A method for calculating chromosome structural variation and uniparental disomy information

Abstract

The present invention discloses a method for calculating chromosome structural variation and uniparental disomy information, comprising the following steps: S1, randomly selecting original sequencing files of 10,000 all-foreign single samples, and using bed files supporting illumina sequencing; S2, based on the selected 10,000 all-foreign single samples, representative heterozygous beds are screened out, and the UPD baseline is calculated according to the homozygosity of each heterozygous bed; S3, the test sample is compared with the UPD baseline calculated in step S2 to generate the corresponding UPD result; S4, the UPD calculation result is visualized. The present invention can realize the rapid and comprehensive locking of possible chromosome deletion, duplication, and uniparental disomy, and comprehensively displays the variation form of each chromosome through hidden Markov model prediction and data visualization, thereby realizing the maximum efficient analysis at present.

Description

Technical Field

[0001] The present invention relates to the technical field of chromosome structure analysis, and more specifically to a method for calculating chromosome structure variation and uniparental disomy information. Background Art

[0002] Whole exome sequencing has become a common method for detecting human genetic diseases, covering nearly 6,000 genetic diseases. However, there are still huge challenges in analyzing the test results. Copy number variation is an important part of gene structure variation, which is caused by genome rearrangement. It generally refers to the increase or decrease in the copy number of large genomic fragments with a length of more than 1 kb, mainly manifested as submicroscopic deletions and duplications. Chromosome uniparental disomy is often associated with familial genetic diseases. Each clinical sample analysis needs to analyze these three variations from different angles. Manual analysis of a large number of clinical samples requires a lot of time and effort.

[0003] Currently, the full-length and CNVseq reports available on the market do not have the accompanying drawings that doctors want to see and can understand immediately. In actual work, it is occasionally encountered that non-biological fathers participate in the examination, which may lead to variant sites that are mistakenly identified as "spontaneous mutations", and then their pathogenicity classification may be inappropriately overestimated. Summary of the invention

[0004] The purpose of the present invention is to provide a method for calculating chromosome structural variation and uniparental disomy information, and by selecting representative heterozygous beds to establish a UPD baseline, accurate locking of possible chromosome deletions, duplications, and uniparental disomy variations is achieved.

[0005] To achieve the above object, the present invention provides the following technical solution: a method for calculating chromosome structural variation and uniparental disomy information, comprising the following steps:

[0006] S1, randomly select the original sequencing files of 10,000 all-foreign single samples, and use the bed files provided by Illumina sequencing;

[0007] S2. Based on the selected 10,000 all-foreign single samples, representative heterozygous beds were screened out, and the UPD baseline was calculated according to the homozygosity of each heterozygous bed;

[0008] S3. Compare the test sample with the UPD baseline calculated in step S2 to generate a corresponding UPD result.

[0009] As a further improvement of the present invention, step S2 comprises:

[0010] S201, screening the heterozygous sites of each sample in the original sequencing file, the screening condition types include SNP site, Freq, Filter and SegDup;

[0011] S202, performing interval comparison on the results of all screened samples and the bed files supporting the Illumina sequencing, and selecting representative heterozygous beds.

[0012] As a further improvement of the present invention, the screening conditions in step S201 include screening SNP sites with single base substitution, Freq greater than or equal to 20X and less than or equal to 80X, Filter quality control passed, and SegDup is not equal to the null value of heterozygous sites.

[0013] As a further improvement of the present invention, the method of separately calculating the long arm and the short arm of the chromosome is adopted in S201, and representative heterozygous beds are selected through multiple alignment analysis.

[0014] As a further improvement of the present invention, the step S2 further includes:

[0015] S203, merging the continuous heterozygous bed regions in the representative heterozygous bed selected in step S202.

[0016] As a further improvement of the present invention, the step S2 further includes:

[0017] S204, counting the number of heterozygous sites in each bed region of the heterozygous bed regions merged in step S203, and calculating the homozygosity of each bed region based on the number of heterozygous sites, and calculating the UPD baseline according to the homozygosity of each bed region.

[0018] As a further improvement of the present invention, step S3 includes:

[0019] S301, comparing the heterozygous sites of the test sample with the UPD baseline using annovar software to screen out heterozygous sites with high heterozygosity;

[0020] S302, bringing the result obtained in step S301 into the hidden Markov model, using the method of separately predicting the long arm and short arm of each chromosome to predict the region of heterozygosity loss on each chromosome, and generating a UPD calculation result.

[0021] As a further improvement of the present invention, step S3 further includes:

[0022] S303, sorting the UPD calculation results obtained in step S302 according to chromosomes to obtain continuous ROH;

[0023] S304. Calculate the homozygosity of each group of ROH according to the homozygosity of each bed region in the UPD baseline, adjust the ROH homozygosity according to the number of heterozygous sites in each group, and calculate the p value based on the homozygosity of each group of ROH.

[0024] S305, filtering the UPD calculation results, the filtering condition being data with a chromosome length of more than 2.5M and a P value less than or equal to 1 / 10,000.

[0025] As a further improvement of the present invention, in step S304: the P value refers to the result of multiplying the homozygosity of each bed contained in each group of ROH;

[0026] The adjusting the ROH homozygosity according to the number of heterozygous sites in each group includes calculating the number of heterozygous sites in each group of ROH, and multiplying the P value calculated for other homozygous sites by 10000 to the Nth power, wherein N is the number of heterozygous sites.

[0027] As a further improvement of the present invention, the method further comprises:

[0028] S4, visualization of UPD calculation results;

[0029] R language was used to process the CNV data of all foreign samples, and R program was used to organize the CNV results and UPD results. Chromosome structural variation and uniparental disomy information diagrams were drawn based on the UPD results. The method of drawing male and female samples separately was used to show the variation form of each chromosome of the test sample.

[0030] Beneficial effects of the present invention: The present invention provides a method for calculating UPD, which can accurately lock in possible chromosome deletions, duplications, and uniparental disomy by selecting representative heterozygous beds. The present invention can quickly and comprehensively lock in possible chromosome deletions, duplications, and uniparental disomy, and comprehensively display the variation form of each chromosome through hidden Markov model prediction and data visualization, thereby achieving the most efficient analysis to date. BRIEF DESCRIPTION OF THE DRAWINGS

[0031] Figure 1 A schematic flow chart of a first embodiment of a method for calculating chromosome structural variation and uniparental disomy information of the present invention;

[0032] Figure 2 A schematic flow chart of a second embodiment of a method for calculating chromosome structural variation and uniparental disomy information of the present invention;

[0033] Figure 3 A schematic diagram of the UPD calculation results of male samples in a method for calculating chromosome structural variation and uniparental disomy information of the present invention;

[0034] Figure 4 A schematic diagram of the UPD calculation results of female samples in a method for calculating chromosome structural variation and uniparental disomy information of the present invention;

[0035] Figure 5 A bed file diagram of Illumina sequencing used in a method for calculating chromosome structural variation and uniparental disomy information of the present invention;

[0036] Figure 6 This is a diagram of the upd.tsv file in a method for calculating chromosome structural variation and uniparental disomy information of the present invention. DETAILED DESCRIPTION

[0037] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0038] Reference Figure 1 As shown, a first embodiment of a method for calculating chromosome structural variation and uniparental disomy information. In this embodiment, the method for calculating chromosome structural variation and uniparental disomy information includes the following steps:

[0039] S1. Randomly select the original sequencing files of 10,000 all-foreign single samples and use the bed files provided by Illumina sequencing. The bed files provided by Illumina sequencing are as follows: Figure 5 shown.

[0040] S2. Based on the selected 10,000 all-foreign single samples, representative heterozygous beds were screened out, and the UPD baseline was calculated according to the homozygosity of each heterozygous bed;

[0041] S3, comparing the test sample with the UPD baseline calculated in step S2 to generate a corresponding UPD result;

[0042] S4, Visualization of UPD calculation results.

[0043] like Figure 3 and Figure 4As shown in the figure, the chromosome structural variation and uniparental disomy information diagrams of male and female obtained after visualization of UPD calculation results, respectively, wherein visualization of UPD calculation results includes processing CNV data of all foreign samples using R language, collating CNV results and UPD results using R program, drawing chromosome structural variation and uniparental disomy information diagrams according to UPD results, and using the method of drawing male and female samples separately to show the variation of each chromosome of the test sample.

[0044] Among them, the chromosome structural variation and uniparental diploid information diagram includes three display areas from left to right, namely chromosome number, copy number variation and heterozygosity loss. The copy number variation area shows

[0045] The horizontal coordinate is established based on the copy number, and the vertical coordinate is the segment division along the length of the chromosome. When the coordinate along the X direction is less than 2, it is a chromosome deletion, and when it is greater than 2, it is a chromosome duplication.

[0046] In summary, the present invention provides a method for calculating UPD. By selecting representative heterozygous beds to establish a UPD baseline, accurate locking of possible chromosome deletions, duplications, and uniparental disomy is achieved. The present invention can quickly and comprehensively lock possible chromosome deletions, duplications, and uniparental disomy, and comprehensively display the variation form of each chromosome through hidden Markov model prediction and data visualization, thereby achieving the most efficient analysis to date.

[0047] like Figure 2 As shown, as a further improvement of the present invention, step S2 includes:

[0048] S201, screening the heterozygous sites of each sample in the original sequencing file, the screening condition types include SNP site, Freq, Filter and SegDup;

[0049] The heterozygous sites of each sample were screened. The screening conditions comprehensively considered the SNP sites, sequencing depth, frequency, Freq, Filter, SegDup and other annotation results. The selected sites were more representative. The heterozygous sites detected by the sequencer here were more accurate than the homozygous sites detected. It would be more accurate to give priority to the heterozygous sites to establish the baseline.

[0050] Specifically, the screening conditions in step S201 include screening SNP sites with single base substitution, Freq greater than or equal to 20X and less than or equal to 80X, Filter quality control passed, and SegDup is not equal to the null value of the heterozygous site.

[0051] S202, the results of all the screened samples are compared with the bed files of Illumina sequencing, and representative heterozygous beds are selected. To ensure accuracy, the method of calculating the long arm and short arm of the chromosome separately is adopted in S201, and representative heterozygous beds are selected through multiple alignment analysis.

[0052] As a further improvement of the present invention, the step S2 further includes:

[0053] S203, merging the continuous heterozygous bed regions in the representative heterozygous bed selected in step S202. The continuous heterozygous bed regions are merged. The bed file supporting the Illumina sequencing contains a total of 204618 bed regions. After merging, 33844 representative beds are selected.

[0054] As a further improvement of the present invention, the step S2 further includes:

[0055] S204, counting the number of heterozygous sites in each bed region of the heterozygous bed regions merged in step S203, and calculating the homozygosity of each bed region based on the number of heterozygous sites, and calculating the UPD baseline according to the homozygosity of each bed region.

[0056] As a further improvement of the present invention, step S3 includes:

[0057] S301, comparing the heterozygous sites of the test sample with the UPD baseline using annovar software to screen out heterozygous sites with high heterozygosity;

[0058] S302, bringing the result obtained in step S301 into the hidden Markov model, using the method of separately predicting the long arm and short arm of each chromosome to predict the region of heterozygosity loss on each chromosome, and generating a UPD calculation result.

[0059] As a further improvement of the present invention, step S3 further includes:

[0060] S303, sorting the UPD calculation results obtained in step S302 according to chromosomes to obtain continuous ROHs; (the hidden Markov model can predict which one is ROH and which one is not ROH from the beginning to the end of each chromosome long arm or short arm, and then sorting ROH1 and ROH2 according to the predicted results)

[0061] S304. Calculate the homozygosity of each group of ROH according to the homozygosity of each bed region in the UPD baseline, adjust the ROH homozygosity according to the number of heterozygous sites in each group, and calculate the p value based on the homozygosity of each group of ROH.

[0062] S305, the UPD calculation results are screened, and the screening conditions are data with a chromosome length of more than 2.5M and a P value less than or equal to 1 / 10,000. The smaller the P value, the better the accuracy, and false positives are eliminated. The chromosome length is set to be screened at more than 2.5M to ensure accuracy and eliminate false positives.

[0063] As a further improvement of the present invention, in step S304: the P value refers to the result of multiplying the homozygosity of each bed contained in each group of ROH;

[0064] The adjusting the ROH homozygosity according to the number of heterozygous sites in each group includes calculating the number of heterozygous sites in each group of ROH, and multiplying the P value calculated for other homozygous sites by 10000 to the Nth power, wherein N is the number of heterozygous sites.

[0065] The calculation of UPD for a single sample includes the following steps:

[0066] 1. Compare the heterozygous sites of the sample's test data with the defined baseline using the annovar program. The data obtained after the comparison are heterozygous sites with high heterozygosity.

[0067] 2. The results obtained in the previous step are brought into the hidden Markov model. Here, the method of separately predicting the long arm and short arm of each chromosome is adopted to obtain the area of ​​heterozygosity loss on each chromosome.

[0068] 3. Rearrange the UPD calculation results obtained in the previous step according to the chromosome to obtain continuous ROH.

[0069] 4. Calculate the homozygosity of ROH in each group based on the homozygosity of each bed in the defined baseline. Adjust the ROH homozygosity based on the number of heterozygous sites in each group and take sequencing errors into consideration. Define the p-value of ROH in each group based on the above calculation results.

[0070] 5. Filter the calculated UPD results, with the screening conditions being data above 2.5M and P value less than or equal to 1 / 10,000, to make the screening results more accurate.

[0071] The present invention provides another embodiment, UPD software automation, specifically including:

[0072] The Python language was used to screen the heterozygous sites of clinical samples, and the Annovar annotation was performed according to the defined bed file. The annotated files were sorted and analyzed using the R language. The hidden Markov model was used to predict the UPD regions of heterozygous sites, and the predicted high-risk UPD regions were summarized to generate the upd.tsv file. The upd.tsv file is as follows: Figure 6 shown.

[0073] Determine the UPD pipeline, use the Python language to assemble the Python programs and R programs in each processing module, and use the program loop to perform UPD calculations on all samples at once.

[0074] Determine the CNV exompipline, the CNV exompipline program will automatically call the UPDpipline, and use the Python language to automatically process the data and make statistical graphs for all external CNV data. One command can process all samples, achieving full automation.

[0075] The present invention also includes UPD reliability verification: one thousand all-cause clinical samples are randomly selected for UPD calculation, and the calculation results are statistically analyzed to find that the deletion CNV-positive areas are all accompanied by UPD, and the calculation results are accurate.

[0076] Working principle: The present invention provides a novel method for calculating UPD, which selects bed files supporting illumina sequencing and 10,000 clinical samples of full-length sequencing as the data source for calculating the loss of heterozygosity, compares and analyzes, and selects representative bed regions as heterozygous beds. The 10,000 fully-length clinical samples selected are random samples, and the heterozygous sites of each sample are screened. The screening conditions comprehensively consider the annotation results of SNP sites, Freq, Filter, SegDup, etc., and the selected sites are more representative. In order to ensure the accuracy of UPD calculation, the short arm and long arm are calculated separately, and the defined bed is split according to the gene. The defined bed file is compared and analyzed again with the heterozygous regions of the 10,000 samples, and the proportion of heterozygous sites of each sample in each defined bed file is calculated, and the final defined bed file is obtained according to the final statistical results.

[0077] This solution can quickly and comprehensively identify possible chromosome deletions, duplications, and uniparental disomy variants, and comprehensively display the variation forms of each chromosome through hidden Markov model prediction and data visualization, thus achieving the most efficient analysis currently available.

[0078] Compared with other existing tools, this tool will be more accurate, can save analysts' time and energy to a greater extent, and will also reduce the risk of missing pathogenic variants. The CNVexompipline program can automatically process data, calculate UPD, and map male and female samples for all exome samples. The CNVseqpipline program can automatically process data, map male and female samples for all CNVseq samples. One command can complete all the work, achieving true automation and greatly improving work efficiency.

[0079] The above is only a preferred embodiment of the present invention. It is obvious to those skilled in the art that the present invention is not limited to the details of the above exemplary embodiments, and the present invention can be implemented in other specific forms without departing from the spirit or basic features of the present invention. All technical solutions under the concept of the present invention belong to the protection scope of the present invention. Therefore, no matter from which point of view, the embodiments should be regarded as exemplary and non-restrictive. The scope of the present invention is defined by the attached claims rather than the above description, and it is intended to include all changes within the meaning and scope of the equivalent elements of the claims. Any figure mark in the claims should not be regarded as limiting the claims involved.

Claims

1. A method for calculating chromosome structural variation and uniparental disomy information, characterized in that: The steps include: S1. Randomly select the original sequencing files of 10,000 all-foreign single samples and use the bed files provided by Illumina sequencing; S2. Based on the selected 10,000 all-foreign single samples, representative heterozygous beds were screened out, and the UPD baseline was calculated according to the homozygosity of each heterozygous bed; S3, comparing the test sample with the UPD baseline calculated in step S2 to generate a corresponding UPD result; S4, UPD calculation results visualization; R language was used to process CNV data of all samples, and R program was used to organize CNV results and UPD results. Chromosome structural variation and uniparental disomy information diagrams were drawn based on UPD results. The variation form of each chromosome of the test sample was presented by drawing male and female samples separately. The chromosome structural variation was chromosome deletion and duplication. The step S2 comprises: S201, screening the heterozygous sites of each sample in the original sequencing file, the screening condition types include SNP site, Freq, Filter and SegDup; S202, performing interval comparison on the results of all the screened samples and the bed files provided with Illumina sequencing, and selecting representative heterozygous beds; S203, merging the continuous heterozygous bed regions in the representative heterozygous bed selected in step S202; S204, counting the number of heterozygous sites in each bed region in the heterozygous bed regions merged in step S203, and calculating the homozygosity of each bed region based on the number of heterozygous sites, and calculating the UPD baseline according to the homozygosity of each bed region; The step S3 comprises: S301, comparing the heterozygous sites of the test sample with the UPD baseline using annovar software, and screening out heterozygous sites with high heterozygosity; S302, bringing the result obtained in step S301 into the hidden Markov model, using the method of separately predicting the long arm and short arm of each chromosome to predict the region of loss of heterozygosity on each chromosome, and generating a UPD calculation result.

2. The method for calculating chromosome structural variation and uniparental disomy information according to claim 1, characterized in that: The screening conditions in step S201 include screening SNP sites with single base substitution, Freq greater than or equal to 20X and less than or equal to 80X, Filter quality control passed, and SegDup is not equal to the null value of the heterozygous site.

3. The method for calculating chromosome structural variation and uniparental disomy information according to claim 2, characterized in that: In the S202, a method of separately calculating the long arm and the short arm of the chromosome is adopted, and a representative heterozygous bed is selected through multiple alignment analysis.

4. The method for calculating chromosome structural variation and uniparental disomy information according to claim 3, characterized in that: The step S3 further comprises: S303, sorting the UPD calculation results obtained in step S302 according to chromosomes to obtain continuous ROHs; S304, calculating the homozygosity of each group of ROH according to the homozygosity of each bed region in the UPD baseline, adjusting the ROH homozygosity according to the number of heterozygous sites in each group, and calculating the p value based on the homozygosity of each group of ROH; S305. Filter the UPD calculation results, and the filtering condition is that the chromosome length is greater than 2.5M and the P value is less than or equal to 1 / 10,000.

5. The method for calculating chromosome structural variation and uniparental disomy information according to claim 4, characterized in that: In step S304: the P value refers to the result of multiplying the homozygosity of each bed contained in each group of ROH; The adjusting the ROH homozygosity according to the number of heterozygous sites in each group includes calculating the number of heterozygous sites in each group of ROH, and multiplying the P value calculated for other homozygous sites by 10000 to the Nth power, wherein N is the number of heterozygous sites.

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