TITLE: Methods from: Multiplex, single-cell CRISPRa screening for cell type specific regulatory elements
AUTHORS: Florence Chardon, Troy McDiarmid

[DESCRIPTION]
CRISPR-based gene activation (CRISPRa) is a promising therapeutic approach for gene therapy, upregulating gene expression by targeting promoters or enhancers in a tissue/cell-type specific manner. Here, we describe an experimental framework that combines highly multiplexed perturbations with single-cell RNA sequencing (sc-RNA-seq) to identify cell-type-specific, CRISPRa-responsive cis-regulatory elements and the gene(s) they regulate. Random combinations of many gRNAs are introduced to each of many cells, which are then profiled and partitioned into test and control groups to test for effect(s) of CRISPRa perturbations of both enhancers and promoters on the expression of neighboring genes. Applying this method to candidate cis-regulatory elements in both K562 cells and iPSC-derived excitatory neurons, we identify gRNAs capable of specifically and potently upregulating target genes, including autism spectrum disorder (ASD) and neurodevelopmental disorder (NDD) risk genes. A consistent pattern is that the responsiveness of individual enhancers to CRISPRa is restricted by cell type, implying a dependency on either chromatin landscape and/or additional trans-acting factors for successful gene activation. The approach outlined here may facilitate large-scale screens for gRNAs that activate therapeutically relevant genes in a cell type-specific manner.

[STEPS]
SECTION: Cell Lines and Culture
1. K562 cell culture
K562s cells are a pseudotriploid ENCODE Tier I erythroleukemia cell line derived from
a female (age 53) with chronic myelogenous leukemia15. All K562 cells were
grown at 37°C, and cultured in RPMI 1640 + L-Glutamine (GIBCO, Cat. No.
11-875-093) supplemented with 10% fetal bovine serum (Rocky Mountain
Biologicals, Cat No. FBS-BSC) and 1% penicillin-streptomycin (GIBCO/ Thermo
Fisher Scientific; Cat. No. 15140122).
SECTION: Cell Lines and Culture
2. Induced pluripotent stem cell (iPSC) culture
Human WTC11 iPSCs equipped with a doxycycline-inducible NGN2 transgene
expressed from the AAVS1 safe-harbor locus as well as an
ecDHFR-dCas9-VPH construct (VPH consists of 12 copies of VP16, fused with a
P65-HSF1 activator domain) expressed from the CLYBL safe-harbor locus were a
gift from the Kampmann lab6. These iPSCs were cultured in mTeSR Plus Basal Medium (Stemcell technologies; Cat. No. 100-0276) on Greiner Cellstar plates (Sigma-Aldrich; assorted Cat. Nos.) coated with Geltrex‱ LDEV-Free, hESC-Qualified, Reduced Growth Factor Basement Membrane
Matrix (Gibco; Cat. No. A1413302) diluted 1:100 in Knockout DMEM (GIBCO/Thermo
Fisher Scientific; Cat. No. 10829018). mTeSR Plus Basal Medium was replaced
every other day. When 70–80% confluent, cells were passaged by aspirating
media, washing with DPBS (GIBCO/Thermo Fisher Scientific; Cat. No. 14190144),
incubating with StemPro Accutase Cell Dissociation Reagent (GIBCO/Thermo Fisher
Scientific; Cat. No. A1110501) at 37 °C for 5 min, diluting Accutase 1:1 in
mTeSR Plus Basal Medium, collecting cells in conical tubes, centrifuging at 800g for
3 min, aspirating supernatant, resuspending cell pellet in mTeSR Plus Basal
Medium supplemented with 0.1% dihydrochloride ROCK Inhibitor (Stemcell
technologies; Cat. No. Y-27632), counting and plating onto Geltrex-coated
plates at the desired number.
SECTION: Cell Lines and Culture
3. Human iPSC-derived neuronal cell culture,
differentiation, and CRISPRa induction
The iPSCs described above were used for the differentiation
protocol below. On day -3, iPSCs were dissociated and centrifuged as above, and
pelleted cells were resuspended in Pre-Differentiation Medium containing the
following: Knockout DMEM/F-12 (GIBCO/Thermo Fisher Scientific; Cat. No.
12660012) as the base, 1X MEM Non-Essential Amino Acids (GIBCO/Thermo Fisher
Scientific; Cat. No. 11140050), 1X N-2 Supplement (GIBCO/ Thermo Fisher
Scientific; Cat. No. 17502048), 10 ng/mL NT-3 (PeproTech; Cat. No. 450-03),
10ng/mL BDNF (PeproTech; Cat. No. 450-02), 1 ug/mL Laminin mouse protein
(Thermo Fisher Scientific; Cat. No. 23017015), 10 nM ROCK inhibitor, and 2
mg/mL doxycycline hyclate (Sigma-Aldrich; Cat. No. D9891) to induce expression
of NGN2. iPSCs were counted and plated at 800K cells per
Geltrex-coated well of a 12-well plate in 1 mL of Pre-Differentiation Medium,
for three days. At day -2 and day -1, media changes were performed using
pre-differentiation medium without ROCK inhibitor. On day -1, 12-well plates
for differentiation were coated with 15 ug/mL Poly-L-Ornithine (Sigma-Aldrich;
Cat. No. P3655) in DPBS, and incubated overnight at 37 degrees Celsius. On day
0, the Poly-L-Ornithine coated plates were washed three times using DPBS, and
the plates were air dried in a 37 degree Celsius incubator until all the DPBS
evaporated. Pre-differentiated cells were dissociated and centrifuged as above,
and pelleted cells were resuspended in Maturation Medium containing the
following: 50% Neurobasal-A medium (GIBCO/Thermo Fisher Scientific; Cat. No.
10888022) and 50% DMEM/F-12 (GIBCO/Thermo Fisher Scientific; Cat. No. 11320033)
as the base, 1X MEM Non-Essential Amino Acids, 0.5X GlutaMAX Supplement
(GIBCO/Thermo Fisher Scientific; Cat. No. 35050061), 0.5X N-2 Supplement, 0.5X
B-27 Supplement (GIBCO/Thermo Fisher Scientific; Cat. No. 17504044), 10 ng/mL
NT-3, 10 ng/mL BDNF, 1 ug/mL Laminin mouse protein, and 2 ug/mL doxycycline
hyclate. Pre-differentiated cells were subsequently counted and plated at
400,000-450,000 cells per well of a 12-well plate coated with Poly-L-Ornithine
in 1 mL of Maturation medium with 20 uM trimethoprim (TMP) (Sigma-Aldrich, Cat
No. 92131) to activate the CRISPRa machinery in these cells (TMP stabilizes the
degron-tagged CRISPRa machinery). On day 7, half of the medium was removed and
an equal volume of fresh Maturation medium without doxycycline was added. On
day 14, half of the medium was removed and twice that volume of fresh medium
without doxycycline was added. On day 19, neurons were harvested for
sc-RNA-seq.
SECTION: Cell Lines and Culture
4. 
SECTION: Cell line generation and CRISPRa validation
5. K562 cells
K562 cells expressing dCas9-VP64 were generated in-house via lentiviral integration of a dCas9-VP64-blast construct7 (Addgene Plasmid #61422) into K562 cells. Cells were selected with 10 ug/mL blasticidin, and polyclonal cells were single-cell sorted into 96-well plates to grow up clonal
cell lines expressing dCas9-VP64. Clonal cell lines were tested for CRISPRa activity by testing the ability of a CRISPRa gRNA to activate a minP-tdTomato construct20, and the highest tdTomato expressing cell line was used for experiments. K562 cells expressing dCas9-VPR were purchased from Horizon Discovery/Perkin Elmer (catalog ID: HD dCas9-VPR-005), and these cells were tested for CRISPRa activity using the same tdTomato expression assay described above.
SECTION: Cell line generation and CRISPRa validation
6. iPSC-derived neurons
Human WTC11 iPSCs equipped with a doxycycline-inducible NGN2 transgene expressed from the AAVS1 safe-harbor locus as well as an ecDHFR-dCas9-VPH construct expressed from the CLYBL
safe-harbor locus were a gift from the Kampmann lab6. These cells were tested
for CRISPRa activity using the same tdTomato expression assay that was used to
validate the K562 cell lines, which is described above.
SECTION: gRNA selection and design
7. Enhancer-targeting gRNAs were selected from our CRISPRi library2, 33. Specifically, 50
spacer sequences (2 per candidate enhancer) were randomly selected from the
list of 664 significant “hit” enhancer-gene pairs in the at-scale library.
Another 50 spacer sequences targeting an additional 25 candidate enhancers
(again 2 per candidate enhancer) were randomly selected from candidate enhancer
non-hits (i.e., gRNAs from the at-scale library targeting candidate
enhancer regions with strong biochemical marks predictive of regulatory
activity that did not yield significant downregulation of any neighboring genes
in our previous CRISPRi study). An additional 30 TSS-positive control gRNAs
were randomly sampled from the top quartile of gRNAs recommended by
Horlbeck et al. (hCRISPRa-v2 library)16. 50 NTC negative
control spacer sequences were also selected from the hCRISPRa-v2 library16. The 313 candidate
promoter targeting gRNAs were either selected from the Horlbeck et al. library16 or designed using
FlashFry33 .
Briefly, 50 candidate promoters of 9 NDD risk genes (TCF4, FOXP1, SCN2A, CHD8, BCL11A, TBR1, SHANK3, SYNGAP1, ANK2)23, 24 were pulled from
Basic GENCODE annotations34 and were filtered
for “type” == “transcript” and “transcript_type” == “protein coding”. Separate
bed files were generated for all promoter regions defined as the 500bp upstream
of each protein coding transcript. Careful attention was paid to the strand
orientation of each transcript when annotating promoter regions. Bed files were
sorted and merged to combine multiple promoters with >1bp overlap into a
single promoter annotation. Transcript bounds provided for each merged promoter
begin +1bp from the end of the promoter and end at the position corresponding
to the longest transcript mapping to that promoter. NGG-protospacer within
these candidate promoters were identified using FlashFry and subsequently
scored using default parameters (see FlashFry manuscript and user guide for a
complete description of scoring metrics/algorithms)33. A TSS-distance metric
was then calculated for each gRNA using human fetal brain 5’ Capped Analysis of
Gene Expression (CAGE) data35, 36 obtained from
FANTOM (https://fantom.gsc.riken.jp/5/sstar/FF:10085-102B4;
CTSS, hg38). First, the strongest FANTOM annotated TSS was identified within
each +/-500 bp region up and downstream of each hg38 Gencode Basic protein
coding transcript TSS. For regions with a tie between the highest scoring
FANTOM TSSs, the TSS position closest to Gencode annotated TSS position was
prioritized. Each candidate sgRNA from FlashFry was annotated with the distance
to the nearest FANTOM TSS using the command “bedtools closest -a
sgRNAs_with_fantom_tss -b strongest_fantom_tss_within_gencode_promoter -D b -t
first.” For Gencode Basic protein coding transcripts without a human fetal
brain FANTOM peak within 500 +/- bp, the distance of each sgRNA to the nearest
Gencode TSS was reported instead. A distance of zero indicates that an sgRNA
overlaps with the nearest annotated TSS. Multiple rounds of successively
relaxing score and distance thresholds were then iterated until the top 4 gRNAs
for each candidate promoter were selected (five selection rounds in total).
Optimal TSS-distances were approximated using genome-wide CRISPRa design rules28. gRNAs flagged for
potentially problematic polythymidine tracks or GC content were excluded. The
gRNA selection criteria used in each round were as follows:

 
Round
     1: 1. TSS Distance between -150 and -75 BP 2. Doench2014OnTarget
     >= 0.2 3. Dangerous_in_genome <= 1 4. Hsu2013
     > 80.

 
Round
     2: 1. TSS Distance between -400 and -50 BP 2. Doench2014OnTarget
     >= 0.2 3. Dangerous_in_genome <= 1 4. Hsu2013
     > 80.

 
Round
     3: 1. TSS Distance between -400 and -50 BP 2. Doench2014OnTarget
     >= 0.2 3. Dangerous_in_genome <= 1 4. Hsu2013
     > 50.

 
Round
     4: 1. TSS Distance between -400 and -50 BP 2. Doench2014OnTarget
     >= 0.2 3. Dangerous_in_genome <= 2 4. Hsu2013 > 50.

 
Round
     5: 1. Doench2014OnTarget >= 0.2 2. Dangerous_in_genome
     <= 2 3. Hsu2013 > 10 4. DoenchCFD_maxOT
     < 0.95
Complete oligo sequences with gRNA spacers and additional
sequences for cloning into piggyFlex are listed in Table S1. Note
all gRNAs in our library are designed/modified to start with a G followed by
the 19 base pair spacer to facilitate Pol III transcription.
SECTION: gRNA library cloning into piggyFlex vector
8. The 493 gRNAs with associated 10N random barcodes were
ordered as an IDT oPool and PCR amplified with Q5 High-Fidelity polymerase
(NEB, Cat. No. M0491S) to make double stranded DNA. The piggyFlex backbone
vector was digested with SalI (NEB, Cat. No. R3138S) and BbsI (NEB, Cat. No.
R0539S) in 10X NEBuffer r2 at 37 degrees Celsius overnight to ensure complete
digestion of the backbone. This digestion cuts out the EF1a-puro-GFP cassette
of the vector which is then added back in a later cloning step. The digestion
product was run on a 1% agarose gel in TAE buffer, and the linear backbone
vector (5098 base pairs in size) was gel extracted using a gel extraction kit
(NEB, Cat. No. T1020S). The second product from the digestion (2878 base pairs)
which contains the EF1a-puro-GFP cassette was saved for a later assembly
reaction in the final cloning step (described below). The PCR amplified IDT
oPool gRNAs with associated 10N random barcodes were cloned into the linear
backbone using NEBuilder HiFi DNA Assembly (NEB, Cat. No. E2621S) using 0.15
pmol of the insert (gRNA library) and 0.02 pmol of the linear backbone.
Assembled product was transformed into electrocompetent cells (NEB, Cat. No.
C3020K) and plasmid DNA was extracted with a midiprep kit (Zymo Research, Cat.
No. D4200). The resulting vector was then digested with SapI (NEB, Cat. No.
R0569S), for one hour at 37 degrees Celsius. Digested product was cleaned with
0.5X AMPure beads (Beckman Coulter, Cat. No. A63880) and cleaned digested
linear backbone was used for a subsequent assembly reaction to add the
EF1a-puro-GFP cassette back into the final piggyFlex vector between the gRNA
sequence and the 10N random barcode sequences. 0.014 pmol of the linear
backbone was assembled with 0.056 pmol of the insert sequence and the assembly
reaction was cleaned with a 0.5X AMPure step. The assembled product was
transformed into electrocompetent cells and plasmid DNA was extracted with a
midiprep kit. The final plasmid library was subsequently PCR amplified and
sequenced to ensure that all 493 gRNAs were successfully cloned into the
piggyFlex vector. Note: The 10N barcode is an additional gRNA identification
strategy that can be used to assign gRNAs to cells, however, we used directly
sequenced gRNAs (from the 10x Genomics capture sequence) to identify gRNAs in
this work as this more accurately assigns gRNA transcripts to cells37.
SECTION: gRNA library cloning into piggyFlex vector
9. 
SECTION: Transfection of the gRNA library and selection for transfected cells
10. K562 cells
16 million K562 cells (8 million K562-VP64 cells
and 8 million K562-VPR cells) were transfected with the gRNA library and the
piggyBac transposase (System Biosciences, Cat. No. PB210PA-1) at a 20:1 molar
ratio of library:transposase using a Lonza 4D nucleofector and the Lonza
nucleofector protocol for K562 cells. The 16 million cells were split across 8
100 uL nucleofection cartridges, with each individual nucleofection cartridge
receiving 2 million cells and 2 ug of total DNA. After nucleofection, cells were
transferred to pre-warmed RPMI media in a cell culture flask and incubated at
37 degrees Celsius. One day after transfection, cells were selected with 2
ug/mL puromycin (GIBCO/Thermo Fisher Scientific; Cat. No. A1113803). After 9
days, cells were harvested for single-cell transcriptome profiling.
SECTION: Transfection of the gRNA library and selection for transfected cells
11. Induced pluripotent stem cells
6 million dCas9-VPH iPSCs (same cells as described above)
were transfected with the gRNA library and the piggyBac transposase at a 5:1
molar ratio of library:transposase using the Lonza nucleofector and the Lonza
nucleofector CB-150 program. The 6 million cells were split across 6 100 uL
nucleofection cartridges, with each individual nucleofection cartridge
receiving 1 million cells and 17.5 ug of total DNA. After nucleofection, cells
were transferred to pre-warmed mTeSr Plus basaI medium with ROCK inhibitor in a
cell culture flask and incubated at 37 degrees Celsius. One day after
transfection, cells were selected with 20 ug/mL puromycin (note: the AAVS1-NGN2
construct has a puromycin resistance cassette on it, so a higher dose of
puromycin was used to successfully select for cells that received a gRNA in the
presence of an existing puromycin resistance cassette). Media changes were
performed daily (mTeSr Plus basaI medium with ROCK inhibitor and 10 ug/mL
puromycin) for seven days prior to initiating neuron differentiation (described
in “Human iPSC-derived neuron cell culture and differentiation” methods
section).
SECTION: 10x Genomics sc-RNA-seq with associated gRNA transcript capture
12. K562 screen
Cells were harvested and prepared into single-cell
suspensions following the 10x Genomics Single Cell Protocols Cell Preparation
Guide (Manual part number CG00053, Rev C). Four lanes were used for the
single-cell transcriptome profiling, with two lanes containing cells from the
K562-VP64 cell line, and two lanes containing cells from the K562-VPR cell
line. Roughly 10,000 cells were captured per lane of a 10x Chromium chip (Next
GEM Chip G) using Chromium Next GEM Single Cell 3ʹ Reagent Kits v3.1 with Feature
Barcoding technology for CRISPR Screening (10x Genomics, Inc, Document number
CG000205, Rev D).
SECTION: 10x Genomics sc-RNA-seq with associated gRNA transcript capture
13. iPSC-derived neuron screen
iPSC-derived neurons were harvested and prepared into
single-cell suspensions following a published protocol 38. Cells were split into
two batches, with one batch going through a fluorescence-activated cell sorting
(FACS) step to sort on the top 40% of green fluorescent protein (GFP)
expression to enrich for neurons with greater numbers of gRNAs integrated, and
the second batch going directly into the 10x Genomics single-cell library
preparation protocol. Sorting on the top 40% of GFP expression resulted in a
two-fold increase in the mean number of gRNAs integrated in those cells as
compared to unsorted cells. Four lanes were used for the single-cell
transcriptome profiling, with two lanes containing GFP-positive sorted cells,
and two lanes containing unsorted cells. Roughly 13,000 cells were captured per
lane of a 10x Chromium high-throughput chip (Next GEM Chip M) using Chromium
Next GEM Single Cell 3’ HT Reagent Kits v3.1 (Dual Index) with Feature Barcode
technology for CRISPR Screening (10x Genomics, Inc, Document number CG000418,
Rev C).
SECTION: 10x Genomics sc-RNA-seq with associated gRNA transcript capture
14. Sequencing of scRNA-seq libraries
Final libraries were sequenced on a NextSeq 2000 P3 100
cycle kit (R1:28 I1:10, I2:10, R2:90) for each screen (K562 and iPSC-derived
neuron screens). Gene expression and gRNA transcript libraries were pooled at a
4:1 ratio for sequencing.
SECTION: 10x Genomics sc-RNA-seq with associated gRNA transcript capture
15. Transcriptome data processing and quality control
filtering for K562 and iPSC-derived neuron screens
CellRanger version 6.0.1 was used to perform bcl2fastq and
count matrix generation. CellRanger mkfastq was run using default parameters,
and CellRanger count was run using the GRCh38-3.0.0 reference transcriptome
from 10x Genomics and default parameters. For the K562 screen, cells with
greater than 10% mitochondrial reads and less than 4000 UMIs were filtered out.
For the iPSC-derived neuron screen, cells with greater than 17% mitochondrial
reads and less than 1500 unique molecular identifiers (UMIs) were filtered out.
After quality control filtering, 33,944 cells were retained in the K562 screen,
and 51,183 cells were retained in the iPSC-derived neuron screen. The resulting
count matrix output after this filtering was used for all downstream analyses.
SECTION: 10x Genomics sc-RNA-seq with associated gRNA transcript capture
16. Neuron differentiation transcriptome projection
Single-cell transcriptome data from a time course study of
iPSC-derived neurons26 was downloaded
from https://www.ebi.ac.uk/biostudies/arrayexpress/studies/E-MTAB-10632 (Accession
No. E-MTAB-10632, matrices_timecourse.tar.gz), and integrated with the neuron
CRISPRa screening dataset described here. Seurat v4 was used for all data
analyses39. The CRISPRa dataset
was randomly downsampled to 5,000 cells for this analysis. Count matrices from
both matrices were filtered to include only shared genes from the two datasets
(n=14,777 genes). SelectIntegrationFeatures() and FindIntegrationAnchors() were
run using default parameters to identify anchors for integration. 20,606
anchors were found and 2,953 anchors were retained for data integration.
IntegrateData() was run using the retained 2,953 anchors to integrate the two
datasets. After integration, standard Seurat single-cell analysis was performed
to scale the data, and run the PCA and UMAP algorithms.
SECTION: gRNA assignment and differential gene expression testing
17. Genomic coordinates (hg38) for final gRNA spacers were
isolated using a loop built around the matchPattern() function from the
BSgenome package40. A 2Mb window (1Mb
upstream and downstream) around each gRNA was then calculated and all genes
within the 2Mb window were isolated using a loop built around ENSEMBL biomaRt
getBM() function41, 42. These 1Mb neighboring
gene sets were then filtered to unique entries (unique HGNC symbols) for
compatibility with the Seurat FindMarkers() function used in DE testing.
A global UMI filter of 5 gRNA UMIs/cell was used to assign
gRNAs to single cell transcriptomes for both K562 and iPSC- derived neuron
datasets (note this heuristic threshold was chosen based on manual inspection
of the UMI count distributions for each gRNA and prior work)2. gRNA UMI counts for
each cell were derived from the count matrix of passing cells output by
CellRanger (which applies an automatic total UMI threshold to cells) and which
also passed QC.
Expression of a given gene within 1Mb of the gRNA of
interest was compared between all cells with a given gRNA and all other cells
as control. log2() fold changes in expression for a given gene were calculated
using the Seurat FindMarkers() function with the following arguments: ident.1 =
gRNA_Cells, ident.2 = Control_Cells, min.pct = 0, min.cells.feature = 0,
min.cells.group = 0, features = target_gene, logfc.threshold = 0. A Wilcoxon
rank-sum test was used to generate raw differential expression P-values.
This process was then iterated for all genes within 1Mb of all gRNAs. NTCs were
tested against all genes within 1Mb of any targeting gRNA. Only tests involving
genes detected in >0.2% of test gRNA and control cells were carried forward.
These raw differential expression P-values were
then used to calculate empirical P-values to call EFDR < 0.1 sets2. Specifically, an
empirical P-value was calculated for each gRNA-gene test as:

 

Empirical P-values were then Benjamini-Hochberg
corrected, and those < 0.1 were kept for 10% EFDR sets. Log2 fold changes
between gRNA and control cells were visualized using the gviz package43 along with tracks
for RefSeq transcripts (ENSEMBL biomaRt), H3K27ac, and ATAC seq peaks. The K562
ATAC and H3K27ac data were downloaded from ENCODE 44. ATAC-seq and H3K27ac
CUT&RUN data from 7-8 week old NGN2-iPSC inducible excitatory neurons was
obtained from Song et al. 201932. As previously
described, ATAC-seq and CUT&RUN reads were trimmed to 50bp using TrimGalore
with the command --hardtrim5 50 before alignment (https://github.com/FelixKrueger/TrimGalore).
ATAC-seq reads were realigned to hg38 using the standard Encode Consortium
ATAC-seq and ChIP-seq pipelines respectively with default settings and pseudo
replicate generation turned off. Trimmed, sorted, duplicate and chrM removed
ATAC-seq bam files from multiple biological replicates were combined into a
single bam file using samtools merge v1.1045. Trimmed CUT&RUN
reads were realigned to hg38 using Bowtie2 v2.3.5.1 with the following settings
-- local --very-sensitive-local --no-mixed --no-discordant -I 10 -X 700 and
output sam files were convert to bam format using samtools view45, 46. Duplicated reads were
removed from the CUT&RUN bam file using Picard MarkDuplicates v2.26.0 with
the --REMOVE_DUPLICATES =true and --ASSUME_SORTED=true options (http://broadinstitute.github.io/picard/).
Finally, bam files were converted using the bedtools genomecov followed by the
UCSC bedGraphToBigWig utility.