Genome editing (CRISPR/Cas9)

Selection of guide RNA by ChIP

While a number of computational tools help design sgRNAs to target specific loci, the accurate prediction of whether Cas9 and the sgRNA of interest will bind specifically to the genome is still a challenge.

In order to ensure specific targeting of CRISPR/Cas9, the verification of the specific binding of the sgRNA at the locus of interest is required. The methodology of choice for such verification is chromatin immunoprecipitation followed either by real-time PCR (ChIP-qPCR) or sequencing (ChIP-seq) to analyze protein-DNA interactions.

Diagenode’s iDeal ChIP-seq Kit for Transcription Factors provides a robust workflow to investigate dCas9 binding in the genome by specifically enriching dCas9 in the on-target region by ChIP followed by real-time PCR. In addition, sequencing analysis of the DNA immunoprecipitated with the Cas9 antibody illustrates potential genome-wide off-target effects. This information is essential to verify the correct binding of dCas9 fused to an effector.

1. Monitoring of sgRNA efficiency by ChIP-qPCR

Figure 1.

ChIP was performed on sheared chromatin from 4,000,000 HEK293T cells using the iDeal ChIP-seq Kit for Transcription Factors, 5 µl of the polyclonal Cas9 antibody and 1 µg of the negative control IgG. Primers specific for the human H19, GAPDH, Myt1 and SLC17A4 were used for the qPCR. The figure shows the recovery, expressed as a percent of input (the relative amount of immunoprecipitated DNA compared to input after qPCR analysis).

Figure 2.

ChIP was performed on sheared chromatin from 4 000 000 HEK293T cells using the iDeal ChIP-seq kit for Transcription Factors, 5 µl of the polyclonal Cas9 antibody and 1 µg of the negative control IgG. The libraries were sequenced on Illumina HiSeq 3000 in 1X50 pb. The picture shows the read distribution for the manual IP (up), automated IP (middle) and IgG (bottom) samples. A-B. Peaks distribution of the three datasets in the region surrounding H19 (A) and a representative region of the genome (B) for HEK293T cells expressing a sgRNA for H19. C-D. Peaks distribution of the three datasets in the region surrounding GAPDH (C) and YIPF4 (D) for HEK293T cells expressing a sgRNA for GAPDH