ​​together to obtain a longer complete sequence. Therefore, second-generation sequencing cannot directly quantify complete long sequences. However, the length quality control requirements of rAAV require accurate quantitative assessment of DNA sequences of different lengths that may exist in rAAV. This requires a high-throughput sequencing method with a read length that can cover sequences of different lengths in the sample at one time. With the emergence of third-generation sequencing technology, due to its long read length advantage, it provides a new technical means for the analysis of complex repetitive regions in gene sequences, full-length sequencing and accurate quantification of long fragment sequences, and high-quality genome assembly.

[0005] In recent years, third-generation sequencing technology has further developed and improved, and its clinical application value has gradually been demonstrated in related fields such as oncology, immunology, and reproduction. However, AAV genome sequencing generally uses fragmentation followed by PCR amplification to construct libraries, and conventional AAV genome extraction methods result in low-quality and poorly intact DNA sample fragments (Kung SN, TranNT, Manokaran S, He R, et al. Direct ITR-to-ITR Nanopore Sequencing of AAV Vector Genomes. Hum Gene Ther. 2022 Nov;33(21-22):1187-1196.). During the sequencing process, due to random factors such as base forward speed, base calls with short intervals are prone to miss or premature sequencing termination, leading to systematic errors in subsequent analysis and limiting the value of nanopore sequencing results. Therefore, optimizing detection systems and developing analysis algorithms to correct nanopore sequencing results are very meaningful research directions. Summary of the Invention

[0006] Third-generation sequencing is used in a variety of applications for single-molecule long sequence sequencing. During the sequencing process, due to the randomness of the base forward speed, base recognition is easily missed or sequencing is terminated prematurely when the interval is too short, resulting in systematic errors in subsequent analysis and limiting the value of nanopore sequencing results. The inventors of the present invention have invented a simple and efficient quality control program analysis method for third-generation sequencing. Specifically, referring to Figure 1 , including the following steps:

[0007] S1a: The extracted gene sequence is sequenced to obtain the POD5 text of the initial data.

[0008] The present invention obtains data by directly reading the full-length DNA sequence. Any relatively complete double-stranded DNA sequence can be subjected to data analysis using the method provided by the present invention. In some embodiments, DNA or RNA samples are sequenced primarily using a Nanopore device, and the collected data is typically in a long-read format, which has a high base error rate but can cover complex regions of the genome, such as repetitive sequences. The initial format of the data is POD5 text, which is the file format used by Oxford Nanopore to store raw current signals. The data contains unprocessed sequencing information, including the Q (Qualities) value of the DNA. The Q value is a standard indicator used to assess the accuracy of base reading during the sequencing process, with a higher score indicating better base quality. Without limitation, data read out by other third-generation sequencing devices that can read double-stranded DNA sequences can also be analyzed using the quality control program analysis method provided by the present invention.

[0009] In some embodiments, the third-generation sequencing is third-generation sequencing of rAAV, and the extracted genes are genes of rAAV.

[0010] S2a: Preprocess the initial data, convert the POD5 text into a FASTQ file, and remove the adapter data to obtain the second data.

[0011] This processing step is fundamental to ensuring data purity and high quality. FASTQ files are a commonly used data format for bioinformatics analysis, containing the base sequence of sequencing reads and the quality score of each base. Specific tasks in this preprocessing step include:

[0012] Adapter Removal: Adapters are non-biological sequences added during the sequencing process to guide the sequencing process. These redundant adapter sequences must be removed before analysis to ensure that analysis is based solely on the biological sequence of the sample.

[0013] Data format conversion: Convert raw sequencing data from POD5 text format to FASTQ format to facilitate subsequent analysis using other tools.

[0014] In some embodiments, Dorado is selected to process the initial data and obtain the second data. Dorado is a data processing tool officially recommended by Oxford Nanopore, which is mainly used to convert POD5 format files into the standard FASTQ format.

[0015] S3a: Perform quality assessment on the second data to obtain clean, non-redundant Reads data.

[0016] In some embodiments, NanoPlot is used to perform a quality assessment on the second data. NanoPlot is a quality assessment and visualization tool for long-read sequencing data from sources such as Oxford Nanopore and PacBio. Its primary function is to generate visual charts that allow researchers to quickly assess the quality of a dataset. It is currently widely used as a standard quality assessment software. Charts generated by NanoPlot include:

[0017] Read Length Distribution: This graph shows the length distribution of each read. Researchers can use this graph to understand whether the lengths of reads in a dataset are within the expected range and whether there are abnormally short or long reads.

[0018] Quality score distribution graph: Generates a Q-value quality score distribution graph to evaluate the overall quality of reads.

[0019] Other visualizations: NanoPlot can also generate a variety of charts such as base composition, quality score variation with position, and correlation between read length and quality score.

[0020] Through these charts, researchers can quickly identify potential problems in the data, such as low-quality reads or abnormal length distribution, so as to adjust subsequent analysis strategies in a timely manner.

[0021] S4a: Compare and analyze the reads data with the target base sequence of theoretical length to obtain the first statistical result.

[0022] In some embodiments, Minimap2 is used to align filtered reads with the theoretical length of the target base sequence. Minimap2 is a sequence alignment tool designed specifically for processing long-read data. Unlike traditional short-read alignment tools, Minimap2 offers higher speed and accuracy when processing long reads, making it particularly suitable for Nanopore and PacBio sequencing data. Its core features include:

[0023] Whole-genome alignment: Minimap2 efficiently aligns long reads to a reference genome, generating alignment results in SAM / BAM file formats. These results include not only the mapping positions of the reads to the reference genome, but also detailed information such as alignment quality and mismatches at each site.

[0024] Variant Detection: Because long-read data can cover longer genomic regions, Minimap2 is well-suited for detecting complex genomic structural variations (SVs), such as large-scale insertions, deletions, and inversions. These variants are difficult to identify with short-read data, and the wider coverage of long-read data makes Minimap2 perform well in variant detection.

[0025] Molecular Biology Research Support: Minimap2's alignment results can be used not only for genome reconstruction but also for RNA-seq, transcriptome analysis, and other fields. For diverse biological research, Minimap2 provides a reliable and efficient alignment solution.

[0026] In addition, Minimap2 has adjustable parameters that allow researchers to adjust the accuracy and speed of the alignment according to specific needs.

[0027] S5a: Based on the first statistical result, the second data is further screened to filter out impurities to obtain pure third data.

[0028] In some embodiments, the impurities are long sequences greater than 10,000 bp, short sequences less than 500 bp, and low-quality sequences with a Q value less than 10, and the pure third data are data of sequences with a length within 500-10,000 bp and a Q value greater than or equal to 10.

[0029] Quality (Q) is an important indicator for measuring the accuracy of read alignment to the reference genome. Generally, a Q ≥ 10 is considered a highly reliable alignment. In this step, high-quality reads are screened and only those with Q ≥ 10 are retained. This ensures that subsequent analysis is based on high-quality data and minimizes the impact of low-quality alignments on the analysis.

[0030] The present invention uses the conventional value 10 as the critical value of Q to judge the quality of the detection fragment. However, in some embodiments, other values ​​can be selected as the critical value to judge the quality of the detection fragment according to actual needs, such as 8, 9, 11, 12, 13, etc.

[0031] In some embodiments, Nanofilt is used for filtering. Nanofilt is a filtering tool for Nanopore data that allows researchers to filter reads based on multiple dimensions, such as quality score, length, and GC content. Nanofilt can filter out short or low-quality reads, ensuring that the remaining data meets the needs of subsequent analysis.

[0032] This step provides a high-quality, reliable data set for subsequent analysis, thereby improving the accuracy and stability of the final analysis results.

[0033] S6a: Perform sequence length and sequence alignment analysis on the clean third data to obtain a detection result.

[0034] This stage involves further detailed analysis of the filtered reads. In some implementations, a combination of NanoPlot, Minimap2, and Pysamstats is used. The specific functions of each tool are as follows:

[0035] NanoPlot: Used to visualize indicators such as read length distribution and quality score, providing a reference for sequence length analysis.

[0036] Minimap2: In this step, the Minimap2 alignment results obtained in the previous step will be used for further genome annotation, variation analysis, and other tasks. Its alignment information not only provides read mapping locations but also assists in studies such as gene expression and structural variation detection.

[0037] Pysamstats: A Python-based SAM / BAM file analysis tool that can extract detailed statistical information about alignment data. Its features include:

[0038] 1) Coverage analysis of each site: Counting how many reads cover each site helps researchers determine the coverage of the genome.

[0039] 2) Mutation frequency statistics: Pysamstats can calculate the frequency of mismatched bases, helping researchers identify potential mutation sites.

[0040] 3) Insertion / deletion analysis: It can also detect insertion or deletion events that occur during sequencing and help analyze the structural characteristics of reads.

[0041] The combination of these tools provides researchers with a detailed analysis of data characteristics, helping to conduct in-depth quality control and characteristic analysis of data from multiple perspectives.

[0042] The present invention also provides a method for rAAV third-generation sequencing, comprising:

[0043] S1c: Extract gene sequence.

[0044] S2c: Use any of the third-generation sequencing data processing methods described above to read and process the gene sequence to obtain the detection results.

[0045] In some embodiments, the third-generation sequencing is third-generation sequencing of rAAV, and the extracted genes are genes of rAAV.

[0046] The present invention also provides a method for extracting rAAV genes for third-generation sequencing, comprising the following steps:

[0047] S1c: The purified rAAV virus was disrupted with proteinase K to obtain the initial reaction solution.

[0048] rAAV consists of an icosahedral protein capsid with a diameter of approximately 26 nm and a single-stranded DNA genome. The rAAV protein capsid is digested and broken by proteinase K to obtain an initial reaction solution containing the single-stranded DNA genome.

[0049] S2c: The initial reaction solution is subjected to alkaline denaturation, neutralized, purified using a DNA product purification kit, and then eluted with nuclease-free water to obtain denatured viral genomic DNA.

[0050] The AAV genome consists of a single strand, either positive or negative, containing inverted terminal repeats (ITRs) at each end of the DNA strand. Alkaline denaturation effectively unravels the complementary secondary structures of the ITRs, denaturing them into pure single strands. During subsequent annealing, the positive and negative strands can form effective double-stranded ends, facilitating the addition of sequencing adapters and assembly of the motor protein required for nanopore sequencing during library construction. In some embodiments, the alkaline denaturation involves sodium hydroxide denaturation. In some embodiments, ammonium acetate is used for neutralization after denaturation.

[0051] S3c: Incubate and anneal the denatured viral genomic DNA to eventually form double-stranded DNA.

[0052] The positive or negative strands of the AAV genome can be complementary. After the alkaline denaturation step, the positive or negative strand has been denatured into a pure single strand. After incubation and annealing, double-stranded DNA is finally formed. In some embodiments, the incubation temperature is 45-70°C. Specifically, the temperature can be 45, 50, 55, 60, 65, or 70°C. In some embodiments, the incubation time is 1 hour.

[0053] Compared with traditional AAV genome extraction methods, the method provided by the present invention is simpler and more efficient, and the extracted DNA has higher integrity.

[0054] Furthermore, the method also includes denoising the test results, that is, by setting a positive control to detect noise, and then removing the noise of the test results with reference to the noise detected by the positive control, thereby obtaining a corrected result. In some embodiments, the positive control is a 5' ITR-target sequence-3' ITR linearized fragment obtained after enzyme digestion of the vector plasmid. The positive controls are all complete DNA sequences, and the signals of the incomplete sequences that appear during the detection process are the background noise of the instrument or detection system itself. The background noise of the positive control and the object to be detected should be basically the same under the same environment. With reference to the background noise detected by the positive control, the noise of the object to be detected is filtered out, thereby obtaining a purer test result.

[0055] After the above steps, researchers can generate a quality control report containing information from multiple dimensions. The report will include:

[0056] 1) Read length distribution and quality score of the dataset.

[0057] 2) Statistics of coverage and mutation frequency of each site.

[0058] 3) Visual display of sequence length and alignment quality.

[0059] By interpreting the report, researchers can better understand the characteristics of sample data, providing support for subsequent biological analysis or experimental validation. The entire process, from raw data acquisition, preprocessing, quality assessment, alignment analysis, to final report generation, forms a highly optimized and reliable bioinformatics analysis pipeline. NanoPlot provides convenient quality control and visualization tools, Minimap2 excels in long-read data processing with its fast and accurate alignment capabilities, and Pysamstats provides powerful support for detailed statistical analysis after alignment. This combination of tools makes the entire analysis process both efficient and robust, suitable for complex bioinformatics problems and the processing of long-read data.

[0060] The present invention also provides a computer program product, which may be a software comprising one or more stored instruction sequences, which are accessible to a processor and, when executed by the processor, cause the processor to implement the steps of any of the above-described sequencing methods.

[0061] In some embodiments, a computer program product includes: a first unit, a second unit, a third unit, a fourth unit, a fifth unit, and a sixth unit, wherein:

[0062] The first unit can be used to perform third-generation sequencing on the gene sequence of rAAV and generate POD5 sequencing data after sequencing on the machine;

[0063] The second unit is used for initial filtering and data conversion, which can filter the Adapter data and convert the POD5 text into FASTQ files;

[0064] The third unit can perform quality assessment on the data of FASTQ files and obtain the data of Reads distribution;

[0065] In the fourth unit, the reads data can be compared with the theoretical reference sequence;

[0066] The fifth unit can be used for data classification and screening, and screen out abnormal data and data that do not meet quality requirements based on the comparison analysis results. In some embodiments, data that do not meet quality requirements are fragments with a Q value less than 10;

[0067] The sixth unit can perform sequence length analysis and sequence alignment analysis on the filtered data and output the final results.

[0068] The present invention also provides a computer-readable medium carrying one or more instruction sequences of the computer program product.

[0069] Unless expressly stated otherwise, it should be understood that throughout this specification, discussions using terms such as "compute," "calculate," "generate," or similar terms refer to the actions and / or processes of a computer or computing system or similar electronic computing device that manipulate data represented as physical (e.g., electronic) quantities within the computing system's registers and / or memories and / or transform them into other data similarly represented as physical quantities within the computing system's memories, registers, or other such information storage, transmission, or display devices.

[0070] Embodiments of the present invention may include apparatus for performing the operations described herein. This apparatus may be specially constructed for the desired purpose, or the apparatus may include a general-purpose computer or a digital signal processor (DSP) selectively activated or reconfigured by a computer program stored in the computer. Such a computer program may be stored on a computer-readable storage medium, such as, but not limited to, any type of disk, including a floppy disk, an optical disk, a CD-ROM, a magneto-optical disk, a read-only memory (ROM), a random access memory (RAM), an electrically programmable read-only memory (EPROM), an electrically erasable programmable read-only memory (EEPROM), a magnetic or optical card, or any other type of medium suitable for storing electronic instructions and capable of being coupled to a computer system bus.

[0071] The process and display mode proposed herein are not originally relevant to any specific computer or other equipment. Various general-purpose systems can be used together with the program according to the teaching herein, or it can prove to be very easy to build a more specialized device to perform the desired method. The desired structure of various these systems will be understood from the above description. In addition, embodiments of the present invention are not described with reference to any specific programming language. It will be appreciated that various programming languages ​​can be used to realize the teaching of the present invention as described herein. BRIEF DESCRIPTION OF THE DRAWINGS

[0072] In order to better understand the present invention and more clearly show how to implement the present invention, the features of the solution implemented according to the present invention are now described by way of example with reference to the accompanying drawings, in which:

[0073] Figure 1 : Flowchart of analytical methods for quality control procedures.

[0074] Figure 2 : Capillary electrophoresis detection of extracted genomic DNA integrity.

[0075] Figure 3 : Capillary electrophoresis detection of genomic DNA integrity after step optimization.

[0076] Figure 4 : NanoPlot analysis results: A: Length distribution plot, the horizontal axis represents the corresponding base sequence length of the Reads sequence, and the vertical axis represents the number of reads in the corresponding sequence length interval; B: Weighted length distribution plot: the horizontal axis represents the corresponding base sequence length of the Reads sequence, and the vertical axis represents the number of bases in the corresponding sequence length interval; C: Logarithmically transformed length distribution plot; D: Logarithmically transformed weighted length distribution plot.

[0077] Figure 5 : Analysis results of the Virus_QC quality control length distribution ratio of AAV genome DNA third-generation sequencing.

[0078] Figure 6 : Capillary electrophoresis detection of rAAV genomic DNA treated with different annealing conditions.

[0079] Figure 7 : Capillary electrophoresis detection of genomic DNA integrity after further optimization of the steps.

[0080] Figure 8 : Pie chart showing the proportion of Virus_QC quality control alignment reads for AAV genome DNA third-generation sequencing.

[0081] Figure 9: Pie chart showing the proportion of base numbers in Virus_QC quality control alignment of AAV genome DNA in third-generation sequencing.

[0082] Figure 10 : Analysis results of the length distribution ratio of Virus_QC quality control positive controls in the third-generation sequencing of AAV genome DNA.

[0083] Figure 11 : Analysis results of the length distribution ratio of the tested samples before Virus_QC quality control correction of the third-generation sequencing of AAV genome DNA.

[0084] Figure 12 : Analysis results of the length distribution ratio of the tested samples after Virus_QC quality control correction of the third-generation sequencing of AAV genome DNA.

[0085] Figure 13 : Visual analysis results of Virus_QC quality control sequence alignment of AAV genome DNA third-generation sequencing. DETAILED DESCRIPTION

[0086] definition:

[0087] In order to provide a clear and consistent understanding of the terms used in the specification of the present invention, some definitions are provided below. In addition, unless otherwise specified, all technical and scientific terms used in the present invention have the same meaning as commonly understood by those of ordinary skill in the art to which the present invention belongs.

[0088] When used in conjunction with the term "comprising" in the claims and / or the specification, the use of the word "a" can mean "one", but it is also known in the sense of "one or more", "at least one" and "one or more than one". Similarly, the word "another" can mean at least a second or many.

[0089] As used in this specification and claims, the words "comprising" (and any form of comprising, such as "including" and "comprising"), "having" (and any form of having, "having", "including" and "containing") are inclusive and open-ended and do not exclude additional, unrecited elements or process steps.

[0090] Example:

[0091] The present invention will be more readily understood by reference to the following examples, which are provided to illustrate the invention and are not to be construed as limiting the scope of the invention in any way.

[0092] Unless otherwise defined or the context clearly dictates otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which the invention belongs. It should be understood that any methods and materials similar or equivalent to those described herein can be used in the practice or testing of the present invention.

[0093] Although the present invention has been described in detail with reference to the embodiments of the present invention, these embodiments are provided to illustrate rather than limit the present invention. Other embodiments that can be obtained according to the principles of the present invention all fall within the scope defined by the claims of the present invention.

[0094] Experimental methods not specifically described herein were performed according to the methods in Joseph Sambrook's Molecular Cloning: A Laboratory Manual (Fourth Edition) or in accordance with the instructions of relevant products. Unless otherwise specified, all terms used herein are to be understood according to their ordinary meanings in the art. Unless otherwise specified, the biological reagents and instruments used in this invention are commercially available.

[0095] instrument:

[0096] MinION Mk1B, Oxford Nanopore Technologies;

[0097] Bio-Fragment Analyzer, Qsep1-Plus, C100001-P.

[0098] Material:

[0099] Proteinase K solution (20 mg / ml) was purchased from Sangon Biotech;

[0100] Common DNA product purification kit was purchased from TIANGEN;

[0101] Ligation Sequencing Kit V14, purchased from Oxford Nanopore Technologies;

[0102] The chip FLO-MIN114 R10.4.1 was purchased from Oxford Nanopore Technologies.

[0103] Example 1: rAAV genome extraction

[0104] Purified rAAV virus (10 10AAV viral particles were collected from a 500 μL PBS solution (20 μL / mL Proteinase K, Sangon Biotech) and incubated at 50°C for 1 hour. The solution was denatured with 0.2 N sodium hydroxide (incubated at room temperature for 5 minutes), neutralized with 5 M ammonium acetate, precipitated with ethanol, and eluted with nuclease-free water. The solution was purified using a standard DNA product purification kit (DP204, Tiangen) and resuspended in 1× SSC (0.15 M NaCl + 0.015 M sodium citrate). rAAV DNA was incubated at 70°C for 1 hour and then slowly cooled (1°C / min) to 20°C to denature and anneal the DNA to form double-stranded AAV genomic DNA.

[0105] The AAV genomic DNA obtained by the above experimental steps was tested by capillary electrophoresis. The results are shown in Figure 2 , this test uses a 20 nt marker. The thin arrow indicates the actual length of AAV genomic DNA detected by capillary electrophoresis. The theoretical length of AAV genomic DNA sample is 4493 bp (SEQ ID NO: 1). Figure 2 The test results showed that the AAV genomic DNA obtained in this example had poor integrity.

[0106] Example 2: Optimization of rAAV genome extraction steps

[0107] Purified rAAV virus (10 10 AAV viral particles were collected (400 μL / mL) and 20 μL of 20 mg / mL proteinase K (Sangon Biotech) was added and incubated at 50°C for 1 hour. The cells were then denatured with 0.2 N sodium hydroxide (incubated at room temperature for 5 minutes) and neutralized with 5 M ammonium acetate. Ethanol precipitation and elution with nuclease-free water were omitted and the cells were directly purified using a standard DNA product purification kit (DP204, TIANGEN). The cells were then resuspended in 1× SSC (0.15 M NaCl + 0.015 M sodium citrate). rAAV genomic DNA was incubated at 70°C for 1 hour and then slowly cooled (1°C / min) to 20°C to denature and anneal the double-stranded AAV genomic DNA.

[0108] The AAV genomic DNA obtained by the above experimental steps was tested by capillary electrophoresis. The results are shown in Figure 3 This test uses a 20 bp-5000 bp marker. The thin arrow indicates the actual length of AAV genomic DNA detected by capillary electrophoresis; the theoretical length of AAV genomic DNA sample is 4493 bp. Figure 3 The test results showed that the AAV genomic DNA extracted under these optimized conditions would degrade and the integrity of the genomic DNA was still low.

[0109] Example 3: Analysis Software NanoPlot

[0110] Compared with the second-generation Illumina sequencing data, the third-generation Nanopore sequencing data has the characteristics of longer read length, high error rate, and uneven length distribution. NanoPlot analysis software is a sequence length analysis software provided by Nanopore. It provides a visualization tool that can be used for long-read sequencing data and alignment results. It aims to provide a visual statistical and graphical report on the quality of the sequencing data itself, helping users understand whether the test process is proceeding normally and whether the obtained sequencing data has achieved the expected abundance, accuracy and coverage. It can also be used as a preliminary reference for AAV length quality control. NanoPlot is mainly based on the Linux system command to run. The specific instruction is "NanoPlot - t12 -- fastq . / SQK-NBD114-24_barcode04.fastq.gz -- maxlength 40000 -- plotsdot -- legacy hex". Take the AAV genomic DNA sample in Example 2, and get the analysis results after running NanoPlot. Figure 4 .

[0111] Depend on Figure 4 It can be seen that NanoPlot's length analysis results can only visualize the length distribution of sequenced reads in different length regions. Regardless of whether weight conversion or log transformation is performed, the visualization results cannot display detailed information. They can only serve as a rough quality assessment of the sequencing data itself (rather than a quality control analysis of AAV viral particles). It cannot customize appropriate analysis parameters (such as setting the width of each data bar) based on the specific length and type of AAV viral samples, nor can it use control samples for ratio correction or calculate the ratio of other non-AAV genomic sequences. Because NanoPlot is not specifically designed for the needs of AAV product quality control, its analysis results are overly simplistic, have serious flaws and limitations, are inaccurate, and can be misleading. It cannot be used for accurate assessment of AAV product quality.

[0112] Example 4: Quality Control Program Analysis Software Virus_QC

[0113] A computer software product, Virus_QC, for quality control program analysis includes: a first unit, Nanopore, which sequences DNA or RNA samples using a Nanopore device, collects raw POD5 sequencing data of AAV (adeno-associated virus) viral samples, performs sequencing on the Nanopore device, and performs preliminary collection of sequencing data and comprehensive evaluation of the data format; a second unit, Dorado, which primarily includes operations such as sequencing adapter removal and data format conversion, and is used for initial filtering and data conversion. It can filter adapter data and convert POD5 text into FASTQ files; a third unit, NanoPlot, which can perform quality assessment on the data in the FASTQ files to obtain read distribution data; a fourth unit, Minimap2, which can align and analyze the read data with a theoretical reference sequence; a fifth unit, Nanofilt, which can be used for data classification and screening, filtering out abnormal data and data with a Q < 10 based on the alignment analysis results; and a sixth unit, a combined unit of NanoPlot, Minimap2, and Pysamstats, which can perform sequence length analysis and sequence alignment analysis on the filtered data and output the final results.

[0114] Example 5: Nanopore sequencing library construction and sequencing

[0115] 1 μg of the AAV genomic DNA sample from Example 2 was taken and a library was constructed using the Ligation Sequencing Kit V14 (ONT, SQK-LSK114) from Oxford Nanopore, UK. The constructed library was sequenced on a MinION Mk1B device, using the chip code FLO-MIN114 R10.4.1 and a run time setting of 72 h. The sequencing results were analyzed using the Virus_QC quality control program designed in Example 4. Figure 5 As shown in the figure, the number of reads with a theoretical length of 4493 bp in the AAV genomic DNA sample accounts for only 1.35%, indicating that the degraded AAV genomic DNA during the experiment has a greater impact on the sequencing results.

[0116] Example 6: Effects of different annealing temperatures on double-stranded DNA

[0117] Referring to the steps of Example 2, rAAV purified virus (10 10AAV virus particles), 20 μl 20 mg / ml proteinase K (Sangon Biotech) was added and incubated at 50 ℃ for 1 h. Denatured with 0.2 N sodium hydroxide alkali (incubated at room temperature for 5 min), neutralized with 5 M ammonium acetate, purified using a common DNA product purification kit (DP204, TIANGEN), and resuspended in 1×SSC (0.15 MNaCl + 0.015 M sodium citrate). Six groups of equal amounts of rAAV genomic DNA were selected and annealed as follows: 45 ℃ for 1 h, 50 ℃ for 1 h, 55 ℃ for 1 h, 60 ℃ for 1 h, 65 ℃ for 1 h and 70 ℃ for 1 h, and finally slowly cooled (1 ℃ / min) to 20 ℃. These 6 treated samples were subjected to capillary electrophoresis detection, and the test results are shown in Figure 2. Figure 6 The results showed that the capillary electrophoresis detection results of samples treated with different annealing conditions were consistent, so the annealing temperature did not have a significant impact on the detection results.

[0118] Example 7: Further optimization of rAAV genome extraction steps

[0119] Purified rAAV virus (10 10 AAV virus particles were added to 20 µl of 20 mg / ml proteinase K (Sangon Biotech) and incubated at 50°C for 1 hour. The DNA was denatured with 0.2 N sodium hydroxide (incubated at room temperature for 5 minutes) and neutralized with 5 M ammonium acetate. The DNA was purified using a standard DNA product purification kit (DP204, TIANGEN) and eluted with nuclease-free water. After incubation at 70°C for 1 hour, the DNA was slowly cooled (1°C / min) to 20°C to denature and anneal the DNA to form double-stranded AAV genomic DNA. Capillary electrophoresis was performed and the results were shown in the table below. Figure 7 As shown in the figure, the theoretical length of the AAV genomic DNA sample is 4493 bp. The capillary electrophoresis detection results show that the AAV genomic DNA has good integrity, and the sample DNA peaks are rich and far higher than the 20 bp marker peak.

[0120] Example 8: Detection of rAAV genomic DNA integrity by third-generation sequencing

[0121] The AAV virus sample was subjected to genome extraction and sequencing library construction according to the optimized method in Example 7. Read sequences were obtained after sequencing. The impurity ratio analysis of the AAV genome sequence based on Virus_QC and the minimap2 sequence alignment were performed. The results of the proportion of each read sequence component are shown in Figure 8 and Figure 9, of which the proportion of AAV genome sequences accounts for more than 85%, the packaging plasmid remains in approximately 5%, and there are some other components (such as random connection of adapters generated during library construction, misidentified sequences of the Basecalling algorithm, or residual host cell genome fragments in the sample).

[0122] Example 9: Positive Control Calibration

[0123] Set up a positive control, i.e., a linearized plasmid fragment containing ITRs at both ends (labeled ctr), and process AAV and the positive control (double-stranded DNA fragment of a linearized plasmid containing ITRs at both ends) simultaneously according to the steps of Example 6. The fragment length of the positive control is 3558 bp (SEQ ID NO: 2). Figure 10 As shown in the figure, the sequencing results of the positive control ctr data were good through the length analysis of the Virus_QC quality control program. The detection sequence of the theoretical length of 3558 bp was relatively concentrated, and the proportion distributed in the theoretical length region was 46.09%. This data can be used as a control for sample correction in the actual AAV group to remove short fragments caused by possible accidental interruptions in the sequencing process. Figure 11 As shown in Figure 2, the target sequence length before correction accounts for 51.32%; after correction by the data of the positive control group, as shown in Figure 2 Figure 12 As shown in the figure, the target sequence length accounts for 86.38%, which is a significant improvement compared with before correction.

[0124] Figure 13 This is a visualization of the consistency analysis of the corrected AAV genome sequence. The overall match rate of the AAV genome sequence is approximately 95%, indicating that the genomic DNA sequence of this sample is also highly consistent.

[0125] The present invention provides a third-generation sequencing method that can not only display a length analysis graph corresponding to the target length of the gene sequence, but also display the quality value (Q value) of the read sequence in the target length region, as well as a sequence alignment graph of the target region where the sequence is located with the reference genome sequence. The present invention also provides a concise and efficient method for obtaining complete viral genomic DNA from recombinant adeno-associated virus (rAAV) particles. Researchers can directly measure the complete rAAV gene sequence to better understand the characteristics of the sample data and provide support for subsequent biological analysis or experimental verification. The entire process, from raw data acquisition, preprocessing, quality assessment, alignment analysis to final report generation, forms a highly optimized and reliable bioinformatics analysis process.

[0126] The above-described embodiments merely represent several embodiments of the present invention, and their descriptions are relatively specific and detailed, but they should not be construed as limiting the scope of the present invention. It should be noted that those skilled in the art may make various changes, modifications, and substitutions without departing from the spirit of the present invention, and all of these variations, modifications, and substitutions fall within the scope of protection of the present invention. Therefore, the scope of protection of the present invention shall be determined by the appended claims.

[0127] Although the present invention has been described in detail with reference to the embodiments of the present invention, these embodiments are provided to illustrate rather than limit the present invention. Other embodiments that can be obtained according to the principles of the present invention all fall within the scope defined by the claims of the present invention.

[0128] The sequences mentioned in this article are as follows:

[0129] SEQ ID NO: 1

[0130]

[0131] SEQ ID NO:2

[0132]

Claims

1. A quality control program analysis method for rAAV third-generation sequencing, characterized in that: The method comprises the following steps: S1a: Performing original sequencing on the extracted gene sequence to obtain a POD5 text of the initial data, wherein the extraction of the gene sequence includes: i) using proteinase K to disrupt the purified rAAV virus to obtain an initial reaction solution; ii) subjecting the initial reaction solution to alkaline denaturation, neutralizing it, purifying it using a DNA product purification kit, and then eluting it with nuclease-free water to obtain denatured viral genomic DNA; iii): incubating and annealing the denatured viral genomic DNA to ultimately form double-stranded DNA, wherein the incubation and annealing are performed at a temperature of 45-70° C. for 1 hour; and the extraction of the gene sequence does not include the use of an SSC solution; S2a: Preprocessing the initial data, converting the POD5 text into a FASTQ file using Dorado, and removing the adapter data to obtain the second data; S3a: Use NanoPlot to perform quality assessment on the second data and select reads with a Q value ≥ 10; S4a: performing alignment analysis on the read data and the target base sequence of theoretical length using Minimap2 to obtain a first statistical result; S5a: further screening the second data based on the first statistical result to filter out impurities and obtain pure third data; The impurities are long sequences greater than 10,000 bp, short sequences less than 500 bp, and sequences with a Q value less than 10; The pure third data is data of a sequence with a length of 500-10000 bp and a Q value greater than or equal to 10. S6a: performing sequence length analysis and sequence alignment analysis on the clean third data to obtain a detection result; S7a: Denoising the test results: The denoising step is to detect noise by setting a positive control, and then removing the noise of the test result with reference to the noise of the positive control to obtain a correction result. The positive control is a 5' ITR-target sequence-3' ITR linearized fragment obtained by enzyme digestion of the vector plasmid, as shown in SEQ ID NO: 2, and the positive control is processed under the same sequencing environment as the sample to be tested; S8a: Use NanoPlot, Minimap2, and Pysamstats to analyze the sequence length distribution and mutation frequency of the corrected data and output a quality control report.

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