A method for assembling the mitochondrial genome of American ginseng

Abstract

The present invention provides a method for assembling the mitochondrial genome of American ginseng, which solves the technical problem that the existing TIPPo method has a high dependence on sequencing depth and requires a high mitochondrial genome coverage depth, otherwise it is difficult to accurately distinguish mitochondrial and nuclear genome fragments. The method can be widely used in the field of plant gene assembly. Specifically, it includes the following steps: inputting initial mitochondrial sequencing data, including second-generation sequencing and third-generation sequencing; assembling and extracting mitochondrial contigs using the second generation, and screening candidate mitochondrial contigs; aligning the third-generation data to the candidate mitochondrial contigs, extracting mitochondrial reads, and screening mitochondrial long reads; assembling the mitochondrial long reads to generate a mitochondrial assembly result; simplifying the mitochondrial assembly result to obtain a graphical mitochondrial genome, correcting the graphical mitochondrial genome, and generating accurate mitochondrial genome data.

Description

Technical Field

[0001] The present invention belongs to the technical field of plant gene assembly, and particularly relates to a method for assembling the mitochondrial genome of American ginseng. Background Art

[0002] Plant mitochondrial genome assembly is an important area of ​​bioinformatics research, with significant application value in fields such as phylogenetics, molecular evolutionary analysis, and germplasm resource development. However, the plant mitochondrial genome (mtDNA) exhibits unique biological characteristics that differ significantly from those of animals or fungi: its genome size generally expands by orders of magnitude (typically 200-2400 kb), contains a high proportion of non-coding repetitive sequences, undergoes frequent dynamic gene rearrangement events, and contains exogenous DNA fragments acquired through horizontal transfer. This complex structural plasticity and dynamic evolutionary characteristics make traditional genome assembly methods (such as de novo assembly or reference genome alignment) susceptible to interference from repetitive sequences, resulting in assembly fragmentation, or misidentification of chimeric sequences due to homologous recombination when analyzing plant mitochondrial genomes, severely limiting the integrity and reliability of the assembly results.

[0003] In 2025, Wenfei Xian and others proposed a new organelle genome assembly software - TIPPo. TIPPo can extract mitochondrial and chloroplast genome sequences from Oxford Nanopore and PacBio sequencing data without relying on the nuclear genome information of related species, and is suitable for mixed genome data analysis. Its core principles include: screening target sequences based on k-mer frequency and coverage depth, and using Nanopore and PacBio data to assemble mitochondrial genomes, thereby resolving complex structural variations (such as inverted repeats, large fragment insertions and deletions, etc.). Compared with PMAT, TIPPo is compatible with Nanopore and PacBio data, while PMAT only supports PacBio HiFi data, making TIPPo suitable for a wider range of third-generation sequencing data types, and able to handle mixed sequencing data and complex genome structures. However, TIPPo is highly dependent on sequencing depth and requires a higher mitochondrial genome coverage depth, otherwise it is difficult to accurately distinguish mitochondrial from nuclear genome fragments. Summary of the Invention

[0004] The purpose of the present invention is to address the deficiencies of the above-mentioned technologies and to provide a method for assembling the mitochondrial genome of American ginseng.

[0005] To this end, the present invention provides a method for assembling the American ginseng mitochondrial genome, comprising the following steps:

[0006] S10: Input initial mitochondrial sequencing data, including second-generation sequencing and third-generation sequencing;

[0007] S20: Use the second generation of assembly and extraction of mitochondrial contigs, and screen candidate mitochondrial contigs;

[0008] S30: Align the three-generation data to the candidate mitochondrial contigs, extract mitochondrial reads, and screen out mitochondrial long reads;

[0009] S40: Assemble the long reads of mitochondria to generate mitochondrial assembly results;

[0010] S50: Simplify the mitochondrial assembly results, correct the simplified results, and generate genome data.

[0011] Furthermore, the steps of assembling and extracting mitochondrial contigs using the second generation and screening candidate mitochondrial contigs are as follows:

[0012] Calculate the GC content of each sequence and evaluate the quality of each sequence;

[0013] Trim low-quality bases and remove low-quality bases;

[0014] Based on the existing plant mitochondrial genome, blastn and Bandage were used to extract candidate mitochondrial contigs.

[0015] Furthermore, the steps of aligning the three-generation data to the candidate mitochondrial contigs, extracting mitochondrial reads, and screening out the mitochondrial long reads are as follows:

[0016] Minimap2 was used to align the three-generation sequencing data to the candidate mitochondrial contigs, and all three-generation reads matching the mitochondrial contigs were screened;

[0017] Reads with alignment length greater than 1000bp and read length greater than 10000bp were screened out as long reads.

[0018] Furthermore, the steps for assembling the long reads of mitochondria and generating the preliminary assembly results of mitochondria are as follows:

[0019] Use Flye to perform de novo assembly of mitochondrial long reads, overlap the long reads and construct an overlap-layout-consensus graph to represent the genome;

[0020] Combine the data fragments together to generate a candidate genome sequence and produce a preliminary genome assembly result;

[0021] The repeated regions are then spliced ​​and positioned to generate the final genome assembly result.

[0022] Furthermore, the steps of simplifying the mitochondrial assembly results, obtaining a graphical mitochondrial genome, and correcting the graphical mitochondrial genome to generate accurate mitochondrial genome data are as follows:

[0023] Remove redundant and repeated regions in the mitochondrial assembly results and delete low-quality pathways;

[0024] Remove complex cross paths, correct the graph into a closed ring structure, and generate a simplified result;

[0025] Pilon was then used to determine the splicing points in the three generations of long-read data to generate a continuous mitochondrial genome;

[0026] Finally, the mitochondrial genome is corrected using NGS data to generate accurate mitochondrial genome data.

[0027] The present invention provides a method for assembling the mitochondrial genome of American ginseng, which has the following beneficial effects:

[0028] Compared to existing mitochondrial genome assembly methods, the hybrid assembly strategy employed in this paper, combining second-generation sequencing (NGS) with third-generation sequencing (TGS), fully leverages the advantages of both sequencing technologies. This strategy leverages the long-read information provided by third-generation sequencing (TGS, PacBio / Nanopore) to ensure the structural integrity of the genome, while simultaneously combining it with the highly accurate short-read data provided by second-generation sequencing (NGS, Illumina) for fine correction. This strategy demonstrates significant advantages in terms of genome integrity, assembly accuracy, and data applicability, successfully achieving a high-quality assembly of the American ginseng mitochondrial genome. BRIEF DESCRIPTION OF THE DRAWINGS

[0029] Figure 1 This is the mitochondrial genome map of American ginseng assembled by the present invention.

[0030] Figure 2 This is the mitochondrial genome map of American ginseng assembled by TIPPo.

[0031] Figure 3 This is the gene distribution map of the American ginseng mitochondrial genome assembled by TIPPo.

[0032] Figure 4 This is the gene distribution map of the American ginseng mitochondrial genome assembled by the present invention.

[0033] Figure 5 This is the mitochondrial genome map of ginseng assembled by the present invention.

[0034] Figure 6 This is the mitochondrial genome map of ginseng assembled by TIPPo.

[0035] Figure 7 This is the mitochondrial genome map of Panax japonicus assembled by the present invention.

[0036] Figure 8 This is the mitochondrial genome map of Panax japonicus assembled by TIPPo.

[0037] Figure 9 This is the mitochondrial genome map of Panax notoginseng assembled by the present invention.

[0038] Figure 10 This is the mitochondrial genome map of Panax notoginseng assembled by TIPPo. DETAILED DESCRIPTION

[0039] The present invention is further described below with reference to the accompanying drawings and specific examples to facilitate understanding of the present invention. The methods used in the present invention are conventional methods unless otherwise specified; the raw materials and devices used are conventional commercially available products unless otherwise specified.

[0040] The present invention provides a method for assembling the mitochondrial genome of American ginseng, comprising the following steps:

[0041] 1) Input sequencing data: including second-generation sequencing (NGS) Illumina paired-end sequencing (PE150 / PE250); third-generation sequencing (TGS) PacBio HiFi or Oxford Nanopore (ONT).

[0042] 2) Second-generation assembly and extraction of mitochondrial contigs (seeds): During next-generation sequencing, quality control (QC) of the raw data is required. Raw data are typically in FastQ format and require preliminary evaluation using quality control tools. FastQC assesses the quality of each sequence, including sequencing quality distribution, quality scores (Phred quality values) at each position, and Q-values ​​to determine sequence accuracy. The GC content of each sequence is calculated; abnormal GC distribution may indicate low quality or contamination. Sequence lengths are also checked to ensure they fall within the expected range. Trimmomatic uses a sliding window technique to trim bases with low quality (Phred values), particularly at the ends of the sequence, with a high proportion of N-bases or adapter contamination, or with excessive low-complexity regions, which may indicate sequencing errors. Bases with quality values ​​below a certain threshold are removed. The high-quality NGS data is then optimized using SPAdes to adjust the k-mer (splicing unit) size to various sizes, typically ranging from 21 to 127, to optimize assembly. Then, with the published plant mitochondrial genome as a reference, blastn and Bandage software were used to extract candidate mitochondrial contigs, which served as seeds for the subsequent three generations of data extraction and assembly.

[0043] 3) Aligning the third-generation data to the second-generation contigs and extracting mitochondrial reads: Minimap2 was used to align the obtained third-generation sequencing data to the high-confidence mitochondrial contigs obtained above by analyzing sequence matching and alignment quality. Long mitochondrial reads (alignment length > 1000bp; read length > 10,000bp) were screened from the third-generation data using a series of screening criteria, including extracting alignment regions related to the mitochondrial genome, selecting all third-generation reads that matched the mitochondrial contigs, and selecting reads with high alignment quality based on a set quality threshold.

[0044] 4) Using Flye to Assemble Mitochondrial Long Reads. Flye performs denovo assembly on mitochondrial long reads: First, the input long read data is preprocessed to remove low-quality or substandard reads. The genome is represented by overlapping the long reads and constructing an overlap-layout-consensus (OLC) graph. Using this graph, Flye combines the data fragments to generate a candidate genome sequence and a preliminary genome assembly. After correctly splicing and positioning these complex repetitive regions, Flye generates the final assembly.

[0045] 5) Bandage manually simplified the mitochondrial genome assembly graph. Redundant and repetitive regions were removed: redundant paths and nodes were deleted to ensure the graph did not contain repetitive parts. Low-quality paths were removed: low-coverage and low-quality paths were removed to optimize the graph quality. Closure and connectivity of the genome were ensured: the graph was corrected to a closed ring structure consistent with the characteristics of the mitochondrial genome. Reasonableness was assessed based on the expected size: if the assembly result did not meet the expected size of the mitochondrial genome, it was corrected promptly. Complex structures were simplified: overly complex intersecting paths were removed to optimize the graph's readability. Annotation information was integrated: irrelevant regions were deleted based on the genome annotation results to ensure the functionality of the assembly graph.

[0046] 6) Pilon Correction: During the assembly process, Pilon uses third-generation long-read data to correct splicing errors generated by short-read data, especially in repetitive regions. Using third-generation long reads to provide continuous long sequences across repetitive regions, Pilon uses the information in the long-read data to determine splicing points, ensuring correct assembly of repetitive regions and generating a continuous mitochondrial genome. Due to the high error rate and complex data processing of third-generation long-read data, and the high throughput and accuracy of second-generation sequencing data, error correction is required using NGS data.

[0047] 7) By converting the obtained genomic data into a graphical representation format, the mitochondrial graphical structure is confirmed, and finally a result with high integrity and accuracy is obtained.

[0048] By analyzing the downloaded raw sequencing data, it was found that there were large differences in the sequencing technologies used in different data sets. In the absence of HiFi high-quality sequencing data, methods such as PMAT are difficult to achieve effective assembly. In addition, even if the data set contains second-generation sequencing or third-generation sequencing data, the assembly results of TIPPo and GetOrganelle are still not ideal, and the genome integrity is poor. When the above three methods failed to successfully assemble the mitochondrial genome, a hybrid assembly strategy combining second-generation sequencing (NGS) and third-generation sequencing (TGS) was adopted, and significantly optimized assembly results were obtained. Compared with TIPPo, PMAT and GetOrganelle, this hybrid strategy greatly improved the integrity and accuracy of the genome. As Figure 1 As shown in Figure 2, it is clear that the TIPPo assembly results contain large, unclosed fragments, while the hybrid assembly strategy achieves a more complete assembly. Assembly methods such as GetOrganelle and PMAT failed to achieve a successful assembly result. This shows that the hybrid assembly strategy is superior to TIPPo in terms of genome integrity, further validating the advantages of this method.

[0049] After assembly, the mitochondrial genome of American ginseng obtained using the dominant hybrid assembly method was larger than both the currently published mitochondrial genome and the mitochondrial genome assembled using TIPPo, as shown in Table 1. The mitochondrial genome assembled using TIPPo was even smaller than the currently published mitochondrial genome, indicating that the contigs obtained during the assembly process using our dominant hybrid assembly method were relatively more comprehensive, and the resulting assembly results were more complete and reliable.

[0050] Table 1: Comparison of the mitochondrial genome sizes of the previously published and assembled American ginseng genomes

[0051]

[0052] In addition, this hybrid assembly strategy not only significantly improves assembly accuracy, but also effectively ensures gene integrity and avoids the loss of key genes during the assembly process. Figure 4 In the assembly results of the American ginseng mitochondrial genome shown in Figure 3 As shown in Figure 2, it causes the loss of some gene copies during the assembly process, such as the cob gene, which loses one repeat copy during the assembly of the mitochondrial genome. Figure 4 As shown, the cob gene has a normal number of duplicate copies, with no loss. Furthermore, TIPPo assembly results in gene fragmentation. For example, during assembly, a 382bp segment of the cox2 gene is split into two segments of 251bp and 132bp, whereas the hybrid assembly strategy results in a complete cox2 gene.

[0053] Furthermore, the hybrid assembly strategy yielded a richer set of genes. For example, the sdh4 gene in Table 2 was confirmed in the second-generation assembly results, as well as the depth of the gene assembly, indicating that the American ginseng mitochondrial genome contains this gene, whereas the published mitochondrial genome had lost this gene during the assembly process. These results further demonstrate that the hybrid assembly strategy is superior to the aforementioned methods in terms of assembly accuracy, enabling more precise reconstruction of the mitochondrial genome structure and providing more reliable foundational data for subsequent gene function studies.

[0054] Table 2: Comparison of gene content of published mitochondrial genomes and the mitochondrial genome assembled in this study

[0055]

[0056] This hybrid assembly strategy has a wider range of applicability and can adapt to different species and sample conditions. When using TIPPo for assembly, the resulting mitochondrial genome showed an open network structure, while PMAT and GetOrganelle showed no results for a long time during the assembly process of Panax species. This indicates that PMAT and GetOrganelle may not be suitable for the mitochondrial genome of American ginseng, and their scope of application has certain limitations. In contrast, the hybrid assembly strategy is compatible with data from different sequencing platforms. It not only successfully assembled a complete and high-quality American ginseng mitochondrial genome, but also further optimized downstream functional annotation and evolutionary analysis. Overall, this hybrid assembly strategy combining second-generation sequencing (NGS) and third-generation sequencing (TGS) is significantly superior to PMAT, TIPPo and GetOrganelle in terms of genome completeness, assembly accuracy and applicability, providing a more efficient, stable and reliable solution for the study of the American ginseng mitochondrial genome.

[0057] In addition, the present invention also provides a comparison of the mitochondrial genome maps of ginseng, panax japonicus and Panax notoginseng assembled by a hybrid assembly strategy and the mitochondria assembled by TIPPo.

[0058] Table 3: Comparison of gene content of published mitochondrial genomes and the mitochondrial genome assembled in this study

[0059]

[0060] The assembly steps of ginseng, japonica ginseng and Panax notoginseng are basically the same as those of American ginseng, so we will not introduce them in detail here. Figure 5-10 As shown, the superiority of this assembly method can be seen from the completeness of the assembly result diagram and the accuracy of the assembly.

[0061] However, the above description is merely a specific embodiment of the present invention and should not be used to limit the scope of implementation of the present invention. Therefore, the replacement of equivalent components, or equivalent changes and modifications made according to the scope of protection of the present invention should still fall within the scope covered by the claims of the present invention.

Claims

1. A method for assembling the mitochondrial genome of American ginseng, characterized in that: The following steps are involved: S10: Input initial mitochondrial sequencing data, including second-generation sequencing and third-generation sequencing; S20: Use the second generation of assembly and extraction of mitochondrial contigs, and screen candidate mitochondrial contigs; S30: Align the three-generation data to the candidate mitochondrial contigs, extract mitochondrial reads, and screen out mitochondrial long reads; Among them, Minimap2 was used to analyze the sequence matching and alignment quality to align the obtained third-generation sequencing data to the mitochondrial contigs; by extracting the alignment regions related to the mitochondrial genome, all third-generation reads that matched the mitochondrial contigs were screened; Reads with alignment length greater than 1000bp and read length greater than 10000bp were screened as long reads; S40: Assemble the long reads of mitochondria to generate mitochondrial assembly results; S50: Simplify the mitochondrial assembly results, obtain a graphical mitochondrial genome, correct the graphical mitochondrial genome, and generate accurate mitochondrial genome data.

2. The method for assembling the American ginseng mitochondrial genome according to claim 1, characterized in that The steps for assembling and extracting mitochondrial contigs using the second generation and screening candidate mitochondrial contigs are as follows: Calculate the GC content of each sequence and evaluate the quality of each sequence; Trim low-quality bases and remove low-quality bases; Based on the existing plant mitochondrial genome, blastn and Bandage were used to extract candidate mitochondrial contigs.

3. The method for assembling the American ginseng mitochondrial genome according to claim 1, characterized in that The steps for assembling mitochondrial long reads and generating preliminary mitochondrial assembly results are as follows: Use Flye to perform de novo assembly of mitochondrial long reads, overlap the long reads and construct an overlap-layout-consensus graph to represent the genome; Combine the data fragments together to generate a candidate genome sequence and produce a preliminary genome assembly result; The repeated regions are then spliced ​​and positioned to generate the final genome assembly result.

4. The method for assembling the American ginseng mitochondrial genome according to claim 1, characterized in that The steps for simplifying the mitochondrial assembly results, obtaining a graphical mitochondrial genome, correcting the graphical mitochondrial genome, and generating accurate mitochondrial genome data are as follows: Remove redundant and repeated regions in the mitochondrial assembly results and delete low-quality pathways; Remove complex cross paths, correct the graph into a closed ring structure, and generate a simplified result; Pilon was then used to determine the splicing points in the three generations of long-read data to generate a continuous mitochondrial genome; Finally, the mitochondrial genome is corrected using NGS data to generate accurate mitochondrial genome data.

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