A P P L I C AT I O N N O T E

CRISPRi:
Transcriptional
repression
screening withgenome-wide
CRISPR
interference.

Introduction
Building on the transformative impact of pooled screening using
CRISPR-Cas9 researchers have developed catalytically inactive
Cas9 (dCas9) and have demonstrated that it can be used totune genetic output. These systems are known as CRISPRi(interference) and CRISPRa (activation), respectively.
Revvity have previously developed a powerful CRISPR-Cas9
knockout platform and have demonstrated improved screening
quality by small but crucial modifications to the tracrRNAsequence (Cross et al., 2016). We now present a novel all-inone human whole-genome CRISPRi platform and demonstrate
its effectiveness in identifying resistance and sensitivity genes
to the BRAF inhibitor vemurafenib. The ability to negatively
control transcription by several orders of magnitude opens new
avenues and offers researchers the opportunity to identify novel
hits in both positive and negative selection screens where dCas9Authors

is non-mutagenic.

Carlos le Sage
Benedict CS Cross
Revvity, Inc.

Figure 1: CRISPR interference, or CRISPRi, uses a catalyticallyinactivated Cas9 fused to a transcriptional repression domain (Krüppelassociated box ; KRAB) to enact sitespecific gene repression.

CRISPRi: Transcriptional repression screening with genome-wide CRISPR interference.

Platform design

We hypothesized that a CRISPRi system would allow aFor CRISPRi screening we produced a custom all-in-one

vemurafenib treatment as a result of decreased gene

lentiviral vector system containing a dCas9-KRAB fusiontranscription.

subset of cells in the population to become resistant toas well as a U6-promoter driven guideRNA cassette.
The simultaneous expression of both dCas9-KRAB and
CRISPR from a single lentiviral insert provides a highly efficient
targeting strategy required for pooled functional screening.
To further enhance performance, we implemented ourmodified tracrRNA which had previously been demonstrated
to improve the robustness of pooled CRISPR-Cas9 drop-out
screening (Cross et al., 2016). Finally, we constructed a humanwhole-genome guide RNA library based on the latest guideRNA design by Horlbeck et al (2016) who have demonstrated
strongly improved performance of guide RNAs that bind togenomic DNA locations away from local nucleosomes. Thissecond generation CRISPRi library contains 5 guide RNAs per
gene targeting a total of 19,050 genes.

CRISPRi Screening platform validation
After 16 days of vemurafenib treatment, screen end pellets
were taken and the relative abundance of each of theguide RNAs was measured by next-generation sequencing.
Subsequently, guide RNA and gene hit level ranking wereevaluated by running the NGS data on a CRISPR-Cas9 screen
analysis platform, equipped with an adapted version of theMAGeCK workflow (Li et al., 2014). We observed excellent
overall QC performance, as evaluated by the drop-out of
key essential genes from the cell population when targeted
for repression.

Proof-of concept screening
As proof of concept we performed a genome-wide
positive selection screen to identify genes associated withvemurafenib resistance (PLX-4032). Vemurafenib is a BRAF
kinase inhibitor which has been shown to act cytostaticallyin A375 melanoma cells, which carry a BRAF V600E
gain-of-function mutation (Davies et al., 2002; Flaherty et al.,2010; Shalem et al., 2014).
Figure 3: Comparison of guide RNA abundance in DMSO treatedcells relative to the plasmid library input. We observed a strong
drop-out of core essential genes, such as ribosomal genes andgenes involved in replication indicating a strong transcriptional
repression effect had been enacted in the screen.

Figure 2: Screen schematic. Resistance to vemurafenib wasmonitored in response to CRISPRi screening to evaluate theplatform performance.
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CRISPRi: Transcriptional repression screening with genome-wide CRISPR interference.

CRISPRi screening hit identificationFollowing vemurafenib treatment we found >100 foldAenrichment of 375 guide RNAs, many of which targeted thesame gene.

BFigure 4: Enrichment of sgRNAs after vemurafenib treatment.
Scatterplot of log2-transformed guide RNA counts in screen
conditions after 16 days of DMSO (x-axis) versus vemurafenib
treatment (y-axis). Among the guides that were enriched in thevemurafenib treated condition (circled) was a set of guide RNAs
targeting the same genes multiple times (highlighted in colour).

Gene-level hit identification was then conducted usingassimilated scores from each of the guides targeting eachgene. Among the highest ranking genes were MED12, NF1,CUL3, TADA1, NF2 and TADA2B, genes whose loss is known
to confer resistance to vemurafenib (Huang et al., 2012;Whittaker et al., 2013; Shalem et al., 2014). In addition, we findmore members belonging to either Mediator (MED15, MED16,MED23 and MED24) or SAGA (TAF5L and TAF6L) complexes.
Many additionally identified hits were found to be membersof the of the MED complex, and these genes which are notspecifically detected by the equivalent screens conductedusing CRISPR knock out technology.

Figure 5: Data from the vemurafenib screening analysis. A. Fullscreen data showing log2 fold enrichment of each gene andassociated p-values. Highlighted hits have been previously
identified and validated by CRISPR knock-out screening.
B. Individual guide performance for each of the highlighted hits
showing enrichment level in each case.

Importantly, when evaluating ranking of the individual guide
RNAs of the resistance top hits, only few guide RNAs did not
perform optimally, indicating the robustness of CRISPRi andreflecting its ability to effectively downregulate gene output
to enable resistance to vemurafenib.
Interestingly, although the screen was specifically designed
to identify vemurafenib resistance factors. Genes whose loss
increase sensitivity to the compound included EGFR andITGB5, two genes previously reported to aid in vemurafenib
resistance when expression is enhanced by CRISPRatechnology (Konermann et al., 2015).
This finding underlines the high level of performance of theguide RNAs enabling hit identification even when the windowof detection is small due to the high selective pressure
treatment conditions for a given phenotype.

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CRISPRi: Transcriptional repression screening with genome-wide CRISPR interference.

Methods
A375 melanoma cells were infected with Revvity’s
CRISPRi-dCas9 lentivirus at low MOI, to ensure integrationof a single construct per cell. Cells carrying integrated
lentivirus were selected with an antibiotic to eliminate
non-transduced cells. The screen dose phase was theninitiated and cell populations were treated with media
containing vemurafenib (2μM) or control (DMSO), each in tworeplicates. When control treated cells reached population
doubling 16, end pellets were collected, genomic DNA
was extracted and guideRNA abundance in each condition
Figure 6: Genes which were found depleted in the vemurafenibtreated population included ITGB5 and EGFR, which are known
sensitising factors to treatment with this drug.

measured by NGS.

References
Cross, B. C. S. et al., Sci. Rep. 2016; 6(31782)

Summary

Davies et al., Nature. 2002 Jun 27;417(6892):949-54

Taken together, we have used a proof-of-concept approach
to examine the ability of our CRISPRi platform to produce

Flaherty et al., N. Engl. J. Med. 2010 Aug 26;363(9):809-19

resistance to the BRAF inhibitor vemurafenib. We were able

Horlbeck, M. A. et al., eLife. 2016; 5

to identify all validated genes previously shown to confer

Huang et al., Cell. 2012 Nov 21;151(5):937-50

resistance to vemurafenib treatment by the CRISPR-Cas9
knockout technology. Overall, the platform performance wasKonermann, S. et al., Nature. 2015;517(7536):583-8

very high, with excellent precision and hit identification power.

Li et al., Genome Biol. 2014;15(12):554

As a new member of the genetic manipulation toolbox,

Shalem et al., Science. 2014 Jan 3;343(6166):84-7

CRISPRi will be invaluable to study hypomorphic

Whittaker et al., Cancer Discov. 2013 Mar;3(3):350-62

phenotypes, such as those involving essential genes.

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