CN116497106B - Identification method for maternal pollution in prenatal diagnosis - Google Patents
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Abstract
The invention provides a method for identifying maternal pollution in prenatal diagnosis by using CNV-seq sequencing data, namely, directly using prenatal diagnosis data without additional experiments. The determination of maternal contamination is achieved by using parameters of single chromosome allele frequencies. According to the method, extra peripheral blood of a pregnant woman is not required to be collected, an STR maternal pollution investigation experiment is not required to be added, the maternal pollution can be rapidly identified while the chromosome copy number variation of the amniotic fluid sample is diagnosed, the detection efficiency is improved, and the detection cost is reduced.
Description
Technical Field
The invention relates to a method for identifying sample maternal pollution in prenatal diagnosis.
Background
Prenatal diagnosis is an important way of birth defect prevention and control, but it still has problems of clinical use, and is susceptible to maternal cell contamination of varying degrees due to invasive materials (1). Researches show that the maternal pollution rate in amniotic fluid specimens is as high as 9-26%, and the maternal pollution rate is more than 5%, which can interfere with the detection result of prenatal diagnosis, and cause misdiagnosis or missed diagnosis (2, 3). At present, a common practice is to additionally carry out short tandem repeat (short tandem repeats, STR) and check whether the maternal pollution exists or not through a fluorescent quantitative PCR experiment, and the method needs to additionally extract a pregnant woman blood sample, has a complicated process, can only relatively quantify and has limited sensitivity (4). Therefore, the development of a simple, rapid and accurate method for identifying the maternal pollution has great significance in reducing the cost of prenatal diagnosis and improving the accuracy of prenatal detection. The technology is helpful for reducing birth defects and improving the quality of birth population in China.
Conventional detection items of fetal chromosomes in prenatal diagnosis are classified into: chromosome karyotyping and genome copy number variation detection. Karyotyping is the most commonly used cytogenetic examination means to detect chromosomal abnormalities in number and structure, including balanced structural rearrangements (balanced translocation, rogowski translocation, inversion, etc.), large fragment deletions/duplications, etc., but it is difficult to see chromosomal deletions or duplications of less than 5-10 Mb (5). For detection of deletion and duplication of micro-fragments on chromosomes, genomic copy number variation sequencing (copy number variation sequencing, CNV-seq), whole genome SNP microarray chips (Single Nucleotide Polymorphism array, SNP array) and the like are generally employed. With the progress of molecular genetics, sequencing technology is becoming increasingly sophisticated. The CNV-seq technology has the advantages of wide detection range, high resolution, simple operation, short detection period and the like, and becomes a first-line diagnosis method (6, 7) for prenatal diagnosis.
Common parent source contamination is due to: the prenatal diagnosis method comprises amniocentesis, chorionic puncture sampling, percutaneous cord blood puncture and the like, and in the sampling process, the mixture of maternal peripheral blood, uterine basal decidua tissue and the like in the sample is difficult to be completely avoided, so that the sample is polluted by maternal cells (maternal cell contamination, MCC) (8) with different degrees. Since the subsequent CNV-seq detection has the characteristic of high sensitivity, trace maternal tissue pollution is likely to seriously interfere with the diagnosis result, thereby generating the risk of misdiagnosis. Thus, determining whether an obvious MCC is present in a prenatal sample is critical to prenatal diagnostic accuracy.
The current methods for identifying the presence or absence of MCC in fetal tissue mainly include Kleihaure acid-fast staining, flow cytometry, STR experiments and the like. Kleihaure acid fast staining method is mainly based on the characteristic that fetal hemoglobin is more resistant to acid denaturation than adult hemoglobin, and is used for distinguishing maternal blood from fetal blood (9). The Kleihaure acid-fast staining method is widely applied to clinical detection of neonatal anemia, maternal and infant hemolysis, trauma during pregnancy and the like, and has the advantages of simplicity in operation, low cost and the like. However, once the fetal hemoglobin content of maternal blood is abnormally elevated, such as sickle cell disease or thalassemia, false identification of maternal blood as fetal blood occurs during staining (10-12).
Flow cytometry uses fluorochromes and antibodies to specifically label maternal or fetal cells and performs data processing analysis in combination with multiple parameter signals to distinguish the cells. Compared with Kleihaure acid-fast staining method, flow cytometry is rapid, sensitive and specific, but depends on antibody specificity and flow cytometry, and simultaneously has a large amount of cell loss, so that the flow cytometry is complex in operation, relatively high in cost and not suitable for large-scale popularization (13).
The detection of maternal contamination by means of STR on the chromosome is currently the detection method used routinely in clinic. STRs are widely present in the human genome and are genetic marker sequences with high polymorphism and genetic stability, whose core constitutive sequences are 3-5 bases, and which undergo several to several tens of tandem repeats to constitute a specific DNA fragment genetic marker (14, 15). Fetal samples have one STR allele at each site from both the mother and father. Thus, if the second allele from the mother is present in the fetal sample, this indicates that maternal cell contamination is present in the extracted genetic material (16). However, the specificity of STR sites across different human genomes results in difficult detection of some patient genome segment alleles. Additionally, allele deletions or the presence of rare alleles may lead to STR detection difficulties (17). Meanwhile, the detection time is long, the flow is complicated, and the additional mother blood needs to be reserved, so that the technology is limited in clinical application. There is therefore a great need for an efficient, accurate, rapid, economical, high throughput, low cost method of identifying maternal contamination.
[ reference ] to
1.Giovannopoulou E, Tsakiridis I, Mamopoulos A, Kalogiannidis I, Papoulidis I, Athanasiadis A, et al. Invasive Prenatal Diagnostic Testing for Aneuploidies in Singleton Pregnancies: A Comparative Review of Major Guidelines. Medicina (Kaunas). 2022;58(10).
2.Stojilkovic-Mikic T, Mann K, Docherty Z, Mackie Ogilvie C. Maternal cell contamination of prenatal samples assessed by QF-PCR genotyping. Prenat Diagn 2005;25:79-83.
3.Weida J, Patil AS, Schubert FP, et al. Prevalence of maternal cell contamination in amniotic fluid samples. J Matern Fetal Neona 2017;30:2133-37.
4.Navarro-Bailon A, Carbonell D, Escudero A, Chicano M, Muniz P, Suarez-Gonzalez J, et al. Short Tandem Repeats (STRs) as Biomarkers for the Quantitative Follow-Up of Chimerism after Stem Cell Transplantation: Methodological Considerations and Clinical Application. Genes-Basel. 2020;11(9).
5.Bayani J, and Squire JA. Advances in the detection of chromosomal aberrations using spectral karyotyping. Clin Genet. 2001;59(2):65-73.
6.Dong Z, Xie W, Chen H, Xu J, Wang H, Li Y, et al. Copy-Number Variants Detection by Low-Pass Whole-Genome Sequencing. Curr Protoc Hum Genet. 2017;94:8 17 1-8 6.
7.Wang J, Chen L, Zhou C, Wang L, Xie H, Xiao Y, et al. Prospective chromosome analysis of 3429 amniocentesis samples in China using copy number variation sequencing. Am J Obstet Gynecol. 2018;219(3):287 e1- e18.
8.Lamb AN, Rosenfeld JA, Coppinger J, Dodge ET, Dabell MP, Torchia BS, et al. Defining the impact of maternal cell contamination on the interpretation of prenatal microarray analysis. Genet Med. 2012;14(11):914-21.
9.Martel-Petit V, Petit C, Marchand M, Fleurentin A, Fontaine B, Miton A, et al. Use of the Kleihauer test to detect fetal erythroblasts in the maternal circulation. Prenat Diagn. 2001;21(2):106-11.
10.Bataille P, Petit L, and Winer N. Performance of the Kleihauer Betke test in the prediction of neonatal anemia. J Matern Fetal Neonatal Med. 2022;35(19):3670-6.
11.Das SS, Agarwal P, and Chaudhary R. Gel Technology: An Easy and Useful Method for Estimating Fetomaternal Hemorrhage in the Blood Banks of Developing Nations. Labmedicine. 2010;41(3):147-9.
12.Gereg C, and Fung MK. Assessment of Flow Cytometry and Kleihauer-Betke Method When Calculating Fetomaternal Hemorrhage and Rh Immunoglobulin Dose. Arch Pathol Lab Med. 2022;146(3):271-.
13.Fernandes BJ, von Dadelszen P, Fazal I, Bansil N, and Ryan G. Flow cytometric assessment of feto-maternal hemorrhage; a comparison with Betke-Kleihauer. Prenatal Diag. 2007;27(7):641-3.
14.A collection of ordered tetranucleotide-repeat markers from the human genome. The Utah Marker Development Group. Am J Hum Genet. 1995;57(3):619-28.
15.Hammond HA, Jin L, Zhong Y, Caskey CT, and Chakraborty R. Evaluation of 13 short tandem repeat loci for use in personal identification applications. Am J Hum Genet. 1994;55(1):175-89.
16.Butler JM. Short tandem repeat typing technologies used in human identity testing. Biotechniques. 2007;43(4):ii-v.
17.Budowle B, Masibay A, Anderson SJ, Barna C, Biega L, Brenneke S, et al. STR primer concordance study. Forensic Sci Int. 2001;124(1):47-54.
Disclosure of Invention
The invention provides a method for rapidly identifying parent source pollution based on CNV-seq data. According to the method, maternal peripheral blood does not need to be additionally collected, an additional maternal pollution investigation experiment does not need to be added, CNV-seq sequencing data is utilized for analysis, and maternal pollution can be accurately and rapidly judged.
Specifically, genomic DNA is extracted from amniotic fluid, cord blood or villus samples, library construction and second generation sequencing are performed. And (3) performing data cleaning on the sequencing data of the next machine to obtain pure reading data, comparing the pure reading data with a human reference genome, performing operation to obtain the genotype of the sample, screening high-quality SNP loci, and calculating allele frequency. AFR= |1/2-allele frequency| is defined, and homozygous sites are rejected using the AFR+|1/2 condition. In a pure fetal sample, AFR is theoretically equal to 0. And the AFR of the sample is less than 1/2 after the mixed parent source is polluted. Based on this, the AFR value can be used for detection of MCC. The result of the standard deviation SD can amplify the differences to some extent according to basic mathematical principles.
Compared with the prior art, the invention has the following remarkable progress:
compared with the prior art reported in the literature, the invention uses CNV-seq sequencing data, namely directly uses the data of prenatal diagnosis without additional experiments to identify maternal pollution in prenatal diagnosis. The determination of maternal contamination is achieved by using parameters of single chromosome allele frequencies. The method does not need to additionally collect peripheral blood of pregnant women and does not need to be used as an STR maternal pollution investigation experiment, and can rapidly identify maternal pollution while diagnosing chromosome copy number variation of flow products, amniotic fluid and umbilical blood samples, thereby further improving detection efficiency, reducing detection cost and meeting clinical high-efficiency, accurate, rapid, economic, high-throughput and low-cost diagnosis requirements.
Drawings
The accompanying drawings are included to provide a further understanding of the invention and are incorporated in and constitute a part of this specification, illustrate the invention and together with the embodiments of the invention, serve to explain the invention. In the drawings:
FIG. 1 is a schematic diagram of the principle of high throughput sequencing to identify maternal contamination;
FIG. 2 is SD of each autosomal AFR
Fig. 3 is ROC (subject work profile) plotted against SD of chr16AFR values.
Detailed Description
The preferred embodiments of the present invention will be described below with reference to the accompanying drawings, it being understood that the preferred embodiments described herein are for illustration and explanation of the present invention only, and are not intended to limit the present invention.
Example 1 rapid identification of maternal contamination in flow products and prenatal samples using CNV-Seq
1. Whole genome library building experiments
Genomic DNA was extracted from abortions and prenatal amniotic fluid and cord blood samples, and after DNA purification, library construction was performed. The amplified library products were purified with magnetic beads and sequenced on an upper machine.
2. Sequencing data analysis
The sequencing adapter at the end of the next data was deleted using trim_galore, primers and low quality bases were amplified, resulting in clean read data. Using bwa software, clean reads were aligned onto human reference genome hg 38. Repeated reads resulting from PCR repeat expansion were deleted using the Picard tool.
3. Calculation of allele frequencies
Generating dictionary files for sample genome bam files by using a Picard tool, re-comparing insertion deletion areas in the sample genome bam files by using GATK software, and generating a data set in vcf format to obtain genotypes of the samples. Vcftools were used to screen high quality SNP sites for subsequent analysis. Allele frequencies were calculated using R software using mutant reads/(wild-type reads+mutant reads) ×100%.
4. Calculation of SD value of AFR for identification of maternal contamination
Allele Frequency (AF) is the ratio of variant allele (Alt) to the total allele (Alt+reference gene ref). All the mixed data are removed by using Alt+ref not less than 3, and AFR= |1/2-AF|, and AFR is not less than 1/2 of the homozygous sites are removed. In a pure fetal sample, AFR is theoretically equal to 0. And the AFR of the sample is less than 1/2 after the mixed parent source is polluted. Based on this, the AFR value can be used for detection of MCC (as shown in fig. 1). The result of the standard deviation SD relatively amplifies this difference according to basic mathematical principles.
Example 2 standard deviation of chromosome 16AFR enables rapid identification of maternal contamination
By calculating the standard deviation of AFR on all autosomes of the data of two groups of amniotic fluid samples (13 cases of pollution group and 21 cases of control group), it was found that not all chromosomes can be used to identify maternal pollution, the standard deviation of No. 16 chromosome AFRP<0.001 Best effect of distinguishing control from contaminated groups (as shown in fig. 2). All amniotic fluid sample groupings were verified by stringent STR experiments. The AFR value of SNP of all chromosomes of one sample is calculated, the calculation time is long, and the aim of clinical rapid detection can not be achieved. Therefore, in order to reduce the calculation amount, the invention focuses on a single chromosome, and the identified chr16 chromosome can be used as a typical chromosome, and the standard deviation of the AFR can well distinguish a control group from a pollution group.
Example 3 determination of standard deviation of AFR values using chromosome 16Threshold for identification of maternal contamination
Accordingly, the standard deviation of the No. 16 chromosome AFR is used as a threshold value to set a baseline, SD distribution is studied, an ROC curve is drawn, the AUC is 0.864, the specificity is 0.810, and the sensitivity is 0.769, so that the method has a good prediction effect. Considering that the whole comparison group SD is smaller than the pollution group, the maximum value 0.09213102 of the comparison group SD is selected as a threshold value A, and the minimum value 0.08067486 of the pollution group SD is selected as a threshold value B: if the sample SD to be detected is greater than the threshold A, judging that pollution exists; if the sample SD to be detected is smaller than the threshold B, judging that no pollution exists; if the sample SD to be tested is between the threshold a and the threshold B, the method cannot determine whether there is contamination, and the STR test is required to be performed for verification (as shown in fig. 3).
When the present invention was used to predict new samples, SD of 5 contaminated samples chr16 were 0.1081066,0.1073787,0.1059396,0.1078371,0.09872871, respectively, and all were greater than threshold a, and therefore all were judged to be contaminated, consistent with the results of STR experiments.
It will be apparent to those skilled in the art that various modifications and variations can be made to the present invention without departing from the spirit or scope of the invention. Thus, it is intended that the present invention also include such modifications and alterations insofar as they come within the scope of the appended claims or the equivalents thereof.
Claims (3)
1. A method for identifying maternal contamination in prenatal diagnosis, comprising the steps of:
1) Full genome library building experiments: extracting genome DNA from a sample to be detected, constructing a sequencing library based on the genome DNA, amplifying the sequencing library, and sequencing the amplified library product on the machine;
2) Sequencing data analysis is carried out to obtain reading data;
3) Allele frequencies were calculated: analyzing the read data to obtain genotype of a sample to be detected, generating a vcf format data set, and screening high-quality SNP loci by using vcftools for subsequent analysis; using R software, allele frequencies were calculated using mutant reads/(wild-type reads+mutant reads) ×100%;
wherein, alt+ref is more than or equal to 3, all the mixed data are removed, and then the SNP locus with high quality is obtained by screening; defining AFR= |1/2-allele frequency|, wherein AFR is not equal to 1/2, and eliminating homozygous sites; in a pure fetal sample, AFR is theoretically equal to 0; after the mixed parent source is polluted, the AFR of the sample is less than 1/2;
4) Calculating the SD value of the AFR of the heterozygous SNP locus of the sample to be detected on chromosome 16 for identifying maternal pollution;
setting a base line by taking the standard deviation of AFR of heterozygous SNP loci on No. 16 chromosomes of a pure fetal sample control group and a maternal pollution group as a threshold value, and drawing an ROC curve; selecting the maximum SD value of a pure fetal sample control group as a threshold A and the minimum SD value of a maternal pollution group as a threshold B;
5) Identification of maternal contamination: if the SD value of the sample to be detected is greater than the threshold value A, judging that the parent source pollution exists; if the SD value of the sample to be detected is less than the threshold B, judging that no parent source pollution exists; if the SD value of the sample to be detected is between the threshold A and the threshold B, whether the parent source pollution exists or not cannot be judged, and STR experiments are required to be sent for verification.
2. The method of claim 1, wherein step 1) comprises extracting genomic DNA from amniotic fluid or cord blood, villus, and sequencing library construction using the fransngs Tn5 DNA Library Prep Kit kit; the library construction procedure was as follows: the DNA fragmentation and linker insertion are completed through Tn5 transposition and digestive enzyme treatment; the magnetic beads select fragmented DNA fragments, and the DNA fragments are added with index sequence primers to carry out library amplification; and (5) purifying the amplified products of the library by using magnetic beads, mixing multiple samples, and sequencing by using a machine.
3. The method of claim 1, wherein step 2) comprises deleting sequencing adaptors at the lower data end using trim_gap, amplifying primers and low quality bases to obtain clean read data; using bwa software, clean reads were aligned onto human reference genome hg 38; repeated reads resulting from PCR amplification were deleted using the Picard tool.
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