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 .
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.
Claims Status
Claims 1-20 are pending.
Claims 1-20 are examined below.
Priority
As detailed on the 03/09/2022 filing receipt, this application claims priority to as early as 01/27/2021.
Information Disclosure Statement
No Information Disclosure Statements have been filed.
Drawings
The drawings filed 01/27/2022 are accepted.
Claim Rejections - 35 USC § 112
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claims 1-20 are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
Claims 1, 12 and 20 recite “determine whether the candidate guide maps to an expressed sequence and keeping the candidate guide for further selection if it maps to an expressed sequence.” The relationship between the 2 instances of “expressed sequence” is unclear. It is unclear whether the second instance of “expressed sequence” is the same “expressed sequence” as the first instance.
Claims 1, 12 and 20 recite “determine whether the candidate guide meets a common SNP overlap threshold and keeping the candidate guide for further selection if it meets an SNP overlap threshold.” The relationship between “a common SNP overlap threshold” and “an SNP overlap threshold” is unclear. It is unclear whether “a common SNP overlap threshold” is the same “an SNP overlap threshold.”
Claims 1, 12 and 20 recite “determine whether the candidate guide has a precomputed prediction of editing outcomes and keeping the candidate guide for further selection if there is a precomputed prediction of editing outcomes.” The relationship between the 2 instances of is “precomputed prediction of editing outcomes” is unclear. It is unclear whether the second instance of “precomputed prediction of editing outcomes” is the same as the first instance.
Dependent claims are rejected for depending on rejected claims.
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 1-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Analysis of claims in Step 1.
Step 1: Are the claims directed to a 101 process, machine, manufacture, or composition of matter (MPEP 2106.03)?
Independent claim 1 is directed to a 101 machine or manufacture, here a "system," with non-transitory elements such as "a memory; and a processor"
Independent claim 12 is directed to a 101 process, here a "method of selecting CRISPR guides," with process steps such as "determining…, generating…"
Independent claim 20 is directed to a 101 machine or manufacture, here a non-transitory "computer-readable storage medium."
[Step 1: claims 1-20: YES]
In accordance with MPEP § 2106, claims found to recite statutory subject matter (Step 1: YES) are then analyzed to determine if the claims recite any concepts that equate to an abstract idea, law of nature or natural phenomenon (Step 2A, Prong 1). In the instant application, the claims recite the following limitations that equate to an abstract idea:
Mental processes recited include:
Claims 1, 12 and 20 recite: " determine a transcript support level of a candidate guide of the multiplicity of candidate guides and keeping the candidate guide for further selection if it meets a transcript support threshold; determine whether the candidate guide targets a consensus sequence of a target gene and keeping the candidate guide for further selection if it meets a consensus threshold; determine which exon of the target gene is targeted and keeping the candidate guide for further selection if it meets a first exon threshold; determine whether the candidate guide targets a primary transcript and keeping the candidate guide for further selection if it meets a primary transcript threshold; determine whether the candidate guide targets a common isoform and keeping the candidate guide for further selection if it meets a common isoform threshold; determine whether the candidate guide has a precomputed prediction of editing outcomes and keeping the candidate guide for further selection if there is a precomputed prediction of editing outcomes; determine whether the candidate guide maps to an expressed sequence and keeping the candidate guide for further selection if it maps to an expressed sequence; determine a fraction of gene expression attributable to targeted transcripts for the candidate guide and keeping the candidate guide for further selection if it meets a fraction of gene expression attributable to targeted transcripts threshold; determine whether the candidate guide meets a common SNP overlap threshold and keeping the candidate guide for further selection if it meets an SNP overlap threshold; determine which exon of the target gene is targeted and keeping the candidate guide for further selection if it meets a guide per exon threshold; determine whether the candidate guide overlaps a selected guide and keeping the candidate guide for further selection if it meets a guide overlap threshold; determine a predicted frameshift percentage for the candidate guide and keeping the candidate guide for further selection if it meets a predicted frameshift percentage threshold; determine a GC content of the candidate guide and keeping the candidate guide for further selection if it meets a minimum GC content threshold; determine the GC content of the candidate guide and keeping the candidate guide for further selection if it meets a maximum GC content threshold; determine an off-target score for the candidate guide and keeping the candidate guide for further selection if it meets an off-target score threshold; determine a position where the candidate guide targets a coding sequence and keeping the candidate guide for further selection if it meets a coding sequence position threshold; and responsive to the candidate guide meeting the thresholds, select the candidate guide as a selected CRISPR guide." The recited determining and selecting are acts of evaluating, analyzing and judging data that could be practically performed in the human mind and/or with pen and paper.
Claims 2 and 13 recite: "…to select the candidate guide as the selected guide if it meets all the thresholds and has the highest predicted frameshift percentage of the candidate guides." Selecting is an act of evaluating, analyzing and judging data that could be practically performed in the human mind and/or with pen and paper.
Claims 3 and 14 recite: "…to keep the candidate guide for further selection if it meets a threshold for targeting a primary transcript or a main isoform of a transcript." Selecting is an act of evaluating, analyzing and judging data that could be practically performed in the human mind and/or with pen and paper.
Claims 4 and 15 recite: "... to reject the candidate guide for further selection if it targets a first exon of a CDS." Rejecting the guide from further selection is an act of evaluating, analyzing and judging data that could be practically performed in the human mind and/or with pen and paper.
Claims 5 and 16 recite: "... to adjust one or more thresholds and iterate the determination and the selection from the candidate guides until a desired number of selected guides are selected." Adjusting, determining and selecting are acts of evaluating, analyzing and judging data that could be practically performed in the human mind and/or with pen and paper.
Mathematical concepts recited include:
Claims 1, 12 and 20 recite: "…predicted frameshift percentage threshold." Percentage is a mathematical concept and/or formula.
Claims 2 and 13 recite: "…has the highest predicted frameshift percentage of the candidate guides..." Percentage is a mathematical concept and/or formula.
Claims 1-5, 12-16 and 20 are involved with determining whether the candidate guide meets specific criteria and then selecting for the guide. These claims are involved with acts of evaluating, analyzing, observing and judging data as indicated above. Acts of evaluating and analyzing data could be practically performed in the human mind and/or with pen and paper because they merely require making observations, evaluations, judgments, and opinions (See MPEP 2106.04(a)(2) subsection III). Although, claims 1, 12 and 20 recite performing the method with a processor, memory and non-transitory computer readable storage medium, there are no additional limitations to indicate that anything other than a generic computer is required. However, merely requiring that the steps are carried out with a generic computer does not negate the mental nature of these steps and equates rather to merely using a computer as a tool to perform the mental process. Therefore, under the broadest reasonable interpretation, the indicated claims above can be practically carried out in the human mind or with pen and paper as claimed, which falls under the "Mental processes" grouping of abstract ideas.
Claims 1-2, 12-13 and 20 recite mathematical concepts and formulas as discussed above. Percentage is a mathematical concept and/or formula that falls under the “mathematical concepts” grouping of abstract ideas.
As such, claims 1-20 recite an abstract idea (Step 2A, Prong 1: YES).
Claims found to recite a judicial exception under Step 2A, Prong 1 are then further analyzed to determine if the claims as a whole integrate the recited judicial exception into a practical application or not (Step 2A, Prong 2). The above indicated judicial exceptions are not integrated into a practical application because the claims do not recite additional elements that apply, rely on or use the judicial exception in such a manner to amount to integration into a practical application. For example, there are no limitations that reflect an improvement to technology or applies or uses the recited judicial exception in some other meaningful way. Rather, the instant claims recite additional elements that equate to mere instructions to implement an abstract idea or insignificant extra solution activity. Specifically, the instant claims recite the following additional elements:
Claim 1 recites a memory; and a processor coupled with the memory.
Claim 12 recites a processor.
Claim 20 recites "a non-transitory machine readable storage medium comprising instructions" and "a processor"
The elements of claims 1, 12 and 20 as indicated above equate to generic computer components. The claims invoke the computer components merely as tools to execute the abstract idea. The use of a computer or other machinery in its ordinary capacity for economic or other tasks (e.g., to receive, store, or transmit data) or simply adding a general purpose computer or computer components after the fact to an abstract idea (e.g., a fundamental economic practice or mathematical equation) does not integrate a judicial exception into a practical application or provide significantly more. (see MPEP 2106.05(f)). Additionally, the listed additional elements are mere instructions to apply an exception because they recite no more than an idea of a solution or outcome and does not recite a technological solution to a technological problem. (See MPEP 2106.05(f)(1)). As such, as currently recited, the claims do not appear to recite an improvement to technology or apply or use the recited judicial exception in some other meaningful way. Therefore, claims 1-20 are directed to an abstract idea (Step 2A, Prong 2: NO).
Claims found to be directed to a judicial exception are then further evaluated to determine if the claims recite an inventive concept that provides significantly more than the judicial exception itself (Step 2B). The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception because the claims recite additional elements that equate to well-understood, routine and conventional activities, insignificant extra-solution activity or mere instructions to implement the abstract idea on a generic computer. The instant claims recite the following additional elements:
Claim 1 recites a memory; and a processor coupled with the memory.
Claim 12 recites a processor.
Claim 20 recites "a non-transitory machine readable storage medium comprising instructions" and "a processor"
The additional elements indicated above do not comprise an inventive concept when considered individually or as an ordered combination that transforms the claimed judicial exception into a patent-eligible application of the judicial exception. The limitations equate to data processing and outputting via generic computer components, which amounts to insignificant extra-solution activity. For instance, receiving data at a computer or outputting data, amount to insignificant extra-solution activity as set forth by the courts in Mayo, 566 U.S. at 79, 101 USPQ2d at 1968 and OIP Techs., Inc, v, Amazon.com, Inc., 788 F.3d 1359, 1363, 115 USPQ2d 1090, 1092-93 (Fed. Cir. 2015). Also, the additional elements include storing and retrieving information in memory. Storing and retrieving information in memory were identified by the courts as well-understood, routine and conventional in Versata Dev. Group, Inc. v. SAP Am., Inc., 793 F.3d 1306, 1334, 115 USPQ2d 1681, 1701 (Fed. Cir. 2015); OIP Techs., 788 F.3d at 1363, 115 USPQ2d at 1092-93. Also, the use of a computer or other machinery in its ordinary capacity for economic or other tasks (e.g., to receive, store, or transmit data) or simply adding a general purpose computer or computer components after the fact to an abstract idea (e.g., a fundamental economic practice or mathematical equation) does not integrate a judicial exception into a practical application or provide significantly more as identified by the courts in Affinity Labs v. DirecTV, 838 F.3d 1253, 1262, 120 USPQ2d 1201, 1207 (Fed. Cir. 2016) (cellular telephone); TLI Communications LLC v. AV Auto, LLC, 823 F.3d 607, 613, 118 USPQ2d 1744, 1748 (Fed. Cir. 2016) (computer server and telephone unit). Therefore, the claims do not amount to significantly more than the judicial exception itself (Step 2B: No). As such, claims 1-20 are not patent eligible.
Claim Rejections - 35 USC § 103
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.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
Claim(s) 1-20 is/are rejected under 35 U.S.C. 103 as being unpatentable over Hough ("Guide Picker is a comprehensive design tool for visualizing and selecting guides for CRISPR experiments." BMC bioinformatics 18.1 (2017): 167.; cited on the attached 892 form) in view of Veeneman ("PINCER: improved CRISPR/Cas9 screening by efficient cleavage at conserved residues." Nucleic acids research 48.17 (2020): 9462-9477.; cited on the attached 892 form).
Regarding independent claims 1, 12 and 20, Hough teaches the recited limitation determine a transcript support level of a candidate guide of the multiplicity of candidate guides and keeping the candidate guide for further selection if it meets a transcript support threshold; determine whether the candidate guide targets a consensus sequence of a target gene and keeping the candidate guide for further selection if it meets a consensus threshold with “Transcript representation Representation refers to the proportion of the gene’s protein-coding transcripts a given guide RNA design can target. The stepped axis levels represent the percentage of targeted transcripts versus the total transcripts for that gene. This value is useful for designing guides against highly represented (consensus) exons. A graphical representation of how Transcript Representation is computed can be found in Fig. 4b. Plotting PPS against Transcript Representation in Guide Picker can be useful to determine the location of highly conserved transcripts in the context of the MCDS (Fig. 4c).” (page 4, col. 2, para. 3) and with Figure 4b and 4c (page 7).
Hough teaches the recited limitation determine which exon of the target gene is targeted and keeping the candidate guide for further selection if it meets a first exon threshold with “On-target activity score (Doench 2014) The Doench 2014 on-target activity score predicts the ability of the guide RNA to knock out the target gene [7]. This score was developed based on a large-scale CRISPR experiment using 1841 guide RNAs saturating nine genes [7]. The group investigated position-based nucleotide composition.” (page 4, col. 2, para. 6).
Hough teaches the recited limitation determine whether the candidate guide targets a primary transcript and keeping the candidate guide for further selection if it meets a primary transcript threshold with “Percent peptide score The percent peptide score (PPS) refers to the guide position within the protein-coding portion of the entire gene. In Guide Picker, protein coding exons for each transcript are concatenated together from the ATG/AUG codon to the STOP codon and multiple transcripts are overlaid to produce one theoretical master coding DNA sequence (MCDS) per gene (Fig. 4a). The base pair values for this sequence are normalized from 0 to 100, 5′–3′ to provide percentage progression through the MCDS. Guides with a PPS of 50% PPS target the 3′ half.” (page 4, col. 2, para. 2) and with “Transcript representation Representation refers to the proportion of the gene’s protein-coding transcripts a given guide RNA design can target. The stepped axis levels represent the percentage of targeted transcripts versus the total transcripts for that gene. This value is useful for designing guides against highly represented (consensus) exons. A graphical representation of how Transcript Representation is computed can be found in Fig. 4b. Plotting PPS against Transcript Representation in Guide Picker can be useful to determine the location of highly conserved transcripts in the context of the MCDS (Fig. 4c).” (page 4, col. 2, para. 3).
Hough teaches the recited limitation determine whether the candidate guide targets a common isoform and keeping the candidate guide for further selection if it meets a common isoform threshold with “By using all transcripts for a given gene, Guide Picker can offer more guide design options and help the user target as many transcript variants as possible to ensure gene knockout.” (page 2, col. 1, para. 3).
Hough teaches the recited limitation determine whether the candidate guide has a precomputed prediction of editing outcomes and keeping the candidate guide for further selection if there is a precomputed prediction of editing outcomes with “In addition to pre-loading guide sequences, Guide Picker further speeds up the CRISPR design process by pre-computing all scores for every guide RNA targeting coding genomic regions in the mouse and human reference genomes. For any given scoring function and gene, rendering all available guides takes fewer than five seconds (even for large genes with ~3000 guides, such as MUC4). Guide Picker displays all of these guides in an easily manageable graphical format that can be adjusted to improve visual accessibility.” (Page 2, col. 1, para. 5) and with “On-target activity (Doench 2016 full and positionless) Like the Doench 2014 score, the Doench 2016 on-target activity score also predicts the ability of the guide RNA to knock out the target gene [8]. This score is an improvement on Doench 2014 because it ranks data from multiple large-scale CRISPR experiments and combines their information to build a new algorithm with a more generalizable model [8]. Once again, the group investigated the nucleotide composition of the guide RNAs and compared this data to activity [8]. A score of 100 represents the highest predicted guide RNA activity based on nucleotide sequence.” (Page 5, col. 1, para. 2).
Hough teaches the recited limitation determine whether the candidate guide maps to an expressed sequence and keeping the candidate guide for further selection if it maps to an expressed sequence with “A higher score indicates the guide is less likely to direct SpCas9 to cut at unintended (off-target) sites in the genome. A score of over 50 means the guide has no exact matches elsewhere in the genome, and a score of 100 represents maximum specificity.” (page 4, col. 2, para. 5).
Hough teaches the recited limitation determine a fraction of gene expression attributable to targeted transcripts for the candidate guide and keeping the candidate guide for further selection if it meets a fraction of gene expression attributable to targeted transcripts threshold with “Transcript representation Representation refers to the proportion of the gene’s protein-coding transcripts a given guide RNA design can target. The stepped axis levels represent the percentage of targeted transcripts versus the total transcripts for that gene. This value is useful for designing guides against highly represented (consensus) exons. A graphical representation of how Transcript Representation is computed can be found in Fig. 4b. Plotting PPS against Transcript Representation in Guide Picker can be useful to determine the location of highly conserved transcripts in the context of the MCDS (Fig. 4c).” (page 4, col. 2, para. 3)
Hough teaches the recited limitation determine which exon of the target gene is targeted and keeping the candidate guide for further selection if it meets a guide per exon threshold with “Transcript representation Representation refers to the proportion of the gene’s protein-coding transcripts a given guide RNA design can target. The stepped axis levels represent the percentage of targeted transcripts versus the total transcripts for that gene. This value is useful for designing guides against highly represented (consensus) exons. A graphical representation of how Transcript Representation is computed can be found in Fig. 4b. Plotting PPS against Transcript Representation in Guide Picker can be useful to determine the location of highly conserved transcripts in the context of the MCDS (Fig. 4c).” (page 4, col. 2, para. 3).
Hough teaches the recited limitation determine whether the candidate guide overlaps a selected guide and keeping the candidate guide for further selection if it meets a guide overlap threshold with “Due to the volume of guide RNA data and our decision to round score values to the nearest integer, highly dense overlapping regions became common in the scatterplots. In order to explore these dense regions more easily, we implemented a “Force Layout” view and “Fisheye” lensing (advanced Guide Picker features) to allow users to visualize overlapping guides or guides in close proximity to one another (Fig. 3). In concert, displaying all guides for a gene side-by-side across two plots according to four variable guide RNA scores offers unprecedented ease and control over guide design.” (page 4, col. 1, para. 3).
Hough teaches the recited limitation determine a predicted frameshift percentage for the candidate guide and keeping the candidate guide for further selection if it meets a predicted frameshift percentage threshold with “Microhomology score The microhomology score predicts the likelihood of creating an out-of-frame mutation via NHEJ-mediated repair [13]. Regions of microhomology close to the cut site can facilitate indel formation, The higher the score, the more likely the guide RNA is to produce a frameshift-causing indel (desirable for knockout experiments).” (page 6, col. 2, para. 2).
Hough teaches the recited limitation determine a GC content of the candidate guide and keeping the candidate guide for further selection if it meets a minimum GC content threshold; determine the GC content of the candidate guide and keeping the candidate guide for further selection if it meets a maximum GC content threshold with “GC content Extreme GC content (low or high) can lead to poor or depleted guide RNA activity. The percentage of GC content refers specifically to the guide RNA protospacer element (not including the PAM). A recent study concluded that a range of 30–70% GC content yields optimal guide RNA activity [9]. GC content is implemented in Guide Picker as a continuous score of 0–100%.” (Page 5, col. 2, para. 4 to page 6, col. 1, para. 1).
Hough teaches the recited limitation determine an off-target score for the candidate guide and keeping the candidate guide for further selection if it meets an off-target score threshold with “Guide Picker can compare on- and off-target scores, as well as other parameters, for every guide RNA targeting the protein-coding transcripts in a given mouse or human gene. Filtering and selecting guides according to different scores in one interface alleviates the labor involved in testing designs across disparate guide RNA design tools (Fig. 1). Once the user has generated suitable designs, the list of guide RNAs can be saved and passed on for synthesis and experimental application.” (page 2, col. 1, para. 2); “Specificity score (Hsu 2013) The Hsu 2013 score predicts the specificity of the guide RNA. Off-target sites are evaluated based on genomic similarity to the guide RNA sequence. This evaluation takes into account mismatch number, position and density [4]. It is important to note that while Hsu 2013 evaluates mismatch position and nucleotide number, it does not consider nucleotide identity (ATGC) [8].” (page 4, col. 2, para. 4) and “Hsu 2013 considers both canonical NGG and noncanonical NAG PAM sites for SpCas9 [4]. This information is accumulated into a continuous score from 0 to 100. A higher score indicates the guide is less likely to direct SpCas9 to cut at unintended (off-target) sites in the genome. A score of over 50 means the guide has no exact matches elsewhere in the genome, and a score of 100 represents maximum specificity.” (page 4, col. 2, para. 5).
Hough teaches the recited limitation determine a position where the candidate guide targets a coding sequence and keeping the candidate guide for further selection if it meets a coding sequence position threshold with “Doench 2016 comes in two forms: Full and Positionless. The Doench 2016 Full score is adjusted based on the target location in the coding DNA sequence while the Doench 2016 Positionless score does not. This adjustment is based on the percent peptide score (PPS) which represents the progression through the CDS of that gene.” (page 5, col. 2, para. 2) and “The reason to consider accounting for position in the CDS is that some studies have suggested that targeting in the 3′ end of the gene is less likely to lead to gene knockout [8], possibly due to nonsense-mediated decay [11]. Therefore, Doench 2016 Full scores tend to be lower near the 3′ end of the gene. Conversely, Positionless does not penalize for targeting in the last third of the CDS.” (page 5, col. 2, para. 3).
Hough teaches the recited limitation and responsive to the candidate guide meeting the thresholds, select the candidate guide as a selected CRISPR guide with “The final guide selection can be highlighted on the right to verify that they still target along the full length of the MCDS (as evidenced by a broad range of PPS values on the left-hand plot) (Fig. 6d).” (Page 9, col. 1, para. 1).
Hough teaches the recited a memory; and a processor coupled with the memory in claim 1; processor in claim 12 and a non-transitory computer readable storage medium comprising instructions and the processor in claim 20. Hough teaches “Guide sequences are determined by performing an exhaustive search throughout all protein-coding regions of the mouse or human genome based solely on available NGG SpCas9 PAM sites. This is accomplished using inhouse Python scripts which, along with the scores, are contained in a Python wrapper to facilitate automation. This loading process occurs on a cloud-based web server and not on the user’s computer.” (Page 2, col. 1, para. 4). The recited processor, memory and a non-transitory computer readable storage medium corresponds to the cloud-based web server as taught by Hough.
Hough does not explicitly teach the recited limitation determine whether the candidate guide meets a common SNP overlap threshold and keeping the candidate guide for further selection if it meets an SNP overlap threshold of independent claims 1, 12 and 20. However, this limitation is taught by Veeneman.
Veeneman teaches the recited limitation determine whether the candidate guide meets a common SNP overlap threshold and keeping the candidate guide for further selection if it meets an SNP overlap threshold with “(SNP) whether guides and their PAMs overlap known point mutation or indel polymorphisms at a 10% VAF as defined by dbSNP” (page 9471, col. 1, para. 1).
It would have been prima facia obvious to combine the teachings of Hough and Veeneman to arrive at the claimed invention. Veeneman’s ProteIN ConsERvation (PINCER) genome-wide CRISPR library combines enzymatic efficiency optimization with conserved length protein region targeting, and also incorporates domains, coding sequence position, U6 termination (TTT), restriction sites, polymorphisms and specificity and demonstrate superior performance of the PINCER library compared to alternative genome-wide CRISPR libraries in head-to-head validation (Abstract). A person of ordinary skill in the art would have been motivated to combine the method of Hough with Veeneman to include selecting for the candidate guide if it meets an SNP overlap threshold for the purpose of improving the specificity of the guide. Furthermore, there would have been a reasonable expectation of success, since Hough and Veeneman teach methods that pertain to selecting Crispr guides with desired features.
Regarding claims 2 and 13, Hough teaches the recited limitation select the candidate guide as the selected guide if it meets all the thresholds and has the highest predicted frameshift percentage of the candidate guides with “Microhomology score The microhomology score predicts the likelihood of creating an out-of-frame mutation via NHEJ-mediated repair [13]. Regions of microhomology close to the cut site can facilitate indel formation, The higher the score, the more likely the guide RNA is to produce a frameshift-causing indel (desirable for knockout experiments).” (page 8, col. 2, para. 2).
Regarding claims 3 and 14, Hough teaches the recited limitation to keep the candidate guide for further selection if it meets a threshold for targeting a primary transcript or a main isoform of a transcript with “Percent peptide score The percent peptide score (PPS) refers to the guide position within the protein-coding portion of the entire gene. In Guide Picker, protein coding exons for each transcript are concatenated together from the ATG/AUG codon to the STOP codon and multiple transcripts are overlaid to produce one theoretical master coding DNA sequence (MCDS) per gene (Fig. 4a). The base pair values for this sequence are normalized from 0 to 100, 5′–3′ to provide percentage progression through the MCDS. Guides with a PPS of 50% PPS target the 3′ half.” (page 4, col. 2, para. 2) and “Transcript representation Representation refers to the proportion of the gene’s protein-coding transcripts a given guide RNA design can target. The stepped axis levels represent the percentage of targeted transcripts versus the total transcripts for that gene. This value is useful for designing guides against highly represented (consensus) exons. A graphical representation of how Transcript Representation is computed can be found in Fig. 4b. Plotting PPS against Transcript Representation in Guide Picker can be useful to determine the location of highly conserved transcripts in the context of the MCDS (Fig. 4c).” (page 4, col. 2, para. 3).
Regarding claims 4 and 15, Hough teaches the recited limitation reject the candidate guide for further selection if it targets a first exon of a CDS with Figure 2. Figure 2 depicts the Guide Picker Workflow with the following steps. a First, an Ensembl gene name is provided from either the mouse or human reference genome. b Then, the guide RNAs populate the left- and right-hand plots, organized on axes according to the scores selected in the corresponding dropdown menus. Guides are filtered and selected based on these parameters. c Finally, a list of guide sequences are output and can be saved or sent to an oligo synthesis provider. (Figure 2 caption, page 5) and “Guides with a PPS of <50% target toward the 5′ half of the MCDS, while guides with a >50% PPS target the 3′ half.” (page 4, col. 2, para. 2). Hough also teaches “Doench 2016 comes in two forms: Full and Positionless. The Doench 2016 Full score is adjusted based on the target location in the coding DNA sequence while the Doench 2016 Positionless score does not. This adjustment is based on the percent peptide score (PPS) which represents the progression through the CDS of that gene.” (page 5, col. 2, para. 2). PPS scores of Hough allows for the selection or rejection of guides that target certain regions of the MCDS.
Regarding claims 5 and 16, Hough teaches the recited limitation to adjust one or more thresholds and iterate the determination and the selection from the candidate guides until a desired number of selected guides are selected with “Axes can be dragged to filter guides based on score thresholds. Drop-down menus below each plot can be used to reassign x- and y axes to various scoring functions (Fig. 2b).” (page 4, col. 1, para. 5)
Regarding claims 6 and 17, Hough teaches the recited limitation the off-target score comprises an elevation search score with “Hsu 2013 considers both canonical NGG and noncanonical NAG PAM sites for SpCas9 [4]. This information is accumulated into a continuous score from 0 to 100. A higher score indicates the guide is less likely to direct SpCas9 to cut at unintended (off-target) sites in the genome. A score of over 50 means the guide has no exact matches elsewhere in the genome, and a score of 100 represents maximum specificity.” (page 4, col. 2, para. 5) and “All guides above this threshold are then brought over to the right-hand plot and further narrowed down according to, for example, a relatively high Hsu 2013 off-target score (68, which is >50 and means they have no exact matches elsewhere in the genome) and a GC content range of 30–70% [9] (Fig. 6c). The final guide selection can be highlighted on the right to verify that they still target along the full length of the MCDS (as evidenced by a broad range of PPS values on the left-hand plot) (Fig. 6d).” (page 9, col. 1, para. 1). The recited elevation search score corresponds to Hsu 2013 off-target score of Hough.
Regarding claims 7 and 18, Hough teaches the recited limitation the candidate guides comprise guides of one of: a Type II CRISPR-Cas system, a Type V CRISPR-Cas system, and a Type VI CRISPR-Cas system with “Similarly, Guide Picker only uses SpCas9 guide RNA design rules. We made this decision because all guide RNA scoring algorithms to date were written to accommodate this nuclease and not its orthologs (e.g. NmCas9) which vary in PAM recognition, specificity and more.” (page 2, col. 2, para. 3). The recited Type II CRISPR-Cas system corresponds to SpCas9 of Hough.
Regarding claims 8 and 19, Hough teaches the recited limitation the candidate guides comprise one of: an RNA guide, a DNA-RNA hybrid guide, and a chemically modified base guide with “Guide Picker is a cloud-based tool that allows the user to visualize guide RNA designs plotted according to ten scoring functions using one simple graphical interface.” (page 2, col. 1, para. 2).
Regarding claim 9, Hough teaches the recited limitation the primary transcript a MANE transcript with “Guide Picker is also unique because it is the only online resource that allows guide design around all protein coding transcripts of a gene. Transcripts are identified using Ensembl database annotations indicating known coding DNA sequences. Some design tools limit guide design to a 250 nucleotide input sequence while others only generate guides for a single transcript. By using all transcripts for a given gene, Guide Picker can offer more guide design options and help the user target as many transcript variants as possible to ensure gene knockout.” (page 2, col. 1, para. 3). The recited MANE transcript corresponds to the Transcripts are identified using Ensembl database annotations indicating known coding DNA sequences of Hough.
Hough does not explicitly teach the recited limitation the common isoform threshold comprises an APPRIS score threshold in claim 10 and the fraction of gene expression attributable to targeted transcripts comprises transcripts per million (TPM) from targeted transcripts for the candidate guide in claim 11. However, these limitations are taught by Veeneman.
Regarding claim 10, Veeneman teaches the recited limitation the common isoform threshold comprises an APPRIS score threshold with “Finally, to generate a genome-wide protein conservation score, we used PROVEAN and Blast NR v2011 to predict (page 9445, col. 2, para. 4) the detrimental impact of the deletion of every single amino acid in APPRIS principal isoforms of Refseq genes (human and mouse) and multiplied by −1 such that larger positive numbers correspond to higher conservation. We named this score AADelCons, for amino acid deletion conservation.” (page 9446, col. 1, para. 1).
Regarding claim 11, Veeneman teaches the recited limitation the fraction of gene expression attributable to targeted transcripts comprises transcripts per million (TPM) from targeted transcripts for the candidate guide with “Following sequencing, sgRNAs were counted with a custom pipeline based on Bowtie and Oculus (81,82). Reads per million mapped reads (RPMs) were computed for each sample, then normalized to the total abundance of guides targeting negative control genes (across libraries, such that the normalization factor for each cell line was the same) to account for variation between cell lines. sgRNA-level log2-fold-changes (LFCs), gene-level LFCs and gene-level coefficient of variation across sgRNAs (CV = standard deviation/mean) were computed with custom R code and gene-level beta values were computed with MAGeCKVISPR’s maximum likelihood estimation model using negative control normalization (83). We plotted the distributions of counts in each gene category over time (Supplementary Figure S17).” (page 9467, col. 2, para. 3).
It would have been prima facia obvious to combine the teachings of Hough and Veeneman to arrive at the claimed invention. Veeneman’s ProteIN ConsERvation (PINCER) genome-wide CRISPR library combines enzymatic efficiency optimization with conserved length protein region targeting, and also incorporates domains, coding sequence position, U6 termination (TTT), restriction sites, polymorphisms and specificity and demonstrate superior performance of the PINCER library compared to alternative genome-wide CRISPR libraries in head-to-head validation (Abstract). Veeneman observed that low confidence short isoforms hinder domain targeting (page 4961, col. 1 para. 2). A person of ordinary skill in the art would have been motivated to combine the method of Hough with Veeneman to include APPRIS score threshold for isoforms for the purpose of determining the level of conservation and whether the isoforms hinder domain targeting. A person of ordinary skill in the art would have also been motivated to combine the method of Hough with Veeneman to include gene expression of transcripts per million (TPM) from targeted transcripts for the candidate guide for the purpose of screen analysis. Furthermore, there would have been a reasonable expectation of success, since Hough and Veeneman teach methods that pertain to selecting Crispr guides with desired features.
Conclusion
No claims are allowed.
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/K.K./Examiner, Art Unit 1686
/LARRY D RIGGS II/Supervisory Patent Examiner, Art Unit 1686