Sequence-graph based tool for determining variation in short tandem repeat regions

Abstract

To provide methods, apparatus, systems and computer program products for genotyping repeat sequences such as medically significant short tandem repeats (STRs).SOLUTION: The methods involve aligning reads in a repeat sequence represented by a sequence graph, and using the aligned reads to genotype the repeat sequence. The sequence graph is a directed graph including at least one self-loop each representing a repeat sub-sequence. The reads are paired end reads, and both mates of each read pair may be used to genotype the repeat sequences. Some implementations can be used to determine degenerate codon repeats. Some implementations can be used to genotype repeat sequences each including two or more repeat sub-sequences. Some implementations can be used to genotype nucleic acid sequences each including at least one repeat sub-sequence and another genetic variant such as an insertion, deletion or substitution.SELECTED DRAWING: Figure 1C

Description

[Technical field]

[0001] (Incorporated by reference) The PCT application form is filed as a part of this application and is hereby co-filed. Each application claiming the benefit of or priority to any of the applications specified in the PCT application filed in is incorporated herein by reference in its entirety. [Background technology]

[0002] Repeat expansions are a special class of microsatellitera that contain short tandem repeat (STR) polymorphisms. Repeat expansions are short tandem repeats that form specific subunits. Also known as dynamic mutations due to their instability when stretched beyond their size Among the genetic diseases caused by unstable repeat expansions are fragile X chromosome 1 (FX chromosome 2), These include myelopathy, follicle-wide syndrome (FXS), Huntington's disease, and amyotrophic lateral sclerosis (ALS). .

[0003] Identifying repeat expansions is important in the diagnosis and treatment of certain genetic diseases. However, it is not possible to determine repeat sequences using short reads that do not completely traverse the repeat sequence. Therefore, to identify medically relevant repeat expansions, It is desirable to develop a method for using the Summary of the Invention

[0004] The disclosed embodiments include repeat sequences, such as short tandem repeat sequences, that may be associated with genetic diseases. Methods, devices, systems, and computer programs for sequencing genomic loci The method relates to a program product in which reads are organized into a sequence graph, each of which represents a genomic locus. and using the aligned reads to identify one or more repeats at a genomic locus. and genotyping the sequences. The sequence graphs are each a small set of sequences representing repeat sequences. It is a directed graph that contains at least one self-loop.

[0005] The first aspect of the present disclosure is a method for genotyping genomic loci that contain repetitive sequences. The present invention provides a computer-implemented method for a processor that includes one or more processors and a system memory. The method is carried out using a computer-implemented method for detecting a sequence of a nucleic acid sequence comprising one or more repeat subsequences. The method can be used to genotype one or more repeat sequences, including ) using one or more processors to collect sequence reads for test samples from a database; (b) collecting, by one or more processors, the sequence graph is a graph of the nucleic acid sequence. A data structure of a directed graph with vertices representing columns and directed edges connecting the vertices, The graph contains one or more self-loops, each of which represents a repeating subsequence, and each repeating subsequence A sequence contains one or more repeats of a nucleotide repeat unit, each of which is represented by a sequence graph. (c) aligning the sequence reads to one or more repeat sequences represented in one or more profiles; One or more genotypes for one or more repeat sequences are detected by the sequencer. and determining using the sequence reads aligned in rows.

[0006] In some embodiments, the repeat sequence of the one or more repeat sequences comprises at least one non-repeated sequence. In some embodiments, the repeat unit contains a specific repeat unit that contains a fully specified nucleotide. In the above example, the particular repeat unit contains a degenerate codon.

[0007] In some embodiments, one or more self-loops are 2 or more repeat subsequences. Contains one or more self-loops.

[0008] In some embodiments, the sequence graph includes two or more alternatives for two or more alleles. In some embodiments, the two or more alleles further comprise an indel or a substitution. In some embodiments, the substitution is a single nucleotide variant (SNV) or single nucleotide polymorphism. In some embodiments, the method includes aligning two or more alternative pathways. and further comprising genotyping two or more alleles using the sequence reads. In some embodiments, genotyping two or more alleles comprises genotyping two or more alleles. To determine the probability of allele selection, two or more alternative pathways are provided to the probability model. In some embodiments, the probability model is a function of allele coverage. The function simulates the allele probability using the Poisson distribution, negative binomial distribution, and binomial distribution. In some embodiments, the distribution is selected from a Poisson distribution, Kinetic parameters are estimated from the read length and average depth observed at genomic loci. will be done.

[0009] In some embodiments, prior to (b), the method further comprises aligning the sequence reads to a reference genome. The genomic coordinates of sequence reads are determined by combining the two, and each is represented by a sequence graph. Selecting a subset of sequence reads as those that align with one or more repeat sequences In some embodiments, the subset of sequence reads is represented by a sequence graph. In some embodiments, the reads are aligned in or near a region represented by In, a subset of sequence reads is located in or near the region represented by the sequence graph. In some embodiments, a subset of sequence reads may be combined to generate a map of unaligned reads. The target is one or more off-target genes that are known hotspots for mismatching reads. Contains reads aligned to the target region.

[0010] In some embodiments, aligning the sequence reads to the sequence graph comprises: Finding kmer matchings between paths in a sequence graph and matching one or more self- Extending the sequence graph including self-loops to a perfect alignment of the nodes and edges. nothing.

[0011] In some embodiments, aligning sequence reads to a sequence graph can be used to identify low confidence intervals for alignment. This involves reducing the graph by eliminating the results of reliability.

[0012] In some embodiments, aligning sequence reads to a sequence graph comprises aligning a portion of the reads to a sequence graph. Aligning sequences to a sequence graph and merging partial sequences to generate a complete sequence read This includes aligning and merging by forming sequences.

[0013] In some embodiments, the method comprises the step of: It further includes generating the sequence graph based on the specification.

[0014] In some embodiments, the sequence reads comprise paired-end reads, and operation (c) comprises: (i) Identifying anchor reads and anchored reads within paired-end reads and the anchor read aligns to or near one or more repeat sequences. An anchored read is a non-aligned read paired with an anchored read. (ii) identifying anchor reads and anchor-type reads within the end reads; One or more genotypes for one or more repeat sequences using at least anchored reads and determining:

[0015] In some embodiments, act (ii) comprises using an anchored lead and an anchored lead. The method includes determining one or more genotypes for one or more repeat sequences using a nucleic acid sequence encoding one or more of the nucleic acid sequences. In some embodiments, the anchor reads align within about 5 kb of the repeat sequence. In an embodiment, unaligned reads are reads that cannot be aligned to a sequence graph, or Contains reads that are poorly aligned to the column graph.

[0016] In some embodiments, the one or more repeat sequences comprise a short tandem repeat (STR) sequence. In some embodiments, the STR expansion is associated with fragile X syndrome, amyotrophic lateral sclerosis, ALS, Huntington's disease, Friedreich's ataxia, spinocerebellar degeneration, spinal and bulbar myopathy Atrophy, myotonic dystrophy, Machado-Joseph disease, or dentatorubral-pallidoluysian corpus Associated with atrophy.

[0017] In some embodiments, the method further comprises: extracting pairs of sequences from a test sample using a sequencer; generating end reads.

[0018] In some embodiments, the method further comprises extracting a test sample from the individual. nothing.

[0019] In some embodiments, the test sample may be a blood sample, a urine sample, a saliva sample, or a combination of both. The sample may be a blood sample or a tissue sample.

[0020] In some embodiments, the repeat unit comprises 1-50 nucleotides.

[0021] In some embodiments, the read comprises at least one of the one or more repeat sequences. It's also short.

[0022] Another aspect of the disclosure is a system for genotyping genomic loci that contain repetitive sequences. In some embodiments, the system includes a system memory and (a) a Using the above processor, sequence reads for test samples are collected from the database. (b) by one or more processors, The sequence graph is configured to align sequence reads to one or more repeat sequences that are generated by the nucleus. a data structure of a directed graph with vertices representing sequences of acids and directed edges connecting the vertices; A sequence graph contains one or more self-loops, each of which represents a repeating subsequence, and each repeat The subsequence comprises repeats of one or more nucleotide repeat units, and (c) one or more promoters. One or more genotypes for one or more repeat sequences are detected by the sequencer. one or more processors configured to determine using the sequence reads aligned in rows. Including,

[0023] In some embodiments, the system also sequences the nucleic acid of the test sample. It also includes a sequencer for

[0024] In some embodiments, one or more processors may perform various methods described herein. is configured to run

[0025] Another aspect of the present disclosure is a method for implementing a method for performing a program executed by one or more processors of a computer system. The above method for genotyping genomic loci containing repetitive sequences is then A non-transitory machine-readable medium storing program code for execution by a computer system, To provide a computer program product, the program code of which is (a) extracted from a database; (b) code for collecting sequence reads of test samples and (b) displaying them in sequence graphs. Code for aligning sequence reads to one or more repeat sequences represented by each of the sequences, Data in a directed graph, with vertices representing nucleic acid sequences and directed edges connecting the vertices. structure, the sequence graph contains one or more self-loops, each of which contains a repeating subsequence wherein each repeat subsequence comprises a repeat of one or more nucleotide repeat units, (c) aligning one or more genotypes for one or more repeat sequences to one or more repeat sequences. and code for determining using the induced sequence reads.

[0026] In some embodiments, the program code performs the operations of the methods described herein. Contains the code to run

[0027] Although the examples herein relate to humans and the language is primarily directed to humans, The concepts described herein are applicable to genomes from any plant or animal. These and other objects and features of the present invention will become apparent from the following description and appended claims. These and other aspects will become more fully apparent from or may be learned by practice of the present disclosure as set forth hereinafter. [Brief description of the drawings]

[0028] [Figure 1A] FIG. 1 is a schematic showing the difficulties in aligning sequence reads to repetitive sequences on a reference sequence. [Figure 1B] FIG. 1B is a schematic diagram showing alignment of sequence reads using paired-end reads, in accordance with certain disclosed embodiments, to overcome the difficulties depicted in FIG. 1A. [Figure 1C] 1 shows a flowchart illustrating a process for genotyping genomic loci that contain repetitive sequences according to some embodiments. [Figure 1D] 1 shows a first sequence graph representing a first genomic locus. [Figure 1E] 1 shows a second sequence graph representing a second genomic locus. [Figure 1F] 1 shows a third sequence graph representing a third genome. [Figure 1G] FIG. 1 shows a schematic diagram of a process for genotyping a variant in HTT comprising two STR sequences, according to some embodiments. [Figure 1H] FIG. 1H shows a schematic of a process for genotyping variants at the Lynch I locus, including SNVs and STRs, according to some embodiments. The left panel of FIG. 1H shows a schematic of the general process for targeted genotyping, and the right panel shows application of this process to genotyping variants at a locus associated with Lynch I syndrome. [Diagram 2] FIG. 1 is a flow diagram providing a high-level depiction of an example of a method for determining the presence or absence of a repeat sequence expansion in a sample. [Diagram 3] FIG. 1 is a flow diagram showing an example of a method for detecting repeat expansions using paired-end reads. [Figure 4] FIG. 1 is a flow diagram showing an example of a method for detecting repeat expansions using paired-end reads. [Diagram 5] FIG. 1 is a flow diagram of a method for using unaligned reads that are not related to any repetitive sequence of interest to determine repeat expansions. [Figure 6] FIG. 1 is a block diagram of a distributed system for processing samples for testing. [Figure 7] We demonstrate the accuracy of genotyping the CAG and CCG STRs at the HTT locus using different methods. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0029] The present disclosure provides methods for identifying repeat expansions of interest, such as expansions of repetitive sequences that are medically significant. The present invention relates to a method, an apparatus, a system, and a computer program product for performing repeat extension. Examples of long-term disorders include fragile X syndrome, ALS, Huntington's disease, and Friedreich's ataxia. Neuromuscular atrophy, spinocerebellar degeneration, spinal-bulbar muscular atrophy, myotonic dystrophy, Machado Joseph These include those associated with genetic diseases such as cerebral pallidal atrophy and dentatorubral-pallidoluysian atrophy. The present invention is not limited to these.

[0030] Unless otherwise indicated, practice of the methods and systems disclosed herein may be practiced in any manner suitable for use in molecular biology, Microbiology, protein purification, protein engineering, protein and DNA sequencing Conventional techniques and equipment commonly used, and recombinant DNA technology within the skill of the art. Such techniques and devices are known to those skilled in the art and are described in numerous texts and references. Studies (e.g., Sambrook et al., "Molecular Cloning g:A Laboratory Manual” Third Edition (Cold Spring Harbor, 2001), and Ausubel "Current Protocols in Molecular Biology" by This is described in "Y"

[1987] .

[0031] Numeric ranges are inclusive of the numbers defining the range. A maximum numerical limitation shall apply unless such lower numerical limitation is expressly written herein. As such, any lower numerical limit is intended to be included. Every minimum numerical limitation stated herein is the same as unless such higher numerical limitation is expressly written herein. As used herein, the term "numeric limit" includes any higher numerical limit as if the term "numeric limit" was given in its entirety. Any numerical range expressed herein includes all narrower numerical ranges expressly stated herein. includes any narrower numerical range that falls within such broader numerical range, as if each narrower numerical range were a nothing.

[0032] The headings provided herein are not intended to limit the disclosure.

[0033] All technical and scientific terms used herein unless otherwise defined herein The terms used herein have the same meaning as commonly understood by one of ordinary skill in the art. Various scientific dictionaries containing the words are known and available in the art. Any methods and materials similar or equivalent to those described herein may be used in the practice of the present disclosure. It has been found that several methods can be used in the practice or testing of the embodiments. and materials are described.

[0034] The terms defined below are more fully described by reference to the specification as a whole. The disclosure may be modified depending on the context in which it is used by those skilled in the art, so the invention will be described. It should be understood that no limitations to particular methodologies, protocols, and reagents are intended. definition

[0035] As used herein, the singular forms "a," "an," and "the" are used interchangeably unless the context indicates otherwise. Plural references are included unless expressly indicated otherwise.

[0036] Unless otherwise indicated, nucleic acids are written left to right in 5' to 3' orientation and amino acid sequences are Each is written left to right in amino to carboxy orientation.

[0037] The term "plurality" means two or more elements. For example, the term may be used in The method used was to determine the significance of repeat expansion in test and control samples. As used herein, it refers to a large number of nucleic acid molecules or sequence reads sufficient to identify them.

[0038] The term "repeated sequence" refers to a nucleic acid sequence that contains repeated occurrences of shorter sequences. The short sequences are referred to herein as "repeat units." Repeated occurrences of repeat units are In many contexts, the position of a repeating sequence is called a "repeat" or "copy" of the repeating unit. The repeat sequence is associated with a gene that codes for a protein. The repeat units may be in non-coding regions. For example, in normal samples, the FMR1 gene may occur in a repeat sequence that is not a repeat of the C In the GG repeat, for example, AGG such as (CGG)10+(AGG)+(CGG)9 There are samples with no breaks as well as long repeat sequences with some breaks. The sequence is prone to repeat expansions of related genes, which means that when the repeats exceed a certain number In various embodiments of the present disclosure, the repeats may be expanded, which may lead to genetic diseases. The number of repeats is counted as an intraframe repeat, regardless of breaks. Methods for this are further described below.

[0039] In various embodiments, the repeating unit comprises 1 to 100 nucleotides. Many of the repeating units shown are trinucleotide or hexannucleotide units. Several other well-studied methods are applicable to the embodiments disclosed herein. The repeating units may be 4, 5, 6, 8, 12, 33 or 42 nucleotide units. Examples of such methods include, but are not limited to, Richards (2001) Human See Molecular Genetics, 10, No. 20, 2187-2194. Applications of the present disclosure include repeating molecules that have multiple repeats or copies of the repeating unit. It is not limited to the specific number of nucleotide bases listed above, so long as it is relatively short compared to the sequence. For example, the repeating unit is at least 3, 6, 8, 10, 15, 20, 30, 40, 50 Alternatively or additionally, the repeat unit can contain up to about 100, 90, 80, 70, 60, 50, 40, 30, 20, 10, 6 or 3 nucleotides It may contain

[0040] Repeated sequences can expand under evolutionary, developmental, and mutational conditions, resulting in duplication of the same repeating unit. You can create more, which is called "repeat extension" in the field. This process is also called "dynamic mutation" due to the unstable nature of the stretch of repeat units. Several repeat expansions have been shown to be associated with genetic diseases and pathological conditions. Other repeat expansions are less well understood or studied. The methods may be used to identify both known and novel repeat expansions. In the present study, the repeat sequence having a repeat expansion is about 100, 150, 300 or 500 base pairs ( In some embodiments, the repeat sequence having a repeat expansion is longer than about 10 bp. 00bp, 2000bp, 3000bp, 4000bp, 5000bp, or 10000 bp etc. is longer.

[0041] In graph theory, vertices and edges are the two basic units upon which graphs are constructed. A vertex or node is one of the points at which a graph is defined and which may be connected by edges. In a graph diagram, vertices can be represented by labeled shapes and edges by A vertex is represented by a line (undirected edge) or an arrow (directed edge) extending from one vertex to another. will be done.

[0042] The two vertices connected by an edge are said to be the endpoints of the edge. A vertex x is said to be adjacent to another vertex y if x contains an edge (x, y).

[0043] An untargeted graph is a set of vertices and a set of vertices (connecting pairs of irregular vertices) A directed graph consists of a set of vertices and (regular) edges. It consists of a set of directed edges (connecting pairs of edges).

[0044] In graph theory, each edge is connected to two (or higher) nodes, called its endpoints. In a pergraph, there are more vertices. Edges may be directed or undirected. Undirected edges are also called lines, and directed edges are also called arcs or arrows. .

[0045] A directed edge is an edge that connects an upstream vertex and a downstream vertex. , and downstream vertices occur after the directed edge.

[0046] An edge that is not considered is an edge that connects two vertices, neither of which is a They may appear before one another in the rough path.

[0047] Loop, self-loop, and single-node loop are used interchangeably herein. A loop has one node and ends connected at both ends to one node.

[0048] A cycle is a path that contains two or more vertices, and the paths of a cycle start and end at the same vertex. A simple cycle has no repeated vertices or edges other than the start and end vertices. It's a cycle.

[0049] A cyclic graph is a graph that contains at least one cycle.

[0050] An acyclic graph is a graph that does not contain any cycles or self-loops.

[0051] The target acyclic graph (DAG) is a directed acyclic graph that does not contain any cycles or self-loops. This is a graph.

[0052] A graph path is an array of vertices and edges, where both ends of an edge are adjacent to the edges of the array. A graph path in a directed graph appears before a directed edge (or arc or arrow). It has an upstream vertex that occurs and a downstream vertex that occurs after the directed edge.

[0053] The Poisson distribution assumes that these events occur at a known constant rate and that the time since the last event is When occurring independently, it expresses the probability of a given number of events occurring at a given time or space interval. It is a discrete probability distribution.

[0054] The fully specified base symbols are G for guanine, adenine, thymine, and cytosine. , A, T, and C.

[0055] Non-fully specified nucleic acid nomenclature includes, among others, the following:

[0056] Purine (adenine or guanine): R

[0057] Pyrimidine (thymine or cytosine): Y

[0058] Adenine or thymine: W

[0059] Guanine or cytosine: S

[0060] Adenine or cytosine: M

[0061] Guanine or thymine: K

[0062] Adenine or Thymine or Cytosine: H

[0063] Guanine or cytosine or thymine: B

[0064] Guanine or adenine or cytosine: V

[0065] Guanine or adenine or thymine: D

[0066] Guanine or adenine or thymine or cytosine: N

[0067] The term "paired end reads" refers to two reads, one from each end of a nucleic acid fragment. To obtain the reads, paired end sequencing Paired-end sequencing refers to the reads obtained from a single insert. Some of the techniques used by Illumina include fragmenting DNA into sequences. Some protocols allow for reads from shorter inserts (e.g., about 10 to several hundred bp). are called short-insert paired-end reads, or simply paired-end reads. In contrast, reads from longer inserts (e.g., on the order of several thousand bp) In this disclosure, short insert paired reads are called mate pair reads. Both long-insert mate-pair reads and long-insert mate-pair reads may be used. No distinction is made regarding the process for analyzing peat elongation. Hence, the term "pair "Paired-end reads" are short insert paired-end reads and long insert main reads. It may also refer to both paired and unpaired reads, as further described later in this specification. In some embodiments, the paired-end reads are reads of about 20 bp to 1000 bp. In some embodiments, the paired-end reads include between about 50 bp and 500 bp. , containing reads of about 80bp to 150bp, or about 100bp. It will be understood that the codes need not be located at the very ends of the fragments being sequenced. Rather, one or both reads may be proximal to the ends of the fragment. The methods exemplified herein in the context of paired-end reads may involve the determination of the ends or ends of fragments. The various paired reads are independent of whether the reads are derived from other parts of the fragment. It can be run with either one.

[0068] As used herein, the terms "align" and "aligned" refer to the comparison of a read to a reference sequence. "refers to the process of comparing a reference sequence with a lead sequence, thereby determining whether the reference sequence contains the lead sequence." The alignment process seeks to determine whether a read can be mapped to a reference sequence. However, reads are not always aligned to the reference sequence. When the reference sequence contains reads In certain other embodiments, the reads may be mapped to a reference sequence, or in certain other embodiments, within a reference sequence. In some cases, the alignment may be performed to determine whether the reads are specifically located. Whether a read is a member of a given reference sequence (i.e., whether the read is present in the reference sequence or not) For example, the reference sequence for human chromosome 13 simply conveys whether a The alignment of the reads to the reference sequence of chromosome 13 indicates whether the read is present in the reference sequence of chromosome 13. The tool that provides this information is the Set Membership Tester. In some cases, the alignment is done by dividing the positions in a reference sequence to which the reads map. For example, if the reference sequence is the entire human genome sequence, the alignment will further indicate the location of the and / or the read is located on a particular strand of chromosome 13. or at a site.

[0069] Aligned reads are the ordering of those nucleic acid molecules against a known reference sequence, such as a reference genome. One or more sequences that are identified as being aligned in terms of sequence. The reads and their determined positions constitute a sequence tag. Alignment can be done manually. However, it is possible to align the reads in a time period that is reasonable for carrying out the methods disclosed herein. Since it is not possible to calculate the optimality of a particular step, it is typically performed by a computer algorithm. An example of an algorithm for aligning sequences is Illumina Genomics Ana ELAND Compilation, a distributed nucleotide data collection (ELAND) library, is part of the lysis pipeline. Efficient local alignment of computer programs. Also known as Bloom filters. Align the reads to the reference genome using a set membership tester (Seq. Ilter) or similar. No. 14 / 3, filed on Oct. 23, 2007, the entire contents of which are incorporated herein by reference. See US Pat. No. 5,445,288, filed April 25, 2014. Alignment of sequence reads is performed in a 1 The sequence may be a 0.00% sequence match, or a match of less than 100% (i.e., a non-perfect match). .

[0070] As used herein, the term "mapping" refers to the process of aligning a larger sequence, e.g. For example, this means assigning a read sequence to a reference genome.

[0071] In some cases, one end read of the two paired-end reads is identical to the reference sequence. The two paired-end reads are aligned to the repeat sequence, while the other end reads are aligned to the repeat sequence. In such cases, the paired reads aligned to the repeats of the reference sequence are not aligned. The reads that are not aligned to the repeat sequence but are aligned with the anchored read are called "anchor reads." Paired-end reads are called anchored reads. The reads can be anchored to and associated with the repeat sequences. In this embodiment, a non-aligned read is a read that cannot be aligned to a reference sequence and a read that cannot be aligned to a reference sequence. This includes both poorly aligned reads and reads with more misalignments than a certain criterion. A read is considered poorly aligned if it is aligned to a reference sequence that has bases. For example, in various embodiments, at least about 1, 2, 3, 4, 5, 6, 7, 8, 9, or 10 If the mismatch is not aligned, the read is considered to be poorly aligned. In such cases, both of the paired reads are aligned to a reference sequence. In such cases, in various embodiments, may analyze both reads as "anchor reads."

[0072] The terms "polynucleotide," "nucleic acid," and "nucleic acid molecule" are used interchangeably and refer to one The 3' position of the pentose of the nucleotide is phosphodiester-linked to the next pentose A covalently linked sequence of nucleotides attached to the 5' position of ribonucleotides, and in the case of DNA, deoxyribonucleotides). The nucleic acids include RNA molecules and DNA molecules, such as cell-free DNA (cfDNA) molecules. The term "polynucleotide" includes, but is not limited to, any form of sequence of nucleic acid. This includes, but is not limited to, single-stranded and double-stranded polynucleotides.

[0073] As used herein, the term "test sample" refers to a small sample that is evaluated for copy number alterations. Biological fluids, cells, tissues containing nucleic acids or mixtures of nucleic acids having at least one nucleic acid sequence; In certain embodiments, the sample is at least Each gene contains a single nucleic acid sequence, the number of copies of which may be mutated. Samples may include sputum / oral fluid, amniotic fluid, blood, blood fractions, or fine needle biopsy samples, urine The samples include, but are not limited to, peritoneal fluid, pleural fluid, etc. In some cases, the samples are taken from human subjects (e.g., patients), but assays can also be performed on dogs, cats, horses, goats, and other animals. In any mammalian sample, including but not limited to, sheep, cow, pig, etc. , copy number variation (CNV). The sample is obtained from a biological source. They may be used directly, as in Example 1, or after pretreatment to modify the sample properties. Such pretreatment includes preparing plasma from blood, diluting viscous fluids, etc. The pretreatment method may be filtration, precipitation, dilution, distillation, mixing, centrifugation, freezing, freeze-drying, These may include concentration, amplification, nucleic acid fragmentation, inactivation of interfering components, addition of reagents, lysis, etc. When such a pretreatment method is applied to a sample, Such pretreatment methods typically involve the occasional pretreatment of an untreated test sample (e.g., at concentrations proportional to the samples (not subjected to such pretreatment method(s) of interest) Such "treatment" is such that the nucleic acid(s) that "Treated" or "processed" samples are as described herein. For the purposes of the method, the sample is still considered to be a biological "test" sample.

[0074] The control sample may be a negative control sample or a positive control sample. "Sample" or "unaffected sample" refers to a sample that contains a large number of repeats within the non-pathogenic range. "repetitive sequences" refers to a sample that contains a nucleic acid that is known or suspected to have a repetitive sequence The "positive control sample" or "affected sample" is a sample that is highly contaminated within the pathogenic range. The negative control sample is known or expected to have a repetitive sequence with a number of repeats. Repeats of repetitive sequences in the samples were not usually extended beyond their normal range, but were not extended beyond the normal range in the positive control samples. The repeats of the repeat sequence in the sample are usually extended beyond their normal range. Nucleic acid in a test sample can be compared to one or more control samples.

[0075] The term "sequence of interest" as used herein refers to a sequence that is specific to a gene in healthy versus diseased individuals. The sequence of interest refers to a nucleic acid sequence that is associated with a difference in sequence expression due to a disease or genetic condition. The sequence of interest may be a repeat sequence on a chromosome that is expanded by It may be part of a coding or non-coding sequence.

[0076] As used herein, the term "next generation sequencing (NGS)" refers to the sequencing of clonally amplified molecules. and a sequencing method that allows for massively parallel sequencing of single nucleic acid molecules. A non-limiting example of NGS is reversible dye terminator sequencing. Sequencing-by-synthesis using reversible dye terminators synthesis, and sequencing-by-ligation Some examples include:

[0077] As used herein, the term "parameter" refers to a numerical value that characterizes a physical property. Often, parameters are quantitative data sets and / or numerical relationships between quantitative data sets. For example, the number of sequence tags that map to chromosomes and the number of tags that map to chromosomes are used to characterize the The ratio (or a function of the ratio) of the length of the chromosome being mapped is a parameter.

[0078] As used herein, the term "call criteria" refers to a set of criteria for determining whether a person has a medical condition. Used as a cutoff to characterize samples, such as test samples, that contain nucleic acids By comparing this threshold value with the parameter value, A sample giving rise to a parameter value such as In certain embodiments, the threshold may determine whether to suggest a control data set. It is calculated using the α-terminal repeat length and serves as a diagnostic limit for repeat expansion in organisms. In an embodiment, if the results obtained from the methods disclosed herein exceed a threshold, the subject The subject may be diagnosed with a repeat expansion. A suitable threshold for the methods described herein is , by analyzing the values ​​calculated for a training set of samples or control samples. The threshold can also be determined based on empirical performance parameters such as sequencing depth, read length, repeat length, etc. Alternatively, it can be calculated from the parameters of the repeat expansion. Using the affected samples, the selected threshold is verified to be consistent with the unaffected samples in the test set. It may also be useful to distinguish affected samples from unaffected samples. The choice of threshold depends on the confidence with which the user wants the classification to be made. In some embodiments, the training set used to identify an appropriate threshold value comprises at least 10, at least 20, at least 30, at least 40, at least 50, at least 60, at least 70, at least 80, at least 90, at least 100, at least At least 200, at least 300, at least 400, at least 500, at least 600 , at least 700, at least 800, at least 900, at least 1000, at least At least 2000, at least 3000, at least 4000, or more eligible samples Use a larger set of eligible samples to improve the diagnostic utility of the threshold. It may be advantageous to

[0079] The term "read" refers to a sequence read from a portion of a nucleic acid sample. Typically, but not necessarily, a read is a short sequence of consecutive base pairs in a sample. Represents a sequence. A read is symbolically represented by the base pair sequence (ATCG) of the sample portion. To determine whether a read matches a reference sequence or meets other criteria, The reads may be stored in a memory device and processed appropriately. The sequence information may be obtained directly from the sequence information stored in the database or indirectly from stored sequence information about the sample. Some sequences may be aligned and mapped to, for example, a chromosome or genomic region or gene. A sequence of sufficient length (e.g., a small It is a DNA sequence of at least about 25 bp.

[0080] The term "genomic read" refers to the read of any segment in the entire genome of an individual. It is used as such.

[0081] The term "site" refers to a unique location on a reference genome (e.g., chromosome ID, chromosomal location, and In some embodiments, a site refers to a residue, a sequence tag, or a segment on a sequence. It may also be the position of a segment.

[0082] As used herein, the term "reference genome" or "reference sequence" refers to a sequence that is determined from a subject. Any partial or complete sequence of any organism or virus that can be used to reference the sequence Refers to a specific known genomic sequence, such as a reference genome, a set of sequences, or a set of sequences that are used for human subjects. and many other organisms, all of which are managed by the National Center for Biotechnology Information. Nology Information at ncbi.nlm.nih.gov "Genome" means the complete genetic information of an organism or virus, expressed as a nucleic acid sequence. It means information.

[0083] In various embodiments, the reference sequence may be significantly larger than the reads aligned to it. For example, it is at least about 100 times greater, or at least about 1000 times greater. or at least about 10,000 times greater, or at least about 10 5 Twice as much or as little About 10 6 times larger, or at least about 10 7 It may be twice as large.

[0084] In one embodiment, the reference sequence is that of the full-length human genome. In another example, a reference sequence may be a specific chromosome, such as chromosome 13. In some embodiments, the reference Y chromosome is the human genome version. The Y chromosome sequence from the hg19 variant. Such sequences are called chromosomal reference sequences. Other examples of reference sequences include genomes of other species, as well as genomes of any species. Examples include chromosomes, partial chromosome regions (strands, etc.), etc.

[0085] In some embodiments, the reference sequence for alignment is about 1 to about 100 times the length of the read. In such an embodiment, the alignment and sequencing may have a sequence length of Instead of whole genome alignment or sequencing, it is considered as targeted alignment or sequencing. In these embodiments, the reference sequence typically comprises a gene and / or a repeat sequence of interest. include.

[0086] In various embodiments, the reference sequence is a consensus sequence or other combination of sequences from multiple individuals. However, in certain applications, the reference sequence may be taken from a particular individual. This is also fine.

[0087] As used herein, the term "clinically relevant sequences" refers to sequences that are known or have been linked to a genetic or medical condition. The absence of clinically relevant sequences or Determining the presence of a condition may include determining a diagnosis or confirming a diagnosis of a medical condition, or may be useful in providing a prognosis of disease development.

[0088] The term "derived" when used in the context of a nucleic acid or mixture of nucleic acids is used herein to refer to By "nucleic acid" is meant the means by which the nucleic acid(s) are obtained from the source from which the nucleic acid originates. For example, in one embodiment In some embodiments, the mixture of nucleic acids from two different genomes is a mixture of nucleic acids, e.g., cfDNA, They are naturally released by cells through naturally occurring processes such as necrosis or apoptosis. In another embodiment, the mixture of nucleic acids from two different genomes comprises the nucleic acids This means that the two different types of cells were extracted from the subject.

[0089] The term "based on" when used in the context of obtaining a particular quantitative value, It means using another quantity as an input to calculate a certain quantitative value as an output.

[0090] As used herein, the term "patient sample" refers to a biological sample obtained from a patient, i.e. A patient sample is a sample obtained from a subject, i.e., a recipient of medical attention, care, or treatment. In certain embodiments, the patient sample may be any of the samples obtained by It can be obtained by invasive procedures, such as a peripheral blood sample or a fecal sample. The methods described need not be limited to humans. Thus, patient samples may be derived from non-human mammals. Various veterinary samples can be from animals (e.g., cats, pigs, horses, cows, etc.) The uses are conceivable.

[0091] As used herein, the term "biological fluid" refers to a liquid obtained from a biological source. For example, blood, serum, plasma, sputum, lavage fluid, cerebrospinal fluid, urine, semen, sweat, tears, saliva, etc. As used herein, the terms "blood," "plasma," and "serum" refer to fractions thereof. Similarly, the term "sample" refers to a biopsy, swab, smear, etc. etc., a "sample" is a processed sample obtained from a biopsy, swab, smear, etc. The term expressly encompasses any fraction or portion thereof.

[0092] As used herein, the term "corresponding" refers to nucleic acids that are present in the genomes of different subjects. It means a sequence, e.g. a gene or chromosome, which is present in the genome of different subjects and which is necessarily Although not all genomes necessarily have the same sequence, the sequence of interest (e.g., a gene or a plasmid) It serves to provide identity, but not genetic information, of the chromosome (chromosome 1).

[0093] As used herein, the term "chromosome" refers to a set of DNA and protein components (especially histidine). The present invention has the efficacy of a living cell derived from a chromatin strand containing Means a genetic carrier. Conventional internationally recognized individual human genome chromosome number A marking system is used herein.

[0094] As used herein, the term "polynucleotide length" refers to the length of a region of a sequence or of a reference genome. The term "chromosome length" refers to the absolute number of nucleic acid monomer subunits (nucleotides) in a region. " refers, for example, to the |genome|.|ucsc|. on the World Wide Web. |edu / cgi-bin / hgTracks?hgsid=167155613&ch NCBI36 / hg18 assembly of human chromosomes found at romInfoPage= The term refers to the known length of a chromosome, given in base pairs, provided in

[0095] As used herein, the term "subject" refers to a mammal, an invertebrate, a vertebrate, a fungus, a yeast, or the like. The term "human" refers to non-human subjects such as bacteria, viruses, and the like. Examples herein relate to humans, Although the language primarily relates to humans, the concepts disclosed herein may be applied to genomes from any plant or animal. The present invention is applicable to veterinary medicine, animal science, laboratories, and similar fields. be.

[0096] As used herein, the term "primer" refers to a primer that is conducive to the synthesis of an extension product ( For example, the conditions include nucleotides, an inducing agent such as a DNA polymerase, and a suitable temperature and The isolated β-lactamases can act as starting points for synthesis when placed under conditions of pH Primers are preferred for maximum efficiency in amplification. It may be single-stranded or double-stranded. If it is double-stranded, it may be subjected to elongation. Before being used to prepare a composition, it is first treated to separate its strands. The primer may be an oligodeoxyribonucleotide. The length of the primer is sufficient to prime the synthesis of extension products in the presence of the inducer. The exact length depends on the temperature, source of primer, method used, and parameters used in primer design. The amount of data depends on many factors, including the introduction

[0097] Short tandem repeats (STRs) are ubiquitous throughout the human genome. Although our understanding of STRs is incomplete, emerging evidence indicates that STRs play important roles in fundamental cellular processes. This suggests that it will fulfill its role.

[0098] Repeat expansions are a special class of microsatellites and minisatellites, including STR polymorphisms. Repeat expansions are short tandem repeats that extend beyond a certain size. STR expansions are also known as dynamic mutations due to their instability when Atrophic lateral sclerosis, Friedreich's ataxia (FRDA), Huntington's disease (HD), and It is the leading cause of more than 20 severe neurological disorders, including idiopathic pulmonary fibrosis and fragile X syndrome. The following illustrates a small number of pathogenic repeat expansions that differ from the repetitive sequences in normal samples. The authors identified genes associated with repeat sequences, nucleic acid sequences of repeat units, and repeats of normal and pathogenic sequences. The repeat number of the repeat unit and diseases associated with repeat expansion are shown. [Table 1]

[0099] Genetic diseases involving repeat expansions are heterogeneous in many respects: size of the repeat unit, The severity, location relative to the affected gene, and pathogenic mechanism may vary from disease to disease. For example, ALS is located on the short arm of open reading frame 72 of chromosome 9. Hexane nucleotide repeat of the nucleotide GGGGCC in the C9orf72 gene In contrast, fragile X syndrome involves the fragile X mental retardation syndrome 1 (FMR1) on the X chromosome. A CGG trinucleotide repeat (triplet repeat) that affects the (FMR1) gene The expansion of CGG repeats is required for normal neurodevelopment, and is associated with the expansion of the fragile X chromosome. The expression of the mental retardation protein (FMRP) was not possible due to the length of the CGG repeat. Accordingly, alleles can be normal (not affected by the syndrome), premutated (fragile X-associated), or are classified as either a mutation (risk of a related disease) or a complete mutation (usually affected by a syndrome) Various estimates suggest that carriers with ataxia tendencies have between 60 and 230 reactions. and 5–54 repeats in affected and unaffected individuals. Mutations in the FMR1 gene that cause fragile X syndrome in individuals with There are 1,000 CGG repeats in the FMR1 gene. Repeat expansion in the FMR1 gene is thought to be responsible for approximately 5% of autism cases. It is believed that this mutation is the cause of autism, as it has been found to have an FMR1 repeat expansion. ennan,et al.(2011),Fragile X Syndrome,Cu Current Genomics 12(3):216-224. A definitive diagnosis involves genetic testing to determine the number of CGG repeats.

[0100] Several common characteristics of repeat expansion associated diseases have been identified in several studies. Repeat expansion or dynamic mutations are usually manifested as an increase in repeat number, and the mutation rate is related to the repeat number. Rare events such as loss of repeat interruptions may lead to alleles with increased probability of expansion. Such events can result in the formation of a new repeat sequence, known as a founder event. There is a relationship between the number of repeats and the severity and / or onset of diseases caused by repeat expansions. There may be a relationship.

[0101] Therefore, identifying and calling repeat expansions is useful in the diagnosis and treatment of various diseases. However, it is important to use reads that do not completely traverse the repeat sequences. Identifying repetitive sequences in a genome-wide dataset poses several challenges. First, the correlation between the reads and the reference genome It is difficult to align repeats to a reference sequence because there is no clear one-to-one mapping between repeats and a reference sequence. In addition, even if the reads are aligned to a reference sequence, the reads may not be relevant to medical applications. Reads are often too short to fully cover the repetitive sequences associated with It may be about 100 bp. In comparison, repeat expansions can span hundreds to thousands of base pairs. In fragile X syndrome, for example, the FMR1 gene contains more than 1000 repeats. Therefore, the 100 bp reads can be used for up to 3000 bp. cannot map the entire length of the repeat expansion. Assembling sequences may not overcome the short read vs. long repeat problem However, this is due to ambiguous alignment of a repeat in one read with a repeat on another read. This is because it is difficult to assemble short reads into longer sequences.

[0102] Alignment can be performed to check the completeness of the reference sequence, the non-specific correspondence between reads and sites on the reference sequence, or It is the primary source of information loss due to any significant deviation from the reference sequence. Read accuracy Systematic sequencing errors and other problems affecting detection of repetitive sequences In some experimental protocols, approximately 7% of the reads are aligned. The researchers have not yet developed the sequencing technology and analytical tools. Even if you are working to improve alignment, you may find yourself with unaligned or poorly aligned links. A significant amount of repeat expansions may always be present. To achieve this, they rely on unalignable or poorly aligned reads.

[0103] Methods using long reads to detect repeat expansions have their own challenges. Next-generation sequencing, currently available techniques that use longer reads, It is slower and more error prone than techniques that use short reads. For some applications, such as sequencing cell-free DNA, long reads are not feasible Cell-free DNA obtained from maternal blood can be used for prenatal genetic testing. Cellular DNA exists as fragments typically shorter than 200 with cell-free DNA Embodiments of the methods described herein can be used to identify medically relevant repeat expansions. To achieve this, short reads are used.

[0104] Furthermore, conventional methods are not designed to handle complex loci with multiple repeats. Important examples of such loci include HD, which is flanked by CCG repeats. CAG repeats that cause FRDA, flanked by adenosine homopolymers Causes spinocerebellar ataxia type 8 (SCA8) flanked by AA and CT repeats An even more extreme example is myotonic dystrophy type 2 (D The CCTG repeat in the CNBP gene causes M2. This repeat is a polymorphic TG and TCTG repeats (JELee and Cooper 2009), Accurate alignment of reads to gene loci is particularly difficult. Another type of complex repeat is Nine disease-associated polyalanine repeats (Shoubridge and Gecz 2012). The polyalanine repeats are the α-amino acid codons GCA, GCC, and GCG. , or repeated GCTs.

[0105] The population of variants can affect the accuracy of alignment and genotyping (Lincol Variants adjacent to low-complexity polymorphic sequences are Methods for discovery of consistently expressed or false barriers in such genomic regions are proposed. This can be even more problematic because it can output clusters of point calls. This is due to the increased error rate in these regions in the sequencing data (Benjamin ni and Speed ​​2012;Dolzhenko et al. 2017). One example is the adenosine homopolymer in MSH2 that causes Lynch syndrome I. It is a single nucleotide variant (SNV) adjacent to the . 99).

[0106] The embodiments disclosed herein are capable of handling such complex loci. They use sequence graphs as a general and flexible model of each target locus.

[0107] In some embodiments, the disclosed methods utilize paired-end sequencing. This addresses the aforementioned challenges in identifying and calling repeat expansions. Add-end sequencing fragments DNA into sequences, called inserts. Some protocols used by Illumina include Reads from inserts (e.g., about 10 to several hundred bp) are paired with short inserts. In contrast, longer insert reads are called double-end reads, or simply paired-end reads. Reads from the target (e.g., about several thousand bp) are called mate pair reads. As mentioned above, short-insert paired-end reads and long-insert Both mate pair reads of the cert are capable of being sequenced in accordance with various embodiments of the methods disclosed herein. It may be used in the above embodiment.

[0108] FIG. 1A shows sequence reads obtained from a sample of long repetitive sequences, particularly those with repeat expansions. We address the specific difficulty of aligning sequence reads to repetitive sequences on a reference sequence when aligning At the bottom of FIG. 1A, there is a relatively short repeat shown by vertical hatched lines. There is a reference sequence 101 with sequence 103. In the middle of the figure, the Also shown is a hypothetical patient sample with a long repeat sequence 107 having a repeat expansion. At the top of the figure, the positions of the corresponding sites in the sample sequence 105 are indicated. The sequence reads 109 and 111 shown are the sequence reads 109 and 111 that are related to the sequence of the nucleotide ... In some of these sequence reads, several base pairs arise from long repeat sequences107 and form vertical halves. The repeats in the lead 1 are highlighted in circles, as shown by the cross-hatched lines. 11 is aligned to reference sequence 101 because the repeat does not have a clear corresponding position on reference sequence 101. These potentially unaligned reads are potentially difficult to align to the reference sequence 101. These potential non-aligned reads cannot be clearly linked to the repeat sequence 103 in It is difficult to obtain information about the repeat sequence and the extent of the repeat sequence from the 111. These reads tend to be shorter than the long repetitive sequences with repeat expansions107, No definitive information about the identity or location of repeat sequence 107 can be directly provided. In addition, the repeats in the read 111 are identified by their ambiguous corresponding positions in the reference sequence 101 and the The ambiguous relationship between the cards 111 makes it difficult to assemble them. The 107 repeats in the sample are shown as black and semi-solid black. Reads may be aligned by bases occurring outside of the repeat sequence 107. If a read has too few base pairs outside of 07, the read may be poorly aligned. Therefore, some of these reads with partial repeats may not be aligned. Some of the reads may be analyzed as anchored reads, and other reads may be analyzed as described further below. The reads may be analyzed as anchor reads so that the reads can be easily identified.

[0109] FIG. 1B illustrates a method for overcoming the difficulties illustrated in FIG. 1A in some disclosed embodiments. FIG. 1 is a schematic showing how paired-end reads can be used in In end sequencing, the sequencing is performed on both ends of a nucleic acid fragment in a test sample. Shown at the bottom of FIG. 1B are a reference sequence 101 and a sample sequence 105. , and leads 109 and 111 equivalent to those shown in FIG. 1A. Shown are fragments 125 derived from a test sample sequence 105, as well as pairs Primers for read 1 to obtain two end reads, reads 135 and 137 region 131 and primer region 133 of read 2. Fragment 125 is a paired-end Also referred to as an insert for the lead. In some embodiments, the insert is These may be amplified with or without PCR. Some repetitive sequences cannot be successfully sequenced by conventional methods, including PCR amplification. For such sequences, amplification may not involve PCR. Alternatively, amplification may be carried out by PCR.

[0110] The insert 125 shown in FIG. 1B is flanked by two vertical arrows shown in the lower half of the figure. Specific examples of the sample sequence 105 include those shown in FIG. In this example, the insert 125 is an antisense fragment corresponding to a portion of the long repeat 107 in the sample sequence 105. The length of the insert may be adjusted for various applications. In some embodiments, the insert comprises a repeat sequence or repeat expansion of interest. In other embodiments, the insert may be somewhat shorter than the repeat sequence. Or it may have a length similar to a repeat sequence with a repeat extension. In the form, the insert is somewhat longer than the repeat sequence or the repeat sequence having a repeat expansion. Such inserts may be, in some embodiments, further described below. For paired sequencing, inserts may be long. Typically, The reads from the insert are shorter than the repeats. The inserts are longer than the reads. Paired-end reads identify longer repetitive sequences in a sample than single-end reads. This allows for better signal capture from the stretch.

[0111] The illustrated insert 125 has two lead primers on two edges of the insert. In some embodiments, the read primer region has regions 131 and 133. In other embodiments, the primer region is unique to the insert. The primer for Read 1 is introduced into the insert by extension. The primers of read 1 allow hybridization of insert 125 of insert 132. The immer region 131 is shown. The extension of primer 132 of read 1 is shown as 135. The insert 125 is labeled to generate a first lead, or lead 1. The right end of the insert 125 contains: Allow hybridization of primer 134 of lead 2 to insert 125 The primer region 133 of read 2 is shown, which is labeled as 137. , beginning the second lead, or lead 2. In some embodiments, the insert 125 It may also contain an index barcode region (not shown here), Rex also provides a mechanism for identifying different samples in the sequencing process. In some embodiments, the paired-end reads 135 and 137 are generated from a synthesis platform. These can be obtained by Illumina sequencing using the platform. An example of a sequencing process carried out on such a platform is hereinafter referred to as a sequencing method. As described further in the next section, this process generates two paired-end reads and two index Create a sex lead.

[0112] Next, as shown in Figure 1B, the resulting paired-end reads were sequenced to identify relatively short repeat sequences1 03. Thus, the relative positions of the pair of reads and orientation are known. This allows for the determination of alignment or alignment issues, such as those shown in circle 111. As can be seen at the bottom of Figure 1B, the insufficient reads correspond to a pair of reads, read 1. 09, which is indirectly associated with a relatively long repeat sequence 107 in the sample sequence 105. In an exemplary embodiment, paired-end sequencing is used to The reads obtained from this example are approximately 100 bp and the inserts are approximately 500 bp. In our experiment, the relative positions of two paired-end reads were approximately 300 bases from their 3' ends. The relationship between the read pairs is that one read is located in the repeat region. In some cases, the first read of the pair is a reference sequence. The second read of the pair is aligned to the reference sequence, and the non-repetitive sequence flanking the repeat region on the array is For example, the pair of leads 109a and 110b shown in the bottom half of FIG. 1a, the left one of the pair, 109a, is the first lead, and the right one, 11 1a is the second lead. Considering the pair of two leads 109a and 111a, Despite the fact that read 111a of the present invention cannot be aligned to the reference sequence 101, The second read 111a can then be associated with the repeat region 107 in the sample sequence 105. By knowing the distance and direction of the second lead 111a relative to the first lead 109a, This allows the position of the second lead 111a within the long repeat region 107 to be further determined. If there is a break between the repeats in the second lead 111a, the reference sequence 101 The location of the break relative to the reference may also be determined. Anchor reads are referred to as anchor reads in this disclosure. The lead on the right side, such as 111a, paired with the lead is called an anchored lead. Thus, the non-aligned sequence can be anchored and associated with the repeat expansion. Thus, short reads can be used to detect long repeat expansions. The challenge in detecting repeat expansions is that it is typically difficult to identify the expansions due to the difficulty of sequencing. While this increases with length, the methods disclosed herein provide a higher yield than shorter repeat extension sequences. This allows detection of higher signals from longer repeat expansion sequences. The longer the repetitive sequence or repeat expansion, the more reads are anchored to the expansion region. This allows more reads to fall completely within the repeat region, resulting in more repeats per read. This is because.

[0113] In some embodiments, the disclosed methods include: In some embodiments, the method further comprises analyzing the frequency distribution of the number of repeats found in the In other embodiments, only the anchored reads and the anchor Both types of lead are analyzed. The distribution of test samples is determined from the affected samples to the unaffected samples. can be compared to empirically or theoretically derived criteria that separate samples that are not affected In this way, it is determined whether the test sample contains the repeat expansion under consideration, Able to make clinically relevant calls.

[0114] The methods and devices described herein employ next generation sequencing technology (NGS). This allows for massively parallel sequencing. In the present invention, a clonally amplified DNA template or a single DNA molecule is Volkerding et al. Clin Chem 55:641-658

[2009] ; Metzker M Nature Rev 11:31-46

[2010] The DNA is sequenced in a massively parallel fashion in a flow cell (described below). These include pyrosequencing, reversible dye terminator synthesis (sequ encing-by-synthesis with reversible dye terminators), sequencing by oligonucleotide probe ligation These include, but are not limited to, ion-semiconductor sequencing. The DNA from each sample can be sequenced individually (i.e., single-stranded). or on a single sequencing run, indexed Pooling DNA from multiple samples into genomic molecules (i.e., multiplexing) This method (sequencing) can generate up to several million DNA sequences. Examples of sequencing techniques that can be used to obtain sequence information are further described below.

[0115] Various repeat extension analyses using DNA samples are performed to determine the alignment of the DNA from a sequencer to a reference sequence. The reference sequence may be the sequence of a whole genome, a chromosome, or a subunit of a genome. From a computational perspective, the repetition reduces the ambiguity of the alignment. This can result in bias and error at the overall chromosome counting level. In some embodiments, the paired-end reads coupled with adjustable insert length are This can eliminate ambiguity in the alignment of sequences and aid in the detection of repeat expansions. Genotyping variants at repetitive sequence loci using sequence graphs

[0116] FIG. 1C shows a method for genotyping genomic loci that contain repeat sequences, according to some embodiments. 1 shows a flowchart illustrating a process 140 for detecting genetic A locus is a variant catalog that contains the genomic location and the structure of the locus at the genomic location. 1D, 1E, and 1F are diagrams illustrating some embodiments of the present invention. Three different sequence graphs are shown.

[0117] FIG. 1G shows a barrier in HTT comprising two STR sequences according to some embodiments. FIG. 1G, panel (a) shows a schematic of the process for determining the genotype of a genotyped sample. A part of the variant catalogue, including the nome loci and their structures as locus specifications. For example, ignoring repeats, the sequence at the HTT locus is CAGCAACA GCGG (SEQ ID NO: 2) and the sequence at the CNBP locus is CAGGCAGAC A (sequence number 3).

[0118] FIG. 1H illustrates the Lynch I gene, including SNVs and STRs, according to some embodiments. A schematic diagram of the process for genotyping variants at a locus is shown in FIG. Box 162 shows the general structure of the locus specification, and Box 163 shows the Lynch I A specific example of locus specification for (MSH2) is shown.

[0119] In the heterologous catalog, locus structures are expressed using a restricted subset of regular expression syntax. For example, the repeat region bound to the HD is designated by the CAACAG interruption. Expression shown to have variable numbers of separated CAG and CCG repeats (CAG) * CAACAG (CGG) * or SEQ ID NO:2 (ignoring repeats). The region bound to is expressed (A). * (GAA) * The region bound to SCA8 corresponds to , (CTA) * (CTG) * The DM2 repeat region, consisting of three adjacent repeats, corresponds to (CAGG) * (CAGA) * (CA) * or as defined by SEQ ID NO:3 (ignoring repeats) , MSH2 SNVs adjacent to homopolymers causing Lynch syndrome I are (A| T)(A) * Corresponds to.

[0120] Furthermore, normal expression may be multi-allelic, or International Union of Pure and Applied Chemistry (IUPAC) notation ( “Nomenclature for Incompletely Specified Bases in Nucleic Acid Sequences.Recomme ndations 1984.Nomenclature Committee of the International Union of Biochemistry( The present invention includes "degenerate" base abbreviations that can be specified using the International Union of Standards and Standards (IUB) (1986). This makes it possible.

[0121] Incompletely specified bases corresponding to bases in degenerate codons are referred to as degenerate bases herein. By degenerating the bases, certain classes of imperfect DNA repeats can be represented. For example, different bases may occur at the same position. * Polyalanine repeats can be encoded by the nucleotide sequence of ... R) * It can be coded as follows:

[0122] In some embodiments, the repeat sequence contained in the genomic locus is a short tandem repeat (S In some embodiments, the FTR expansion is a cause of Fragile X syndrome, myocardial infarction, myocardial infarction, and myocardial infarction. Amyotrophic lateral sclerosis (ALS), Huntington's disease, Friedreich's ataxia, spinocerebellar degeneration spinal-bulbar muscular atrophy, myotonic dystrophy, Machado-Joseph disease, or dentate red neuropathy Associated with nuclear pallidoluysian atrophy.

[0123] Process 140 includes collecting nucleic acid sequence reads for a test sample from a database. See block 142. In some embodiments, the nucleic acid sequence reads include The genome is first aligned to a reference genome, as described below. The sequence reads are realigned to the genomic locus of interest. can be directly aligned to the sequence graph without first being aligned to a reference genome.

[0124] Process 140 identifies sequence reads for genomic loci that contain one or more repeat sequences. See Block 144. Genomic Locus Sequence is represented by data stored in system memory having a sequence graph data structure. A sequence graph is a directed graph with vertices representing nucleic acid sequences and directed edges connecting the vertices. A nucleic acid sequence in a vertex contains one or more nucleic acid bases. A sequence graph contains one or more Each self-loop represents a repeat sequence of one or more repeat sequences. The string contains repeats of one or more nucleotide repeat units.

[0125] In some embodiments, the sequence reads are first aligned to a reference genome. A subset of the reads are aligned to one or more sequence graphs that represent one or more sequences of interest. In some embodiments, the genomic coordinates of the reads are determined before the reads are aligned. The reads determine repeat expansions in tens to thousands of regions (each region corresponds to a sequence graph). The total number of initially aligned reads that are realigned to the sequence graph during each implementation of the embodiment. can range from thousands to millions of reads.

[0126] In some embodiments, a sequence or locus of interest is first aligned to or Reads that are in the vicinity are selected as a subset of reads, and the subset is then grouped into a sequence group. The sequence graph is arranged to repeat the sequences represented by each of the graphs, and the sequence graph is In various embodiments, the sequence of interest has one or more self-loops that represent a repeat sequence of or about 10, 50, 100, 500, 1,000, 2,000, 3,000 from the locus , 4,000, 5,000, 6,000, 7,000, 8,000, 9,000, 10, Reads of 000, 50,000, or 100,000 bases are not relevant to the sequence or gene of interest. In some embodiments, the target gene is located approximately 1.0 to 200 nm from the target gene locus. 00, 2,000, 3,000, 4,000, 5,000, 6,000, 7,000, 8 Reads within 2,000, 9,000, or 10,000 bases are located near the locus of interest. Some of the raw reads contain repeat sequences that are difficult to align unambiguously, for example. In some embodiments, the initial alignment may be insufficient because the Reads with poor initial alignment (e.g., as measured by alignment score) are not considered. Reads that align to or near a given locus (paired-end read pair) In some embodiments, the reads are paired with the previously described mismatched reads. The reads that were initially aligned to off-target regions, which are hotspots of knowledge, were are aligned to.

[0127] 1D, 1E, and 1F show three different sequence graphs according to some embodiments. FIG. 1D shows a first gel containing a repeat sequence having the trinucleotide repeat unit CAG. 11 shows a first sequence graph 1100 representing the NOM locus. The first sequence graph 1100 shows The first sequence graph also includes vertices 1102 and 1112, each of which represents two adjacent sequences. It also includes vertex 1106, which represents a repeat sequence containing the trinucleotide repeat unit CAG. The sequence graph of 1 connects vertex 1102 (adjacent sequence) and vertex 1106 (CAG repeat sequence). The edge 1104 continues from the vertex 1102 to the vertex 1106. The orientation of the vertices indicates the relative positions of the two nucleic acid sequences. The first sequence graph also includes vertices 1102 and 1103. (adjacent sequence) and vertex 1106 (CAG repeat sequence). , the direction goes from vertex 1102 to vertex 1106. The first sequence graph also 6 (CAG repeat sequence) and a vertex 1112 (adjacent sequence). The first sequence graph also has a repeating sequence contains the repeating unit CAG (shown at vertex 1106) which repeats one or more times. The path from the start vertex to the end vertex of the sequence graph contains a self-loop 1108. Represents the sequence of a locus, which sequence includes nucleotides near repeat sequences, such as flanking sequences. There are cases.

[0128] FIG. 1E shows a second sequence graph 1200 representing a second genomic locus. The graph 1200 includes vertices 1202 and 1224, each of which represents two adjacent sequences. The sequence graph of FIG. 2 also shows repeat sequences containing the trinucleotide repeat unit CAG, and vertices 120, each of which represents a repeat sequence containing a nucleotide repeat unit CCG; The second sequence graph includes vertex 1, which represents the unique sequence CAACAG, and vertex 1, which represents the unique sequence CAACAG. The second sequence graph further includes directed edges 1204, 1210, 1214, and These directed edges include vertices 1202, 1206, and 1220, as shown. , 1212, 1216, and 1224 in a directed manner. The second sequence graph also The repeat sequence includes one or more repeating units of the repeating unit CAG (shown at vertex 1206). The second sequence graph also includes a self-loop 1208 representing the repeat sequence, which may be repeated one or more times. The self-loop 121 represents the inclusion of a repeating unit CCG (shown at vertex 1216) that returns Includes 8.

[0129] FIG. 1F shows a third sequence graph 1300 representing a third genomic locus. Graph 1300 is similar to the second sequence graph 1200, but with two alleles CA The two alleles are SNV or SNP pairs. A directed edge 1310, a vertex 1312, and a directed edge 1314. represents the first allele of the CAC. Edge 1320 represents the second allele of CAT. The third sequence graph is , 1306, 1322, and 1328, It also contains a self-loop 1308 which represents the repeat sequences CAG and CCG. and 1324. It further includes directed edges 1304 and 1326.

[0130] In some embodiments, sequence reads are synthesized using the techniques described below. are aligned to.

[0131] 1. The Kmer index is the number of times that a Kmer is opened given a Kmer from a sequence. Constructed over the entire graph so that all graph nodes that start or end can be enumerated In some cases, kmer may start on one node and restart on another. It may end.

[0132] 2. For each graph hit, extract two subgraphs, one in kmer order. The subgraph is then extended by repeats up to the remaining lead length. length, but assuming the repeats are not elongated, the remaining read length is It does not include any nodes further away from the kmer hit. The procedure is a breadth-first search. , generate a data structure that contains:

[0133] -Concatenation of all node sequences (including expanded repeats) in the subgraph

[0134] -Backtack on the Smith-Waterman algorithm When racking, you can easily get the node ID from its offset in the array. The index of such a node

[0135] - an array of offsets for the end nodes that the edge is in, relative to the start offset of each node

[0136] -Easily indicate whether a base is at the start of a node or not at the start of a node For each node, enumerate the offsets of all the terminal offsets of its predecessor nodes. Index.

[0137] 3. Alignment

[0138] -Supports affine gaps.

[0139] - Find the best score for the sequence given the above information and the penalty matrix. Find the column(s).

[0140] Two diff interfaces are available:

[0141] -The best alignment and the second best alignment scores are reported.

[0142] - The entire array of best alignment and second best alignment scores.

[0143] The alignment is penalized for gaps between the candidate kmer and the start of the aligned sequence. Some embodiments impose two compile-time parameters: Fine tune the.

[0144] The current algorithm for matrix filling is available in two embodiments: be.

[0145] -N * A continuous loop with complexity M.

[0146] - Fixed length compile time parameters, fixed size loops with consecutive loops to 16 By default, gcc will use SSE or AVX vector instructions on the CPU. Automatically recognizes and converts commands.

[0147] In some embodiments, a particular repeat unit of the repeat sequence of one or more repeat sequences is In some embodiments, the sequence includes at least one incompletely specified nucleotide. The repeating unit of comprises a degenerate codon.

[0148] In some embodiments, one or more self-loops comprise two or more repeat sequences representing two or more repeat sequences. See, for example, panels (b) of Figures 1E, 1F, and 1G. sea ​​bream.

[0149] In some embodiments, the sequence graph includes two or more alternatives for two or more alleles. See, for example, FIG. 1F, reference numbers 1312 and 1318. See also 1H, reference numbers 165 and 166 for the locus Lynch I (MSH2). In 67a, the upper pathway includes the apex of nucleobase A and the lower pathway includes the apex of nucleobase T.

[0150] In some embodiments, two or more alleles contain indels or substitutions. In one embodiment, the substitution comprises a single nucleotide variant (SNV) or a single nucleotide polymorphism (SNP). See, for example, FIG.

[0151] In some embodiments, aligning sequence reads to a sequence graph comprises: Finding a kmer matching between a path in a string graph and then matching this path to a perfect alignment In some embodiments, the alignment includes extending a subgraph around the path. and unrolling any loops in the subgraph to produce a directed acyclic graph. and the Smith-Waterman alignment of sequence reads to a directed acyclic graph. and executing the above.

[0152] In some embodiments, aligning sequence reads to a sequence graph can be used to identify low confidence intervals for alignment. This involves reducing the graph by eliminating the results of reliability. The leads are aligned to the graph. The method then searches for other similar alternative alignments, which are This is done by reordering the paths through the graph that overlap with the path. For example, it is possible to detect cases where one or both ends of the initial alignment have low confidence. , which indicates that they may have been aligned in different ways. It is possible to detect low and high confidence regions, which leads to the identification of gene variants. It is possible to accurately determine what the

[0153] In some embodiments, aligning sequence reads to a sequence graph comprises aligning a portion of the reads to a sequence graph. Aligning sequences to a sequence graph and merging partial sequences to generate a complete sequence read This includes aligning and merging by forming sequences.

[0154] In some embodiments, the process also includes a genetic analysis of the genomic locus, including the locus structure. generating a sequence graph based on the specification of the loci. The locus specifications are defined in the variant catalogue as described above.

[0155] Panel (b) of Figure 1G for a schematic of read alignment to the sequence graph of the HTT locus. See also (d). Figure 1H shows a sequence group including the locus Lynch I(165). 1 shows a schematic of a locus analyzer 164 for performing alignment of reads to rough loci.

[0156] The process 140 uses the sequence reads aligned in the sequence graph to generate one or more repeat sequences. Further comprising determining the genotype of one or more of the sequences. See Block 140. FIG. 1G shows the determination of two STRs (CAG and CCG) at the TT locus. See also panel (e) of Figure 1. The sequence on the left, which contains a CAG repeat, is CAGCAGCAGC AGCAG (SEQ ID NO: 4). The left sequence containing the CCG repeat is CCGCCGCCG CCGCCG (sequence number 5).

[0157] FIG. 1H shows an S chromosome carrying an A / T allele (169a) and an A monomer repeat (169b). A variant gene analysis was performed to determine variants at the Lynch I locus, including NV. FIG. 1H also shows the genotyper module (168). and providing them to a variant genotyper (168). The analyzer module (166), and the A / T allele (167a) and A monomer repeat ( An example of a variant analyzer for SNVs with genotype 167b is shown. The locus results are shown in box 170 of FIG. 1H, specifically, the A / T allele. (171a) and SNV genotypes with A monomer repeats (171b) are shown. .

[0158] In some embodiments, the sequence graph shows two alternative pathways for two alleles. the method further comprising: detecting two or more alleles using sequence reads aligned to two or more alternative pathways; In some embodiments, the gene is further genotyped. Genotyping the offspring involves genotyping two or more genes to determine the probability of two or more alleles. In some embodiments, the method further comprises providing a coverage of alternative routes to the probabilistic model. Rate models simulate the probability of an allele as a function of allele coverage, , the function is selected from the Poisson distribution, the negative binomial distribution, the binomial distribution, or the beta binomial distribution .

[0159] In some embodiments, the probability function is a Poisson distribution and the rate parameter is a It is estimated from the read length and average depth observed at the NOM locus.

[0160] In the Poisson model, the allele probabilities are expressed as follows:

[0161] P(Y=y)=(C y ×e -C ) / y!

[0162] y is the read probability of the base.

[0163] C is the average depth at the genomic locus.

[0164] In some embodiments, the average depth C is

[0165] It is estimated as C=LN / G.

[0166] G is the length of the genomic locus.

[0167] L is the lead length.

[0168] N is the number of all reads. Graph Tools Library

[0169] In some embodiments, basic sequence graph functionality is implemented using the Graph Tools library ( We apply the GraphTools library. The library handles the core graph extraction (the graph itself, the Algorithms for sorting linear sequences into graphs (paths, graph sorting), their behavior, and Implement the algorithm.

[0170] In some embodiments, the sequence graph consists of nodes and directed edges. It is possible to have self-loops (edges connecting a node to itself), but other loops are not allowed. The nodes contain sequences consisting of core bases and IUPAC degenerate base codes. .

[0171] A graph path is a set of nodes that are connected by a starting point of the path on the first node and an ending point on the last node. The position is defined by an array of nodes passed through it together with the zero-based half-open coordinate system. The library is used for pathway extension and contraction, overlap checking, and pathway Define multiple actions on a path, including merging.

[0172] Graph alignment is the process of aligning how a linear query sequence (usually a sequenced read) fits into a graph. In some embodiments, graph alignment involves the process of determining whether a graph path and a graph are aligned. and an array of linear alignments that define alignments of the query sequence to the nodes of the rough path. Use the corresponding operations above to reduce the graph alignment or merge it with other graph alignments. Path reduction provides a mechanism for removing unreliable aligned ends, On the other hand, alignment merging is a method to derive a complete alignment of a query sequence from the alignment of partial sequences (e.g., kmer). Used by the graph alignment algorithm for stitching. The alignment algorithm works by finding kmer matches between the query sequence and the graph. In some embodiments, the alignment is performed by , Extract the subgraph around the path that corresponds to the kmer match (any Then, it performs a directed acyclic graph on the resulting Then perform the Smith-Waterman alignment. In some embodiments, the algorithm is , supports affine gap penalties, and compilation produces SIMD code It is written using constant-length loops to allow do.

[0173] In some embodiments, a search algorithm may be used to obtain the graph path. However, the search algorithm must wait until the alignment reaches the search criteria or convergence (e.g., the alignment score is the highest). Increase or decrease the number of repetitions of the repeating unit represented by the self-loop until This involves lengthening or shortening the path.

[0174] In some embodiments, a plurality of graph paths are generated from the sequence graph, and each graph path A path represents a particular number of repeats of a repeating unit represented by a self-loop. Multiple graph paths are sorted, and then paths that satisfy the sorting criteria are selected for graph sorting. will be done. Application Architecture

[0175] Some embodiments are described as a general tool for targeted variant genotyping. During each run, the program genotypes a set of variants (Figure 1H). Try to do so.

[0176] Variants that are close to each other are listed in the variant catalog file. , are grouped into the same locus. The locus structure is a restriction of the regular expression (RE) syntax. Res is the core base abbreviation and IUPAC degenerate base code. It contains an alphabetical sequence consisting of group codes, optionally separated by interruptions in the sequence. To be isolated, one or more expressions (<sequence>)?, (<sequence a>|<sequence b>), (<sequence>) * , (<sequence>)+. These expressions include insertions / deletions, substitutions, 0 Each of the sequences corresponds to a sequence that is repeated at least once. The locus description includes a set of reference regions for the locus and reference coordinates for each constituent variant. nothing.

[0177] The bulk of the work is to synthesize a sequence graph representing the loci from the corresponding RE during initialization. Organized in harmony by objects of the Locus Analyzer class After initialization, the locus analyzer aligns them into a graph and then computes the resulting alignment as Variant analysis is performed for each variant in the locus. e) processes the relevant reads by passing them through the variant analyzer. Extract the relevant information to genotype the variants that correspond to the actual genotype The resulting sequence is passed through a genotyper that performs a decision. Use the results to create the output VCF file.

[0178] For example, the processing of loci by pathogenic variants associated with Lynch I syndrome The locus analyzers used were SNV and STR analyzers (Fig. S1, right panel). do. Indel genotyper

[0179] Some STRs may have small insertions or deletions (indels) nearby. Indels such as are modeled as additional subgraphs in the flanking sequences of STRs. The number of reads mapped to each allele (or graph path) is modeled by a Poisson distribution. The kinetic parameters are calculated based on the average depth and read length observed at the locus. The genotype likelihoods are calculated under a Bayesian framework. Identification of repeat expansions

[0180] The use of the embodiments disclosed herein provides increased efficiency, sensitivity, and and / or selectively determining various genetic conditions associated with repeat expansion. Some embodiments of the invention use sequence reads that do not completely traverse the repetitive sequences. In addition, we will investigate the medical causes of mental retardation, such as CGG repeat expansions in fragile X syndrome. The present invention provides a method for identifying and calling genetically related repeat expansions. Short reads, such as those in However, when analyzed by the disclosed method, samples with repeat expansions were The pool shows a statistically significant excess of reads containing multiple repetitive sequences. Large repeat expansions are those in which both reads are composed completely or nearly completely of repetitive sequences. Contains non-aligned read pairs. A standard sample is used to identify background expectations.

[0181] The conventional wisdom is that repeat expansions cannot be detected without reads spanning the entire repeat. Previous approaches to detect repeat expansions have focused on sequences that are sufficiently long to span the repetitive sequences. Targeted sequencing with long reads when the reads were abnormal due to length Results of some disclosed embodiments are based on normal (non-targeted) sequence data. Surprisingly, the results are not as accurate as they might be, because the read length is only about 100 bp. The method described herein provides a method for detecting repeat expansions that provides very high sensitivity. The described method involves insert lengths shorter than the length of the entire repeat sequence (i.e., two sequences Repeat units in repeat extensions using paired reads (with leading and intervening sequences) The number of can be detected.

[0182] See details of the method for determining the presence of a repeat expansion according to some embodiments. FIG. 2 shows an embodiment for determining the presence or absence of a repeat expansion of a repetitive sequence in a sample. A flow diagram providing a high level depiction is shown. Repeated sequences are made up of short sequences called repeat units. A nucleic acid sequence that contains a repetitive pattern of repeating units. Table 1 above lists examples of repeating units, both normal and pathogenic. The number of repeats in the repeat sequence of the repeating sequence of the sex sequence, the gene associated with the repeat sequence, and the linker To provide examples of diseases associated with peat elongation, the process 200 of FIG. Begin by obtaining paired-end reads. See block 202. The paired-end reads are processed to align to a reference sequence that contains the repeat sequence of interest. In some syntaxes, the alignment process is also called the mapping process. The test sample may be a body fluid, such as a nucleic acid-containing sample and as further described in the Sample section below; The sequence reads may be in the form of a tissue or the like. The sequence reads are subjected to an alignment process to map to a reference sequence. As described elsewhere in this disclosure, various alignment tools and algorithms are available. Alignment algorithms may attempt to align reads to a reference sequence using a Some reads are successfully aligned to the reference sequence, while other reads are not. may not be aligned normally to the reference sequence, or may not be aligned to the reference sequence. Reads that are contiguously aligned to a reference sequence are associated with sites on the reference sequence. The reads and their associated sites are also called sequence tags. Some sequence reads, including If a read aligns to a reference sequence that has more mismatched bases than a certain threshold, In various embodiments, the reads are considered to be poorly aligned. A read is misaligned if it aligns with 3, 4, 5, 6, 7, 8, 9, or 10 mismatches. In other embodiments, alignment with at least about 5% mismatch is considered sufficient. In other embodiments, the reads are considered to be poorly aligned if If the reads align with approximately 10%, 15%, or 20% mismatched bases, is considered inadequate.

[0183] As shown in FIG. 2, the process 200 includes: Proceed to identify anchored leads. See block 204. Anchor Reads are generated using paired-end reads that align to or are close to the repeat sequence of interest. For example, an anchor read is a read that has a sequence length shorter than the length of the insert. The repeat sequence can be aligned to a position on the reference sequence separated from the repeat sequence by a separation length of For example, the anchor read may be shorter than the sequence length of the anchor read. Only the length of the sequence, or the anchor lead and the sequence connecting the anchor lead to the anchored lead The length of the insert minus the length of the anchored read is then combined with the The alignment is added to a position on the reference sequence separated from the repeat sequence by a sequence length that is less than the length of the alignment. In some embodiments, the repeat sequence can be a repeat of the repeat unit CGG. The usual reference sequence may be a repeat sequence in the FMR1 gene, including The repeat sequence in the gene contains about 6 to 32 repeats of the repeating unit CGG. When expanded beyond this repeat, the repeat expansion becomes pathogenic and causes fragile X syndrome. In some embodiments, the repeat sequence of interest is aligned within 1000 bp. When the reads are aligned in the same order, they are considered to be aligned near the sequence of interest. In morphology, this parameter is approximately 100bp, 200bp, 300bp, 400bp, 5 00bp, 600bp, 700bp, 800bp, 900bp, 1500bp, 2000 bp, 3000 bp, 5000 bp, etc. In addition, this In addition, reads paired with anchor reads may not align well with the reference sequence. It also identifies anchored reads that are or cannot be aligned. Further details of the code are provided above.

[0184] The process 200 detects whether repeat expansions of repetitive sequences are present in the identified anchored reads. Based in part on the presence of See block 206. This determining step is described further below. In some embodiments, the process may include any suitable analysis and calculation. The process uses the identified anchored reads as well as the anchored reads to identify repeat extensions. In some embodiments, the identified amplicons are used to determine whether a potential The number of repeats in the car and anchored reads was analyzed and theoretically derived or influenced The results are compared to one or more criteria derived from empirical data of control samples received.

[0185] In various embodiments described herein, the repetition is obtained as an intraframe repetition. Two repeats of the same repeating unit fall into the same reading frame. The sequence of nucleotides in a nucleic acid (NA or RNA) molecule is divided into a set of contiguous non-overlapping triplets. During translation, triplets code for amino acids and are called codons. Thus, any particular sequence has three possible read frames. In an embodiment, the repeats are counted according to three different lead frames, and the maximum of the three counts is Large is determined to be the number of corresponding repeats that are read.

[0186] An example of a process with additional operations and analysis is shown in Figure 3. Figure 3 shows a process with multiple iterations. 3 shows a process 300 for detecting repeat expansions using paired-end reads; A flow diagram is shown. The process 300 includes additional upstream steps for processing the test sample. The process involves sequencing test samples containing nucleic acids to generate paired-end reads. The process begins by obtaining a code. See block 302. In some embodiments, Test samples may be obtained in a variety of ways, as further described in the Samples section below. For example, a test sample may be prepared from a biological fluid, such as plasma, or The sample may be any suitable sample as described below. The sample may be a simple blood draw. In some embodiments, the test samples can be obtained using non-invasive procedures such as The pool contains a mixture of nucleic acid molecules, e.g., cfDNA molecules. The test sample was a maternal plasma sample containing a mixture of fetal and maternal cfDNA molecules. It is.

[0187] Prior to sequencing, the nucleic acids are extracted from the sample. Suitable extraction processes and devices include: As described elsewhere herein. In some embodiments, the device is a multiplexed Process DNA from multiple samples in total to provide library and sequence data In some embodiments, the device 20 analyzes DNA from eight or more test samples. As described below, the sequencing system processes the extracted DNA fragments in parallel. Processing A to generate a library of encoded (e.g., barcoded) DNA fragments can be generated.

[0188] In some embodiments, the nucleic acid in the test sample is selected from the group consisting of: Multiplex sequencing or synthesizing, as described further in the Recombination section, To prepare sequencing libraries for groupplex sequencing, After the sample has been processed and prepared, sequencing of the nucleic acid may be performed on the species. In some embodiments, the method may be further described in the Sequencing Methods section below. Various next generation sequencing platforms and protocols have been employed, as described. Good too.

[0189] Regardless of the particular sequencing platform and protocol, in block 302 In the method, at least a portion of the nucleic acids contained in the sample is sequenced to obtain hundreds of thousands, Generate tens or even millions of sequence reads (e.g., 100 bp reads). In an embodiment, the reads include paired-end reads, as described below with respect to FIG. In other embodiments, such as those described above, in addition to paired-end reads, hundreds, thousands, or even hundreds of Single-end long reads containing 100,000 bases may be used to determine repeat sequences. In some embodiments, the sequence reads are about 20 bp, about 25 bp, about 30 bp, about 35bp, approx. 36bp, approx. 40bp, approx. 45bp, approx. 50bp, approx. 55bp, approx. 60bp , about 65bp, about 70bp, about 75bp, about 80bp, about 85bp, about 90bp, about 95 bp, about 100bp, about 110bp, about 120bp, about 130, about 140bp, about 150 bp, about 200bp, about 250bp, about 300bp, about 350bp, about 400bp, about 4 Technical advances include single end sequences greater than 500 bp. When paired-end reads are generated, the length of the This is expected to enable further advances in clinical trials.

[0190] The process 300 converts the paired-end reads obtained from block 302 into The sequence then proceeds to align the sequence to a reference sequence containing the sequence. See block 304. In embodiments, the repeat sequence is subject to expansion. In some embodiments, the repeat expansion is In another embodiment, the repeat expansion of the repetitive sequence is However, it has not been previously studied to establish a link with genetic disease. The method allows for the detection of repetitive sequences and repeat expansions regardless of any associated pathology. In some embodiments, the reads are aligned to a reference genome, such as, for example, hg18. In other embodiments, the reads are generated based on a sequence of a reference genome, e.g., a chromosome or chromosome segment. A read that uniquely maps to a reference genome is known as a sequence tag. In one embodiment, at least about 3×10 6 Limited sequence tags of at least Approximately 5×10 6Limited sequence tags, at least about 8 × 10 6 Limited sequence tags, few At least about 10 x 10 6 Limited sequence tags, at least about 15 × 10 6 Limited Sequence tags, at least about 20 x 10 6 Limited sequence tags, at least about 30 × 10 6 Limited sequence tags, at least about 40 × 10 6 or at least Also about 50 x 10 6 Limited sequence tags are obtained from reads that uniquely map to the reference genome. can be done.

[0191] In some embodiments, the process comprises filtering the sequence reads prior to alignment. In some embodiments, the filtering of reads can be performed to eliminate false reads and low quality reads. A software program implemented in the sequencer to filter the reads For example, Illumina's Sequencing Control Software (SCS) and Conse nsus Assessment of Sequence and Variatio The software program enhanced the raw image data generated by the sequencing reaction. Degree scores, base calls, quality score alignments, and biologically relevant information for downstream analysis by converting false reads and low quality reads into additional formats to provide Filter.

[0192] In certain embodiments, the reads generated by the sequencing device are stored in an electronic format. The alignment is accomplished using a computing device as described below. Each read is compared to a reference genome, which is often It is too large (millions of base pairs) to identify a unique corresponding site. In this embodiment, the alignment procedure can limit the mismatches between the reads and the reference genome. In some cases, one, two, three or more base pairs in a read may match the corresponding base pairs in the reference genome. Mismatches in base pairs are tolerated and mapping is still performed. , if the read is aligned to a reference sequence with 1, 2, 3, or 4 base pairs or less, the read are considered aligned reads. Correspondingly, unaligned reads are considered aligned. Poorly aligned reads are more difficult to assemble than aligned reads. In some embodiments, the reads are 1%, 2%, or more mismatches. , 3%, 4%, 5%, or 10% of the base pairs to a reference sequence. The reads are considered aligned reads.

[0193] Paired-end reads are aligned to a reference sequence containing the repeat sequence of interest and then processed. The method 300 identifies anchor reads and anchored reads among paired-end reads. See block 306. As described above, the anchor reads may be located at or near repeat sequences. is an end read aligned near it. Anchor reads are paired-end reads that align to within 1 kb of a repeat sequence. are paired with anchored reads, but as mentioned above, cannot be aligned to the reference sequence or is poorly aligned to the reference sequence.

[0194] The process 300 comprises sequencing the identified anchorages to determine whether or not there are expansions of the repetitive sequence. The repeat number of repeat units in the reads and / or anchored reads is analyzed. More specifically, The process 300 may include: This involves using the number of repeats in a read to obtain a high-count read. In some embodiments, high count reads are reads that have more repeats than a threshold. In other embodiments, high count reads are obtained only from anchored reads. is obtained from both the anchored reads and the anchored reads. If the number of repeats is close to the maximum number of repeats that can be read, the read is considered to be high-column. For example, if the read is 100 bp and the repeat unit under consideration is If the length of the repeats is 3 bp, the maximum number of repeats is 33. In other words, the maximum is It is calculated from the length of the read and the length of the repeat unit. Specifically, the maximum number of repeats is , obtained by dividing the lead length by the length of the repeating unit and rounding down In this example, various embodiments may have at least about 28, 29, 30, 31, 3 100 bp reads with 2 or 33 repeats were identified as high-count reads. The number of replicates may be increased or decreased for high count reads based on empirical factors and considerations. In various embodiments, the threshold for high count reads may be adjusted up or down. At least about 80%, 85%, 90%, or 95% of the maximum number.

[0195] Next, the process 300 determines whether the repeat extension of the repetitive sequence is based on the number of high count reads. See block 310. In this embodiment, the analysis involves comparing the obtained high count reads to a call criteria and determining whether the criteria are exceeded. In some embodiments, the repeat expansion is determined to be likely present if The call criteria are obtained from the distribution of high-count reads in the control sample. Multiple control samples known to contain or suspected to contain repetitive sequences were analyzed. The control sample is analyzed and high count reads are obtained for the same control sample. The distribution of high-count reads in a sample can be obtained, and the number of high-count reads greater than a certain value can be obtained. We can estimate the probability of an unaffected sample having this particular Given the call criteria set at a fixed value, sensitivity and selectivity can be determined. In some embodiments, the call criteria is set to a threshold, whereby calls with more high counts than the threshold are The probability of an unaffected sample having a back lead is less than 5%. In other words, p The value is less than 0.05. In these embodiments, as the repeat sequence is extended, the repeat The sequences are longer and can occur entirely within the repeat sequences, resulting in more high counts. In various alternative embodiments, a lower core lead can be obtained for the sample. The rule criterion is the probability of an unaffected sample having high-count reads higher than the threshold. is selected to be less than about 1%, 0.1%, 0.01%, 0.001%, 0.0001%, etc. Call criteria may be adjusted upward or downward based on a variety of factors. It will be appreciated that there may be a need to improve the sensitivity or selectivity of tests.

[0196] In some embodiments, the call criteria for the number of high count reads from a control sample is Alternatively, or in addition to experimentally obtaining call criteria to determine repeat extensions, Theoretically, the length of the paired-end reads and the length of the repeat-extension sequences can be obtained. The sequence is then fully present within the repeat, taking into account a number of parameters, including length and sequencing depth. It is possible to calculate the expected number of reads that will be generated using, for example, sequencing depth. By using the approximation function, the average spacing between reads in the aligned genome can be calculated. If a genome is sequenced to a depth of 30x, the total bases sequenced are the size of the genome multiplied by the depth. For humans, this is approximately 3x10 9 x30=9x10 10 Each If the reads are 100bp long, a total of 9x the read depth required to achieve this depth 10 8 Since the genome is diploid, half of these reads are Sequence chromosomes / haplotypes, and the rest sequence other chromosomes / haplotypes. Sequencing: 4.5 × 10 per haplotype 8 There are leads, and this number is the total By dividing the genome size, we obtain the average spacing between the start positions of each read (i.e., an average of 6. 3x10 every 7bp 9 / 4.5x10 8 Using this number, we obtain the average interval of 1. Based on the size of the repeat in a particular individual, a link that can be completed within the repeat is generated. If the total size of the repeat sequence is 300 bp, the number of Any read that starts within the first 200 bp of a repeat sequence can be complete within the repeat sequence (Any reads starting within the last 100 bp will be (At least partially outside the repeat sequence). Reads can be aligned every 6.7 bp. Therefore, 200bp / (6.7bp / read) = 30 reads are expected to be located within the repeat sequence. It is expected that the alignment will be perfect at . There is some variability around this number, but this allows This allows for an estimation of all reads that can be complete within a repeat sequence with respect to the size of the stretch. The length of the repeat sequence and the corresponding predicted sequences that are perfectly aligned in the repeat sequence calculated according to the method. The expected number of leads is shown in Table 2 of Example 1 below.

[0197] In some embodiments, the calling criteria is based on the first and last observation of a repeat sequence in a read. The distance between the nucleotides is calculated from the distance between the nucleotides and the repeats, and therefore the difference in the sequence Allows for mutations.

[0198] In some embodiments, the process is characterized by the presence of fragile X syndrome, ALS, Huntington's disease, , Friedreich's ataxia, spinocerebellar degeneration, spinal-bulbar muscular atrophy, myotonic dystrophy Risk of genetic diseases such as glaucoma, Machado-Joseph disease, and dentatorubral-pallidoluysian atrophy The present invention may further include diagnosing the individual from whom the sample was obtained with a repeat It is likely that repeat expansions are present in the test sample, and that they involve gene and repeat expansions. This may be based on a determination that the repeat sequence is more likely to be present. In the absence of a known genetic disease, some embodiments detect abnormally high repeat numbers. This allows new genetic causes of disease to be identified.

[0199] FIG. 4 shows another process for detecting repeat expansions, according to some embodiments. 4 is a flowchart illustrating a process for detecting a test sample rather than a high count read. The number of repeats in the paired-end reads is used to determine the presence of repeat expansions. The Seq 400 sequences test samples containing nucleic acids and generates paired-end reads. The process begins by obtaining block 402, which is equivalent to block 302 of process 300. The process 400 aligns paired-end reads to a reference sequence, which includes repetitive sequences. Block 304 in process 300 continues by aligning the See Block 404. This process involves the anchoring of paired-end reads. The method proceeds by identifying repeat and anchored reads. Leads aligned in or near a row, and anchored leads are In some embodiments, the non-aligned read is a non-aligned read paired with a non-aligned read. Reads that cannot be aligned to the reference sequence and reads that align poorly to the reference sequence. Includes both.

[0200] After identifying the anchor leads and anchor-type leads, the process 400 Block 40 obtains the anchor read and / or the number of repeats in the anchored read from the sample. 8. The process then proceeds to remove all anchors from the test sample. A distribution of repeat numbers for the reads and / or anchored reads is obtained. In this embodiment, only the repeats from the anchored reads are analyzed. Replicates of both the cured and anchored leads are analyzed. The distribution of the multiple samples is compared to the distribution of one or more control samples. See block 410. In some embodiments, the process further comprises: determining whether the distribution of the test sample is greater than the distribution of the control sample; If the repeat expansion is statistically significantly different from the repeat expansion, the repeat expansion is present in the test sample. See block 412. Process 400 is similar to process 300. Unlike the process described above, which analyzes only high-count reads, Analyze the repeat counts of reads including low count reads as well as the repeat counts of reads.

[0201] In some embodiments, the comparison of the distribution of the test sample to the distribution of the control sample is Use the Whitney rank test to determine whether two distributions are significantly different In some embodiments, the analysis comprises comparing the distribution of the test sample to the control sample. If the trend is more toward higher replicates in the test sample, The presence of t-proliferation was determined to be highly probable, and the p-value of the Mann-Whitney rank test was approximately 0. p-value is less than .0001 or 0.00001. It improves the selectivity or sensitivity of the test. It can be adjusted as necessary.

[0202] The process for detecting repeat expansions described above with respect to Figures 2-4 includes the use of anchored We use reads that are non-aligned and paired with reads that align to the repeat sequence of interest. Variations of these processes may be medically relevant, new, Both of these studies have been carried out in order to discover previously unidentified repeat expansions. Searching through unaligned reads of a read pair, which is composed almost entirely of repetitive sequences The method does not quantify the exact number of repeats, but further quantification is possible. It is powerful in identifying extreme repeat expansions or outliers that should be flagged for optimization. By combining this method with longer reads, it is possible to obtain sequences up to 200 bp in length. The above repeats can be both identified and quantified.

[0203] FIG. 5 is not related to any repeat sequence of interest to identify repeat expansions. A flow diagram of a process 500 using unaligned reads is shown. To detect extensions, unaligned reads across the genome may be used. By sequencing test samples containing the acid and obtaining paired-end reads. See block 502. The process 500 begins with paired-end reads. To the reference genome, proceed as follows. See block 504. The process identifies non-aligned reads with respect to the entire genome. Paired-end sequences cannot be aligned to the sequence or are poorly aligned to the reference sequence. See block 506. Next, the process performs a step of The repeat number of the repeat unit in the test sample is analyzed to determine whether repeat expansions may be present in the test sample. This analysis is agnostic to any particular repeat sequence. The analysis can be applied to a variety of potential repeat units and the test samples The repeat numbers of different repeat units from the sample can be compared to those of multiple control samples. The comparison techniques between test and control samples described above can be applied to this analysis. Comparison shows that the test sample has an unusually large number of repeats of the repeating unit. If so, determine whether the test sample contains a repeat expansion of the particular repeat sequence of interest. To do so, additional analysis may be performed (see block 510).

[0204] In some embodiments, further analysis is performed to identify long repeats with medically relevant repeat expansions. The reads in this additional analysis include very long sequence reads that may span multiple sequences. In some embodiments, single molecule sequencing is Long reads are obtained using sequencing or synthetic long-read sequencing. In this embodiment, the relationship between repeat expansions and genetic diseases is known in the art. However, in other embodiments, the association between the repeat expansion and the genetic disease is It need not be established in the art.

[0205] In some embodiments, the number of repeats of the repeat unit in the unaligned reads of operation 510 is The analyzing includes a high count analysis equivalent to act 308 of FIG. The high count reads include obtaining a number of reads having more repeats than a threshold. The number of high count reads in the test sample is compared to the call criteria. In some embodiments, the threshold for high count reads is a maximum number of replicates. This maximum is at least approximately 80% of the paired-end length over the length of the repeat unit. In some embodiments, high count reads are calculated as a ratio of the length of the read. It also includes reads that are paired with unaligned reads and that are more repetitive than a threshold.

[0206] In some embodiments, prior to the further analysis of operation 510, the process further comprises: (a) determining whether the Paired reads that align on or near repetitive sequences in the reference genome (b) identifying a particular repeat sequence of interest for operation 510; and and then further analyzing the repeat sequence of interest. Any of the methods described above in relation to FIGS. 2 to 4 may be employed. sample

[0207] The samples used to determine repeat expansion contain one or more repeat sequences of interest. The nucleic acid may be extracted from any cell, fluid, tissue, or organ containing the nucleic acid in which the repeat expansion is to be determined. In some embodiments involving fetal diagnosis, the cell-free nucleic acid sample may include For example, it is advantageous to obtain cell-free DNA (cfDNA) from maternal body fluids. Cell-free nucleic acids, including NA, can be isolated from biological samples, including plasma, serum, and urine, by techniques known in the art. The nucleotide sequences can be obtained by various methods known in the art (e.g., Fan et al., Proc Natl Acad Sci 105:16266-16271

[2008] , Koide et al., Prenatal Diagnosis 25:604- 607

[2005] , Chen et al., Nature Med.2:1033- 1035

[1996] , Lo et al., Lancet 350:485- 487

[1997] , Botezatu et al., Clin Chem. 46:1 078-1084,2000, and Su et al., J Mol.Diagn.6: (See 101-107

[2004] .)

[0208] In various embodiments, nucleic acids (e.g., DNA or RNA) present in a sample can be used Prior to use (e.g., prior to preparing a sequencing library), specific or non-specific enrichment DNA is used as an example of a nucleic acid in the following illustrative examples. Nonspecific enrichment of cfDNA is the process of enriching samples prior to preparing cfDNA sequencing libraries. Pull DNA from the sample using genomic DNA, which can be used to increase the level of DNA. It refers to whole genome amplification of a fragment. Whole genome amplification methods are known in the art. Degenerate oligonucleotide-primed PCR (DOP), primer extension PCR technique (PEP) ), and multiple displacement amplification (MDA) are 1 is an example of a DNA amplification method. In some embodiments, the sample is enriched for DNA. do not have.

[0209] The nucleic acid-containing sample to which the methods described herein are applied is typically prepared as described above. In some embodiments, the repeat extension fragment is a repeat fragment. The nucleic acids to be screened for length can be purified or isolated by any of a number of known methods. are separated.

[0210] Thus, in certain embodiments, the sample comprises purified or isolated polynucleotides. The sample may comprise or consist essentially of a peptide, or the sample may be a tissue sample, a biological fluid sample, Suitable biological fluid samples include blood, plasma, and the like. , serum, sweat, tears, sputum, urine, sputum, ear fluid, lymph, saliva, cerebrospinal fluid, lavage, bone marrow Suspension, vaginal fluid, cervical fluid, femoral neck fluid, cerebral fluid, ascites, milk, respiratory tract, intestinal tract and urogenital tract These include, but are not limited to, vaginal secretions, amniotic fluid, milk, and leukocytosis samples. In some embodiments, the sample may be, for example, blood, plasma, serum, sweat, tears, sputum, urine, Samples that can be easily obtained by non-invasive procedures, such as sputum, ear fluid, saliva, or feces, In certain embodiments, the sample is a peripheral blood sample or a blood sample of a peripheral blood sample. In other embodiments, the biological sample is a swab or or a smear, a biopsy, or a cell culture. In another embodiment, the sample is The biological sample is a mixture of the above biological samples. For example, the biological sample may be a biological fluid sample, a tissue sample, or the like. The present invention can include two or more of a sample, a culture sample, and a cell culture sample. In the present context, the terms "blood," "plasma," and "serum" refer to any fraction thereof or processed portion thereof. Similarly, where a sample is taken from a biopsy, swab, smear, etc. "Sample" explicitly refers to a processed fraction or portion obtained from a biopsy, swab, smear, etc. Includes.

[0211] In certain embodiments, the samples are from different individuals, either from the same individual or from different individuals. Samples from different developmental stages of the body, samples from different affected individuals (e.g. Samples obtained in individuals suspected of having the disease, normal individuals, and individuals at different stages of the disease samples from individuals receiving different treatments for a disease; samples from individuals with different environmental factors; samples from individuals with a medical condition, individuals predisposed to a medical condition, individuals exposed to infectious agents Examples of samples that can be used include, but are not limited to, samples from individuals who have been infected with the virus.

[0212] In one exemplary, but non-limiting embodiment, the sample is obtained from a pregnant female, e.g. A maternal sample obtained from a pregnant woman. In this case, the detection of potential chromosomal abnormalities in the fetus. Analyzing samples using the methods described herein to provide an early diagnosis The maternal sample may be a tissue sample, a biological fluid sample, or a cell sample. Examples of biological fluids include, but are not limited to, blood, plasma, serum, sweat, tears, sputum, urine, and sputum. , ear fluid, lymphatic fluid, saliva, cerebrospinal fluid, lavage, bone marrow suspension, vaginal flow, cervical fluid, Femoral neck fluid, cerebrospinal fluid, ascites, milk, respiratory, intestinal and genitourinary secretions, and leukocytopenia Examples include:

[0213] In certain embodiments, the sample may also include in vitro cultured tissues, cells, or other The cultured samples may be obtained from any polynucleotide-containing source. A culture (e.g., tissue or cell) maintained in a culture medium and under conditions (e.g., pH, pressure, or temperature). ), cultures (e.g., tissues or cells) maintained for different periods of time, different factors or reagents ( For example, cultures (e.g., tissues or cells) treated with a drug candidate or modulator (e.g., a drug candidate or modulator) or from sources including, but not limited to, tissue and / or cell cultures of any type; It can be collected.

[0214] Methods for isolating nucleic acids from biological sources are known and can vary depending on the nature of the source. One of skill in the art can readily isolate nucleic acids from a source as required for the methods described herein. In some cases, it may be useful to fragment the nucleic acid molecules in the nucleic acid sample. Fragmentation can be random or, for example, by restriction endonuclease. Random fragmentation can be specific, as achieved using enzyme digestion. Methods for the preparation of nucleotide sequences are known in the art and include, for example, limited DNAse digestion, alkaline treatment, etc. These include mechanical stresses, mechanical forces, and physical shear. Sequencing library preparation

[0215] In various embodiments, sequencing requires the preparation of a sequencing library. The preparation may be carried out on a variety of sequencing platforms. Fragmentation of NA (by sonication, nebulization or shearing) followed by DNA repair and terminal cleavage 3. Polishing (blunt end or A-overhang), and platform-specific adaptor ligation In one embodiment, the method described herein comprises using next generation sequencing technology (N GS) can be used to sequence multiple samples individually as genomic molecules. Sequence determination (i.e., singleplex sequencing) or single sequence determination On the sequencing run, individual pooled samples containing indexed genomic molecules are This allows for multiplex sequencing (e.g., multiplex sequencing). The method can generate up to several million DNA sequence reads. In the embodiment, the genomic nucleic acid sequence and / or the sequence of the indexed genomic nucleic acid can be, for example, For example, this can be determined using next generation sequencing (NGS) techniques as described herein. In various embodiments, analysis of the large amounts of sequence data obtained using NGS can be performed. , may be executed using one or more processors as described herein.

[0216] In various embodiments, the use of such sequencing techniques includes sequencing live. It does not involve the preparation of lari.

[0217] However, in certain embodiments, the sequencing methods contemplated herein include In one exemplary approach, the sequencing library is prepared. The preparation of the library consists of adapter-modified DNA fragments (e.g., poly(A)-1, 1-diamino-2-propanediol) that are ready to be sequenced. The process involves generating a random set of sequences (nucleotides) for sequencing polynucleotides. A fragment is a complementary fragment generated from an RNA template, for example, by the action of reverse transcriptase. Either DNA or cDNA, such as DNA or cDNA that is a target DNA or copy DNA It can be prepared from DNA or RNA, including equivalents and analogs of either. Otides are in double-stranded form (e.g., genomic DNA fragments, cDNA, PCR amplification products, etc.). In certain embodiments, the polynucleotide may occur in a single It can occur in single stranded forms (e.g., ssDNA, RNA, etc.) and be converted to the dsDNA form. By way of example, in certain embodiments, the following is used to prepare a sequencing library: The single stranded mRNA molecule can be copied into a double stranded cDNA suitable for amplification. The exact sequence of the nucleotide molecule is generally not critical to the method of library preparation. In one embodiment, the polynucleotide molecule is a DNA molecule. More specifically, in certain embodiments, the polynucleotide molecule is a genetic It represents the entire or substantially the entire genetic complement of an organism and is a genomic DNA molecule (e.g., For example, cellular DNA, cell-free DNA (cfDNA), etc., typically contain intron sequences and Exon sequences (coding sequences) and non-coding regulatory sequences such as promoter and enhancer sequences In certain embodiments, the primary polynucleotide molecule comprises a human genomic DNA molecule. , for example, cfDNA molecules present in the peripheral blood of a pregnant subject.

[0218] Preparation of sequencing libraries for several NGS sequencing platforms This is facilitated by the use of polynucleotides that contain a specific range of fragment sizes. Preparation of such libraries typically involves the preparation of a desired size range to determine repeat expansion. To obtain a polynucleotide within a large polynucleotide (e.g., a cellular genomic DNA A) fragmentation.

[0219] The length of the fragment or insert is longer than the length of the read, typically the length of two reads. longer than the sum of the

[0220] In some exemplary embodiments, the sample nucleic acid(s) is obtained as genomic DNA. This may be about 100 or more, about 200 or more, about 300 or more, about 400 or more, or about 5 The DNA is fragmented into fragments of 1000 or more base pairs, making it amenable to NGS methods. In some embodiments, paired-end reads are generated from inserts of approximately 100-5000 bp. In some embodiments, the insert is about 100-1000 bp in length. These are usually performed as short insert paired end reads. In some embodiments, the insert is about 1000-5000 bp in length. These will be run as long-insert mate-pair reads as described above. There is a saying.

[0221] In some embodiments, the long insert allows for evaluation of very long, extended repeat sequences. In some embodiments, the ribosomes are designed to have multiple nucleotides spaced apart by several thousand base pairs. Mate-pair reads may be applied to obtain index data. The insert or fragment ranges from hundreds to thousands of base pairs and has two bispecific sequences on both ends of the insert. Then, the biotin-binding adapter binds the two ends of the insert. The fragments containing the biotin-binding adaptors are then fragmented. The two ends of the original insert were then inserted into a plug designed to sequence the shorter fragment. The resulting sequences are then selected for sequencing on the platform.

[0222] Fragmentation can be accomplished by any of a number of methods known to those of skill in the art. For example, fragmentation includes, but is not limited to, nebulization, sonication, and hydroshear. This can be accomplished by mechanical means. However, mechanical fragmentation is typically breaks the DNA backbone at CO, PO, and CC bonds, resulting in defective C Blunt and 3'-overhanging ends and 5'- Although this results in heterogeneous mixing with overhanging ends (e.g., Alnemri and Liwack, J Biol. Chem 265:17323-17333

[1990] , Richards and Boyer, J Mol Biol 11:327-24 0

[1965] ), because they are the primary enzymes in subsequent enzymatic reactions (e.g., Sequel et al. Ligation of sequencing adaptors required to prepare DNA for sequencing It is possible that the 5'-phosphate required for transcription is missing and therefore needs to be repaired. .

[0223] In contrast, cfDNA typically exists as fragments of less than about 300 base pairs, As a result, fragmentation is a critical step in generating sequencing libraries using cfDNA samples. It is typically not necessary to

[0224] Typically, the polynucleotide is forcibly fragmented (e.g., fragmented in vitro). Whether the 5'-phosphate and 3'-hydroxylase are present in the 5'- or 3'-hydroxylase fragments, respectively, The DNA is converted to blunt-ended DNA having xyl groups. Using the Illumina platform as described elsewhere in this document The sequencing protocol is as follows: -Prior to tailing, the end-repaired products were purified to allow for the adapter-labeling of the library preparation. Instruct the user to purify the dA-tailing product prior to the gating step .

[0225] Various embodiments of the methods for preparing sequence libraries described herein include methods for preparing sequences by NGS. To obtain modified DNA products that can be sequenced, the DNA is typically purified according to standard protocols. The method eliminates the need to perform one or more of the steps listed in the ABB The one-step method, the one-step method, and the two-step method are described in US Pat. No. 5,393,943, which are incorporated herein by reference in their entireties. See application Ser. No. 13 / 555,037 (filed July 20, 2012). 1 is an example of a method for preparing a sequencing library. Sequencing Methods

[0226] As described above, prepared samples (e.g., sequencing libraries) are stored in duplicate. Numerous sequencing techniques are used to identify genomic variations. You can use either one of them.

[0227] Several sequencing technologies are available from Affymetrix, as described below. Sequencing by Hybridization from Inc (Sunnyvale, CA) Sequencing-by-hybridization platform and 454 Life e Sciences (Bradford, CT), Illumina / Solexa ( San Diego, CA), and Helicos Biosciences (Cambodian, CA). Sequencing-by-synthesis platform (Seq. Ridge, MA) synthesis platforms from), and Applied Biosystems (Fost Sequencing platform by ligation from Eppendorf City, CA ( Sequencing-by-ligation platforms and other similar platforms are commercially available. This was carried out using sequencing-by-synthesis of In addition to the single molecule sequencing currently being performed, other single molecule sequencing techniques include is a member of Pacific Biosciences' SMRT™ technology, ION TOR RENTTM Technology 、 and, for example, Oxford Nanopore Tech These include, but are not limited to, nanopore sequencing developed by Nologies. Not determined.

[0228] Although automated Sanger sequencing is considered a "first generation" technology, Sanger sequencing, including sequencing by PCR, can also be employed in the methods described herein. Further suitable sequencing methods include nucleic acid imaging techniques, such as atomic force microscopy (AFM). Exemplary techniques include, but are not limited to, fluorescence microscopy (FM) or transmission electron microscopy (TEM). Such sequencing techniques are described in further detail below.

[0229] In some embodiments, the disclosed methods are implemented using Illumina's (e.g., Bent ley et al., Nature 6:53-59

[2009] ) Using sequencing chemistry based on nucleotide synthesis and reversible terminators, hundreds of Massively parallel sequencing of millions of DNA fragments provides a unique set of information about the nucleic acids in the test sample. The template DNA may be genomic DNA, e.g., cellular DNA. In some embodiments, the DNA from the isolated cells may be cellular DNA or cfDNA. It uses genomic DNA as a template and fragments it into pieces several hundred base pairs long. In the embodiment, cfDNA is used as a template, but the fragmentation is performed on the cfDNA It is not necessary for the DNA to be present as short fragments. For example, fetal cfDNA is It circulates in the bloodstream as a fragment of approximately 170 base pairs (bp) (Fan et al., 2003). lin Chem 56:1279-1286

[2010] ), DNA prior to sequencing Illumina sequencing technology does not require fragmentation of the GPCR. of genomic DNA to a flat, optically transparent surface to which oligonucleotide anchors are attached. It depends on the attachment of a 5' phosphorylated blank to the template DNA by end repair. The polymerase activity of the Klenow fragment is then used to insert a single A base into the blank. This addition increases the efficiency of ligation. To achieve this, oligonucleotides with a single T base overhang at their 3' ends were used. Prepare DNA fragments for ligation to adapter oligonucleotides. is complementary to the anchor oligo of the flow cell (anchor oligo in the repeat extension analysis) (Not to be confused with lead / anchored reads). Single-stranded template DNA is added to the flow cell and subjected to hybridization to amplify the DNA. The DNA fragment is then extended, and the bridge is amplified to produce hundreds of millions of DNA fragments. Fabricate ultra-high density sequencing flow cells with clusters, each containing the same template. In one embodiment, the randomly fragmented gate The genome DNA is amplified using PCR before undergoing cluster amplification. A wide genomic library preparation was used and randomly fragmented genomic DNA was isolated from the clusters. Enriched using amplification alone (Kozarewa et al., Nature Mechanisms thods 6:291-295

[2009] ). The template is a removable fluorescent dye. Robust four-color DNA sequencing by synthesis using reversible terminators with The sequence was determined using robust four-color DNA sequencing-by-synthesis technology. Highly sensitive fluorescence detection is achieved using laser excitation and total internal reflection optics. Short sequence reads of about tens to hundreds of base pairs are aligned to a reference genome. The unique mapping of short sequence reads to the genome is achieved using a specially developed data analysis pipeline. After the first read is completed, the template is It can be regenerated in situ to allow a second read from the opposite end of the fragment. This allows single-end or paired-end sequencing of DNA fragments. Either of the following can be used:

[0230] Various embodiments of the present disclosure provide sequencing by synthesis that enables paired-end sequencing. In some embodiments, sequencing by synthesis using Illumina Sequencing by the platform includes clustered fragments. In some embodiments, the method described herein is a process in which fragment molecules are isothermally amplified. As an example, a fragment may have two different adapters attached to the two ends of the fragment. The adapters allow the fragments to hybridize with two different oligos on the surface of the flow cell lanes. The fragment may further comprise or include two index sequences at the two ends of the fragment. This index sequence is connected to It provides a label to identify different samples. In this form, the fragment to be sequenced is also called the insert.

[0231] In some embodiments, for clustering within the Illumina platform, The flow cell for this purpose is a glass slide with lanes. Each lane contains two oligonucleotides. The hybridization is performed on a glass channel coated with a bacterial lawn of This is made possible by the first of two oligos, one of which is located at one end of the fragment. The polymerase generates a complementary strand of the hybrid fragment, which is complementary to the first adaptor. The double-stranded molecule is denatured and the original template strand is washed away. The remaining strand is made up of many other In parallel with the strand, the first strand is clonally amplified by bridge application.

[0232] In bridge amplification, a second adapter region on the second end of the strand is attached to a first adapter region on the flow cell surface. The polymerase hybridizes to two types of oligos, producing a complementary strand and forming a double-stranded bridge molecule. The double-stranded molecule is denatured and split into two fragments tethered to the flow cell via two different oligos. This process is then repeated across millions of clusters. , which occur simultaneously, resulting in clonal amplification of all fragments. After bridge amplification, the opposite strands The 3' end is cut and washed to leave only the forward strand. are blocked in order to

[0233] After clustering, sequencing is performed by extending a first sequencing primer to generate a first It starts by generating reads. In each cycle, a fluorescently labeled nucleotide compete to add to the growing chain. Only one will be selected based on the sequence of the template. After each nucleotide is added, the cluster is excited by a light source and a characteristic A fluorescent signal is emitted. The number of cycles determines the length of the read. Emission wavelength and signal intensity determines the base call. For a given cluster, all identical strands are read simultaneously. Hundreds of millions of clusters are sequenced in a massively parallel fashion. Upon completion of the first read, The read product is washed away.

[0234] In the next step of the protocol that includes two index primers, index 1 A primer is introduced and hybridizes to the index 1 region on the template. The region is used to demultiplex samples during the multiplex sequencing process. The index 1 read is the first read and provides the identification of a fragment that is useful for testing. After the index 1 read is complete, the read products are flushed out. The template strand is then coupled to the second oligo on the flow cell. The sequence of index 2 is the same as that of index 1. The same method is used to read the lead product. Then, upon completion of the process, the lead product at index 2 is washed out. .

[0235] After two index reads, polymerase is used to initiate read 2, and a second flow The cell oligo is extended to form a double-stranded bridge. This double-stranded DNA is denatured and 3' The end is blocked. The original forward strand is cut and washed away, leaving the reverse strand. Read 2 is Start with the introduction of a sequencing primer for Read 2. As with Read 1, the desired length is The sequencing process is repeated until the read 2 product is achieved. The entire process generates millions of reads, representing all fragments. Pool Sample Live Sequences from each library are separated based on a unique index introduced during sample preparation. For a sample, reads with similar stretches of base calls are locally clustered. The reads in the opposite direction are paired to generate contiguous sequences. These contiguous sequences are The sequences are aligned to a reference genome for identification.

[0236] The above synthetic sequencing examples are used in many embodiments of the disclosed methods. , including paired-end reads. Paired end sequences are sequences of two sequences from the two ends of a fragment. Paired-end reads are used to resolve ambiguous alignments. End sequencing allows the user to determine the length of the insert (or the fragment to be sequenced). Select and sequence either end of the insert to generate high-quality, alignable sequence data. Since the distance between each pair of reads is known, the alignment algorithm This information can be used to more precisely position reads on repetitive regions. This allows for better alignment of reads, especially across difficult-to-sequence repetitive regions of the genome. Paired-end sequencing identifies insertions and deletions (indels) and inversions. It is possible to detect realignments including

[0237] Paired-end reads are generated for inserts of different lengths (i.e., different The default meaning in this disclosure is paired-end Reads are used to refer to the reads obtained from various insert lengths. In some cases, paired-end reads with short inserts may be combined with paired-end reads with long inserts. To distinguish them from mate-pair reads, the latter are specifically called mate-pair reads. In some embodiments involving mate-pair reads, two biotin-conjugated adaptors are first The nucleotide sequence is attached to the two ends of a relatively long insert (e.g., several kb). A biotin-binding adaptor then links the two ends of the insert to form a circular molecule. Subfragments containing biotin-binding adaptors are then used to further fragment the circulating molecules. Then, a subfragment containing the two ends of the original fragment in the reverse order can be obtained by: Sequence the short inserts using the same procedure as described above for paired-end sequencing. Mate-pair sequencing using the Illumina platform Further details of the study are provided in an online publication at the following address, which can be read in its entirety: The following link is incorporated by reference: res.illumina.com / document ts / products / technotes / technote_nextera_m atepair_data_processing.pdf

[0238] After sequencing the DNA fragments, sequence reads of a given length (e.g., 100 bp) are Mapped or aligned reads and references to a known reference genome. Their corresponding positions on the reference sequence are also called tags. The analysis of many embodiments disclosed herein may involve the analysis of poorly aligned or unaligned reads. In one embodiment, the method uses reads that cannot be identified, as well as aligned reads (tags). The reference genome sequence is the NCBI36 / hg18 sequence, and genome.ucsc.e du / cgi-bin / hgGateway?org=Human&db=hg18&h Available on the World Wide Web (www. Alternatively, the reference genome sequence is GRCh37 / hg19, available at genome.uc At sc.edu / cgi-bin / hgGateway, the World Wide Web ( Other sources of public sequence information include GenBank, dbEST,dbSTS,EMBL(the European Molecular Biology Laboratory, and DDBJ (DNA Database of Japan) Many computer algorithms are available for aligning sequences. These include BLAST (Altschul et al., 1990), BLITZ (MPsrch) (Sturrock & Collins, 1993), FASTA (Pe rson & Lipman, 1988), BOWTIE (Langmead et al. , Genome Biology 10:R25.1-R25.10

[2009] ), and The company was led by ELAND (Illumina, Inc., San Diego, CA, USA). In one embodiment, the present invention includes, but is not limited to, clonal expansion copies of plasma cfDNA molecules. One aspect of this is Efficient Large-Scale Alignment of Using the Nucleotide Databases (ELAND) software, Genetic alignment analysis using the Illumina Genome Analyzer The data are then arranged and processed.

[0239] In one exemplary, but non-limiting embodiment, the methods described herein include For example, see Harris TD et al., Science 320:106-109

[2008] ) Helicos True Single Molecule Se Using single molecule sequencing (tSMS) technology, The tSMS technique involves obtaining sequence information about the nucleic acids in a DNA sample. The sample is cut into strands of approximately 100-200 nucleotides, and the 3' end of each DNA strand is Add a polyA sequence. Each strand is tagged by the addition of fluorescently labeled adenosine nucleotides. Next, the DNA strand is hybridized to the flow cell, but the DNA strand is immobilized on the surface of the flow cell. In certain embodiments, the template contains approximately 100 million oligo T capture sites. Plates / cm 2 The flow cell can then be inserted into an instrument, e.g., a HeliSc The OPE™ sequencer detects the surface of the flow cell with a laser and measures each template. The CCD camera detects the position of the template on the surface of the flow cell. The template fluorescent label is then cleaved and washed away. The sequencing reaction is carried out by introducing DNA polymerase and fluorescently labeled nucleotides. The oligo-T nucleic acid acts as a primer. The polymerase reacts with the template. The polymerase and the non-incorporating nucleotides are incorporated into the primer in a nucleotide-inducing manner. Remove only the nucleotides. Template with induced incorporation of fluorescently labeled nucleotides. The rate is determined by imaging the surface of the flow cell. After imaging, the cleavage process is The photolabel was removed. This process was repeated for other fluorescent labels until the desired read length was achieved. Sequence information is gathered with each nucleotide addition step. Whole genome sequencing using single molecule sequencing technology is a The present method precludes or typically precludes PCR-based amplification in the preparation of This allows for direct measurement of the sample rather than measuring a copy of the sample.

[0240] In another exemplary but non-limiting embodiment, the methods described herein include, for example, (Margulies, M. et al. Nature 437:376-380

[2005] ) 454 sequencing (Roche) was used to sequence the nuclei in the test samples. The process involves obtaining sequence information about the nucleic acid. 454 sequencing typically involves two steps: In the first step, DNA is sheared into fragments of about 300-800 base pairs. The fragments are then ligated to the ends of the fragments using oligonucleotide adapters. The adapters act as primers for fragment amplification and sequencing. The fragments can be ligated to DNA capture nucleotides using, for example, adapter B, which contains a 5' biotin tag. The capture beads can be attached to beads, e.g., streptavidin-coated beads. The bead-attached fragments are amplified by PCR within droplets of an oil-in-water emulsion. The result is multiple copies of a clonally amplified DNA fragment on each bead. In a second step, the beads are captured in wells (e.g., picoliter-sized wells). Pyrosequencing is performed in parallel on each DNA fragment. The addition of one or more nucleotides is recorded by a CCD camera in the sequencing instrument. The intensity of the signal is proportional to the number of nucleotides incorporated. Sequencing uses pyrophosphate (PPi), which is released upon addition of a nucleotide. PPi is converted to ATP by ATP sulfurylase in the presence of adenosine 5' phosphosulfate. Luciferase converts luciferin to oxyluciferin. The reaction uses ATP to produce light, which is measured and analyzed.

[0241] In another exemplary but non-limiting embodiment, the methods described herein include SOLi Test samples were analyzed using Applied Biosystems' D™ technology. The method includes obtaining sequence information about the nucleic acid in the SOLiD™ ligation. Sequencing by ELISA involves shearing genomic DNA into fragments and isolating the 5' and 3' ends of the fragments. Attach an adapter to the end of the library to generate a fragment library. Alternatively, an internal adapter can be added to the The antibody is ligated to the 5' and 3' ends of the fragment, circularizing the fragment. The resulting fragment was digested to generate internal adapters, which were then attached to the 5' and 3' ends of the resulting fragment. Next, the mate-pair library can be generated by attaching the In a microreactor containing beads, primers, template, and PCR components, Prepare a clonal bead population. After PCR, denature the template and enrich the beads. The beads are separated from the extended templates by the addition of a fluorescein. The templates on the selected beads are separated from the extended templates by the addition of a fluorescein. The sequence is modified at the 3' end to allow binding to a glass slide. Partially random oligonucleotides with a specified central determinant (or base pair) The color can be determined by sequential hybridization and ligation of the After the sequence is recorded, the ligated oligonucleotides are cleaved and removed, and then the Repeat the process.

[0242] In another exemplary but non-limiting embodiment, the methods described herein include fic Biosciences' Single Molecule, Real-Time (SMRT™) Sequencing The method includes obtaining sequence information about the nucleic acids in a test sample using sequencing techniques. In MRT sequencing, sequential incorporation of dye-labeled nucleotides occurs during DNA synthesis. Single DNA polymerase molecules are imaged as individual zero-mode molecules that capture sequence information. The bottom of the zero-mode wavelength detectors (ZMW detectors) while the phospho-linked nucleotide is incorporated into the growing primer strand. The detector detects the flux of fluorescent nucleotides that rapidly diffuse (e.g., in microseconds) out of the ZMW. This allows the observation of the incorporation of a single base by DNA polymerase against a background It contains a constraining structure that typically requires several millimeters to incorporate a nucleotide into the growing chain. During this time, the fluorescent label is excited, producing a fluorescent signal, and the fluorescent label is cleaved. Measurement of the corresponding fluorescence of the dye indicates which base has been incorporated. This process is then repeated. This provides the array.

[0243] In another exemplary but non-limiting embodiment, the methods described herein include, for example, , Soni GV and Meller A.Clin Chem 53:1996- 2001

[2007] using a nanopore sequencing method to identify The method includes obtaining sequence information about the nucleic acid of the nucleic acid. For example, Oxford Nanopore Technologies (Oxford d, United Kingdom), Sequenom, NABsys, and many others. Nanopore sequencing is being developed by companies that specialize in DNA sequencing, where a single molecule of DNA passes through a nanopore. Nanopores are a typical single molecule sequencing technology that allows molecules to be sequenced directly as they pass through. The nanopores are typically small, with diameters on the order of one nanometer. The nanopores are immersed in a conductive fluid, When a potential (voltage) is applied, a small current flows due to the conduction of ions through the nanopore. The amount of current that flows is sensitive to the size and shape of the nanopore. As it passes through the pore, each nucleotide on the DNA molecule blocks the nanopore to a different extent, This changes the magnitude of the current passing through the nanopore to different degrees. This change in current as it passes through the pore provides a DNA sequence read.

[0244] In another exemplary but non-limiting embodiment, the methods described herein are Chemically sensitive field effect transistors (described in Patent Publication No. 2009 / 0026082) A chemFET (chem-sensitive field effect transistor) array was used for testing. This involves obtaining sequence information about the nucleic acids in a sample. The molecules can be placed in a reaction chamber, and the template molecules are attached to a primer pair bound to a polymerase. The 3' end of the sequencing primer can hybridize to the The incorporation of one or more triphosphates into the new nucleic acid strand at the end of the nucleic acid is then induced by electrochemical chemFET. The array can be identified as a change in flow. In another embodiment, a single nucleic acid can be attached to a bead and the nucleic acid can be attached to the bead. Amplification can be performed on individual beads by connecting individual reaction channels on the chemFET array. The cells were then transferred to a chamber, each of which contained a chemFET sensor capable of sequencing nucleic acids. Cut.

[0245] In another embodiment, the DNA sequencing technology is a single sequencing technology using semiconductor technology. Paired with chemistry, chemically encoded information (A, C, G, T) is stored on a semiconductor chip. Ion Torrent single molecule sequencing for direct translation into digital information (0, 1) Essentially, when a nucleotide is incorporated into a strand of DNA by a polymerase, When this happens, hydrogen ions are released as a by-product. Ion Torrent is a micromechanical Using high-density arrays of engineered wells, this biochemical process can be carried out in a massively parallel fashion. Each well holds a different DNA molecule. Below the well is an ion-sensitive layer. When a nucleotide, e.g., C, is added to the DNA template, When it is then incorporated into a strand of DNA, it releases a hydrogen ion. The pH of a solution can be detected by an Ion Torrent ion sensor. The sequencer (essentially the world's smallest solid-state pH meter) can change the base Call Ion personal to go directly from chemical information to digital information. The PGM™ Genome Machine sequencer sequentially reads nucleotides If the next nucleotide to be loaded onto the chip does not match, No voltage change is recorded and no bases are called. The presence of two identical bases on a DNA strand If so, the voltage can be doubled and the chip will record two identical bases being called. Contact detection allows recording of nucleotide incorporation on a second-by-second basis.

[0246] In another embodiment, the method uses sequencing by hybridization. Hybridization involves obtaining sequence information for the nucleic acids in a test sample. Sequencing by ligation involves ligating multiple polynucleotide sequences with multiple polynucleotide probes. wherein each of the plurality of polynucleotide probes is optionally contacted with a substrate. The substrate can be a flat surface that contains an array of known nucleotide sequences. The pattern of hybridization to the array can be used to identify the nucleotides present in the sample. In another embodiment, the polynucleotide sequence associated with each probe can be determined. The hybridization to the beads is carried out by hybridization to the beads. The sequences are determined and used to identify multiple polynucleotide sequences within a sample. can be done.

[0247] In some embodiments of the methods described herein, the sequence reads are about 20 bp, about 25 bp, about 30bp, about 35bp, about 40bp, about 45bp, about 50bp, about 55bp, about 60bp, about 65bp, about 70bp, about 75bp, about 80bp, about 85bp, about abou t90bp, about 95bp, about 100bp, about 110bp, about 120bp, about 130, about 1 40bp, about 150bp, about 200bp, about 250bp, about 300bp, about 350bp, About 400 bp, about 450 bp, or about 500 bp. A technical advance is greater than 500 bp. When paired-end reads are generated, It is expected that the reads will be greater than about 1000 bp. , paired-end reads are about 20bp to 1000bp, about 50bp to 500bp, or Used to determine repeat extensions containing sequence reads that are between 80bp and 150bp In various embodiments, paired-end reads evaluate sequences with repeat expansions. The sequence having the repeat expansion is longer than the read. In some embodiments, the sequence having a repeat expansion is about 100 bp, 500 bp, 1000 bp, or Mapping of sequence reads is done by comparing the sequence of the reads to a reference sequence. This is accomplished by determining the chromosomal origin of the sequenced nucleic acid molecule, No sequence information is required. Small mismatches (0-2 mismatches per read) are acceptable for mixed samples. It is possible to take into account minor polymorphisms that may exist between the reference genome and the genome in the In some embodiments, the reads aligned to the reference sequence are used as anchor reads, The reads are paired with anchor reads, but cannot be aligned to the reference sequence or are poorly aligned to the reference sequence. In some embodiments, the poorly aligned leads are used as anchored leads. Poorly aligned reads may have a relatively high rate of mismatches per read, e.g. or at least about 5%, at least about 10%, at least about 15%, or at least about 2 It can have 0% mismatch.

[0248] Multiple sequence tags (i.e., reads aligned to a reference sequence) are typically generated per sample. In some embodiments, at least about 3×10 6 sequence tags, at least about 5 × 10 6 sequence tags, at least about 8 × 10 6 Array tag , at least about 10×10 6 sequence tags, at least about 15 × 10 6 Sequence tags, at least Both are about 20 x 10 6 sequence tags, at least about 30 × 10 6 sequence tags, at least about 4 0×10 6 or at least about 50×10 6 sequence tags per sample It is obtained from mapping of reads to a reference genome. In some embodiments, all sequences The reads are mapped to all regions of the reference genome to provide genome-wide reads. In this embodiment, the sequence of interest, e.g., a chromosome, a segment of a chromosome, or a region of interest, It is located in a repeat sequence. Apparatus and system for determining repeat expansions

[0249] Analysis of sequencing data and the diagnostics derived therefrom are typically performed using a variety of computer The implementation is therefore The form may be stored or processed in one or more computer systems or other processing systems. The present invention employs a process for transmitting data through the The embodiments also relate to an apparatus for performing these operations. may be specially constructed for this purpose, or may be computer programs stored in a computer A general-purpose computer (or In some embodiments, a group of processors The systems may perform some or all of the listed analytical operations collaboratively (e.g., across a network or a cluster). via computer-aided computation), and / or in parallel. The processor or group of processors for the Microcontrollers and microprocessors such as PLDs and FPGAs, and games This includes non-programmable devices such as array ASICs or general purpose microprocessors. They may be of various kinds.

[0250] One embodiment provides a method for genotyping variants at genomic loci that contain repeat sequences. The present invention provides a system for use in detecting a nucleic acid sample, the system comprising: a sequencer for providing nucleic acid sequence information from the nucleic acid sequence; A machine-readable storage medium having instructions stored thereon for executing genotyping of variants. The variants are identified by: (a) identifying nucleic acid sequence reads for a test sample from a database; (b) arranging the one or more repeat sequences, each of which is represented by a sequence graph. Aligning the reads, wherein a sequence graph is formed of vertices representing nucleic acid sequences and connecting the vertices. The data structure of the sequence graph has one or more self-loops. each self-loop represents a repeat subsequence, each repeat subsequence comprising one or more nucleotides and (c) one or more genetic elements related to one or more repeat sequences. determining a subtype using sequence reads aligned to one or more repeat sequences; and a machine-readable storage medium in which the gene is determined.

[0251] In some embodiments of any of the systems provided herein, the sequencer , configured to perform next generation sequencing (NGS). In this embodiment, the sequencer uses sequence-by-synthesis with reversible dye terminators to generate large-scale In other embodiments, the sequence is configured to perform parallel sequencing. The sequencer is configured to perform sequencing by ligation. In other embodiments, the sequencer is configured to perform single molecule sequencing. It is being done.

[0252] Additionally, certain embodiments may include programs for performing various computer-implemented operations. Tangible and / or non-transitory content, including instructions and / or data (including data structures) Examples of computer readable media include computer program products. Examples include semiconductor memory devices, magnetic media such as disk drives, magnetic tape, and optical Media (CDs, magneto-optical media, etc.), as well as read-only memory devices (ROMs) and A memory specially designed to store and execute program instructions, such as random access memory (RAM). Examples of hardware devices include, but are not limited to, a computer. The readable medium may be directly controlled by the end user, or the medium may be Examples of directly controlled media include user premises and Indirectly, the media may be located in a medium that is not shared with other components. Examples of controlled media include over an external network and / or via the "cloud" Which media is indirectly accessible to users through a service that provides shared resources? Examples of program instructions include function instructions, such as those generated by a compiler. Machine code and higher than can be executed by a computer using an interpreter Both files contain the code for the levels.

[0253] In various embodiments, the data or information used in the disclosed methods and apparatus may be electronic. Such data or information may include, but is not limited to, data derived from a nucleic acid sample. The reads and tags to be analyzed, the reference sequences (including reference sequences that provide the sole or primary polymorphisms), Examples of such calls include call extension calls, counseling recommendations, diagnostic calls, etc. Where data or other information is provided in electronic form, it may be stored on a machine and transferred between machines. Traditionally, data in electronic form is provided digitally and is available for transmission in various formats. It may be stored as bits and / or bytes in a data structure, list, database, etc. The data may be embodied electronically, optically, etc.

[0254] One embodiment provides a method for generating an output indicative of the presence or absence of a repeat expansion in a test sample, comprising: A computer program product is provided, the computer program product determining repeat expansions. The method may include instructions for performing any one or more of the above methods for As used herein, a computer product is a computer executable or A non-transitory and / or tangible computer readable medium having executable logic (e.g., instructions) The anchor lead may include a body, whereby the processor may and repeats, as well as whether a repeat expansion is present or absent. In one embodiment, the computer product includes a processor for diagnosing a repeat expansion. A computer executable or compilable program having recorded thereon for enabling The present invention also includes a computer readable medium having instructions (e.g., instructions) for encoding a repeat sequence. a receiver for receiving sequencing data from at least a portion of the nucleic acid molecules from the array; and computer-aided logic for analyzing the received data for repeat extensions. and an output procedure for generating an output indicative of the presence or absence or type of the repeat expansion.

[0255] The sequence information from the sample under consideration is mapped to chromosomal repeat sequences and is Identify paired-end reads that are aligned or anchored to repeat sequences that match the repeat sequences. In various embodiments, the reference sequence can be a relational data set. The information is stored in a database such as a database or an object database.

[0256] It is possible to perform the computational operations of the methods disclosed herein without human assistance. It should be understood that this is not practical, or even possible in most cases. For example, a single 30bp read from a sample can be matched to any one of the human chromosomes. Mapping can be a significant effort without the aid of a computing device. However, reliable repeat expansion calls generally require the identification of several thousand repeats (e.g., For example, at least about 10,000 reads) or millions of reads need to be mapped. Therefore, the issue is complex.

[0257] In various embodiments, the raw sequence reads comprise one or more sequences that represent one or more sequences of interest. In various embodiments, at least 10,000, 100 ,000 pieces, 500,000 pieces, 1,000,000 pieces, 5,000,000 pieces, or 1 0,000,000 reads are aligned to one or more sequence graphs. So, one or more sequence graphs are at least 1, 2, 5, 10, 50, 100 , 500, 1000, 5,000, 10,000, or 50,000 sequences Includes graphs.

[0258] In some embodiments, the raw sequence reads are first aligned to a reference genome to initially One or more sequence graphs in which a subset of the aligned reads represents one or more sequences of interest In various embodiments, the genomic coordinates of the reads are determined before the reads are aligned to the target sequence. 0,000 pieces, 100,000 pieces, 500,000 pieces, 1,000,000 pieces, 5,00 0,000, 10,000,000, or 100,000,000 leads are the best In some embodiments, the initially aligned reads are aligned to a reference genome. Reordered into a column graph, repeats in multiple regions (each region corresponds to an array graph) The total number of reads realigned to the sequence graph during each implementation of the embodiment is determined to be several thousand. In various embodiments, the number of reads may range from 10,000,000 to several million. Therefore, the reads are realigned to each sequence graph. In various embodiments, one or more sequence graphs are Ruff is at least 1, 2, 5, 10, 50, 100, 500, 1000 The graphs may include 5,000, 10,000, or 50,000 sequence graphs.

[0259] 5 The methods disclosed herein include the detection of variants in genomic loci that contain repetitive sequences. The method can be carried out using a system for determining a genotype, the system comprising: (a) a subunit; a sequencer for receiving nucleic acids from a test sample and providing nucleic acid sequence information from the sample; (b) a processor; and (c) on the processor, a genomic locus that includes a repeat sequence. having instructions stored thereon for performing genotyping of variants in and a computer-readable storage medium. The method for identifying any repeat expansions can be carried out by using the stored computer. The method is directed to a computer readable medium having computer readable instructions. One embodiment, when executed by one or more processors of a computer system, A computer program product including a non-transitory machine-readable medium storing program code. and a computer system for detecting repeats of a repetitive sequence in a test sample containing nucleic acid. and performing a method for identifying repeat extensions, the repeat sequence comprising repeats of nucleotide repeat units. The program code includes: (a) collecting sequence reads for a test sample from a database; and (b) a code for arranging one or more repeat sequences, each represented by a sequence graph. Code for aligning sequence reads, the sequence graph comprising vertices and vertices representing nucleic acid sequences. A data structure of a directed graph with directed edges connecting the points, and a sequence graph is one or more Each self-loop represents a repeating subsequence, and each repeating subsequence comprises one or more nucleases. (c) a code comprising a repeat of a repeating nucleotide unit; and One or more genotypes are determined using sequence reads that align to one or more repeat sequences. and code for:

[0260] In some embodiments, the instructions relate to methods such as iterative reading and anchored reading. and repeat information in the patient medical records of the human subjects providing the test samples. The method may further include automatically recording the presence or absence of elongation. may be held by a laboratory, a doctor's office, a hospital, a health maintenance organization, an insurance company, or The personal medical record method prescribes, initiates, and administers treatment to the human subject from whom the test sample was taken. This may further include modifying the identity of the subject by determining whether the subject has a known identity, and / or whether the subject has a known identity, for additional samples taken from the subject. This may include performing one or more additional tests or analyses.

[0261] The disclosed methods are also adapted to carry out methods for identifying any repeat expansion. The present invention may also be implemented using a computer processing system having or configured. The embodiment may include a computer process adapted or configured to perform the methods described herein. In one embodiment, the apparatus comprises a processing system as described elsewhere herein. At least some of the nucleic acid molecules in the sample are sequenced to obtain a variety of sequence information. The apparatus also includes a sequencing device adapted or configured to sequence the sample. Such components may include components for processing the It is stated in the place.

[0262] The sequence or other data can be input into a computer or directly or may be stored on the computer readable medium, either directly or indirectly. The computer system performs a sequence analysis to read and / or analyze nucleic acid sequences from the sample. The sequence or other information from such tools can be directly linked to a sensing device. Provided through an interface in a computer system or provided to the system The sequences processed thereby are extracted from a sequence storage source, such as a database or other repository. Once the processing unit is available, the memory device or mass storage device In addition, the memory device may be used to at least temporarily buffer or store sequences of nucleic acids. The memory may also store a number of tags, such as a number of chromosomes or genomes. Various routines and / or programs for analyzing the presentation of data may be stored. Such programs / routines may include programs for performing statistical analysis, etc. good.

[0263] In one embodiment, a user provides a sample to a sequencing device. The DNA is collected and / or analyzed by a sequencing device connected to a computer. The software on the computer allows for data collection and / or analysis. The data is stored and , displayed (via a monitor or other similar device) and / or transmitted to another location. The computer may be operated by a remote user (e.g., a physician, scientist, or analyst). The internet is used to transmit data to handheld devices that are used It is understood that the data may be stored and / or analyzed prior to transmission. In some embodiments, the raw data is collected and a remote system is used to analyze and / or store the data. The transmission process may be carried out by storing the information on a computer-readable medium. The media may be delivered (e.g., via email) to the end user. A remote user may be a user of a building, city, state, country, or continent, including, but not limited to, They may be in the same or different geographic locations.

[0264] In some embodiments, the method also comprises the steps of: chromosome sequences (e.g., tags, and / or reference chromosome sequences) and and transmitting the information to a computer or other computing system. For example, the computer may: Laboratory equipment, e.g., sample collection devices, nucleotide amplification devices, nucleotide sequencers The device can then be connected to a computer, a scanning device, or a hybridization device. The data processor may collect applicable data gathered by the test laboratory devices. Data may be collected at any stage, e.g., during collection in real time, before transmission, during transmission, or in connection with transmission. The data may be stored on the computer after transmission or after the data is extracted from the computer. The collected or stored data may be stored on a computer readable medium. The data may be stored in a location remote from the computer, for example, on a local network or the Internet. The remote location may transmit the information over a wide area network, such as a As described above, various operations can be performed on the transmitted data.

[0265] Storage, transmission, analysis, and / or manipulation by the systems, devices, and methods disclosed herein The types of electronically formatted data that can be obtained include, among others: Reads obtained by sequencing the nucleic acid in a test sample The reads are obtained by aligning them to a reference genome or other reference sequence or sequences. Tags that can be used Reference genome or sequence Locus specification indicating locus identity, location, and structural read coverage Variant Genotype Sequence Graph Graph Pathway Graph alignment information Actual calls of repeat expansions Diagnosis (clinical condition related to the call) Recommendations for further testing derived from the call and / or diagnosis Treatment and / or monitoring plans derived from the call and / or diagnosis

[0266] These various types of data may be captured and stored in one or more locations using separate devices. , transmitted, analyzed, and / or manipulated. Processing options span a wide spectrum At one end of the spectrum, all or much of this information is processed by the test sample. Stored and used in locations where the information is used, such as a physician's office or other clinical setting. In the extreme case, samples may be obtained at one location, processed at a different location, and optionally sequenced. A decision is made, leads are lined up, calls are made at one or more different locations, and then a second location ( A diagnosis, recommendation, and / or plan is prepared at the location (which may be the location where the sample was obtained).

[0267] In various embodiments, the reads are generated by a sequencing device and then subjected to repeat extension coding. The remote location may then transmit the signal to a remote site where it is processed to generate a rule. The reads are aligned to a reference sequence to generate anchored reads and anchored reads. Processing operations that may be employed at separate locations are, inter alia: Sample collection Sample processing preliminary to sequencing Analyze sequence data and derive repeat extension calls diagnosis Report the diagnosis and / or call to the patient or healthcare provider. Develop plans for testing and / or monitoring counseling

[0268] Any one or more of these operations may be performed as described elsewhere herein. Typically, the sequencing and analysis of sequence data and repeat The derivation of the decompression call may be performed computationally. Other operations may be performed manually or automatically. This may be done.

[0269] FIG. 6 illustrates one implementation of a distributed system for generating a call or diagnosis from a test sample. Sample collection site 01 is used to collect a test sample from a patient. The sample can then be processed and sequenced for testing as described above. The samples are then provided to processing and sequencing position 03, which can then be used to process the samples. This specification includes an apparatus for sequencing the processed samples. The results of sequencing, as described elsewhere in this document, will typically be provided in electronic form. 05 in FIG. 6. A lead is a collection of leads provided to a customer.

[0270] The sequence data is provided to a remote location 07 where analysis and call generation is performed. may include one or more powerful computing devices, such as a computer or processor. The computational resources at location 07 complete their analysis and call the received sequence information. After generating the , the call is relayed back to the network 05. In some embodiments, Not only is the call generated in position 07, but the associated diagnosis is also generated. And / or diagnostics may be transmitted across the network and sampled, as shown in FIG. Return to position 01. As will be explained, this is related to making a call or diagnosis. Many variations in how the various operations can be divided among the various positions. One common variant is a single location, which is sampled and processed Another variation includes providing analysis and call generation and This includes providing co-location of processing and sequencing. experiment EXAMPLES

[0271] The present inventors have demonstrated that the HTT locus contains a wide range of CAG and CCG repeat sizes. The program was applied to the simulated data set. ntingtin is a genetic signaling protein associated with Huntington's disease (HD). This is a neurodegenerative disorder characterized by loss of striatal neurons. Caused by an expanded unstable trinucleotide repeat in the huntingtin gene It is believed that this is translated as polyglutamine repeats in the protein product. A fairly wide range of trinucleotide repeats (9-35) was identified in normal controls. Repeat numbers greater than 40 have been described as abnormal.

[0272] As expected, the accuracy obtained using the methods according to some embodiments is high for both Compared to when the repeats were analyzed independently, the sequence graph aligned to contain both repeats was Similar improvements were observed compared with other STR genotypes. (Figure 7).

[0273] To demonstrate that embodiments can genotype degenerate DNA repeats, We analyzed the PHOX2B gene and known pathogenic expansions in 150 healthy controls. In one of the samples we retained, we analyzed the polyalanine repeats. PHOX2B is It causes congenital central hypoventilation syndrome. It contains a polyalanine repeat of 20 codons that can be extended to Consistent with known (Amiel et al. 2003), all but a few pairs The control was genotyped as 20 / 20. An embodiment is a control with an elongation as 20 / 27. The accuracy of this genotype is measured using the Sanger sequence. The embodiment is also confirmed by SeraCare Life Science ces (see Supplementary Materials) Adenosine homopolymers in the MSH2 gene were identified in three WGS replicates of the sample. The pathogenic SNVs adjacent to the .

[0274] In summary, the inventors have addressed the need for more accurate genotyping of complex loci. We have developed a novel method to genotype polyalanine repeats and identify small variances. It can solve difficult domains that involve iterations in close proximity to ants and other iterations. The inventors believe that the flexibility of the currently implemented sequence graph framework will allow for a variety of novel It is hoped that this may enable variant calling applications. Analysis of CAG and CCG STRs in the HTT locus

[0275] Using wgsim(Li,nd), each combination of CAG and CCG repeat genotypes was We simulated short-read samples for the combination of read lengths. 150, the distance between mate ends is 350, and the standard deviation of the distance between mate ends is 50 The mutation rate and base error rate were set to 0.0010, and the fraction of indels was set to 0. The number was set to obtain a 40x probability of locus. Reads were generated using BWA-MEM 0.7.1 Alignment was performed to the GRCh37 reference using 7-r1194-dirty (LL2013).

[0276] These data were analyzed in two ways in some embodiments. First, we is expressed (CAG) * CAACAG (CCG) * Identifying the structure of the HTT locus using This ensures that the reads are aligned to a sequence graph that includes both repeats. Each repeat is analyzed independently using the embodiment of The graphs were aligned to represent the TRs and, separately, to represent the CCG STRs. We use GangSTR, which aligns reads to repeat regions without using a sequence graph. Both reads were analyzed independently using the latest version of TredParse ( Figure 7).

[0277] FIG. 7 illustrates the steps of genotyping CAG and CCG STRs at the HTT locus. (a) Implementation when reads are aligned to a sequence graph that includes both repeats. (b) the performance of the embodiment when the replicates are analyzed independently; (c) the performance of the embodiment when the replicates are analyzed independently; (d) Performance of R. (e) Performance of TredParse. For each simulated sample. , measured the maximum percentage deviation of predicted STR length from expected STR length. Blue dotted line corresponds to the genotype in the reference genome, and the solid red line represents the threshold for pathogenic expansion. The mode is that the appropriate genotype is found for all samples when both replicates are genotyped together. Co-genotyping accurately predicts the type of repeats that are significantly longer than the other repeats. The relative error rates for both reads using any of the three tools were particularly high when It offers significant advantages over separate genotyping. Dataset

[0278] For 150 unrelated controls used in the analysis of PHOX2B polyalanine repeats PCR-free WGS sequencing data from the Polaris Diversity cohort (Polaris Diversity Cohort). This is an International Geno me Sample Resource(1000 Genomes Project Consortium et al.2015)(www|.|internation The WGS data consist of samples selected from the following sources: European Genome-phenome Archive(EGA;www| .|ebi|.|ac|.|uk / ega / home;PRJEB20654), and N CBI Sequence Read Archive(SRA;www|.|ncbi |.|nlm|.|nih|.|gov / sra;bioproject:387148 ) can be obtained from the sample description (github||com / Illumi na / Polaris / wiki / HiSeqX Diversity-Cohort) .

[0279] Samples with the 20 / 27 expansion in PHOX2B were purchased from the Genetics Lab oratories Molecular Genetics,Addenbrooke 's Treatment Centre,and Cambridge University Obtained from sity.

[0280] Seraseq I, a sample from SeraCare Life Sciences nherited Cancer DNA Mix v1 for pathogenicity and calling Contains variants known to be both hard and soft. All variants are 50% The well-characterized cell line GM24385 has an expected variant frequency of One of these engineered mutations is located immediately adjacent to a long homopolymeric A tract. It corresponds to an SNV in the adjacent MSH2 gene.

[0281] SeraCare's TruSeq PCR-free kit from Illumina Three replicates of samples were prepared. The replicates were run on NovaS using the XP workflow. Sequences were run on a single lane of the eq6000 with a read length of 2 × 151. ntieon DNASeq FASTQ to VCF' and 'Whole Geno me Requencing v8.0.0'Basespace apps(http Replicates were analyzed using the Illumina ELISA Kit (http: / / basespace.illumina.com). Sentieon is a registered trademark of Broad's GATK software as Sentieon. It can be seen as a proxy for the variant calling performance of the software solution. None of the Fast RT-PCR analyses were able to accurately identify the MSH2 SNVs. The q files and analysis results are available on Basespace: https: / / basespace Available via .illumina.com / s / HAQNxJyEtJLP.

[0282] The present disclosure may be embodied in other specific forms without departing from its spirit or essential characteristics. The described embodiments are considered in all respects only as illustrative and not restrictive. Accordingly, the scope of the present disclosure should not be construed as being limited to the foregoing description. The scope of the appended claims is intended to cover all aspects of the present invention, including, but not limited to, the scope of the present invention. All such modifications are intended to be encompassed within their scope.

Claims

1. To genotype one or more repeat sequences, each of which contains one or more repeat subsequences. The method is implemented using a computer having one or more processors and a system memory. The method comprises: (a) using the one or more processors to compile sequence reads for test samples into a database; and (b) by the one or more processors, the aligning the sequence reads to one or more repeat sequences, The data structure of the directed graph has vertices representing sequences of amino acids and directed edges connecting the vertices. wherein the sequence graph includes one or more self-loops, each self-loop representing a repeated subsequence. Each repeat subsequence comprises a repeat of one or more nucleotide repeat units. To align and (c) detecting the sequence of the sequence aligned to the one or more repeat sequences by the one or more processors. The sequence reads are used to determine one or more genotypes for the one or more repeat sequences. A method comprising:

2. The repeat sequence of the one or more repeat sequences is selected from the group consisting of at least one incompletely specified nucleotide. The method of claim 1, comprising a specific repeating unit comprising a tide.

3. The method of claim 2 , wherein the particular repeating unit comprises a degenerate codon.

4. The one or more self-loops may include two or more self-loops representing two or more repeat subsequences. The method according to any one of claims 1 to 3, comprising:

5. The sequence graph further comprises two or more alternative pathways for two or more alleles. The method according to any one of claims 1 to 4.

6. 6. The method of claim 5, wherein the two or more alleles comprise an indel or a substitution.

7. 5. The method of claim 4, wherein the substitution comprises a single nucleotide variant (SNV) or a single nucleotide polymorphism (SNP). The method described above.

8. Using sequence reads aligned to the two or more alternative pathways, 6. The method of claim 5, further comprising genotyping the offspring.

9. Genotyping the two or more alleles determines the likelihood of the two or more alleles. providing a coverage of the two or more alternative paths to a probabilistic model to determine a rate at which the two or more alternative paths can be used; The method of claim 8 , comprising:

10. The probability model determines the probability of the allele as a function of the coverage of the allele. and the function is a Poisson distribution, a negative binomial distribution, a binomial distribution, or a beta-quadratic distribution. The method of claim 9 , wherein the distribution is selected from a nominal distribution.

11. The rate parameters of the Poisson distribution are the read lengths observed at the genomic loci. and the average depth.

12. Prior to (b), the sequence reads are aligned to a reference genome to identify genomic loci of the sequence reads. determining a target sequence for each of the sequence reads; and selecting a subset of sequence reads as said sequence reads that align with one or more repeat sequences; The method of any one of claims 1 to 11, further comprising:

13. The subset of sequence reads are located in or near the region represented by the sequence graph. The method of claim 12 comprising aligned reads.

14. The subset of sequence reads are located in or near the region represented by the sequence graph. The method of claim 12, comprising unaligned reads binding maps.

15. The subset of sequence reads is subjected to known hotspots for mismatching reads. The method according to claim 12, further comprising: Method of posting.

16. aligning sequence reads to the sequence graph, finding kmer matches between said sequence reads and paths in the sequence graph; The kmer matching is a function of the nodes and edges of the sequence graph that contain one or more self-loops. and extending the second end of the second guide wire into perfect alignment with the first end of the second guide wire. method.

17. Aligning sequence reads to the sequence graph removes low-confidence ends of the alignment. The method of any one of claims 1 to 16, comprising graph reduction by:

18. aligning sequence reads to the sequence graph, aligning partial sequences of the reads into a sequence graph; merging the alignments of the partial sequences to form a complete alignment of the sequence reads; The method of any one of claims 1 to 17, comprising aligning and merging the

19. generating said sequence graph based on a locus specification including a locus structure of said genomic locus; The method of any one of claims 1 to 18, further comprising:

20. the sequence reads include paired-end reads, and operation (c) further comprises: (i) identifying anchor reads and anchored reads in the paired-end reads; wherein the anchor read is a read that aligns to the one or more repeat sequences or are adjacently aligned leads, and the anchor lead is and identifying unaligned reads paired with (ii) detecting the one or more repeat sequences using at least the anchored reads; and determining the one or more genotypes of the individual. The method described.

21. Operation (ii) comprises:

21. The method of claim 20, further comprising determining the genotype of said one or more repeat sequences. Method of posting.

22. 22. The method of claim 20 or 21, wherein the anchor reads align within about 5 kb of a repeat sequence. Method of posting.

23. The unaligned reads cannot be aligned to the sequence graph or The method of any one of claims 20 to 22, comprising reads that align poorly to

24. The one or more repeat sequences of claims 1 to 23, wherein the one or more repeat sequences comprise a short tandem repeat (STR) sequence.

2. The method according to any one of claims 1 to 11.

25. The STR expansion is a cause of Fragile X syndrome, amyotrophic lateral sclerosis (ALS), huntingtin syndrome, and other conditions. Tonne's disease, Friedreich's ataxia, spinocerebellar degeneration, spinal-bulbar muscular atrophy, myotonic dystonia Claims related to Roffey, Machado-Joseph disease, or dentatorubral-pallidoluysian atrophy 25. The method according to item 24.

26. Using a sequencer to generate paired-end reads from the test sample. The method of any one of claims 1 to 25, further comprising:

27. The method according to any one of claims 1 to 26, further comprising extracting the test sample from an individual. The method according to claim 5.

28. The test sample may be a blood sample, a urine sample, a saliva sample, or a tissue sample. The method according to any one of claims 1 to 27, wherein

29. 29. Any one of claims 1 to 28, wherein the repeating unit comprises 1 to 50 nucleotides. The method according to claim 5.

30. 13. The method of claim 1, wherein the read is shorter than at least one of the one or more repeat sequences.

30. The method according to any one of claims 1 to 29.

31. 1. A system comprising: System memory; One or more processors, (a) collecting sequence reads for a test sample from a database; (b) applying the sequence link to the one or more repeat sequences, each of which is represented by a sequence graph. The sequence graph is a set of vertices representing nucleic acid sequences and directed edges connecting the vertices. The data structure of the directed graph includes one or more self-loops. Each self-loop represents a repeat subsequence, and each repeat subsequence is a repeat of one or more nucleotides. Includes repeating return units, (c) using the sequence reads aligned to the one or more repeat sequences to identify the one or more and a processor configured to determine one or more genotypes for the repetitive sequences of the A system that can.

32. A computer program product including a non-transitory machine-readable medium storing program code.

2. An article of manufacture that, when executed by one or more processors of a computer system, The computer system is adapted to genotype repetitive sequences in a test sample comprising nucleic acid. and causing the program code to execute a method for (a) code for collecting sequence reads for a test sample from a database; (b) applying the sequence link to the one or more repeat sequences, each of which is represented by a sequence graph. a sequence graph including vertices representing nucleic acid sequences and A data structure of a directed graph with directed edges connecting the points, the sequence graph having one or more wherein each self-loop represents a repeating subsequence, and each repeating subsequence has one or more a code comprising a repeat of a repeat unit of nucleotide (c) using the sequence reads aligned to the one or more repeat sequences to identify the one or more and code for determining one or more genotypes for the repeat sequences of the Program products.

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