HOPE (homologous 3’ extension mediated prime editor) utilizes paired prime editing guide RNAs (pegRNAs) encoding the same edits in both sense and antisense DNA strands to achieve high editing efficiency in human HEK293T cells as well as mismatch repair (MMR)-deficient HCT116 cells
The desired editing efficiencies of HOPE (substitution/insertion/deletion) are calculated by CRISPResso2 (https://github.com/pinellolab/CRISPResso2), a software designed to enable rapid and intuitive interpretation of genome editing experiments.
Herein, we use CRISPResso2 to calculate the efficiencies of desired substitution and insertion/deletion with “PE (Prime-edited) mode” and “HDR mode”, respectively.
The analysis of substitution events needs following parameters: “—prime editing pegRNA spacer seq”, “—prime editing pegRNA extension seq”, “—prime editing pegRNA scaffold seq”, “—prime editing nicking guide seq”. Specifically, for insertions and deletions, the HDR amplicon sequence was used as HDR reference with “-e” parameter, and “—prime editing pegRNA spacer seq”, “—prime editing nicking guide seq” were also needed. And “—discard indel reads” parameter was used for the calculation of the substitution, insertion, and deletion events, while “—ignore substitutions” was used for calculation of undesired indel type. The precise editing frequencies were calculated based on the “CRISPResso quantification of editing frequency” files that were obtained from CRISPResso2. The corresponding formulas are shown below: $$ \text { Substitution ratio }=\frac{\text { [# Unmodified reads (Prime - edited amplicon)] }}{[\text {# Reads aligned all amplicons }]} \times \text{100 %} $$
To evaluate the detailed undesired indel types of HOPE, we carry out the indel analysis with “HOPE_indel_analysis.py” (Python3).
For help info, please run python HOPE_indel_analysis.py -h:
$python HOPE_indel_analysis.py -h
usage: HOPE_indel_analysis.py [-h] -ifa INPUT_FASTA -iat INPUT_ALLELE_TABLE -event_indel OUTPUT_EVENT_INDEL -idx_indel OUTPUT_IDX_INDEL -ins
OUTPUT_INS_INFO -del OUTPUT_DEL_INFO
Get all the related insertions and deletions information based on the CRISPResso2 allele table result file
optional arguments:
-h, --help show this help message and exit
-ifa INPUT_FASTA, --input_fasta INPUT_FASTA
The input reference fasta file
-iat INPUT_ALLELE_TABLE, --input_allele_table INPUT_ALLELE_TABLE
The input CRISPResso2 allele table file
-event_indel OUTPUT_EVENT_INDEL, --output_event_indel OUTPUT_EVENT_INDEL
Output each reference index exist event position plus total indel information
-idx_indel OUTPUT_IDX_INDEL, --output_idx_indel OUTPUT_IDX_INDEL
Output the only the idx indel info, not plus each idx
-ins OUTPUT_INS_INFO, --output_ins_info OUTPUT_INS_INFO
Output each insertion event position, length and count
-del OUTPUT_DEL_INFO, --output_del_info OUTPUT_DEL_INFO
Output each deletion event position, length and countTest example command for calculate indel analysis results.
python HOPE_indel_analysis.py -ifa Test_ref.fa -iat Test_allele_filt.txt \
-event_indel Test_event_indel.txt \
-idx_indel Test_idx_indel.txt \
-ins Test_ins.txt \
-del Test_del.txtThe script needs two inputs. The "-ifa" parameter is the input of the corresponding amplicon sequence, and the "-iat" is the input filtered from the "Alleles_frequency_table.txt" file analyzed by CRISPResso2. For example, filter the column” Reference_Name“ as ”Prime-edited“ and column ”Read_Status“ as ”MODIFIED“.
Aligned_Sequence Reference_Sequence Reference_Name Read_Status n_deleted n_inserted n_mutated #Reads %Reads
CAGGTGAAGGTGTGGTTCCAGAACCGGAGGACAAAGTACAAACGGCAGAAGCTGGAGGAGGAAGGGCCTGAGTCCGAGCAGAAGAACAAGGGCTCCCATCACATCAACCGGTGGCGCATTGCCACGA----------------GGACATCGATGTCACCTCCAATGACTAGGGTGGGCAAC CAGGTGAAGGTGTGGTTCCAGAACCGGAGGACAAAGTACAAACGGCAGAAGCTGGAGGAGGAAGGGCCTGAGTCCGAGCAGAAGAACAAGGGCTCCCATCACATCAACCGGTGGCGCATTGCCACGAAGCAGGCCAATGGGGAGGACATCGATGTCACCTCCAATGACTAGGGTGGGCAAC Prime-edited MODIFIED 16 0 0 69 0.0312864158010003
CAGGTGAAGGTGTGGTTCCAGAACCGGAGGACAAAGTACAAACGGCAGAAGCTGGAGGAGGAAGGGCCTGAGTCCGAGCAGAAGAACAAGGGCTCCCATCAC------------------GCCACGAAGCAGGCCAATGGGGAGGACATCGATGTCACCTCCAATGACTAGGGTGGGCAAC CAGGTGAAGGTGTGGTTCCAGAACCGGAGGACAAAGTACAAACGGCAGAAGCTGGAGGAGGAAGGGCCTGAGTCCGAGCAGAAGAACAAGGGCTCCCATCACATCAACCGGTGGCGCATTGCCACGAAGCAGGCCAATGGGGAGGACATCGATGTCACCTCCAATGACTAGGGTGGGCAAC Prime-edited MODIFIED 18 0 0 68 0.0308329894850437
CAGGTGAAGGTGTGGTTCCAGAACCGGAGGACAAAGTACAAACGGCAGAAGCTGGAGGAGGAAGGGCCTGAGTCCGAGCAGAAGAACAAGGGCTCCCATCACATCAACCGGTGGCGCATTGCCACGAAGCAGGCCAATGGGGGAGGACATCGATGTCACCTCCAATGACTAGGGTGGGCAAC CAGGTGAAGGTGTGGTTCCAGAACCGGAGGACAAAGTACAAACGGCAGAAGCTGGAGGAGGAAGGGCCTGAGTCCGAGCAGAAGAACAAGGGCTCCCATCACATCAACCGGTGGCGCATTGCCACGAAGCAGGCCAATG-GGGAGGACATCGATGTCACCTCCAATGACTAGGGTGGGCAAC Prime-edited MODIFIED 0 1 0 67 0.0303795631690872
CAGGTGAAGGTGTGGTTCCAGAACCGGAGGACAAAGTACAAACGGCAGAAGCTGGAGGAGGAAGGGCCTGAGTCCGAGCAGAAGAACAAGGGCTCCCATCAC-GCAAACGGTTGCGCATTGCCACGAAGCAGGCCAATGGGGAGGACATCGATGTCACCTCCAATGACTAGGGTGGGCAAC CAGGTGAAGGTGTGGTTCCAGAACCGGAGGACAAAGTACAAACGGCAGAAGCTGGAGGAGGAAGGGCCTGAGTCCGAGCAGAAGAACAAGGGCTCCCATCACATCAACCGGTGGCGCATTGCCACGAAGCAGGCCAATGGGGAGGACATCGATGTCACCTCCAATGACTAGGGTGGGCAAC Prime-edited MODIFIED 1 0 1 67 0.0303795631690872
CAGGTGAAGGTGTGGTTCCAGAACCGGAGGACAAAGTACAAACGGCAGAAGCTGGAGGAGGAAGGGCCTGAGTCCGAGCAGAAGAACAAGGGCTCCCATCA-----ACCGGTGGCGCATTGCCACGAAGCAGGCCAATGGGGAGGACATCGATGTCACCTCCAATGACTAGGGTGGGCAAC CAGGTGAAGGTGTGGTTCCAGAACCGGAGGACAAAGTACAAACGGCAGAAGCTGGAGGAGGAAGGGCCTGAGTCCGAGCAGAAGAACAAGGGCTCCCATCACATCAACCGGTGGCGCATTGCCACGAAGCAGGCCAATGGGGAGGACATCGATGTCACCTCCAATGACTAGGGTGGGCAAC Prime-edited MODIFIED 5 0 0 65 0.0294727105371742The details of INDEL can be obtained through the pipeline which is mentioned above, including the positions of insertion, length of insertion sequence, reads statistics and insertion sequence.
Ins_Ref_idx Length_ins(bp) c_Reads Ins_seq
139 1 70 G
33 2 1 TC
181 2 1 AG
154 1 1 A
15 1 1 G
...Furthermore, you can also obtain the start and end positions of the deletion sequence, deletion sequence length, and the reads statistics.
Del_Ref_Start Del_Ref_End Length_del(bp) c_Reads
103 120 18 75
103 103 1 73
102 106 5 72
103 113 11 64
117 127 11 64
...The results of cumulative statistical reads of insertion and deletion events at each location of amplicon reference can be obtained.
Idx Event_type c_Reads
...
100 del-count 80
100 ins-count 0
101 del-count 80
101 ins-count 0
102 del-count 152
102 ins-count 0
103 del-count 429
103 ins-count 0
...In addition, you can also obtain statistics on reads that begin to occur at certain locations of the amplicon reference for insertion and deletion.
idx ins_count del_count
...
100 0 70
101 0 1
102 0 72
103 0 277
104 0 0
105 0 51
106 0 0
...Cas-OFFinder (https://github.com/snugel/cas-offinder) is used to predict the off-target sites. The substitution or indel ratio at the predicted off-target editing sites, or a ± 25 bp region surrounding the off-target sites could be calculated as descripted above. Average substitution/indel ratios observed out of potential off-target editing regions (± 25 bp surrounding the predicted off-target sites) are defined as “BackGround” (excluding the ± 15 bp from the two side of the amplicon sequence). Note that SNPs are not taken into the calculation (SNP serve as mutation ratio more than 10%).
The R script shows an example for calculating the BG ratio. The input “.bmat” file contain the information of substitution, insertion, deletion and ambiguous statical reads for each location index of amplicon reference, which could be found in Detect-seq pipeline (http://detect-seq.com/).
The “.bmat” file looks like:
chr_name chr_index ref_base A G C T del_count insert_count ambiguous_count deletion insertion ambiguous mut_num
F-AS-MIS3-10 1 G 0 342389 0 0 0 0 0 . . . 0
F-AS-MIS3-10 2 G 0 342388 0 0 0 0 0 . . . 0
F-AS-MIS3-10 3 A 342392 0 0 0 0 0 0 . . . 0
F-AS-MIS3-10 4 G 0 342392 0 0 0 0 0 . . . 0
F-AS-MIS3-10 5 A 342392 0 0 0 0 0 0 . . . 0
F-AS-MIS3-10 6 G 0 342391 0 0 0 0 0 . . . 0
F-AS-MIS3-10 7 A 342392 0 0 0 0 0 0 . . . 0
F-AS-MIS3-10 8 T 0 0 0 342386 0 0 0 . . . 0
F-AS-MIS3-10 9 G 0 342392 0 0 1 8 0 AC A,A,A,A,A,A,A,A . 0