shRNA Selection and Quality Control for Cancer Target Gene Validation

Adhana Asfaw; Brenton Paolella; Francisca Vazquez

Jun 17, 2020

shRNA Selection and Quality Control for Cancer Target Gene Validation

This protocol is a draft, published without a DOI.

Adhana Asfaw¹,
Brenton Paolella¹,
Francisca Vazquez¹

¹Broad Institute

Cancer Dependency Map Target Validation
Tech. support email: depmap-tda@broadinstitute.org

Adhana Asfaw

Protocol Citation: Adhana Asfaw, Brenton Paolella, Francisca Vazquez 2020. shRNA Selection and Quality Control for Cancer Target Gene Validation. protocols.io https://protocols.io/view/shrna-selection-and-quality-control-for-cancer-tar-bfmnjk5e

License: This is an open access protocol distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited

Protocol status: Working

We use this protocol and it's working

Created: April 27, 2020

Last Modified: June 17, 2020

Protocol Integer ID: 36238

Abstract

Proper design of shRNA sequences can be challenging, requiring empirical testing of up to 10-20 shRNA sequences. To address these issues, we leverage data from RNAi loss of function screens aggregated by the Cancer Dependency Map project (Depmap.org). We identify and prioritize shRNAs more likely to have both strong “on-target” effects and lower off-target effects ("shRNA Seed effects"). Throughout this protocol, we detail how to identify top shRNAs from these large-scale screens, and provide guidance on the design of seed-matched controls. We then describe how to evaluate the selected shRNAs to identify the shRNAs with the maximal differential between on-target and off target effects. It is important to test multiple shRNAs and their corresponding seed control sequences to ensure they do not retain partial on target activity or have broad off-target toxicity. shRNAs and their seed controls can have different viability effects depending on the design, and the cell line being used, so it is crucial to rigorously test multiple shRNAs in multiple cell lines. If used properly, shRNAs can be a great genetic perturbation reagent for target validation, particularly for inducible in vivo experiments.  

1. shRNA Selection and Evaluation: Genes with high-quality shRNAs tested in RNAi Data

For genes that were profiled in the RNAi datasets, we can use the shRNA quality estimates calculated using DEMETER2 to identify high-quality shRNAs (5). 

Choose hairpin sequences
(a)Select hairpins that that have high “G_eff” and a low “S_eff” and “unpred_offset_mean” to maximize on target effects and minimize off target effects. 

Access the excel sheets on shRNA quality metrics and shRNA sequence to gene mapping from the DEMETER2 found on Figshare. 

For the shRNA sequence to gene mapping, download “shRNA-mapping.csv”

For the shRNA Quality Control Excel metrics, download “D2_combined_hp_data.csv"

Map the gene(s) of interest to the shRNA sequences for that gene

Look up the gene of interest in ‘shRNA-mapping.csv” in the “Gene Symbol” column and extract the matching shRNA target sequences in the “Barcode Sequence” column

Find the shRNA sequences in the “D2_combined_hp_data.csv file”

Choose hairpin sequences

Select hairpins that that have high “G_eff” and a low “S_eff” and “unpred_offset_mean” to maximize on target effects and minimize off target effects. 

A description of the table columns is provided below:

Table of model parameters estimated for each shRNA (shRNAs are indexed by their targeting sequence) includes the following columns:
Geff: Estimated gene knockdown efficacy of each shRNA (alpha_i).
Seff: Estimated off-target efficacy of each shRNA (beta_i)
unpred_offset_mean: Posterior mean of 'unpredicted' across-cell-line average off-target effect per shRNA (c_i)
unpred_offset_sd: Posterior std dev of 'unpredicted' across-cell-line average off-target effect per shRNA (c_i)
hairpin_offset_mean: Posterior mean of additive offset per shRNA and batch (theta_ik), averaged across batches k.
hairpin_offset_sd: Posterior std dev of additive offset per shRNA and batch (theta_ik), averaged across batches (as sqrt(<sigma_k^2>)) 

NOTE: Not all genes have quality shRNA sequences from the shRNA libraries and additional shRNA sequences may need to be designed and tested empirically. It is our experience that some genes may not have suitable shRNA sequences unless 10-20 sequences are tested. In those cases RNAi may be less tractable than alternative experimental systems to inactivate a gene or protein product, such as CRISPR or degron tags.

1. shRNA Selection and Evaluation: Genes without shRNAs quality control from RNAi Data

It is recommended that you design multiple on-target sequences for each gene. Some helpful tools are below:

Whitehead siRNA Design Tool or Horizon Discovery siRNA Design Tool (note both are for siRNA design so alter sequences accordingly)

Various protocols recommend 30-50% GC content

1. shRNA Selection and Evaluation: Cloning shRNAs into Tet Inducible Cellecta vector

To clone shRNA oligonucleotides we prefer the Cellecta shRNA Tet Inducible Expression Vector. The general design for this vector is as follows:

5’-accgG-(21sense)-(Stem-Loop-Stem)-(21antisense)-TTTT-3’

Sense oligo: 
5’-accgGNNNNNNNNNNNNNNNNNNNNNGTTAATATTCATAGCNNNNNNNNNNNNNNNNNNNNNTTTT-3’ 

Antisense oligo: 
5’cgaaAAAANNNNNNNNNNNNNNNNNNNNNGCTATGAATATTAACNNNNNNNNNNNNNNNNNNNNNC-3’

The sense strand is the shRNA target sequence from the Achilles/DRIVE library found in the “D2_combined_hp_data.csv” file

To design a seed control, nucleotides in the 9-11 position in the oligos should be altered to the complement nucleotides. This should disrupt on-target binding, but maintains knockdown of off-target genes.

Notice in the above example that the seed (nucleotides 2-8) remains constant between the on-target shRNA and the seed, hence these sequences being called seed-matched controls.

In certain cases, C9-11 seed controls retain partial on-target knockdown. In those cases it is possible to design seed controls with additional base pair alterations to further reduce on-target gene affinity. 
(For example, controls with positions 9-13 nt can be mutated that retain the seed sequence).

Link to C9-11 design tool

Once you have designed 3-5 targeting sequences and their corresponding seed controls, clone sequences into the Cellecta tet-inducible vector and lentivirally transduce cells to create cell lines stably expressing inducible shRNA vector.

2. Evaluation of KD by qRT-PCR or western blot

We evaluate on-target knockdown performance of each shRNA and seed control. We use standard lab techniques for both qPCR and western blotting to determine the effect of knockdown in the cell lines of interest. 

4. Assessing cell viability effects with 10-14 day Foci Formation and 7 day Cell Titer Glo assays: CV Assay

To determine the short-term and long-term viability effects of the on-target and seed shRNAs in vitro, we use 7-Day CTGs and Crystal Violet Assays. The 7-Day CTG provides a quantitative short-term readout, while the crystal violet assay provides long-term qualitative data. Both assays are important when assessing on-target viability effects and seed toxicity, as the potency and viability timeline of shRNAs can vary widely between cell lines; seed effects that appear minimal at seven days may have a larger viability effect at the 14-day time point or vice versa. Additionally, seed effects and on-target viability that appear strong in one cell line may not have the same phenotype in another. Therefore, vigorous testing of each cell line is essential in determining its use for future in vivo experiments.

Trypsinize and count the on-target shRNA and associated seed control cell lines

Dilute the cells to 0.18*105/ .06*105cells/mL in 14 mL media
Italicized - Slow growing cell Line
Bold- Fast Growing Cell Line

Plate cell suspension at 1 mL/well according to the plate map below
 
  shX    shX    shX    shX    shX    shX  
  seedX    seedX    seedX    seedX    seedX    seedX

Add 4 mL of media to cell suspension for a final concentration 0.12*105/ .04*105cells/mL in 12 mL

Plate cell suspension in a new 24 well plate at 1mL/well according to the plate map above

Add 6 mL of media to the original cell suspension for a final concentration of 0.06*105/ 0.02*105cells/mL at 12mL

Plate cell suspension in a new 24 well plate at 1mL/well according to the 24 well plate map above

Add doxycycline at a final concentration of 0.5mg/mL, to half the wells according to the plate map below 
  shX -dox    shX -dox    shX - dox    shX +dox    shX +dox    shX +dox  
  seedX -dox    seedX -dox    seedX -dox    seedX +dox    seedX +dox    seedX +dox

4. Assessing cell viability effects with 10-14 day Foci Formation and 7 day Cell Titer Glo assays: CTG

Plate cells in a 96 well for a 7-day CTG according to the plate map below at 2000 cells/well at 200 uL/well. (Note: Seeding density can be optimized for each cell line)
 
  PBS    PBS    PBS    PBS    PBS    PBS                                
  PBS    shX -dox    shX +dox    Seed  -dox    Seed +dox    PBS                                
  PBS    shX -dox    shX +dox    Seed  -dox    Seed +dox    PBS                                
  PBS    shX -dox    shX +dox    Seed  -dox    Seed +dox    PBS                                
  PBS    shX -dox    shX +dox    Seed  -dox    Seed +dox    PBS                                
  PBS    shX -dox    shX +dox    Seed  -dox    Seed +dox    PBS                                
  PBS    shX -dox    shX +dox    Seed  -dox    Seed +dox    PBS                                
  PBS    PBS    PBS    PBS    PBS    PBS                                
 

4. CTG readout

Monitor the – dox wells to ensure the wells are confluent by day 7

Add CTG reagent and readout by the Envision

5. Crystal Violet Fixation

Continuously monitor the 24 well plates to determine when the -dox wells become 100% confluent. Once the 24 well plates become confluent, fix and stain the plate according to the below protocol.

Gently aspirate the media and add 250 uL of 1X PBS to wash the wells. Add PBS to the sides of the wells to not dislodge any cells

Aspirate the PBS and add 250 uL of 4% Paraformeldahyde in 1X PBS. Leave the plates on the shaker for 15 minutes to completely fix the cells

Remove the 4% paraformeldahyde and wash wells with 250 uL of water.

Remove the water and add 250 uL Crystal Violet to each well. Leave plates on shaker for 20 minutes to stain cells

Remove the crystal violet stain and wash wells multiple times with water until the residual crystal violet is completely removed. 

Let the plates dry for 24 hours and then image these plates on a scanner (600 dpi, increased brightness). 

To quantify the crystal violet stain, add 250 uL of 10% acetic acid to each of the wells. Place plates on the shaker for 20 minutes to remove crystal violet stain from cells

In a 96-well plate, take 25 uL from each well and dilute it in 75 uL water according to the plate map below. Measure the OD at 600 nm.
 
  shX-1  -dox    shX-1  -dox    shX-1  -dox    shX-1  -dox    seedX-1  -dox    seedX-1  -dox    seedX-1  -dox    seedX-1  -dox                      
  shX-1  +dox    shX-1  +dox    shX-1  +dox    shX-1  +dox    seedX-1  +dox    seedX-1  +dox    seedX-1  +dox    seedX-1  +dox                      
  shX-2  -dox    shX-2  -dox    shX-2  -dox    shX-2  -dox    seedX-2  -dox    seedX-2  -dox    seedX-2  -dox    seedX-2  -dox                      
  shX-2  +dox    shX-2  +dox    shX-2  +dox    shX-2  +dox    seedX-2  +dox    seedX-2  +dox    seedX-2  +dox    seedX-2  +dox                      
  shX-3 -dox    shX-3 -dox    shX-3 -dox    shX-3 -dox    seedX-3  -dox    seedX-3  -dox    seedX-3  -dox    seedX-3  -dox                      
  shX-3  +dox    shX-3  +dox    shX-3  +dox    shX-3  +dox    seedX-3  +dox    seedX-3  +dox    seedX-3  +dox    seedX-3  +dox                      
                                                            
                                                            
 

shX	shX	shX	shX	shX	shX
seedX	seedX	seedX	seedX	seedX	seedX

shX -dox	shX -dox	shX - dox	shX +dox	shX +dox	shX +dox
seedX -dox	seedX -dox	seedX -dox	seedX +dox	seedX +dox	seedX +dox

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shRNA Selection and Quality Control for Cancer Target Gene Validation