A method and device for splitting a transcriptome chimera based on third-generation sequencing

Abstract

The present application relates to a kind of based on three generation sequencing transcriptome chimera segmentation method, device, its method includes: obtaining the three generation sequencing data of to be measured transcriptome;Based on reference genome, the alignment analysis of the three generation sequencing data is obtained one or more reads;Multiple fragments in each reads are matched with the gene fragments located at multiple different positions of reference genome;According to whether the multiple different positions of gene fragments matched contain primer sequence, whether each reads is judged as chimeric reads;According to the position of primer sequence in each chimeric reads in reads, determine chimeric site and according to it to the transcriptome data is segmented.The present application uses the position of gene fragment and primer sequence as the criterion of chimeric reads, and can more accurately determine chimeric reads in combination with fuzzy matching, to realize the segmentation of a large number of chimeric reads of transcriptome.

Description

TECHNICAL FIELD

[0001] The application belongs to the technical field of biological information, relates to the field of transcriptome sequencing, and particularly relates to a transcriptome chimera splitting method and device based on third-generation sequencing. BACKGROUND

[0002] Nanopore sequencing is a third-generation sequencing technology developed by Oxford Nanopore Company. The principle is to make the DNA or RNA molecules to be measured pass through a biological membrane with many nanopores, and the two sides of the membrane are provided with a voltage. In the process of the DNA or RNA molecules passing through the nanopores, the current at the nanopore position will change, and the current changes caused by different bases (A, T, C, G) will be different. Therefore, the bases on the molecules to be measured can be identified by identifying the fluctuation trend of the current signal, so as to achieve the purpose of determining the sequence of the DNA or RNA molecules.

[0003] However, in the data of nanopore sequencing, there will be a certain proportion of chimera reads. The reasons for forming the chimera reads are as follows: one is that in the process of PCR amplification of the DNA molecules, due to the non-specific binding of the primers and the DNA templates, different DNA molecules will be incorrectly connected together to become chimeras; and the other reason for forming the chimeras is that after a DNA molecule passes through the nanopore, there is a certain probability that other DNA molecules will immediately pass through the same nanopore, and since the interval between the two DNA molecules passing through the nanopore is too short, the sequencing instrument will read two different DNA molecules into one sequencing read, thus forming the chimera reads.

[0004] The existing genome splitting method uses duplex-tools to split the chimera reads in genome sequencing. However, it cannot split the chimera reads in transcriptome sequencing. The chimera reads contain two or more different DNA molecules on the same read and cannot be directly used for data analysis. It must be split into several independent reads, each of which comes from a unique DNA molecule. Compared with genome sequencing, the DNA molecules to be measured in transcriptome sequencing are shorter and need to undergo a PCR amplification process. Therefore, the proportion of chimera reads in transcriptome sequencing is higher, which can be as high as 40%. Therefore, how to effectively and accurately split the chimera reads in transcriptome sequencing is one of the technical problems to be solved in third-generation sequencing. SUMMARY

[0005] In order to effectively and accurately split the chimeric reads of transcriptome sequencing, in a first aspect of the present application, a method for splitting chimeric reads of transcriptome sequencing based on third-generation sequencing is provided, comprising: obtaining third-generation sequencing data of a transcriptome to be tested; performing alignment analysis on the third-generation sequencing data based on a reference genome to obtain one or more reads; determining whether multiple fragments in each read match gene fragments located at multiple different positions of the reference genome; determining whether each read is a chimeric read according to whether the multiple different positions of the gene fragments matched contain primer sequences within the read fragments corresponding to the multiple different positions of the gene fragments; determining a chimeric site according to the position of the primer sequence of each chimeric read in the read, and splitting the transcriptome data according to the chimeric site.

[0006] In some embodiments of the present application, the determination of whether the multiple fragments in each read match the gene fragments located at the multiple different positions of the reference genome comprises: aligning each read with the reference genome to determine whether the read matches the fragments of multiple genes located at different positions in the reference genome.

[0007] In some embodiments of the present application, the determination of whether each read is a chimeric read according to whether the multiple different positions of the gene fragments matched contain primer sequences within the read fragments corresponding to the multiple different positions of the gene fragments comprises: performing double-sequence alignment of the reference primer sequence with each read based on the edlib local alignment algorithm; if at least one primer sequence is matched, determining that the read is a chimeric read.

[0008] Further, the double-sequence alignment of the reference primer sequence with each read based on the edlib local alignment algorithm comprises: finding the read fragment most similar to the primer sequence in the read under the condition of allowing error matching by the HW mode of the edlib local alignment algorithm.

[0009] Preferably, the condition of allowing error matching comprises fuzzy matching.

[0010] In the above embodiments, the determination of the chimeric site according to the position of the primer sequence of each chimeric read in the read, and the splitting of the transcriptome data according to the chimeric site comprises: determining the position of the primer sequence of one or more chimeric reads according to the multiple different positions of the gene fragments of the reference genome matched by each chimeric read; determining a chimeric site based on the position of the primer sequence of each chimeric read, and splitting the chimeric reads in the transcriptome to be tested into multiple non-chimeric reads according to the chimeric site.

[0011] In a second aspect, the present application provides a device for splitting a transcriptome chimera based on third-generation sequencing, comprising: an acquisition module configured to acquire third-generation sequencing data of a transcriptome to be tested; performing alignment analysis on the third-generation sequencing data based on a reference genome to obtain one or more reads; a first judgment module configured to determine whether a plurality of segments in each read match gene segments located at a plurality of different positions of the reference genome; a second judgment module configured to determine whether each read is a chimeric read according to whether the primer sequence is contained in the read segment corresponding to the plurality of different positions of the gene segments matched; and a splitting module configured to determine a chimeric site according to the position of the primer sequence in each chimeric read and split the transcriptome data according to the chimeric site.

[0012] In a third aspect, the present application provides an electronic device, comprising: one or more processors; and a storage device configured to store one or more programs, when the one or more programs are executed by the one or more processors, the one or more processors implement the method for splitting a transcriptome chimera based on third-generation sequencing provided in the first aspect of the present application.

[0013] In a fourth aspect, the present application provides a computer readable medium having stored thereon a computer program, wherein the computer program is executed by a processor to implement the method for splitting a transcriptome chimera based on third-generation sequencing provided in the first aspect of the present application.

[0014] The present application has the following beneficial effects:

[0015] The present application searches for a primer sequence in a read sequence by using a local alignment algorithm in double sequence alignment, and uses fuzzy matching search instead of exact matching, so that the adaptability to third-generation sequencing is better; since a step of alignment with a reference genome is added, whether a read is a chimeric read is determined by judging whether different segments of the read are aligned to different positions of reference transcriptome data, so that the accuracy is improved. The primer sequence is no longer fixed, and can be applied to different primer sequences; meanwhile, the alignment position of the read on the reference genome is considered, so that the identification and splitting of the chimeric read are more accurate. BRIEF DESCRIPTION OF DRAWINGS

[0016] Figure 1 A basic flowchart of the method for splitting a transcriptome chimera based on third-generation sequencing in some embodiments of the present application;

[0017] Figure 2 A specific flowchart of the method for splitting a transcriptome chimera based on third-generation sequencing in some embodiments of the present application;

[0018] Figure 3Alignment diagram shown for different modes in Edlib local alignment method in some embodiments of the application;

[0019] Figure 4 Structure diagram of the splitting device for the transcriptome chimera based on third-generation sequencing in some embodiments of the application;

[0020] Figure 5 Structure diagram of the electronic device in some embodiments of the application. DETAILED DESCRIPTION

[0021] The principles and features of the application are described below in conjunction with the accompanying drawings, and the examples are only used to explain the application and not to limit the scope of the application.

[0022] For the convenience of description, the related terms appearing in the present disclosure are generally explained:

[0023] Second-generation sequencing: second-generation gene sequencing technology, also called next-generation sequencing (NGS, Next Generation Sequencing), mainly using sequencing instruments of Illumina platform, sequencing tens of thousands to hundreds of thousands of DNA molecules at a time, and obtaining short fragment reads, usually tens to hundreds of base pairs (bp, base pair).

[0024] Third-generation sequencing: third-generation gene sequencing technology (TGS, Third Generation Sequencing), represented by sequencing technologies of Pacbio or Oxford Nanopore platform, obtaining long fragment reads, length from several kb (kilo base) to several tens or hundreds of kb, suitable for genome assembly, full-length transcriptome research and other work.

[0025] Nanopore sequencing: third-generation sequencing technology developed by Oxford Nanopore company, its principle is to make the DNA or RNA molecules to be tested pass through a biological membrane with many nanopores, and there is a voltage on both sides of the membrane. In the process of DNA or RNA molecules passing through the nanopore, the current at the nanopore position will change, and the current changes caused by different bases (A, T, C, G) will be different, so the trend of current signal fluctuation can be used to identify the bases on the molecules to be tested, thereby achieving the purpose of determining the sequence of DNA or RNA molecules.

[0026] Reads: a sequence read of a gene fragment obtained in the sequencing process, called reads, usually composed of A, T, C, and G four bases.

[0027] PCR: Polymerase Chain Reaction, is a molecular biology technique for amplifying specific DNA fragments, which can be regarded as a special DNA replication in vitro, characterized by exponential amplification of trace amounts of DNA, resulting in a substantial increase in its content.

[0028] Primer: also called primer, is a small nucleic acid sequence that binds to DNA molecules during PCR amplification, which plays a role in guiding PCR extension reaction.

[0029] Genome: refers to the sum of all genetic information in the body, and the genome sequence includes a nucleic acid sequence, usually a nucleic acid sequence is a chromosome, which is composed of A, T, C, and G four bases. The process of sequencing the genome of an organism is called genome sequencing.

[0030] Transcriptome: refers to the sum of all gene transcripts in the body, including different types of RNA molecules, each RNA molecule is called a transcript, and the collection of all transcripts is called a transcriptome. The process of sequencing the transcriptome is called transcriptome sequencing.

[0031] Chimera: during PCR amplification or sequencing of nucleic acid molecules, due to technical defects, different nucleic acid fragments are incorrectly connected to the same reads. Such reads containing different nucleic acid fragments are called chimeras.

[0032] Reference Figure 1 Or Figure 2 In the first aspect of the present application, a method for splitting a transcriptome chimera based on third-generation sequencing is provided, comprising: S100. Obtain the third-generation sequencing data of the transcriptome to be tested; based on the reference genome, perform alignment analysis on the third-generation sequencing data to obtain one or more reads; S200. Determine whether the multiple fragments in each read match the gene fragments located at multiple different positions in the reference genome; S300. Determine whether each read is a chimeric read according to whether the primer sequence is contained in the reads corresponding to the multiple different position gene fragments matched; S400. Determine the chimeric site according to the position of the primer sequence in each chimeric read, and split the transcriptome data according to the chimeric site.

[0033] In step S100 of some embodiments of the present application, the third-generation sequencing data of the transcriptome to be tested is obtained; based on the reference genome, the third-generation sequencing data is subjected to alignment analysis to obtain one or more reads.

[0034] Specifically, S101. Obtain sequencing data. First, RNA extraction is performed on a sample of human peripheral blood using an RNA extraction kit, and then the extracted RNA is quality inspected. The standards for RNA quality inspection are as follows: (1) The sample has no foreign matter in its appearance; (2) 1% agarose electrophoresis detects that the sample has no degradation and no genomic DNA contamination, and the 28s and 18s bands in the gel electrophoresis imaging are clear; (3) The NanoDrop TM One UV-Vis spectrophotometer (Thermo Fisher Scientific, USA) is used to detect the purity of the RNA (A260 / A280 is between 2.0 and 2.2, and A260 / A230 is between 1.8 and 2.1); (4) The RNA is accurately quantified using a Qubit® 3.0 Fluorometer (Invitrogen, USA); (5) The RIN value and 28S / 18S (28s:18s≥1.5, RIN≥8) are detected using an Agilent 2100 Bioanalyzer (Agilent technologies, USA).

[0035] S102. After obtaining the RNA sample that passes the quality inspection, the official library building kit of the Nanopore platform is used to construct the RNA sequencing library.

[0036] Specifically, it includes: S1021. Take 100 ng of the total RNA sample that passes the quality inspection, use the full-length transcriptome (cDNA-PCR) sequencing kit (Oxford Nanopore Technologies, SQK-PCS109) (the type of kit here is only an example), perform reverse transcription and complete strand displacement to synthesize the first strand of cDNA; S1022. Use the bar code labeled primer LWB01-LWB12 in the rapid bar code kit (Oxford Nanopore Technologies, SQK-PBK004) to select full-length transcripts through subsequent PCR reactions, and complete amplification while adding bar code labels (the final amplification cycle number is determined through cycle number optimization experiments); S1023. Connect the rapid sequencing adapter to the PCR product to complete the construction of the sequencing library, and use Qubit to accurately quantify the constructed cDNA library.

[0037] ​S103. After the sequencing library preparation is complete, load the prepared sequencing library into a PromethION Flow Cell (R9.4.1) chip (the chip type here is only an example) and place it into an Oxford Nanopore PromethION sequencer. Select the matching sequencing mode for sequencing. After sequencing, you will obtain sequencing data in FastQ format. For example, the sequencer data shows that a total of 20,281,315 reads were obtained in this sequencing, with a total length of 29,046,359,402 bases (29 Gb), and an average read length of 1432 bases.

[0038] In step S200 of some embodiments of the present invention, determining whether multiple fragments in each read match gene fragments located at multiple different positions in a reference genome includes: comparing each read with a reference genome to determine whether the read matches fragments of multiple genes located at different positions in the reference genome.

[0039] Specifically, the sequencing data is aligned to the reference genome using the minimap2 software (alignment parameters: minimap2-ax splice genome.fadata.fastq) to obtain the aligned BAM format file.

[0040] Example of the comparison results (first 5 rows):

[0041]

[0042] Each row in the alignment results represents an alignment, and there are 17 columns in total. The meaning of each column is explained below:

[0043] 1. The ID identifier of reads;

[0044] 2. The length of reads;

[0045] 3. The starting position of the alignment on the reads;

[0046] 4. The ending position of the alignment on the reads;

[0047] 5. Whether the reads are aligned to the positive (+) or negative (-) strand of the reference genome;

[0048] 6. The ID identifier that is compared to the reference genome sequence;

[0049] 7. The length of the sequence compared to the reference genome sequence;

[0050] 8. The start position of the alignment on the reference genome sequence;

[0051] 9. The termination position of the alignment on the reference genome sequence;

[0052] 10. The number of matching bases in the alignment;

[0053] 11. The length of the alignment;

[0054] 12. Alignment quality value;

[0055] Columns 13 onwards contain a series of label values ​​for comparison. This disclosure primarily utilizes the first 9 columns of the comparison results for analysis.

[0056] In step S300 of some embodiments of the present invention, determining whether each read is a chimeric read based on whether the reads corresponding to the matched gene fragments at multiple different positions contain primer sequences includes: performing a double sequence alignment between the reference primer sequence and each read based on the edlib local alignment algorithm; if at least one primer sequence is matched, the read is determined to be a chimeric read.

[0057] Specifically, to determine if a read is a chimeric read, two conditions must be met: 1. One segment of a read aligns to a position on the reference genome, while another segment aligns to a different position on the reference genome; 2. The two segments that align to different positions on the reference genome must contain a primer sequence between them.

[0058] If a read is not a chimeric read but a normal read, then PCR primers or sequencing primers should only appear at both ends of the read; while if a read is a chimeric read, then PCR primers or sequencing primers will appear in the middle of the read.

[0059] As shown below, "=" indicates a gene fragment in the read, and ">>" or "<<" indicates a primer sequence. Normal reads will only have primer sequences at both ends, for example:

[0060] >>= ...

[0061] In chimeric reads, primers will appear in the middle of the reads, for example (when gene fragment A and gene fragment B are chimeric and sequenced onto the same read):

[0062] >>====A====<>>=========================<<

[0063] Each read is compared and judged. If a primer sequence is identified within a read, it is considered a chimeric read and is then segmented into different sub-reads, as follows:

[0064] >>====A====<<

[0065] >>===========B===========<<

[0066] In one example, for the following reads:

[0067] @1a33524c-db21-4316-9e50-2d0c710938b5runid=67e8721595902135970856a9938a6794dce4ae16read=32386ch=169start_tim e=2021-12-30T22:00:53Zflow_cell_id=PAI17966protocol_group_id=basecalledsample_id=20211230-NPL3956-P6-PAI17966

[0068] GTGTTATGGTTCCTTCGTTCAGTTACGTATTGCT AAGCAGTGGTATCAACGCAGTACATGGGGCTCTTTCCCTAAGCAGCCTGAGGTGATCTGTGAAAATGGTTCGCTATTCACTTGACCCGGAGAACCCCACGAAATCATGCAAATCAAGAGGTTCCAATCTTCGTGTTCACTTTAAGAACACTCGTGAAACTGCTCAGGCCATCAAGGGTATGCATATACGAAAAGCCACGAAGTATCTGAAAGATGTCACTTTACAGAAACAGTGTGTACCATTCCGACGTTACAATGGTGGAGTTGGCAGGTGTGCGCAGGCCAAGCAATGGGGCTGGACACAAGGTCGGTGGCCCAAAAAGAGTGCTGAATTTTTGCTGCACATGCTTAAAAACACAGAGAGTAAATGCTGAACTTAAGGGTTTAGATGTAGATTCTCTGGTCATTGAGCATATCCAAGTGAACAAAGCACCTAAGATGCGCCGCCGGACCTACAGAGCTCATGGTCGGATTAACCCATACATGAGCTCTCCCTGCCACATTGAGATGATCCTTACGGAAAAGGAACAGATTATTTTAAACCAGAAGAGGAGGTTGCCCAGAAGAAAAAAGATATCCAGAAGAAACTGAAGAAACAAAAACTTATGGCACGGGAGTAAATTCAGCATTAAAATAAATGTAATTAAAAGCAAAAAAAAAAAAAAAAAACTACATTACCCTTCTGTGTCCGAGATCGGAAGAGCGTCCGTGTAGAGCAATGGTTGTGTCCTCTACTCGTTCAGTTACGTATTGCT AGCAGTGGTATCAACGCGGAGAGTACATGGGCAGAAATCACATCGCGTCAACACCCGCCGCGGGCCTTCGCGATGCTTTGTTTTAATTAAACAGTCGGATTCCCCTGGTCCGCACCAGTTCTAAGTCGGCTGCTAGGCGCCGGCCGAGGCGAGGCGCCGCGCGGAACCGCGGGCCCGGGGGGCAGACCCCGCGGGGGGGACCGGCCCGCGGCCCCTCCGCCGCCCGCCGCCGCCGCCGCGCGCCGAGGAGGAGGGGGGAACGGGGGGCGGACGGGGCCGGGGGGGTAGGGCGGGGGGACGAACCGCCCCGCCCCGCCGCCCGCCGACCGCCGCCGCCCGACCGCTCCCCGCCCCCAGCGGACGCGCGCGCGACGAGACGTGGGGTGGGGGGGGGGCGCGCCGGCGCCCGCCGGGCTCCCCGGGGGCGGCCGCGACGCCCGCCGCAGCTGGGGCGATCCACGGGAAGGGCCCGGCTCGCGTCCAGAGTCGCCGCCGCCGCCGGCCCCCCGGTGCCCGGGCCCCCCTCGCGGGGGACCGTGCCCCCGCCGCCGGCCCTGTCTCTCAGTTAATACCAAATGTTGGTTGTGTAGCGCACTTGGTTCAGTTACGTATTGCTAGTGGTATCAACGCCGAGTACATGGGACAAATAAGTGGTCTTAGGTCAAGCAGTGGCTCATGACTGTAATCCCATCACTTTGGGAGGCCAAGGTCGTTGGATCGTTTGAGTTTAGGAGTTCGAGACCAGCCTGGGCAACATGGCGAAACCCCATCTCTACTAAAAATACAAAAATTAGTCGGGAGTGGTGATATGTGCAGAAGGATCACTTGTGCCTCAGAGGCAGGGGCTGCAGTGAGCTGAGATCATGTCACTGACTGCACTCCAGCCGGGGTGACAAAGTGAAACCCTGTCTCAAAAAACAAGAACAGAAAAAAAAAAACTGTTTAAATAATTAAGATGAAAAAAAAAAAAAAAAAAAAAAAGCTAAGATTTGCGCTGAACTGAGATAAG

[0069] It is understood that this disclosure requires determining whether a read is a chimeric read, which necessitates meeting the two conditions mentioned above. By parsing the alignment result file, this invention found that this read aligned to three positions on the reference genome, as follows:

[0070] 1a33524c-db21-4316-9e50-2d0c710938b5 1797 1453 1756+17 8325744142613175 42613476 300 303 60

[0071] 1a33524c-db21-4316-9e50-2d0c710938b5 1797 63 688-188037328549488483 49492479 6196270

[0072] 1a33524c-db21-4316-9e50-2d0c710938b5 1797 807 1340-21467099838444318 8444851 5275358

[0073] This read is 1797 bases long. Bases 63 to 688 correspond to positions 49488483 to 49492479 on chromosome 18 of the human reference genome. Bases 807 to 1340 correspond to positions 8444318 to 8444851 on chromosome 21 of the human reference genome. Bases 1453 to 1756 correspond to positions 42613175 to 42613476 on chromosome 17.

[0074] It is understandable that due to the inherent error rate in the base sequences of third-generation sequencing, primer sequences cannot be directly searched within the reads sequence. This invention utilizes the local alignment algorithm of edlib to perform a double sequence alignment between the primer sequence and the reads sequence. Allowing for erroneous matches, it can find the most similar portion of the primer sequence within the reads sequence, thus achieving the goal of searching for primer sequences within the reads.

[0075] Therefore, the process of performing a double sequence alignment between the reference primer sequence and each read based on the edlib local alignment algorithm includes: using the HW mode of the edlib local alignment algorithm to find the read fragment that is most similar to the primer sequence in the reads, while allowing for erroneous matches.

[0076] Specifically, Edlib local alignment is primarily based on Myers's bit-vector for sequence alignment, and it employs banded alignment to further improve computational speed and reduce memory consumption. Edlib offers three alignment modes: NW, SHW, and HW. Let's assume we have two sequences: s1 (reads sequence) GCTAACTGGC and s2 (primer sequence) CGTAGCTG.

[0077] refer to Figure 3 It shows a comparison diagram of three different modes. Figure 3 In this sequence alignment scoring system, a vertical line represents a matching portion between two sequences, awarding points. A short horizontal line (gap) represents a mismatch, resulting in a penalty in the scoring system. Sequence alignment uses a dynamic programming algorithm to find the optimal alignment result (highest score) among all possible results, i.e., finding the best matching position of s2 on s1. Since the NW and SHW modes incur gap penalties at both ends of the primer sequence, and this invention only needs to find the best matching position of s2 on s1 without considering the differences between the ends of s2 and s1, this invention adopts the HW mode. The HW mode, allowing for erroneous matches, utilizes local alignment to quickly find the most similar portion of the primer sequence within the reads, thus enabling rapid processing of long-read data and the discovery of more precise primer sequences.

[0078] The search revealed primer sequences between different alignment positions in the reads, as shown in bold below:

[0079]

[0080]

[0081] Through the above two steps, this read satisfies the above two conditions: 1. One segment of a read is aligned to one position on the reference genome, and the other segment is aligned to another position on the reference genome; 2. The two segments aligned to different positions on the reference genome need to contain primer sequences between them.

[0082] Therefore, this invention determines that this read is a chimeric read consisting of three sequences.

[0083] In another example, for the following reads:

[0084] @fff171a0-6eda-4274-82f8-2f1890cd5a99runid=67e8721595902135970856a9938a6794dce4ae16read=87021ch=177start_time=2021-12-31T08:24:12Zflow_cell_id=PAI17966protocol_group_id=basecalledsample_id=20211230-NPL3956-P6-PAI17966

[0085]

[0086] First, by analyzing the alignment results, it was found that the sequences at both ends of this read aligned to two different positions on the reference genome, as follows:

[0087] fff171a0-6eda-4274-82f8-2f1890cd5a99 1815 1153 1779+12 13327530911622695711622758461863160

[0088] fff171a0-6eda-4274-82f8-2f1890cd5a99 1815 59 1065-214670998335037919 35047930 9941019 60

[0089] This read is 1815 bases long. Bases 59 to 1065 are mapped to positions 35037919 to 35047930 on chromosome 21 of the human reference genome, while bases 1153 to 1779 are mapped to positions 116226957 to 116227584 on chromosome 12 of the human reference genome.

[0090] Then, fuzzy matching of primer sequences was performed within the reads, and the primer sequence was found between two sequences at different alignment positions, as shown in bold below:

[0091] @fff171a0-6eda-4274-82f8-2f1890cd5a99runid=67e8721595902135970856a9938a6794dce4ae16read=87021ch=177start_tim e=2021-12-31T08:24:12Zflow_cell_id=PAI17966protocol_group_id=basecalledsample_id=20211230-NPL3956-P6-PAI17966

[0092]

[0093] Through the above two steps, this read satisfies the two conditions mentioned above: 1. One segment of the read aligns to a location on the reference genome, while the other segment aligns to a different location on the reference genome; 2. The two sequences that align to different locations on the reference genome must contain a primer sequence between them. Therefore, this read is determined to be a chimeric read consisting of two sequences.

[0094] In step S400 of the above embodiment, determining the chimeric site based on the position of the primer sequence of each chimeric read and segmenting the transcriptome data accordingly includes: determining the position of one or more primer sequences of the chimeric reads based on gene fragments at multiple different positions in the reference genome matched by each chimeric read; determining the chimeric site based on the position of the primer sequence of each chimeric read; and segmenting the chimeric reads in the transcriptome to be tested into multiple non-chimeric reads according to the chimeric site.

[0095] Specifically, after determining that a read is a chimeric read, the specific site of chimerism is found by comparing the primer sequence between two sequences at different positions on the reference genome, thereby improving the accuracy of the segmentation and avoiding false positives. Then, the read is segmented into different reads from that site to obtain non-chimeric reads.

[0096] For example, taking the above implementation example 1 as an example,

[0097]

[0098]

[0099] In determining whether they are chimeric reads, it was found that: from the 63rd to the 688th base, they correspond to positions 49488483 to 49492479 on chromosome 18 of the human reference genome; from the 807th to the 1340th base, they correspond to positions 8444318 to 8444851 on chromosome 21 of the human reference genome; and from the 1453rd to the 1756th base, they correspond to positions 42613175 to 42613476 on chromosome 17.

[0100] Between the 688th and 807th bases, the primer sequence "AGCAGTGGTATCAACGCGGAGAGTACATGGG" was matched. Therefore, subtracting the length of the matched primer sequence (31) before the 807th base gives the specific position where the chimeric reads were cut: the (807-31=776)th base. Then, using the 776th base as the breakpoint, the first to the 775th bases form the first read after the cut, and the last base from the 776th base to the last base forms the second read. In other words, by cutting the chimeric reads, two non-chimeric reads were obtained.

[0101] The segmentation results of the sequencing data show that this disclosure successfully segmented 5,998,473 chimeric reads. The segmentation method provided by this invention can improve the accuracy of chimeric read identification, segment more chimeric reads, and thus improve the accuracy of sequencing.

[0102] Example 2

[0103] refer to Figure 4 In a second aspect, the present invention provides a transcriptome chimera segmentation device 1 based on third-generation sequencing, comprising: an acquisition module 11 for acquiring third-generation sequencing data of a transcriptome to be tested; performing comparative analysis on the third-generation sequencing data based on a reference genome to obtain one or more reads; a first judgment module 12 for judging whether multiple fragments in each read match gene fragments located at multiple different positions in the reference genome; a second judgment module 13 for judging whether each read is a chimeric read based on whether the read fragments corresponding to the gene fragments at multiple different positions contain primer sequences; and a segmentation module 14 for determining chimeric sites based on the position of the primer sequences of each chimeric read in the reads and segmenting the transcriptome data accordingly.

[0104] Furthermore, the segmentation module 14 includes: a determining unit, used to determine the position of primer sequences of one or more chimeric reads based on gene fragments at multiple different positions in the reference genome matched by each chimeric read; and a segmentation unit, used to determine chimeric sites based on the position of primer sequences of each chimeric read, and segment the chimeric reads in the transcriptome to be tested into multiple non-chimeric reads based on the chimeric sites.

[0105] Example 3

[0106] refer to Figure 5In a third aspect, the present invention provides an electronic device comprising: one or more processors; and a storage device for storing one or more programs, wherein when the one or more programs are executed by the one or more processors, the one or more processors implement the transcriptome chimera segmentation method based on third-generation sequencing of the present invention in the first aspect.

[0107] Electronic device 500 may include a processing unit (e.g., a central processing unit, a graphics processing unit, etc.) 501, which can perform various appropriate actions and processes according to a program stored in read-only memory (ROM) 502 or a program loaded from storage device 508 into random access memory (RAM) 503. RAM 503 also stores various programs and data required for the operation of electronic device 500. The processing unit 501, ROM 502, and RAM 503 are interconnected via bus 504. Input / output (I / O) interface 505 is also connected to bus 504.

[0108] Typically, the following devices can be connected to I / O interface 505: input devices 506 including, for example, touchscreens, touchpads, keyboards, mice, cameras, microphones, accelerometers, gyroscopes, etc.; output devices 507 including, for example, liquid crystal displays (LCDs), speakers, vibrators, etc.; storage devices 508 including, for example, hard disks; and communication devices 509. Communication device 509 allows electronic device 500 to communicate wirelessly or wiredly with other devices to exchange data. Although Figure 5 An electronic device 500 with various devices is shown; however, it should be understood that it is not required to implement or possess all of the devices shown. More or fewer devices may be implemented or possessed alternatively. Figure 5 Each box shown can represent a device or multiple devices as needed.

[0109] Specifically, according to embodiments of this disclosure, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, embodiments of this disclosure include a computer program product comprising a computer program carried on a computer-readable medium, the computer program containing program code for performing the methods shown in the flowcharts. In such embodiments, the computer program can be downloaded and installed from a network via a communication device 509, or installed from a storage device 508, or installed from a ROM 502. When the computer program is executed by a processing device 501, it performs the functions defined in the methods of embodiments of this disclosure. It should be noted that the computer-readable medium described in embodiments of this disclosure can be a computer-readable signal medium or a computer-readable storage medium, or any combination of the two. A computer-readable storage medium can be, for example—but not limited to—an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples of computer-readable storage media may include, but are not limited to: electrical connections having one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof. In embodiments of this disclosure, a computer-readable storage medium may be any tangible medium containing or storing a program that can be used by or in connection with an instruction execution system, apparatus, or device. In embodiments of this disclosure, a computer-readable signal medium may include a data signal propagated in baseband or as part of a carrier wave, carrying computer-readable program code. Such propagated data signals may take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination thereof. A computer-readable signal medium may also be any computer-readable medium other than a computer-readable storage medium, which can send, propagate, or transmit a program for use by or in connection with an instruction execution system, apparatus, or device. Program code contained on a computer-readable medium may be transmitted using any suitable medium, including but not limited to: wires, optical fibers, RF (radio frequency), etc., or any suitable combination thereof.

[0110] The aforementioned computer-readable medium may be included in the aforementioned electronic device; or it may exist independently and not assembled into the electronic device. The aforementioned computer-readable medium carries one or more computer programs, which, when executed by the electronic device, cause the electronic device to:

[0111] Computer program code for performing the operations of embodiments of this disclosure can be written in one or more programming languages ​​or a combination thereof. Programming languages ​​include object-oriented programming languages—such as Java, Smalltalk, C++, and Python—and conventional procedural programming languages—such as the "C" language or similar programming languages. The program code can be executed entirely on the user's computer, partially on the user's computer, as a standalone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving remote computers, the remote computer can be connected to the user's computer via any type of network—including a local area network (LAN) or a wide area network (WAN)—or can be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0112] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of this disclosure. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions indicated in the blocks may occur in a different order than those indicated in the drawings. For example, two consecutively indicated blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should be noted that each block in the block diagrams and / or flowcharts, and combinations of blocks in the block diagrams and / or flowcharts, can be implemented using a dedicated hardware-based system that performs the specified function or operation, or using a combination of dedicated hardware and computer instructions.

[0113] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A method for resolving transcriptome chimeras based on third-generation sequencing, characterized in that, The method comprises the following steps: obtaining third-generation sequencing data of a to-be-tested transcriptome; performing alignment analysis on the third-generation sequencing data based on a reference genome to obtain one or more reads; determining whether multiple fragments in each read match gene fragments located at multiple different positions of the reference genome; determining whether each read is a chimeric read according to whether a primer sequence is contained in a read fragment corresponding to the multiple different positions of the gene fragments that are matched: performing double-sequence alignment of a reference primer sequence and each read based on an edlib local alignment algorithm, and if at least one primer sequence is matched, the read is determined to be a chimeric read; the double-sequence alignment of the reference primer sequence and each read based on the edlib local alignment algorithm comprises: finding the read fragment that is most similar to the primer sequence in the read under the condition of allowing error matching through the HW mode of the edlib local alignment algorithm; determining a chimeric site according to the position of the primer sequence of each chimeric read in the read and splitting the transcriptome data according to the chimeric site: determining the position of the primer sequence of one or more chimeric reads according to the multiple different positions of the gene fragments of the reference genome that are matched by each chimeric read; determining a chimeric site based on the position of the primer sequence of each chimeric read, and splitting the chimeric reads in the to-be-tested transcriptome into multiple non-chimeric reads according to the chimeric site.

2. The method of claim 1, wherein the method is performed on a sample comprising a plurality of cells, wherein the plurality of cells comprises a plurality of cell types, and wherein the plurality of cells is derived from a biological sample. The determination of whether the multiple fragments in each read match the gene fragments located at the multiple different positions of the reference genome comprises: performing alignment of each read with the reference genome to determine whether the read matches the fragments of multiple genes located at different positions in the reference genome.

3. The method of claim 1, wherein, The condition of allowing error matching comprises fuzzy matching.

4. A device for splitting a transcriptome chimera based on third generation sequencing, characterized in that, The method comprises the following steps: an obtaining module is configured to obtain third-generation sequencing data of a to-be-tested transcriptome; performing alignment analysis on the third-generation sequencing data based on a reference genome to obtain one or more reads; a first determining module is configured to determine whether multiple fragments in each read match gene fragments located at multiple different positions of the reference genome; a second determining module is configured to determine whether each read is a chimeric read according to whether a primer sequence is contained in a read fragment corresponding to the multiple different positions of the gene fragments that are matched: performing double-sequence alignment of a reference primer sequence and each read based on an edlib local alignment algorithm, and if at least one primer sequence is matched, the read is determined to be a chimeric read; the double-sequence alignment of the reference primer sequence and each read based on the edlib local alignment algorithm comprises: finding the read fragment that is most similar to the primer sequence in the read under the condition of allowing error matching through the HW mode of the edlib local alignment algorithm; determining a chimeric site according to the position of the primer sequence of each chimeric read in the read and splitting the transcriptome data according to the chimeric site: determining the position of the primer sequence of one or more chimeric reads according to the multiple different positions of the gene fragments of the reference genome that are matched by each chimeric read; determining a chimeric site based on the position of the primer sequence of each chimeric read, and splitting the chimeric reads in the to-be-tested transcriptome into multiple non-chimeric reads according to the chimeric site. The segmentation module is configured to determine a chimeric site according to the position of the primer sequence of each chimeric read in the reads, and segment the transcriptome data according to the chimeric site: determining the position of the primer sequence of one or more chimeric reads according to the gene fragments of different positions of the reference genome matched by each chimeric read; determining a chimeric site based on the position of the primer sequence of each chimeric read, and segmenting the chimeric reads in the test transcriptome into a plurality of non-chimeric reads according to the chimeric site.

5. An electronic device, comprising: The method comprises: one or more processors; a storage device configured to store one or more programs, when the one or more programs are executed by the one or more processors, the one or more processors are caused to implement the method for segmenting the transcriptome chimeric body based on the third-generation sequencing according to any one of claims 1 to 3.

6. A storage medium having stored thereon a computer program, characterized in that In the method, the computer program is executed by the processor to implement the method for segmenting the transcriptome chimeric body based on the third-generation sequencing according to any one of claims 1 to 3.

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