Detecting and classifying copy number variation

Patent metadata

Field	Value
Publication number	US-10415089-B2
Application number	US-201514983379-A
Country	US
Kind code	B2
Filing date	Dec 29, 2015
Priority date	Jan 19, 2010
Publication date	Sep 17, 2019
Grant date	Sep 17, 2019

Abstract

The invention provides a method for determining copy number variations (CNV) of a sequence of interest in a test sample that comprises a mixture of nucleic acids that are known or are suspected to differ in the amount of one or more sequence of interest. The method comprises a statistical approach that accounts for accrued variability stemming from process-related, interchromosomal and inter-sequencing variability. The method is applicable to determining CNV of any fetal aneuploidy, and CNVs known or suspected to be associated with a variety of medical conditions. CNV that can be determined according to the method include trisomies and monosomies of any one or more of chromosomes 1-22, X and Y, other chromosomal polysomies, and deletions and/or duplications of segments of any one or more of the chromosomes, which can be detected by sequencing only once the nucleic acids of a test sample.

First claim

What is claimed is:

1. A method, implemented using a nucleic acid sequencer and a computer system comprising one or more processors and system memory, of identifying at least one normalizing sequence for normalizing coverage of a sequence of interest suspected of having a copy number variation in an organism, the method comprising:
(a) providing a plurality of qualified samples comprising nucleic acids for the sequence of interest, wherein the qualified samples are known to have a normal copy number of the sequence of interest;
(b) sequencing, using the nucleic acid sequencer, the qualified samples to obtain at least about 10,000 sequence reads;
(c) aligning, by the one or more processors, the at least about 10,000 sequence reads obtained from the qualified samples to a reference genome including the sequence of interest and thereby providing sequence tags corresponding to the sequence reads;
(d) identifying, by the one or more processors, a number of those sequence tags that are from the sequence of interest and identifying a number of those sequence tags that are from a plurality of potential normalizing sequences;
(e) repeatedly determining, by the one or more processors, sequence doses for the sequence of interest using the number of sequence tags for the sequence of interest and the number of sequence tags for the plurality of potential normalizing sequences; and
(f) selecting, by the one or more processors, the at least one normalizing sequence, alone or in a combination with one or more other potential normalizing sequences, giving sequence doses for the sequence of interest having: (i) the smallest variability among two or more of the qualified samples, (ii) the greatest differentiability between two or more of the qualified samples and one or more affected samples known to have a copy number variation of the sequence of interest, (iii) the smallest variability and the greatest differentiability, or (iv) a combination of small variability and large differentiability.

2. The method of claim 1 , wherein selecting the normalizing sequence comprises selecting a combination of normalizing sequences that gives the smallest variability in doses across the plurality of qualified samples.

3. The method of claim 1 , wherein selecting the normalizing sequence comprises selecting the normalizing sequence alone, and not in combination with other normalizing sequences, that gives the smallest variability in doses across the plurality of qualified samples.

4. The method of claim 1 , wherein selecting the normalizing sequence comprises selecting a combination of normalizing sequences that gives the greatest differentiability in calculated doses between an aneuploid test sample and the plurality of qualified samples.

5. The method of claim 1 , wherein selecting the normalizing sequence comprises selecting the normalizing sequence alone, and not in combination with other normalizing sequences, that gives the greatest differentiability in calculated doses between an aneuploid test sample and the plurality of qualified samples.

6. The method of claim 1 , wherein the differentiability comprises a statistical measure of a difference between a distribution of the sequence doses of the two or more qualified samples and a distribution of the sequence doses of the one or more affected samples.

7. The method of claim 1 , further comprising sequencing nucleic acid in the qualified samples using massively parallel sequencing.

8. The method of claim 1 , wherein the sequence of interest comprises a chromosome.

9. The method of claim 1 , wherein the sequence of interest comprises a chromosome segment associated with a partial aneuploidy.

10. The method of claim 1 , wherein the sequence of interest comprises a sequence related to a cancer.

11. The method of claim 1 , wherein applying the normalizing sequence in a copy number variation analysis of the sequence of interest improves sensitivity, selectivity, and/or reliability of the copy number variation analysis.

12. The method of claim 1 , wherein the qualified samples comprise DNA from two genomes.

13. The method of claim 1 , wherein the qualified samples comprise cell-free DNA.

14. The method of claim 1 , wherein the qualified samples are obtained from mothers pregnant with a fetus that has been confirmed to have a normal copy number of the sequence of interest.

15. The method of claim 1 , wherein a qualified sample comprises a maternal plasma sample that contains a mixture of fetal and maternal cfDNA molecules.

16. The method of claim 1 , wherein the qualified samples comprise at least 50 qualified samples.

17. The method of claim 1 , wherein a sequence dose comprises a ratio of a read abundance measurement of the sequence of interest over the read abundance measurement of the normalizing sequence.

18. The method of claim 1 , wherein the sequence of interest comprises chromosome 21, and the normalizing sequence for chromosome 21 is selected from the group consisting of: chromosome 9, chromosome 1, chromosome 2, chromosome 3, chromosome 4, chromosome 5, chromosome 6, chromosome 7, chromosome 8, chromosome 10, chromosome 11, chromosome 12, chromosome 13, chromosome 14, chromosome 15, chromosome 16, chromosome 17, and any combinations thereof.

19. The method of claim 1 , wherein the sequence of interest comprises chromosome 18, and the normalizing sequence for chromosome 18 is selected from the group consisting of: chromosome 8, chromosome 2, chromosome 3, chromosome 4, chromosome 5, chromosome 6, chromosome 7, chromosome 9, chromosome 10, chromosome 11, chromosome 12, chromosome 13, chromosome 14, and any combinations thereof.

20. The method of claim 1 , wherein the sequence of interest comprises chromosome X, and the normalizing sequence for chromosome X is selected from the group consisting of: chromosome 1, chromosome 2, chromosome 3, chromosome 4, chromosome 5, chromosome 6, chromosome 7, chromosome 8, chromosome 9, chromosome 10, chromosome 11, chromosome 12, chromosome 13, chromosome 14, chromosome 15, chromosome 16, and any combinations thereof.

21. The method of claim 1 , wherein the sequence of interest comprises chromosome 13, and the normalizing sequence for chromosome 13 is selected from the group consisting of: chromosome 2, chromosome 3, chromosome 4, chromosome 5, chromosome 6, chromosome 7, chromosome 8, chromosome 9, chromosome 10, chromosome 11, chromosome 12, chromosome 14, chromosome 18, chromosome 21, and any combinations thereof.

22. The method of claim 1 , wherein the sequence of interest comprises chromosome Y, and the normalizing sequence for chromosome Y is selected from the group consisting of: chromosome 2, chromosome 3, chromosome 4, chromosome 5, chromosome 6, and any combinations thereof.

23. The method of claim 1 , wherein the sequence of interest comprises Chr11: 81000082-103000103, and the normalizing sequence comprises Chr5: 13000014-33000033.

24. A computer program product comprising a non-transitory computer readable medium storing program code that, when executed by one or more processors of a computer system, causes the computer system to determine a normalizing sequence of a sequence of interest, said program code comprising:
(a) code for obtaining sequence reads generated using a nucleic acid sequencer from a plurality of qualified samples for the sequence of interest, wherein the qualified samples are known to have a normal copy number of the sequence of interest;
(b) code for a

Assignees

• Verinata Health Inc

Inventors

• Rava Richard P
• Rhees Brian K

Classifications

• C12Q1/6809

  Methods for determination or identification of nucleic acids involving differential detection · CPC title

• C12Q1/6806

  Preparing nucleic acids for analysis, e.g. for polymerase chain reaction [PCR] assay (C12Q1/6804 takes precedence) · CPC title

• C12Q1/6874 Primary

  involving nucleic acid arrays, e.g. sequencing by hybridisation · CPC title

• C12Q2600/106

  Pharmacogenomics, i.e. genetic variability in individual responses to drugs and drug metabolism · CPC title

• C12Q1/6886

  for cancer (immunoassay for cancer G01N33/575) · CPC title