System and method for cleaning noisy genetic data from target individuals using genetic data from genetically related individuals

• US 9,424,392 B2
• Filed: 03/11/2013
• Issued: 08/23/2016
• Est. Priority Date: 11/26/2005
• Status: Active Grant

• Current Assignee: Natera Incorporated (Natera)
• Original Assignee: Natera Incorporated (Natera)
• Inventors: Rabinowitz, Matthew, Banjevic, Milena, Demko, Zachary, Johnson, David
• Primary Examiner(s): Riggs, II, Larry D
• Application Number:
  US13/793,133
• Publication Number:
  US 20130253369A1
• Time in Patent Office: 1,261 Days
• US Class Current: 1/1
• CPC Class Codes: C12Q 1/6827 for detection of mutation or polymorphism
• CPC Class Codes: C12Q 1/6876 Nucleic acid products used in the analysis of nucleic acids, e.g. primers or probes
• CPC Class Codes: C12Q 1/6883 for diseases caused by alterations of genetic material
• CPC Class Codes: C12Q 2537/16 Assays for determining copy number or wherein the copy number is of special importance
• CPC Class Codes: C12Q 2537/165 Mathematical modelling, e.g. logarithm, ratio
• CPC Class Codes: C12Q 2600/118 Prognosis of disease development
• CPC Class Codes: C12Q 2600/156 Polymorphic or mutational markers
• CPC Class Codes: C12Q 2600/158 Expression markers
• CPC Class Codes: G16B 20/00 ICT specially adapted for functional genomics or proteomics, e.g. genotype-phenotype associations
• CPC Class Codes: G16B 20/20 Allele or variant detection, e.g. single nucleotide polymorphism [SNP] detection
• CPC Class Codes: G16B 20/40 Population genetics; Linkage disequilibrium
• CPC Class Codes: G16B 25/00 ICT specially adapted for hybridisation; ICT specially adapted for gene or protein expression
• CPC Class Codes: G16B 30/00 ICT specially adapted for sequence analysis involving nucleotides or amino acids
• CPC Class Codes: G16B 40/00 ICT specially adapted for biostatistics; ICT specially adapted for bioinformatics-related machine learning or data mining, e.g. knowledge discovery or pattern finding

Abstract

A system and method for determining the genetic data for one or a small set of cells, or from fragmentary DNA, where a limited quantity of genetic data is available, are disclosed. Genetic data for the target individual is acquired and amplified using known methods, and poorly measured base pairs, missing alleles and missing regions are reconstructed using expected similarities between the target genome and the genome of genetically related subjects. In accordance with one embodiment of the invention, incomplete genetic data is acquired from embryonic cells, fetal cells, or cell-free fetal DNA isolated from the mother'"'"'s blood, and the incomplete genetic data is reconstructed using the more complete genetic data from a larger sample diploid cells from one or both parents, with or without genetic data from haploid cells from one or both parents, and/or genetic data taken from other related individuals.

Claims

1. A method for detecting the presence or absence of a chromosomal abnormality in a fetus, the method comprising:

(a) measuring the amount of genetic material at multiple polymorphic loci on a chromosome or chromosome segment of interest in a sample comprising DNA from the fetus and DNA from the mother of the fetus;

wherein the amount of genetic material at a particular polymorphic locus is determined irrespective of the identity of the alleles at that polymorphic locus;

(b) determining, on a computer, the probability of the presence and the probability of the absence of a chromosomal abnormality in the fetus by comparing the amount from step (a) to either (i) a threshold value or (ii) an expected amount for a particular copy number hypothesis;

(c) identifying the presence or absence of a chromosomal abnormality in the fetus by selecting the probability most likely to be true; and

(d) outputting the selected probability as an indication of whether the fetus has a chromosomal abnormality.

2. The method of claim 1, wherein the expected amount is a reference amount.

3. The method of claim 1, wherein the expected amount is the mean value for a reference chromosome or chromosome segment that is present in two copies.

4. The method of claim 1, wherein the expected amount is the mean value for samples with two copies of a reference chromosome or chromosome segment.

5. The method of claim 1, further comprising determining the number of copies of the chromosome or chromosome segment of interest in the genome of the fetus.

6. The method of claim 1, wherein sequencing is used to measure the amount of genetic material at the multiple loci.

7. The method of claim 1, wherein the sample is a maternal blood sample comprising DNA from the fetus and DNA from the mother of the fetus.

8. The method of claim 1, wherein the method further comprises performing amniocentesis or chorion villus biopsy.

9. The method of claim 1, wherein the chromosome of interest is selected from the group consisting of chromosome 13, chromosome 18, chromosome 21, the X chromosome, the Y chromosome, and combinations thereof.

10. The method of claim 1, wherein the chromosomal abnormality is selected from the group consisting of monosomy, uniparental disomy, trisomy, other aneuploidies, unbalanced translocations, insertions, deletions, and combinations thereof.

11. A method for detecting the presence or absence of a chromosomal abnormality in a fetus, the method comprising:

(a) using sequencing to measure the amount of genetic material at multiple polymorphic loci on a chromosome or chromosome segment of interest in a sample comprising DNA from the fetus and DNA from the mother of the fetus;

wherein the amount of genetic material at a particular polymorphic locus is determined irrespective of the identity of the alleles at that polymorphic locus;

(b) determining, on a computer, the probability of the presence and the probability of the absence of a chromosomal abnormality in the fetus by comparing the amount from step (a) to either (i) a threshold value or (ii) an expected amount for a particular copy number hypothesis;

(c) identifying the presence or absence of a chromosomal abnormality in the fetus by selecting the probability most likely to be true; and

(d) outputting the selected probability as an indication of whether the fetus has a chromosomal abnormality.