Method, device, medium and program product for detecting mitochondrial genes

Abstract

The present invention relates to a method, device, medium and program product for detecting mitochondrial genes. The method comprises: breaking the mitochondrial reference genome into sequence fragments of different lengths; comparing the broken sequence fragments with the known mitochondrial genome and the self-tested mitochondrial genome respectively, so as to screen out candidate sequence fragments that meet the predetermined coverage conditions; screening out candidate primers based on at least the optimal PCR annealing temperature, GC content and Gibbs free energy variation value of the candidate sequence fragments themselves and the sequences between every two candidate sequence fragments; and screening out two pairs of candidate primer pairs based on the full-length genome coverage of the candidate primers for the mitochondrial genome, so as to determine the target primers for detecting mitochondrial genes. The present invention can significantly improve the detection rate for low-frequency and large-fragment deletion variations.

Description

Technical Field

[0001] The present invention relates generally to biological information processing, and in particular, to methods, computing devices, computer storage media, and computer program products for detecting mitochondrial genes. Background Art

[0002] Mitochondria are organelles within cells that have their own cytoplasmic DNA (mtDNA). Unlike nuclear DNA, mtDNA is inherited through the maternal line and has the characteristics of multiple copies, high heteroplasmy, and high mutation rate. The human mitochondrial genome is 16569bp long and has a double-stranded closed circular structure. Since recombination does not occur during cell division and the relatively high mutation rate of mtDNA, differences in mtDNA sequences between individuals lead to mitochondrial diversity. These differences are affected by many factors, such as the degree of exposure to mutagens and the efficiency of DNA repair mechanisms.

[0003] Mitochondrial diseases are a group of genetic diseases characterized by mitochondrial dysfunction, caused by mutations in genes in nuclear DNA (nDNA) and mitochondrial DNA (mtDNA) that encode mitochondrial structural proteins or proteins involved in mitochondrial function. The main pathogenic mtDNA variants include point variants and large deletion variants.

[0004] Traditional methods for detecting mitochondrial genes are based on, for example, first-generation sequencing and high-throughput sequencing. Since first-generation sequencing can only detect regions of about 1K each time, if the full length of the mitochondria is to be detected, it is necessary to repeat the test about 20 times, which is time-consuming and labor-intensive, and has high requirements for sample size. As for high-throughput sequencing methods, they are mainly mitochondrial detection methods based on probe capture or multiple primer amplification. Due to the characteristics of high-throughput sequencing technology, it cannot guarantee that each region of the full-length mitochondria measured is uniform, resulting in missed detection of low-frequency large-fragment deletion variants. Therefore, it is difficult to improve the detection rate of low-frequency large-fragment deletion variants. As a result, it is impossible to provide more reliable technical support for the early diagnosis and personalized treatment of mitochondrial diseases.

[0005] In summary, the shortcomings of traditional methods for detecting mitochondrial genes are that it is difficult to effectively improve the detection rate of low-frequency large-fragment deletion variants. Summary of the invention

[0006] The present invention provides a method for detecting mitochondrial genes, a computing device, a computer storage medium and a computer program product, which can significantly improve the detection rate of low-frequency large-segment deletion variations.

[0007] According to the first aspect of the present invention, a method for detecting mitochondrial genes is provided. The method comprises: breaking the mitochondrial reference genome into sequence fragments of different lengths; comparing the broken sequence fragments with the known mitochondrial genome and the self-tested mitochondrial genome, respectively, so as to screen out candidate sequence fragments that meet the predetermined coverage conditions; screening out candidate primers based on at least the optimal PCR annealing temperature, GC content and Gibbs free energy variation value of the candidate sequence fragments themselves and the sequence between every two candidate sequence fragments; and screening out two pairs of candidate primer pairs based on the full-length genome coverage of the candidate primers for the mitochondrial genome, so as to determine the target primers for detecting mitochondrial genes.

[0008] According to a second aspect of the present invention, a computing device is also provided, comprising: a memory configured to store one or more computer programs; and a processor coupled to the memory and configured to execute the one or more programs so that the device performs the method of the first aspect of the present invention.

[0009] According to a third aspect of the present invention, a non-transitory computer-readable storage medium is further provided, wherein machine-executable instructions are stored on the non-transitory computer-readable storage medium, and when the machine-executable instructions are executed, the machine executes the method of the first aspect of the present invention.

[0010] According to a fourth aspect of the present invention, a computer program product is further provided, wherein a computer program is stored thereon, and when the computer program is executed by a machine, the method according to the first aspect of the present invention is implemented.

[0011] In some embodiments, based on the full-length genome coverage of the candidate primers for the mitochondrial genome, two pairs of candidate primer pairs are screened out to determine the target primers for detecting mitochondrial genes, including: comparing the characterization data about the full-length genome coverage of the candidate primers for the mitochondrial genome to determine the candidate primer pairs among the candidate primers; determining whether there is an intersection between the candidate primer pairs and the known mutation sites and regions of the mitochondrial genes; and in response to determining that there is no intersection between the candidate primer pairs and the known mutation sites and regions of the mitochondrial genes, determining the candidate primer pairs as target primers for detecting mitochondrial genes.

[0012] In some embodiments, the method for detecting mitochondrial genes also includes: obtaining all human mitochondrial nucleic acid sequences with a sequence length greater than a predetermined length threshold from a predetermined database to obtain a known mitochondrial genome; and obtaining self-assembled existing human mitochondrial high-throughput sequencing data to obtain a self-tested mitochondrial genome.

[0013] In some embodiments, the interrupted sequence fragments are compared with known mitochondrial genomes and self-tested mitochondrial genomes, respectively, to screen out candidate sequence fragments that meet predetermined coverage conditions, including: counting the frequency of occurrence of each sequence fragment in all known mitochondrial genomes and self-tested mitochondrial genomes; sorting the frequency of occurrence of each sequence fragment to obtain sequence fragments that meet predetermined frequency threshold conditions; and filtering out sequence fragments that have intersections with known mitochondrial pathogenic sites or pathogenic regions among the sequence fragments that meet the predetermined frequency threshold conditions, so as to obtain candidate sequence fragments that meet the predetermined coverage conditions.

[0014] In some embodiments, screening out candidate primers based on the optimal PCR annealing temperature, GC content and Gibbs free energy variation value of the candidate sequence fragments themselves and the sequence between every two candidate sequence fragments includes: screening out candidate sequence fragments suitable for primers based on the optimal PCR annealing temperature, GC content and Gibbs free energy variation value of the candidate sequence fragments themselves; and screening out candidate primers based on the length, optimal PCR annealing temperature, GC content and Gibbs free energy variation value of the sequence between the screened candidate sequence fragments suitable for primers.

[0015] In some embodiments, the method for detecting mitochondrial genes also includes: obtaining a predetermined number of test samples; and calculating the average depth of each pair of target primers in each test sample in the predetermined number of test samples to determine an amplification efficiency assessment value for each pair of target primers.

[0016] In some embodiments, the method for detecting mitochondrial genes also includes: for the sample to be tested, using target primers to perform full-length mitochondrial amplification to collect amplification products; performing ultrasonic fragmentation on the collected amplification products to obtain sequencing data; determining the type of variation detected; in response to determining that the type of variation detected is a single nucleotide polymorphism variation and / or an insertion and deletion variation, aligning the sequencing data after quality control to the reference mitochondrial genome to perform variation detection directly based on the alignment result; and in response to determining that the type of variation detected is a structural variation, using the amplification efficiency assessment value to correct the depth of the target primer of the sample to be tested, so as to perform variation detection based on the corrected depth.

[0017] In some embodiments, the structural variation is a large-fragment deletion variation, and variation detection based on the corrected depth includes: determining whether there are mitochondrial fusion breakpoints; in response to determining the presence of mitochondrial fusion breakpoints, counting the ratio of the depth between the mitochondrial fusion breakpoints to the depth of other regions; determining whether the ratio of the depth between the mitochondrial fusion breakpoints to the depth of other regions is greater than a predetermined ratio threshold.

[0018] In some embodiments, the method for detecting mitochondrial genes also includes: in response to determining that the ratio of the depth between mitochondrial fusion breakpoints to the depth of other regions is greater than a predetermined ratio threshold, determining the presence of variant sites and regions; and based on a predetermined variant database, screening the determined variant sites and regions to obtain pathogenic variant sites.

[0019] This Summary is provided to introduce a selection of concepts in a simplified form that are further described below in the Detailed Description. This Summary is not intended to identify key features or essential features of the invention, nor is it intended to limit the scope of the invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] Figure 1 A schematic diagram of a computing device for implementing a method for detecting mitochondrial genes according to an embodiment of the present invention is shown.

[0021] Figure 2 A schematic diagram of non-conserved positions on the NC_012920.1 mitochondrial genome according to an embodiment of the present invention is shown.

[0022] Figure 3 A flow chart of a method for detecting mitochondrial genes according to an embodiment of the present invention is shown.

[0023] Figure 4 A schematic diagram of primer design according to an embodiment of the present invention is shown.

[0024] Figure 5 A schematic diagram showing the amplification of the target primers determined according to an embodiment of the present invention in urine samples, muscle samples and blood samples is shown.

[0025] Figure 6 A flow chart of a method for screening target primers according to an embodiment of the present invention is shown.

[0026] Figure 7 A flow chart of a method for obtaining pathogenic variant sites according to an embodiment of the present invention is shown.

[0027] Figure 8 A schematic diagram showing the results of large fragment deletions with low mutation frequency and high mutation ratio detected by the method according to an embodiment of the present invention is shown.

[0028] Fig. 9 The block diagram of an electronic device suitable for implementing the embodiments of the present invention is schematically shown.

[0029] In the various drawings, the same or corresponding reference numerals represent the same or corresponding parts. DETAILED DESCRIPTION

[0030] The preferred embodiments of the present invention will be described in more detail below with reference to the accompanying drawings. Although the preferred embodiments of the present invention are shown in the accompanying drawings, it should be understood that the present invention can be implemented in various forms and should not be limited by the embodiments set forth herein. On the contrary, these embodiments are provided to make the present invention more thorough and complete, and to fully convey the scope of the present invention to those skilled in the art.

[0031] As used herein, the term "including" and its variations mean open inclusion, i.e., "including but not limited to". Unless otherwise stated, the term "or" means "and / or". The term "based on" means "based at least in part on". The terms "an example embodiment" and "an embodiment" mean "at least one example embodiment". The term "another embodiment" means "at least one additional embodiment". The terms "first", "second", etc. may refer to different or the same objects.

[0032] As described above, the traditional method for detecting mitochondrial genes has the disadvantage that it is difficult to effectively improve the detection rate of low-frequency large-fragment deletion variants.

[0033] For example, in the traditional mitochondrial high-throughput sequencing method based on library construction without PCR (i.e., PCR free), mitochondrial enrichment primers (which use one-step PCR to amplify the full length) are used. Common primer screening methods include, for example, querying the conserved genes of mitochondria, designing primers at the conserved genes, and screening through tedious wet experiments. This is because although the functions of conserved genes are conserved, due to the existence of synonymous codons, the corresponding genomic sequences are not completely consistent. If the primers are designed at these non-conserved synonymous codon positions, it will affect the amplification effect, thereby affecting the detection of mitochondrial mutations. For traditional PCR-free-based full-length amplification and high-throughput mitochondrial detection methods or kits, on the one hand, they fail to fully consider the impact of the diversity of mitochondrial variation on detection when designing primers for full-length amplification. If there are diversity sites on the designed primers or there are large-fragment deletion variation on some mitochondria, it will affect the amplification effect, thereby affecting the detection performance and even causing false negative results. On the other hand, in variation detection, there is no good detection strategy for the detection of large-fragment deletions, especially for the detection of low-frequency large fragments, which is often interfered by the heterogeneity of the system and leads to false negative test results.

[0034] Therefore, the traditional method for detecting mitochondrial genes has the disadvantage that it is difficult to effectively improve the detection rate of low-frequency large-fragment deletion variants.

[0035] In order to at least partially solve one or more of the above problems and other potential problems, an exemplary embodiment of the present invention proposes a method for detecting mitochondrial genes. In this method, the mitochondrial reference genome is broken into sequence fragments of different lengths; the broken sequence fragments are compared with the known mitochondrial genome and the self-tested mitochondrial genome respectively, so as to screen out candidate sequence fragments that meet the predetermined coverage conditions; at least based on the optimal PCR annealing temperature, GC content and Gibbs free energy variation of the candidate sequence fragments themselves and the sequence between each two candidate sequence fragments, the candidate primers are screened; and based on the full-length genome coverage of the candidate primers for the mitochondrial genome, two pairs of candidate primer pairs are screened to determine the target primers for detecting mitochondrial genes; thus, the present invention analyzes conservative short sequences through smaller sequence fragments and the public mitochondrial genome and the laboratory self-tested mitochondrial genome in primer design, and screens out candidate primer pairs based on the full-length genome coverage of the candidate primers for the mitochondrial genome, which can achieve coverage of diverse human mitochondrial genomes, reduce the probability of experimental failure and avoid the risk of false negatives, thereby effectively improving the detection rate of low-frequency large fragment deletion variations.

[0036] Figure 1 A schematic diagram of a computing device for a method for detecting mitochondrial genes according to an embodiment of the present invention is shown.

[0037] Regarding the computing device 100, it is used, for example, to detect mitochondrial genes. Specifically, the computing device 100 can break the mitochondrial reference genome into sequence fragments of different lengths; compare the broken sequence fragments with the known mitochondrial genome and the self-tested mitochondrial genome, respectively, so as to screen out candidate sequence fragments that meet the predetermined coverage conditions; and screen out candidate primers based at least on the optimal PCR annealing temperature, GC content, and Gibbs free energy variation value of the candidate sequence fragments themselves and the sequences between every two candidate sequence fragments. In addition, the computing device 100 can also screen out two pairs of candidate primer pairs based on the full-length genome coverage of the candidate primers for the mitochondrial genome, so as to determine the target primers for detecting mitochondrial genes.

[0038] In some embodiments, the computing device 100 may have one or more processing units, including dedicated processing units such as GPU, FPGA and ASIC, and general processing units such as CPU. In addition, one or more virtual machines may also be running on each computing device. The computing device 100 includes, for example: a sequence fragment interruption unit 112, a candidate sequence fragment screening unit 114, a candidate primer screening unit 116, and a target primer determination unit 118. The above-mentioned sequence fragment interruption unit 112, the candidate sequence fragment screening unit 114, the candidate primer screening unit 116, and the target primer determination unit 118. Can be configured on one or more computing devices 100.

[0039] The sequence segment breaking unit 112 is used to break the mitochondrial reference genome into sequence segments of different lengths.

[0040] The candidate sequence fragment screening unit 114 is used to compare the interrupted sequence fragments with the known mitochondrial genome and the self-tested mitochondrial genome respectively, so as to screen out the candidate sequence fragments that meet the predetermined coverage conditions.

[0041] The candidate primer screening unit 116 is used to screen candidate primers based on at least the optimal PCR annealing temperature, GC content and Gibbs free energy change value of the candidate sequence fragments themselves and the sequence between every two candidate sequence fragments.

[0042] The target primer determination unit 118 is used to screen out two pairs of candidate primers based on the full-length genome coverage of the candidate primers for the mitochondrial genome, so as to determine the target primers for detecting mitochondrial genes.

[0043] The following will be combined Figure 2 , Figure 3 and Figure 4 A method for detecting mitochondrial genes according to an embodiment of the present invention is described. Figure 3 FIG. 3 is a flow chart of a method 300 for detecting mitochondrial genes according to an embodiment of the present invention. The method 300 may be performed, for example, in Fig. 9 The electronic device 900 described above is executed. Figure 1 The method 300 is executed at the described computing device 100. It should be understood that the method 300 may also include additional actions not shown and / or may omit the actions shown, and the scope of the present invention is not limited in this respect.

[0044] At step 302 , the computing device 100 breaks the mitochondrial reference genome into sequence fragments of different lengths.

[0045] For example, NC_012920.1 is used as a mitochondrial reference genome, and is broken into sequence fragments of different lengths of 15-35 bp. The sequence fragments of different lengths of equal lengths are, for example, multiple sequences of equal length of 15 bp and multiple sequences of equal length of 20 bp.

[0046] At step 304, the computing device 100 compares the interrupted sequence fragments with the known mitochondrial genome and the self-tested mitochondrial genome, respectively, so as to screen out candidate sequence fragments that meet the predetermined coverage condition.

[0047] Regarding the known mitochondrial genome, it is obtained, for example, by obtaining all mitochondrial nucleic acid sequences of humans whose length is greater than a predetermined sequence length threshold from a predetermined database. It should be understood that by analyzing all known public mitochondrial genome sequences about humans, it can be used for conservative sequence identification.

[0048] Regarding the self-tested mitochondrial genome, it refers to, for example, the full-length mitochondrial genome sequence marked with variant site information and conserved site information obtained through sequence assembly, sequence analysis and annotation of existing normal human mitochondrial sequencing data. In some embodiments, the self-tested mitochondrial genome is obtained by analyzing laboratory-assembled, existing, and large-sample normal human mitochondrial data obtained by other methods, which can serve as a supplement to the identification of conserved sequences.

[0049] For example, the conservation of each sequence fragment (kmer) of each length in the known mitochondrial genome and the self-tested mitochondrial genome is evaluated separately.

[0050] Specifically, the computing device 100 uses bowtie2, bwa, blast and other alignment tools to align each sequence fragment of each length to the known mitochondrial genome downloaded from the NCBI database and the laboratory self-tested mitochondrial genome (for example, the alignment threshold is set to 100%), and counts the occurrence frequency (i.e., conservation rate) of each sequence fragment in all known mitochondrial genomes and self-tested mitochondrial genomes, and sorts the sequence fragments according to the occurrence frequency to obtain sequence fragments with an occurrence frequency greater than or equal to 95% (i.e., highly conserved sequence fragments). Afterwards, the computing device 100 screens out sequence fragments that have intersections with known mitochondrial pathogenic sites and regions in the highly conserved sequence fragments to obtain candidate sequence fragments.

[0051] Known mitochondrial pathogenic sites and regions, such as the collected and published information on mitochondrial disease sites and regions, can be used as a supplement to the identification of conserved sequences. It should be understood that there are many mutation sites and deletion fragments distributed throughout the mitochondrial genome, and when designing primers, it is necessary to avoid primers falling on these regions. Figure 2 Schematic diagram of the non-conserved positions of the NC_012920.1 mitochondrial genome according to an embodiment of the present invention is shown. Figure 2As shown, marker 414 indicates the position of the point mutation (SNP variation). Marker 412 indicates the position of the deletion variation (deletion variation). In addition, marker 416 indicates ribosomal RNA (Ribosomal RNA, rRNA). Marker 420 indicates transfer RNA (TransferRNA, tRNA). Marker 418 indicates the coding sequence (CDS) of the gene. For example, when designing primers, it is necessary to avoid the primers falling on the positions of the known point mutations (SNP variations) and deletion variations (deletion variations) shown in the figure.

[0052] At step 306 , the computing device 100 selects candidate primers based at least on the optimal PCR annealing temperature, GC content, and Gibbs free energy variation value of the candidate sequence fragments themselves and the sequence between every two candidate sequence fragments.

[0053] For example, the computing device 100 screens out candidate sequence fragments suitable for primers based on the GC content, optimal PCR annealing temperature (Tm value) and Gibbs free energy change value (ΔG value) of the sequence fragments themselves; and screens out candidate primers based on the length, GC content, Tm value and ΔG value of the sequences between the candidate sequence fragments suitable for primers.

[0054] At step 308 , the computing device 100 selects two candidate primer pairs based on the full-length genome coverage of the candidate primers for the mitochondrial genome, so as to determine the target primers for detecting mitochondrial genes.

[0055] For example, two pairs of primers with high scores for covering the full-length genome of the mitochondrial genome and no intersection with known mitochondrial pathogenic sites and regions are selected from the candidate primer pairs to determine the target primers. For example, the first pair of upstream primers is CACACGTTCCCCTTAAATAAGACATCAC (SEQ ID NO: 1), and the downstream primer is CCGCCTCTTCACGGGCAGGTCAATTTCACTGGT (SEQ ID NO: 2). The second pair of primers has an upstream primer of CTTATTTAAGGGGAACGTGTGGGC (SEQID NO: 3) and a downstream primer of GAGGCGGGCATAACACAGCAAGACGAGAAGACC (SEQ ID NO: 4).

[0056] the following Figure 4 A schematic diagram of primer design according to an embodiment of the present invention is shown. Figure 4 Specifically shown are the known pathogenic variant sites, large fragment deletions, and the approximate locations of primer design on the mitochondrial reference genome NC_012920.1. Figure 4As shown, the multiple "thin lines" indicated by the marker 414 indicate, for example, the position of a point mutation (SNP variation). It should be understood that mutations (such as the position of a point mutation) should be avoided when designing primers. The marker 412 indicates the position of a deletion variation. In addition, the marker 416 indicates ribosomal RNA (ribosomal RNA, rRNA). The marker 420 indicates transfer RNA (transfer RNA, tRNA). The marker 418 indicates the coding region (Coding sequence, CDS) of the gene. The markers 410-1 and 410-2 indicate the amplification products of the two primer pairs, respectively. Figure 4 The dotted box in the upper left corner is a partial enlarged view of the area indicated by the mark 424. The dotted box specifically shows a primer position of the first primer pair 422-1 and a primer position of the second primer pair 422-2. Figure 4 As shown, label 410-1 indicates the first amplification product amplified by the first primer pair 422-1. Label 410-2 indicates the second amplification product amplified by the second primer pair 422-2. It should be understood that the target primers designed by the present invention avoid functional regions (e.g., CDS of the coding region of a gene, etc.) and mutation positions.

[0057] In order to further verify the determined target primer, the present invention performs a wet experiment to evaluate the target primer. Figure 5 A schematic diagram showing the amplification of target primers determined according to an embodiment of the present invention in urine samples, muscle samples and blood samples. Figure 5 1 to 9 in respectively indicate real samples. Mark 510 indicates a marker, which can indicate the size (eg, length) of the sample amplification product. Figure 5 It can be seen that the target primer plays an amplification role, and according to the comparison with the marker, the length of the amplified product amplified by the target primer is consistent with the expected length. It should be understood that for mitochondrial gene detection, more mitochondrial gene information can be detected in urine samples and muscle samples. Experimental data show that the target primers designed according to the method of the present invention can be stably amplified in three sample types: urine samples, muscle samples and blood samples, thereby significantly improving the efficiency of wet experiment screening. The experimental data further show that the overall coverage of mitochondria by the target primer is above 99.5%.

[0058] The following will be combined Figure 6 A method for screening a target primer according to an embodiment of the present invention is described. Figure 6 FIG. 6 is a flow chart of a method 600 for screening target primers according to an embodiment of the present invention. It should be understood that the method 600 can be used, for example, in Fig. 9The electronic device 900 described above is executed. Figure 1 The method 600 is executed at the described computing device 100. It should be understood that the method 600 may also include additional actions not shown and / or may omit the actions shown, and the scope of the present invention is not limited in this respect.

[0059] At step 602 , the computing device 100 counts the occurrence frequency of each sequence fragment in all known mitochondrial genomes and the self-tested mitochondrial genome.

[0060] For example, the computing device 100 uses alignment tools such as bowtie2, bwa, and blast to align the sequence fragments to all known mitochondrial genomes (e.g., NCBI downloaded genomes) and self-tested mitochondrial genomes (e.g., laboratory self-tested mitochondrial genomes). The alignment threshold is set to 100%, for example. Then, the frequency of each sequence fragment appearing in all known mitochondrial genomes and self-tested mitochondrial genomes (i.e., conservation rate) is counted.

[0061] At step 604 , the computing device 100 sorts the occurrence frequency of each sequence segment to obtain sequence segments that meet a predetermined frequency threshold condition.

[0062] The sequence segment that meets the predetermined frequency threshold condition is, for example, a sequence segment whose occurrence frequency is greater than or equal to 95%.

[0063] For example, the computing device 100 sorts the sequence segments according to the occurrence frequency of each sequence segment, and then obtains sequence segments with an occurrence frequency (or “conservative rate”) greater than 95% as sequence segments that meet a predetermined frequency threshold condition.

[0064] At step 606, the computing device 100 filters out sequence segments that intersect with known mitochondrial pathogenic sites or pathogenic regions from sequence segments that meet a predetermined frequency threshold condition, so as to obtain candidate sequence segments that meet a predetermined coverage condition.

[0065] At step 608, the computing device 100 selects candidate sequence fragments suitable for primers based on the optimal PCR annealing temperature, GC content and Gibbs free energy variation value of the candidate sequence fragments themselves.

[0066] At step 610, the computing device 100 selects candidate primers based on the length of the sequence between the selected candidate sequence fragments suitable for being primers, the optimal PCR annealing temperature, the GC content, and the Gibbs free energy variation value.

[0067] For example, the computing device 100 selects candidate primers based on the length, GC content, Tm value and ΔG value of the sequence between each pair of sequence fragments that are suitable for being primers for all sequence lengths.

[0068] At step 612, the computing device 100 selects two candidate primer pairs based on the full-length genome coverage of the candidate primers for the mitochondrial genome, so as to determine the target primers for detecting mitochondrial genes.

[0069] For example, the computing device 100 selects two pairs of primers covering the entire genome as target primers based on the coverage of the primer pairs for mitochondria.

[0070] In the above scheme, the present invention can achieve comprehensive coverage of the diverse human mitochondrial genome, reduce the probability of experimental failure and avoid the risk of false negatives.

[0071] The following will be combined Figure 7 A method for obtaining pathogenic variant sites according to an embodiment of the present invention is described. Figure 7 FIG. 7 is a flowchart of a method 700 for obtaining a pathogenic variant site according to an embodiment of the present invention. It should be understood that the method 700 can be, for example, Fig. 9 The electronic device 900 described above is executed. Figure 1 The method 700 is executed at the described computing device 100. It should be understood that the method 700 may also include additional actions not shown and / or may omit the actions shown, and the scope of the present invention is not limited in this respect.

[0072] At step 702 , the computing device 100 performs full-length mitochondrial amplification on the sample to be tested using target primers to collect amplification products.

[0073] At step 704 , the computing device 100 performs ultrasonic shearing on the collected amplification products to obtain sequencing data.

[0074] Specifically, for example, the collected amplification products are ultrasonically sheared, and predetermined (for example, but not limited to Illumina) universal sequencing adapters are added to construct a library adapted to a predetermined type (for example, but not limited to Illumina) of sequencing machines for on-machine sequencing to obtain high-throughput sequencing data. It should be understood that this library construction method based on the completion without PCR (i.e., PCR-free library construction method) can avoid false positive SNPs introduced by PCR errors, thereby realizing low-frequency mutation detection of mitochondria.

[0075] At step 706 , computing device 100 determines the type of variation detected.

[0076] It should be understood that the types of variation include, for example, single nucleotide polymorphism variation (SNP variation), insertion / deletion variation (Indel variation) and structural variation (SV), etc. The structural variation is, for example, a deletion variation of a large sequence fragment.

[0077] At step 708, if the computing device 100 determines that the detected variation type is a single nucleotide polymorphism variation and / or an insertion and deletion variation, the sequencing data after quality control is aligned to the reference mitochondrial genome so as to perform variation detection directly based on the alignment result.

[0078] For example, after the data is downloaded, quality control is performed on the acquired high-throughput sequencing data, such as removing low-quality, N-bases, and adapter sequences, to obtain sequencing data after quality control. The sequencing data after quality control is then aligned to the reference mitochondrial genome to determine the type of variation based on the alignment result. In other words, the computing device 100 directly determines the mutation site and region based on the alignment result for the detection of a variation type of single nucleotide polymorphism variation or insertion and deletion variation.

[0079] At step 710, if the computing device 100 determines that the detected variation type is a structural variation, the sequencing depth of the target primer of the sample to be tested is corrected using the amplification efficiency evaluation value, so as to perform variation detection based on the corrected sequencing depth. For example, the computing device 100 determines whether there is a mitochondrial fusion breakpoint based on the corrected sequencing depth.

[0080] Regarding the amplification efficiency evaluation value, it is, for example, used to correct the depth of the target primer of the sample to be tested during structural variation detection. It should be understood that method 700 also includes constructing two sample sets, one of which is a sample set of the sample to be tested. The other is a test sample set formed by historical sample data. In some embodiments, the test sample set includes, for example, but not limited to, 100 test samples, which are used to determine the amplification efficiency evaluation value. In some embodiments, the amplification efficiency evaluation value is determined based on the mean of the amplification efficiency of each test sample in the test sample set including multiple (for example, but not limited to 100) test samples, the median of the amplification efficiency, or other statistical values ​​about the amplification efficiency. It should be understood that the amplification efficiency of different target primer pairs is different, but the ratio of amplification efficiency in a system is relatively fixed, and the amplification efficiency evaluation value of each pair of target primers is obtained based on multiple test samples (for example, 100 cases).

[0081] In some embodiments, the method for determining the amplification efficiency evaluation value of each pair of target primers includes, for example, obtaining a predetermined number of test samples; and calculating the average sequencing depth of each pair of target primers in each test sample in the predetermined number of test samples; and determining the amplification efficiency evaluation value of each pair of target primers based on the average sequencing depth of each pair of target primers. The predetermined number is, for example, but not limited to, greater than 100.

[0082] The following formula (1) exemplifies an algorithm for calculating the average depth of each pair of target primers. Formula (2) exemplifies an algorithm for calculating the amplification efficiency evaluation value of each pair of target primers.

[0083]

[0084] In the above formulas (1) and (2), i represents the serial number of the target primer pair, and n represents the number of the target primer pairs. Represents the abundance of the i-th pair of target primers in the test sample. Represents the depth of the i-th target primer. Represents the amplification efficiency evaluation value of the i-th pair of target primers.

[0085] The following formula (3) exemplifies an algorithm for correcting the depth of the target primer using the amplification efficiency evaluation value to obtain the corrected depth.

[0086]

[0087] In the above formula (3), Represents the corrected depth. is the depth of the i-th pair of target primers. Represents the amplification efficiency evaluation value of the i-th pair of target primers determined.

[0088] It should be understood that by using the amplification efficiency evaluation value to correct the depth of the target primer of the sample to be tested, it is helpful to evaluate whether the breakpoint actually exists.

[0089] Regarding the method for performing variation detection, it includes, for example: the computing device 100 determines whether there is a mitochondrial fusion breakpoint based on the corrected depth; in response to determining that there is a mitochondrial fusion breakpoint, counting the ratio of the depth between the mitochondrial fusion breakpoints to the depth of other regions; determining whether the ratio of the depth between the mitochondrial fusion breakpoints to the depth of other regions is greater than a predetermined ratio threshold; in response to determining that the ratio of the depth between the mitochondrial fusion breakpoints to the depth of other regions is greater than a predetermined ratio threshold, determining that there are variation sites and regions; and based on a predetermined variation database, screening the determined variation sites and regions to obtain pathogenic variation sites.

[0090] Regarding the predetermined ratio threshold, it is, for example, but not limited to, 1%. For example, if the ratio of the depth between the mitochondrial fusion breakpoints to the depth of other regions is determined to be greater than 1%, it is determined that there are mutation sites and regions. Further, the computing device 100 can integrate all determined mutation sites and regions, analyze the position information and functional information of the mutations, for example, use CADD, PolyPhen-2, SIFT and other tools to predict the harmfulness of these mutation sites and regions, so as to rate the determined mutation sites and regions according to the harmfulness prediction information, and finally obtain a list of pathogenic mutation sites and regions.

[0091] In some embodiments, in order to further achieve efficient and accurate clinical impact evaluation of detected mutation sites / regions, the present invention also establishes an automated interpretation system. By logically combining annotation information such as population frequency, disease databases such as mitomap, pathogenicity prediction, and localized variation interpretation databases, two different automated interpretation schemes for point mutations and large fragment deletions are established to automatically output a list of pathogenic mutation sites.

[0092] It should be understood that in traditional methods, after obtaining high-throughput off-machine sequencing data, the original data is generally subjected to quality control, variation detection (SNP, Indel, copy number variation), heteroplasmy analysis, and harmfulness annotation to complete the detection of mitochondrial pathogenic sites and regions. However, the high-throughput sequencing variation detection in traditional methods has limited ability to detect structural variations of circular mitochondria (e.g., fusions and large fragment deletions).

[0093] The present invention establishes a depth correction step to correct the depth of each pair of primers, thereby achieving sequencing depth uniformity, thereby reducing noise interference, improving the detection effect of low-frequency large fragment deletions, and improving the detection of circular mitochondrial structural variations. Figure 8 The schematic diagram of the results of low mutation frequency and high mutation ratio large fragment deletion detected by the method of an embodiment of the present invention is shown. Figure 8 As shown, the mark 430 indicates the measured sequencing depth of the first sample to be tested (i.e., the first sample sequencing depth). The mark 440 indicates the measured sequencing depth of the second sample to be tested (i.e., the second sample sequencing depth). The sequencing depths of the above two samples to be tested can intuitively reflect the actual sequencing results of the amplification products of the designed first primer pair 422-1 and the second primer pair 422-2. Figure 8As shown, mark 432 indicates the first breakpoint position of the first sample sequencing depth (depth_1) (the dotted box in the upper left corner indicates an enlarged view of the first breakpoint position 432, and the arrow connected to the enlarged view indicates the location of the breakpoint position on the first sample sequencing depth 430). Mark 434 indicates the second breakpoint position of the first sample sequencing depth (depth_1) (the dotted box in the lower right corner indicates an enlarged view of the second breakpoint position 434, and the arrow connected to the enlarged view indicates the location of the breakpoint position on the second sample sequencing depth 440). The position of the first breakpoint position 432 of the first sample sequencing depth is, for example, m.5277, and the position of the second breakpoint position 434 is, for example, m.15439. It can be seen that the sequencing depth of the first sample sequencing depth is substantially reduced between its first breakpoint position 432 and the second breakpoint position 434, and there is a missing. Therefore, Figure 8 The first sample sequencing depth (depth_1) indicated in has a variation with a low mutation frequency (the variation is a low mutation ratio, for example, 1.45%). Figure 8 As shown, the mark 442 indicates the first breakpoint position of the second sample sequencing depth (depth_2), which is, for example, m.12108. The mark 444 indicates the second breakpoint position of the second sample sequencing depth (depth_2), which is, for example, m.14413. It can be seen that the sequencing depth of the second sample sequencing depth is significantly reduced between the first breakpoint position 442 and the second breakpoint position 444, and there is a missing. Therefore, Figure 8 The second sample sequencing depth (depth_2) indicated in has a large fragment deletion with the second highest mutation ratio (which is a high mutation ratio, the mutation ratio is, for example, 69.69%). If primers are set at the above-mentioned position where the deletion exists (for example, primers are set at the position between the first breakpoint position 442 and the second breakpoint position 444 of the second sample sequencing depth, or primers are set at the position between the first breakpoint position 432 and the second breakpoint position 434 of the first sample sequencing depth), the mitochondria at the deletion position will not be amplified, which will make the mitochondria at the deletion position difficult to detect, and then cause the deletion to be missed. It should be understood that the present invention can accurately identify variations with low mutation frequencies (for example, identifying low-frequency large fragment deletions at the first sample sequencing depth) by correcting the depth of the target primers using the amplification efficiency evaluation value for structural variation detection. In addition, by Figure 8It can be seen that the positions of the first primer pair 422-1 and the second primer pair 422-2 of the present invention not only avoid the position of the high mutation ratio deletion of the second sample sequencing depth, but also avoid the position of the low mutation ratio deletion of the first sample sequencing depth, thereby significantly improving the detection rate for low-frequency large fragment deletions. In the above scheme, the present invention can significantly improve the detection effect of low-frequency mutations and large fragment deletions by correcting the sequencing depth of the target primers and reducing noise interference.

[0094] Fig. 9 The block diagram of an electronic device 900 suitable for implementing an embodiment of the present invention is schematically shown. The electronic device 900 may be a device for implementing Figure 3 , Figure 6 , Figure 7 The methods 300, 600, and 700 shown. Fig. 9 As shown, the electronic device 900 includes a central processing unit (i.e., CPU 901), which can perform various appropriate actions and processes according to computer program instructions stored in a read-only memory (i.e., ROM 902) or computer program instructions loaded from a storage unit 908 to a random access memory (i.e., RAM 903). In RAM 903, various programs and data required for the operation of the electronic device 900 can also be stored. CPU 901, ROM 902, and RAM 903 are connected to each other via a bus 904. An input / output interface (i.e., I / O interface 908) is also connected to the bus 904.

[0095] Multiple components in the electronic device 900 are connected to the I / O interface 905, including: an input unit 906, an output unit 907, and a storage unit 908. The CPU 901 performs the various methods and processes described above, such as executing methods 300, 600, and 700. For example, in some embodiments, methods 300, 600, and 700 may be implemented as computer software programs, which are stored in a machine-readable medium, such as a storage unit 908. In some embodiments, part or all of the computer program may be loaded and / or installed on the electronic device 900 via the ROM 902 and / or the communication unit 909. When the computer program is loaded into the RAM 903 and executed by the CPU 901, one or more operations of the methods 300, 600, and 700 described above may be performed. Alternatively, in other embodiments, the CPU 901 may be configured to perform one or more actions of the methods 300, 600, and 700 by any other appropriate means (e.g., by means of firmware).

[0096] It should be further noted that the present invention may be a method, an apparatus, a system and / or a computer program product. The computer program product may include a computer-readable storage medium carrying computer-readable program instructions for executing various aspects of the present invention.

[0097] Computer readable storage medium can be a tangible device that can hold and store instructions used by an instruction execution device. Computer readable storage medium can be, for example, but not limited to, an electrical storage device, a magnetic storage device, an optical storage device, an electromagnetic storage device, a semiconductor storage device, or any suitable combination thereof. More specific examples (non-exhaustive list) of computer readable storage medium include: a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), a static random access memory (SRAM), a portable compact disk read-only memory (CD-ROM), a digital versatile disk (DVD), a memory stick, a floppy disk, a mechanical encoding device, for example, a punch card or a convex structure in a groove on which instructions are stored, and any suitable combination thereof. The computer readable storage medium used here is not interpreted as a transient signal itself, such as a radio wave or other freely propagating electromagnetic wave, an electromagnetic wave propagated by a waveguide or other transmission medium (for example, a light pulse by an optical fiber cable), or an electrical signal transmitted by a wire.

[0098] The computer-readable program instructions described herein can be downloaded from a computer-readable storage medium to each computing / processing device, or downloaded to an external computer or external storage device via a network, such as the Internet, a local area network, a wide area network, and / or a wireless network. The network can include copper transmission cables, optical fiber transmissions, wireless transmissions, routers, firewalls, switches, gateway computers, and / or edge servers. The network adapter card or network interface in each computing / processing device receives the computer-readable program instructions from the network and forwards the computer-readable program instructions for storage in the computer-readable storage medium in each computing / processing device.

[0099] The computer program instructions for performing the operation of the present invention may be assembly instructions, instruction set architecture (ISA) instructions, machine instructions, machine-dependent instructions, microcode, firmware instructions, state setting data, or source code or object code written in any combination of one or more programming languages, including object-oriented programming languages, such as Smalltalk, C++, etc., and conventional procedural programming languages, such as "C" language or similar programming languages. The computer-readable program instructions may be executed entirely on the user's computer, partially on the user's computer, as a separate software package, partially on the user's computer, partially on a remote computer, or entirely on a remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computer (e.g., using an Internet service provider to connect through the Internet). In some embodiments, by using the state information of the computer-readable program instructions to personalize an electronic circuit, such as a programmable logic circuit, a field programmable gate array (FPGA), or a programmable logic array (PLA), the electronic circuit may execute the computer-readable program instructions, thereby implementing various aspects of the present invention.

[0100] Various aspects of the present invention are described herein with reference to the flow chart and / or block diagram of the method, device (system), and computer program product according to an embodiment of the present invention. It should be understood that each box of the flow chart and / or block diagram and the combination of each box in the flow chart and / or block diagram can be implemented by computer-readable program instructions.

[0101] These computer-readable program instructions can be provided to a processor in a voice interaction device, a general-purpose computer, a special-purpose computer, or a processing unit of other programmable data processing devices, thereby producing a machine, so that when these instructions are executed by a processing unit of a computer or other programmable data processing device, a device that implements the functions / actions specified in one or more boxes in the flowchart and / or block diagram is generated. These computer-readable program instructions can also be stored in a computer-readable storage medium, and these instructions enable the computer, programmable data processing device, and / or other equipment to work in a specific manner, so that the computer-readable medium storing the instructions includes a manufactured product, which includes instructions for implementing various aspects of the functions / actions specified in one or more boxes in the flowchart and / or block diagram.

[0102] Computer-readable program instructions may also be loaded onto a computer, other programmable data processing apparatus, or other device so that a series of operating steps are performed on the computer, other programmable data processing apparatus, or other device to produce a computer-implemented process, thereby causing the instructions executed on the computer, other programmable data processing apparatus, or other device to implement the functions / actions specified in one or more boxes in the flowchart and / or block diagram.

[0103] The flow chart and block diagram in the accompanying drawings show the possible architecture, function and operation of the equipment, method and computer program product according to multiple embodiments of the present invention. In this regard, each square box in the flow chart or block diagram can represent a part of a module, program segment or instruction, and a part of this module, program segment or instruction includes one or more executable instructions for realizing the specified logical function. In some alternative implementations, the function marked in the square box can also occur in a sequence different from that marked in the accompanying drawings. For example, two continuous square boxes can actually be executed substantially in parallel, and they can sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each square box in the block diagram and / or flow chart, and the combination of the square boxes in the block diagram and / or flow chart can be implemented with a dedicated hardware-based system that performs the specified function or action, or can be implemented with a combination of special hardware and computer instructions.

[0104] The embodiments of the present invention have been described above, and the above description is exemplary, not exhaustive, and is not limited to the disclosed embodiments. Many modifications and variations will be apparent to those of ordinary skill in the art without departing from the scope and spirit of the described embodiments. The selection of terms used herein is intended to best explain the principles of the embodiments, practical applications, or technical improvements in the market, or to enable other persons of ordinary skill in the art to understand the embodiments disclosed herein.

[0105] The above are only optional embodiments of the present invention and are not intended to limit the present invention. For those skilled in the art, the present invention may have various modifications and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. A method for detecting mitochondrial genes, characterized in that: include: The mitochondrial reference genome was broken into sequence fragments of different lengths; The interrupted sequence fragments are respectively compared with the known mitochondrial genome and the self-tested mitochondrial genome to screen out candidate sequence fragments that meet the predetermined coverage conditions, wherein the screening out candidate sequence fragments that meet the predetermined coverage conditions includes: counting the occurrence frequency of each sequence fragment in all known mitochondrial genomes and the self-tested mitochondrial genome; sorting the occurrence frequency of each sequence fragment to obtain sequence fragments that meet the predetermined frequency threshold condition; and filtering out sequence fragments that have intersections with known mitochondrial pathogenic sites or pathogenic regions from the sequence fragments that meet the predetermined frequency threshold condition, so as to obtain candidate sequence fragments that meet the predetermined coverage condition; Screening candidate primers based on at least the optimal PCR annealing temperature, GC content and Gibbs free energy change value of the candidate sequence fragments themselves and the sequence between every two candidate sequence fragments; and Based on the full-length genome coverage of the candidate primers for the mitochondrial genome, two pairs of candidate primer pairs are screened out to determine the target primers for detecting mitochondrial genes, wherein based on the full-length genome coverage of the candidate primers for the mitochondrial genome, two pairs of candidate primer pairs are screened out to determine the target primers for detecting mitochondrial genes, including: comparing the characterization data about the full-length genome coverage of the candidate primers for the mitochondrial genome to determine the candidate primer pairs among the candidate primers; determining whether there is an intersection between the candidate primer pairs and the known mutation sites and regions of the mitochondrial genes; and in response to determining that there is no intersection between the candidate primer pairs and the known mutation sites and regions of the mitochondrial genes, determining the candidate primer pairs as the target primers for detecting mitochondrial genes.

2. The method according to claim 1, characterized in that Also includes: Obtaining from a predetermined database all mitochondrial nucleic acid sequences of humans whose sequence length is greater than a predetermined length threshold, so as to obtain a known mitochondrial genome; as well as Obtain self-assembled existing, human mitochondrial high-throughput sequencing data to obtain a self-tested mitochondrial genome.

3. The method according to claim 1, characterized in that Based on the optimal PCR annealing temperature, GC content and Gibbs free energy change value of the candidate sequence fragments themselves and the sequence between each two candidate sequence fragments, the candidate primers screened include: Based on the optimal PCR annealing temperature, GC content and Gibbs free energy change value of the candidate sequence fragments themselves, the candidate sequence fragments suitable for primers are screened; and Candidate primers are screened out based on the length of the sequences between the candidate sequence fragments that are screened out to be suitable for primers, the optimal PCR annealing temperature, the GC content and the Gibbs free energy change value.

4. The method according to claim 1, characterized in that Also includes: obtaining a predetermined number of test samples; as well as The average depth of each pair of target primers in each test sample in a predetermined number of test samples is counted to determine an evaluation value of the amplification efficiency of each pair of target primers.

5. The method according to claim 4, characterized in that Also includes: For the sample to be tested, the target primers are used to perform full-length mitochondrial amplification so as to collect the amplification product; Performing ultrasonic shearing on the collected amplification products to obtain sequencing data; Determine the type of variant being detected; In response to determining that the detected variation type is a single nucleotide polymorphism variation and / or an insertion and deletion variation, aligning the sequencing data after quality control to a reference mitochondrial genome, so as to perform variation detection directly based on the alignment result; as well as In response to determining that the detected variation type is a structural variation, the depth of the target primer of the sample to be tested is corrected using the amplification efficiency assessment value, so as to perform variation detection based on the corrected depth.

6. The method according to claim 5, characterized in that The structural variation is a large fragment deletion variation, and variation detection based on the depth after correction includes: Determine if mitochondrial fusion breakpoints are present; In response to determining that there are mitochondrial fusion breakpoints, calculating the ratio of the depths between the mitochondrial fusion breakpoints to the depths of other regions; and Determine whether the ratio of the depth between the mitochondrial fusion breakpoints to the depth of other regions is greater than a predetermined ratio threshold.

7. The method according to claim 6, characterized in that Also includes: In response to determining that a ratio of the depth between mitochondrial fusion breakpoints to the depth in other regions is greater than a predetermined ratio threshold, determining that the variant site and region exist; as well as Based on a predetermined mutation database, the determined mutation sites and regions are screened to obtain pathogenic mutation sites.

8. A computing device comprising: at least one processing unit; At least one memory, the at least one memory being coupled to the at least one processing unit and storing instructions for execution by the at least one processing unit, the instructions, when executed by the at least one processing unit, causing the device to perform the steps of the method according to any one of claims 1 to 7.

9. A computer-readable storage medium having a computer program stored thereon, wherein the computer program implements the method according to any one of claims 1 to 7 when executed by a machine.

10. A computer program product, characterized in that The invention comprises a computer program which, when executed by a machine, performs the method according to any one of claims 1 to 7.

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