METHODS, MODELS, SYSTEMS, AND APPARATUS FOR IDENTIFYING TARGET SEQUENCES FOR CAS ENZYMES OR CRISPR-CAS SYSTEMS FOR TARGET SEQUENCES AND CONVEYING RESULTS THEREOF

• US 20150356239A1
• Filed: 06/12/2015
• Published: 12/10/2015
• Est. Priority Date: 12/12/2012
• Status: Active Grant

• Current Assignee: President and Fellows of Harvard College (Harvard Corporation), Massachusetts Institute of Technology, The Broad Institute, Inc.
• Original Assignee: President and Fellows of Harvard College (Harvard Corporation), Massachusetts Institute of Technology, The Broad Institute, Inc.
• Inventors: Zhang, Feng, Hsu, Patrick, Li, Yinqing, Scott, David Arthur, Weinstein, Joshua Asher
• Granted Patent: US 10,930,367 B2
• Time in Patent Office: Days
• US Class Current: 1/1
• CPC Class Codes: C12N 15/1082 Preparation or screening gene libraries by chromosomal integration of polynucleotide sequences, HR-, site-specific-recombination, transposons, viral vectors
• CPC Class Codes: C12N 15/1089 Design, preparation, screening or analysis of libraries using computer algorithms
• CPC Class Codes: C12N 15/113 Non-coding nucleic acids modulating the expression of genes, e.g. antisense oligonucleotides; Antisense DNA or RNA; Triplex- forming oligonucleotides; Catalytic nucleic acids, e.g. ribozymes; Nucleic acids used in co-suppression or gene silencing when used in plants C12N15/8218
• CPC Class Codes: C12N 2310/20 involving clustered regularly interspaced short palindromic repeats [CRISPRs]
• CPC Class Codes: C12N 2320/11 for the determination of target sites, i.e. of active nucleic acids
• CPC Class Codes: C12N 9/22 Ribonucleases RNAses, DNAses catalytic nucleic acids C12N15/113
• CPC Class Codes: G16B 20/00 ICT specially adapted for functional genomics or proteomics, e.g. genotype-phenotype associations
• CPC Class Codes: G16B 20/30 Detection of binding sites or motifs

Abstract

Disclosed are thermodynamic and multiplication methods concerning CRISPR-Cas systems, and apparatus therefor.

Claims

1. A method for selecting a CRISPR complex for targeting and/or cleavage of a candidate target nucleic acid sequence within a cell, comprising the steps of:

(a) determining amount, location and nature of mismatch(es) of guide sequence of potential CRISPR complex(es) and the candidate target nucleic acid sequence,

(b) determining contribution of each of the amount, location and nature of mismatch(es) to hybridization free energy of binding between the target nucleic acid sequence and the guide sequence of potential CRISPR complex(es) from a training data set,

(c) based on the contribution analysis of step (b), predicting cleavage at the location(s) of the mismatch(es) of the target nucleic acid sequence by the potential CRISPR complex(es), and

(d) selecting the CRISPR complex from potential CRISPR complex(es) based on whether the prediction of step (c) indicates that it is more likely than not that cleavage will occur at location(s) of mismatch(es) by the CRISPR complex.

2. The method of claim 1 wherein the candidate target sequence is a DNA sequence, and the mismatch(es) are of RNA of potential CRISPR complex(es) and the DNA.

3. The method of claim 1, wherein step (b) is performed by

determining known local free energies, Δ

Gij(k), between every guide RNA sequence i and target DNA nucleic acid sequence j at position k,

calculating values of the effective free-energy Z_ij using the relationship p_ij∝

e<sup>−

β

Zij</sup>, where p_ij is measured cutting frequency by guide RNA sequence i on target DNA nucleic acid sequence j in the training set and β

is a positive constant of proportionality,

determining the weights which are position-dependent weights α

_□

by fitting the known value of Δ

Gij(k) and the calculated value of Z_ij across each guide RNA/target DNA sequence pair in the training set in the sum across all N bases of the guide-sequence

Z_ij=Σ

_k=1^Nα

_kΔ

G_ij(k)

by writing the above equation in the matrix form {right arrow over (Z)}=G{right arrow over (α

)}

and wherein, step (c) is performed by

estimating the effective free-energy Z_est using the determined position dependent weights in the equation

{right arrow over (Z_est)}=G{right arrow over (α

)}

and determining estimated spacer-target cutting frequencies p_est∝

e<sup>−

β

Zest</sup>, to thereby predict cleavage.

4. The method of claim 2 wherein the distance, in bp, between the first and last base of the target sequence is 18.

5. The method of claim 1 wherein predicting cleavage comprises predicting whether cleavage is more likely than not to occur at location(s) of mismatch(es), and thereby predicting cleavage.

6. The method of claim 1, further comprising normalizing the calculated values of the effective free energy of hybridization Z for each guide RNA/target DNA sequence pair in the training set.

7. The method of claim 1, further comprising filtering out calculated value of the effective free energy of hybridization Z for each guide RNA/target DNA sequence pair in the training set which have a sequencing depth which is below a minimum sequencing depth.

8. A computer-readable medium comprising codes that, upon execution by one or more processors, cause said one or more processors to implements the method as set out in any one of claims 1 to 7.

9. A computer system for selecting a CRISPR complex for targeting and/or cleavage of a candidate target nucleic acid sequence within a cell, the system comprising:

a. a memory unit configured to receive and/or store sequence information of the candidate target nucleic acid sequence; and

b. one or more processors alone or in combination programmed to

(a) determine amount, location and nature of mismatch(es) of potential CRISPR complex(es) and the candidate target nucleic acid sequence,

(b) determining the contribution of the mismatch(es) based on the amount and location of the mismatch(es),

(c) based on the contribution analysis of step (b), predicting cleavage at the location(s) of the mismatch(es), and

(d) select the CRISPR complex from potential CRISPR complex(es) based on whether the prediction of step (c) indicates that it is more likely than not that cleavage will occur at location(s) of mismatch(es) by the CRISPR complex.

10. A method of identifying one or more unique target sequences in a genome of a eukaryotic organism, whereby the target sequence is susceptible to being recognized by a CRISPR-Cas system, wherein the method comprises:

a) determining average cutting frequency of guide-RNA/target mismatches at a particular position for a particular Cas from a training data set as to that Cas, and/or

b) determining average cutting frequency of a particular mismatch-type for the particular Cas from the training data set,

to thereby obtain a ranking, which allows for the identification of one or more unique target sequences.

11. The method of claim 10, comprising

c) multiplying the average cutting frequency at a particular position by the average cutting frequency of a particular mismatch-type to obtain a first product,

d) repeating steps a) to c) to obtain second and further products for any further particular position(s) of mismatches and particular mismatches and multiplying those second and further products by the first product, for an ultimate product, and omitting this step if there is no mismatch, at any position or if there is only one particular mismatch at one particular position, and

e) multiplying the ultimate product by the result of dividing the minimum distance between consecutive mismatches by the distance, in bp, between the first and last base of the target sequence and omitting this step if there is no mismatch at any position or if there is only one particular mismatch at one particular position, to thereby obtain the ranking, which allows for the identification of one or more unique target sequences.

12. The method of claim 10, comprising creating the training data set as to a particular Cas before performing step (a).

13. The method of claim 11, comprising creating the training data set as to a particular Cas before performing step (a).

14. The method of any one of claims 10 to 13, wherein the distance, in bp, between the first and last base of the target sequence is 18.

15. The method of any one of claims 10 to 13, wherein the average cutting frequency p_est is determined from P_est∝

e<sup>−

β

Zest</sup>, where β

is a positive constant of proportionality and Z_est is the effective free-energy determined using {right arrow over (Z_est)}=G{right arrow over (α

)} where G is the local free energy and α

are position dependent weights determined using the training set.

16. A computer-readable medium comprising codes that, upon execution by one or more processors, implements a method of identifying one or more unique target sequences in a genome of a eukaryotic organism, whereby the target sequence is susceptible to being recognized by a CRISPR-Cas system, wherein the method comprises a method according to any one of claims 10 to 13.

17. A computer system for identifying one or more unique target sequences in a genome of a eukaryotic organism, the system comprising:

I. a memory unit configured to receive and/or store sequence information of the genome; and

II. one or more processors alone or in combination programmed to perform a method according to any one of claims 10 to 13.