WO2017051996A1 - Procédé de détermination d'aneuploïdie chromosomique fœtale de type non invasif - Google Patents

Procédé de détermination d'aneuploïdie chromosomique fœtale de type non invasif Download PDF

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WO2017051996A1
WO2017051996A1 PCT/KR2016/000099 KR2016000099W WO2017051996A1 WO 2017051996 A1 WO2017051996 A1 WO 2017051996A1 KR 2016000099 W KR2016000099 W KR 2016000099W WO 2017051996 A1 WO2017051996 A1 WO 2017051996A1
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average
ratio
chromosome
polynucleotide
test
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Korean (ko)
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윤태균
이병철
박정선
박동윤
이정호
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에스케이텔레콤 주식회사
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    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16B—BIOINFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR GENETIC OR PROTEIN-RELATED DATA PROCESSING IN COMPUTATIONAL MOLECULAR BIOLOGY
    • G16B20/00—ICT specially adapted for functional genomics or proteomics, e.g. genotype-phenotype associations
    • G16B20/10—Ploidy or copy number detection
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16B—BIOINFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR GENETIC OR PROTEIN-RELATED DATA PROCESSING IN COMPUTATIONAL MOLECULAR BIOLOGY
    • G16B20/00—ICT specially adapted for functional genomics or proteomics, e.g. genotype-phenotype associations
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16B—BIOINFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR GENETIC OR PROTEIN-RELATED DATA PROCESSING IN COMPUTATIONAL MOLECULAR BIOLOGY
    • G16B30/00—ICT specially adapted for sequence analysis involving nucleotides or amino acids
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16B—BIOINFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR GENETIC OR PROTEIN-RELATED DATA PROCESSING IN COMPUTATIONAL MOLECULAR BIOLOGY
    • G16B30/00—ICT specially adapted for sequence analysis involving nucleotides or amino acids
    • G16B30/10—Sequence alignment; Homology search
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16B—BIOINFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR GENETIC OR PROTEIN-RELATED DATA PROCESSING IN COMPUTATIONAL MOLECULAR BIOLOGY
    • G16B20/00—ICT specially adapted for functional genomics or proteomics, e.g. genotype-phenotype associations
    • G16B20/20—Allele or variant detection, e.g. single nucleotide polymorphism [SNP] detection

Definitions

  • a non-invasive fetal chromosome analysis method for determining fetal chromosome aneuploidy using chromosome sequencing information obtained from biological samples isolated from mothers.
  • Prenatal diagnosis can be divided into invasive and non-invasive diagnosis.
  • Invasive diagnostic methods include amniocentesis, percutaneous umblical blood sampling, chorionic villus, fetal tissue collection, etc. During the examination, the fetus may be shocked to cause miscarriage, disease, or malformation.
  • Non-invasive diagnostic methods have been developed to overcome the problems of these invasive diagnostic methods.
  • cffDNA cell-free fetal DNA
  • NGS Next Generation Sequencing
  • One example provides a non-invasive fetal chromosome analysis method for determining fetal chromosome aneuploidy using chromosome base information obtained from biological samples isolated from mothers.
  • the non-invasive fetal chromosome analysis method is a sequence information analysis method for determining (identifying, identifying, or diagnosing) fetal chromosome aberration, or information on determining the fetal chromosome aneuploidity (discriminating, confirming, or diagnosing). It can be expressed in a way to provide a, they all have the same meaning
  • the non-invasive fetal chromosome analysis method is a specific chromosome (for example, 13, 18 or 21) to determine whether the fetal chromosome aneuploid from the DNA sequence information obtained from the biological sample separated from the mother Chromosome weighted averaged by CV (Coefficient of Variation) value by removing the deviation between experiments by comparing the average number of leads of the chromosome) and the average number of leads present in the merged bins generated from other chromosomes except the chromosome
  • CV Coefficient of Variation
  • DNA sequence information obtained from biological samples separated from the mother may be data generated by whole genome sequencing (WGS) of large-scale parallel sequencing such as next generation sequencing (NGS).
  • WGS whole genome sequencing
  • NGS next generation sequencing
  • the non-invasive fetal chromosome analysis method may comprise the following steps:
  • step 1-2-1 The sequence information of the polynucleotide fragments of the test sample obtained in step 1-1) is compared with a reference genome sequence, and a preset bin number for each chromosome is obtained. Test to have
  • n of the average polynucleotide fragments of the target chromosome to be tested for aneuploidy among the test polynucleotide fragments n selected from chromosomes other than the target chromosome (n is an integer selected from 1 to 21) Obtaining a ratio of the average polynucleotide fragment number of each merged bin generated from the chromosomes to obtain an average test polynucleotide fragment number ratio (the ratio is obtained by the number of merged bins);
  • step 3-1) Among the average test polynucleotide fragment ratios of step 3-1), the values corresponding to the top N cvs having a small CV value are selected and weighted average test is performed.
  • a weighted average reference poly is obtained by using values corresponding to the upper N cv of the CV values selected in step 5-1) with respect to the ratio of the average reference polynucleotide fragment number in step 3-2). Obtaining the nucleotide fragment number ratio; 6) comparing the obtained weighted average test polynucleotide fragment number ratio with the weighted average reference polynucleotide fragment number ratio.
  • the comparing step of 6) above is a weighted average test
  • the polynucleotide fragment number ratio and the weighted average reference polynucleotide fragment number ratio can be used to obtain a Z-score of the desired chromosome.
  • the non-invasive fetal chromosome analysis method after the step 6),
  • steps 1-1) and 1-2) may be performed simultaneously or sequentially in any order, and steps 2-1) and 2-2) may be performed simultaneously or in any order. It may be performed continuously, and steps 3-1 and 3-2) may be performed simultaneously or sequentially without regard to order. ,
  • the non-invasive fetal chromosome analysis method after the steps 2-1) and 2-2) (and before the steps 3-1 and 3-2) for a more accurate result, a)
  • the method may further comprise removing bias of the obtained test polynucleotide fragment number and the reference polynucleotide fragment number.
  • the bias removal step may be performed by applying SVD (Singular Value Decomposition).
  • the chromosome may be an autosomal body, and in humans, it may be selected from the group consisting of chromosomes 1 to 22.
  • the 'purpose chromosome' is a fetal chromosome As a chromosome to check whether or not aneuploidy, for example, human chromosome 13, 18 or 21 may be a chromosome, but is not limited thereto, and may be selected from all the autosomal to check the chromosome aneuploid.
  • the ' n chromosomes selected from other chromosomes except the target chromosome' is a chromosome selected from the other autosomal bodies other than the target chromosome to determine whether the chromosome is a dimeric ( ⁇ is an integer selected from 1 to 21).
  • the test sample isolated from the mother may be blood, plasma, or serum isolated from the mother.
  • Applicable mothers of the noninvasive fetal chromosome analysis methods proposed herein may be mothers whose target chromosomes are normal, i.e., do not have the aneuploidy of the target chromosomes.
  • Another example provides a computer-readable method for determining chromosomal aneuploidies in a fetus comprising the following steps:
  • A-1) The sequence information of polynucleotide fragments of a test sample is mapped to a reference genome sequence, so that the number of test polynucleotide fragments has a predetermined bin number for each chromosome. determining a fragment count)
  • A-2) determining the reference polynucleotide fragment number to have a preset number of bins by using sequence information of the polynucleotide fragments of the reference sample;
  • n number (n is an integer selected from 1 to 21) of the average polynucleotide fragments of the target chromosome to be tested for aneuploidy among the test polynucleotide fragments selected from other chromosomes except the target chromosome Obtaining a ratio of the average polynucleotide fragment number of each merged bin generated from the chromosomes to obtain an average test polynucleotide fragment number ratio;
  • n of the average polynucleotide fragments of the target chromosome to be tested for aneuploidy among the reference polynucleotide fragments n selected from other chromosomes except the target chromosome (n is an integer selected from 1 to 21)
  • step B-1 In the average test polynucleotide fragment number ratio increase of step B-1), the weighted average test was selected by selecting the values corresponding to the top N cv with a low CV value.
  • step D-2 A weighted average reference poly, using values corresponding to the top N cv of the CV values selected in step D-1) with respect to the ratio of the average reference polynucleotide fragment number in step B-2). Obtaining the nucleotide fragment number ratio;
  • step F using the result of comparing the weighted average test polynucleotide fragment number ratio and the weighted average reference polymorph fragment ratio ratio (e.g., ⁇ -score) obtained in step E) to determine whether the fetal target chromosome is aberrant .
  • the weighted average test polynucleotide fragment number ratio e.g., ⁇ -score
  • the computer-readable method is a test obtained after steps A-1) and A- 2 ) (and before steps B-1 and B-2) for a more accurate result.
  • the method may further include removing the bias.
  • the bias removal step may be performed by applying SVD (Singular Value Decomposition).
  • Another example provides a computer program stored in a computer readable storage medium for carrying out the steps of the computer reading method.
  • Another example provides a computer readable storage medium (or recordable medium) containing computer executable instructions for executing the steps of the computer readable method.
  • Aneu ploidy means that the number of target chromosomes differs from the number of normal chromosomes (two), i.e., there are zero, one, or more than three (e.g. three) target chromosomes.
  • This chromosome aberration is important in fetal diagnosis because it is associated with regressive genetic disorders, for example in the presence of three chromosomes 13 on the human chromosome (trisomy 13), Patau syndrome ), Three chromosomes 18 (trisomy I 8 ), Edward syndrome, three chromosomes 2 1 (trisomy 21), Down syndrome is caused.
  • Reference genome sequence refers to a genomic base sequence database representing one species. Current human reference genomes may be constructed based on published (eg, UCSC, NCBI, etc.) reference genomic sequences such as build 37 (GRCh37), hgl8, hgl9, hg38.
  • sequence of each fragment is read out at the same time, and the sequence data thus obtained are combined using bioinformatics to generically decipher sequential genomic information. Additional explanations of large scale parallel sequencing can be found in Rogers and Ventner, Nature (2005) 437: 326–327.
  • Step 1) Obtaining sequence information of polynucleotide fragments covering the entire genome
  • Sequence information of the polynucleotide fragments can be obtained by sequencing template DNA selected from a sample.
  • the polynucleotide fragments are assigned to specific positions on each chromosome through mapping with standard genomic sequences, covering the entire genome.
  • the base sequences of the polynucleotide fragments may be obtained by large scale parallel sequencing methods, such as next generation sequencing.
  • the polynucleotide fragment is a read used for next-generation sequencing, and the polynucleotide fragment number is a read count, and the average
  • the polynucleotide fragment number may be the average read number.
  • the polynucleotide fragments or leads are about 10 to about 2000 bp, about 10 to about lOOOObp, about 10 to about 500 bp, about 10 to about 300 bp, about 10 to about 200 bp, about 25 to about 2000 bp, about 25 to about 1000 bp, about 25 to about 500 bp, about 25 to about 300 bp, about 25 to about 200 bp, about 25 to about 100 bp, about 50 to about 2000 bp, about 50 to about 1000 bp, about 50 to About 500 bp, about 50 to about 300 bp : about 50 to about 200 bp, about 50 to about 100 bp, about 100 to about 2000 bp, about 100 to about 1000 bp, about 100 to about 500 bp, about 100 to about 300 bp, about 100 to It may be about 200bp, about 150 to about 2000 bp, about 150 to about 1000 bp, about 150 to about 500bp, or about 150 to about 300bp in
  • polynucleotide fragments assigned to one or more chromosomes and / or polynucleotide fragments not assigned to any chromosome may be ignored and ignored in later steps.
  • the large scale parallel sequencing can be performed by, for example, 454 platform (Margulies, et al., Nature (2005) 437: 376-380), lllumina Genome Analyzer (or Solexa TM platform), lllumina HiSeq2000, HisSeq2500, MiSeq, NextSeq500, Life Tech Ion PGM, Ion Proton, Ion S5, Ion S5XL, or SOLiD (Applied Biosystems) or Helicos True Single Molecule DNA Sequencing Technology (Harris, et al., Science (2008) 320: 106-109), single molecule from Pacific Biosciences , And / or real-time (SMRT TM) technology or the like.
  • 454 platform Margulies, et al., Nature (2005) 437: 376-380
  • lllumina Genome Analyzer or Solexa TM platform
  • lllumina HiSeq2000, HisSeq2500, MiSeq, NextSeq500 Life Tech Ion P
  • sequencing may be performed by various other known sequencing methods and / or modifications thereof.
  • the test sample isolated from the mother may be blood, plasma, or serum isolated from the mother.
  • the mother may be a human female, and may be a mother whose target chromosome to be identified as chromosome aneuploid is normal, that is, the mother does not have the dimerity of the target chromosome.
  • the blood, plasma, or serum may be separated by a conventional method, and pregnancy 8-12, 12-16, 16-20, 20-24, 24-28, 28-32, 32-36, 36-40, or 40-44 weeks, for example between 8 and 28 weeks gestation.
  • test sample i) performing massively parallel sequencing on the test sample, such as next generation sequencing;
  • the reference sample is a genome pool that already knows 'genome sequence information of the genome and sequence information of polynucleotide fragments covering the entire genome' (hereinafter referred to as 'genome sequence information'), and which does not have the aneuploid of the target chromosome.
  • Genomic sequence information set obtained from mothers may be a genomic sequence obtained from mothers whose fetuses are identified as having no chromosome aneuploids after childbirth among genome sequence information obtained from the mothers.
  • the number of reference samples (corresponding to the number of mothers or genomes) is not particularly limited but may be selected from the range of about 50 to about 200,000 in consideration of the convenience of data processing and the accuracy of the results, for example, in the range (Ie, with an upper limit of 200,000), at least about 50, at least about 100, or at least about 200.
  • the reference sample may be selected from a group of genomic sequence information broken down by race such as Korean, Asian, or Western, or two or more races may be used.
  • Preparing sequence information of polynucleotide fragments covering the entire genome of the reference sample may be obtained from, or already obtained, genomic sequence information from normal mothers pregnant with a fetus that does not have a target chromosome The method may be performed by selecting among genomic sequence information of the generated genomic pool. Step 2) Determining Polynucleotide Fragment Count
  • step 2) the sequence information of each of the polynucleotide fragments of the test sample and the reference sample may be converted into a ' reference genome sequence and a reference genome sequence.
  • the polynucleotide fragment count is determined to have a preset bin number for each chromosome.
  • Step 2-1) targets sequence information of polynucleotide fragments covering the entire genome sequence mapped to a standard genomic sequence obtained from a test sample, and selects an arbitrary number (B) of bin numbers. Calculate the number of test polynucleotide fragments (polynucleotide fragmeni count or read count)
  • Equation 1 the number of polynucleotide fragments or read number vector (S) of a test sample can be expressed by Equation 1 below:
  • the number of bins is about 10,000 to about 20,000,000 bins, about 20,000 to about 15,000,000 bins, about 30,000 to about 10,000,000 bins, or about
  • the bin number is about 1 to about 30,000, about 1 to about 10,000, about 1 to about 5,000, about 1 to about 1,000, about 1 to about 500, about 2 to about 30,000, about 2 to about 10,000, about About 2 to about 5,000, about 2 to about 1,000, about 2 to about 500, about 5 to about 30,000, about 5 to about 10,000, about 5 to about 5,000, about 5 to about 1,000, about 5 to about 500, about 10 to about 30,000, about 10 to about 10,000, about 1.0 to about 5,000, about 10 to about 1,000, about 10 to about 5030, about 20 to about 30,000, about 20 to about 10,000, about 20 to about 5 000, About 20 to about 1,000, about 20 to about 500, about 50 to about 30,000, about 50 to about 10,000, about 50 to about 5 000, about 50 to about 1,000, about 50 to about 500, about f 1 ⁇ 0 ⁇ 0 ⁇ to About f 3 ⁇ 0 ⁇ ,, 0 ⁇ 0 ⁇ 0 ', about 100 to about 10,000, about f 1 ⁇ 0 ⁇ 0 ⁇ to About f 3 ⁇
  • Step 2-2) is a polynucleotide fragment count or read so as to have ⁇ bin numbers based on the sequence information of polynucleotide fragments of the ⁇ reference sample groups selected from the obtained reference sample ⁇ . Calculating a reference count to generate a reference polynucleotide fragment number matrix (or a reference read count matrix).
  • polynucleotide fragment number or read number matrix (R) of a reference sample can be represented by the following Equations 2 and 3:
  • Step a) is to remove the bias from the obtained polynucleotide fragment number value to obtain a more accurate result, which may be additionally performed between step 2) and step 3).
  • Step a) above refers to the number of test polynucleotide fragments and to
  • Singular Value Decomposition Singular Value Decomposition
  • step a) may be performed by applying SVD, in which case, i) a reference polynucleotide fragment number matrix and a test, as shown in Equation 4-7
  • Step 3) compares the average number of polynucleotide fragments of the target chromosome with the average number of polynucleotide fragments of the other chromosomes except for the target chromosome, thereby eliminating the deviation between experiments and confirming the aneuploidity of the trace fetal chromosome. Contribute to further improving the sensitivity of the results.
  • the 'target chromosome' is a chromosome for determining whether a fetus is chromosome aberrant, for example, human chromosome 13, 18 or 21 chromosome, but is not limited thereto. Or, it can be selected from all autosomal to be confirmed whether or not chromosomal aneuploidy.
  • the 'n chromosomes selected from other chromosomes except the target chromosome' is the remainder of the target chromosome objective to determine whether the chromosome is aneuploid.
  • n is an integer selected from 1 to 21.
  • ⁇ can be used to determine the average polynucleotide fragment ratio of 21, i.e., the average polynucleotide fragment number of each of 21 chromosomes excluding the desired chromosome among 22 human autosomes.
  • the “average number of polynucleotide fragments” may be obtained by averaging the number of all polynucleotide fragments or reads existing within a boundary such as a target chromosome or a merged bin.
  • the ⁇ average number of polynucleotide fragments of chromosomes other than the target chromosome '' is an average value of the number of polynucleotide fragments corresponding to a merged bin of each bin so as to have a predetermined fixed length for each chromosome.
  • the average test polynucleotide fragment number ratio or the average reference polynucleotide fragment number ratio can be calculated by the following steps:
  • the mb size which is the average size of Merged Bins, is determined by dividing the total number of bins by the product of the total number of autosomal bodies, 22, and k presets, and integrating the bins to have a length of 0 1 ⁇ 6 for each chromosome.
  • the k value is a value selected by the user, and for example, a value of 1 to 20, 1 to 15, 1 to 10, or 1 to 5 may be used. . 3-1) Determining the Average Test Polynucleotide Fragment Number Ratio Step 3-1) of the test polynucleotide fragment counts, except for the target chromosome, of the average polynucleotide fragment number of the target chromosome to be tested for aneuploidy.
  • n is an integer selected from 1 to 21
  • the average test polynucleotide fragment number ratio (the above ratio) Is obtained by the number of merged bins).
  • step 3-1) refers to the number of test polynucleotide fragments (or the number of test leads), and the average number of polynucleotide fragments (or the number of test leads) of the target chromosome and n chromosomes excluding the target chromosome.
  • Polynucleotide fragment number ratio vector (or mean test read number ratio vector) may be performed by generating a Case read count ratio vector.
  • Step 3-1) is the number of the average polynucleotide fragment of the target chromosome to be tested for abundance among the reference polynucleotide fragment number, n selected from other chromosomes except the target chromosome ( n is selected from 1 to 21)
  • the ratio of the average number of polynucleotide fragments of each merged bin generated for the chromosome of an integer) to obtain the average number of reference polynucleotide fragments Step (the ratio is (number of reference samples) X number of merged bins (mbm) is obtained).
  • step 3-2) is a reference obtained from the N reference samples
  • the average number of polynucleotide fragments (or reference reads) of the target chromosome and the mbm merged bin average polynucleotide fragments (or average number of reads) excluding the target chromosome Taking and calculating the ratio between these [mean number of polynucleotide fragments (or mean number of reads) / merged bin mean polynucleotide fragments (or mean number of reads) of the target chromosome)] (Read count ratio) N) * obtained by mbm), average reference polynucleotide fragment number ratio matrix (or reference read number ratio matrix)
  • Equation 11 The average reference polynucleotide fragment number ratio matrix (RCRM chcroft) for another chromosome of the i chromosome i can be expressed by Equation 11 below:
  • Step 4 It is a step of obtaining the CV (Coefficient of Variation) value for each average polynucleotide fragment number ratio from the obtained average reference polynucleotide fragment number ratio matrix.
  • the step calculates the CV for the reference sample group for the average polynucleotide fragment ratio (average read number ratio) and merged bin average polynucleotide fragment ratio (average lead number ratio) (RCRi) for each chromosome.
  • CV CV chcroft
  • i chromosome i can be obtained by the following equation:
  • oRCR n , mbm represents the standard deviation of the ratio of reads for each chromosome and merged bin calculated for the reference sample group
  • RCR n, mbm for each chromosome, merged calculated for the reference sample group The average of the number of leads per bin is shown.
  • Step 5 is to increase the reliability and accuracy of the result in addition to step 3, and selects any number in the order of low CV from the average number of polynucleotide fragments (mbn) of the target chromosomes obtained above, wherein the 4
  • the average value (weighted average polynucleotide fragment number ratio) of the numerical value obtained by multiplying the reciprocal of CV corresponding to each fraction number ratio obtained by the step is characterized by using.
  • step 5-1) is based on the CV value calculated for the reference sample group for each chromosome chri in step 4), and the average of the top N cv of the small CV value
  • the weighted average polynucleotide fragment number is CV value corresponding to the ratio of the number of polynucleotide fragments to the average test polynucleotide fragment number ratios. This can be done by calculating the ratio value.
  • the N cv is an average polynucleotide fragment having a value of at least about 1.1 times, at least about 1.3 times, at least about 1.5 times, at least about 1.7 times, at least about 2 times, or at least about 3 times greater than the minimum value of Cv chn .
  • Number ratio value such as from about 1.1 times to about 5 times, about 1.1 times to about 3 times, about 1.1 times to about 2 times, about 1.3 times to about 5 times, about 1.3 to about Cv chr ⁇ minimum 3 times, about 1.3 times to about 2 times, about 1.5 times to about 5 times, about 1.5 times to about 3 times, about 1.5 times to about 2 times, about 1.7 times to about 5 times, about 1.7 times to about 3 times, Average polynucleotide fragment number ratio values (RCRs) having a value from about 1.7 times to about 2 times, about 2 times to about 5 times, or about 2 times to about 3 times larger can be selected, but are not limited to experimental. And / or empirically appropriate values may be selected.
  • the weighted average polynucleotide fragment number ratio (WRCRchn) of the i th chromosome i can be obtained from Equation 13 below:
  • the weighted average polynucleotide fragment number ratio value which is the weighted average (multiplied by the inverse of CV, is averaged) with the CV value corresponding to the polynucleotide fragment number ratio, can be calculated to generate a reference weighted average polynucleotide fragment number ratio vector.
  • the polynucleotide fragment number ratio vector (R WRCRchri ) can be obtained from Equation 14 below:
  • R chri WRCR, chri WRCR 2 , hn , WRCR ⁇ chri WRCR ⁇ WRCR N , hn ]
  • the comparing step 6) is a step of comparing the weighted average test polynucleotide fragment number ratio and the weighted average polynucleotide fragment ratio ratio, wherein the comparison is performed by obtaining a Z-score of a target chromosome. Can be.
  • Z-score Z cv -ratio. Chri
  • Equation 15 the average of the leotard "fragment number ratio vector Reference
  • Step 7) Identify Fetal Chromosome Amerity Fetal chromosome aberration can be determined based on a comparison result of the weighted average test polynucleotide fragment number ratio obtained in step 6).
  • the weighted average test polynucleotide fragment number ratio was significantly higher or lower than the weighted average reference polynucleotide fragment number ratio. We believe the possibility of completion is high.
  • the comparison ratio of the number of polynucleotide fragments is performed by Z-score, it may be determined that the higher the Z-score value, the higher the possibility of aneuploid of the target chromosome of the fetus.
  • the absolute value of Z-score (Z cv-rat , 0. chn ) for the target chromosome (chromosome i) is above a certain value, such as about 3 or more, the chromosome on chromosome i of the fetal chromosome of the test sample is It can be determined that aneuploid exists:
  • the system may be a system comprising means adapted for use in the non-invasive fetal chromosome assay described above.
  • the system is
  • Information processing and reading media capable of receiving information from the sequence analyzer or reading of information in the information storage medium.
  • the system may comprise a plurality of biological samples and / or multiples separated from the mother.
  • Polynucleotide fragments eg, a test sample as described above
  • Polynucleotide fragments and / or reference sample polynucleotide fragments may be implemented on known computer readable media through a program capable of executing the steps described above. More specifically, the noninvasive fetal chromosome analysis method presented above and / or each
  • the information obtained in the step may be implemented and / or processed in whole or in part on known computer readable media.
  • the methods described herein may be implemented in combination with hardware.
  • the hardware may mean a specially designed hardware or firmware such as a computer, a standard multi-purpose CPU, an application-specific integrated circuit (ASIC), or a hard-wired device.
  • ASIC application-specific integrated circuit
  • the term 'computer' used may be used to generically refer to them.
  • Another example of the present invention provides a computer readable method for determining chromosomal aneuploidies in a fetus comprising the following steps:
  • A-1) The sequence information of polynucleotide fragments of a test sample is mapped to a reference genome sequence, so that the number of test polynucleotide fragments has a predetermined bin number for each chromosome. fragment count) (corresponding to step 2-1) described above),
  • A-2) determining the reference polynucleotide fragment number to have a preset number of bins by using sequence information of the polynucleotide fragments of the reference sample (corresponding to the above-described step 2-2);
  • n number ( n is an integer selected from 1 to 21) of the average number of polynucleotide fragments of the target chromosome to be tested for aneuploidy among the test polynucleotide fragments selected from other chromosomes except the target chromosome Obtaining the ratio of the average polynucleotide fragment number of each merged bin generated from the chromosome to obtain the average test polynucleotide fragment ratio (the ratio is obtained by the number of merged bins) (step 3-1 described above) Equivalent);
  • n of the average polynucleotide fragments of the target chromosome to be tested for aneuploidy among the reference polynucleotide fragments n selected from other chromosomes except the target chromosome (n is an integer selected from 1 to 21)
  • n is an integer selected from 1 to 21
  • C) corresponds to the average reference polynucleotide fragment by ratio to afford a Coefficient of Variation (CV) value (step 4 described above));
  • a weighted average reference poly using values corresponding to the top N cv of the CV values selected in step D-1) with respect to the average number of reference polynucleotide fragments in step B-2). to obtain a nucleotide fragment may correspond to the rate (steps 5-2 described above));
  • step F A comparison of the weighted average test polynucleotide fragment number ratio and the weighted average reference polynucleotide fragment number ratio (e.g., Z-score) obtained in step E) to confirm whether the fetus and the target chromosome are aneuploid (previous) Corresponds to step 7) described).
  • the weighted average test polynucleotide fragment number ratio e.g., Z-score
  • the computer-readable method is a test obtained after steps A-1) and A-2) (and before steps B-1 and B-2) for a more accurate result.
  • the method may further include removing the bias.
  • the bias removal step may be performed by applying SVD (Singular Value Decomposition).
  • the computer readable method may be embodied as a program executable on a computer on a computer readable medium.
  • Another example provides a computer program stored in a computer readable storage medium for carrying out the steps of the computer readable method.
  • the computer program stored in the computer readable storage medium may be combined with hardware.
  • the computer program stored in the computer readable storage medium is as described above.
  • a program for executing each step of the computer reading method on a computer, wherein all of the above steps may be executed by one program or by two or more programs executing one or more ' steps.
  • Another example provides a computer readable storage medium (or recording medium) containing a computer executable instruction for executing a step of the computer readable method.
  • the program executable in the computer may be stored in a computer readable storage medium (eg, a memory or the like) and implemented in software implemented on one or more processors.
  • a processor may have one or more
  • the program may be combined with a controller, a calculation unit, and / or other unit of a computer system, or may be implanted in appropriate firmware.
  • the program may be combined with a controller, a calculation unit, and / or other unit of a computer system, or may be implanted in appropriate firmware.
  • RAM Random Access Memory
  • ROM Read Only Memory
  • EEPROM Electrically Erasable Programmable Read-Only Memory
  • Flash Memory eg, Universal Serial Bus (USB) Memory, Secure Digital (SD) Memory) , Soli State Drive (SSD), Compact Flash (CF) memory, xD memory, etc.
  • Programs or software stored on the computer readable storage medium may be any, including, for example, on a communication channel such as a telephone line, the Internet, a wireless connection, or the like, or on a portable medium such as a computer readable disk, a flash drive, or the like. It can be delivered to a computer device through known delivery methods.
  • the blocks, tasks, techniques, etc. may be, for example, custom ICs, application specific integrated circuits (ASICs), field programmable logic arrays (FPGAs), programmable logic arrays (PLAs).
  • ASICs application specific integrated circuits
  • FPGAs field programmable logic arrays
  • PDAs programmable logic arrays
  • the software may be a known computer readable medium, such as a magnetic disk, optical disk, or other storage medium, RAM of a computer, or ROM or flash memory, processor, hard disk drive, optical It can be stored in a disk drive, a tape drive, or the like.
  • the software may, for example, be computer readable. It may be delivered to a user or computer system through known delivery methods, including discs or other portable computer storage mechanisms.
  • the computer readable method, program, and storage medium may be operated in any number of other general purpose or toxin computing system environments or structures.
  • Computing systems, environments, and / or structures suitable for implementing the computer-readable methods, programs, and storage media are, for example, personal computers (PCs), server computers, portable or laptop devices, multiprocessor systems, microprocessors, and the like.
  • PCs personal computers
  • server computers portable or laptop devices
  • multiprocessor systems microprocessors, and the like.
  • Distributed computing performed by programmable consumer electronics, network PCs, minicomputers, mainframe computers, and / or remote processing devices including the systems or devices described above and connected via a communications network. ) May include, but is not limited to.
  • program models may be located in local and remote computer storage media, including memory storage modules.
  • Computers may typically include a variety of computer readable media.
  • Computer-readable media can be media that are accessible and available by a computer and can include volatile and nonvolatile media, removable media, and non-removable media.
  • Computer readable media may include computer storage media and / or communication media.
  • the computer storage media may include volatile or nonvolatile, and / or removable or non-removable media, implemented in a method or technology for storage of information such as computer readable instructions, data structures, program modules, and / or other data. Can be.
  • Computer storage media include RAM, ROM, EEPROM, flash memory (eg, USB memory, SD memory, SSD, CF memory, xD memory, etc.), magnetic disks, laser disks, or other memory, CD-ROM, DVD (digital versatile disk). ) Or other optical disc, magnetic
  • One or more of a magnetic cassette, magnetic tape, magnetic disk storage or other magnetic storage device, or any medium that can be used to store desired information and accessible by a computer can be selected, but is not limited thereto.
  • the communication medium typically carries information that implements data transmission or other transport mechanisms among modulated data signals, such as computer readable instructions, data structures, program modules, or carrier waves.
  • modulated data signal means a signal that has one or more of its characteristics set or changed in such a manner as to encode information in the signal.
  • the communication medium may be a wired medium such as a wired network or a direct-wired connection, and
  • Wireless media such as acoustic media, RF, infrared and other wireless media. Combinations of one or more of the above may also be included within the scope of computer readable media.
  • the average of specific chromosomes to be determined By comparing the number of reads with the average number of reads of the other chromosomes except for the chromosome, the deviation between experiments was eliminated, and the ratio and the specificity of the number of reads among the chromosomes weighted averaged by the CV (Coefficient of Variation) value were used.
  • CV Coefficient of Variation
  • FIG. 1 is a schematic diagram showing each step of the non-invasive fetal chromosome aneuploidity determination method according to an example.
  • FIG. 2 is a graph showing a pattern of removing GC bias before and after applying an SVD.
  • the Y axis represents a read count fraction and the X axis represents a GC content.
  • 3 is a graph showing a Z-score obtained as a result of fetal chromosome aberration determination, A is the result according to the method proposed in the present specification, and ⁇ to D according to the conventional method that does not perform the weighted average lead count ratio The result is.
  • Example 3 Lead Count Determination
  • the nucleotide sequence of the read generated from the prepared test sample is standard genome.
  • a test read vector (S) was generated as follows.
  • a reference read number matrix (R) was generated as follows:
  • Bias was removed with the following method about the lead number vector S of the obtained test sample and the lead number matrix R of the reference sample.
  • matrix X is generated by combining the reference lead number matrix and the test lead number vector, and SVD is performed on the combined matrix as follows:
  • the bias is removed by substituting the value of the corresponding singular value in the matrix D with 0.
  • the GC content when the bias was removed by applying SVD was measured as the sum of the base numbers of guanine (G) and cytosine (C) by chromosome, and the total number of bases by chromosome, and the bias was not removed. Compared with the case, it is shown in FIG. As confirmed in FIG. 2, it can be seen that the polynucleotide fragment count (read count) is maintained at a constant level regardless of the GC content by applying SVD, and these results show that the GC bias is removed by the SVD application.
  • Example 5 Calculating the Average Polynucleotide Fragment Number Ratio
  • the average size of mb size of the Merged Bin - establish divided by the product of the k is set to one full Bin number throughout the chromosome, the number of 22 and a dictionary, and integrating the bin so as to have a length of mb size for each chromosome:
  • the average value was calculated for each merged binj of the 13th, 18th, or 21st chromosome and the chromosome except for the chromosome, and the read count ratio was calculated.
  • RCR ch ' was generated as follows:
  • a reference read count ratio matrix for each chromosome was generated by calculating a read count ratio for each chromosome chri of a reference sample as follows: RGR mbZ RCR mbz
  • RCR m RCR mb32 RCR, RCR m, b z , N ⁇ RCR,
  • the upper N cv lead number ratio having a small CV value is selected, and then the average read number ratio values of the test sample are read.
  • the weighted average read number ratio value weighted averaged by the CV value corresponding to the ratio was calculated by Equation 13 below.
  • N cv was selected from the values of read resins having a value of 1.1 to 5 times larger than the minimum value of Cv chri .
  • the Z-score was calculated as follows by comparing the weighted average read ratio of the chromosome-specific experimental samples obtained in Example 7 with the weighted average read ratio ratio vector of the reference sample:
  • ⁇ WRCR chr weighted average reference polynucleotide fragment number ratio vector average
  • ⁇ WRCR chn standard deviation of weighted average reference polynucleotide fragment number ratio vectors
  • the absolute value of the Z-score is 3 or more, it was determined that the fetal chromosome of the sample had aneuploidy.
  • the Z-score was measured by the lead-based method, the method using the ratio of the number of leads between chromosomes with similar biological characteristics, and the ratio between the number of leads and the total number of leads of the target chromosome. Chromosome apoptosis was determined. Specifically, fetal chromosome aberration determination by the lead-based method is to remove the bias by applying the SVD of Example 4 [step a), the step of calculating the polynucleotide fragment number ratio of Example 5 [step 3-1) and 3-2), and the steps [step 4), 5-1), and 5-2) of calculating the weighted average lead number ratio of Examples 6 and 7 are not performed.
  • Fetal chromosome aberration determination by the method using the ratio of the number of chromosomes between chromosomes with similar biological characteristics to the target chromosome is to remove the bias by applying the SVD of Example [step a) and weighting of Examples 6 and 7 Obtained in Example 3 (corresponding to steps 2-1) and 2-2) without performing steps [corresponding to steps 4), 5-1), and 5-2) for calculating the average number of leads;
  • the average lead number of the target chromosome and the average number of chromosomes with similar biological characteristics such as the target chromosome and GC content (chromosome 9 if the target chromosome is 21) Z-score was calculated by referring to Equations 15 and 16 using the ratio between the number of leads, and the results are shown in Table 1 C and FIG.
  • Fetal chromosome aberration determination by the method using the ratio between the number of leads and the total number of leads of the target chromosome is a step of removing the bias by applying the SVD of Example 4 [step a) and weighted average of Examples 6 and 7 Test obtained in Example 3 (steps 2-1) and 2-2) without performing steps [steps 4), 5-1), and 5-2) for calculating the number of leads;
  • Z-scores were calculated by referring to Equations 15 and 16 using the ratio between the average number of leads of the target chromosome and the average number of leads of the entire chromosome, using the lead number vector and the reference lead number matrix.
  • the score absolute values are shown in Table 1 D and FIG. 3D.
  • fetal chromosome aberration was determined from fetal chromosome adifferentiation from maternal blood by the Bangbab of the present invention (all of Examples 1-7).
  • a total of 20 test samples identified were all over Z-score 3, indicating 100% accuracy (A in Table 1 and A in FIG. 3).
  • 6 test samples were determined to be non-fetal chromosome apoptotic among the total 20 test samples (Table 1B and FIG. 3B), and the target chromosome and biological characteristics.

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Abstract

L'invention concerne un procédé d'analyse chromosomique fœtale de type non invasif permettant de déterminer une aneuploïdie chromosomique fœtale au moyen d'informations de séquençage nucléotidique chromosomique obtenues à partir d'un échantillon biologique isolé d'une mère.
PCT/KR2016/000099 2015-09-24 2016-01-06 Procédé de détermination d'aneuploïdie chromosomique fœtale de type non invasif WO2017051996A1 (fr)

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