CN109628579B - Detection method for determining whether chromosome number in biological sample is abnormal - Google Patents
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Abstract
A test method for determining whether a chromosome number in a biological sample is abnormal, the method comprising the steps of: determining the minimum number of the types of genes to be detected on each chromosome to be detected, selecting at least one reference chromosome, and determining the copy number of the genes with the known number on each chromosome to be detected and the genes with the known number on each reference chromosome; and determining the number of chromosomes to be detected in the sample, thereby determining whether the number of chromosomes to be detected is abnormal. The method can accurately and parallelly detect the abnormal conditions of various chromosome numbers, and has wide application prospect for noninvasive prenatal screening of 13, 18 and 21 chromosome trisomy syndrome, X and Y chromosome number abnormality and other major requirements.
Description
Technical Field
The invention relates to the field of nucleic acid detection, in particular to a detection method for determining whether the number of chromosomes in a biological sample is abnormal.
Background
In humans, a change in the number of chromosomes causes severe congenital diseases. At present, the most common is that chromosome 21 changes from normal diploid to abnormal triploid, which is called syndrome type, and the incidence rate is about 1/700-1/600. Similar quantitative changes occur in chromosome 18 and chromosome 13, which cause syndromes of pathological changes in perception, limbs, development and the like, and the incidence rates are about 1/2000 and 1/4000 respectively. In addition, the number of X and Y chromosomes varies, and this also causes serious problems in sexual development.
The earliest method for detecting the change in chromosome number was karyotyping, which requires taking fetal cells from the mother using an invasive sampling method such as amniocentesis and observing the chromosome configuration in the nucleus under a microscope to determine the abnormal number of chromosomes, and this method is often used for postnatal diagnosis of newborns. Obviously, such invasive prenatal screening methods are painful for the pregnant woman and also increase the risk of miscarriage. Therefore, researchers have proposed methods for noninvasive prenatal diagnosis. One of the methods is cervical scraping, that is, cells exfoliated from a fetus at the cervix of a pregnant woman are separated and purified (for example, magnetic bead enrichment, immunization, flow sorting and the like) to obtain fetal cells with high purity. The disadvantage of this method is that the sample handling process is complicated. Another more direct idea is to detect fetal free nucleic acids in maternal peripheral blood. Fetal-free nucleic acids are some highly fragmented nucleic acid sequences of fetal origin. Very challenging is the low proportion of fetal free nucleic acid in the peripheral blood of pregnant women, and the results of second generation sequencing show that at early gestation, the proportion of fetal free nucleic acid in the peripheral blood of pregnant women is only 4% (determined by the relevant gene on the Y chromosome originating from the male fetus). Although the second generation sequencing can detect a lower proportion of fetal free nucleic acid in a multi-target form, the quantification of nucleic acid and gene copy number by the second generation sequencing is difficult to be very accurate, so that it is difficult to distinguish the small changes of the gene copy number on the chromosome caused by the change of the number of fetal chromosomes in the fetal free nucleic acid with low abundance, especially the number changes of 13 th, 18 th, 21 st chromosomes and X chromosomes, because the genes derived from the chromosomes are commonly present in the mother, and the influence of the change of the fetal free nucleic acid copy number on the gene copy number derived from the mother in the peripheral blood of the mother is very little.
Disclosure of Invention
In order to solve the problem that the chromosome quantity abnormality of the fetus is difficult to non-invasively detect from the maternal peripheral blood due to the insufficient accurate quantification capacity of the gene copy number, the invention discloses a method for detecting the chromosome quantity change.
In one embodiment, the present invention provides a test method for determining whether a chromosome number in a biological sample is abnormal, the method comprising the steps of: step 1: determining the minimum number of the gene types to be detected on each chromosome to be detected according to the number change value of the chromosomes to be detected, the nucleic acid equivalent in the sample and the confidence coefficient of the detection method, and selecting a known number of genes from each chromosome to be detected, wherein the known number is not less than the minimum number of the gene types; nucleic acid equivalents in the sample refer to the ratio of the mass of nucleic acid in the sample to the mass of the whole genome in the organism being detected; the number variation value of the chromosomes refers to the smallest absolute difference value which can occur between the number of the chromosomes to be detected under all abnormal conditions and the number of the chromosomes to be detected under normal conditions in a single genome of the organism; step 2: selecting at least one reference chromosome, and selecting a known number of genes from each reference chromosome; and step 3: determining the copy number of the selected known number of genes on each chromosome to be detected and the selected known number of genes on each reference chromosome; and step 4: and determining the number of the chromosome to be detected in the sample according to the copy number of each gene, the number of the reference chromosomes and the proportion of the nucleic acid quality of the chromosome to be detected in the sample nucleic acid quality, thereby determining whether the number of the chromosome to be detected is abnormal.
In one embodiment, the organism is a human, and the reference chromosomes comprise one or more of human chromosomes 1-7, 9-12, 14-17, 19, 20, 22, preferably one or more of human chromosomes 1 and 2, and more preferably human chromosome 1; the chromosome to be detected is one or more of human chromosomes 13, 18, 21, X and Y.
In one embodiment, the required minimum gene copy number is calculated based on the number variation of the chromosome to be detected, the nucleic acid equivalent in the sample, and the confidence of the detection method; the minimum number of gene copies required is then divided by the nucleic acid equivalent to obtain the minimum number of gene species.
In one embodiment, the method of determining the copy number of a selected known number of genes on each reference chromosome comprises nucleic acid amplification, specific hybridization and/or sequencing, preferably one or more of polymerase chain reaction, loop-mediated isothermal amplification, rolling circle amplification, exponential amplification, nucleic acid sequence dependent amplification, microarray chip hybridization and/or second generation sequencing, more preferably droplet digital polymerase chain reaction.
In one embodiment, the droplet digital polymerase chain reaction uses one or more of optical detection, electrochemical detection, chromatographic detection, mass spectrometric detection, and/or sequencing methods; preferably one or more of fluorescence signal detection, gel electrophoresis chromatography detection, capillary electrophoresis sequencing and/or second generation sequencing; more preferably, polymerase chain reaction of genes on each chromosome produces the same kind of fluorescent signal, and polymerase chain reaction of genes on different chromosomes produces different kinds of fluorescent signals.
In one embodiment, in determining the gene copy number, the droplets are first divided into two categories based on the intensity of the fluorescent signal for each fluorescent signal: wherein the first type of droplets are droplets that do not contain the gene; the second type of droplets are droplets containing one or more of the genes; then, determining the gene copy number according to a statistical model of the droplet digital polymerase chain reaction, wherein the statistical model comprises one or more of a binomial distribution model, a poisson distribution model, a normal distribution model, a chi-square distribution model, a gamma distribution model, an F distribution model and/or a marshall-paler distribution model, and preferably one or more of the binomial distribution model and/or the poisson distribution model; more preferably, the gene copy number is calculated using a poisson distribution model, wherein if the number of droplets of the first type is N and the number of droplets of the second type is P, then the total copy number of the gene on the chromosome is-ln [ 1-P/(P + N) ].
In one embodiment, the number of chromosomes to be detected, t j ＝(Σ i {[B j -k ji A i ×(1-f)]×q i }×Σ i k ji /Σ i A i /f/m), j =1,2, \ 8230;, n, wherein a represents the unnormalized number of a reference chromosome, which is the total copy number of the gene on the reference chromosome divided by the total copy number of the gene on a single corresponding reference chromosome, the unnormalized number of the ith reference chromosome being a i I =1,2, \ 8230;, m, m is the reference chromosome number; b represents the non-normalized number of the chromosome to be detected, which is the total copy number of the gene on said chromosome to be detected divided by the total copy number of said gene on the single corresponding chromosome to be detected, B j Representing the unnormalized number of the j & ltth & gt chromosome to be detected, wherein j =1,2, \8230, and n is the number of the chromosome to be detected; k is a radical of ji Is the ratio of the number of the j (th) chromosome to be detected to the number of the i (th) reference chromosome, q, normally present on a single genome of said organism i F is the number of the ith reference chromosome on a single genome of the organism under normal conditions, and f is the proportion of the nucleic acid mass of the chromosome to be detected in the sample nucleic acid mass.
In one embodiment, the number of chromosomes to be detected is rounded, and whether the number of chromosomes to be detected is abnormal is determined according to the absolute difference between the number of chromosomes to be detected after rounding and the number of chromosomes to be detected under normal conditions.
The method adopts the droplet digital polymerase chain reaction (ddPCR) method which is the most accurate in gene copy number quantification at present, does not need to depend on a standard curve of the traditional quantitative PCR, and can carry out absolute quantification on the gene copy number. Secondly, even if ddPCR is used, it is still challenging to distinguish the copy number variation of a certain gene if the copy number of the gene directly represents the number of the corresponding chromosome, because the quantitative result of ddPCR has a confidence interval with a certain width in a statistical principle (as reported in Milbury et al). Aiming at the challenge, the invention further selects different genes with proper types and quantity on each chromosome, utilizes the characteristic of high fragmentation of the fetal episomal nucleic acid (different genes from the same chromosome are on different fetal episomal nucleic acid fragments with high probability), increases the target quantity for ddPCR amplification, further compresses the width of the confidence interval, and improves the resolution of ddPCR on the copy numbers of different genes, thereby realizing the non-invasive detection of the quantity change of the chromosomes of the fetus from the maternal peripheral blood. Meanwhile, the invention further indicates that the method can also detect the quantity change of various chromosomes of the fetus in a non-invasive and parallel manner from the maternal peripheral blood, and the condition of chromosome quantity abnormality (chromosome 13, 18 and 21 and chromosomes X and Y) common to all five human beings can be found only by one-time detection.
The detection method for determining whether the chromosome number in the biological sample is abnormal can accurately and parallelly detect the abnormal conditions of various chromosome numbers, and has wide application prospect for noninvasive prenatal screening of 13, 18 and 21 chromosome trisomy syndrome, X and Y chromosome number abnormality and other major requirements.
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In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings needed to be used in the embodiments will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments described in the present application, and it is obvious for those skilled in the art to obtain other drawings based on these drawings without creative efforts.
FIG. 1 is a flow chart of an embodiment of the present invention.
Detailed Description
In order to make those skilled in the art better understand the technical solutions in the present application, the present invention will be further described below with reference to the following embodiments, and it is obvious that the described embodiments are only a part of the embodiments of the present application, and not all embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present application. The invention is further described with reference to the following figures and examples.
The first embodiment is as follows: liquid drop digital PCR-based method for detecting whether chromosome quantity in biological sample is abnormal
FIG. 1 is a flow chart of detection of a change in chromosome number based on droplet digital PCR, in which the detection flow is divided into four steps in total.
Step 1: the minimum number of gene species to be detected on each chromosome is calculated.
The value of the change in the number of chromosomes is the smallest absolute difference that can occur between the number of chromosomes to be detected in an abnormal situation and the number of chromosomes to be detected in a normal situation in a single genome of the organism. Taking the number of human chromosome 21 on a single genome as an example, the number of chromosomes may be 3 in an abnormal case and 2 in a normal case, so that the smallest absolute difference between the two may be δ = |3-2| =1.
The nucleic acid equivalent in a sample is generally the ratio of the mass of nucleic acid in the sample to the mass of the whole genome in the organism being tested. For example, for humans, the DNA content in diploid cells is 6.4pg, i.e.the total genome mass is 6.4/2=3.2pg, and the nucleic acid equivalent in the sample is equal to the mass of nucleic acid in the sample (in pg) divided by 3.2pg, as reported in the literature by Landers et al.
The confidence is generally set by human, and the confidence is usually 90%, 95%, 99%, etc., and in all embodiments of the present invention, the confidence of 95% is used uniformly.
Firstly, according to the number change value delta and the confidence coefficient of the chromosome to be detected, the minimum gene copy number required for detecting the number change value delta is calculated.
When the detection method is droplet digital PCR, the rootsAccording to the Milbury et al, it is reported that when the copy number of a gene is greater than 20, the upper and lower boundaries (U) of the gene copy number quantification result are found when the confidence is 95%, according to the central limit theorem + And U - ) Can be approximated as a confidence interval that satisfies a normal distribution:
U ± (P,N)＝-ln[1-P/(P+N)±1.96×(PN) 0.5 /(P+N)/1000]
for other detection methods than droplet digital PCR, the more general formula can also be derived using the central limit theorem and the probability distribution (generally similar to a normal distribution) of the detection results for duplicate samples: u shape ± (μ,σ)＝μ±1.96σ。
Let the number of gene copies detected on the reference chromosome be R in total (the corresponding number of positive and negative droplets are P, respectively) R And N R ) The total number of gene copies on the chromosome to be detected is S (the corresponding number of positive droplets and the number of negative droplets are P respectively) S And N S ) Normally, the number of reference chromosomes on a single genome is 2, and if necessary to resolve the following three cases with 95% confidence: S/kR-2= - δ, S/kR-2= -0, and S/kR-2= δ, where k is the ratio of the number of chromosomes to be detected to the number of reference chromosomes under normal conditions, one of the following two conditions needs to be satisfied:
when S is<R is, U + (P S ,N S )/kU - (P R ,N R )-2<-δ
When S is>When R is, U - (P S ,N S )/kU + (P R ,N R )-2>δ
From the above conditions, P can be calculated S /(P S +N S ) And P R /(P R +N R ) Taking the larger value as p, and calculating the minimum gene copy number required for detecting the quantity change value delta to be-10 according to p 6 ×ln[1-p*]。
The minimum number of gene copies is then divided by the nucleic acid equivalent in the sample (representing the number of normal human chromosomes) to determine the minimum number of gene types to be detected per chromosome. Selecting a known number of species on each reference chromosome, none of the species being less than the calculated minimum number of gene species.
Step 2: a reference chromosome is selected, and genes on the reference chromosome are selected.
Generally, the reference chromosome is selected from one or more of human chromosomes 1-7, 9-12, 14-17, 19, 20, 22, and is usually human chromosome 1, except the chromosome to be detected. The known number of types of genes is selected from the reference chromosome, but the number of types of genes on the reference chromosome described in this step is not necessarily not less than the minimum number of types of genes described in step one.
And 3, step 3: the copy number of the gene was detected using droplet digital PCR.
Samples containing nucleic acids were formulated into a PCR system and PCR amplification was performed using temperature cycling. After the PCR amplification is completed, the reaction units are classified according to their fluorescence intensity, each fluorescence being classified into two categories, the first being a droplet not containing the gene and characterized by a weaker fluorescence signal, and the second being a droplet containing one or more of the genes and characterized by a stronger fluorescence signal. Let the detection result of the digital PCR be: the number of positive units containing a certain chromosome double-stranded sequence to be detected is P (with strong fluorescence), the number of negative units is N, and according to a Poisson distribution model (when the number of liquid drops is large, the binomial distribution model can be similar to the Poisson distribution model), the total number of genes on a certain chromosome can be obtained to be-10 6 ×ln[1-P/(P+N)]。
And 4, step 4: calculating the estimated number of each chromosome to be detected, and outputting the number change value and abnormal condition of the chromosome to be detected.
The proportion f of the nucleic acid mass of the chromosome to be detected in the nucleic acid mass of the sample is a known amount of the sample, and the proportion f =1 can be considered for the nucleic acid samples directly or indirectly derived from fetuses such as amniotic fluid, chorionic tissue, umbilical vein blood, and fetal cells in cervix; for the nucleic acid samples mainly derived from the mother body, such as the peripheral blood of the pregnant woman, the ratio f is related to the parameters of the pregnancy period, and the like, particularly, for the peripheral blood of the pregnant woman, f is generally more than or equal to 4%, and when the pregnancy period is 10 weeks, f is generally approximately equal to 10%.
First, the calculated total copy number of genes is divided by the total number of these genes on the corresponding chromosome to obtain the non-normalized number of this kind of chromosome. For example, 10000 copies of 10 genes are detected on a chromosome; by aligning the sequences of the chromosomes and the genes, wherein the copy number of 5 genes on a single one of the chromosomes is 1, the copy number of 4 genes on a single one of the chromosomes is 2, and the copy number of 1 gene on a single one of the chromosomes is 7, the non-normalized number of the one chromosome is: 10000/(5 × 1+4 × 2+ 7) =500.
Then, let the non-normalized number of the i-th reference chromosome be A i And the unnormalized number of the jth chromosome to be detected is B j (ii) a Then, for each chromosome j to be detected, the number of chromosomes to be detected = (Σ) is calculated from each reference chromosome i in turn i {[B j -k ji A i ×(1-f)]×q i }×Σ i k ji /Σ i A i /f/m), j =1,2, \ 8230;, n. For example, human chromosome 21 is used as the chromosome to be detected (j =1, n = 1), human chromosome 1 is used as the reference chromosome (i =1, m = 1), and both are diploid (k) = in normal cases 11 ＝2/2＝1,q 1 = 2), selecting 1 gene on each of two chromosomes, each gene having 1 number on the corresponding chromosome, and measuring a 1 ＝10000，B 1 =10500, f =10%, then the number t of chromosomes to be detected is calculated 1 ＝(Σ i＝1 {[B 21 -k 11 A i ×(1-f)]×q i }×Σ i＝1 k ji /Σ i＝1 A i /f/m)＝(Σ i＝1 {[10500-1×10000×(1-10％)]×2}×Σ i＝1 1/Σ i＝1 10000/10%/1=3.00. Rounding, and calculating the number of chromosomes to be detected (t) after rounding 1 * = 3) and the number of chromosomes to be detected (k) under normal conditions 11 q 1 Absolute difference of =1 × 2= 2): | t 1 *-k 11 q 1 I = 3-1 × 2 i =1, so the chromosome to be detected is abnormal.
Example two: detecting whether the number of fetus No. 21 chromosomes in cervical smear samples is abnormal based on droplet digital PCR
Based on the procedure described in example one, in this example, the number of human chromosome 21 was determined using human chromosome 1 as a reference chromosome.
Step 1: for human chromosome 21, the number change value of the chromosome to be detected is |3-2| =1; the mass of the nucleic acid was determined by uv spectrophotometer to be 10ng total (total 10000 pg) by calculation: nucleic acid equivalent in the sample is 10000/6.4 × 2=3125.0; the confidence was 95%.
If the number of chromosomes to be realized varies by a value of δ =1 (S)>R), then U is required - (P S ,N S )/kU + (P R ,N R )-2>δ, calculated to give p =1.1E-3, then-10 6 X ln (1-p) =1100.6. Dividing the calculation result 1100.6 by the nucleic acid equivalent 3125.0 to obtain: 1100.6/3125.0<1, i.e., the minimum number of types of genes to be detected on each chromosome to be detected is 1.
And 2, step: human chromosome 1 was selected as a reference chromosome, and 1 gene was detected on this chromosome.
And 3, step 3: primers and probes for chromosome 1 were designed as follows: 5 'gggcgtgccgcacggacaag-3', 5 'gtgagagaaagagagagagccctgag-BHQ-3', and 5'-FAM-cacgct-BHQ0-3'; primers and probes for chromosome 21 were designed as follows: 5 'ctoggagaacataggcttg-BHQ 3',5 'agggggagaacataggcttg-BHQ 3' and 5'-VIC-ccctgcctct-BHQ1-3'. After the PCR system is prepared, carrying out droplet digital PCR with the following temperature cycle: 95 ℃ for 10 minutes followed by 40 cycles of 95 ℃ for 30 seconds, 55 ℃ for 60 seconds, with a temperature change rate of 2 ℃/second.
And 4, step 4: after completion of PCR, the copy number of one gene on chromosome 1 and the copy number of another gene on chromosome 21 are:
since the sample is a cervical scrape, the main source of the sample is fetal, f ≈ 90%. Chromosome 21 and chromosome 1 are normally diploid, so k is 11 ＝1，q 1 ＝2，A 1 ＝3216.2/1＝3216.2，B 1 =4703.0/1=4703.0. Calculating the number t of chromosome 21 1 ＝(Σ i＝1 {[B 1 -k 11 A i ×(1-f)]×q i }×Σ i＝1 k ji /Σ i＝ 1 A i /f/m)＝(Σ i＝1 {[4703.0-1×3216.2×(1-90％)]×2}×Σ i＝1 1/Σ i＝1 3216.2/90%/1=3.03. After rounding off and rounding off, t 1 *＝3，|t 1 *-k 11 q 1 I = 3-1 × 2 i =1, so the detected sample belongs to an abnormal situation: a fetus with trisomy 21 syndrome.
Example three: detection of whether the number of chromosomes 13, 18, 21, X and Y is abnormal in fetal episomal nucleic acid from maternal peripheral blood samples based on digital PCR
Based on the procedure described in the first example, in this example, the number of human chromosomes 13, 18, 21, X and Y was determined using human chromosome 1 as a reference chromosome.
Step 1: the number of chromosomes to be detected changes by δ = |3-2| =1 for chromosomes 13, 18, and 21, and δ =1 for X and Y chromosomes, but there are four different cases: δ = |3-2| =1 (only X chromosome appears), δ = |2-1| =1 (only X chromosome appears), δ = |1-2| =1 (only Y chromosome appears), or δ = |1-0| =1 (only Y chromosome appears), so different formulas need to be used depending on both S > R and S < R cases; the mass of the nucleic acid was determined by UV spectrophotometer to be 14ng (14000 pg total), calculated from the nucleic acid mass of the sample: nucleic acid equivalent in sample 14000/6.4 × 2=4375.0; the confidence was 95%.
If a detection with a value of 1 for the number of chromosomes to be detected is to be effected, U is required - (P S ,N S )/kU + (P R ,N R )-2>Delta or U + (P S ,N S )/kU - (P R ,N R )-2<δ, calculated to give p =7.6E-2, then-10 6 Xln (1-p) =78605.1, so 78605.1/4375.0=17.9, i.e. at least 18 genes need to be detected on each chromosome to be detected. In order to leave a certain technical margin, 20 genes were detected on each chromosome in this example, and the number of each gene on the corresponding chromosome was 1.
Step 2: chromosome 1 was selected as the reference chromosome, and the number of types of genes selected was not limited by the minimum number of types of genes 18 calculated in step 1, so 5 genes, each of which had a number of 1 on the corresponding chromosome, could be selected.
And step 3: preparing a PCR reaction system: since this example requires detection of a plurality of chromosomes, probes used in droplet digital PCR were labeled with FITC (for chromosome 13), VIC (for chromosome 18), NED (for chromosome 21), ROX (for chromosome X), cy5 (for chromosome Y), and Cy5.5 (for chromosome 1) with six different fluorescein respectively, and fluorescence quenching was performed using BHQ0 (for FITC), BHQ1 (for VIC), BHQ2 (for NED and ROX), and BHQ3 (for Cy5 and Cy 5.5) groups, respectively. The sequences of the primers (wherein F represents the forward primer and R represents the reverse primer) and the probes (including the fluorescein species used) required for the reaction system are as follows:
the first set of nucleic acid sequences is shown below for binding to 20 different regions on chromosome 13:
the second set of nucleic acid sequences is shown below for binding to 20 different regions on chromosome 18:
the third set of nucleic acid sequences is shown below for binding to 20 different regions on chromosome 21:
the fourth set of nucleic acid sequences is shown below for binding to 20 different regions on the X chromosome:
the fifth set of nucleic acid sequences is shown below for binding to 20 different regions on the Y chromosome:
the sixth set of nucleic acid sequences is shown below for binding to 20 different regions on chromosome 1 (reference chromosome):
the above reaction system was used to perform droplet digital PCR with temperature cycling: 95 ℃ for 10 minutes followed by 40 cycles of 95 ℃ for 30 seconds, 60 ℃ for 60 seconds, with a temperature change rate of 2 ℃/second.
The results of the total number of genes on each chromosome calculated by the micro-droplet digital PCR, the number of positive units (number of positive droplets), the number of negative units (number of negative droplets), and the poisson distribution are as follows:
and 4, step 4: the sample type was maternal peripheral blood sample (10 weeks gestation) with the nucleic acid source being maternal (f ≈ 10%). According to the detection result of ddPCR, A 1 ＝23592.7/5＝4718.5，B j = Total copy number of Gene/20,q in line j of the above Table 1 =2,f =0.1,m =1, since no Y chromosome (k) was detected 51 =0/2= 0), the fetus is female, the X chromosome is diploid, k 41 =2/2=1, calculating t j ＝(Σ i＝1 {[B j1 -k j1 A 1 ×(1-f)]×q 1 }×Σ i＝1 k j1 /Σ i＝1 A 1 /f/m)、t j Rounded value t j * And absolute difference | t j *-k j1 q 1 L, as follows (where j is the row number):
due to all | t j *-k j1 q 1 I =0,j =1,2,3,4,5, so the number of chromosomes 13, 18, 21, X and Y of the detected sample all belong to normalThe situation is.
It is to be understood that the invention disclosed is not limited to the particular methodology, protocols, and materials described, as these may vary. It is also to be understood that the terminology used herein is for the purpose of describing particular embodiments only, and is not intended to limit the scope of the present invention which will be limited only by the appended claims.
Those skilled in the art will also recognize, or be able to ascertain using no more than routine experimentation, many equivalents to the specific embodiments of the invention described herein. Such equivalents are also encompassed by the appended claims.
Claims (1)
1. A test method for determining whether a chromosome number in a biological sample is abnormal, for non-diagnostic purposes, said method comprising the steps of:
step 1: determining the minimum number of the gene types to be detected on each chromosome to be detected according to the number change value delta of the chromosomes to be detected, the nucleic acid equivalent in the sample and the confidence coefficient of the detection method, and selecting a known number of genes from each chromosome to be detected, wherein the known number is not less than the minimum number of the gene types; the nucleic acid equivalent in the sample refers to the ratio of the mass of the nucleic acid in the sample to the mass of the genome in the detected organism; the quantity change value of the chromosome to be detected is the smallest absolute difference which is possibly generated between the quantity of the chromosome to be detected under all abnormal conditions and the quantity of the chromosome to be detected under normal conditions in the organism;
and 2, step: selecting at least one reference chromosome, and selecting said known number of genes from each reference chromosome;
and step 3: determining the copy number of the selected known number of genes on each chromosome to be detected and the selected known number of genes on each reference chromosome; and
and 4, step 4: determining the number of the chromosomes to be detected in the sample according to the copy number of each gene, the number of the reference chromosomes and the proportion of the nucleic acid quality of the chromosomes to be detected in the nucleic acid quality of the sample, thereby determining whether the number of the chromosomes to be detected is abnormal;
in the step 1, the organism is diploid under normal conditions, the confidence of the detection method is 95%, the detection is carried out by using droplet digital PCR, the detected gene copy number on the reference chromosome is totally R, and the corresponding positive droplet number and negative droplet number are respectively P R And N R The gene copy number on the chromosome to be detected is S in total, and the corresponding positive drop number and negative drop number are P respectively S And N S K is the ratio of the number of chromosomes to be detected to the number of reference chromosomes under normal conditions, U + Upper boundary, U, for quantitative results of gene copy number - The lower boundary of the gene copy number quantification result;
when S is<When R is, U + (P S ,N S )/kU - (P R ,N R )-2<-δ，
When S is>When R is, U - (P S ,N S )/kU + (P R ,N R )-2>δ；
Based on the above conditions, P is calculated S /(P S + N S ) And P R /(P R +N R ) Taking the larger value as p, calculating the minimum gene copy number required for detecting the quantity change value delta according to p as-10 6 ×ln[1-p*](ii) a Then dividing said desired minimum number of gene copies by said nucleic acid equivalent to obtain a minimum number of said gene species;
in the step 3, the method for determining the copy number of the selected genes with known number on each reference chromosome is a droplet digital polymerase chain reaction; fluorescent signal detection is used in the liquid drop digital polymerase chain reaction; in determining the gene copy number, first, for each fluorescent signal, droplets are classified into two types according to the intensity of the fluorescent signal: wherein the first type of droplets are droplets that do not contain the gene; the second type of droplets are droplets containing one or more of the genes; then, determining the gene copy number according to a statistical model of the droplet digital polymerase chain reaction, wherein the statistical model isA poisson distribution model; calculating the gene copy number by using a Poisson distribution model, wherein the number of the first type of liquid drops is N, the number of the second type of liquid drops is P, and then the total copy number of the gene on the chromosome is-10 6 ×ln[1-P/(P+N)]；
In said step 4, the number t of chromosomes to be detected j =(Σ i {[B j -k ji A i ×(1-f)]×q i }×Σ i k ji /Σ i A i /f/m), j =1,2, \ 8230;, n, wherein A represents the unnormalized number of a reference chromosome, which is the total copy number of the gene on the reference chromosome divided by the total number of the gene on a single corresponding reference chromosome, the unnormalized number of the i-th reference chromosome being A i I =1,2, \ 8230;, m, m is the reference chromosome number; b represents the non-normalized number of chromosomes to be detected, which is the total copy number of the genes on the chromosome to be detected divided by the total number of the genes on the single corresponding chromosome to be detected, B j Representing the unnormalized number of the j & ltth & gt chromosome to be detected, wherein j =1,2, \8230, and n is the number of the chromosome to be detected; k is a radical of formula ji The ratio of the number of the j (th) chromosome to be detected to the number of the i (th) reference chromosome of the organism under normal conditions, q i The number of the ith reference chromosome of the organism under normal conditions, and f is the proportion of the nucleic acid mass of the chromosome to be detected in the nucleic acid mass of the sample; rounding the number of the chromosomes to be detected, and determining whether the number of the chromosomes to be detected is abnormal according to the absolute difference value between the number of the chromosomes to be detected after rounding and the number of the chromosomes to be detected under normal conditions.
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| multiplex droplet digital PCR assay for noninvasive prenatal testing of fetal aneuploidies;Chianru Tan等;《Analyst》;20190108;第144卷;第2239–2247页 * |
| 早孕期孕妇外周血的胎儿游离DNA检测分析;郭辉;《数理医药学杂志》;20181231;第32卷(第3期);第459-461页 * |
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