US 10,854,317 B2Granted

Method and system for sequence alignment and variant calling

OwnerKo-Wen Wu, Kun-Lin Liinventors

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Abstract

A method to align a next generation sequencing read to a reference sequence includes: (a) receiving a sequencing read; (b) performing a first alignment of the sequencing read to a reference sequence so as to identify a target sequence within the reference sequence whereto the sequencing read maps; (c) selecting a first and a second anchor sequence; (d) attaching the first anchor sequence to the upstream region of the sequencing read and the second anchor sequence to the downstream region of the sequencing read so as to generate an extended sequencing read; (e) attaching the first anchor sequence to the upstream region of the target sequence and the second anchor sequence to the downstream region of the target sequence, so as to generate an extended target sequence; (f) performing a second alignment of the extended sequencing read to the extended target sequence, so that the second alignment is more correctly mapped to the target sequence than the first alignment; (g) identifying a position where one or more bases between the extended sequencing read and the extended target sequence are different based on the second alignment result; and (h) calling a variant based on the identification in step (g).

Claims17

Dependent claims

A method of identifying a variant from a clinical sample by aligning a next generation sequencing (NGS) read to a reference sequence implemented on a NGS computing platform, comprising:

(a) collecting a clinical sample from a human subject;
(b) extracting nucleic acids from the clinical sample;
(c) amplifying the nucleic acids by multiplexed polymerase chain reaction (PCR);
(d) generating a NGS read of a gene;
(e) performing a first alignment of the NGS read to a reference sequence;
(f) identifying a target sequence within the reference sequence whereto the NGS read maps;
(g) generating a first and a second anchor sequence;
(h) generating an extended NGS read by attaching the first anchor sequence to the upstream region and the second anchor sequence to the downstream region of the NGS read respectively;
(i) generating an extended target sequence by attaching the first anchor sequence to the upstream region and the second anchor sequence to the downstream region of the target sequence respectively;
(j) matching the first anchor sequence of the extended NGS read to the first anchor sequence of the extended target sequence and the second anchor sequence of the extended NGS read to the second anchor sequence of the extended target sequence respectively;
(k) performing a second alignment of the extended NGS read to the extended target sequence, wherein a misalignment rate of the second alignment is lower than a misalignment rate of the first alignment;
(l) identifying a position on the extended NGS read that does not align with the extended target sequence based on the second alignment, wherein the position includes or lacks at least one base;
and
(m) calling a variant based on the position, wherein at least the steps of (d) generating the NGS read, (e) performing the first alignment and (k) performing the second alignment are conducted via a NGS computing platform.

11 more elements

A method of identifying a human subject having a variant by aligning a next generation sequencing (NGS) read to a reference sequence, implemented on a NGS computing platform, comprising:

(a) collecting a clinical sample from a human subject;
(b) extracting nucleic acids from the clinical sample;
(c) amplifying the nucleic acids by multiplexed polymerase chain reaction (PCR);
(d) generating a NGS read of a gene, wherein the NGS read is no more than 500 nucleotides;
(e) performing a first alignment of the NGS read to a reference sequence;
(f) identifying a target sequence within the reference sequence whereto the NGS read maps;
(g) generating a first, and a second anchor sequences, wherein the anchor sequences is at least 4 nucleotides;
(h) generating an extended NGS read by attaching the first anchor sequence to the upstream region and the second anchor sequence to the downstream region of the NGS read respectively;
(i) generating an extended target sequence by attaching the first anchor sequence to the upstream region and the second anchor sequence to the downstream region of the target sequence respectively;
(j) matching the first anchor sequence of the extended NGS read to the first anchor sequence of the extended target sequence and the second anchor sequence of the extended NGS read to the second anchor sequence the extended target sequence respectively;
(k) performing a second alignment of the extended NGS read to the extended target sequence, wherein a misalignment rate of the second alignment is lower than a misalignment rate of the first alignment;
(l) identifying a position on the extended NGS read that does not align with the extended target sequence based on the second alignment, wherein the position includes or lacks at least one base;
(m) calling a variant based on the position, and the variant is at least 2 nucleotides;
(n) identifying a disease selected from the group consisting of cancer, cardiovascular disease, metabolic syndrome, neurological disease and immune status,
wherein at least the steps of (d) generating the NGS read, (e) performing the first alignment and (k) performing the second alignment are conducted via a NGS computing platform.

12 more elements

A method of identifying a human subject having a variant by aligning a next generation sequencing (NGS) read to a reference sequence, implemented on a NGS computing platform, comprising:

(a) collecting a clinical sample from a human subject;
(b) extracting nucleic acids from the clinical sample;
(c) amplifying the nucleic acids by multiplexed polymerase chain reaction (PCR);
(d) generating a NGS read of a gene;
(e) performing a first alignment of the NGS read to a reference sequence;
(f) identifying a target sequence within the reference sequence whereto the NGS read maps;
(g) generating a first, and a second anchor sequences;
(h) generating an extended NGS read by attaching the first anchor sequence to the upstream region and the second anchor sequence to the downstream region of the NGS read respectively;
(i) generating an extended target sequence by attaching the first anchor sequence to the upstream region and the second anchor sequence to the downstream region of the target sequence respectively;
(j) matching the first anchor sequence of the extended NGS read to the first anchor sequence of the extended target sequence and the second anchor sequence of the extended NGS read to the second anchor sequence the extended target sequence respectively;
(k) performing a second alignment of the extended NGS read to the extended target sequence, wherein a misalignment rate of the second alignment is lower than a misalignment rate of the first alignment;
(l) identifying a position on the extended NGS read that does not align with the extended target sequence based on the second alignment, wherein the position includes or lacks at least one base;
(m) calling a variant based on the position;
and
(n) identifying a disease selected from the group consisting of cancer, cardiovascular disease, metabolic syndrome, neurological disease and immune status, wherein at least the steps of (d) generating the NGS read, (e) performing the first alignment and (k) performing the second alignment are conducted via a NGS computing platform.

12 more elements

Dependencies are inferred from the claim text.

Facts

Application: 16/479,928Filed 28 Dec 2018 · us provisional application
Priority: 29 Dec 2017
Published: US 2019/0385701 A119 Dec 2019
Granted: 1 Dec 2020
Term ends: Not estimatedThe source records don’t support an estimate.

Classification5 codes

G16B 30/10
ICT specially adapted for sequence analysis involving nucleotides or amino acids: sequence alignment; Homology search
C12Q 1/6869
Involving nucleic acids: methods for sequencing
G16B 20/20
ICT specially adapted for functional genomics or proteomics, e.g. genotype-phenotype associations: allele or variant detection, e.g. single…
G16B
Bioinformatics, i.e. information and communication technology [ict] specially adapted for genetic or