Systems and methods to detect rare mutations and copy number variation
The present disclosure provides a system and method for the detection of rare mutations and copy number variations in cell free polynucleotides. Generally, the systems and methods comprise sample preparation, or the extraction and isolation of cell free polynucleotide sequences from a bodily fluid; subsequent sequencing of cell free polynucleotides by techniques known in the art; and application of bioinformatics tools to detect rare mutations and copy number variations as compared to a reference. The systems and methods also may contain a database or collection of different rare mutations or copy number variation profiles of different diseases, to be used as additional references in aiding detection of rare mutations, copy number variation profiling or general genetic profiling of a disease.
1. A method, comprising:
a) providing a population of cell free DNA (“cfDNA”) molecules obtained from a bodily sample from a subject;
b) converting the population of cfDNA molecules into a population of non-uniquely tagged parent polynucleotides, wherein each of the non-uniquely tagged parent polynucleotides comprises (i) a sequence from a cfDNA molecule of the population of cfDNA molecules, and (ii) an identifier sequence comprising one or more polynucleotide barcodes;
c) amplifying the population of non-uniquely tagged parent polynucleotides to produce a corresponding population of amplified progeny polynucleotides;
d) sequencing the population of amplified progeny polynucleotides to produce a set of sequence reads;
e) mapping sequence reads of the set of sequence reads to one or more reference sequences from a human genome;
f) grouping the sequence reads into families, each of the families comprising sequence reads comprising the same identifier sequence and having the same start and stop positions, whereby each of the families comprises sequence reads amplified from the same tagged parent polynucleotide;
g) at each genetic locus of a plurality of genetic loci in the one or more reference sequences, collapsing sequence reads in each family to yield a base call for each family at the genetic locus; and
h) determining a frequency of one or more bases called at the locus from among the families.
2. The method of claim 1 , further comprising detecting, at one or more loci, at least one single nucleotide variant, at least one gene fusion and at least one copy number variant.
3. The method of claim 1 , wherein converting comprises any of blunt-end ligation, sticky end ligation, molecular inversion probes, PCR, ligation-based PCR, single strand ligation and single strand circularization.
4. The method of claim 1 , wherein the one or more reference sequences comprise a sequence from a human genome assembly.
5. The method of claim 1 , wherein making the base call comprises voting, averaging, maximum a posteriori or maximum likelihood detection, dynamic programming, Bayesian methods, hidden Markov methods or support vector machine methods.
6. The method of claim 1 , wherein determining the frequency comprises detecting a rare mutation.
7. The method of claim 1 , further comprising generating a set of consensus sequences from the sequence reads, wherein determining the frequency of one or more bases comprises detecting a presence of sequence variations in the set of consensus sequences compared with the one or more reference sequences.
8. The method of claim 1 , wherein d) comprises sequencing a panel of actionable cancer-related genes.
9. The method of claim 1 , wherein mapping the sequence reads comprises using information about a length of each of the sequence reads.
10. The method of claim 1 , further comprising filtering out sequence reads that fail to meet a quality threshold.
11. The method of claim 1 , wherein the population of cfDNA molecules is tagged with from 10 to 100,000 different identifiers.
12. The method of claim 1 , wherein the population of polynucleotides is tagged with n different unique identifiers, wherein n is no more than 100*z, wherein z is a mean of an expected number of duplicate molecules having the same start and stop positions in the sample.
13. The method of claim 1 , wherein no more than 100 nanograms of polynucleotides from the bodily sample are converted in b).
14. The method of claim 1 , wherein converting comprises converting the population of cfDNA molecules into the population of non-uniquely tagged parent polynucleotides at a conversion efficiency of at least 30%.
15. The method of claim 1 , wherein converting comprises converting the population of cfDNA molecules into the population of non-uniquely tagged parent polynucleotides at a conversion efficiency of at least 50%.
16. The method of claim 1 , wherein converting comprises converting the population of cfDNA molecules into the population of non-uniquely tagged parent polynucleotides at a conversion efficiency of at least 80%.
17. The method of claim 1 , further comprising selectively enriching regions from a genome or transcriptome of the subject prior to sequencing.
18. The method of claim 1 , wherein d) comprises sequencing a panel of tumor suppressor genes.
19. The method of claim 1 , further comprising removing a subset of the sequence reads from further analysis prior to e).
20. The method of claim 1 , wherein the population of cfDNA molecules is tagged with from 50 to 10,000 different identifiers.