DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Claims Status
Claims 1-20 are pending.
Claim 14 is withdrawn.
Claims 1-13 and 15-20 are currently under examination.
Election/Restrictions
Applicant's election with traverse of Group I (claims 1-13 and 15-20) in the reply filed on 06/10/2025 is acknowledged. The Applicant argues that the traversal is on the ground(s) “that while the Examiner has properly applied the “special technical features” test, it seems she has ignored the administrative instructions directing unity of invention to be considered only in relation to the independent claims. See MPEP, Appendix A1… Claim 14 depends from claim 1 and thus may not properly be characterized as a “separate invention” under the unity of invention standards. For this reason, Applicant respectfully petitions for reconsideration and withdrawal of the outstanding restriction.
As a further matter, Applicant reminds the Examiner that restriction is only proper when there would be a serious search or examination burden to consider the entirety of the claims in a single application. Herein, Applicant submits that the search required for the in vivo method of claim 14 et seg. necessarily overlaps with the search required for the in vitro methods set forth in elected claims 1-13. As such, Applicant respectfully submits that it would not be an undue burden for the Examiner to search and consider the entire claim slate, namely claims 1-14, in a single application. For this additional reason, Applicant respectfully petitions for reconsideration and withdrawal of the restriction between Groups I and II.
This is not found persuasive because the Group I is based on in vitro assays whereas Group II is based on in vivo based assays, which is not the same as Group I, this would require additional search and consideration under 112(a) statute.
The requirement is still deemed proper and is therefore made FINAL.
Priority
This application is a U.S. National phase filed under 35 U.S.C. § 371 claiming benefit to International Patent Application No. PCT/EP2020/079188, filed October 16, 2020, which claims the benefit of priority to European Patent Application No. 19204418.8 filed on October 21, 2019. Acknowledgment is made of applicant' s claim for foreign priority under 35 U.S.C. 119 (a)-(d). The certified copy of EP 19204418.8 has been filed on 04/19/2022. The priority date of claim set filed on 04/19/2022, is determined to be 10/21/2019.
Claim Objections
Claims 8-9 and 11-13 are objected to because of the following informalities:
“is used to enriched” (ln 4) should read “is used to enrich” (Claim 8).
“by first: d1)” (ln 3-4) and “and second d2)” (ln 5-6) should read “further comprises the steps of: d1) … d2)”. Thus, replacing the “by first” with “further comprises the steps of:” and removing the term second (ln5) (Claim 9).
“centre” (ln 8) should read “center” (Claim 11)
“equal or” (ln 10) should read “equal to or” (Claim 12)
“6 or more”(ln 8) should read “6 or more nt” (Claim 13)
“10 or more”(ln 8) should read “10 or more nt” (Claim 13)
Appropriate correction is required.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 11-13 and 19-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed towards an abstract idea of mathematical concepts/computer program using an algorithm and routine and conventional parameter optimization, without significantly more. The claim(s) recite(s) an abstract idea and routine and conventional methods. This judicial exception is not integrated into a practical application because no additional elements integrate the judicial exceptions into a practical application. The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception because no additional elements are considered significantly more than the judicial exceptions.
Claim analysis
The instant claim 11 is directed towards: The method of claim 1, wherein in step e) putative cleavage sites are determined by - dividing the reference genome comprising aligned sequence reads into bins of a defined length; and determining for each bin comprising at least one sequence read start and at least one sequence read end, one or more putative cleavage sites as sites with a local maximum for the sum of sequence read starts and sequence read ends, and optionally minimizing the distance to the centre of the bin; wherein a sequence read start consists of the first 1 to 5 nt and a sequence read end consists of the last 1 to 5 nt of an aligned sequence read.
The dividing the reference genome comprising aligned sequence reads into bins of a defined length; and determining for each bin comprising at least one sequence read start and at least one sequence read end, one or more putative cleavage sites as sites with a local maximum for the sum of sequence read starts and sequence read ends are abstract ideas and considered to be a step requiring computer algorithms.
The instant claim 12 is directed towards: The method of claim 1 wherein in step e) cleavage sites are identified by: e1) dividing the reference genome comprising aligned sequence reads into bins of set sequence length; e2) determining for each bin a read coverage, discarding bins with a read coverage of 0 and combining bins with a read coverage of >0 consecutively, based on the sequence order in the reference genome, into a continuous set of bins; e3) dividing each bin into windows of set width; with a set step size, which is equal or smaller than the width of the windows; e4) determining start, end and background coverage of each window, by grouping, - sequence read starts falling in the window region into a start coverage group; - sequence read ends falling in the window region into an end coverage group; and - sequence reads falling into the window region but not belonging to the start coverage group and the end coverage group into a background coverage group; and summing up for each window the number of reads in the start coverage, end coverage and background coverage group, respectively; e5) determining for each bin comprising at least one sequence read start and at least one sequence read end, one or more putative cleavage sites by maximizing for the sum of start coverage and end coverage and minimizing the distance to the centre of the bin; and e6) excluding false positive cleavage sites; wherein a sequence read start consists of the first 1 to 5 nt and a sequence read end consists of the last 1 to 5 nt of an aligned sequence read.
Steps e1- e6 are abstract ideas and considered to be steps requiring computer algorithms.
Dependent claims 19 and 20 set forth further limitations about the set sequence length, bin, sequence read start and end. The dependent claims are routine and conventional parameter optimization of ranges as discussed in the 35 USC § 103 rejections stated below.
The instant claim 13 is directed towards: The method of claim 1, wherein false positive cleavage sites are excluded by selecting only putative cleavage sites with: 1. a ratio of background coverage to signal coverage, which does not exceed a threshold of about 0.5; and/or 2. a ratio of start coverage to end coverage at the putative cleavage site, falling within a numerical range between about 1/5 and 5/1; and/or 3. a minimum site coverage of 6 or more; and/or 4. a minimum bin coverage of 10 or more.
The ratio of background coverage to signal coverage is an abstract idea and considered to be a step requiring computer algorithms.
According to the 2019 Patent Eligibility Guidance an initial two step analysis is required for determining statutory eligibility.
Step 1. Is the claim directed to a process, machine, manufacture, or composition of matter? In the instant case, the Step 1 requirement is satisfied as the claims are directed towards a process.
Step 2A Prong one. Does the claim recite a law of nature, a natural phenomenon or an abstract idea? Yes, abstract ideas.
Regarding claim 11, The dividing the reference genome comprising aligned sequence reads into bins of a defined length; and determining for each bin comprising at least one sequence read start and at least one sequence read end, one or more putative cleavage sites as sites with a local maximum for the sum of sequence read starts and sequence read ends are abstract ideas and considered to be a step requiring computer algorithms.
Regarding claim 12, steps e1- e6 are abstract ideas and considered to be steps requiring computer algorithms.
Regarding claim 13, the ratio of background coverage to signal coverage is an abstract idea and considered to be a step requiring computer algorithms
Step 2A prong two. Does the claim recite additional elements that integrate the judicial exception into a practical application? No, there are no additional steps that integrate the claims into a practical application.
Step 2B. Does the claim recite additional elements that are significantly more than the judicial exceptions? No, there are no additional elements that are significantly more than the judicial exceptions.
Regarding claim 11-13, the claims are similar to the sequence analysis of off-target cleavage sites of that of Zhu et al. (“Zhu”; (2017). GUIDEseq: a bioconductor package to analyze GUIDE-Seq datasets for CRISPR-Cas nucleases. BMC genomics, 18(1), 379.)
Zhu discloses an open source, open development software suite, GUIDEseq, for GUIDE-seq data analysis and annotation as a Bioconductor package in R. The GUIDEseq package provides a flexible platform with more than 60 adjustable parameters for the analysis of datasets associated with custom nuclease applications. These parameters allow data analysis to be tailored to different nuclease platforms with different length and complexity in their guide and PAM recognition sequences or their DNA cleavage position. They also enable users to customize sequence aggregation criteria and vary peak calling thresholds that can influence the number of potential off-target sites recovered. GUIDEseq also annotates potential off-target sites that overlap with genes based on genome annotation information, as these may be the most important off-target sites for further characterization. In addition, GUIDEseq enables the comparison and visualization of off-target site overlap between different datasets for a rapid comparison of different nuclease configurations or experimental conditions. For each identified off-target, the GUIDEseq package outputs mapped GUIDE-Seq read count as well as cleavage score from a user specified off-target cleavage score prediction algorithm permitting the identification of genomic sequences with unexpected cleavage activity. (Abstract)
Dependent claims 19 and 20 set forth further limitations about the set sequence length, bin, sequence read start and end. The dependent claims are routine and conventional parameter optimization of ranges as discussed in the 35 USC § 103 rejections stated below, which are all routine and conventional parameters that can be adjusted during analysis based on Joung et al. (“Joung”; US 2017/0088833 A1, March 30, 2017) in view of Zhu et al. (“Zhu”; (2017). GUIDEseq: a bioconductor package to analyze GUIDE-Seq datasets for CRISPR-Cas nucleases. BMC genomics, 18(1), 379.) and Liao et al. (“Liao”; (2014). featureCounts: an efficient general purpose program for assigning sequence reads to genomic features. Bioinformatics (Oxford, England), 30(7), 923–930.), and Kim et al. (“Kim”; (2018). DIG-seq: a genome-wide CRISPR off-target profiling method using chromatin DNA. Genome research, 28(12), 1894–1900.).
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claims 1-7, 10 and 15-17 are rejected under 35 U.S.C. 103 as being unpatentable over Joung et al. (“Joung”; US 2017/0088833 A1, March 30, 2017).
Claim interpretation: Regarding claim 1, “affinity adapter” is interpreted as any adapter in close proximity to the fragment. Regarding claim 1, “target specific programmable nucleases” are interpreted as any nuclease that can be engineered to specific target sites.
Joung discloses sensitive, unbiased methods for genome-wide detection of potential CRISPR-Cas9 off-target cleavage sites from cell type-specific genomic DNA samples. (Abstract)
Regarding claim 1 steps (a-c), Joung teaches a method comprising “a novel cell-free strategy that enables highly efficient selective enrichment of nuclease-cleaved genomic DNA, which can then be used for high-throughput sequence and genomic off-target cleavage site discovery. …CIRCLE-seq is based on the principle of generating a starting library of randomly sheared genomic DNA fragments whose DNA ends are protected in a way that prevents any subsequent ligation of a sequencing adapter. …this population of molecules is created by a novel unbiased … method followed by exonuclease treatment to degrade any remaining residual linear fragments (FIG. 2) …genomic DNA molecules is then treated with an engineered nuclease of choice. Any DNA fragments harboring sites cleaved by this nuclease will be linearized, thereby releasing two available DNA ends to which a sequencing adapter can be ligated. Linearized, adapter-ligated fragments are subsequently amplified by PCR for high-throughput sequencing. (Para. 30). Thus, Joung teaches A method for detecting off-target sites of one or more target-specific programmable nucleases in a genome in vitro comprising the steps of:(a) providing an input sample comprising genomic DNA, randomly fragmenting the genomic DNA into dsDNA fragments, ligating a blocking adapter to the ends of the dsDNA fragments and removing dsDNA fragments comprising ends are not end-blocked to prepare purified end-blocked dsDNA fragments; (b) preparing a cleaved and amplified DNA library of dsDNA fragments, by bl) cleaving the purified end-blocked dsDNA fragments ,with one or more target-specific programmable nucleases to obtain cleaved dsDNA fragments; b2) ligating an affinity adapter to cleavage sites of cleaved dsDNA fragments to obtain affinity-adapter-modified dsDNA fragments; b3) enriching for affinity-adapter-modified dsDNA fragments using the affinity adapter to obtain enriched affinity-adapter-modified dsDNA fragments; and b4) amplifying enriched affinity-adapter-modified dsDNA fragments by PCR amplification to obtain a cleaved and amplified DNA library of dsDNA fragments and (c) performing a sequencing of the cleaved and amplified DNA library of dsDNA fragments to obtain sequence reads;
Regarding claim 1 step (d), Joung teaches a method wherein “align … to the genome” Thus, Joung teaches a method comprising: (d) aligning the sequence reads to a reference genome to obtain aligned sequence reads.
Regarding claim 1 step (e), Joung teaches a method comprising “detects virtually all off-target cleavage sites” (Para. 28) and “dramatically increased the signal-to-noise ratio resulting from the CIRCLE-seq method and reduced the probability of false positive calls” (Para. 40). Joung teaches a method comprising “Paired-end reads were merged and then mapped… The start mapping positions of reads that map in the expected orientation with mapping quality ≧50 were tabulated and genomic intervals that are enriched in nuclease-treated samples were identified. The interval and 20-bp of flanking reference sequence on either side was searched for potential nuclease-induced off-target sites ...” (Para. 93). “Paired-end reads” is interpreted as two DNA sequences obtained from opposite ends of the same DNA fragment thus the start and stop. Thus, Joung teaches a method comprising: (e) identifying cleavage sites, by determining putative cleavage sites and excluding false positive cleavage sites, wherein putative cleavage sites are determined by locating sequence regions in the reference genome where both sequence read starts and sequence read ends of aligned sequence reads coincide, and identifying putative cleavage sites as the sites in these sequence regions where sequence read starts and sequence read ends meet.
Regarding claim 2, Joung teaches a method wherein “Input DNA (0.1-5 ug)” (Pg. 17, left column Protocol 1). Thus, Joung teaches a method wherein the input sample comprises less than 1 ug of genomic DNA.
Regarding claim 3, Joung teaches a method wherein “preparing a library of … double-stranded DNA fragments. The methods can include providing dsDNA, e.g., genomic DNA (gDNA) … randomly shearing the DNA to a defined average length, … to provide a population of DNA fragments… ligating to the ends of the fragments a stem-loop adapter … to prepare a population of ligated linear dsDNA fragments; contacting the library with an exonuclease …to degrade any remaining linear fragments with unligated ends, to produce a purified population of ligated linear dsDNA fragments; contacting the library with enzymes that nick the ligated dsDNA fragments … to nick the DNA … incubating the nicked linear dsDNA fragments under conditions sufficient to promote … purifying the ligated fragments … thereby preparing a library of covalently closed fully circular double-stranded DNA fragments. (Para. 7). “fully circular double-stranded DNA fragments” is interpreted as end-blocked. Thus, Joung teaches a method wherein step a) comprises a1) randomly fragmenting the genomic DNA to a defined length to provide dsDNA fragments; a2) protecting the ends of the dsDNA fragments by ligating a blocking adapter to obtain end-blocked dsDNA fragments are optionally obtained by: 1) preparing the dsDNA fragments for blocking adapter ligation; and 2) ligating a blocking adapter to ends of dsDNA fragments, to obtain end-blocked dsDNA fragments; and a3) contacting the sample comprising the end-blocked dsDNA fragments with one or more exonucleases to remove dsDNA fragments are not end-blocked to obtain purified end-blocked DNA fragments.
Regarding claim 4, Joung teaches a method wherein “The adapters are preferably modified” (Para. 53) and “The adapters can also include one or more additional modifications” (Para. 54). Joung teaches a method wherein “Circle-SEQ … prevents any subsequent ligation” and “Linearized, adapter-ligated fragments” (Para 38). “Linearized, adapter-ligated fragments” is interpreted as cleavage was prevented at the adapter-ligated ends. Thus, Joung teaches a method wherein the blocking adapter comprises one or more modifications, which after ligation of the blocking adapter to a dsDNA fragment, prevent ligation of the end to which the blocking adapter is ligated to the dsDNA fragment and one or more of modifications, which after ligation of the blocking adapter to a dsDNA fragment, prevent exonuclease cleavage of the dsDNA fragment from the end to which the blocking adapter is ligated to the dsDNA fragment.
Regarding claim 5, Joung teaches a method wherein “the engineered nuclease is selected from the group consisting of meganucleases, MegaTALs, zinc-finger nucleases, transcription activator effector-like nucleases (TALEN), Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR)/Cas RNA-guided nucleases (CRISPR/Cas RGNs), and FokI-dCas9 fusions (RNA-guided FokI nuclease)” (Para. 16). Thus, Joung teaches a method wherein in step b1) the one or more target-specific programmable nucleases is selected from the group consisting of: Transcription Activator-Like Effector Nucleases (TALEN), zinc finger nucleases (ZFN), meganucleases, megaTAL, Fokl-dCas9, Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR)/Cas RNA-guided nucleases (CRISPR/Cas RGN) and variants thereof, Argonaute-family protein-based DNA- guided DNA nucleases and variants thereof, and a combinations thereof.
Regarding claim 6, Joung teaches a method wherein “Annealed Hairpin Adapter” (Para.124). “Annealed Hairpin Adapter” is interpreted as comprising dsDNA. Thus, Joung teaches a method wherein the blocking adapter and/or the affinity adapter are dsDNA-based adapters, and further wherein the blocking adapter and/or the affinity adapters comprise a primer site compatible for use in PCR priming.
Regarding claim 7, Joung teaches a method wherein “the hairpin adapters is biotinylated. The biotin can be anywhere internal to the hairpin adapters” and “physically pulled down and enriched by using the biotin, e.g., by binding to streptavidin-coated magnetic beads” (Para. 54). Thus, Joung teaches a method wherein the affinity adapter is a dsDNA-based adapter comprising one or more biotin or biotin-based modifications and wherein in step b3) streptavidin or a variant thereof, optionally immobilized on magnetic beads, is used as an affinity adapter binding molecule to enrich for cleaved and affinity-adapter-modified dsDNA fragments.
Regarding claim 10, Joung teaches a method wherein “prepared from the same source of genomic DNA (human U2OS cells)” (Para. 26) and “reference human genome” (Para. 30). Thus, Joung teaches a method wherein the genomic DNA is human genomic DNA and wherein the reference genome is a human reference genome.
Regarding claims 15-16, Joung teaches a method wherein “Input DNA (0.1-5 ug)” (Pg. 17, left column Protocol 1). “Less than 800 ng” is interpreted as being comprised in “0.1-5 ug”. “Less than 600 ng” is interpreted as being comprised in “0.1-5 ug” Thus, Joung teaches a method wherein the input sample is less than 800 ng; wherein the input sample is less than 600 ng.
Regarding claim 17, Joung teaches a method wherein “the engineered nuclease is selected from the group consisting of meganucleases, MegaTALs, zinc-finger nucleases, transcription activator effector-like nucleases (TALEN), Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR)/Cas RNA-guided nucleases (CRISPR/Cas RGNs), and FokI-dCas9 fusions (RNA-guided FokI nuclease)” (Para. 16). Thus, Joung teaches a method wherein the one or more target-specific programmable nucleases comprise one or more CRISPR/Cas RGN, wherein the Cas endonuclease of the CRISPR/Cas RGN is selected from the group consisting of Cas9 endonuclease, a variant of Cas9 endonuclease, Cpfl endonuclease, and a variant of Cpfl endonuclease.
Claims 8-9 and 18 are rejected under 35 U.S.C. 103 as being unpatentable over Joung et al. (“Joung”; US 2017/0088833 A1, March 30, 2017) in view of Frock et al. (“Frock; (2015). Genome-wide detection of DNA double-stranded breaks induced by engineered nucleases. Nature biotechnology, 33(2), 179-186.).
The teachings of Joung are documented above in the rejection of claims 1-7, 10 and 15-17 under 35 U.S.C. 103. Claims 8, 9, 18 depend on claim 1.
Frock discloses a linear amplification–mediated modification of a previously published high-throughput, genome-wide, translocation sequencing (HTGTS) method that robustly detects DNA double-stranded breaks (DSBs) generated by engineered nucleases across the human genome based on their translocation to other endogenous or ectopic DSBs. HTGTS with different Cas9: sgRNA or TALEN nucleases revealed off-target hotspot numbers for given nucleases that ranged from a few or none to dozens or more and extended the number of known off-targets for certain previously characterized nucleases more than tenfold. We also identified translocations between bona fide nuclease targets on homologous chromosomes, an undesired collateral effect that has not been described previously. Finally, HTGTS confirmed that the Cas9D10A paired nickase approach suppresses off-target cleavage genome-wide. (Abstract)
Regarding claim 8, Frock teaches a method comprising the steps illustrated in Figure 1 (Figure 1- see highlighted figure below).
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Thus, Frock teaches a method, wherein step b4) to obtain the cleaved and amplified DNA library of dsDNA fragments comprises a two-step PCR amplification wherein, 1. a first PCR amplification step for linear PCR amplification is used to enriched affinity-adapter-modified dsDNA fragments bound via an adapter binding molecule to a solid support as a template and an affinity-adapter-specific primer; and 2. after the first step a second PCR amplification step, is performed after removal of enriched affinity adapter modified dsDNA fragments bound via adapter binding molecule to the solid support from the reaction mix, at which point a blocking-adapter-specific primer is added as a second primer.
Regarding claim 9 and 18, Frock teaches a method wherein “adaptor ligation” (Pg. 9, HTGTS, Para. 2), “adaptor sequence trimmed” and “Reads were mapped to the hg19” (Pg. 9, Sequence analysis and hotspot identification, Para. 1). Thus, Frock teaches a method wherein in step d) the sequence reads are aligned to a reference genome to obtain aligned sequence reads, by first d1) trimming off blocking adapter, affinity adapter, and optional sequencing adapter sequence from sequence reads to obtain trimmed sequence reads; and second d2) mapping the trimmed sequence reads to a reference genome to obtain aligned sequence reads.
Therefore, it would have been obvious to someone of ordinary skill in the art before the effective filing date of the claimed invention to have modified the method of detecting off-target sites of programable target specific nucleases as taught by Joung to incorporate the method comprising two PCR amplification steps to enrich and add incorporate a blocking specific primer and method of trimming the adapter from the sequence reads and aligning the trimmed reads to a reference genome using Hg19 as taught by Frock and provide a method of systematically processing and aligning reads to a reference. Doing so would improve sensitive and unbiased genome-wide methods for the detection of off-target cleavage events and allow for someone skilled in the art to process the reads and align to the same reference.
Claim 11 is rejected under 35 U.S.C. 103 as being unpatentable over Joung et al. (“Joung”; US 2017/0088833 A1, March 30, 2017) in view of Zhu et al. (“Zhu”; (2017). GUIDEseq: a bioconductor package to analyze GUIDE-Seq datasets for CRISPR-Cas nucleases. BMC genomics, 18(1), 379.).
The teachings of Joung are documented above in the rejection of claims 1-7, 10 and 15-17 under 35 U.S.C. 103. Claims 11 depends on claim 1.
Zhu discloses an open source, open development software suite, GUIDEseq, for GUIDE-seq data analysis and annotation as a Bioconductor package in R. The GUIDEseq package provides a flexible platform with more than 60 adjustable parameters for the analysis of datasets associated with custom nuclease applications. These parameters allow data analysis to be tailored to different nuclease platforms with different length and complexity in their guide and PAM recognition sequences or their DNA cleavage position. They also enable users to customize sequence aggregation criteria and vary peak calling thresholds that can influence the number of potential off-target sites recovered. GUIDEseq also annotates potential off-target sites that overlap with genes based on genome annotation information, as these may be the most important off-target sites for further characterization. In addition, GUIDEseq enables the comparison and visualization of off-target site overlap between different datasets for a rapid comparison of different nuclease configurations or experimental conditions. For each identified off-target, the GUIDEseq package outputs mapped GUIDE-Seq read count as well as cleavage score from a user specified off-target cleavage score prediction algorithm permitting the identification of genomic sequences with unexpected cleavage activity. (Abstract)
Regarding claim 11, Zhu teaches a method "All alignment filtering criteria have a default setting but can be easily adjusted by users. Zhu teaches a method wherein “Unique putative cleavage sites … user-defined sliding window of a specific sequence length" (Pg. 4 , Col. 1, Para.1-2) and "sequencing reads are then aggregated within a defined window and peaks that are potential off target sites are identified" (Pg. 3 , Col. 1, Para. 2). Zhu teaches a method wherein "bin sequencing reads" (Pg. 3 , Col. 2, Para. 2). Zhu teaches a method wherein “The data analysis parameters permit detailed adjustment of the read filtering criteria, peak-calling parameters (read aggregation window size and coverage threshold), and peak merging criteria” (Pg. 3 , Col. 1, Para. 3). Zhu teaches a method wherein “For the purposes of peak calling, unique paired-end reads are condensed into single-base genomic ranges” (Pg. 4, Figure 2 legend). The “window” is interpreted as the division of a genome into smaller segments, also interpreted by the term “bin”. “Peaks” are interpreted as local maximum. “Paired end” is interpreted as comprising start and stop sequence reads of the original DNA. “minimizing the distance to the centre of the bin; wherein a sequence read start consists of the first 1 to 5 nt and a sequence read end consists of the last 1 to 5 nt of an aligned sequence read” is interpreted as optional. Thus, Zhu teaches a method wherein wherein in step e) putative cleavage sites are determined by - dividing the reference genome comprising aligned sequence reads into bins of a defined length; and determining for each bin comprising at least one sequence read start and at least one sequence read end, one or more putative cleavage sites as sites with a local maximum for the sum of sequence read starts and sequence read ends, and optionally minimizing the distance to the centre of the bin; wherein a sequence read start consists of the first 1 to 5 nt and a sequence read end consists of the last 1 to 5 nt of an aligned sequence read.
Therefore, it would have been obvious to someone of ordinary skill in the art before the effective filing date of the claimed invention to have modified the method of detecting off-target sites of programable target specific nucleases as taught by Joung to incorporate the method adjusting parameters for the analysis of sequencing datasets associated with custom nucleases as taught by Zhu and provide a method of identifying cleavage sites by determining putative cleavage sites excluding false positive cleavage sites. Doing so would allow someone skilled in the art to facilitate sensitive and unbiased detection of off-target cleavage events by using flexible bioinformatics analysis tools for processing, analysis, and annotation.
Claims 12 and 19-20 are rejected under 35 U.S.C. 103 as being unpatentable over Joung et al. (“Joung”; US 2017/0088833 A1, March 30, 2017) in view of Zhu et al. (“Zhu”; (2017). GUIDEseq: a bioconductor package to analyze GUIDE-Seq datasets for CRISPR-Cas nucleases. BMC genomics, 18(1), 379.) as applied to claim 11 above, and further in view of Liao et al. (“Liao”; (2014). featureCounts: an efficient general purpose program for assigning sequence reads to genomic features. Bioinformatics (Oxford, England), 30(7), 923–930.).
The teachings of Joung are documented above in the rejection of claims 1-7, 10 and 15-17 under 35 U.S.C. 103. Claims 12 and 19-20 depend on claim 1. Claim 19 depends on claim 12. Claim 20 depends on claim 19. Joung does not specifically teach the limitations of claim 12 and 19-20.
Zhu discloses an open source, open development software suite, GUIDEseq, for GUIDE-seq data analysis and annotation as a Bioconductor package in R. The GUIDEseq package provides a flexible platform with more than 60 adjustable parameters for the analysis of datasets associated with custom nuclease applications. These parameters allow data analysis to be tailored to different nuclease platforms with different length and complexity in their guide and PAM recognition sequences or their DNA cleavage position. They also enable users to customize sequence aggregation criteria and vary peak calling thresholds that can influence the number of potential off-target sites recovered. GUIDEseq also annotates potential off-target sites that overlap with genes based on genome annotation information, as these may be the most important off-target sites for further characterization. In addition, GUIDEseq enables the comparison and visualization of off-target site overlap between different datasets for a rapid comparison of different nuclease configurations or experimental conditions. For each identified off-target, the GUIDEseq package outputs mapped GUIDE-Seq read count as well as cleavage score from a user specified off-target cleavage score prediction algorithm permitting the identification of genomic sequences with unexpected cleavage activity. (Abstract)
Regarding claims 12 and 19-20, Zhu teaches a method "All alignment filtering criteria have a default setting but can be easily adjusted by users. Zhu teaches a method wherein “Unique putative cleavage sites … user-defined sliding window of a specific sequence length" (Pg. 4 , Col. 1, Para.1-2) and "sequencing reads are then aggregated within a defined window and peaks that are potential off target sites are identified" (Pg. 3 , Col. 1, Para. 2). Zhu teaches a method wherein "bin sequencing reads" (Pg. 3 , Col. 2, Para. 2). Zhu teaches a method wherein “The data analysis parameters permit detailed adjustment of the read filtering criteria, peak-calling parameters (read aggregation window size and coverage threshold), and peak merging criteria” (Pg. 3 , Col. 1, Para. 3). Zhu teaches a method wherein “Redundant reads are discarded. For the purposes of peak calling, unique paired-end reads are condensed into single-base genomic ranges” (Pg. 4, Figure 2 legend). Zhu teaches a method wherein “paired reads that are too far away from each other, or that are of insufficient length or mapping quality are removed” (Pg. 4 Col. 1, Para. 1). Zhu teaches a method wherein “The height of each … peak equals the sum of the unique putative cleavage sites within the window, and its position is defined by the center of the 20 base window. Peak calling also filters out clusters with a small number of putative cleavage sites or a high pvalue calculated from a Poisson distribution based on the local background estimate (default to a 5 kb window)” (Pg. 4, Col. 1, Para.2). Zhu teaches method wherein start, end and background coverage is illustrated in Figures 2-3. The “window” is interpreted as the division of a genome into smaller segments, also interpreted by the term “bin”. “user-defined sliding window” is interpreted as dividing the sequence segments into any length/width desired to encompass a window, bin, and/or set step size. “Peaks” are interpreted as local maximum. “Paired end” is interpreted as comprising start and stop sequence reads of the original DNA. “single-base genomic ranges” is interpreted as comprising at least one base.
Thus, Zhu teaches a method wherein in step e) cleavage sites are identified by: e1) dividing the reference genome comprising aligned sequence reads into bins of set sequence length e2) determining for each bin a read coverage, discarding bins with a read coverage of 0 and combining bins with a read coverage of >0 consecutively, based on the sequence order in the reference genome, into a continuous set of bins; e3) dividing each bin into windows of set width; e4) determining start, end and background coverage of each window, by grouping, - sequence read starts falling in the window region into a start coverage group; - sequence read ends falling in the window region into an end coverage group; and - sequence reads falling into the window region but not belonging to the start coverage group and the end coverage group into a background coverage group; and summing up for each window the number of reads in the start coverage, end coverage and background coverage group, respectively; e5) determining for each bin comprising at least one sequence read start and at least one sequence read end, one or more putative cleavage sites by maximizing for the sum of start coverage and end coverage and minimizing the distance to the centre of the bin; and e6) excluding false positive cleavage sites.
The following limitations are considered as optimized working ranges: wherein a sequence read start consists of the first 1 to 5 nt and a sequence read end consists of the last 1 to 5 nt of an aligned sequence read (e6 of claim 12) ; wherein said set sequence length is at least about 100 nt; each bin is divided into windows of 4 nt with a set step size of 2 nt; - a sequence read start consists of the first 2 to 4 nt; and a sequence read end consists of the last 2 to 4 nt of an aligned sequence read (Claim 19); wherein the sequence read start consists of the first 3 nt and the sequence read end consists of the 3 nt of an aligned sequence read (Claim 20). The MPEP recites, “Where the general conditions of a claim are disclosed in the prior art, it is not inventive to discover the optimum or workable ranges by routine experimentation." (see MPEP 2144.05).
Joung and Zhu do not specifically teach the limitation of “dividing each bin of a set width with a set step size, which is equal or smaller than the width of the windows” in claim 12.
Liao discloses “…The process of counting reads is called read summarization. Read summarization is required for a great variety of genomic analyses but has so far received relatively little attention in the literature. We present featureCounts, a read summarization program suitable for counting reads generated from either RNA or genomic DNA sequencing experiments. featureCounts implements highly efficient chromosome hashing and feature blocking techniques. It is considerably faster than existing methods (by an order of magnitude for gene-level summarization) and requires far less computer memory. It works with either single or paired-end reads and provides a wide range of options appropriate for different sequencing applications…” (Abstract)
Regarding claim 12, Liao teaches an end read method wherein “the use of a hierarchical data structure (features within blocks within bins) is a key component of the featureCounts algorithm” (Pg. 6, Genome bins and feature blocks, Para. 2).
Therefore, it would have been obvious to someone of ordinary skill in the art before the effective filing date of the claimed invention to have modified the method of detecting off-target sites of programable target specific nucleases as taught by Joung to incorporate the method adjusting parameters for the analysis of sequencing datasets associated with custom nucleases as taught by Zhu and method of dividing each bin into a smaller step size as taught by Liao and provide a method of identifying cleavage sites without false positive cleavage sites. Doing so would improve sensitivity the methods for the detection of off-target cleavage events and allow for someone skilled in the art to rapidly facilitate read assignment by quickly narrowing down the genomic region.
Claim 13 is rejected under 35 U.S.C. 103 as being unpatentable over Joung et al. (“Joung”; US 2017/0088833 A1, March 30, 2017) in view of Kim et al. (“Kim”; (2018). DIG-seq: a genome-wide CRISPR off-target profiling method using chromatin DNA. Genome research, 28(12), 1894–1900.).
The teachings of Joung are documented above in the rejection of claims 1-7, 10 and 15-17 under 35 U.S.C. 103. Claims 13 depends on claim 1. Joung does not specifically teach the limitations of claim 13.
Kim discloses whether and how CRISPR-Cas9 on-target and off-target activities are affected by chromatin in eukaryotic cells, we first identified a series of identical endogenous DNA sequences present in both open and closed chromatin regions and then measured mutation frequencies at these sites in human cells using Cas9 complexed with matched or mismatched sgRNAs. Unlike matched sgRNAs, mismatched sgRNAs were highly sensitive to chromatin states, suggesting that off-target but not on-target DNA cleavage is hindered by chromatin. We next performed Digenome-seq using cell-free chromatin DNA (now termed DIG-seq) and histone-free genomic DNA in parallel and found that only a subset of sites, cleaved in histone-free DNA, were cut in chromatin DNA, suggesting that chromatin can inhibit Cas9 off-target effects in favor of its genome-wide specificity in cells. (Abstract)
Regarding claim 13, Kim teaches a method wherein “the cutoff value was determined experimentally. Briefly, we counted the number of sites whose DNA cleavage scores were over a cutoff value that ranged from 0.0001 to 10... We chose a cutoff value of 0.1 because WGS data obtained using intact genomic DNA, which served as a negative control, did not yield any false-positive sites with this cutoff score (Digenome v. 2.0)” (Pg. 1899, WGS and Digenome sequencing, Para. 1). “and/or” is interpreted as introducing optional limitations. Thus, Kim teaches a method wherein false positive cleavage sites are excluded by selecting only putative cleavage sites with: 1. a ratio of background coverage to signal coverage, which does not exceed a threshold of about 0.5; and/or 2. a ratio of start coverage to end coverage at the putative cleavage site, falling within a numerical range between about 1/5 and 5/1; and/or 3. a minimum site coverage of 6 or more; and/or 4. a minimum bin coverage of 10 or more.
Therefore, it would have been obvious to someone of ordinary skill in the art before the effective filing date of the claimed invention to have modified the method of detecting off-target sites of programable target specific nucleases as taught by Joung to incorporate the method determining a background to signal ratio threshold cutoff and using the determined threshold cutoff to avoid detection of false positive cleavage sites as taught by Kim and provide a method of excluding false positive cleavage sites. Doing so would decrease the number of false positive cleavage sites identified when trying to determine an unbiased assessment off-target cleavage sites.
Conclusion
No claims are in condition for allowance.
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/KENDRA R VANN-OJUEKAIYE/Examiner, Art Unit 1682
/WU CHENG W SHEN/Supervisory Patent Examiner, Art Unit 1682