Genome assembly optimization method based on telomere sequence detection and overlay network graph reconstruction

Abstract

The invention discloses a genome assembly optimization method based on telomere sequence detection and overlay network graph reconstruction, and relates to the technical field of bioinformatics. The method comprises the following steps: performing telomere detection and fragment interception on sequencing data to be assembled to obtain a telomere-containing fragment; performing genome preliminary assembly on the sequencing data to generate a contig sequence and an overlapping network diagram; detecting whether the two ends of the contig sequence contain telomere sequences or not; and for the first contig sequence which does not contain the telomere sequence, selecting an extended path where the telomere-containing fragment is located in the overlay network diagram to carry out telomere splicing on the first contig sequence, generating a telomere-containing contig sequence, and obtaining an optimized genome assembly result. According to the invention, the problem of insufficient assembly of the genome assembly telomere region is solved, and the integrity and accuracy of the telomere region in the genome assembly result are improved.

Description

Technical Field

[0001] The present invention relates to the technical field of bioinformatics, and in particular to a genome assembly optimization method based on telomere sequence detection and overlapping network graph reconstruction. Background Art

[0002] Genome assembly is one of the core tasks in bioinformatics, which aims to splice a large number of short sequence reads into long continuous sequences (contigs) to reconstruct a complete genome. With the development of high-throughput sequencing technology, the amount of sequencing data generated has increased dramatically, prompting the continuous advancement of assembly algorithms to improve the accuracy and completeness of assembly. At present, the mainstream genome assembly methods are mainly divided into the following categories:

[0003] 1. Overlap-Layout-Consensus (OLC) method: This method constructs an overlap graph or string graph by identifying the overlapping relationship between read segments, and then generates a continuous genome sequence through layout and consensus steps. Representative software includes Canu, Hifiasm, etc.

[0004] 2. De Bruijn graph method: De Bruijn graph is constructed by decomposing read segments into k-mers, and then contigs are generated through graph simplification and path search. Representative software includes SPAdes, ABySS, etc.

[0005] 3. String Graph Approach: Similar to the OLC method, it uses a more efficient graph structure to represent the overlapping relationship between read segments. Representative software includes Flye, etc.

[0006] Telomeres are special structures at the ends of chromosomes, consisting of highly repetitive short sequences (such as TTAGGG / CCCTAA repeat sequences in eukaryotes). Telomeres play a key role in maintaining chromosome stability and preventing chromosome end fusion and degradation. Complete telomere sequences are of great significance for genome integrity analysis, chromosome structure research, and cell aging mechanism research. However, due to the high repetitiveness and complex structure of telomere sequences, telomere regions are often difficult to assemble accurately during genome assembly, resulting in missing telomere sequences or broken telomere regions in the assembly results.

[0007] Although existing genome assembly methods perform well in most genomic regions, they still have the following shortcomings when dealing with telomere sequences:

[0008] 1. Low coverage depth: Due to its high repetitiveness and complexity, the telomere region often cannot obtain sufficient coverage depth during the sequencing process, which makes it difficult for the assembly software to accurately identify the repeating units of the telomere sequence, resulting in failed or incomplete assembly of the telomere region.

[0009] 2. High complexity of overlapping graphs: In the OLC method, the high repetitiveness of the telomeric region leads to a large number of repeated nodes and complex connection relationships in the overlapping graph, which increases the complexity of the graph and makes it difficult to find a unique assembly path.

[0010] 3. Lack of specialized processing mechanisms: Existing assembly software generally lacks specialized processing mechanisms for telomere sequences and cannot effectively identify and extend contigs containing telomere sequences, resulting in the majority of contigs in the assembly results lacking telomere sequences.

[0011] 4. Increased risk of misassembly: Due to the high repetitiveness of telomere sequences, existing assembly methods are prone to misassembly in the telomere region, such as incorrectly connecting sequences at the ends of different chromosomes, affecting the overall assembly quality of the genome.

[0012] In summary, existing assembly methods still have significant deficiencies when processing telomere sequences and lack a processing mechanism specifically for telomere sequences. There is an urgent need for a method and system that can specifically detect and extend the reading path containing telomere sequences and improve the integrity of the telomere region in genome assembly. Summary of the invention

[0013] The purpose of the present invention is to provide a genome assembly optimization method based on telomere sequence detection and overlapping network graph reconstruction to solve the problems of insufficient coverage and incomplete assembly in the telomere region of existing genome assembly methods.

[0014] To achieve the above object, the present invention adopts the following technical solutions:

[0015] According to one aspect of the present invention, a genome assembly optimization method based on telomere sequence detection and overlapping network graph reconstruction is provided, comprising: performing telomere detection and fragment interception on sequencing data to be assembled to obtain telomere-containing fragments; performing preliminary genome assembly on the sequencing data by a genome assembly tool to generate a contig sequence and an overlapping network graph, wherein the contig sequence is a continuous sequence assembled from sequencing reads, and the overlapping network graph is used to display the overlapping relationship between sequencing reads, each node in the graph represents a sequencing read, and each edge represents the overlap between two reads; detecting whether both ends of the generated contig sequence contain telomere sequences; for a first contig sequence that does not contain a telomere sequence, determining a first connection path of the first contig sequence in the overlapping network graph; searching for a potential extension path in the overlapping network graph according to the first connection path; selecting the path where the telomere-containing fragment is located from the potential extension path to perform telomere splicing on the first contig sequence to generate a telomere-containing contig sequence, and obtaining an optimized genome assembly result.

[0016] Optionally, the telomere detection and fragment extraction of the sequencing data to be assembled to obtain the telomere-containing fragments includes: searching for telomere sequences in the sequencing data by a character string search method; for each position where a telomere sequence appears, starting from the start position of the telomere sequence, taking a preset length fragment to extract a subsequence; counting the number of occurrences of the telomere sequence in the extracted subsequence; if the number of occurrences of the telomere sequence in the subsequence reaches or exceeds a preset number, outputting the subsequence, and the output subsequence is the telomere-containing fragment.

[0017] Optionally, taking a preset length fragment to truncate a subsequence further comprises: calculating a truncable length according to a starting position of the telomere sequence and a maximum length of a read segment where the telomere sequence is located; comparing the truncable length with the preset length, and selecting the smaller length to truncate the subsequence.

[0018] Optionally, searching for potential extended paths in the overlapping network graph based on the first connection path includes: locating and marking the end connection node of the first connection path in the overlapping network graph; starting from the marked end connection node, along the connection relationship in the overlapping network graph, tracing and extracting all potential extended paths connected to the end connection node.

[0019] Optionally, the step of selecting the path containing the telomere fragment from the potential extension path to perform telomere splicing on the first contig sequence to generate a contig sequence containing telomeres includes: determining whether each potential extension path contains the telomere fragment; using the path containing the telomere fragment as the target extension path for the first contig sequence; and splicing all parts of the terminal connection node along the target extension path to the telomere end to the end of the first contig sequence to generate a contig sequence containing telomeres.

[0020] Optionally, after performing telomere splicing on the first contig sequence, the method further comprises: performing telomere detection on the spliced ​​contig sequence to determine whether the spliced ​​contig sequence contains a completely covered telomere sequence; if the spliced ​​contig sequence contains a completely covered telomere sequence, the spliced ​​contig sequence is used as the final assembly sequence.

[0021] Optionally, the determining whether the spliced ​​contig sequence contains a completely covered telomere sequence includes: obtaining the telomere sequence length of the spliced ​​contig sequence; if the telomere sequence length of the spliced ​​contig sequence is not less than the known telomere length, it is considered that the spliced ​​contig sequence contains a completely covered telomere sequence.

[0022] The present invention detects telomere sequences, performs telomere splicing on contig sequences that do not contain telomeres according to the paths containing telomere reads in the overlapping network diagram, and extends the existing contigs, thereby solving the problem of insufficient assembly of telomere regions in genome assembly and improving the integrity and accuracy of telomere regions in genome assembly results. In addition, by checking the spliced ​​contig sequences, it is ensured that the spliced ​​and extended contig sequences are accurate, thereby improving the quality and reliability of the assembly results. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] The drawings described herein are used to provide a further understanding of the present invention and constitute a part of the present invention. The exemplary embodiments of the present invention and their descriptions are used to explain the present invention and do not constitute an improper limitation of the present invention. In the drawings:

[0024] Figure 1 It is a flow chart of the genome assembly optimization method based on telomere sequence detection and overlapping network graph reconstruction in Example 1 of the present invention;

[0025] Figure 2 is a flow chart of the genome assembly optimization method based on telomere sequence detection and overlapping network graph reconstruction in Example 2 of the present invention;

[0026] Figure 3This is a schematic diagram of contig extension in Example 2 of the present invention;

[0027] Figure 4 This is a comparison chart of the telomere number results of Agaricus bisporus contigs in Example 2 of the present invention. DETAILED DESCRIPTION

[0028] In order to enable those skilled in the art to better understand the present application, the technical solutions in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only embodiments of a part of the present application, not all embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in the field without creative work should fall within the scope of protection of the present application. It should be noted that the embodiments in the present application and the features in the embodiments can be combined with each other without conflict.

[0029] Secondly, the term "one embodiment" or "embodiment" as used herein refers to a specific feature, structure, or characteristic that may be included in at least one implementation of the present invention. The term "in one embodiment" that appears in different places in this specification does not necessarily refer to the same embodiment, nor does it refer to a separate or selective embodiment that is mutually exclusive with other embodiments.

[0030] It should be noted that the terms "first", "second", etc. in the specification and claims of the present application and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchangeable where appropriate, so that the embodiments of the present application described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any of their variations are intended to cover non-exclusive inclusions, for example, a process, method, product or device comprising a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0031] Example 1

[0032] Reference Figure 1 , Figure 1 is a flow chart of a genome assembly optimization method based on telomere sequence detection and overlapping network graph reconstruction in an embodiment of the present invention, such as Figure 1 As shown, the method comprises the following steps:

[0033] S1, perform telomere detection and fragment extraction on the sequencing data to be assembled to obtain telomere-containing fragments;

[0034] Telomere is a short DNA-protein complex present at the end of linear chromosomes in eukaryotic cells. It is composed of a short, multi-repeated non-transcribed sequence (TTAGGG) and some binding proteins. The common telomere sequence is a repeat of TTAGGG.

[0035] Telomere detection can be achieved by using telomere detection tools, such as TRF (Tandem Repeats Finder), Telomerecat, etc. Fragment extraction can be achieved by extracting gene fragments at specified locations using biological software.

[0036] Further, in an implementation manner of an embodiment of the present invention, step S1 includes:

[0037] S11, searching for telomere sequences in the sequencing data by a string search method;

[0038] Sequencing data contains several reads, each of which is a sequence on the genome.

[0039] The string search method (String SearchMethod) can search for a specific target string (i.e., telomere sequence) in a string (i.e., read segment). Each read segment of the entire sequencing data set is traversed, and all occurrences of the telomere sequence M (such as TTAGGG or CCCTAA) are found through string search.

[0040] S12, for each position where a telomere sequence appears, starting from the start position of the telomere sequence, a fragment of a preset length is taken to obtain a subsequence;

[0041] The purpose of intercepting subsequences in this step is to detect telomere sequences. From the detected reads containing telomere sequences, a subsequence of a preset length is intercepted. This subsequence is not the telomere sequence itself, but a sequence fragment intercepted from the reads containing telomere sequences. The reason for intercepting such a subsequence is that telomere sequences are usually composed of specific repeating units (such as "TTAGGG" in humans). Directly counting the number of occurrences of telomere sequences in the entire read may not be accurate. By intercepting a subsequence of a fixed length, the repetitive pattern of the telomere sequence can be better matched and counted.

[0042] For each position p found, a subsequence (k-mer) of length k is intercepted. That is, the telomere sequence starts at position p in the read segment, and the end position of the intercepted subsequence is p+k, where k represents the length of the intercepted subsequence, that is, the k-mer size. It should be noted that this step detects the position and frequency of occurrence of the telomere sequence without performing a comprehensive k-mer analysis of the entire sequence. The selection of k is based on the length and structure of the telomere repeat sequence, and a k value that can cover one or more repeat units is usually selected. Exemplarily, for TTAGGG of human telomeres, k is usually set to 6 or its multiples (such as 12, 18). If the goal is to detect longer telomere repeat sequences, k may be set larger to more accurately capture the repeat pattern of the telomere.

[0043] Further, S12, taking a preset length segment to extract a subsequence comprises:

[0044] S121, calculating the truncation length according to the starting position of the telomere sequence and the maximum length of the read segment where the telomere sequence is located;

[0045] S122, comparing the truncation length with the preset length, and selecting the smaller length to truncate the subsequence.

[0046] In order to ensure that the truncation operation does not exceed the boundary of the read segment, the embodiment of the present invention calculates the truncation length of the subsequence according to the maximum length maxlen of the read segment where the telomere sequence is located. This truncation length is the length from the starting position where the telomere sequence appears to the end of the read segment. If the truncation length is less than the preset length, the truncation length is used as the final truncation length. If the preset length is less than the truncation length, the preset length is used as the final truncation length.

[0047] S13, counting the occurrence times of telomere sequences in the intercepted subsequences;

[0048] In the truncated subsequence, the number of occurrences of the telomere sequence M is counted, that is, count(M, subseq(p, k)), where M represents the telomere sequence, p represents the starting position of the telomere sequence, k represents the truncation length, subseq(p, k) means starting from position p, truncating a subsequence of length k, and count represents the number of statistics.

[0049] S14, if the number of times the telomere sequence appears in the subsequence reaches or exceeds a preset number, the subsequence is output, and the output subsequence is the telomere-containing fragment.

[0050] A preset number threshold (cutoff) is set, which is used to determine whether a read segment should be considered to contain a telomere sequence. If the number of occurrences of the telomere sequence in a subsequence is greater than or equal to the preset number, then the subsequence will be marked as containing a telomere sequence. According to the marking result, the subsequence marked as containing a telomere sequence is output, and the output subsequence is the truncation of the preset length containing the telomere. The output expression is: output(chr, p, min(p+k, maxlen), maxlen); in the formula, chr is the chromosome identifier; min(p+k, maxlen) represents the actual end position of the telomere sequence (not exceeding maxlen).

[0051] S2, performing preliminary genome assembly on the sequencing data using a genome assembly tool to generate contig sequences and overlapping network diagrams;

[0052] Contig sequences are longer continuous sequences obtained by assembling shorter sequence reads obtained by sequencing. The assembly software hifiasm can be used to assemble the genome and generate contig sequences. These generated contig sequences are continuous on the genome, but may still contain some deficiencies (such as telomere sequence deletions, etc.).

[0053] In addition, hifiasm generates an Overlap Graph during the assembly process, which represents the overlapping relationship between sequencing reads. Each node represents a sequencing read, and each edge represents the overlap between two reads. By analyzing the Overlap Graph, the overall structure of the genome can be constructed.

[0054] The principle of constructing contigs and overlapping network graphs by the assembly software hifiasm is:

[0055] 1. Find the overlapping regions of sequences: find the overlapping regions between them by aligning all the sequencing reads;

[0056] 2. Construct an Overlap Graph: Represent the read segments as nodes in the graph and the overlapping relationships as edges to generate a network graph;

[0057] 3. Find the best path (Layout): Find the most reasonable path through graph analysis and splice it into a longer sequence.

[0058] Due to the threshold problem of the software and the low sequencing coverage of reads containing telomeres at both ends, the contigs finally presented by the software are only those generated by the path it believes to be certain. However, in the overlapping network diagram it generates, there are other longer or more complete paths. In this embodiment of the present invention, whether the ends of these longer paths in the overlapping network diagram contain reads with telomeres, if so, the initial contigs originally generated by the software are extended according to the path containing telomeres.

[0059] S3, detect whether both ends of the generated contig sequence contain telomere sequences;

[0060] In order to make as many contigs as possible contain telomeres, the contigs without telomeres are extended in the embodiment of the present invention. For each initially assembled contig, the two ends of the contig are detected to see whether they contain telomere sequences. The telomere sequence detection method can refer to the above step S1. If it is detected that the two ends of a contig contain telomere sequences, the information is recorded.

[0061] S4, for a first contig sequence that does not contain a telomere sequence, determining a first connection path of the first contig sequence in the overlapping network graph;

[0062] The first contig sequence refers to the contig sequence that does not contain the telomere sequence in the generated contig sequence. In order to avoid a prefix that is too long, it is referred to as the first contig sequence.

[0063] The first connection path refers to the connection path of the contig sequence that does not contain the telomere sequence (ie, the first contig sequence) in the overlapping network diagram, representing the region in the genome that is not covered by the telomere sequence.

[0064] The purpose of this step S41 is to first determine the specific position of the contig without telomeres to be supplemented in the overlapping network diagram, and then search for possible extension paths outward from this position.

[0065] S5, searching for a potential extension path in the overlapping network graph according to the first connection path;

[0066] By utilizing the overlapping relationship between the read segments in the overlapping network graph, possible potential extension paths are searched and located in the overlapping network graph according to the first connection path. These potential extension paths represent all possible paths that can be extended from the end of the first contig sequence.

[0067] Specifically, the terminal connection node of the first connection path is located and marked in the overlapping network graph; starting from the marked terminal connection node, all potential extended paths connected to the terminal connection node are traced and extracted along the connection relationship in the overlapping network graph.

[0068] S6, selecting the path where the telomere-containing fragment is located from the potential extension path to perform telomere splicing on the first contig sequence to generate a telomere-containing contig sequence, and obtaining an optimized genome assembly result.

[0069] In the embodiment of the present invention, the path containing the telomere-containing read segment is selected as the extension path to extend the contig sequence without telomeres, so as to optimize the gene assembly result. It is determined whether each extracted potential extension path contains the telomere-containing segment; the path where the telomere-containing segment is located is used as the target extension path of the first contig sequence; all parts between the terminal connection node of the first contig sequence along the target extension path to the telomere end are spliced ​​to the end of the first contig sequence, and a contig sequence containing the telomere sequence is generated by splicing.

[0070] Furthermore, after performing telomere splicing on the first contig sequence, the method further comprises performing telomere detection on the spliced ​​contig sequence to determine whether the spliced ​​contig sequence contains a completely covered telomere sequence, so as to further ensure the integrity of the spliced ​​contig sequence.

[0071] Wherein, judging whether the spliced ​​contig sequence contains a completely covered telomere sequence includes: obtaining the telomere sequence length of the spliced ​​contig sequence, wherein the telomere sequence length can be obtained by telseq software; the normal telomere length of the species is generally known, if the telomere sequence length of the spliced ​​contig sequence is less than the known telomere length (such as hundreds of bases), it is considered that the spliced ​​contig sequence contains an incompletely covered telomere sequence and can be determined as "incomplete", if the telomere sequence length of the spliced ​​contig sequence is not less than the known telomere length, it is considered that the spliced ​​contig sequence contains a completely covered telomere sequence, that is, the telomere sequence completely covers the end of the contig, which can be determined as "complete", and the contig sequence determined as "complete" is used as the final contig sequence for genome assembly.

[0072] By testing the extended contig sequences, the accuracy and integrity of the telomere sequences can be ensured. All extended "complete" contig sequences are integrated to generate the final genome assembly results.

[0073] The present invention detects telomere sequences, performs telomere splicing on contig sequences that do not contain telomeres according to the extension path where the telomere sequences are located in the overlapping network diagram, and extends the contigs that lack telomeres, thereby solving the problem of insufficient assembly of telomere regions in genome assembly and improving the integrity and accuracy of telomere regions in genome assembly results.

[0074] Example 2

[0075] The technical solution of the present invention is further described in detail below in conjunction with a specific embodiment and the accompanying drawings. It should be understood that the following embodiment is only used to explain the present invention, and is not used to limit the present invention.

[0076] Agaricus bisporus is a fungus of the Agaricus family and the Agaricus genus, also known as white mushroom, mushroom, and foreign mushroom. Agaricus bisporus is a widely cultivated edible mushroom, and the demand for cultivation is growing, while the difficulties associated with breeding programs now mean that strains are effectively treated as monocultures. Although commercial cultivation methods are efficient and strictly controlled, the overuse of a single strain has led to multiple disease outbreaks caused by a range of pathogens including bacteria, fungi, and viruses. Therefore, the integrity of its genome assembly is of great significance for studying its biological characteristics. Agaricus bisporus has thirteen chromosomes. When processing the Agaricus bisporus genome, existing assembly software can usually only accurately assemble 12 to 16 telomeres, failing to cover the telomere regions of all chromosomes, resulting in incomplete genome assembly. However, after adopting the genome assembly optimization method provided by the present invention, 26 telomeres can be finally assembled to achieve a complete assembly of the genome. Specifically, referring to Figure 2 , Figure 2 FIG. 4 is a flow chart of a genome assembly optimization method based on telomere sequence detection and overlapping network graph reconstruction in an embodiment of the present invention, as shown in FIG. Figure 2 As shown, the embodiment of the present invention adopts the following main steps to optimize the genome assembly of Agaricus bisporus:

[0077] Step 1, detect telomeres in sequencing data: determine the Agaricus bisporus telomere sequence, the telomere repeat sequence TTAGGG and its complementary sequence CCCTAA. The algorithm traverses all sequencing reads, uses the string search method to find the position of the telomere sequence in the read, and counts its occurrence. For each read containing the telomere sequence, apply the repeat counting algorithm to calculate the number of repetitions of the telomere sequence in the read. If the number of repetitions of the telomere sequence in a read reaches or exceeds the preset threshold (5 times), it is marked as a read containing the telomere sequence.

[0078] Step 2, preliminary genome assembly and telomere detection: Use PacBio HiFi data to perform preliminary genome assembly through the assembly software hifiasm to generate initial contig sequences. For each preliminary assembled contig, check whether its two ends contain the telomere sequence detected in step 1. If a contig contains a telomere sequence at the end, record the information for subsequent processing.

[0079] Step 3, overlapping network graph construction and non-telomeric contig path extraction: Extract the overlapping network graph generated by the assembly software hifiasm to construct the overall structure of the genome. Based on the contig information containing telomere sequences recorded in step 2, screen out contig paths that do not contain telomere sequences. These paths represent regions in the genome that are not covered by telomere sequences. Extract the screened non-telomeric contig paths as the basis for subsequent extension and optimization.

[0080] Step 4: Compare the reads containing telomere sequences selected in step 1 with the non-telomere contig paths extracted in step 3, and determine the correct path for extending the contig based on which path of the overlapping network graph the reads containing telomere sequences are located on. For the matched contig ends, the contig sequences are extended based on the matched paths.

[0081] like Figure 3 As shown, Figure 3 This is a schematic diagram of contig extension. The specific method is to splice the telomere sequence part in the read segment to the end of the contig to form a complete telomere region, where circles 1 to 5 indicate the initial connection of the contig, circles 6 and 7 represent the paths in the overlapping network diagram that do not contain telomere reads, and circle 8 represents the path in the overlapping network diagram that contains telomere reads. The path in circle 8 is selected to extend the contig.

[0082] Telomere detection is performed on the extended contig sequence to ensure the accuracy and integrity of the telomere sequence. If the extended sequence contains a fully covered telomere sequence, the telomere region is considered to be fully assembled. All extended contig sequences are integrated to generate the final genome assembly result, which includes 26 telomere sequences of all thirteen chromosomes. Figure 4 , Figure 4 2 is a comparison chart of the telomere number of Agaricus bisporus contigs according to an embodiment of the present invention. Figure 4 As shown, after adopting the method of the present invention, the number of telomeres in the assembly result is significantly increased, and the genome assembly shows a better effect.

[0083] In this embodiment, a genome assembly device is also provided to implement the above embodiments and preferred implementation modes, and those that have been explained will not be repeated here.

[0084] Optionally, the specific examples in this embodiment may refer to the examples described in the above embodiments and optional implementation modes, and this embodiment will not be described in detail here.

[0085] An embodiment of the present invention further provides a storage medium, in which a computer program is stored, wherein the computer program is configured to execute the steps of any of the above method embodiments when running.

[0086] For specific examples in this embodiment, reference may be made to the examples described in the above embodiments and optional implementation modes, and this embodiment will not be described in detail here.

[0087] Optionally, in this embodiment, the above-mentioned storage medium may include but is not limited to: a USB flash drive, a read-only memory (ROM), a random access memory (RAM), a mobile hard disk, a magnetic disk or an optical disk, and other media that can store computer programs.

[0088] The serial numbers of the above embodiments of the present invention are only for description and do not represent the advantages or disadvantages of the embodiments.

[0089] In the above embodiments of the present invention, the description of each embodiment has its own emphasis. For parts that are not described in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0090] The steps in the above-mentioned embodiment of the present invention can be adjusted in order, combined and deleted according to actual needs. The technical features can be combined arbitrarily. In order to make the description concise, all possible combinations of the technical features in the embodiment are not described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of the present invention.

[0091] The above is only a preferred embodiment of the present invention. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principle of the present invention. These improvements and modifications should also be regarded as the scope of protection of the present invention.

Claims

1. A genome assembly optimization method based on telomere sequence detection and overlapping network graph reconstruction, characterized in that: include: Perform telomere detection and fragment extraction on the sequencing data to be assembled to obtain telomere-containing fragments; Performing preliminary genome assembly on the sequencing data using a genome assembly tool to generate a contig sequence and an overlapping network diagram, wherein the contig sequence is a continuous sequence assembled from sequencing reads, and the overlapping network diagram is used to display the overlapping relationship between sequencing reads, wherein each node in the diagram represents a sequencing read, and each edge represents the overlap between two reads; Detect whether the two ends of the generated contig sequence contain telomere sequences; For a first contig sequence that does not contain a telomere sequence, determining a first connection path of the first contig sequence in the overlapping network graph; According to the first connection path, searching for a potential extension path in the overlapping network graph; The path where the telomere-containing fragment is located is selected from the potential extension paths to perform telomere splicing on the first contig sequence to generate a telomere-containing contig sequence, thereby obtaining an optimized genome assembly result.

2. The genome assembly optimization method based on telomere sequence detection and overlapping network graph reconstruction according to claim 1, characterized in that: The telomere detection and fragment extraction are performed on the sequencing data to be assembled to obtain telomere-containing fragments, including: Searching for telomere sequences in the sequencing data by a string search method; For each telomere sequence, starting from the start of the telomere sequence, a fragment of a preset length is taken to obtain a subsequence; Count the occurrence times of telomere sequences in the intercepted subsequences; If the number of times the telomere sequence appears in the subsequence reaches or exceeds the preset number, the subsequence is output, and the output subsequence is the telomere-containing fragment.

3. The genome assembly optimization method based on telomere sequence detection and overlapping network graph reconstruction according to claim 2, characterized in that: The method of taking a preset length segment to intercept a subsequence further comprises: The truncation length is calculated based on the starting position of the telomere sequence and the maximum length of the read segment where the telomere sequence is located; The truncation length is compared with the preset length, and the smaller length is selected to truncate the subsequence.

4. The genome assembly optimization method based on telomere sequence detection and overlapping network graph reconstruction according to claim 1, characterized in that: The searching for a potential extension path in the overlapping network graph according to the first connection path comprises: Locating and marking the end connection node of the first connection path in the overlapping network graph; Starting from the marked terminal connection node, all potential extended paths connected to the terminal connection node are traced and extracted along the connection relationship in the overlapping network graph.

5. The genome assembly optimization method based on telomere sequence detection and overlapping network graph reconstruction according to claim 4, characterized in that: The step of selecting the path where the telomere-containing fragment is located from the potential extension path to perform telomere splicing on the first contig sequence to generate a telomere-containing contig sequence comprises: Determining whether each potential extension pathway contains the telomere-containing fragment; Using the path where the telomere-containing fragment is located as the target extension path of the first contig sequence; All the parts between the terminal connection node and the telomere end along the target extension path are spliced ​​to the end of the first contig sequence to generate a telomere-containing contig sequence.

6. The genome assembly optimization method based on telomere sequence detection and overlapping network graph reconstruction according to claim 1, characterized in that: After performing telomere splicing on the first contig sequence, the method further comprises: Perform telomere detection on the spliced ​​contig sequence to determine whether the spliced ​​contig sequence contains a completely covered telomere sequence; If the spliced ​​contig sequence contains a completely covered telomere sequence, the spliced ​​contig sequence is used as the final assembly sequence.

7. The genome assembly optimization method based on telomere sequence detection and overlapping network graph reconstruction according to claim 6, characterized in that: The step of judging whether the spliced ​​contig sequence contains a completely covered telomere sequence comprises: Obtain the telomere sequence length of the spliced ​​contig sequence; If the telomere sequence length of the spliced ​​contig sequence is not less than the known telomere length, it is considered that the spliced ​​contig sequence contains a completely covered telomere sequence.

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