Gene mutation analysis

Abstract

Provided herein are compositions and methods for accurate and scalable primary template directed amplification (PTA) nucleic acid amplification and sequencing methods, and their use for mutation analysis in research, diagnosis, and therapy. Such methods and compositions facilitate highly accurate amplification of target (or "template") nucleic acids, thereby improving the accuracy and sensitivity of downstream applications (such as next-generation sequencing).

Description

[0001] Cross-references

[0002] This application claims the benefit of U.S. Provisional Patent Application No. 62 / 881,180, filed on July 31, 2019, the contents of which are incorporated herein by reference in their entirety. Background Art

[0003] Research methods using nucleic acid amplification, such as next-generation sequencing, provide a wealth of information about complex samples, genomes, and other nucleic acid sources. In some cases, these samples are subject to mutagenic conditions in the environment or through gene editing techniques. For research, diagnosis, and treatment involving small samples such as those subjected to mutagenic conditions, highly accurate, scalable, and efficient nucleic acid amplification and sequencing methods are needed. Summary of the invention

[0004] Described herein are methods for detecting mutations in a sample, genome, or other nucleic acid source.

[0005] Methods for determining mutations are described herein, comprising: (a) exposing a cell population to a gene editing method, wherein the gene editing method utilizes an agent configured to achieve a mutation in a target sequence; (b) isolating a single cell from the population; (c) providing a cell lysate from a single cell; (d) contacting the cell lysate with at least one amplification primer, at least one nucleic acid polymerase, and a nucleotide mixture, wherein the nucleotide mixture includes at least one terminator nucleotide that terminates nucleic acid replication performed by the polymerase, (d) amplifying the target nucleic acid molecule to generate a plurality of terminated amplification products, wherein the replication is performed by strand displacement replication; (e) connecting the molecule obtained in step (e) to an adapter to generate an amplification product library; and (f) sequencing the amplification product library and comparing the amplification product sequence to at least one reference sequence to identify at least one mutation. Methods are also described herein, wherein at least one mutation is present in the target sequence. Methods are also described herein, wherein at least one mutation is not present in the target sequence. Methods are also described herein, wherein the gene editing method includes the use of CRISPR, TALEN, ZFN, recombinase, large-range nuclease or viral integration (intentional or unintentional). Methods are also described herein, wherein the gene editing technology includes the use of CRISPR. Methods are also described herein, wherein the gene editing technology includes the use of gene therapy methods. Methods are also described herein, wherein the gene therapy method is not configured to modify the somatic DNA or germline DNA of the cell. Methods are also described herein, wherein the reference sequence is a genome. Methods are also described herein, wherein the reference sequence is a specific determination sequence, wherein the specific determination sequence is configured to bind to a target sequence. Methods are also described herein, wherein at least one mutation is present in a sequence region that is at least 1 base different from the specific determination sequence. Methods are also described herein, wherein at least one mutation is present in a sequence region that is at least 2 bases different from the specific determination sequence. Methods are also described herein, wherein at least one mutation is present in a sequence region that is at least 3 bases different from the specific determination sequence. Methods are also described herein, wherein at least one mutation is present in a sequence region that is at least 5 bases different from the specific determination sequence. Methods are also described herein, wherein at least one mutation comprises an insertion, a deletion or a substitution. Some methods are also described herein, wherein the reference sequence is a CRISPR RNA (crRNA) sequence. Some methods are also described herein, wherein the reference sequence is a single guide RNA (sgRNA) sequence. Some methods are also described herein, wherein at least one mutation is present in the sequence region that binds to the catalytically active Cas9. Some methods are also described herein, wherein the single cell is a mammalian cell. Some methods are also described herein, wherein the single cell is a human cell. Some methods are also described herein, wherein the single cell is derived from the liver, skin, kidney, blood or lung.Also described herein are methods in which the single cell is a primary cell. Also described herein are methods in which the single cell is a stem cell. Also described herein are methods in which at least some of the amplified products comprise a barcode. Also described herein are methods in which at least some of the amplified products comprise at least two barcodes. Also described herein are methods in which the barcode comprises a cell barcode. Also described herein are methods in which the barcode comprises a sample barcode. Also described herein are methods in which at least some of the amplification primers comprise a unique molecular identifier (UMI). Also described herein are methods in which at least some of the amplification primers comprise at least two unique molecular identifiers (UMI). Also described herein are methods in which the method further comprises an additional amplification step using PCR. Also described herein are methods in which the method further comprises removing at least one terminator nucleotide from the terminated amplified product prior to being connected to an adapter. Also described herein are methods in which a single cell is isolated from a population using a method comprising a microfluidic device. Also described herein are methods in which at least one mutation occurs in less than 50% of a cell population. Also described herein are methods in which at least one mutation occurs in less than 25% of a cell population. Also described herein are methods in which at least one mutation occurs in less than 1% of a cell population. Also described herein are methods in which at least one mutation occurs in no more than 0.1% of a cell population. Also described herein are methods in which at least one mutation occurs in no more than 0.01% of a cell population. Also described herein are methods in which at least one mutation occurs in no more than 0.001% of a cell population. Also described herein are methods in which at least one mutation occurs in no more than 0.0001% of a cell population. Also described herein are methods in which at least one mutation occurs in no more than 25% of amplified product sequences. Also described herein are methods in which at least one mutation occurs in no more than 1% of amplified product sequences. Also described herein are methods in which at least one mutation occurs in no more than 0.1% of amplified product sequences. Also described herein are methods in which at least one mutation occurs in no more than 0.01% of amplified product sequences. Also described herein are methods in which at least one mutation occurs in no more than 0.001% of amplified product sequences. Also described herein are methods in which at least one mutation occurs in no more than 0.0001% of amplified product sequences. Also described herein are methods in which at least one mutation is present in a sequence region associated with a genetic disease or condition. Also described herein are methods in which at least one mutation is present in a sequence region that is not associated with binding of a DNA repair enzyme. Also described herein are methods in which at least one mutation is present in a sequence region that is not associated with binding of MRE11. Also described herein are methods in which the method further comprises identifying false positive mutations previously sequenced by another off-target detection method.The present invention also describes some methods, wherein the off-target detection method is computer simulation prediction, ChIP-seq, GUIDE-seq, circle-seq, HTGTS (high-throughput whole-genome translocation sequencing), IDLV (integration-defective lentivirus), Digenome-seq, FISH (fluorescence in situ hybridization) or DISCOVER-seq.

[0006] Methods for identifying specificity determining sequences are described herein, including: (a) providing a nucleic acid library, wherein at least some nucleic acids comprise specificity determining sequences; (b) performing a gene editing method on at least one cell, wherein the gene editing method comprises contacting the cell with a reagent comprising at least one specificity determining sequence; (c) sequencing the genome of at least one cell using the method described herein, wherein the specificity determining sequence contacted with at least one cell is identified; and (d) identifying at least one specificity determining sequence that provides minimal off-target mutations. Methods are also described herein, wherein the off-target mutations are synonymous or non-synonymous mutations. Methods are also described herein, wherein the off-target mutations are present outside the gene coding region.

[0007] Methods for in vivo mutation analysis are described herein, comprising: (a) performing a gene editing method on at least one cell in a living organism, wherein the gene editing method comprises contacting the cell with a reagent comprising at least one specific determination sequence; (b) isolating at least one cell from the organism; (c) sequencing the genome of at least one cell using the method described herein. Methods are also described herein, wherein the method comprises at least two cells. Methods are also described herein, which also include identifying mutations by comparing the genome of a first cell with the genome of a second cell. Methods are also described herein, wherein the first cell and the second cell are from different tissues.

[0008] Methods for predicting the age of an object are described herein, comprising: (a) providing at least one sample from an object, wherein the at least one sample comprises a genome; (b) sequencing the genome using the methods described herein to identify mutations; (c) comparing the mutations obtained in step b with a standard reference curve, wherein the standard reference curve associates mutation counts and positions with verified ages; and (d) predicting the age of the object based on the comparison of mutations with the standard reference curve. Methods are also described herein, wherein the standard reference curve is specific for the sex of the object. Methods are also described herein, wherein the standard reference curve is specific for the race of the object. Methods are also described herein, wherein the standard reference curve is specific for the geographic location of the object, where the object spent a period of its life. Methods are also described herein, wherein the object is less than 50 years old. Methods are also described herein, wherein the object is less than 18 years old. Methods are also described herein, wherein the object is less than 15 years old. Methods are also described herein, wherein the at least one sample is greater than 10 years. Methods are also described herein, wherein the at least one sample is greater than 100 years. Methods are also described herein, wherein the at least one sample is greater than 1000 years. Some methods are also described herein, wherein at least 2 samples are sequenced. Some methods are also described herein, wherein at least 5 samples are sequenced. Some methods are also described herein, wherein at least two samples are from different tissues.

[0009] Methods for sequencing a microbial or viral genome are described herein, comprising: (a) obtaining a sample comprising one or more genomes or genome fragments; (b) sequencing the sample using the methods described herein to obtain multiple sequencing reads; and (c) assembling and sorting the sequencing reads to generate a microbial or viral genome from even a single bacterial cell or a single viral particle. Methods are also described herein, wherein the sample comprises genomes from at least two organisms. Methods are also described herein, wherein the sample comprises genomes from at least ten organisms. Methods are also described herein, wherein the sample comprises genomes from at least 100 organisms. Methods are also described herein, wherein the sample source is an environment including a deep-sea vent, an ocean, a mine, a stream, a lake, a meteorite, a glacier, or a volcano. Methods are also described herein, further comprising identifying at least one gene in a microbial genome. Methods are also described herein, wherein the microbial genome corresponds to an uncultured organism. Methods are also described herein, wherein the microbial genome corresponds to a symbiotic organism. Methods are also described herein, further comprising cloning at least one gene in a recombinant host organism. Methods are also described herein, wherein the recombinant host organism is a bacterium. Some methods are also described herein, wherein the recombinant host organism is Escherichia, Bacillus or Streptomyces. Some methods are also described herein, wherein the recombinant host organism is a eukaryotic cell. Some methods are also described herein, wherein the recombinant host organism is a yeast cell. Some methods are also described herein, wherein the recombinant host organism is yeast or Pichia pastoris.

[0010] The present invention describes a kit for nucleic acid sequencing, comprising: at least one amplification primer; at least one nucleic acid polymerase; a mixture of at least two nucleotides, wherein the mixture of nucleotides includes at least one terminator nucleotide that terminates nucleic acid replication by the polymerase; and instructions for using the kit for nucleic acid sequencing. The present invention also describes a kit, wherein at least one amplification primer is a random primer. The present invention also describes a kit, wherein the nucleic acid polymerase is a DNA polymerase. The present invention also describes a kit, wherein the DNA polymerase is a strand displacement DNA polymerase. The present invention also describes a kit, wherein the nucleic acid polymerase is bacteriophage phi29 (Φ29) polymerase, genetically modified phi29 (Φ29) DNA polymerase, Klenow fragment of DNA polymerase I, bacteriophage M2 DNA polymerase, bacteriophage phiPRD1 DNA polymerase, Bst DNA polymerase, Bst large fragment DNA polymerase, exo(-)Bst polymerase, exo(-)Bca DNA polymerase, Bsu DNA polymerase, Vent R DNA polymerase, Vent R(exo-)DNA polymerase, Deep Vent DNA polymerase, Deep Vent (exo-)DNA polymerase, IsoPol DNA polymerase, DNA polymerase I, Therminator DNA polymerase, T5 DNA polymerase, Sequenase, T7 DNA polymerase, T7-sequenase or T4 DNA polymerase. Test kits are also described herein, wherein the nucleic acid polymerase comprises 3'->5' exonuclease activity, and at least one terminator nucleotide inhibits the 3'->5' exonuclease activity. Test kits are also described herein, wherein the nucleic acid polymerase does not comprise 3'->5' exonuclease activity. Test kits are also described herein, wherein the polymerase is Bst DNA polymerase, exo(-)Bst polymerase, exo(-)Bca DNA polymerase, Bsu DNA polymerase, VentR (exo-)DNA polymerase, Deep Vent (exo-)DNA polymerase, Klenow fragment (exo-)DNA polymerase or Therminator DNA polymerase. Also described herein are kits, wherein the at least one terminator nucleotide comprises a modification of the r group of the 3' carbon of the deoxyribose. Also described herein are kits, wherein the at least one terminator nucleotide is selected from a 3' blocked reversible terminator comprising a nucleotide, a 3' unblocked reversible terminator comprising a nucleotide, a terminator comprising a 2' modification of a deoxynucleotide, a terminator comprising a modification of a nitrogenous base of a deoxynucleotide, and combinations thereof. Also described herein are kits, wherein the at least one terminator nucleotide is selected from a dideoxynucleotide, a reversed dideoxynucleotide, a 3' biotinylated nucleotide, a 3' amino nucleotide, a 3'-phosphorylated nucleotide, a 3'-O-methyl nucleotide, a 3' carbon spacer nucleotide (including a 3' C3 spacer nucleotide), a 3' C18 nucleotide, a 3' hexanediol spacer nucleotide, an acyclic nucleotide, and combinations thereof. Also described herein are kits, wherein the at least one terminator nucleotide is selected from a nucleotide containing a modification to an alpha group, a C3 spacer nucleotide, a locked nucleic acid (LNA), a reversed nucleic acid, a 2' fluoro nucleotide, a 3' phosphorylated nucleotide, a 2'-O-methyl modified nucleotide, and a trans nucleic acid. Also described herein are kits, wherein the nucleotide containing the modification to the alpha group is an alpha-thiodideoxynucleotide. Also described herein are kits, wherein the length of the amplification primer is 4 to 70 nucleotides. Also described herein are kits, wherein the length of the at least one amplification primer is 4 to 20 nucleotides. Also described herein are kits, wherein the at least one amplification primer comprises a random region. Also described herein are kits, wherein the length of the random region is 4 to 20 nucleotides. Also described herein are kits, wherein the length of the random region is 8 to 15 nucleotides. Also described herein are kits, wherein the kit further comprises a library preparation kit.Also described herein are kits, wherein the library preparation kit comprises one or more of the following: at least one polynucleotide adapter; at least one high-fidelity polymerase; at least one ligase; reagents for nucleic acid shearing; and at least one primer. Also described herein are kits, wherein the kit further comprises reagents configured for gene editing.

[0011] Incorporation by reference

[0012] All publications, patents, and patent applications mentioned in this specification are herein incorporated by reference to the same extent as if each individual publication, patent, or patent application was specifically and individually indicated to be incorporated by reference. BRIEF DESCRIPTION OF THE DRAWINGS

[0013] The novel features of the present invention are particularly set forth in the appended claims. A better understanding of the features and advantages of the present invention will be obtained by referring to the following detailed description and accompanying drawings which set forth illustrative embodiments in which the principles of the invention are utilized, in which:

[0014] Figure 1A The workflow for detecting mutations using the PTA method, single-cell sequencing, and alignment is shown. Edited cells and unedited control cells were amplified using PTA, sequenced using short-read sequencing, and aligned to a reference genome.

[0015] Figure 1B Detection of small indels is shown. Indels (black ovals) are identified by comparing aligned sequence data to a reference genome using variant calling software. Indels that may be candidates for CRISPR editing events are identified by comparing indels between edited and unedited control cells and limiting the search space to genomic regions that show sequence similarity to the gRNA target site. Evidence for candidate editing events includes 1) indels 3-4 bases upstream of the putative PAM sequence in a genomic region that shows similarity to the target site, and 2) these indels are limited to edited cells with no evidence in unedited control cells.

[0016] Figure 1C and 1DDetection of translocations and large deletions is shown. CRISPR-induced structural variants, including inter- and intra-chromosomal translocations, inversions, and large deletions can be identified by comparing read-pair mapping patterns between edited and unedited cells. CRISPR-induced translocations are identified by read pair alignments in edited cells, where at least two regions of the read pair are aligned to different chromosomes and the breakpoints are located in regions that show similarity to the gRNA target sequence. These inconsistent read pairs should not be present in the alignment of unedited cells ( Figure 1C Large deletions are identified by read pairs that show the correct orientation but contain regions that align to distal portions of the reference genome ( Figure 1D ).

[0017] Figure 1E Shown is a comparison of a previous multiple displacement amplification (MDA) method with one embodiment of a primary template directed amplification (PTA) method, namely the PTA-irreversible terminator method.

[0018] Figure 1F A comparison of the PTA-irreversible terminator method with a different embodiment, namely the PTA-reversible terminator method, is shown.

[0019] Figure 1G Shown is a comparison of the MDA and PTA-irreversible terminator approaches as they relate to mutation propagation.

[0020] Figure 1H The process steps performed after amplification are shown, including removal of terminators, repair of ends, and A-tailing prior to adapter ligation. Hybridization-mediated enrichment of all exons or other specific regions of interest can then be performed in the pooled cell library prior to sequencing. The cell originating from each read is identified by a cell barcode (shown as green and blue sequences).

[0021] Figure 2A The size distribution of amplicons after PTA and addition of increasing concentrations of terminator (upper gel) is shown. The lower gel shows the size distribution of amplicons after PTA and addition of increasing concentrations of reversible terminator, or after addition of increasing concentrations of irreversible terminator.

[0022] Figure 2B (GC) shows the comparison of GC content of sequenced bases of MDA and PTA.

[0023] Figure 2C Shown are the mapping quality scores (e) (mapQ) of single cells mapped to the human genome (p_mapped) after undergoing PTA or MDA.

[0024] Figure 2D Percentage of reads mapped to the human genome (p_mapped) after single cells were subjected to PTA or MDA.

[0025] Figure 2E (PCR) Shown is a comparison of the percentage of reads that are PCR replicates among 20 million subsampled reads after single cells were subjected to MDA and PTA.

[0026] Figure 2F Amplification kinetics, ie, amplicon yields of MDA, MDA no template control (NTC), PTA, and PTA no template control (NTC) over time (hours), are shown.

[0027] Figure 3A Shown are the mapping quality scores (c) (mapQ2) mapped to the human genome (p_mapped2) after single cells were subjected to reversible or irreversible terminator PTA.

[0028] Figure 3B Shown are the percentages of reads mapped to the human genome (p_mapped2) after single cells were subjected to reversible or irreversible terminator PTA.

[0029] Figure 3C A series of box plots derived using various methods are shown, depicting the average percentage of aligned reads overlapping Alu elements. PTA has the maximum number of reads aligned to the genome.

[0030] Figure 3D Shown is a series of box plots derived using various methods, depicting the average percentage of reads overlapping Alu elements across PCR replicates.

[0031] Figure 3E Shown is a series of box plots derived using various methods, depicting the GC content of the average percentage of reads overlapping with Alu elements.

[0032] Figure 3F A series of box plots are shown using various methods, depicting the mapping quality of the average percentage of reads overlapping Alu elements. PTA had the highest mapping quality of the methods tested.

[0033] Figure 3G Shown is a comparison of the SC mitochondrial genome coverage breadth using different WGA methods at a fixed 7.5X sequencing depth.

[0034] Figure 4AShown is the average coverage depth for a 10 kilobase window on chromosome 1 after selecting high-quality MDA cells (representing ˜50% of cells) compared to cells amplified with random primers PTA after downsampling to 40 million paired reads per cell. The figure shows that MDA is less uniform, with more windows having a coverage depth that is two-fold greater (box A) or less (box C) than the average coverage depth. There is no coverage at the centromere for both MDA and PTA (box B) due to high GC content and low mapping quality in repetitive regions.

[0035] Figure 4B A plot of sequencing coverage versus genomic position for the MDA and PTA methods is shown (top). The lower box plot shows the allele frequencies for the MDA and PTA methods compared to bulk samples.

[0036] Figure 5A A plot of the fraction of the genome covered versus the number of genome reads is shown to evaluate the coverage of various methods at increasing sequencing depth. The PTA method approached both bulk samples at each depth, an improvement over the other methods tested.

[0037] Figure 5B The coefficient of variation of genome coverage versus the number of reads is shown to assess coverage uniformity. The PTA method was found to have the highest uniformity among the methods tested.

[0038] Figure 5C Lorenz plots of the cumulative fraction of total reads versus the cumulative fraction of the genome are shown. The PTA method was found to have the highest uniformity among the methods tested.

[0039] Figure 5D A series of box plots of the calculated Gini index for each method tested are shown in order to assess the differences in each amplification reaction in terms of complete uniformity. The PTA method was found to have reproducibly higher uniformity than the other methods tested.

[0040] Figure 5E The fraction of called bulk variants versus the number of reads is shown. The variant call rate of each method was compared to the corresponding bulk sample at increasing sequencing depth. To assess sensitivity, the percentage of variants found in each cell that were called in the corresponding bulk sample downsampled to 650 million reads was calculated at each sequencing depth ( Figure 5A The improved coverage and uniformity of PTA allowed the detection of 30% more variants compared to the next most sensitive method, Q-MDA.

[0041] Fig. 5FA series of box plots showing the average percentage of reads overlapping with Alu elements are shown. The PTA method significantly reduced the allele skew at these heterozygous sites. The PTA method amplified both alleles in the same cell more evenly relative to the other methods tested.

[0042] Figure 5G A plot of the accuracy of variant calls versus the number of reads is shown to assess the accuracy of mutation calls. Variants found using various methods that are not found in a large number of samples are considered false positives. Among the methods tested, the PTA method has the lowest false positive calls (highest accuracy).

[0043] Figure 5H The fraction of false positive base changes for each type of base change is shown for various methods. Without being bound by theory, this pattern may be polymerase dependent.

[0044] Fig.5I A series of box plots showing the average percentage of reads overlapping Alu elements for false positive variant calls are shown. The PTA method produced the lowest allele frequency for false positive variant calls.

[0045] Figure 5J Shown are the mean coefficient of variation (CV) of coverage with increasing bin size in primary leukemia samples using commercial kits as an assessment of the accuracy of CNV calls.

[0046] Figure 5K The chromosome CNV atlas of the PTA product from a single cell is shown, wherein CNV (shaded arrow) is determined in a large number of samples. Unshaded arrows represent regions that are inferred to be subclonal CNVs but not determined in a large number of samples, wherein two of five cells are found to have the same change. The region where CNV detection is reduced in the karyotype diagram represents the centromere, which indicates that coverage is reduced in PTA-amplified cells (for dot plots and line plots, error bars represent one SD, and for box plots, the center line is the median; box specification limits represent upper and lower quartiles; box whiskers represent 1.5 times the interquartile range; point displays outliers).

[0047] Fig. 6A A schematic diagram of a clonotype drug sensitivity catalogue in accordance with the present disclosure is depicted. By identifying the drug sensitivity of different clonotypes, a catalogue can be created from which an oncologist can translate the clonotypes identified in a patient's tumor into a list of drugs that are most suitable for the resistant population.

[0048] Figure 6BThe number of leukemia clones after 100 simulations is shown as the number of leukemia cells per clone increases. Using the mutation rate of each cell, the simulation predicts that as one cell expands to 10 to 100 billion cells, a large number of small clones will be generated (box A). Current sequencing methods only detect the 1-5 most frequent clones (box C). In one embodiment of the invention, a method is provided for determining drug resistance of hundreds of clones just below the detection level of current methods (box B).

[0049] Figure 7 An exemplary embodiment of the present disclosure is shown. Compared to the diagnostic samples in the bottom row, the culture without chemotherapy selected clones with activated KRAS mutations (red box, lower right corner). In contrast, the clones were killed by prednisolone or daunomycin (green box, upper right corner), while the clones with lower frequencies underwent positive selection (dashed box).

[0050] Figure 8 is an overview of one embodiment of the present disclosure, namely an experimental design for quantifying the relative sensitivity of clones with specific genotypes to specific drugs.

[0051] Fig. 9 (Part A) shows beads with oligonucleotides attached with cleavable adapters, unique cell barcodes and random primers. Part B shows that a single cell and beads are encapsulated in the same droplet, and then the cell is lysed and the primer is cut. The droplet can then be fused with another droplet comprising a PTA amplification mixture. Part C shows that the droplet breaks after amplification, and the amplicons from all cells are merged. The scheme according to the present disclosure is then used to remove terminators, end repair and add A tails, followed by connecting adapters. Then, before sequencing, the merged cell library is subjected to hybridization-mediated enrichment for exons of interest. Then, the cell barcode is used to identify the cell derived from each read.

[0052] Fig. 10A Demonstrated is the incorporation of cellular barcodes and / or unique molecular identifiers into PTA reactions using primers comprising the cellular barcodes and / or unique molecular identifiers.

[0053] Fig. 10B The incorporation of cellular barcodes and / or unique molecular identifiers into PTA reactions using hairpin primers comprising the cellular barcodes and / or unique molecular identifiers is demonstrated.

[0054] Fig.11A (PTA_UMI) shows that the incorporation of unique molecular identifiers (UMIs) enables the creation of consensus reads, reducing false positive rates caused by sequencing and other errors, leading to increased sensitivity when making germline or somatic variant calls.

[0055] Fig. 11B It is shown that collapsing reads with the same UMI can correct for amplification and other biases that can lead to false detections or limited sensitivity when calling copy number variants.

[0056] Fig. 12A A plot of the number of mutations versus treatment group is shown for direct measurements of environmental mutagenicity experiments. Single human cells were exposed to vehicle (VHC), mannose (MAN), or the direct mutagen N-ethyl-N-nitrosourea (ENU) at varying treatment levels, and the number of mutations was measured.

[0057] Fig. 12B A series of graphs showing the number of mutations versus different treatment groups and levels are shown, further broken down by type of base mutation.

[0058] Fig. 12C A pattern representation of mutations in a trinucleotide context is shown. The base on the y-axis is at the n-1 position, and the base on the x-axis is at the n+1 position. Darker areas represent lower mutation frequencies, and lighter areas represent higher mutation frequencies. The solid black boxes (cytosine mutations) in the top row indicate that the frequency of cytosine mutagenesis decreases when cytosine is followed by guanine. The dotted black boxes (thymine mutations) in the bottom row indicate that most thymine mutations occur at the position when adenine is directly in front of thymine.

[0059] Fig.12D A graph comparing the positions of known DNase I hypersensitive sites in CD34+ cells with the corresponding positions in N-ethyl-N-nitrosourea treated cells is shown. No significant enrichment of cytosine variants was observed.

[0060] Fig.12E Shown is the ratio of ENU induced mutation in DNA enzyme I hypersensitive (DH) site.DH site in CD34+ cell that was previously classified by epigenomics roadmap plan (Roadmap Epigenomics Project) was used to study whether ENU mutation is more prevalent at DH site representing open chromatin site.Significant enrichment is not identified at the variant position of DH site, and enrichment of variant limited to cytosine is not observed at DH site.

[0061] Fig.12F A series of box plots showing the proportion of ENU-induced mutations in genomic positions with a particular annotation are shown. No specific enrichment is seen in a particular annotation for variants in each cell (left box) relative to the proportion of the genome included by each annotation (right box).

[0062] Fig.13AShown are insertion / deletion (indel) counts in edited versus unedited cells within a Hamming distance of 7 at the target site after genome editing experiments and PTA.

[0063] Fig. 13B Shown are the structural variant counts in edited versus unedited cells within a Hamming distance of 6 of the target site after genome editing experiments and PTA.

[0064] Fig.14A Detection of CRISPR-induced editing in single cells after 2 edits using PTA is shown.

[0065] Fig. 14B Shown is the use of PTA to detect a large (>1KB) deletion resulting from CRISPR-induced editing that is restricted to edited #1 cells.

[0066] Fig. 14C Detection of an interchromosomal translocation between chromosome 2 position 241,275,213 and chromosome 4 position 38,536,006 in edited #1 cells using PTA is shown.

[0067] Fig.15A Shown are alignment and SNV calling metrics in primary leukemia cells at increasing sequencing depth of coverage (n=5 for each method, error bars represent 1 SD).

[0068] Fig. 15B Shown are alignment and SNV calling metrics in primary leukemia cells at increasing sequencing depth of CV coverage (n=5 for each method, error bars represent 1 SD).

[0069] Fig. 15C Shown are alignment and SNV calling metrics in primary leukemia cells at increasing sequencing depth for call sensitivity (n=5 for each method, error bars represent 1 SD).

[0070] Fig.15D Shown are alignment and SNV calling metrics in primary leukemia cells upon increasing sequencing depth for SNV calling accuracy (n=5 for each method, error bars represent 1 SD).

[0071] Fig.16A An overview of a homogenous cell experiment is shown, where single cells are plated and cultured, and individual cells are then re-isolated, PTA, and sequenced.

[0072] Fig. 16B A method for classifying variant types by comparing bulk and single-cell data is shown.

[0073] Fig. 16C The sensitivity and accuracy of SNV calls per cell are shown, based on a large number of cells.

[0074] Fig.16D The percentage of variants called heterozygous for the different variant classes is shown.

[0075] Fig.16E Shown are false positive and somatic mutation rates measured in single CD34+ human cord blood cells.

[0076] Fig.17A An overview of the number of mutations for all variants in each sample is shown.

[0077] Fig. 17B An overview of the number of mutations of somatic variants in each sample is shown.

[0078] Fig. 17C An overview of the number of mutations of false-positive variants in each sample is shown.

[0079] Fig.18A An overview of the allele frequency distribution of germline variants is shown.

[0080] Fig.18B An overview of the allele frequency distribution of somatic variants is shown.

[0081] Fig. 18C An overview of the allele frequency distribution of false-positive variants is shown.

[0082] Fig.19 The density of homozygous or heterozygous false positive variant calls on chromosome 14 is shown (this chromosome had the greatest number of false positive calls). The average GC content of 100 Kb bins runs below the karyotype diagram.

[0083] Fig. 20A Experimental and computational methods are shown to measure off-target activity of genome editing strategies at single-cell resolution, where individual edited cells are sequenced and indel calls are restricted to sites with a maximum of five mismatches to the protospacer sequence.

[0084] Fig. 20B The number of indel calls per cell is shown. Indel calls were made for each control or experimental cell type where the target region had a mismatch of up to 5 bases with the VEGFA or EMX1 protospacer sequence. The gRNA or control listed in the legend specifies which gRNA the cell received. Indel calls in genomic regions that did not match the gRNA the cell received were considered false positives.

[0085] Fig. 20CTable showing the total number of off-target indel positions identified that were either unique to one cell or present in multiple cells.

[0086] Fig.20D The genomic locations of recurrent indels using EMX1 or VEGFA gRNA are shown. On-target sites are marked in grey.

[0087] Fig.20E Circos plots of SVs identified in each cell type receiving EMX1 or VEGFA gRNA are shown, with sites containing at least one recurrent breakpoint that occurred across cell types shown in green or that occurred only in that cell type shown in red. The number of SVs detected in each cell is plotted on the right (for box plots, the center line is the median; box specification limits represent the upper and lower quartiles; box whiskers represent 1.5 times the interquartile range; dots show outliers).

[0088] Fig.21 Experiments to improve the accuracy of off-target detection by removing non-recurrent single base pair insertions are shown. Indels were called for each control or experimental cell type, requiring no more than 5 mismatches to the VEGFA or EMX1 guide RNA sequence. Off-target events specify which genomic region the gRNA must match, while the gRNA or control listed in the legend specifies which gRNA the cell received. Indels called in genomic regions that did not match the gRNA the cell received were considered false positives.

[0089] Fig.22A The longest contig lengths of bacterial samples analyzed using the PTA method are shown.

[0090] Fig. 22B A graph is shown for each sample, containing the ratio of cumulative length to cumulative contig length, and the genus of the closest hit for each sample based on alignment to the genome sequence.

[0091] Fig. 22C A plot of the ratio of cumulative length to cumulative contig length for bacterial samples 10 is shown, along with the genus of the closest hit for each sample based on alignment to the Haemophilus and Streptococcus genome sequences.

[0092] Fig.22D Shown are the read pairs aligned to the human chromosome for each bacterial sample tested.

[0093] Fig.22E A schematic diagram for designating reads as human in origin is shown.

[0094] Fig.22FShown are the read pair mapping positions for all read pairs that had at least one human-mapped read for all bacterial samples tested.

[0095] Figure 22G The taxonomic ranks assigned to the contigs belonging to bacterial sample 10 are shown. DETAILED DESCRIPTION

[0096] It is necessary to develop new scalable, accurate and efficient nucleic acid amplification (including single cell and multi-cell genome amplification) and sequencing methods, which will overcome the limitations of current methods by increasing sequence presentation, uniformity and accuracy in a reproducible manner. Provided herein are compositions and methods for providing accurate and scalable primary template directional amplification (PTA) and sequencing. These methods and compositions promote high-precision amplification of target (or "template") nucleic acids, which increases the accuracy and sensitivity of downstream applications (such as next-generation sequencing). Also provided herein are methods for determining single nucleotide variants, copy number variations, structural variants, clonal typing and environmental mutagenicity measurements. Measuring genomic variation by PTA can be used for various applications, such as environmental mutagenicity, predicting the safety of gene editing technology, measuring genomic changes caused by cancer treatment, measuring the carcinogenicity of compounds or radiotherapy (including genetic toxicity studies for determining the safety of new foods or drugs), assessing age, analyzing drug-resistant bacteria and identifying bacteria in industrial application environments. In addition, these methods can also be used to detect the selection of specific cell populations after changes in environmental conditions, such as exposure to anticancer treatments, and predicting the response to immunotherapy based on mutations and new antigen loads in individual cancer cells.

[0097] definition

[0098] Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which these inventions belong.

[0099] Throughout this disclosure, numerical features are represented in range format. It should be understood that the description of range format is only for convenience and simplicity, and should not be interpreted as a strict limitation of the scope of any embodiment. Therefore, unless the context clearly indicates otherwise, it should be considered that the description of the range has specifically disclosed all possible sub-ranges and a single numerical value up to one-tenth of the lower limit unit within the range. For example, the description of the range such as from 1 to 6 should be considered as specifically disclosing a sub-range, such as from 1 to 3, from 1 to 4, from 1 to 5, from 2 to 4, from 2 to 6, from 3 to 6, etc., and a single value within the range, for example, 1.1, 2, 2.3, 5 and 5.9. Regardless of the width of the range, this applies. The upper and lower limits of these intermediate ranges can be independently included in a smaller range, and are also included in the present invention, subject to any explicit exclusion of restrictions within the specified range. When the range includes one or two limits, unless the context clearly indicates otherwise, the scope that does not include one or two of the included limits is also included in the present invention.

[0100] The terms used herein are for the purpose of describing specific embodiments only and are not intended to limit any embodiments. As used herein, the singular forms "a", "an", and "the" are also intended to include the plural forms, unless the context clearly indicates otherwise. It will also be understood that when the terms "comprises" and / or comprising are used in this specification, they specify the presence of the features, wholes, steps, operations, elements, and / or components, but do not exclude the presence or addition of one or more other features, wholes, steps, operations, elements, components, and / or groups thereof. As used herein, the term "and / or" includes any and all combinations of one or more associated listed items.

[0101] Unless otherwise specified or apparent from the context, as used herein, the term "about" when referring to a numerical value or a range of numerical values ​​should be understood to mean the stated numerical value + / - 10% thereof, or, for values ​​listed in a range, from 10% below the listed lower limit to 10% above the listed upper limit.

[0102] As used herein, the term "subject" or "patient" or "individual" refers to animals, including mammals, such as humans, veterinary animals (e.g., cats, dogs, cows, horses, sheep, pigs, etc.) and disease experimental animal models (e.g., mice, rats). According to the present invention, conventional molecular biology, microbiology and recombinant DNA techniques can be used within the skill of the art. These techniques are fully explained in the literature. See, e.g., Sambrook, Fritsch and Maniatis, Molecular Cloning: A Laboratory Manual, 2nd Edition (1989) Cold Spring Harbor Laboratory Press, Cold Spring Harbor, New York (hereinafter "Sambrook et al., 1989"); DNA Cloning: A practical Approach, Volumes I and II (DN Glover, 1985); Oligonucleotide Synthesis (MJ. Gait, 1984); Nucleic Acid Hybridization (BD Hames and SJ Higgins, (1985)); Transcription and Translation (BD Hames and SJ Higgins, (1984)); Animal Cell Culture (RI Freshney, (1986)); Immobilized Cells and Enzymes (IRL Press (1986)); B. Perbal, A practical Guide To Molecular Cloning: A Laboratory Manual, 2nd Edition (1989) Cold Spring Harbor Laboratory Press, Cold Spring Harbor, New York (hereinafter "Sambrook et al., 1989"); DNA Cloning: A practical Approach, Volumes I and II (DN Glover, 1985); Oligonucleotide Synthesis (MJ. Gait, 1984); Nucleic Acid Hybridization (BD Hames and SJ Higgins, (1985)); Transcription and Translation (BD Hames and SJ Higgins, (1984)); Animal Cell Culture (RI Freshney, (1986)); Immobilized Cells and Enzymes (IRL Press (1986)); B. Perbal, A practical Guide To Molecular Cloning (1984); FM Ausubel et al. (authors), Current Protocols in Molecular Biology, John Wiley & Sons, Inc. (1994); etc.

[0103] The term "nucleic acid" encompasses multi-stranded and single-stranded molecules. In double-stranded or triple-stranded nucleic acids, the nucleic acid chains do not need to be co-extended (i.e., double-stranded nucleic acids do not need to be double-stranded along the entire length of the two chains). Nucleic acid templates as described herein can have any size according to the sample (from small cell-free DNA fragments to the entire genome), including but not limited to a length of 50-300 bases, 100-2000 bases, 100-750 bases, 170-500 bases, 100-5000 bases, 50-10,000 bases, or 50-2000 bases. In some cases, the length of the template is at least 50, 100, 200, 500, 1000, 2000, 5000, 10,000, 20,000, 50,000, 100,000, 200,000, 500,000, 1,000,000 or more than 1,000,000 bases. The methods described herein provide amplification of nucleic acids such as nucleic acid templates. The methods described herein additionally provide the generation of isolated and at least partially purified nucleic acids and nucleic acid libraries. Nucleic acids include, but are not limited to, DNA, RNA, circular RNA, cfDNA (cell-free DNA), cfRNA (cell-free RNA), siRNA (small interfering RNA), cffDNA (cell-free fetal DNA), mRNA, tRNA, rRNA, miRNA (microRNA), synthetic polynucleotides, polynucleotide analogs, any other nucleic acid that meets this specification, or any combination thereof. When a polynucleotide is provided, its length is described in terms of base numbers and abbreviations such as nt (nucleotide), bp (base), kb (kilobase), or Gb (gigabase).

[0104] As used herein, the term "droplet" refers to a volume of liquid on a droplet actuator. In some cases, for example, the droplet is aqueous or non-aqueous, or can be a mixture or emulsion including aqueous and non-aqueous components. For non-limiting examples of droplet fluids that can be subjected to droplet operations, see, for example, International Patent Application Publication No. WO2007 / 120241. In the embodiments presented herein, any system suitable for forming and manipulating droplets can be used. For example, in some cases, a droplet actuator is used. For non-limiting examples of droplet actuators that can be used, see, e.g., U.S. Patent Nos. 6,911,132, 6,977,033, 6,773,566, 6,565,727, 7,163,612, 7,052,244, 7,328,979, 7,547,380, 7,641,779, U.S. Patent Application Publication Nos. US20060194331, US20030205632, US 20060164490, US20070023292, US20060039823, US20080124252, US20090283407, US20090192044, US20050179746, US20090321262, US20100096266, US20110048951, International Patent Application Publication No. WO2007 / 120241. In some cases, the beads are provided in a droplet, in a droplet operations gap, or on a droplet operations surface. In some cases, the beads are provided in a reservoir located outside the droplet operations gap or separate from the droplet operations surface, and the reservoir can be associated with a flow path that allows a droplet including the beads to enter the droplet operations gap or contact the droplet operations surface. Non-limiting examples of droplet actuator technology for immobilizing magnetically responsive beads and / or non-magnetically responsive beads and / or using beads for droplet manipulation protocols are described in U.S. Patent Application Publication No. US20080053205, International Patent Application Publication Nos. WO2008 / 098236, WO2008 / 134153, WO2008 / 116221, WO2007 / 120241. The bead properties can be employed in multiplexing embodiments of the methods described herein. Examples of beads having properties suitable for multiplexing, and methods of detecting and analyzing signals emanating from such beads, can be found in U.S. Patent Application Publication Nos. US20080305481, US20080151240, US20070207513, US20070064990, US20060159962, US20050277197, US20050118574.

[0105] As used herein, the term "unique molecular identifier (UMI)" refers to a unique nucleic acid sequence attached to each of a plurality of nucleic acid molecules. When incorporated into a nucleic acid molecule, in some cases, the UMI is used to correct for subsequent amplification bias by directly counting the UMIs sequenced after amplification. The design, incorporation, and application of UMIs are described, for example, in International Patent Application Publication No. WO 2012 / 142213, Islam et al. Nat. Methods (2014) 11: 163-166; Kivioja, T. et al., Nat. Methods (2012) 9: 72-74; Brenner et al. (2000) PNAS 97 (4), 1665, and Hollas and Schuler, (2003) Conference: 3rd International Symposium on Bioinformatics Algorithms, Vol. 2812.

[0106] As used herein, the term "barcode" refers to a nucleic acid tag that can be used to identify a sample or source of a nucleic acid material. Therefore, in some cases, when the nucleic acid sample is from multiple sources, the nucleic acid in each nucleic acid sample is labeled with different nucleic acid tags, so that the source of the sample can be identified. Barcodes, also commonly referred to as indexes, labels, etc., are well known to those skilled in the art. Any suitable barcode or barcode set can be used. See, for example, the non-limiting examples provided in U.S. Patent No. 8,053,192 and International Patent Application Publication No. WO2005 / 068656. The barcoding of a single cell can be performed, for example, as described in U.S. Patent Application Publication No. 2013 / 0274117.

[0107] The terms "solid surface," "solid support," and other grammatical equivalents herein refer to any material that is suitable or can be modified to be suitable for attachment of primers, barcodes, and sequences described herein. Exemplary substrates include, but are not limited to, glass and modified or functionalized glass, plastics (including acrylic, polystyrene, and copolymers of styrene with other materials, polypropylene, polyethylene, polybutylene, polyurethane, The solid support may be a polymer, such as polysaccharides, nylon, nitrocellulose, ceramics, resins, silica, silica-based materials (e.g., silicon or modified silicon), carbon, metals, inorganic glass, plastics, fiber optic bundles, and various other polymers. In some embodiments, the solid support comprises a patterned surface suitable for immobilizing primers, barcodes, and sequences in an ordered pattern.

[0108] As used herein, the term "biological sample" includes, but is not limited to, tissues, cells, biological fluids, and isolates thereof. In some cases, cells or other samples used in the methods described herein are isolated from human patients, animals, plants, soil, or other samples including microorganisms such as bacteria, fungi, protozoa, etc. In some cases, the biological sample is derived from humans. In some cases, the biological sample is not derived from humans. In some cases, cells undergo the PTA method and sequencing described herein. Variants detected in the entire genome or at a specific location can be compared with all other cells isolated from the subject to track the history of the cell lineage for research or diagnostic purposes.

[0109] In some cases, the terms "precision" and "specificity" are used synonymously. In some cases, precision (or positive predictive value) defines the number of true positive hits divided by the total number of positive hits identified (true positives + false positives).

[0110] When referring to polymerase-mediated amplification reaction, the term "cycle" is used herein to describe at least a portion of the dissociation step of double-stranded nucleic acid (e.g., from the template of the amplicon or the denaturation of the double-stranded template), the hybridization (annealing) of at least a portion of the primer and the template and the extension of the primer to generate the amplicon. In some cases, the temperature remains constant in the amplification cycle (e.g., isothermal reaction). In some cases, the cycle number is positively correlated with the amplicon quantity generated. In some cases, the cycle number of isothermal reaction is controlled by the amount of time allowed for the reaction to proceed.

[0111] Methods and Applications

[0112] The method for using the PTA method to identify cell mutations is described herein. Using the PTA method in some cases can cause the improvement to known methods (for example, MDA). In some cases, compared with the MDA method, the false positive and false negative variant determination rate of PTA is lower. In some cases, by genome, such as NA12878 platinum genome, whether the larger genome coverage and uniformity of PTA can cause lower false negative variant determination rate. Not subject to theoretical constraints, it can be determined that the disappearance of error propagation in PTA reduces the false positive variant determination rate. In some cases, the amplification balance between alleles with these two methods is assessed by the allele frequency determined by the heterozygous mutation at known positive locus. In some cases, the amplicon library generated by using PTA is further amplified by PCR. In some cases, the PTA method identifies a mutation present in a single cell of a population, wherein the mutation detected by PTA occurs in less than 2%, 1%, 0.5%, 0.2%, 0.1%, 0.05%, 0.02%, 0.01%, 0.001%, 0.0001%, or less than 0.00001% of the cells in the population. In some cases, for a given base or region, the PTA method identifies a mutation in less than 2%, 1%, 0.5%, 0.2%, 0.1%, 0.05%, 0.02%, 0.01%, 0.001%, 0.0001%, or less than 0.00001% of the sequencing reads.

[0113] Safety of gene editing

[0114] From correcting genes that cause or contribute to disease (e.g., sickle cell anemia and many other diseases) to eradicating currently untreatable infectious diseases, the continued development of genome editing tools shows great promise for improving human health. However, the safety of these interventions remains unclear because we do not fully understand how these tools interact with and permanently alter other locations in the edited cell genome. Methods have been developed to assess the off-target rates of genome editing strategies, but the tools developed to date interrogate populations of cells together, resulting in an inability to measure off-target rates in each cell and differences in off-target activity between cells, as well as an inability to detect rare editing events that occur in a small number of cells. These suboptimal strategies for measuring the fidelity of genome editing result in limited ability to determine the sensitivity and precision of a given genome editing method.

[0115] Gene therapy methods may include modifying mutated pathogenic genes, knocking out pathogenic genes, or introducing new genes in cells. In some cases, these methods include modification of genomic DNA. In other cases, viruses or other delivery systems are configured so that they will not integrate or modify the genomic DNA in cells. However, such a system may still generate unwanted or unexpected modifications to somatic cells or germline DNA. PTA is utilized to improve the sensitivity and accuracy of variant determination in single cells. In some cases, the unexpected insertion rate of highly sensitive gene therapy methods in single cells is quantitatively measured. In some cases, the method can detect the insertion of specific sequences in unexpected positions by detecting surrounding sequences to determine whether gene therapy methods cause insertion or modification of the host genome.

[0116] Described herein is a method for identifying mutations and structural modifications (i.e., translocations, insertions, and deletions) in animals, plants, or microbial cells that have undergone genome editing (e.g., CRISPR (clustered regularly interspaced short palindromic repeats), TALEN (transcription activator-like effector nuclease), ZFN (zinc finger nuclease), recombinase, meganuclease, viral integration, or other genome editing techniques). In some embodiments, genome editing is unintentional or is a secondary effect of another process. In some cases, genome editing includes site-specific or targeted genome editing. In some cases, such cells can be isolated and PTA and sequencing are performed to determine the mutation load, mutation combination, and structural variants in each cell. In some cases, the mutation rate per cell and mutation position generated by the genome editing scheme are used to assess the safety and / or efficiency of a given genome editing method. In some cases, the identification of mutations includes comparing the sequencing data obtained using the PTA method with a reference sequence. In some cases, the reference sequence is a genome. In some cases, after the gene editing process, at least one mutation is identified by PTA. In some cases, the reference sequence is a specificity-determining sequence that facilitates the introduction of mutations into the target sequence of a nucleic acid. In some cases, after the gene editing process, at least one mutation is identified by PTA, wherein the mutation is located in the target sequence. In some cases, the off-target mutation rate is analyzed by identifying at least one mutation that is not in the target sequence. Although based on the sequence homology with the target sequence, it can be predicted that some regions of the nucleic acid will have off-target mutations, regions with lower homology may also have off-target mutations. In some cases, the PTA method identifies mutations in the off-target region of the sequence, which comprises at least 3, 4, 5, 6, 7 or 8 base mismatches with the target sequence or its reverse complementary sequence. In some cases, single cells are analyzed with PTA. In some cases, cell colonies are analyzed with PTA.

[0117] Many current mutation analysis methods obtain sequencing data for batch cell populations. However, these methods provide limited information about the actual mutation frequency in the population, and the single cell analysis using PTA in some cases provides a higher resolution for insertion off-target rate, chain breakage (causing mutation) and translocation, because the number of cells (i.e. single cells) is known. PTA has a known variation detection rate in a known number of single cells, which allows the method to accurately identify the frequency of each cell in the cell population and the combination of changes. In some cases, PTA is used to analyze at least 10, 100, 1000, 10,000, 100,000 or more than 100,000 single cells to determine the variation rate. In some cases, PTA is used to analyze no more than 10, 100, 1000, 10,000, 100,000 or no more than 100,000 single cells to determine the variation rate. In some cases, 10-1000, 50-5000, 100-100,000, 1000-100,000, 100-1,000,000, or 100-10,000 single cells are analyzed using PTA to determine the mutation rate. In some cases, a mutation identified by analyzing one or more single cells would not be identified or detected from bulk sequencing of a population of cells.

[0118] CRISPR can be used to introduce mutations into one or more cells, such as mammalian cells, and then analyze mutations by PTA. In some cases, the specificity determining sequence is present in CRISPR RNA (crRNA) or single guide RNA (sgRNA). In some cases, the mammalian cell is a human cell. In some cases, the cell is derived from the liver, skin, kidney, blood or lung. In some cases, the cell is a primary cell. In some cases, the cell is a stem cell. Previously reported methods for identifying off-target mutations generated from CRISPR include pulling down sequences bound to catalytically active Cas9, but this may lead to false positives because not all Cas9 binding sites introduce mutations. In some cases, the PTA method identifies at least one mutation present in a sequence region bound to catalytically active Cas9. In some cases, the PTA method produces fewer false positives for at least one mutation present in a sequence region bound to catalytically active Cas9.

[0119] Described herein is a method for identifying mutations in animals, plants or microbial cells that have undergone genome editing (e.g., CRISPR, TALEN, ZFN, recombinase, meganuclease, viral integration or other technologies), wherein the method includes amplifying a genome or a fragment thereof in the presence of at least one terminator nucleotide. In some cases, the amplification with a terminator is carried out in solution. In some cases, at least one primer or at least one genome fragment is attached to a surface. In some cases, at least one primer is attached to a first solid support, and at least one genome fragment is attached to a second solid support, wherein the first solid support and the second solid support are not connected. In some cases, at least one primer is attached to a first solid support, and at least one genome fragment is attached to a second solid support, wherein the first solid support and the second solid support are not the same solid support. In some cases, the method includes amplifying a genome or a fragment thereof in the presence of at least one terminator nucleotide, wherein the number of amplification cycles is less than 12, 10, 9, 8, 7, 6, 5, 4 or less than 3 cycles. In some cases, the average length of the amplified product is 100-1000, 200-500, 200-700, 300-700, 400-1000 or 500-1200 bases. In some cases, the method includes amplifying a genome or a fragment thereof in the presence of at least one terminator nucleotide, wherein the amplification cycle number does not exceed 6 cycles. In some cases, the at least one terminator nucleotide does contain a detectable marker or label. In some cases, the amplification comprises 2, 3 or 4 terminator nucleotides. In some cases, at least two terminator nucleotides contain different bases. In some cases, at least three terminator nucleotides contain different bases. In some cases, four terminator nucleotides each contain different bases.

[0120] Methods for determining the safety of gene therapy are described herein. In some cases, the function of the cell is changed by gene editing or other expression methods. In some cases, the viral delivery system that changes the cell function is configured so that it will not be integrated into the genome of the cell. In some cases, the PTA method is used to identify unexpected or unwanted changes in the cell genome. In some cases, PTA is used to identify mutations to somatic cells or germline DNA caused by gene therapy.

[0121] Tumor cell clone analysis

[0122] In some cases, the cells analyzed using the methods described herein include tumor cells. For example, circulating tumor cells can be separated from body fluids such as but not limited to blood, bone marrow, urine, saliva, cerebrospinal fluid, pleural fluid, pericardial fluid, ascites or aqueous humor taken from the patient. Then, the cells are subjected to the methods described herein (e.g., PTA) and sequenced to determine the mutation load and mutation combination of each cell. In some cases, these data are used to diagnose specific diseases or as a tool for predicting treatment response. Similarly, in some cases, cells with unknown malignant potential are separated from the collection medium around cells in body fluids such as but not limited to blood, bone marrow, urine, saliva, cerebrospinal fluid, pleural fluid, pericardial fluid, ascites, aqueous humor, blastocyst cavity fluid or culture taken from the patient. In some cases, samples are obtained from the collection medium around embryonic cells. After utilizing the methods described herein and sequencing, these methods are also used to determine the mutation load and mutation combination of each cell. In some cases, these data are used to diagnose specific diseases or as a tool for predicting that pre-malignant states develop into dominant malignancies. In some cases, cells can be separated from primary tumor samples. Then, the cells can be subjected to PTA and sequencing to determine the mutation load and mutation combination of each cell. These data can be used to diagnose specific diseases or as a tool to predict the resistance of a patient's malignant tumor to available anticancer drugs. By exposing the sample to different chemotherapeutic drugs, it has been found that the main and secondary clones have different sensitivities to specific drugs, and these sensitivities are not necessarily related to the presence of known "driver mutations", which indicates that the combination of mutations in the clonal population determines its sensitivity to specific chemotherapeutic drugs. Without being bound by theory, these findings suggest that if a precancerous lesion that has not yet expanded and can evolve into a clone with an increased number of genomic modifications that makes it more likely to be resistant to treatment is detected, it may be easier to eradicate the malignancy. See, Ma et al., 2018, "Pan-cancer genome and transcriptome analyses of 1,699pediatric leukemias and solid tumors". In some cases, single-cell genomics protocols are used to detect combinations of somatic genetic variants in a single cancer cell or clonal type within a mixture of normal and malignant cells isolated from a patient sample. In some cases, this technique is also used to identify clonotypes that have undergone positive selection following exposure to a drug in vitro and / or in vivo in patients. Fig. 6AAs shown, by comparing the surviving clones exposed to chemotherapy with the clones identified at diagnosis, a catalog of cancer clonal types can be created that records their resistance to specific drugs. In some cases, the PTA method detects the sensitivity of specific clones in a sample composed of multiple clonal types to existing drugs or new drugs and their combinations, wherein the method can detect the sensitivity of specific clones to drugs. In some cases, this method shows the efficacy of drugs on specific clones, while current drug sensitivity measurements take into account the sensitivity of all cancer clones in one measurement, so this efficacy may not be detected. When the PTA described herein is applied to patient samples collected at diagnosis to detect cancer clonal types in a given patient's cancer, the drug sensitivity catalog can then be used to find these clones, thereby informing oncologists which drugs or drug combinations are ineffective and which drugs or drug combinations are most likely to be effective for the patient's cancer. PTA can be used to analyze samples containing cell populations. In some cases, the sample contains neurons or glial cells. In some cases, the sample includes a nucleus.

[0123] Clinical and environmental mutagenesis

[0124] The method for measuring the mutagenicity of environmental factors is described herein.For example, cells (single cells or cell colonies) are exposed to potential environmental conditions.For example, in some cases, the method uses cells such as those derived from organs (liver, pancreas, lungs, colon, thyroid or other organs), tissues (skin or other tissues), blood or other biological sources.In some cases, environmental conditions include heat, light (for example, ultraviolet rays), radiation, chemicals or any combination thereof.In some cases, after a certain amount of environmental conditions are exposed, this is a few minutes, a few hours, a few days or longer, a single cell is isolated and the PTA method is performed.In some cases, molecular barcodes and unique molecular identifiers are used to mark samples.Samples are sequenced and then analyzed to identify the mutations caused by exposure to environmental conditions.In some cases, this mutation is compared with control environmental conditions such as known non-mutagenic substances, vehicles / solvents or lack of environmental conditions.In some cases, this analysis not only provides the total number of mutations caused by environmental conditions, but also provides the position and properties of this mutation.In some cases, pattern is identified from data, and can be used to diagnose diseases or conditions.In some cases, pattern can be used to predict future disease states or conditions. In some cases, the method described herein measures the mutation load, position and pattern of cells after exposure to environmental agents, for example, potential mutagens or teratogens. In some cases, the method is used to assess the safety of a given agent, including the possibility of inducing mutations that may lead to disease development. For example, the method can be used to predict the carcinogenicity or teratogenicity of the agent to a specific cell type after being exposed to a specific agent of a specific concentration. In some cases, the agent is a medicine or drug. In some cases, the agent is food. In some cases, the agent is genetically modified food. In some cases, the agent is a pesticide or other agricultural chemicals. In some cases, the position and frequency of mutations are used to predict the age of an organism. In some cases, this method is carried out on samples hundreds of years, thousands of years or tens of thousands of years ago. In some cases, mutation patterns are compared with other data methods (such as carbon dating) to generate a standard curve. In some cases, the age of mankind is determined by comparing the number and pattern of mutations in the sample.

[0125] Described herein are methods for determining mutations in cells for use in cell therapy, such as, but not limited to, transplantation of induced pluripotent stem cells, transplantation of hematopoietic or other cells that have not been manipulated, or transplantation of hematopoietic or other cells that have undergone genome editing. The cells can then undergo PTA and sequencing to determine the mutational load and combination of mutations per cell. The per-cell mutation rate and mutation location in a cell therapy product can be used to assess the safety and potential efficacy of a product that includes a measure of neoantigen load.

[0126] Microbiological samples

[0127] The method for analyzing microbial samples is described herein. In another embodiment, microbial cells (e.g., bacteria, fungi, protozoa) can be separated from plants or animals (e.g., microbial population samples [e.g., GI microbial population, skin microbial population, etc.] or body fluids, e.g., blood, bone marrow, urine, saliva, cerebrospinal fluid, pleural fluid, pericardial fluid, ascites or aqueous humor). In addition, microbial cells can be separated from indwelling medical devices, such as, but not limited to, intravenous catheters, urinary catheters, cerebrospinal shunts, prosthetic valves, artificial joints or endotracheal catheters. Then, cells can undergo PTA and sequencing to determine the identity of specific microorganisms, and detect the presence of microbial genetic variants of responses (or resistance) to specific antimicrobial agents. These data can be used for diagnosing specific infectious diseases and / or as a tool for predicting treatment responses. In some cases, the mutation of a single microbial cell is analyzed. In one embodiment, PTA is used to identify microorganisms with high industrial application value such as production of biofuels or environmental remediation (oil spill cleanup, CO2 sequestration / removal). In some cases, microbial samples are obtained from extreme environments such as deep sea vents, oceans, mines, streams, lakes, meteorites, glaciers or volcanoes. In some cases, microbial samples are included in "uncultured" microbial strains under laboratory standard conditions. In some cases, the sequencing of microbial samples prepared using PTA includes obtaining sequencing reads for assembling into overlapping groups. In some cases, obtaining no more than 100,000, 500,000, 1,000,000, 1,500,000, 2,000,000, 3,000,000, 5,000,000, 8,000,000 or 10,000,000 readings. In some cases, the analysis and identification of microbial samples includes comparing the assembled overlapping groups with known microbial genome reference sequences. In some cases, the largest assembly overlapping group is used for comparison with the reference sequence. In some cases, the reading of one or more genes mapped to human genome DNA is filtered. In some cases, if two readings (forward and backward) are all mapped to human genes, then filter. In some cases, if at least one reading (forward and backward) is mapped to human genes, then filter. In some cases, human genes are GRCh38. In some cases, an assembly-free identification method is used with PTA. In some cases, an assembly-free method, such as Kraken, is used. In some cases, the assembly-free method includes assigning reads to taxonomic groups based on k-mers using a reference database.

[0128] Fetal cells

[0129] The cell used for the PTA method can be a fetal cell, such as an embryonic cell. In some embodiments, PTA is used together with non-invasive preimplantation genetic testing (NIPGT). In another embodiment, cells can be isolated from blastomeres or embryonic cells produced by in vitro fertilization. Then, PTA (for example, nucleic acid in PTA amplified cells) and sequencing can be performed on cells to determine the load and combination of potential disease susceptibility genetic variants in each cell. The mutation spectrum of the cell can then be used to infer the genetic susceptibility of the blastomere to a specific disease before implantation. In some cases, the embryo in the culture sheds nucleic acid, which is used to assess the health status of the embryo by low-pass genome sequencing. In some cases, embryos are frozen-thawed. In some cases, nucleic acids are obtained from embryonic cell culture conditioned medium (BCCM), blastocyst cavity fluid (BF) or its combination. In some cases, the PTA analysis of fetal cells is used to detect chromosomal abnormalities, such as fetal aneuploidy. In some cases, PTA is used to detect diseases, such as Down syndrome or Patau syndrome. In some cases, the frozen embryonic cells are thawed and cultured for a period of time, and then nucleic acids are obtained for analysis (e.g., culture medium, BF or cell biopsy). In some cases, the embryonic cells are cultured for no more than 4, 6, 8, 12, 16, 24, 36, 48 hours or no more than 64 hours, and then nucleic acids are obtained for analysis.

[0130] mutation

[0131] In some cases, methods described herein (such as PTA) produce higher detection sensitivity and / or lower false positive rate for mutation detection.In some cases, mutation is the difference between analyzed sequence (for example, using method described herein) and reference sequence.In some cases, reference sequence is obtained from other individuals, organism colonies or other regions of the same genome of other organisms, same or similar species.In some cases, mutation is identified on plasmid or chromosome.In some cases, mutation is SNV (single nucleotide variation), SNP (single nucleotide polymorphism) or CNV (copy number variation or CNA / copy number aberration).In some cases, mutation is base substitution, insertion or deletion.In some cases, mutation is conversion, transversion, nonsense mutation, silent mutation, synonymous mutation or non-synonymous mutation, non-pathogenic mutation, missense mutation or frameshift mutation (deletion or insertion). In some cases, PTA produces higher detection sensitivity and / or lower false positive rate for mutation detection when compared to methods such as computer simulation prediction, ChIP-seq, GUIDE-seq, circle-seq, HTGTS (high-throughput whole-genome translocation sequencing), IDLV (integration-defective lentivirus), Digenome-seq, FISH (fluorescence in situ hybridization) or DISCOVER-seq.

[0132] Directed amplification of primary template

[0133] Nucleic acid amplification methods such as "primary template directed amplification (PTA)" are described herein. For example, Figure 1A-1H The PTA method described herein is schematically presented. In the PTA method, a polymerase (e.g., a strand displacement polymerase) is used to preferentially generate amplicons from a primary template ("direct copy"). Therefore, compared with MDA, in the subsequent amplification process, errors are propagated from the subamplicons at a lower rate. Thus, a method that is easy to perform is obtained, which is different from existing WGA schemes, and can amplify low input DNA (including the genome of a single cell) in an accurate and reproducible manner, and has high coverage and uniformity. In addition, the terminated amplification products can be directed connected after removing the terminator, allowing the cell barcode to be attached to the amplification primer, so that the products from all cells can be merged after performing parallel amplification reactions ( Figure 1F ). In some cases, it is not necessary to remove the terminator prior to amplification and / or adaptor ligation.

[0134] This article describes a method for amplification using a nucleic acid polymerase with strand displacement activity. In some cases, this polymerase has strand displacement activity and a low error rate. In some cases, this polymerase has strand displacement activity and proofreading exonuclease activity, such as 3'->5' proofreading activity. In some cases, nucleic acid polymerases are used in combination with other components, such as reversible or irreversible terminators, or other strand displacement factors. In some cases, polymerases have strand displacement activity but do not have exonuclease proofreading activity. For example, in some cases, these polymerases include bacteriophage phi29 (Φ29) polymerases, which also have very low error rates, which are the result of 3'->5' proofreading exonuclease activity (see, e.g., U.S. Patent Nos. 5,198,543 and 5,001,050). In some cases, non-limiting examples of strand-displacing nucleic acid polymerases include, for example, genetically modified phi29 (Φ29) DNA polymerase, Klenow fragment of DNA polymerase I (Jacobsen et al., Eur. J. Biochem. 45:623-627 (1974)), bacteriophage M2 DNA polymerase (Matsumoto et al., Gene 84:247 (1989)), bacteriophage phiPRD1 DNA polymerase (Jung et al., Proc. Natl. Acad. Sci. USA 84:8287 (1987); Zhu and Ito, Biochim. Biophys. Acta. 1219:267-276 (1994)), Bst DNA polymerases (e.g., Bst large fragment DNA polymerase (Exo(-)Bst; Aliotta et al., Genet. Anal. (Netherlands) 12:185-195 (1996)), exo(-)Bca DNA polymerase (Walker and Linn, Clinical Chemistry 42:1604-1608 (1996)), Bsu DNA polymerase, including Vent R Vent of (exo-)DNA polymerase RDNA polymerase (Kong et al., J. Biol. Chem. 268: 1965-1975 (1993)), Deep Vent DNA polymerase including Deep Vent (exo-) DNA polymerase, IsoPol DNA polymerase, DNA polymerase I, Therminator DNA polymerase, T5 DNA polymerase (Chatterjee et al., Gene 97: 13-19 (1991)), Sequenase (US. Biochemicals), T7 DNA polymerase, T7-Sequenase, T7 gp5 DNA polymerase, PRDI DNA polymerase, T4 DNA polymerase (Kaboord and Benkovic, Curr. Biol. 5: 149-157 (1995)). Additional strand displacement nucleic acid polymerases are also compatible with the methods described herein. The ability of a given polymerase to perform strand displacement replication can be determined, for example, by using the polymerase in a strand displacement replication assay (e.g., as disclosed in U.S. Pat. No. 6,977,148). In some cases, these assays are performed at a temperature suitable for the optimal activity of the enzyme used, for example, 32°C for phi29 DNA polymerase, 46°C to 64°C for exo(-)Bst DNA polymerase, or about 60°C to 70°C for enzymes from hyperthermogenic organisms. Another useful assay for selecting polymerases is the primer blocking assay described in Kong et al., J. Biol. Chem. 268: 1965-1975 (1993). The assay includes a primer extension assay using an M13 ssDNA template in the presence or absence of an oligonucleotide that hybridizes upstream of the extension primer to block its progress. In this assay, other enzymes that can displace the blocking primer are useful for the disclosed method in some cases. In some cases, the polymerase incorporates dNTPs and terminators at approximately equal ratios. In some cases, the polymerases described herein incorporate dNTPs and terminators at a ratio of about 1: 1, about 1.5: 1, about 2: 1, about 3: 1, about 4: 1, about 5: 1, about 10: 1, about 20: 1, about 50: 1, about 100: 1, about 200: 1, about 500: 1, or about 1000: 1. In some cases, the polymerases described herein incorporate dNTPs and terminators at a ratio of 1: 1 to 1000: 1, 2: 1 to 500: 1, 5: 1 to 100: 1, 10: 1 to 1000: 1, 100: 1 to 1000: 1, 500: 1 to 2000: 1, 50: 1 to 1500: 1, or 25: 1 to 1000: 1.

[0135] Amplification methods are described herein, wherein chain displacement can be promoted by using a chain displacement factor such as a helicase. In some cases, these factors are used in combination with other amplification components, such as polymerase, terminator or other components. In some cases, the chain displacement factor is used together with a polymerase that does not have chain displacement activity. In some cases, the chain displacement factor is used together with a polymerase with chain displacement activity. Not subject to theoretical constraints, the chain displacement factor can increase the speed at which less double-stranded amplicon is triggered. In some cases, any DNA polymerase that can carry out chain displacement replication in the presence of a chain displacement factor is suitable for the PTA method, even if the DNA polymerase cannot carry out chain displacement replication in the absence of this factor. In some cases, strand displacement factors that can be used for strand displacement replication include, but are not limited to, BMRF1 polymerase auxiliary subunit (Tsurumi et al., J. Virology 67(12):7648-7653 (1993)); adenovirus DNA binding protein (Zijderveld and van der Vliet, J. Virology 68(2):1158-1164 (1994)); herpes simplex virus protein ICP8 (Boehmer and Lehman, J. Virology 67(2):711-715 (1993); Skaliter and Lehman, Proc. Natl. Acad. Sci. USA 91(22):10665-10669 (1994)); single-stranded DNA binding protein (SSB; Rigler and Romano, J. Biol. Chem. 270:8910-8919 (1995)); bacteriophage T4 gene 32 protein (Villemain and Giedroc, Biochemistry 35:14395-14404 (1996); T7 helicase-primase; T7gp2.5 SSB protein; Tte-UvrD (from Thermoanaerobacter tengcongensis); calf thymus helicase (Siegel et al., J.Biol.Chem.267:13629-13635 (1992)); bacterial SSB (e.g., E. coli SSB); replication protein A (RPA) in eukaryotes; human mitochondrial SSB (mtSSB) and recombinases (e.g., recombinase A (RecA) family proteins, T4 UvsX, Sak4 of bacteriophage HK620, Rad51, Dmc1 or Radb). Combinations of factors that promote strand displacement and initiation are also consistent with the methods described herein. For example, a helicase is used in combination with a polymerase.In some cases, the PTA method includes the use of a single-stranded DNA binding protein (SSB, T4 gp32 or other single-stranded DNA binding protein), a helicase and a polymerase (e.g., SauDNA polymerase, Bsu polymerase, Bst2.0, GspM, GspM2.0, GspSSD or other suitable polymerases). In some cases, a reverse transcriptase is used in combination with a strand displacement factor as described herein. In some cases, a polymerase and a nicking enzyme (such as "NEAR"), such as those described in US 9,617,586, are used for amplification. In some cases, the nicking enzyme is Nt.BspQI, Nb.BbvCi, Nb.BsmI, Nb.BsrDI, Nb.BtsI, Nt.AlwI, Nt.BbvCI, Nt.BstNBI, Nt.CviPII, Nb.BpulOI or Nt.BpulOI.

[0136] Amplification methods are described herein, which include the use of terminator nucleotides, polymerases and other factors or conditions. For example, in some cases, these factors are used to fragment nucleic acid templates or amplicons during amplification. In some cases, these factors include endonucleases. In some cases, factors include transposases. In some cases, mechanical shearing is used to fragment nucleic acids during amplification. In some cases, nucleotides are added during amplification, and fragmentation can be achieved by adding other proteins or conditions. For example, uracil is incorporated into the amplicon; nucleic acids are fragmented at uracil-containing positions by treatment with uracil D-glycosylase. In some cases, other systems of selective nucleic acid fragmentation are also used, for example, engineered DNA glycosylases (Kwon et al. Chem Biol. 2003, 10 (4), 351) that cut modified cytosine-pyrene base pairs.

[0137] Amplification methods including the use of terminator nucleotides are described herein, which terminate nucleic acid replication, thereby reducing the size of the amplified product. In some cases, these terminators are used in combination with polymerases, strand displacement factors or other amplification components as described herein. In some cases, terminator nucleotides reduce or reduce the efficiency of nucleic acid replication. In some cases, these terminators reduce the elongation rate by at least 99.9%, 99%, 98%, 95%, 90%, 85%, 80%, 75%, 70% or at least 65%. In some cases, these terminators reduce the elongation rate by 50%-90%, 60%-80%, 65%-90%, 70%-85%, 60%-90%, 70%-99%, 80%-99% or 50%-80%. In some cases, terminators reduce the average amplicon product length by at least 99.9%, 99%, 98%, 95%, 90%, 85%, 80%, 75%, 70% or at least 65%. In some cases, the terminator reduces the average amplicon length by 50%-90%, 60%-80%, 65%-90%, 70%-85%, 60%-90%, 70%-99%, 80%-99%, or 50%-80%. In some cases, amplicons that include terminator nucleotides form loops or hairpins, thereby reducing the ability of polymerases to use these amplicons as templates. In some cases, the use of terminators slows the rate of amplification at the initial amplification site by incorporating terminator nucleotides (e.g., dideoxynucleotides that have been modified to make them resistant to exonucleases and thereby terminate DNA extension), thereby generating smaller amplification products. By producing smaller amplification products than currently used methods (e.g., the average length of the PTA method is 50-2000 nucleotides, while the average product length of the MDA method is >10,000 nucleotides), in some cases PTA amplification products can be directly ligated to adapters without fragmentation, thereby allowing efficient incorporation of cellular barcodes and unique molecular identifiers (UMIs) (see Figure 1H , Figure 2B-Figure 3E , Fig. 9 , Fig. 10A and Fig. 10B ).

[0138] In some cases, the terminator nucleotides are present in various concentrations, depending on factors such as polymerase, template or other factors. For example, in some cases, in the methods described herein, the amount of terminator nucleotides is expressed as the ratio of non-terminator nucleotides to terminator nucleotides. In some cases, these concentrations allow the length of the control amplicon. In some cases, the ratio of terminator nucleotides to non-terminator nucleotides changes according to the amount of template present or the size of template. In some cases, for a smaller sample size, the ratio of terminator nucleotides to non-terminator nucleotides can be reduced (for example, femtograms to picograms of the range). In some cases, the ratio of non-terminator nucleotides to terminator nucleotides is about 2:1, 5:1, 7:1, 10:1, 20:1, 50:1, 100:1, 200:1, 500:1, 1000:1, 2000:1 or 5000:1. In some cases, the ratio of non-terminator nucleotides to terminator nucleotides is 2: 1-10: 1, 5: 1-20: 1, 10: 1-100: 1, 20: 1-200: 1, 50: 1-1000: 1, 50: 1-500: 1, 75: 1-150: 1 or 100: 1-500: 1. In some cases, at least one nucleotide present during amplification using the methods described herein is a terminator nucleotide. Each terminator does not have to be present at about the same concentration; in some cases, the ratio of various terminators present in the methods described herein can be optimized for a particular set of reaction conditions, sample types or polymerases. Without being bound by theory, each terminator can be incorporated into the growing polynucleotide chain of the amplicon in response to pairing with the corresponding nucleotide on the template strand. For example, in some cases, the concentration of terminators paired with cytosine is about 3%, 5%, 10%, 15%, 20%, 25% or 50% higher than the average terminator concentration. In some cases, the concentration of the terminator paired with thymine is about 3%, 5%, 10%, 15%, 20%, 25% or 50% higher than the average terminator concentration. In some cases, the concentration of the terminator paired with guanine is about 3%, 5%, 10%, 15%, 20%, 25% or 50% higher than the average terminator concentration. In some cases, the concentration of the terminator paired with adenine is about 3%, 5%, 10%, 15%, 20%, 25% or 50% higher than the average terminator concentration. In some cases, the concentration of the terminator paired with uracil is about 3%, 5%, 10%, 15%, 20%, 25% or 50% higher than the average terminator concentration. In some cases, any nucleotide that can terminate the nucleic acid extension by nucleic acid polymerase is used as a terminator nucleotide in the method described herein. In some cases, reversible terminators are used to terminate nucleic acid replication. In some cases, irreversible terminators are used to terminate nucleic acid replication.In some cases, the non-limiting examples of terminators include reversible and irreversible nucleic acids and nucleic acid analogs, for example, including 3' sealed reversible terminators of nucleotides, including 3' unsealed reversible terminators of nucleotides, including 2' modified terminators of deoxynucleotides, including terminators of the modification of the nitrogenous bases of deoxynucleotides or any combination thereof. In one embodiment, terminator nucleotides are dideoxynucleotides. Nucleic acid replication is terminated and other nucleotide modifications applicable to the implementation of the present invention include but are not limited to any modification of the r group of the 3' carbon of deoxyribose, such as reverse dideoxynucleotides, 3' biotinylated nucleotides, 3' aminonucleotides, 3'-phosphorylated nucleotides, 3'-O-methyl nucleotides, including 3'C3 spacer nucleotides, 3'C18 nucleotides, 3' hexanediol spacer nucleotides 3' carbon spacer nucleotides, acyclic nucleotides, and combinations thereof. In some cases, terminators are polynucleotides with a length of 1, 2, 3, 4 or more bases. In some cases, terminators do not include detectable parts or labels (for example, mass labels, fluorescent labels, dyes, radioactive atoms or other detectable parts). In some cases, the terminator does not include a chemical moiety that allows the attachment of a detectable portion or a tag (e.g., a "click" azide / alkyne, a conjugate addition agent, or other chemical treatment for tag attachment). In some cases, all terminator nucleotides include the same modification that reduces amplification at a certain region of the nucleotide (e.g., a sugar moiety, a base moiety, or a phosphate moiety). In some cases, at least one terminator has a different modification that reduces amplification. In some cases, all terminators have substantially similar fluorescence excitation or emission wavelengths. In some cases, terminators with unmodified phosphate groups are used with polymerases that do not have exonuclease proofreading activity. When terminators are used with polymerases (e.g., phi29) that have 3'->5' proofreading exonuclease activity that can remove terminator nucleotides, in some cases, further modification is required to make them resistant to exonucleases. For example, dideoxynucleotides are modified by α-sulfhydryl groups to produce phosphorothioate bonds, making these nucleotides resistant to the 3'->5' proofreading exonuclease activity of nucleic acid polymerases. In some cases, the modification reduces the exonuclease proofreading activity of the polymerase by at least 99.5%, 99%, 98%, 95%, 90%, or at least 85%.In some cases, non-limiting examples of other terminator nucleotide modifications that provide resistance to 3'->5' exonuclease activity include: nucleotides with modifications to the alpha group, such as alpha-thiodideoxynucleotides that produce phosphorothioate bonds, C3 spacer nucleotides, locked nucleic acids (LNA), inverted nucleic acids, 2'fluoro bases, 3' phosphorylation, 2'-O-methyl modifications (or other 2'-O-alkyl modifications), propyne-modified bases (e.g., deoxycytosine, deoxyuridine), L-DNA nucleotides, L-RNA nucleotides, nucleotides with inverted linkages (e.g., 5'-5' or 3'-3'), 5' inverted bases (e.g., 5' inverted 2',3'-dideoxy dT), methylphosphonate backbones, and trans nucleic acids. In some cases, nucleotides with modifications include base-modified nucleic acids with free 3'OH groups (e.g., 2-nitrobenzyl alkylated HOMedU triphosphates, bases with large chemical group modifications such as solid supports or other larger moieties). In some cases, a polymerase having strand displacement activity but not 3'->5' exonuclease proofreading activity is used with a terminator nucleotide that has or has not undergone modification to render it resistant to exonucleases. These nucleic acid polymerases include, but are not limited to, Bst DNA polymerase, Bsu DNA polymerase, Deep Vent (exo-) DNA polymerase, Klenow fragment (exo-) DNA polymerase, Therminator DNA polymerase, and Vent. R (exo-).

[0139] Primers and Amplicon Libraries

[0140] Amplicon libraries produced by the amplification of at least one target nucleic acid molecule are described herein. In some cases, these libraries are generated using methods described herein, such as libraries using terminators. These methods include using strand displacement polymerases or factors, terminator nucleotides (reversible or irreversible) or other features and embodiments described herein. In some cases, the amplicon libraries produced using terminators described herein are further amplified in subsequent amplification reactions (e.g., PCR). In some cases, subsequent amplification reactions do not include terminators. In some cases, the amplicon libraries include polynucleotides, wherein at least 50%, 60%, 70%, 80%, 90%, 95% or at least 98% of the polynucleotides include at least one terminator nucleotide. In some cases, the amplicon libraries include target nucleic acid molecules derived from the amplicon libraries. The amplicon libraries include a variety of polynucleotides, wherein at least some of the polynucleotides are direct copies (e.g., directly from target nucleic acid molecules such as genomic DNA, RNA or other target nucleic acid copies). For example, at least 5%, 10%, 20%, 30%, 40%, 50%, 60%, 70%, 80%, 90%, 95% or more than 95% of the amplicon polynucleotides are direct copies of at least one target nucleic acid molecule. In some cases, at least 5% of the amplicon polynucleotides are direct copies of at least one target nucleic acid molecule. In some cases, at least 10% of the amplicon polynucleotides are direct copies of at least one target nucleic acid molecule. In some cases, at least 15% of the amplicon polynucleotides are direct copies of at least one target nucleic acid molecule. In some cases, at least 20% of the amplicon polynucleotides are direct copies of at least one target nucleic acid molecule. In some cases, at least 50% of the amplicon polynucleotides are direct copies of at least one target nucleic acid molecule. In some cases, 3%-5%, 3-10%, 5%-10%, 10%-20%, 20%-30%, 30%-40%, 5%-30%, 10%-50% or 15%-75% of the amplicon polynucleotides are direct copies of at least one target nucleic acid molecule. In some cases, at least some polynucleotides are direct copies or progeny (first copy of target nucleic acid) of target nucleic acid molecules. For example, at least 5%, 10%, 20%, 30%, 40%, 50%, 60%, 70%, 80%, 90%, 95% or more than 95% of the amplicon polynucleotides are direct copies or progeny of at least one target nucleic acid molecule. In some cases, at least 5% of the amplicon polynucleotides are direct copies or progeny of at least one target nucleic acid molecule. In some cases, at least 10% of the amplicon polynucleotides are direct copies or progeny of at least one target nucleic acid molecule. In some cases, at least 20% of the amplicon polynucleotides are direct copies or progeny of at least one target nucleic acid molecule. In some cases, at least 30% of the amplicon polynucleotides are direct copies or progeny of at least one target nucleic acid molecule.In some cases, 3%-5%, 3%-10%, 5%-10%, 10%-20%, 20%-30%, 30%-40%, 5%-30%, 10%-50% or 15%-75% of the amplicon polynucleotides are direct copies or progeny of at least one target nucleic acid molecule. In some cases, the length of the direct copy of the target nucleic acid is 50-2500, 75-2000, 50-2000, 25-1000, 50-1000, 500-2000 or 50-2000 bases. In some cases, the length of the progeny is 1000-5000, 2000-5000, 1000-10,000, 2000-5000, 1500-5000, 3000-7000 or 2000-7000 bases. In some cases, the average length of the PTA amplified product is 25-3000 nucleotides, 50-2500, 75-2000, 50-2000, 25-1000, 50-1000, 500-2000 or 50-2000 bases. In some cases, the length of the amplicon produced from PTA is no more than 5000, 4000, 3000, 2000, 1700, 1500, 1200, 1000, 700, 500 or no more than 300 bases. In some cases, the length of the amplicon produced from PTA is 1000-5000, 1000-3000, 200-2000, 200-4000, 500-2000, 750-2500 or 1000-2000 bases. In some cases, the amplicon library produced using the methods described herein includes at least 1000, 2000, 5000, 10,000, 100,000, 200,000, 500,000 or more than 500,000 amplicons including unique sequences. In some cases, the library includes at least 100, 200, 300, 400, 500, 600, 700, 800, 900, 1000, 1100, 1200, 1300, 1400, 1500, 2000, 2500, 3000 or at least 3500 amplicons. In some cases, at least 5%, 10%, 15%, 20%, 25%, 30% or more than 30% of the amplicon polynucleotides less than 1000 bases in length are direct copies of at least one target nucleic acid molecule. In some cases, at least 5%, 10%, 15%, 20%, 25%, 30%, or more than 30% of the amplicon polynucleotides of no more than 2000 bases in length are direct copies of at least one target nucleic acid molecule. In some cases, at least 5%, 10%, 15%, 20%, 25%, 30%, or more than 30% of the amplicon polynucleotides of 3000-5000 bases in length are direct copies of at least one target nucleic acid molecule.In some cases, the ratio of direct copy amplicon to target nucleic acid molecule is at least 10: 1, 100: 1, 1000: 1, 10,000: 1, 100,000: 1, 1,000,000: 1, 10,000,000: 1, or greater than 10,000,000: 1. In some cases, the ratio of direct copy amplicon to target nucleic acid molecule is at least 10: 1, 100: 1, 1000: 1, 10,000: 1, 100,000: 1, 1,000,000: 1, 10,000,000: 1, or greater than 10,000,000: 1, wherein the direct copy amplicon is no more than 700-1200 bases in length. In some cases, the ratio of direct-copy amplicon and subamplifier to target nucleic acid molecule is at least 10: 1, 100: 1, 1000: 1, 10,000: 1, 100,000: 1, 1,000,000: 1, 10,000,000: 1, or greater than 10,000,000: 1. In some cases, the ratio of direct-copy amplicon and subamplifier to target nucleic acid molecule is at least 10: 1, 100: 1, 1000: 1, 10,000: 1, 100,000: 1, 1,000,000: 1, 10,000,000: 1, or greater than 10,000,000: 1, wherein the direct-copy amplicon is 700-1200 bases in length and the subamplifier is 2500-6000 bases in length. In some cases, the library includes about 50-10,000, about 50-5,000, about 50-2500, about 50-1000, about 150-2000, about 250-3000, about 50-2000, about 500-2000 or about 500-1500 amplicon, which are direct copies of target nucleic acid molecules. In some cases, the library includes about 50-10,000, about 50-5,000, about 50-2500, about 50-1000, about 150-2000, about 250-3000, about 50-2000, about 500-2000 or about 500-1500 amplicon, which are direct copies or sub-amplicons of target nucleic acid molecules. In some cases, the quantity of direct copy can be controlled by the number of times of pcr amplification circulation. In some cases, no more than 30, 25, 20, 15, 13, 11, 10, 9, 8, 7, 6, 5, 4, or 3 PCR cycles are used to generate copies of the target nucleic acid molecule. In some cases, about 30, 25, 20, 15, 13, 11, 10, 9, 8, 7, 6, 5, 4, or about 3 PCR cycles are used to generate copies of the target nucleic acid molecule. In some cases, 3, 4, 5, 6, 7, or 8 PCR cycles are used to generate copies of the target nucleic acid molecule.In some cases, 2-4, 2-5, 2-7, 2-8, 2-10, 2-15, 3-5, 3-10, 3-15, 4-10, 4-15, 5-10 or 5-15 PCR cycles are used to generate copies of the target nucleic acid molecule. In some cases, the amplicon library generated using the methods described herein is subjected to additional steps, such as adapter connection and further PCR amplification. In some cases, these additional steps are before the sequencing step.

[0141] In some cases, the amplicon library of polynucleotides generated by the PTA methods and compositions described herein (terminators, polymerases, etc.) has increased uniformity. In some cases, uniformity is measured using a Lorentz curve (e.g., Figure 5C) or other similar methods to describe. In some cases, this increase makes the sequencing required for covering the desired target nucleic acid molecule (for example, genomic DNA, RNA or other target nucleic acid molecules) read less. For example, no more than 50% of the cumulative score of the polynucleotide includes at least 80% of the sequence of the cumulative score of the sequence of the target nucleic acid molecule. In some cases, no more than 50% of the cumulative score of the polynucleotide includes at least 60% of the sequence of the cumulative score of the sequence of the target nucleic acid molecule. In some cases, no more than 50% of the cumulative score of the polynucleotide includes at least 70% of the sequence of the cumulative score of the sequence of the target nucleic acid molecule. In some cases, no more than 50% of the cumulative score of the polynucleotide includes at least 90% of the sequence of the cumulative score of the sequence of the target nucleic acid molecule. In some cases, uniformity is described using the Gini index (wherein index 0 represents the complete equality of the library, and index 1 represents completely unequal). In some cases, the Gini index of the amplicon library described herein is no more than 0.55, 0.50, 0.45, 0.40 or 0.30. In some cases, the Gini index of the amplicon library described herein does not exceed 0.50. In some cases, the Gini index of the amplicon library described herein does not exceed 0.40. In some cases, this uniformity metric depends on the number of reads obtained. For example, the read obtained does not exceed 100 million, 200 million, 300 million, 400 million or does not exceed 500 million. In some cases, the length of the read is about 50, 75, 100, 125, 150, 175, 200, 225 or about 250 bases. In some cases, the uniformity metric depends on the coverage depth of the target nucleic acid. For example, the average coverage depth is about 10X, 15X, 20X, 25X or about 30X. In some cases, the average coverage depth is 10-30X, 20-50X, 5-40X, 20-60X, 5-20X or 10-20X. In some cases, the Gini index of the amplicon library described herein does not exceed 0.55, wherein about 300 million reads are obtained. In some cases, the Gini index of the amplicon library described herein does not exceed 0.50, wherein about 300 million reads are obtained. In some cases, the Gini index of the amplicon library described herein does not exceed 0.45, wherein about 300 million reads are obtained. In some cases, the Gini index of the amplicon library described herein does not exceed 0.55, wherein no more than 300 million reads are obtained. In some cases, the Gini index of the amplicon library described herein does not exceed 0.50, wherein no more than 300 million reads are obtained. In some cases, the Gini index of the amplicon library described herein does not exceed 0.45, wherein no more than 300 million reads are obtained. In some cases, the Gini index of the amplicon library described herein does not exceed 0.55, wherein the average depth of sequencing coverage is about 15X. In some cases, the Gini index of the amplicon library described herein does not exceed 0.50, wherein the average depth of sequencing coverage is about 15X.In some cases, the Gini index of the amplicon library described herein is no more than 0.45, and the average depth of the sequencing coverage is about 15X. In some cases, the Gini index of the amplicon library described herein is no more than 0.55, and the average depth of the sequencing coverage is at least 15X. In some cases, the Gini index of the amplicon library described herein is no more than 0.50, and the average depth of the sequencing coverage is at least 15X. In some cases, the Gini index of the amplicon library described herein is no more than 0.45, and the average depth of the sequencing coverage is at least 15X. In some cases, the Gini index of the amplicon library described herein is no more than 0.55, and the average depth of the sequencing coverage is no more than 15X. In some cases, the Gini index of the amplicon library described herein is no more than 0.50, and the average depth of the sequencing coverage is no more than 15X. In some cases, the Gini index of the amplicon library described herein is no more than 0.45, and the average depth of the sequencing coverage is no more than 15X. In some cases, the uniform amplicon library generated using the method described herein needs to be subjected to additional steps, such as adapter connection and further PCR amplification. In some cases, these additional steps precede the sequencing step.

[0142] Primers include nucleic acids for initiating amplification reactions as described herein. In some cases, these primers include, but are not limited to, random deoxynucleotides of any length with or without modification that makes it resistant to exonucleases, random ribonucleotides of any length with or without modification that makes it resistant to exonucleases, modified nucleic acids, such as locked nucleic acids, DNA or RNA primers targeting specific genomic regions, and reactions initiated by enzymes such as initiators. In the case of whole genome PTA, a group of primers with random or partially random nucleotide sequences are preferably used. In very complex nucleic acid samples, it is not necessary to know the specific nucleic acid sequence present in the sample, and it is not necessary to design primers to be complementary to any particular sequence. On the contrary, the complexity of nucleic acid samples results in a large number of different hybridization target sequences in the sample, which will be complementary to various primers of random or partially random sequences. In some cases, the complementary portion of the primer used for PTA is completely random, only includes a random portion, or is selectively random. In some cases, for example, the number of random base positions in the complementary portion of the primer is 20% to 100% of the total number of nucleotides in the complementary portion of the primer. In some cases, the number of random base positions in the complementary part of primers is 10% to 90%, 15-95%, 20%-100%, 30%-100%, 50%-100%, 75-100% or 90-95% of the total number of nucleotides in the complementary part of primers. In some cases, the number of random base positions in the complementary part of primers is at least 10%, 20%, 30%, 40%, 50%, 60%, 70%, 80% or at least 90% of the total number of nucleotides in the complementary part of primers. In some cases, the primer sets with random or partially random sequences are synthesized using standard techniques, which is by allowing any nucleotide to be randomly added at each position. In some cases, primer sets are composed of primers with similar length and / or hybridization properties. In some cases, the term "random primers" refers to primers that can show 4 times of degeneracy at each position. In some cases, the term "random primers" refers to primers that can show 3 times of degeneracy at each position. In some cases, the random primers used in the methods described herein include random sequences of 3, 4, 5, 6, 7, 8, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20 or more bases in length. In some cases, primers include random sequences of 3-20, 5-15, 5-20, 6-12 or 4-10 bases in length. Primers may also include non-extendable elements that limit the subsequent amplification of the amplicon generated. For example, in some cases, primers with non-extendable elements include terminators. In some cases, primers include terminator nucleotides, such as 1, 2, 3, 4, 5, 10 or more than 10 terminator nucleotides. Primers do not need to be limited to components added to amplified reactions from the outside. In some cases, primers are generated in situ by adding nucleotides and proteins that promote initiation.In some cases, the enzyme similar to the priming enzyme combined with nucleotide is used to generate the random primers of the methods described herein. In some cases, the enzyme similar to the priming enzyme is a member of the DnaG or AEP enzyme superfamily. In some cases, the enzyme similar to the priming enzyme is TthPrimPol. In some cases, the enzyme similar to the priming enzyme is T7 gp4 helicase-priming enzyme. In some cases, these priming enzymes are used together with polymerases as described herein or strand displacement factors. In some cases, the priming enzyme starts to initiate with deoxyribonucleotides. In some cases, the priming enzyme starts to initiate with ribonucleotides.

[0143] After PTA amplification, a specific subset of amplicon can be selected. In some cases, this selection depends on size, affinity, activity, hybridization with probe or other known selection factors in the art. In some cases, selection is performed before or after additional steps as described herein such as adapter connection and / or library amplification. In some cases, selection is based on the size (length) of amplicon. In some cases, select a smaller amplicon, which is unlikely to experience exponential amplification, thereby enriching the product derived from the primary template, while further converting amplification from an exponential form into a quasi-linear amplification process ( Figure 1A). In some cases, the amplicon of 50-2000, 25-5000, 40-3000, 50-1000, 200-1000, 300-1000, 400-1000, 400-600, 600-2000 or 800-1000 bases is selected in length. In some cases, size selection is performed by using a scheme such as using solid phase reversible immobilization (SPRI) on carboxylated paramagnetic beads to enrich for nucleic acid fragments of a specific size or other schemes known to those skilled in the art. Optionally or in combination, selection is performed by preferentially connecting and amplifying smaller fragments during PCR when preparing a sequencing library and preferentially forming clusters of smaller sequencing library fragments during sequencing (such as synthetic sequencing, nanopore sequencing or other sequencing methods). Other strategies for selecting smaller fragments also conform to the methods described herein, and include but are not limited to separating nucleic acid fragments of a specific size after gel electrophoresis, using silica gel columns for nucleic acid fragments of a specific size, and using other PCR strategies for more strongly enriching smaller fragments. Any number of library preparation schemes can be used together with PTA method as described herein.In some cases, the amplicon generated by PTA is connected to an adapter (optionally removing terminator nucleotides).In some cases, the amplicon generated by PTA includes homology regions generated by fragmentation based on transposase, and these regions are used as priming sites.In some cases, the library is prepared by mechanical or enzymatic means that nucleic acid is fragmented.In some cases, the library is prepared by the fragmentation of transposase.In some cases, the library is prepared by the fragmentation of transposase.In some cases, the library is prepared by connecting an adapter, such as Y-adapter, universal adapter or circular adapter.

[0144] The non-complementary portion of the primer used in PTA can include a sequence that can be used to further manipulate and / or analyze the amplified sequence. An example of such a sequence is a "detection tag". The detection tag has a sequence that is complementary to the detection probe and is detected using its cognate detection probe. There can be one, two, three, four or more than four detection tags on the primer. Except for the size of the primer, there is no basic limit to the number of detection tags that may be present on the primer. In some cases, there is only one detection tag on the primer. In some cases, there are two detection tags on the primer. When there are multiple detection tags, they can have the same sequence or different sequences, each different sequence being complementary to a different detection probe. In some cases, multiple detection tags have the same sequence. In some cases, multiple detection tags have different sequences.

[0145] Another example of a sequence that can be included in the non-complementary portion of a primer is an "address tag," which can encode other details of the amplicon, such as the location in a tissue section. In some cases, the cell barcode contains an address tag. The address tag has a sequence that is complementary to the address probe. The address tag is incorporated into the end of the amplified chain. If present, there can be one or more address tags on the primer. There is no basic limit to the number of address tags that may be present on the primer, except for the size of the primer. When there are multiple address tags, they can have the same sequence or different sequences, each of which is complementary to a different address probe. The address tag portion can be any length that supports specific and stable hybridization between the address tag and the address probe. In some cases, nucleic acids from more than one source can be incorporated into a variable tag sequence. The length of the tag sequence can be up to 100 nucleotides, preferably 1 to 10 nucleotides in length, most preferably 4, 5 or 6 nucleotides, and includes a combination of nucleotides. In some cases, the length of the tag sequence is 1-20, 2-15, 3-13, 4-12, 5-12 or 1-10 nucleotides. For example, if six base pairs are chosen to form the tag and arrangements of four different nucleotides are used, a total of 4096 nucleic acid anchors (eg, hairpins) can be made, each with a unique 6-base tag.

[0146] The primers described herein may be present in solution or immobilized on a solid support. In some cases, primers with sample barcodes and / or UMI sequences may be immobilized on a solid support. For example, the solid support may be one or more beads. In some cases, individual cells are contacted with one or more beads having a set of unique sample barcodes and / or UMI sequences to identify individual cells. In some cases, lysates from individual cells are contacted with one or more beads having a set of unique sample barcodes and / or UMI sequences to identify individual cell lysates. In some cases, extracted nucleic acids from individual cells are contacted with one or more beads having a set of unique sample barcodes and / or UMI sequences to identify extracted nucleic acids from individual cells. The beads may be manipulated in any suitable manner known in the art, for example, using a droplet actuator as described herein. The beads may be of any suitable size, including, for example, microbeads, microparticles, nanobeads, and nanoparticles. In some embodiments, the beads are magnetically responsive; in other embodiments, the beads have no apparent magnetic response. Non-limiting examples of suitable beads include flow cytometry microbeads, polystyrene microparticles and nanoparticles, functionalized polystyrene microparticles and nanoparticles, coated polystyrene microparticles and nanoparticles, silica microbeads, fluorescent microspheres and nanospheres, functionalized fluorescent microspheres and nanospheres, coated fluorescent microspheres and nanospheres, color-dyed microspheres and nanoparticles, magnetic microspheres and nanoparticles, superparamagnetic microspheres and nanoparticles (e.g., ATCC®, available from Invitrogen Group, Carlsbad, CA). ), fluorescent microparticles and nanoparticles, coated magnetic microparticles and nanoparticles, ferromagnetic microparticles and nanoparticles, coated ferromagnetic microparticles and nanoparticles, and described in U.S. Patent Application Publication Nos. US20050260686, US20030132538, US20050118574, 20050277197, 20060159962. The beads may be pre-coupled with antibodies, proteins or antigens, DNA / RNA probes, or any other molecule with affinity for the desired target. In some embodiments, primers with sample barcodes and / or UMI sequences may be in solution. In certain embodiments, a plurality of droplets may be provided, wherein each droplet in the plurality of droplets has a sample barcode unique to the droplet and a UMI unique to the molecule, such that the UMI is repeated multiple times within a collection of droplets. In some embodiments, individual cells are contacted with droplets having a set of unique sample barcodes and / or UMI sequences to identify the individual cells. In some embodiments, a lysate from an individual cell is contacted with a droplet having a set of unique sample barcodes and / or UMI sequences to identify the individual cell lysate. In some embodiments, an extracted nucleic acid from an individual cell is contacted with a droplet having a set of unique sample barcodes and / or UMI sequences to identify the nucleic acid extracted from the individual cell. Various microfluidic platforms can be used to analyze single cells. In some cases, cells are manipulated by fluid dynamics (droplet microfluidics, inertial microfluidics, vortex flow, microvalves, microstructures (e.g., microwells, microtraps)), electrical methods (dielectrophoresis (DEP), electroosmosis), optical methods (optical tweezers, light-induced dielectrophoresis (ODEP), photothermal capillary), acoustic methods, or magnetic methods. In some cases, the microfluidic platform comprises a microwell. In some cases, the microfluidic platform comprises a PDMS (polydimethylsiloxane)-based device.Non-limiting examples of single-cell analysis platforms compatible with the methods described herein include: ddSEQ single-cell isolator (Bio-Rad, Hercules, CA, USA and Illumina, San Diego, CA, USA); Chromium (10x Genomics, Pleasanton, CA, USA); Rhapsody single-cell analysis system (BD, Franklin Lakes, NJ, USA); Tapestri platform (MissionBio, San Francisco, CA, USA); Nadia Innovate (Dolomite Bio, Royston, UK); C1 and Polaris (Fluidigm, South San Francisco, CA, USA); ICELL8 single-cell system (Takara); MSND (Wafergen); Puncher platform (Vycap); CellRaft AIR system (CellMicrosystems); DEPArray NxT and DEPArray systems (Menarini Silicon Biosystems); AVISO CellCelector (ALS); InDrop system (1CellBio) and TrapTx (Celldom).

[0147] PTA primers may include sequence-specific or random primers, address tags, cell barcodes, and / or unique molecular identifiers (UMIs) (see, e.g., Fig. 10A (linear primer) and Fig. 10B In some cases, the primers include sequence-specific primers. In some cases, the primers include random primers. In some cases, the primers include cell barcodes. In some cases, the primers include sample barcodes. In some cases, the primers include unique molecular identifiers. In some cases, the primers include two or more cell barcodes. In some cases, the barcodes identify a unique sample source or a unique workflow. In some cases, the barcodes or UMIs are 5, 6, 7, 8, 9, 10, 11, 12, 15, 20, 25, 30, or more than 30 bases in length. In some cases, the primers include at least 1000, 10,000, 50,000, 100,000, 250,000, 500,000, 10 6 , 10 7 , 10 8 , 10 9 or at least 10 10In some cases, the primers include at least 8, 16, 96, or 384 unique barcodes or UMIs. In some cases, standard adapters are then ligated to the amplified products prior to sequencing; after sequencing, reads are assigned to specific cells based on the cell barcodes. Suitable adapters that can be used with the PTA method include, for example, the adapters available from Integrated DNA Technologies (IDT). Dual Index μMI adapters. UMIs are then used to group reads from each cell and reads with the same UMI are collapsed into common reads. Using cell barcodes allows all cells to be pooled before library preparation, as they can then be identified by their cell barcodes. In some cases, using UMIs to form common reads corrects for PCR bias, thereby improving copy number variation (CNV) detection ( Fig.11A and Fig. 11B ). In addition, sequencing errors can be corrected by requiring a fixed percentage of reads from the same molecule to have the same detected base change at each position. This approach has been used to improve CNV detection and correct sequencing errors in a large number of samples. In some cases, UMIs are used with the methods described herein, for example, U.S. Pat. No. 8,835,358 discloses a digital counting principle after attaching a random amplifiable barcode. Schmitt et al. and Fan et al. (see above) disclose similar methods for correcting sequencing errors.

[0148] The methods described herein may also include additional steps, including steps performed on the sample or template. In some cases, these samples or templates are subjected to one or more steps before PTA. In some cases, a pretreatment step is performed on the sample including cells. For example, a combination of freeze-thaw, Triton X-100, Tween 20 and proteinase K is used to lyse and proteolyse the cells to increase the accessibility of chromatin. Other lysis strategies are also applicable to the implementation of the methods described herein. These strategies include, but are not limited to, the use of detergents and / or lysozyme and / or protease treatments, and / or other combinations of cell physical destruction such as ultrasound and / or alkaline lysis and / or hypotonic lysis for lysis. In some cases, cells are lysed mechanically (e.g., high pressure homogenizer, bead milling) or non-mechanically (physical method, chemical method or biological method). In some cases, physical lysis methods include heating, osmotic pressure shock and / or cavitation. In some cases, chemical lysis includes alkali and / or detergent. In some cases, biological lysis includes the use of enzymes. The combination of lysis methods is also compatible with the methods described herein. The non-limiting examples of lysing enzymes include recombinant lysozymes, serine proteases and bacterial lysins. In some cases, lysing with enzymes includes using lysozymes, lysostaphin, digestive enzymes, cellulases, proteases or polysaccharidases. In some cases, pretreatment steps are performed on the primary template or target molecule. In some cases, sodium hydroxide is used to denature the primary template (or target), and then the solution is neutralized. Other denaturation strategies may also be applicable to the implementation of the methods described herein. These strategies may include but are not limited to combining alkaline lysis with other alkaline solutions, increasing the sample temperature and / or changing the salt concentration in the sample, adding additives such as solvents or oils, other modifications or any combination thereof. In some cases, additional steps include sorting, filtering or separating samples, templates or amplicons by size. For example, after amplification using the methods described herein, the amplicon library is enriched with amplicons of desired length. In some cases, the amplicon library is enriched in amplicons of 50-2000, 25-1000, 50-1000, 75-2000, 100-3000, 150-500, 75-250, 170-500, 100-500, or 75-2000 bases in length. In some cases, the amplicon library is enriched in amplicons of no more than 75, 100, 150, 200, 500, 750, 1000, 2000, 5000, or no more than 10,000 bases in length. In some cases, the amplicon library is enriched in amplicons of at least 25, 50, 75, 100, 150, 200, 500, 750, 1000, or at least 2000 bases in length.

[0149] The methods and compositions described herein may include buffers or other preparations. In some cases, these buffers include surfactants / detergents or denaturants (Tween-20, DMSO, DMF, PEGylated polymers including hydrophobic groups or other surfactants), salts (potassium phosphate or sodium phosphate (mono or dibasic), sodium chloride, potassium chloride), TrisHCl, magnesium chloride or magnesium sulfate, ammonium salts such as phosphates, nitrates or sulfates, EDTA), reducing agents (DTT, THP, DTE, β-mercaptoethanol, TCEP or other reducing agents) or other components (glycerol, hydrophilic polymers such as PEG). In some cases, buffers are used in combination with components such as polymerases, chain displacement factors, terminators or other reaction components described herein. Buffers may include one or more crowding agents. In some cases, crowding agents include polymers. In some cases, crowding agents include polymers, such as polyols. In some cases, crowding agents include polyethylene glycol polymers (PEG). In some cases, crowding agents include polysaccharides. Examples of crowding agents include, but are not limited to, ficoll (e.g., ficoll PM 400, ficoll PM 70, or ficoll of other molecular weights), PEG (e.g., PEG1000, PEG2000, PEG4000, PEG6000, PEG8000, or PEG of other molecular weights), dextran (dextran 6, dextran 10, dextran 40, dextran 70, dextran 6000, dextran 138k, or dextran of other molecular weights).

[0150] Nucleic acid molecules amplified according to the methods described herein can be sequenced and analyzed using methods known to those skilled in the art. In some cases, non-limiting examples of sequencing methods used include, for example, hybridization sequencing (SBH), ligation sequencing (SBL) (Shendure et al. (2005) Science 309: 1728), quantitative incremental fluorescent nucleotide addition sequencing (QIFNAS), stepwise ligation and cleavage, fluorescence resonance energy transfer (FRET), molecular beacons, TaqMan reporter gene probe digestion, pyrophosphate sequencing, fluorescence in situ sequencing (FISSEQ), FISSEQ beads (U.S. Patent No. 7,425,431), wobble sequencing (International Patent Application Publication No. WO2006 / 073504), multiple sequencing (U.S. Patent Application Publication No. US2008 / 0269068; Porreca et al., 2007, Nat. Methods 4:931), polymerase clone (POLONY) sequencing (U.S. Pat. Nos. 6,432,360, 6,485,944 and 6,511,803, and International Patent Application Publication No. WO2005 / 082098), nanogrid rolling circle sequencing (ROLONY) (U.S. Pat. No. 9,624,538), allele-specific oligonucleotide ligation assays (e.g., oligonucleotide ligation assays (OLA), single template molecule OLA using ligated linear probes and rolling circle amplification (RCA) readout, ligated padlock probes and / or single template molecule OLA using ligated circular padlock probes and rolling circle amplification (RCA) readout), high-throughput sequencing methods, for example, methods using Roche 454, Illumina Solexa, AB-SOLiD, Helicos, Polonator platforms, and the like, and light-based sequencing technologies (Landegren et al. (1998) Genome Res.8:769-76; Kwok (2000) Pharmacogenomics 1:95-100; and Shi (2001) Clin. Chem. 47:164-172). In some cases, the amplified nucleic acid molecules are subjected to shotgun sequencing. In some cases, the sequencing library is sequenced using any appropriate sequencing technology, including but not limited to single molecule real-time (SMRT) sequencing, polymerase cloning sequencing, ligation sequencing, reversible terminator sequencing, proton detection sequencing, ion semiconductor sequencing, nanopore sequencing, electronic sequencing, pyrophosphate sequencing, Maxam-Gilbert sequencing, chain termination (such as Sanger) sequencing, +S sequencing, or sequencing by synthesis (array / colony-based or nanoball-based).

[0151] This article describes a method for generating an amplicon library from a sample including short nucleic acids using the PTA method described herein. In some cases, PTA can improve the fidelity and uniformity of short nucleic acid amplification. In some cases, the length of the nucleic acid does not exceed 2000 bases. In some cases, the length of the nucleic acid does not exceed 1000 bases. In some cases, the length of the nucleic acid does not exceed 500 bases. In some cases, the length of the nucleic acid does not exceed 200, 400, 750, 1000, 2000 or 5000 bases. In some cases, the sample including the short nucleic acid fragment includes but is not limited to ancient DNA (age is hundreds of years, thousands of years, millions or even billions of years), FFPE (formalin fixed paraffin embedded) sample, cell-free DNA or other samples including short nucleic acids.

[0152] Reagent test kit

[0153] Kits that are helpful for implementing the PTA method are described herein. Various combinations of components of the exemplary reaction mixtures and reaction methods set forth above can be provided in kit form. The kit can include separate components that are separated from each other (e.g., loaded in different containers or packages). In some cases, the kit includes one or more sub-combinations of components described herein, which are separated from other components of the kit. In some cases, these sub-combinations can be combined into a reaction mixture as described herein (or combined to carry out a reaction as described herein). In a specific embodiment, the sub-combination of components present in a single container or package is not enough to carry out a reaction as described herein. However, in some cases, the kit as a whole includes a collection of containers or packages, and its contents can be combined to carry out a reaction as described herein.

[0154] The kit may include suitable packaging materials for accommodating the contents of the kit. In some cases, the packaging materials are manufactured by well-known methods, preferably to provide a sterile, non-contaminated environment. The packaging materials used herein include, for example, those commonly used in commercially available kits for use with nucleic acid sequencing systems. Exemplary packaging materials include, but are not limited to, glass, plastic, paper, foil, etc., which are capable of maintaining the components described herein within fixed limits. The packaging material may include a label indicating the specific use of the component. In some cases, the use of the kit indicated by the label is one or more methods described herein, which are suitable for a specific combination of components present in the kit. For example, in some cases, the label indicates that the kit can be used for a method for detecting mutations in a nucleic acid sample using the PTA method. The kit may also include instructions for use of the reagents or components packaged. The instructions typically include descriptions of reaction parameters, such as the relative amounts of the kit components and the samples to be mixed, the maintenance time period of the reagent / sample mixture, temperature, buffer conditions, etc. It should be understood that not all components required for a particular reaction need to be present in a particular kit. On the contrary, in some cases, one or more additional components are provided by other sources. In some cases, the instructions provided with the kit identify the additional components to be provided and where they can be obtained. In one embodiment, the kit provides at least one amplification primer; at least one nucleic acid polymerase; a mixture of at least two nucleotides, wherein the mixture of nucleotides includes at least one terminator nucleotide that terminates nucleic acid replication by the polymerase; and instructions for use of the kit. In some cases, the kit provides reagents for performing the methods described herein, such as PTA. In some cases, the kit also includes reagents configured for gene editing (e.g., Crispr / cas9 or other methods described herein).

[0155] In a related aspect, the present invention provides a kit comprising a reverse transcriptase, a nucleic acid polymerase, one or more amplification primers, a nucleotide mixture comprising one or more terminator nucleotides, and optional instructions for use. In one embodiment of the kit of the present invention, the nucleic acid polymerase is a strand displacement DNA polymerase. In one embodiment of the kit of the present invention, the nucleic acid polymerase is selected from bacteriophage phi29 (Φ29) polymerase, genetically modified phi29 (Φ29) DNA polymerase, Klenow fragment of DNA polymerase I, bacteriophage M2 DNA polymerase, bacteriophage phiPRD1 DNA polymerase, Bst DNA polymerase, Bst large fragment DNA polymerase, exo(-)Bst polymerase, exo(-)Bca DNA polymerase, Bsu DNA polymerase, Vent R DNA polymerase, Vent R(exo-)DNA polymerase, Deep Vent DNA polymerase, Deep Vent (exo-)DNA polymerase, IsoPol DNA polymerase, DNA polymerase I, Therminator DNA polymerase, T5 DNA polymerase, Sequenase, T7 DNA polymerase, T7-sequenase and T4 DNA polymerase. In one embodiment of the kit of the present invention, the nucleic acid polymerase has 3'->5' exonuclease activity, and the terminator nucleotide inhibits this 3'->5' exonuclease activity (e.g., nucleotides modified with an α group [e.g., α-thiodideoxynucleotides], C3 spacer nucleotides, locked nucleic acids (LNA), reverse nucleic acids, 2' fluoronucleotides, 3' phosphorylated nucleotides, 2'-O-methyl modified nucleotides, trans nucleic acids). In one embodiment of the kit of the present invention, the nucleic acid polymerase does not have 3'->5' exonuclease activity (e.g., Bst DNA polymerase, exo(-)Bst polymerase, exo(-)Bca DNA polymerase, Bsu DNA polymerase, Vent R (exo-)DNA polymerase, Deep Vent (exo-)DNA polymerase, Klenow fragment (exo-)DNA polymerase, Therminator DNA polymerase). In a specific embodiment, the terminator nucleotide includes a modification of the r group of the 3' carbon of the deoxyribose. In a specific embodiment, the terminator nucleotide is selected from a reversible terminator including a 3' blocked terminator of a nucleotide, a reversible terminator including a 3' unblocked terminator of a nucleotide, a terminator including a 2' modification of a deoxynucleotide, a terminator including a modification of the nitrogenous base of a deoxynucleotide, and a combination thereof. In a specific embodiment, the terminator nucleotide is selected from dideoxynucleotides, reverse dideoxynucleotides, 3' biotinylated nucleotides, 3' aminonucleotides, 3'-phosphorylated nucleotides, 3'-O-methyl nucleotides, 3' C3 spacer nucleotides, 3' C18 nucleotides, 3' hexanediol spacer nucleotides 3' carbon spacer nucleotides, acyclic nucleotides, and combinations thereof.

[0156] Numbered implementation plan

[0157] The following numbered embodiments 1-104 are described herein. 1. Provided herein is a method for determining a mutation, comprising: a. exposing a cell population to a gene editing method, wherein the gene editing method utilizes an agent configured to achieve a mutation in a target sequence; b. isolating a single cell from the population; c. providing a cell lysate from a single cell; d. contacting the cell lysate with at least one amplification primer, at least one nucleic acid polymerase, and a nucleotide mixture, wherein the nucleotide mixture includes at least one terminator nucleotide that terminates nucleic acid replication by the polymerase; and e. amplifying the target nucleic acid molecule to generate a plurality of terminated amplification products, wherein replication is performed by strand displacement replication; f. ligating the molecule obtained in step (e) to an adaptor to generate an amplification product library; g. sequencing the amplification product library; and h. comparing the amplification product sequence to at least one reference sequence to identify at least one mutation. 2. Also provided herein is a method of embodiment 1, wherein at least one mutation is present in the target sequence. 3. Also provided herein is a method of embodiment 1, wherein at least one mutation is not present in the target sequence. 4. Also provided herein is a method of embodiment 1 or 2, wherein the gene editing method comprises the use of CRISPR, TALEN, ZFN, recombinase or meganuclease. 5. Also provided herein is a method of embodiment 1 or 2, wherein the gene editing technology comprises the use of CRISPR. 6. Also provided herein is a method of embodiment 1 or 2, wherein the gene editing technology comprises the use of a gene therapy method. 7. Also provided herein is a method of embodiment 6, wherein the gene therapy method is not configured to modify the somatic DNA or germline DNA of the cell. 8. Also provided herein is a method of embodiment 5, wherein the reference sequence is a genome. 9. Also provided herein is a method of embodiment 5, wherein the reference sequence is a specificity determining sequence, wherein the specificity determining sequence is configured to bind to a target sequence. 10. Also provided herein is a method of embodiment 9, wherein at least one mutation is present in a sequence region that differs from the specificity determining sequence by at least 1 base. 11. Also provided herein is a method of embodiment 9, wherein at least one mutation is present in a sequence region that differs from the specificity determining sequence by at least 2 bases. 12. The method of embodiment 9 is also provided herein, wherein at least one mutation is present in a sequence region that is at least 3 bases different from the specificity determining sequence. 13. The method of embodiment 9 is also provided herein, wherein at least one mutation is present in a sequence region that is at least 5 bases different from the specificity determining sequence. 14. The method of embodiment 1 is also provided herein, wherein the at least one mutation comprises an insertion, deletion or substitution. 15. The method of embodiment 5 is also provided herein, wherein the reference sequence is a CRISPR RNA (crRNA) sequence. 16. The method of embodiment 5 is also provided herein, wherein the reference sequence is a single guide RNA (sgRNA) sequence.17. The method of embodiment 5 is also provided herein, wherein the at least one mutation is present in the sequence region that binds to the catalytically active Cas9. 18. The method of embodiment 1 is also provided herein, wherein the single cell is a mammalian cell. 19. The method of embodiment 1 is also provided herein, wherein the single cell is a human cell. 20. The method of any one of embodiments 1-19 is also provided herein, wherein the single cell is derived from the liver, skin, kidney, blood or lung. 21. The method of any one of embodiments 1-20 is also provided herein, wherein the single cell is a primary cell. 22. The method of any one of embodiments 1-20 is also provided herein, wherein the single cell is a stem cell. 23. The method of any one of embodiments 1-20 is also provided herein, wherein at least some of the amplified products comprise a barcode. 24. The method of any one of embodiments 1-20 is also provided herein, wherein at least some of the amplified products comprise at least two barcodes. 25. The method of embodiment 23 is also provided herein, wherein the barcode comprises a cell barcode. 26. The method of embodiment 23 or 25 is also provided herein, wherein the barcode comprises a sample barcode. 27. Also provided herein is a method of any one of embodiments 1-26, wherein at least some of the amplification primers comprise a unique molecular identifier (UMI). 28. Also provided herein is a method of any one of embodiments 1-26, wherein at least some of the amplification primers comprise at least two unique molecular identifiers (UMIs). 29. Also provided herein is a method of any one of embodiments 1-27, wherein the method further comprises an additional amplification step using PCR. 30. Also provided herein is a method of any one of embodiments 1-29, wherein the method further comprises removing at least one terminator nucleotide from the terminated amplification product prior to ligation to an adaptor. 31. Also provided herein is a method of any one of embodiments 1-30, wherein a single cell is isolated from a population using a method comprising a microfluidic device. 32. Also provided herein is a method of any one of embodiments 1-31, wherein at least one mutation occurs in less than 50% of the cell population. 33. Also provided herein is a method of any one of embodiments 1-31, wherein at least one mutation occurs in less than 25% of the cell population. 34. Also provided herein is a method according to any one of embodiments 1-31, wherein at least one mutation occurs in less than 1% of a cell population. 35. Also provided herein is a method according to any one of embodiments 1-31, wherein at least one mutation occurs in no more than 0.1% of a cell population. 36. Also provided herein is a method according to any one of embodiments 1-31, wherein at least one mutation occurs in no more than 0.01% of a cell population. 37. Also provided herein is a method according to any one of embodiments 1-31, wherein at least one mutation occurs in no more than 0.001% of a cell population. 38. Also provided herein is a method according to any one of embodiments 1-31, wherein at least one mutation occurs in no more than 0.0001% of a cell population.39. Also provided herein is a method according to any one of embodiments 1-31, wherein at least one mutation occurs in no more than 25% of the amplified product sequences. 40. Also provided herein is a method according to any one of embodiments 1-31, wherein at least one mutation occurs in no more than 1% of the amplified product sequences. 41. Also provided herein is a method according to any one of embodiments 1-31, wherein at least one mutation occurs in no more than 0.1% of the amplified product sequences. 42. Also provided herein is a method according to any one of embodiments 1-31, wherein at least one mutation occurs in no more than 0.01% of the amplified product sequences. 43. Also provided herein is a method according to any one of embodiments 1-31, wherein at least one mutation occurs in no more than 0.001% of the amplified product sequences. 44. Also provided herein is a method according to any one of embodiments 1-31, wherein at least one mutation occurs in no more than 0.0001% of the amplified product sequences. 45. Also provided herein is a method according to any one of embodiments 1-31, wherein at least one mutation is present in a sequence region associated with a genetic disease or condition. 46. ​​The present invention also provides a method according to any one of embodiments 1-31, wherein at least one mutation is present in a sequence region that is not related to the binding of a DNA repair enzyme. 47. The present invention also provides a method according to any one of embodiments 1-31, wherein at least one mutation is present in a sequence region that is not related to the binding of MRE11. 48. The present invention also provides a method according to any one of embodiments 1-31, wherein the method further comprises identifying a false positive mutation previously sequenced by another off-target detection method. 49. The present invention also provides a method according to embodiment 48, wherein the off-target detection method is computer simulation prediction, ChIP-seq, GUIDE-seq, circle-seq, HTGTS (high-throughput whole-genome translocation sequencing), IDLV (integration-defective lentivirus), Digenome-seq, FISH (fluorescence in situ hybridization) or DISCOVER-seq. 50. Provided herein is a method for identifying specificity-determining sequences, comprising: a. providing a nucleic acid library, wherein at least some of the nucleic acids contain specificity-determining sequences; b. performing a gene editing method on at least one cell, wherein the gene editing method comprises contacting the cell with a reagent containing at least one specificity-determining sequence; c. sequencing the genome of at least one cell using the method provided in any one of embodiments 1-38, wherein the specificity-determining sequence contacted with at least one cell is identified; and d. identifying at least one specificity-determining sequence that provides the least off-target mutations. 51. Also provided herein is a method for embodiment 50, wherein the off-target mutation is a silent mutation. 52. Also provided herein is a method for embodiment 50, wherein the off-target mutation exists outside the gene coding region.53. Provided herein is a method for in vivo mutation analysis, comprising: a. performing a gene editing method on at least one cell in a living organism, wherein the gene editing method comprises contacting the cell with an agent comprising at least one specific determining sequence; b. isolating at least one cell from the organism; c. sequencing the genome of at least one cell using the method provided in any one of embodiments 1-49. 54. Also provided herein is a method of embodiment 53, wherein the method comprises at least two cells. 55. Also provided herein is a method of embodiment 54, which further comprises identifying a mutation by comparing the genome of a first cell with the genome of a second cell. 56. Also provided herein is a method of embodiment 54 or 55, wherein the first cell and the second cell are from different tissues. 57. Provided herein is a method for predicting the age of an object, comprising: a. providing at least one sample from an object, wherein the at least one sample comprises a genome; b. sequencing the genome using the method provided in any one of embodiments 1-38 to identify mutations; c. comparing the mutations obtained in step b with a standard reference curve, wherein the standard reference curve associates mutation counts and positions with validated ages; and d. predicting the age of the object based on the comparison of mutations with the standard reference curve. 58. Also provided herein is the method of embodiment 57, wherein the standard reference curve is specific for the subject's sex. 59. Also provided herein is the method of embodiment 57, wherein the standard reference curve is specific for the subject's race. 60. Also provided herein is the method of embodiment 57, wherein the standard reference curve is specific for the subject's geographic location, where the subject spent a period of their life. 61. Also provided herein is the method of any of embodiments 57-60, wherein the subject is less than 50 years old. 62. Also provided herein is the method of any of embodiments 57-60, wherein the subject is less than 18 years old. 63. Also provided herein is the method of any of embodiments 57-60, wherein the subject is less than 15 years old. 64. Also provided herein is the method of any of embodiments 57-63, wherein the at least one sample is greater than 10 years old. 65. Also provided herein is the method of any of embodiments 57-63, wherein the at least one sample is greater than 100 years old. 66. Also provided herein is the method of any of embodiments 57-63, wherein the at least one sample is greater than 1000 years old. 67. Also provided herein is a method according to any one of embodiments 57-66, wherein at least 2 samples are sequenced. 68. Also provided herein is a method according to any one of embodiments 57-66, wherein at least 5 samples are sequenced. 69. Also provided herein is a method according to embodiment 67, wherein the at least two samples are from different tissues.70. Provided herein is a method for sequencing a microbial or viral genome, comprising: a. obtaining a sample comprising one or more genomes or genome fragments; b. sequencing the sample using the method provided in any one of embodiments 1-38 to obtain a plurality of sequencing reads; and c. assembling and sorting the sequencing reads to generate a microbial or viral genome. 71. Also provided herein is a method of embodiment 70, wherein the sample comprises genomes from at least two organisms. 72. Also provided herein is a method of embodiment 70, wherein the sample comprises genomes from at least ten organisms. 73. Also provided herein is a method of embodiment 70, wherein the sample comprises genomes from at least 100 organisms. 74. Also provided herein is a method of any one of embodiments 70-73, wherein the sample originates from an environment of a deep-sea vent, an ocean, a mine, a stream, a lake, a meteorite, a glacier or a volcano. 75. Also provided herein is a method of any one of embodiments 70-74, further comprising identifying at least one gene in the microbial genome. 76. Also provided herein is a method of any one of embodiments 70-75, wherein the microbial genome corresponds to an uncultured organism. 77. Also provided herein is a method of embodiment 76, wherein the microbial genome corresponds to a symbiotic organism. 78. Also provided herein is a method of any of embodiments 70-77, further comprising cloning at least one gene in a recombinant host organism. 79. Also provided herein is a method of embodiment 78, wherein the recombinant host organism is a bacterium. 80. Also provided herein is a method of embodiment 79, wherein the recombinant host organism is Escherichia, Bacillus, or Streptomyces. 81. Also provided herein is a method of embodiment 78, wherein the recombinant host organism is a eukaryotic cell. 82. Also provided herein is a method of embodiment 81, wherein the recombinant host organism is a yeast cell. 83. Also provided herein is a method of embodiment 82, wherein the recombinant host organism is yeast or Pichia pastoris. 84. Also provided herein is a kit for nucleic acid sequencing, comprising: a. at least one amplification primer; b. at least one nucleic acid polymerase; c. a mixture of at least two nucleotides, wherein the mixture of nucleotides includes at least one terminator nucleotide that terminates nucleic acid replication by the polymerase; and d. instructions for using the kit for nucleic acid sequencing. 85. Also provided herein is a kit of embodiment 84, wherein at least one amplification primer is a random primer. 86. Also provided herein is a kit of embodiment 84, wherein the nucleic acid polymerase is a DNA polymerase. 87. Also provided herein is a kit of embodiment 86, wherein the DNA polymerase is a strand displacement DNA polymerase.88. The present invention also provides a kit of any one of embodiments 84-87, wherein the nucleic acid polymerase is bacteriophage phi29 (Φ29) polymerase, genetically modified phi29 (Φ29) DNA polymerase, Klenow fragment of DNA polymerase I, bacteriophage M2 DNA polymerase, bacteriophage phiPRD1 DNA polymerase, Bst DNA polymerase, Bst large fragment DNA polymerase, exo(-)Bst polymerase, exo(-)Bca DNA polymerase, Bsu DNA polymerase, VentR DNA polymerase, VentR (exo-) DNA polymerase, Deep Vent DNA polymerase, Deep Vent (exo-) DNA polymerase, IsoPol DNA polymerase, DNA polymerase I, Therminator DNA polymerase, T5 DNA polymerase, sequencer, T7 DNA polymerase, T7-sequenase or T4 DNA polymerase. 89. Also provided herein is a kit of any one of embodiments 84-88, wherein the nucleic acid polymerase comprises 3'->5' exonuclease activity and at least one terminator nucleotide inhibits the 3'->5' exonuclease activity. 90. Also provided herein is a kit of any one of embodiments 84-88, wherein the nucleic acid polymerase does not comprise 3'->5' exonuclease activity. 91. Also provided herein is a kit of any one of embodiments 84-88, wherein the polymerase is Bst DNA polymerase, exo(-)Bst polymerase, exo(-)Bca DNA polymerase, Bsu DNA polymerase, VentR (exo-)DNA polymerase, Deep Vent (exo-)DNA polymerase, Klenow fragment (exo-)DNA polymerase or Therminator DNA polymerase. 92. Also provided herein is a kit of any one of embodiments 84-91, wherein the at least one terminator nucleotide comprises a modification of the r group of the 3' carbon of the deoxyribose. 93. Also provided herein is a kit of any one of embodiments 84-92, wherein the at least one terminator nucleotide is selected from a 3' blocked reversible terminator comprising a nucleotide, a 3' unblocked reversible terminator comprising a nucleotide, a 2' modified terminator comprising a deoxynucleotide, a terminator comprising a modification of a nitrogenous base of a deoxynucleotide, and a combination thereof. 94. Also provided herein is a kit of any one of embodiments 84-93, wherein the at least one terminator nucleotide is selected from a dideoxynucleotide, an inverted dideoxynucleotide, a 3' biotinylated nucleotide, a 3' amino nucleotide, a 3'-phosphorylated nucleotide, a 3'-O-methyl nucleotide, a 3' carbon spacer nucleotide (including a 3' C3 spacer nucleotide), a 3' C18 nucleotide, a 3' hexanediol spacer nucleotide, an acyclic nucleotide, and a combination thereof.95. Also provided herein is a kit of any one of embodiments 84-94, wherein the at least one terminator nucleotide is selected from a nucleotide containing a modification to the α group, a C3 spacer nucleotide, a locked nucleic acid (LNA), an inverted nucleic acid, a 2'fluoro nucleotide, a 3'phosphorylated nucleotide, a 2'-O-methyl modified nucleotide, and a trans nucleic acid. 96. Also provided herein is a kit of any one of embodiments 84-95, wherein the nucleotide containing a modification to the α group is an α-thiodideoxy nucleotide. 97. Also provided herein is a kit of any one of embodiments 84-96, wherein the length of the amplification primer is 4 to 70 nucleotides. 98. Also provided herein is a kit of any one of embodiments 84-97, wherein the length of the at least one amplification primer is 4 to 20 nucleotides. 99. Also provided herein is a kit of any one of embodiments 84-98, wherein the at least one amplification primer comprises a random region. 100. Also provided herein is a kit of embodiment 99, wherein the length of the random region is 4 to 20 nucleotides. 101. Also provided herein is a kit of embodiment 99 or 100, wherein the length of the random region is 8 to 15 nucleotides. 102. Also provided herein is a kit of any one of embodiments 84-101, wherein the kit further comprises a library preparation kit. 103. Also provided herein is a kit of embodiment 102, wherein the library preparation kit comprises one or more of the following: a. at least one polynucleotide adapter; b. at least one high-fidelity polymerase; c. at least one ligase; d. a reagent for nucleic acid shearing; and e. at least one primer; wherein the primer is configured to bind to an adapter. 104. Also provided herein is a kit of any one of embodiments 84-103, wherein the kit further comprises a reagent configured for gene editing.

[0158] Example

[0159] The following examples are presented to more clearly illustrate the principles and practices of the embodiments disclosed herein to those skilled in the art, and these examples should not be construed as limiting the scope of any claimed embodiments. Unless otherwise indicated, all parts and percentages are by weight.

[0160] Example 1: Primary template directed amplification (PTA)

[0161] Although PTA can be used for any nucleic acid amplification, it is particularly useful for whole genome amplification because it allows a greater percentage of the cellular genome to be captured in a more uniform and reproducible manner with lower error rates than currently used methods such as multiple displacement amplification (MDA), avoiding the shortcomings of currently used methods such as exponential amplification where the polymerase first extends random primers, which can lead to random overrepresentation of loci and alleles and propagation of mutations (see Figure 1A-Figure 1C ).

[0162] Cell culture

[0163] Human NA12878 (Coriell Institute) cells were maintained in RPMI medium supplemented with 15% FBS and 2 mM L-glutamine, 100 units / mL penicillin, 100 μg / mL streptomycin, and 0.25 μg / mL amphotericin B (Gibco, Life Technologies). 5 The cultures were split every 3 days and maintained in a humidified incubator at 37°C with 5% CO2.

[0164] Single cell isolation and WGA

[0165] 3.5×10 5 After inoculation at a density of 10 cells / ml, NA12878 cells were cultured for at least three days, after which 3 mL of the cell suspension was pelleted at 300 x g for 10 minutes. The culture medium was then discarded and 1 mL of cell wash buffer (containing 2% FBS, without Mg) was used. 2 or Ca 2 1X PBS) was washed 3 times, centrifuged at 300xg, 200xg and finally 100xg for 5 minutes. The cells were then resuspended in 500 μL cell washing buffer. Subsequently, 100nM calcein AM (molecular probes) and 100ng / ml propidium iodide (PI; Sigma-Aldrich) were used to distinguish the live cell population. The cells were loaded onto a BD FACScan flow cytometer (FACSAria II) (BD Biosciences) that had been thoroughly washed with ELIMINase (Decon Labs) and calibrated with Accudrop fluorescent beads (BD Biosciences) for cell sorting. Single cells from the calcein AM-positive and PI-negative parts were sorted into each well of a 96-well plate in cells to be subjected to PTA (Sigma-Aldrich), containing 3 μL of PBS (Qiagen, REPLI-g SC kit) and 0.2% Tween 20 in the wells. Multiple wells were intentionally left blank to serve as no template controls (NTCs). Immediately after sorting, the plates were briefly centrifuged and placed on ice. Then, the cells were frozen at -20 °C for at least overnight. The next day, WGA reactions were performed on a pre-PCR workstation that provided constant positive pressure of HEPA-filtered air and was sterilized with UV light for 30 min before each experiment.

[0166] When performing MDA, modifications that have been previously shown to improve amplification uniformity were used. Specifically, exonuclease-resistant random primers were added to the lysis buffer / mix to a final concentration of 125 μM. 4 μL of the resulting lysis / denaturation mixture was added to the tube containing the single cells, vortexed, briefly centrifuged, and incubated on ice for 10 minutes. 3 μL of quenching buffer was added to neutralize the cell lysate, mixed by vortexing, briefly centrifuged, and placed at room temperature. 40 μL of amplification mixture was then added, followed by incubation at 30°C for 8 hours, and amplification was terminated by heating to 65°C for 3 minutes.

[0167] PTA was performed by further lysing the cells after freeze-thaw by adding 2 μL of a pre-cooled solution of a 1:1 mixture of 5% TritonX-100 (Sigma-Aldrich) and 20 mg / ml proteinase K (Promega). The cells were then vortexed and briefly centrifuged before being placed at 40°C for 10 minutes. 4 μL of lysis buffer / mix and 1 μL of 500 μM exonuclease-resistant random primers were then added to the lysed cells to denature the DNA, then vortexed, centrifuged, and placed at 65°C for 15 minutes. 4 μL of room temperature quenching buffer was then added, and the sample was vortexed and centrifuged. 56 μL of amplification mixture (primers, dNTPs, polymerase, buffer) contained an equal proportion of α-thio-ddNTPs at a concentration of 1200 μM in the final amplification reaction. The sample was then placed at 30°C for 8 hours, after which it was heated to 65°C for 3 minutes to terminate the amplification.

[0168] Following the amplification step, DNA from the MDA and PTA reactions was purified using AMPure XP magnetic beads (Beckman Coulter) at a 2:1 bead to sample ratio, and yield was measured using the Qubit dsDNA HS Assay Kit and Qubit 3.0 Fluorometer according to the manufacturer's instructions (Life Technologies).

[0169] Library preparation

[0170] The MDA reaction produced a yield of 40 μg of amplified DNA. 1 μg of product was enzymatically fragmented for 30 minutes according to standard procedures. The samples were then subjected to standard library preparation using 15 μM of dual-index adapters (end-repaired by T4 polymerase, T4 polynucleotide kinase, and Taq polymerase to add A tails) and 4 PCR cycles. Each PTA reaction produced 40-60 ng of material for standard DNA sequencing library preparation. 2.5 μM adapters with UMIs and dual indexes were used for ligation with T4 ligase, and 15 PCR cycles (hot-start polymerase) were used for final amplification. The library was then cleaned up using a double-sided SPRI, with the ratios used for right-side selection and left-side selection being 0.65X and 0.55X, respectively. The final library was quantified using the Qubit dsDNA BR assay kit and 2100 Bioanalyzer (Agilent Technologies) before sequencing on the Illumina NextSeq platform. All Illumina sequencing platforms, including NovaSeq, are also compatible with this protocol.

[0171] Data analysis

[0172] Sequencing reads were demultiplexed based on cellular barcodes using Bcl2fastq. Reads were then trimmed using trimmomatic and subsequently aligned to hg19 using BWA. Reads were duplicate labeled by Picard followed by local realignment and base realignment using GATK 4.0. All files used to calculate quality metrics were downsampled to 20 million reads using PicardDownSampleSam. Quality metrics were obtained from the final bam files using qualimap as well as PicardAlignmentSummaryMetrics and CollectWgsMetrics. Total genome coverage was also estimated using Preseq.

[0173] Variant determination

[0174] Single nucleotide variants and insertions / deletions were determined using GATK UnifiedGenotyper from GATK 4.0. Standard filtering conditions using GATK best practices were used for all steps in the process (https: / / software.broadinstitute.org / gatk / best-practices / ). Copy number variants were determined using Control-FREEC (Boeva ​​et al., Bioinformatics, 2012, 28(3):423-5). Structural variants were also detected using CREST (Wang et al., Nat Methods, 2011, 8(8):652-4).

[0175] result

[0176] like Figure 3A and Figure 3B As shown, the mapping rate and mapping quality score of amplification using only dideoxynucleotides ("reversible") were 15.0 + / - 2.2 and 0.8 + / - 0.08, respectively, while the mapping rate and mapping quality score of amplification incorporating exonuclease-resistant α-thio dideoxynucleotide terminators ("irreversible") were 97.9 + / - 0.62 and 46.3 + / - 3.18, respectively. Experiments were also performed using reversible ddNTPs and different concentrations of terminators ( Figure 2A ,bottom).

[0177] Figure 2B-2E Shown are comparative data produced by NA12878 human single cells through MDA (according to Dong, X. et al., Nat Methods.2017, 14 (5): 491-493 method) or PTA. Although both schemes produce a considerable low PCR repetition rate (MDA is 1.26% + / - 0.52, and PTA is 1.84% + / - 0.99) and GC% (MDA is 42.0 + / - 1.47, and PTA is 40.33 + / - 0.45), the amplicon produced by PTA is smaller. Compared with MDA, the mapping read percentage and mapping quality score of PTA are also significantly higher (PTA 97.9 + / - 0.62 and MDA 82.13 + / - 0.62, and PTA 46.3 + / - 3.18 and MDA 43.2 + / - 4.21). In general, compared with MDA, PTA produces more available mapping data. Figure 4A It was shown that PTA significantly improved the uniformity of amplification compared with MDA, with a wider coverage range and fewer regions with coverage close to 0. Low-frequency sequence variants in nucleic acid populations can be identified using PTA, including variants that account for ≥0.01% of the total sequence. PTA can be successfully used for single-cell genome amplification.

[0178] Example 2: Comparative Analysis of PTA

[0179] Benchmarking PTA and SCMDA cell maintenance and isolation

[0180] Lymphoblastoid cells from the 1000 Genomes Project object NA12878 (Coriell Institute, Camden, NJ, USA) were maintained in RPMI medium supplemented with 15% FBS, 2 mM L-glutamine, 100 units / mL penicillin, 100 μg / mL streptomycin, and 0.25 μg / mL amphotericin B. Cells were grown at 3.5 × 10 5 Cells were seeded at a density of 10 cells / ml and separated every 3 days. They were maintained in a humidified incubator at 37°C, 5% CO2. Before single cell separation, 3 mL of the suspension of cells that had been expanded in the past 3 days was centrifuged at 300 x g for 10 minutes. The precipitated cells were washed with 1 mL of cell wash buffer (containing 2% FBS, without Mg). 2+ or Ca 2+ 1X PBS) was washed 3 times, and then centrifuged at 300xg, 200xg and finally 100xg for 5 minutes to remove dead cells. The cells were then resuspended in 500μL cell washing buffer and then stained with 100nM calcein AM and 100ng / ml propidium iodide (PI) to distinguish live cell populations. The cells were loaded onto a BD FACScan flow cytometer (FACSAria II) that had been thoroughly washed with ELIMINase and calibrated with Accudrop fluorescent beads. Single cells from the calcein AM positive and PI negative parts were sorted into each well of a 96-well plate containing 3μL of PBS and 0.2% Tween 20. Multiple wells were intentionally left empty to serve as a template-free control. After sorting, the plate was briefly centrifuged and placed on ice immediately. Then, the cells were frozen at -80°C for at least overnight.

[0181] PTA and SCMDA experiments

[0182] The WGA reaction was assembled on a pre-PCR workstation that provided constant positive pressure using HEPA-filtered air and was sterilized with ultraviolet light for 30 minutes before each experiment. MDA was performed according to SCMDA according to a published protocol (Dong et al., Nat. Meth. 2017, 14, 491-493). Specifically, random primers resistant to exonucleases were added to the lysis buffer at a final concentration of 12.5 μM. 4 μL of the resulting lysis mixture was added to a tube containing a single cell, pipetted 3 times to mix, centrifuged briefly and incubated on ice for 10 minutes. The cell lysate was neutralized by adding 3 μL of quenching buffer, pipetted 3 times to mix, centrifuged briefly, and placed on ice. 40 μL of amplification mixture was subsequently added, then incubated at 30 ° C for 8 hours, and then amplification was terminated by heating to 65 ° C for 3 minutes. PTA was performed by first further lysing the cells after freeze-thaw by adding 2 μL of a pre-chilled solution of a 1:1 mixture of 5% Triton X-100 and 20 mg / ml proteinase K. The cells were then vortexed and briefly centrifuged before being placed at 40 degrees for 10 minutes. 4 μL of denaturation buffer and 1 μL of 500 μM exonuclease-resistant random primers were then added to the lysed cells to denature the DNA, followed by vortexing, centrifugation and placing at 65°C for 15 minutes. 4 μL of room temperature quenching solution was then added, and the samples were vortexed and centrifuged. The 56 μL amplification mixture contained an equal proportion of α-thio-ddNTPs at a concentration of 1200 μM in the final amplification reaction. The samples were then placed at 30°C for 8 hours and then heated to 65°C for 3 minutes to terminate the amplification. After SCMDA or PTA amplification, DNA was purified using AMPure XP beads at a 2:1 bead-to-sample ratio and yield was measured using the Qubit dsDNA HS Assay Kit and Qubit 3.0 Fluorometer according to the manufacturer's instructions. PTA experiments were also performed using reversible ddNTPs and varying concentrations of terminator ( Figure 2A ,top).

[0183] Library preparation

[0184] According to the standard protocol, 1ug ​​SCMDA product was enzymatically fragmented for 30 minutes. The samples were then subjected to standard library preparation using 15 μM unique dual index adapters and 4 PCR cycles. The entire product of each PTA reaction was used for DNA sequencing library preparation without fragmentation. 2.5 μM unique dual index adapters were used for ligation, and 15 PCR cycles were used in the final amplification. The libraries from SCMDA and PTA were then visualized on 1% agarose E-Gel. Fragments between 400-700 bp were cut from the gel and recovered using a Gel DNA recovery kit. The final library was quantified using a Qubit dsDNA BR assay kit and an Agilent 2100 bioanalyzer before sequencing on the NovaSeq 6000.

[0185] Data analysis

[0186] Data were trimmed using trimmomatic and subsequently aligned to hg19 using BWA. Reads were duplicate marked by Picard followed by local realignment and base realignment using GATK 3.5 best practices. All files were downsampled to the specified number of reads using PicardDownSampleSam. Quality metrics were obtained from the final bam files using qualimap along with Picard AlignmentMetricsAummary and CollectWgsMetrics. Lorentz curves were plotted and the Gini index was calculated using htSeqTools. SNV calling was performed using UnifiedGenotyper followed by filtering using standard recommended criteria (QD<2.0||FS>60.0||MQ<40.0||SOR>4.0||MQRankSum<-12.5||ReadPosRankSum<-8.0). No regions were excluded from the analysis and no other data normalization or manipulation was performed. Sequencing metrics for the methods tested are listed in Table 1.

[0187] Table 1: Comparison of sequencing metrics between the methods tested

[0188]

[0189] CV = coefficient of variation; SNV = single nucleotide variation; values ​​refer to 15X coverage.

[0190] Genome coverage and uniformity

[0191] PTA was comprehensively compared with all common single-cell WGA methods. To achieve this goal, 10 NA12878 cells were subjected to PTA and a modified version of MDA, called single-cell MDA (Dong et al. Nat. Meth. 2017, 14, 491-493) (SCMDA). In addition, data generated as part of the LIANTI study were used to compare results from cells expanded by DOP-PCR (Zhang et al., PNAS 1992, 89, 5847-5851), MDA kit 1 (Dean et al., PNAS 2002, 99, 5261-5266), MDA kit 2, MALBAC (Zong et al., Science 2012, 338, 1622-1626), LIANTI (Chen et al., Science 2017, 356, 189-194), or PicoPlex (Langmore, Pharmacogenomics 3, 557-560 (2002)).

[0192] To normalize between samples, raw data from all samples were aligned and preprocessed for variant calling using the same pipeline. The bam files were then downsampled to 300 million reads before comparison. Importantly, PTA and SCMDA products were not screened before further analysis, whereas all other methods were screened for genome coverage and uniformity before selecting the highest quality cells used in subsequent analyses. Notably, SCMDA and PTA were compared to a bulk diploid NA12878 sample, whereas all other methods were compared to a bulk BJ1 diploid fibroblast cell population used in the LIANTI study. Figure 3C-Figure 3F As shown, PTA had the highest percentage of reads aligned to the genome, as well as the highest mapping quality. PTA, LIANTI, and SCMDA had similar GC content, all lower than the other methods. PCR duplication rates were similar in all methods. In addition, the PTA method enabled smaller templates (such as the mitochondrial genome) to provide higher coverage (similar to larger typical chromosomes) relative to the other methods tested ( Figure 3G ).

[0193] The coverage and uniformity of all methods were then compared. An example of the coverage plot of SCMDA and PTA on chromosome 1 is shown, where PTA has significantly improved coverage uniformity and allele frequency ( Figure 4B The increased number of reads was then used to calculate coverage for all methods. PTA approached both bulk samples at each depth, a significant improvement over all other methods ( Figure 5AWe then used two strategies to measure coverage uniformity. The first approach was to calculate the coverage variation coefficient when increasing sequencing depth, where PTA was found to be more uniform than all other methods ( Figure 5B The second strategy is to compute the Lorentz curve for each downsampled bam file, where PTA is again found to have the greatest uniformity ( Figure 5C To measure the reproducibility of amplification uniformity, the Gini index was calculated to estimate the difference between each amplification reaction and complete uniformity (de Bourcy et al., PloS one 9, e105585 (2014)). PTA was again shown to be more uniform than the other methods ( Figure 5D ).

[0194] SNV sensitivity

[0195] To determine the impact of these differences in amplification method performance on SNV calling, the variant call ratios for each method and the corresponding bulk samples were compared at increasing sequencing depths. To estimate sensitivity, the percentage of variants found in each cell that were called in the corresponding bulk samples downsampled to 650 million reads was compared at each sequencing depth ( Figure 5E The improved coverage and uniformity of PTA resulted in the detection of 45.6% more variants than MDA Kit 2, the second most sensitive method. Examination of sites judged to be heterozygous in a large number of samples showed that PTA significantly reduced allelic skew at those heterozygous sites ( Fig. 5F ). This finding supports the idea that PTA not only has more uniform amplification across the genome, but also more uniform amplification of both alleles in the same cell.

[0196] SNV Accuracy

[0197] To assess the accuracy of mutation calls, variants called in each single cell that were not found in the corresponding bulk sample were considered false positives. The lower lysis temperature of SCMDA significantly reduced the number of false positive variant calls ( Figure 5G ). Methods using thermostable polymerases (MALBAC, PicoPlex, and DOP-PCR) showed that the specificity of SNV calls decreased further with increasing sequencing depth. Without being bound by theory, this is likely a result of the significantly increased error rates of these polymerases compared to phi29 DNA polymerase. In addition, the base change patterns seen in false positive calls also appear to be polymerase dependent ( Figure 5H ).like Figure 5GAs shown in Figure 2, the lower false-positive SNV call rate in PTA compared to the standard MDA protocol supports the model that error propagation is suppressed in PTA. In addition, the allele frequency of false-positive variant calls in PTA is the lowest, which is again consistent with the model that error propagation is suppressed in PTA ( Fig.5I ).

[0198] Example 3: Direct Measurement of Environmental Mutagenicity (DMEM)

[0199] PTA was used to perform a novel mutagenicity assay that provides a framework for conducting high-resolution, genome-wide human toxicogenomics studies. Previous studies, such as the Ames test, relied on measurements from bacterial genetics that were thought to be representative of human cells but provided only limited information about the number and pattern of mutations induced in each exposed cell. To overcome these limitations, a human mutagenesis system, Direct Measures of Environmental Mutagenicity (DMEM), was developed in which individual human cells are exposed to environmental compounds, isolated into single cells, and single-cell sequencing is performed to identify novel mutations induced in each cell.

[0200] Umbilical cord blood cells expressing the stem / progenitor cell marker CD34 were exposed to increasing concentrations of the direct mutagen N-ethyl-N-nitrosourea (ENU). ENU is known to have a relatively low Swain-Scott substrate constant and has therefore been shown to act primarily through a two-step SN1 mechanism that results in preferential alkylation of O4-thymine, O2-thymine, and O2-cytosine. Through limited sequencing of the target gene, ENU also showed a preference for T to A (A to T), T to C (A to G), and C to T (G to A) changes in mice, which is significantly different from the pattern seen in Escherichia coli.

[0201] Isolation and Expansion of Umbilical Cord Blood Cells for Mutagenicity Studies

[0202] ENU (CAS 759-73-9) and D-mannitol (CAS 69-65-8) were placed in solution at their maximum solubility. Fresh anticoagulant-treated umbilical cord blood (CB) was obtained from the St. Louis Cord Blood Bank. CB was diluted 1:2 with PBS and mononuclear cells (MNCs) were isolated by density gradient centrifugation on Ficoll-Paque Plus according to the manufacturer's instructions. CB MNCs expressing CD34 were then immunomagnetically selected using the Human CD34 Microbead Kit and the Magnetic Cell Sorting (MACS) System according to the manufacturer's instructions. Cell counts and viability were determined using a Luna FL cell counter. CB CD34+ cells were centrifuged at 2.5x10 4Cells were plated at a density of 10 cells / mL in StemSpan SFEM supplemented with 1X CD34+ expansion supplement, 100 units / mL penicillin, and 100 ug / mL streptomycin and expanded for 96 hours prior to mutagen exposure.

[0203] Direct Measurement of Environmental Mutagenicity (DMEM)

[0204] Amplified cord blood CD34+ cells are cultured in StemSpan SFEM supplemented with 1X CD34+ expansion supplement, 100 units / mL penicillin and 100ug / mL streptomycin. Cells are exposed to ENU at concentrations of 8.54, 85.4 and 854 μM, D-mannitol at 1152.8 and 11528 μM or 0.9% sodium chloride (vehicle control) for 40 hours. As described above, single cell suspensions from drug-treated cells and vehicle control samples are harvested and stained to measure viability. Single cell sorting is performed as described above. According to the general method of the methods described herein and Example 2, PTA is performed and libraries are prepared using simplified and improved protocols.

[0205] Analysis of DMEM data

[0206] Data obtained from the cells in DMEM experiments were trimmed using Trimmomatic, aligned to GRCh38 using BWA, and further processed using GATK 4.0.1 best practices without deviation from recommended parameters. Genotyping was performed using HaplotypeCaller, again filtering joint genotypes using standard parameters. Variants were only considered as a result of a mutagen if they had a Phred quality score of at least 100 and were found in only one cell but not in a large number of samples. The trinucleotide context for each SNV was determined by extracting surrounding bases from the reference genome using bedtools. Mutation counts and context were visualized in R using ggplot2 and heatmap2.

[0207] To determine whether mutations are enriched in DNase I hypersensitive sites (DHS) in CD34+ cells, the proportion of SNVs overlapping DHS sites from 10 CD34+ primary cell datasets generated through the Roadmap Epigenomics Project was calculated for each sample. DHS sites extend 2 nucleosomes or 340 bases in both directions. Each DHS dataset was paired with a single-cell sample, in which we determined the proportion of the human genome in that cell that overlapped the DHS with at least 10-fold coverage and compared it to the proportion of SNVs found in the covered DHS sites.

[0208] result

[0209] Consistent with these studies, a dose-dependent increase in the number of mutations per cell was observed, with similar numbers of mutations detected at the lowest dose of ENU compared to vehicle control or toxic doses of mannitol ( Fig. 12A ). Also consistent with previous mouse studies using ENU, the most common mutations were T to A (A to T), T to C (A to G), and C to T (G to A). The other three types of base changes were also observed, but C to G (G to C) conversions appeared to be rare ( Fig. 12B ). Examination of the trinucleotide background of SNVs showed two distinct patterns ( Fig. 12C ). The first model is that cytosine mutagenesis appears to be rare when cytosine is followed by guanine. Cytosine followed by guanine is usually methylated at the fifth carbon position in the human genome, which is a hallmark of heterochromatin. Without being bound by theory, it is hypothesized that 5-methylcytosine is not alkylated by ENU due to the inaccessibility of heterochromatin or due to unfavorable reaction conditions for 5-methylcytosine compared to cytosine. To test the former hypothesis, the location of the mutation site was compared to known DNase I hypersensitive sites in CD34+ cells, which were classified by the Roadmap Epigenome Project. As Fig.12D As shown, no enrichment of cytosine variants was observed in DNase I hypersensitive sites. In addition, no enrichment of cytosine-restricted variants was observed in DH sites ( Fig.12E ). In addition, most thymine variants occurred where adenine preceded thymine. The annotation of genomic features of the variants did not differ significantly from the annotation of those features in the genome ( Fig.12F ).

[0210] Example 4: Massively parallel single-cell DNA sequencing

[0211] Using PTA, a protocol for massively parallel DNA sequencing was established. First, the cellular barcodes were added to random primers. Two strategies were used to minimize any bias in amplification introduced by the cellular barcodes: 1) extending the size of the random primers and / or 2) creating primers that loop back on themselves to prevent the cellular barcodes from binding to the template ( Fig. 10B ). Once the optimal primer strategy is established, it can be scaled up to 384 sorted cells using, for example, the Mosquito HTS liquid handler, which can move even viscous liquids down to 25 nL volumes with high precision. This liquid handler also reduces reagent costs by about 50-fold by using 1 μL PTA reactions instead of the standard 50 μL reaction volumes.

[0212] The amplification protocol is translated into droplets by delivering primers with cell barcodes to the droplets. A solid support is optionally used, such as beads created using a split-pooling strategy. Suitable beads can be obtained, for example, from ChemGenes. In some cases, the oligonucleotides contain random primers, cell barcodes, unique molecular identifiers, and cleavable sequences or spacers to release the oligonucleotides after encapsulation of the beads and cells in the same droplet. During this process, the concentrations of template, primers, dNTPs, α-thio-ddNTPs, and polymerase are optimized in low nanoliter volumes in the droplets. In some cases, optimization includes using larger droplets to increase the reaction volume. As Fig. 9 As shown, this process requires two sequential reactions to lyse cells and then perform WGA. The first droplet containing lysed cells and beads is combined with a second droplet containing an amplification mixture. Alternatively or in combination, cells are encapsulated in hydrogel beads before lysis, and then both beads can be added to the oil droplet. See Lan, F. et al., Nature Biotechnol., 2017, 35: 640-646).

[0213] Other approaches include the use of microwells that, in some cases, capture 140,000 single cells in a 20-picoliter reaction chamber on a 3" x 2" microscope slide-sized device. Similar to droplet-based approaches, these wells bind cells to beads containing cellular barcodes, allowing for massively parallel processing. See Gole et al., Nature Biotechnol., 2013, 31: 1126-1132.

[0214] Example 5: Application of PTA in Children with Acute Lymphoblastic Leukemia (ALL)

[0215] Single-cell exome sequencing has been performed on individual leukemia cells with the ETV6-RUNX1 translocation, measuring approximately 200 coding mutations per cell, of which only 25 were present in enough cells from that patient to be detected by standard bulk sequencing. The mutational burden of each cell was then merged with other known features of this type of leukemia, such as the replication-associated mutation rate (1 coding mutation / 300 cell divisions), the time from initiation to diagnosis (4.2 years), and the population size at diagnosis (100 billion cells), to create a computer simulation of the progression of the disease. Surprisingly, even in cancers that are thought to be genetically simple, such as pediatric ALL, there are an estimated 330 million clones with different profiles of coding mutations at the time of patient diagnosis. Interestingly, as Figure 6BAs shown, only 1 to 5 of the most abundant clones are detected by standard bulk sequencing (box C); there are tens of millions of clones that consist of a small number of cells and are therefore unlikely to be clinically significant (box A). Therefore, methods are provided for enhancing the sensitivity of detection so that clones that constitute at least 0.01% (1:10,000) of the cells can be detected (box B), because this is the stratum where most drug-resistant disease that can lead to relapse is hypothesized to reside.

[0216] Given this large amount of genetic diversity in the population, it has been hypothesized that within a given patient there are clones that are more resistant to treatment. To test this hypothesis, samples were placed in culture and the leukemia cells were exposed to increasing concentrations of standard ALL chemotherapy drugs. Figure 7 As shown, a clone with an activating KRAS mutation continued to expand in both control samples and samples that received the lowest dose of asparaginase. However, this clone proved to be more sensitive to prednisolone and daunomycin, while other previously undetectable clones could be more clearly detected after treatment with these drugs ( Figure 7 , dashed box). This approach also allows for bulk sequencing of processed samples. In some cases, the use of single-cell DNA sequencing allows for determination of the diversity and clonal types of an expanding population.

[0217] Create a catalog of ALL clonal drug sensitivities

[0218] like Figure 8 As shown, in order to make a catalog of ALL clonal drug sensitivity, an aliquot of the diagnostic sample was taken and single-cell sequencing of 10,000 cells was performed to determine the abundance of each clonal type. At the same time, the diagnosed leukemia cells were exposed to standard ALL drugs (vincristine, daunomycin, mercaptopurine, prednisolone and asparaginase) in vitro, as well as a group of targeted drugs (ibrutinib, dasatinib and ruxolitinib). Live cells were selected, and single-cell DNA sequencing was performed on at least 2,500 cells per drug exposure. Finally, bone marrow samples from the same patients who completed 6 weeks of treatment were sorted using established protocols for large-scale sequencing studies to detect live residual pre-leukemia and leukemia. PTA was then used to sequence single-cell DNA in tens of thousands of cells in a scalable, efficient and economical manner, thereby achieving the following goals.

[0219] Drug sensitivity catalog from clonotype to drug sensitivity

[0220] Once sequencing data is obtained, the clonotype of each cell is established. To this end, it is necessary to determine the variant and determine the clonotype. By using PTA, the allele loss and coverage bias introduced by the currently used WGA method are limited. The tools for performing MDA for determining variants from single cells were systematically compared, and it was found that the recently developed tool Monovar has the highest sensitivity and specificity (Zafar et al., Nature Methods, 2016, 13: 505-507). Once the variant determination is performed, it can be determined whether two cells have the same clonotype, although some variant determinations are lost due to allele loss. To this end, a mixed model of multivariate Bernoulli distribution can be used (Gawad et al., Proc. Natl. Acad. Sci. USA, 2014, 111 (50): 17947-52). After determining that the cells have the same clonotype, determine which variants to include in the catalog. Genes that meet any of the following conditions are included: 1) they are non-synonymous variants detected in any mutation hotspots or loss-of-function variants (frameshift, nonsense, splicing) that appear in known tumor suppressor genes found in large pediatric cancer genome sequencing projects; 2) they are variants repeatedly detected in relapsed cancer samples; and 3) they are relapse variants that are positively selected in current large-scale sequencing studies of residual disease after ALL patients have received 6 weeks of treatment. If the clone does not have at least two variants that meet these conditions, they are not included in the catalog. As more genes associated with treatment resistance or disease relapse are identified, clones can be "rescued" and included in the catalog. In order to determine whether the clonal type has been positively or negatively selected between the control and drug treatment, Fisher's exact test is used to identify clones that are significantly different from the control. Clones are added to the catalog only when at least two consistent combinations of mutations show the same correlation with exposure to a specific drug. Known activating mutations of oncogenes or loss-of-function mutations of tumor suppressor genes in the same gene are considered equivalent between clones. If the clonal type is not completely consistent, the common mutation is entered into the catalog. For example, if clonotype 1 is A+B+C, and clonotype 2 is B+C+D, the B+C clonotype will be entered into the catalog. If genes are identified that are recurrently mutated in resistant cells with a limited number of concurrent mutations, these clones can be collapsed into functionally equivalent clonotypes.

[0221] Example 6: Measuring the rate and location of CRISPR off-target activity in single human cells

[0222] Using the higher variant determination sensitivity and accuracy of PTA in single cells, highly sensitive CRISPR-mediated genome editing with specific guide RNAs was quantitatively measured in single cells. The conventional PTA method of Example 4 was performed on single cells. Indels and SV counts in unedited cells and edited cells were compared ( Fig.13A and Fig. 13B ).

[0223] We also examined the types of structural variants that these genome editing methods could induce in single human cells, and the results were Figures 14A-14C As shown. Fig.14A As shown, the target region is represented at the bottom (a) and is located between positions 43,770,818 and 43,770,841 on chromosome 6 (b). Sequence data appearing as paired end reads (small horizontal bars without dashed lines) indicate consistency between the single-cell sequence data and the target genome (c). The dashed lines within the reads indicate genomic deletions relative to the reference genome (d). In this example, both edited cells show deletions (d) that overlap with the target site (a). In contrast, the two unedited cells contain reads indicating that they are consistent with the reference genome at this position, so no editing has occurred. Fig. 14B Detection of a large (>1KB) deletion resulting from CRISPR-induced editing that is limited to edited #1 cells is shown. The target region is represented at the bottom (a) and is located between positions 23,779,588 and 23,779,611 on chromosome 18 (b). Sequence data in the form of reads (small colored horizontal bars, typically gray) indicate consistency between the single-cell sequence data and the target genome (c). Regions where alignment reads suddenly drop indicate deviations from the reference genome at these positions. In this case, the sudden loss of read coverage between positions 23,778,472 and 23,779,607 on chromosome 18 indicates the presence of a large deletion in edited #1 cells (d). This deletion was identified as a CRISPR-induced deletion because the rightmost breakpoint in the figure overlaps with a region in the genome that is highly similar to the target site (a) and is not present in unedited cells. Lowercase letters in (a) represent bases that differ from the target site. Fig. 14CDetection of an interchromosomal translocation between chromosome 2 position 241,275,213 and chromosome 4 position 38,536,006 in an edited #1 cell is shown. The translocation breakpoints overlap with gRNA off-target regions in each chromosome that are similar to the gRNA target sites and are indicated at the bottom [(a) and (b)]. The left panel represents reads aligned to the chromosome 2 region containing the breakpoint, while the right panel represents reads aligned to the chromosome 4 region containing the breakpoint. The edited #1 cell is divided into two views: a view of all reads aligned to the region surrounding the breakpoint (c), and a view of the same region but only showing read pairs that are evidence of the translocation (d). For read pairs supporting the translocation, one read in the pair is aligned to chromosome 2 with an abrupt drop in coverage at the breakpoint, and the other read is aligned to chromosome 4 with an abrupt drop in read coverage at the breakpoint (e). This translocation was identified as a CRISPR-induced translocation because at least one of the translocation breakpoints overlapped with a region in the genome that was highly similar to the target site in edited cells (in this case two: a and b), whereas there was no evidence of translocation in unedited cells. Lowercase letters in (a) and (b) indicate bases that differ from the target site.

[0224] To confirm putative off-target sites and to assess the accuracy of variant calling as the number of guide RNA genomic mismatches increased, microfluidics-based high-throughput PCR-based resequencing of putative off-target sites in all cells was also performed (data not shown).

[0225] Example 7: Age Assessment

[0226] Data from at least 1,000 human subjects were collected, including geographic location (where most of the time is spent), gender, age, race, and genomic mutation frequencies and locations established using the PTA method. Samples were obtained in duplicate from one or more tissues of each subject. A standard curve was generated to associate variables such as geographic location (area of ​​longest residence), gender, age, race, mutation frequency, mutation location, or other data obtained with the age of the subject. The genome of a sample from an unknown age subject was sequenced using the PTA method, and the standard curve was used to determine the age of the individual. If other information about the subject (race, geographic location) is known, this will be used to further improve the prediction.

[0227] Example 8: Identification and diagnosis of clinical bacterial samples

[0228] A cell sample from a subject with a suspected bacterial infection is obtained and single-cell genome sequencing is performed using the PTA method. Mutations identified using the PTA method are compared with mutations that confer resistance to known antibiotics or used to identify bacterial strains. This information is used to select appropriate treatments, such as effective antibiotics.

[0229] Example 9: Identification of microbial species and genes

[0230] Water samples are collected from various sources such as deep sea vents, oceans, mines, streams, lakes, meteorites, glaciers or volcanoes. The samples are passed through a 20 micron pre-filter to remove particulates and then graded into particle size groups such as 3-20 microns, 0.8-3 microns, 0.1-0.8 microns and 50kDa to 0.1 micron. The samples are then processed to isolate single cells, or optionally processed in batches. Genomes, plasmids or other DNA are isolated using standard techniques, processed by the PTA method, and then sequenced. After the genome sequence is reassembled, known species are identified, and unknown species and / or genes are characterized for potential industrial applications.

[0231] Example 10. Measuring the rate of unintended insertions in gene therapy approaches

[0232] Utilize the variant determination sensitivity and accuracy improved by PTA in single cells to quantitatively measure the unexpected insertion rate of the highly sensitive gene therapy method in single cells. This method can detect the insertion of a specific sequence at an unexpected position by detecting the surrounding sequences to determine whether the gene therapy method leads to the insertion or modification of the host genome. The nucleic acid encoding the gene producing the protein is introduced into a viral vector and then delivered to one or more cells in or outside the organism. The virus delivers the nucleic acid to the nucleus, and the nucleic acid is then transcribed into mRNA. After mRNA translation, protein is produced. The cells modified by the gene therapy method are sequenced using the conventional PTA method described in Example 4, and the mutations (mutation frequency and position / pattern) caused by the gene therapy method are detected.

[0233] Example 11. Using PTA to determine CNV in primary cancer cells

[0234] Compared with MDA and recently developed or improved commercial kits, the PTA scheme for SNV and copy number variation (CNV) determination was further validated using primary leukemia cells according to the conventional method of Example 1. The PTA scheme showed further improvement in coverage and remained the most uniform method based on CV calculation at base pair resolution ( Fig.19 ). At all sequencing depths, PTA is still the most sensitive SNV calling method and currently has the highest SNV calling specificity by changing to low temperature lysis. PCR-dependent methods (WGA kit 3, PicoPlex Gold) also still show a decrease in specificity as sequencing depth increases, although this decrease in specificity is significantly improved over MALBAC and previous versions of PicoPlex.

[0235] To evaluate the accuracy of each method in calling CNVs of different sizes, each bam file was subsampled to 300 million reads and the CV ( Figure 5J ). Under each bin, PTA was found to have the lowest CV compared to all other WGA methods ( Figure 5J ). The CV values ​​for both WGA Kit 2 and PicoPlex Gold dropped dramatically as depth increased. This particular leukemia sample had known CNVs at 5q and 11q. As expected, a single copy of chromosome X was detected in both the bulk sample and single cells. CNV analysis revealed that the 5q deletion was clonal, while the 11q alteration was only found in a subset of cells ( Figure 5K , shaded arrow). The bulk data suggest that there may be a deletion at 12p, but it was not called in the bulk samples. Two of the five single cells were found to have CNVs at the same position, suggesting that single-cell CNV analysis may be more sensitive and a better strategy for assessing the percentage of cells with a given copy number variation in a tissue.

[0236] Example 12. Measurement of SNV rate in homologous cells

[0237] Syngeneic cell studies were performed by seeding single CD34+ CB cells into individual wells and subsequently expanding for 5 days ( Fig.16A ). Single cells were then isolated from the culture to compare variant calls with genetically nearly identical cells. In addition, germline, false positive, and somatic variant calls were distinguished using bulk cells as reference ( Fig. 16B Using this approach, and again using a large number of samples as ground truth, the accuracy of variant calls determined using the low-temperature protocol combined with GATK4 genotyping was improved to 99.9% ( Fig. 16C ). In addition, most of these primary cells had similar or improved variant detection sensitivity. However, one cell had significantly reduced variant call sensitivity, which, without being bound by theory, may be a result of artificial manipulation of fragile primary cells. In addition, two cells with higher variant call sensitivity had fewer homozygous somatic variant calls, which may be a result of reduced allele dropout ( Fig. 15B ). False positive variants in these cells tend to have lower allele frequencies, which, without being bound by theory, could be explained by the fact that these rapidly dividing cells are tetraploid in the late S or G2 / M phase of the cell cycle, where only one of the four alleles acquires a replication error ( Figures 17A-17C). Homozygous false positive calls were observed to cluster at specific locations, whereas heterozygous calls did not. Without being bound by theory, this could be the result of loss of one allele at these locations or lack of template denaturation during amplification, which does not appear to be dependent on the GC content of the genomic region ( Figures 18A-18C Most false-positive and somatic variants were classified as heterozygous, consistent with a model in which only one allele was mutated due to replication error or during development, respectively ( Fig.16D ). False-positive and somatic mutation rates were measured in neonatal CD34+ hematopoietic cells and were estimated to be 0.9 and 1.4 per Mb genome, respectively.

[0238] Example 13: Measuring the rate and location of CRISPR off-target activity in single human cells

[0239] From correcting genes that cause or contribute to disease to eradicating currently untreatable infectious diseases, the continued development of genome editing tools shows great promise for improving human health. However, the safety of these interventions remains unclear, as it is not fully understood how these tools interact with and permanently alter other locations in the edited cell genome. Methods have been developed to assess the off-target rates of genome editing strategies, but all tools developed to date interrogate populations of cells together, limiting the ability to measure off-target rates in each cell and cell-to-cell variability, as well as the ability to detect rare editing events that occur in a small number of cells. Single-cell cloning of edited cells has been performed, but cells that acquire lethal off-target editing events can be selected and are impractical for many types of primary cells.

[0240] Using the improved variant calling sensitivity and specificity of PTA, we obtained quantitative measurements of CRISPR-mediated genome editing with specific guide RNA (gRNA) in single cells ( Fig. 20A ). These studies used three cell types: the U20S osteosarcoma cell line, primary hematopoietic CD34+CB cells, and embryonic stem (ES) cells. In addition, two previously described gRNAs were used, one known to be an accurate gRNA (EMX1) and the other known to have high levels of off-target activity (VEGFA). To identify indels with high specificity, variant calling was limited to genomic locations with an exact match to the PAM sequence and a maximum of five mismatches to the protospacer sequence ( Fig.16A ).

[0241] Compared to control cells that received Cas9 alone or were mock-transfected, more off-target indels were observed in VEGFA-edited cells, showing broad cell-to-cell variability, while only a few off-target EMX1 editing events were detected ( Fig. 20B ). We noted that most of the putative false-positive edits seen in control cells were single-base pair insertions. Removal of non-recurrent single-base pair insertions further improved the specificity of indel calls ( Fig.21 Most, but not all, recurrent off-target sites were cell-type specific, further supporting the finding that the conventional chromatin structure of a cell type influences off-target genomic location ( Fig.20D Structural variant (SV) calling was performed to identify SVs induced by genome editing, requiring the regions surrounding both breakpoints to perfectly match the PAM sequence and allowing up to 5 mismatches with the protospacer sequence. An increase in the number of SVs was measured using the VEGFA guide RNA, with only 1 SV detected in EMX1-edited cells and no SVs detected in control cells ( Fig.20E ). Recurrent VEGFA-mediated SVs were detected, some of which were cell type specific, and larger SVs were detected in ES cells ( Fig. 20C ).

[0242] Example 14: Assembling bacterial genomes using PTA

[0243] Oral swabs were obtained and cultured overnight in LB medium. Individual colonies were sorted into 96-well plates as individual samples, and the conventional PTA method of Example 1 was performed on each well to prepare each sample for sequencing. 1-2 million reads were obtained for each sample, and the reads were assembled using SPAdes (a contig-based method). Fig.22A The longest contig data for 10 different bacterial samples are shown. For in silico analysis of sequencing data, contigs for each sample were added in order of decreasing length ( Fig. 22B ). The data of bacterial sample 10 is shown in Fig. 22C Then, the proportion of the total assembly that was assigned to each genus was determined. Contaminant sequences appeared with small fragments of genomic DNA; these can be identified as smaller contigs in the dataset (>5KB, Fig.22D A read pair was considered to be of human origin if both reads aligned to GRCh38 in the GRCh38-contig union reference ( Figures 22E-22F Alternatively, reads were assigned to taxonomic groups using k-mers from a reference database, using an assembly-free approach (e.g., Kraken) for all samples. The results of the read-based approach for bacterial sample 10 are shown in Figure 22G , and is consistent with the contig-based approach.

[0244] Example 15: Preimplantation genetic testing using PTA

[0245] According to the conventional method of Kuznyetsov et al. (2018) PLoS ONE, 13(5): e0197262, 20 cultured embryos (frozen or fresh) were prepared for non-invasive preimplantation genetic screening (NIPGS). Briefly, on the 4th day of culture, each embryo was transferred to fresh Global HP medium containing HSA and cultured under oil until the blastocyst stage was reached (on the 5th or 6th day). After reaching a fully expanded blastocyst, each blastocyst was subjected to a laser-assisted trophectoderm biopsy followed by laser folding to mix the BF with the BCCM. The embryos were then transferred to cryopreservation medium and frozen by vitrification. After the embryos were removed, the combined BCCM and BF samples were collected and frozen at -80°C until testing. After the nucleic acid was extracted from the BCCM / BF sample, the conventional PTA method of Example 1 was performed on the nucleic acid. The genomic DNA library generated by PTA was then analyzed for genetic mutations, such as chromosomal abnormalities.

[0246] Although preferred embodiments of the present invention have been shown and described herein, it will be apparent to those skilled in the art that these embodiments are provided by way of example only. Those skilled in the art will now appreciate multiple variations, changes and substitutions without departing from the present invention. It should be understood that various alternatives to the embodiments of the present invention described herein can be used to implement the present invention. The following claims are intended to define the scope of the present invention, and thus encompass methods and structures within the scope of these claims and their equivalents.

Claims

1. A method for determining a mutation, comprising: a. exposing a cell population to a gene editing method, wherein the gene editing method utilizes an agent configured to effect a mutation in a target nucleic acid molecule; b. separating single cells from the population; c. Providing cell lysates from single cells; d. contacting the cell lysate with at least one amplification primer, at least one nucleic acid polymerase comprising 3'->5' exonuclease activity, and a nucleotide mixture, wherein the nucleotide mixture includes at least one terminator nucleotide that terminates nucleic acid replication by the polymerase, wherein the at least one terminator nucleotide is an α-thiodideoxynucleotide, e. amplifying the target nucleic acid molecule to generate a plurality of terminated amplification products, wherein the replication is performed by strand displacement replication; f. connecting the molecule obtained in step (e) to an adaptor to generate an amplification product library; g. sequencing the amplified product library, and h. Comparing the sequence of the amplified product to at least one reference sequence to identify at least one mutation.

2. The method of claim 1, wherein the at least one mutation is present in the target nucleic acid molecule.

3. The method of claim 1, wherein the at least one mutation is not present in the target nucleic acid molecule.

4. The method of claim 1, wherein the gene editing method comprises the use of CRISPR, TALEN, ZFN, recombinase, meganuclease or viral integration.

5. The method of claim 1, wherein the gene editing method comprises using a gene therapy approach.

6. The method of claim 5, wherein the gene therapy approach is not configured to modify somatic DNA or germline DNA of the cell.

7. The method of claim 1, wherein the reference sequence is a genome.

8. The method of claim 1, wherein the reference sequence is a specificity determining sequence, wherein the specificity determining sequence is configured to bind to the target nucleic acid molecule.

9. The method of claim 8, wherein the at least one mutation is present in a sequence region that differs from the specificity determining sequence by at least 1 base.

10. The method of claim 1, wherein the at least one mutation comprises an insertion, a deletion, or a substitution.

11. The method of claim 1, wherein the reference sequence is a CRISPR RNA (crRNA) sequence.

12. The method of claim 1, wherein the reference sequence is a single guide RNA (sgRNA) sequence.

13. The method of claim 1, wherein the at least one mutation is present in a sequence region that binds to catalytically active Cas9.

14. The method of claim 1, wherein at least some of the amplification products comprise a barcode.

15. The method of claim 1, wherein the method further comprises removing at least one terminator nucleotide from the terminated amplification product prior to ligating to an adaptor.

16. The method of claim 1, wherein the at least one mutation occurs in less than 1% of the cell population.

17. The method of claim 1, wherein the at least one mutation occurs in no more than 0.0001% of the cell population.

18. The method of claim 1, wherein the at least one mutation occurs in no more than 0.01% of the amplified product sequences.

19. The method of claim 1, wherein the at least one mutation is present in a sequence region that is not associated with binding of a DNA repair enzyme.

20. The method of claim 1, wherein the at least one mutation is present in a sequence region not associated with binding of MRE11.

21. The method of claim 1, wherein the method further comprises identifying false positive mutations previously sequenced by another off-target detection method.

22. The method of claim 21, wherein the off-target detection method is computer simulation prediction, ChIP-seq, GUIDE-seq, circle-seq, HTGTS (high-throughput whole-genome translocation sequencing), IDLV (integration-defective lentivirus), Digenome-seq, FISH (fluorescence in situ hybridization) or DISCOVER-seq.

23. The method of claim 1, wherein the single cell is a cancer cell.

24. The method of claim 1, wherein the single cell is a neuron or a glial cell.

25. The method of claim 1, wherein the single cell is a fetal cell.

26. A method for identifying a specificity determining sequence, comprising: a. providing a library of nucleic acids, wherein at least some of the nucleic acids comprise specificity determining sequences; b. performing a gene editing method on at least one cell, wherein the gene editing method comprises contacting the cell with a reagent comprising at least one specificity determining sequence; and c. sequencing the genome of the at least one cell using the method of claim 1 to identify at least one specific determining sequence, wherein the specific determining sequence in contact with the at least one cell is identified, and wherein the at least one specific determining sequence provides minimal off-target mutations.

27. The method of claim 26, wherein the off-target mutation is a synonymous or non-synonymous mutation.

28. The method of claim 26, wherein the off-target mutation exists outside the coding region of the gene.

29. A method for in vivo mutation analysis, comprising: a. performing a gene editing method on at least one cell in a living organism, wherein the gene editing method comprises contacting the cell with a reagent comprising at least one specificity determining sequence; b. separating at least one cell from said organism; and c. Sequencing the genome of the at least one cell using the method of claim 1.

30. The method of claim 29, wherein the method comprises at least two cells.

31. The method of claim 30, further comprising identifying a mutation by comparing the genome of the first cell to the genome of the second cell.

32. The method of claim 31, wherein the first cell and the second cell are from different tissues.

33. A method for predicting the age of a subject, comprising: a. providing at least one sample from the subject, wherein the at least one sample comprises a genome; b. Sequencing the genome using the method described in steps b to h of claim 1 to identify mutations; c. comparing the mutations obtained in step b to a standard reference curve, wherein the standard reference curve relates mutation counts and positions to validated age; as well as d. predicting the age of the subject based on comparison of the mutation with the standard reference curve.

34. The method of claim 33, wherein the standard reference curve is specific for the sex of the subject.

35. The method of claim 33, wherein the standard reference curve is specific to the race of the subject.

36. The method of claim 33, wherein the standard reference curve is specific to a geographic location of the subject where the subject spent a period of their life.

37. The method of claim 33, wherein the subject is less than 15 years old.

38. The method of claim 33, wherein the at least one sample is older than 1000 years.

39. The method of claim 33, wherein at least 5 samples are sequenced.

40. The method of claim 39, wherein the at least five samples are from different tissues.

41. A method for sequencing a microbial or viral genome, comprising: a. obtaining a sample comprising one or more genomes or genome fragments; b. sequencing the sample using the method described in steps b to h of claim 1 to obtain a plurality of sequencing reads; as well as c. Assembling and sorting the sequencing reads to generate the microbial or viral genome.

42. The method of claim 41, wherein the sample comprises genomes from at least ten organisms.

43. The method of claim 41, wherein the sample comprises genomes from at least 100 organisms.

44. The method of claim 41, wherein the sample source is an environment comprising a deep sea vent, ocean, mine, stream, lake, meteorite, glacier, or volcano.

45. The method of claim 41, further comprising identifying at least one gene in the microbial genome.

46. ​​The method of claim 41, wherein the microbial genome corresponds to an uncultured organism.

47. The method of claim 46, wherein the microbial genome corresponds to a symbiotic organism.

48. The method of claim 41, further comprising cloning at least one gene in a recombinant host organism.

49. The method of claim 1, wherein the nucleic acid polymerase is bacteriophage phi29 (Φ29) polymerase, genetically modified phi29 (Φ29) DNA polymerase, Klenow fragment of DNA polymerase I, bacteriophage M2 DNA polymerase, bacteriophage phiPRD1 DNA polymerase, Bst DNA polymerase, Bst large fragment DNA polymerase, exo(-)Bst polymerase, exo(-)Bca DNA polymerase, Bsu DNA polymerase, VentR DNA polymerase, VentR (exo-) DNA polymerase, Deep Vent DNA polymerase, Deep Vent (exo-) DNA polymerase, IsoPol DNA polymerase, DNA polymerase I, Therminator DNA polymerase, T5 DNA polymerase, sequencer, T7 DNA polymerase, T7-sequenase or T4 DNA polymerase.

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