Nucleic acid sequence assembly

• US 10,318,706 B2
• Filed: 06/26/2017
• Issued: 06/11/2019
• Est. Priority Date: 02/17/2015
• Status: Active Grant

• Current Assignee: Dovetail Genomics, Llc
• Original Assignee: Dovetail Genomics, Llc
• Inventors: Putnam, Nicholas H., Stites, Jonathan C., Rice, Brandon J.
• Primary Examiner(s): Leith, Nancy J
• Application Number:
  US15/632,895
• Publication Number:
  US 20170300615A1
• Time in Patent Office: 715 Days
• Field of Search: None
• CPC Class Codes: C12Q 1/6874 involving nucleic acid arrays, e.g. sequencing by hybridisation
• CPC Class Codes: G16B 30/00 ICT specially adapted for sequence analysis involving nucleotides or amino acids
• CPC Class Codes: G16B 30/10 Sequence alignment; Homology search
• CPC Class Codes: G16B 30/20 Sequence assembly

Abstract

Disclosed herein are compositions, systems and methods related to sequence assembly, such as nucleic acid sequence assembly of single reads and contigs into larger contigs and scaffolds through the use of read pair sequence information, such as read pair information indicative of nucleic acid sequence phase or physical linkage.

Claims

1. A method for determining locally optimal contig configuration of a plurality of contigs within a cluster, the method comprising:

(I) obtaining read pair data mapping to the plurality of contigs within the cluster, wherein read pair data is obtained from a set of paired end reads obtained by digesting sample DNA to generate internal double strand breaks within the DNA, allowing the double strand breaks to re-ligate randomly to form a plurality of re-ligation junctions, and sequencing at each side of the plurality of re-ligation junctions;

(II) obtaining a set of clustered contigs; and

(III) processing said set of clustered contigs by;

(a) identifying a window of size w contigs starting at position i along the set of clustered contigs;

(b) considering w! 2^w ordering and orienting options for contigs of the window of size w contigs by examining scores of orders and orientations of the contigs of the window in each position i in the window;

(c) orienting and ordering w contigs of the window to obtain an optimal score;

(d) shifting the window to position i+1 along the set of clustered contigs;

(e) repeating steps (a), (b) and (c) for said window at position i+1 using the orienting and ordering of w for said window at position i+1 contigs to determine an optimal score, thereby orienting and ordering said plurality of contigs in a locally optimal configuration relative to the score; and

(f) outputting said locally optimal configuration to a network, screen or server.

2. The method of claim 1, comprising obtaining read pair data mapping to the plurality of contigs within the cluster, obtaining a standard paired-end read frequency data set, and wherein the score for an orienting and ordering of said w contigs is a measure of how closely a read pair distance data set for the read pair data mapping to the plurality of contigs in the cluster matches the standard paired-end read frequency data set.

3. The method of claim 2, wherein standard paired-end read distance frequency data is obtained from paired-end reads where both reads map to a common contig.

4. The method of claim 3, wherein standard paired-end read distance frequency data is obtained from previously generated curves.

5. The method of claim 2, wherein read pair distance frequency data for read pairs that map to separate contigs more closely approximates the paired-end read distance frequency data when a read pair distance likelihood increases.

6. The method of claim 5, wherein read-pair distance likelihood is maximized.

7. The method of claim 2, wherein read pair distance frequency data for read pairs that map to separate contigs more closely approximates the paired-end read distance frequency data when a statistical measure of difference between the read pair distance frequency data and the standard paired-end read distance frequency data decreases.

8. The method of claim 7, wherein the statistical measure of distance between the read pair distance frequency data and the standard paired-end read distance frequency data comprises at least one of ANOVA, a t-test, and a X-squared test.

9. The method of claim 8, wherein read pair distance for read pairs that map to separate contigs more closely matches the paired-end read distance frequency data when deviation of read pair distance distribution among ordered contigs obtained as compared to standard paired-end read distance frequency decreases.

10. The method of claim 9, wherein deviation of read pair distance distribution among ordered contigs obtained as compared to standard paired-end read distance frequency is minimized.

11. The method of claim 2, wherein read pair data mapping to the plurality of contigs in the cluster is obtained, wherein the score is total read pair distance, and wherein the score is optimized when total read pair distance is minimized.

12. The method of claim 1, wherein the method comprises at least one of ordering the set of contigs, orienting the set of contigs, merging at least two contigs end to end, inserting one contig into a second contig, and cleaving a contig into at least two constituent contigs.

13. The method of claim 1, wherein w is 3.

14. The method of claim 1, wherein w is 4.

15. The method of claim 1, wherein w is 5.

16. The method of claim 1, wherein w is 6.

17. The method of claim 1, wherein w has a first value for a first cluster and wherein w has a second value at a second cluster.

18. The method of claim 1, wherein w is selected to comprise 1% of the contigs of the set.

19. The method of claim 1, wherein w is selected to comprise 5% of the contigs of the set.

20. The method of claim 1, wherein the score is a read pair distance likelihood score, and wherein the score is optimal when the score is maximized for a given window size.

21. The method of claim 1, wherein the score is a deviation from an expected read pair distribution, and wherein the score is optimal when the score is minimized for a given window size.

22. The method of claim 1, wherein the score is calculated using formula 1.

23. The method of claim 1, wherein the set of contig sequences is obtained by extracting the DNA from a biological sample and sequencing the DNA.

24. The method of claim 1, wherein the DNA is crosslinked to at least one DNA binding agent.

25. The method of claim 1, wherein the DNA comprises isolated naked DNA.

26. The method of claim 25, wherein the isolated naked DNA is reassembled into reconstituted chromatin.

27. The method of claim 26, wherein the reconstituted chromatin is crosslinked.

28. The method of claim 26, wherein the reconstituted chromatin comprises a DNA binding protein.

29. The method of claim 26, wherein the reconstituted chromatin comprises a nanoparticle.