Methods for analyzing massively parallel sequencing data for noninvasive prenatal diagnosis

Patent metadata

Field	Value
Publication number	US-9218449-B2
Application number	US-201313802268-A
Country	US
Kind code	B2
Filing date	Mar 13, 2013
Priority date	Jul 23, 2007
Publication date	Dec 22, 2015
Grant date	Dec 22, 2015

Abstract

This invention provides several ways of managing GC bias that occurs during seequencing and analysis of genomic DNA. Maternal plasma can be used as a source of fetal DNA for analysis. DNA segments or tags obtained from the plasma can be aligned with a chromosomal region of interest and with an artificial reference chromosome assembled from regions of the genome having matching GC content. This technology can be used, for example, to detect and evaluate aneuploidy and other chromosomal abnormalities.

First claim

What is claimed is:

1. A method of characterizing a test genome or portion thereof, the method comprising:
identifying a first chromosomal region having a first GC content in a reference genome;
assembling an artificial reference chromosome including a plurality of disjoint regions of the reference genome, the plurality of disjoint regions being at least 50 kb in length, the artificial reference chromosome having a second GC content that is about the first GC content;
aligning, by a computer system, each of a plurality of sequence tags with the first chromosomal region and with the artificial reference chromosome, wherein the sequence tags have been obtained by sequencing nucleic acids in a biological sample comprising cell-free nucleic acids from a first tissue and a second tissue;
determining, by a computer system, a first amount of sequence tags that align with the first chromosomal region;
determining, by a computer system, a reference amount of sequence tags that align with the artificial reference chromosome;
determining a parameter from the first amount and the reference amount, the parameter including a ratio of the first amount and the reference amount; and
comparing the parameter to a cutoff value, thereby determining a classification of an amplification or deletion in the first chromosomal region of the first tissue.

2. The method of claim 1 , wherein the first tissue is from a fetus and the second tissue is from a female pregnant with the fetus.

3. The method of claim 1 , wherein the first tissue is from a tumor and the second tissue is from healthy cells of a patient having the tumor.

4. The method of claim 1 , wherein the first chromosomal region includes a plurality of disjoint subregions.

5. The method of claim 1 , wherein the plurality of disjoint regions are from the same chromosome.

6. The method of claim 1 , wherein the plurality of disjoint regions are from different chromosomes.

7. The method of claim 1 , wherein all the plurality of disjoint regions together have the first GC content within a specified percentage.

8. The method of claim 7 , wherein each of the disjoint regions separately has the first GC content within the specified percentage.

9. The method of claim 1 , wherein the biological sample is maternal plasma.

10. The method of claim 1 , wherein the genome is human, wherein the first chromosomal region is part of a chromosome selected from chromosome 13, chromosome 18, or chromosome 21, and wherein the classification is trisomy of said chromosome.

11. The method of claim 1 , wherein the disjoint regions were obtained by sequencing nucleic acids in the sample.

12. A computer program product comprising a non-transitory computer readable medium storing a plurality of instructions for controlling a processor to perform an operation, the instructions comprising:
identifying a first chromosomal region having a first GC content;
assembling an artificial reference chromosome including a plurality of disjoint regions of the reference genome, the plurality of disjoint regions being at least 50 kb in length, the artificial reference chromosome having a second GC content that is about the first GC content;
aligning each of a plurality of sequence tags with the first chromosomal region and with the artificial reference chromosome, wherein the sequence tags have been obtained by sequencing nucleic acids in a biological sample comprising cell-free nucleic acids from a first tissue and a second tissue;
determining a first amount of sequence tags that align with the first chromosomal region;
determining a reference amount of sequence tags that align with the artificial reference chromosome;
determining a parameter from the first amount and the reference amount, the parameter including a ratio of the first amount and the reference amount; and
comparing the parameter to a cutoff value, thereby determining a classification of an amplification or deletion in the first chromosomal region of the first tissue.

13. A system comprising one or more processors configured for characterizing a genome or portion thereof by a process that comprises:
identifying a first chromosomal region that has a first GC content;
assembling an artificial reference chromosome including a plurality of disjoint regions of the reference genome, the plurality of disjoint regions being at least 50 kb in length, the artificial reference chromosome having a second GC content that is about the first GC content;
aligning each of a plurality of sequence tags determined for a biological sample with the first chromosomal region and with the artificial reference chromosome;
determining a first amount of sequence tags that align with the first chromosomal region;
determining a reference amount of sequence tags that align with the artificial reference chromosome;
determining a parameter from the first amount and the reference amount, the parameter including a ratio of the first amount and the reference amount; and
comparing the parameter to a cutoff value, thereby determining a classification of an amplification or deletion in the biological sample.

14. The method of claim 1 , further comprising sequencing at least part of the cell-free nucleic acids of the first tissue and at least part of the cell-free nucleic acids of the second tissue before the aligning.

15. The method of claim 14 , wherein the biological sample is plasma.

16. The method of claim 1 , wherein the parameter is a probability value that the first amount and the reference amount are statistically different.

17. The method of claim 16 , wherein the cutoff value is 0.05.

18. The method of claim 1 , wherein identifying the first chromosomal region comprises selecting gene-rich regions.

19. The method of claim 1 , wherein identifying the first chromosomal region comprises selecting regions at either end of the long arm of chromosome 13 and excluding regions in between.

20. The computer program product of claim 12 , wherein the parameter is a probability value that the first amount and the reference amount are statistically different.

21. The computer program product of claim 20 , wherein the cutoff value is 0.05.

22. The computer program product of claim 12 , wherein identifying the first chromosomal region comprises selecting gene-rich regions.

23. The computer program product of claim 12 , wherein identifying the first chromosomal region comprises selecting regions at either end of the long arm of chromosome 13 and excluding regions in between.

24. The computer program product of claim 12 , wherein the instructions further comprise correcting GC bias in the first amount and the reference amount by regression analysis.

25. The method of claim 1 , wherein the assembling of the artificial chromosome comprises assembling disjoint regions having both about the same GC content and about the same mappability as the first chromosomal region.

26. The method of claim 25 , wherein the first chromosomal region is chromosome 13, and the artificial reference chromosome has about the same GC content and about the same mappability as chromosome 13.

27. The method of claim 25 , wherein the first chromosomal region is chromosome 18, and the artificial reference chromosome has about the same GC content and about the same mappability as chromosome 18.

28. The computer program product of claim 12 , wherein the instruct

Assignees

• Univ Hong Kong Chinese

Inventors

• Lo Yuk Ming Dennis
• Chiu Wai Kwun Rossa
• Chan Kwan Chee
• Zheng Wenli
• Sun Hao
• Chen Zhang

Classifications

• G16B30/00

  ICT specially adapted for sequence analysis involving nucleotides or amino acids · CPC title

• G16B20/00

  ICT specially adapted for functional genomics or proteomics, e.g. genotype-phenotype associations · CPC title

• G06F19/22

  Physics · mapped topic

• G06F19/18

  Physics · mapped topic

• G06F19/16 Primary

  Physics · mapped topic