Profiling APOL1 Nephropathy Risk Variants in Genome-Edited Kidney

Original Investigation

Proﬁling APOL1 Nephropathy Risk Variants in Genome-Edited Kidney Organoids with Single-Cell Transcriptomics

Esther Liu,1 Behram Radmanesh,1 Byungha H. Chung,2 Michael D. Donnan,1 Dan Yi,1 Amal Dadi,1 Kelly D. Smith,3 Jonathan Himmelfarb,2 Mingyao Li,4 Benjamin S. Freedman,2,3 and Jennie Lin 1,5

Abstract Background DNA variants in APOL1 associate with kidney disease, but the pathophysiologic mechanisms remain incompletely understood. Model organisms lack the APOL1 gene, limiting the degree to which disease states can be recapitulated. Here we present single-cell RNA sequencing (scRNA-seq) of genome-edited human kidney organoids as a platform for proﬁling effects of APOL1 risk variants in diverse nephron cell types.

Methods We performed footprint-free CRISPR-Cas9 genome editing of human induced pluripotent stem cells (iPSCs) to knock in APOL1 high-risk G1 variants at the native genomic locus. iPSCs were differentiated into kidney organoids, treated with vehicle, IFN-g, or the combination of IFN-g and tunicamycin, and analyzed with scRNA-seq to proﬁle cell-speciﬁc changes in differential gene expression patterns, compared with isogenic G0 controls.

Results Both G0 and G1 iPSCs differentiated into kidney organoids containing nephron-like structures with glomerular epithelial cells, proximal tubules, distal tubules, and endothelial cells. Organoids expressed detectable APOL1 only after exposure to IFN-g. scRNA-seq revealed cell type–speciﬁc differences in G1 organoid response to APOL1 induction. Additional stress of tunicamycin exposure led to increased glomerular epithelial cell dedifferentiation in G1 organoids.

Conclusions Single-cell transcriptomic proﬁling of human genome-edited kidney organoids expressing APOL1 risk variants provides a novel platform for studying the pathophysiology of APOL1-mediated kidney disease. KIDNEY360 1: 203–215, 2020. doi: https://doi.org/10.34067/KID.0000422019

Introduction Human kidney organoids derived from induced Apolipoprotein L1 (APOL1)-mediated kidney disease pluripotent stem cells (iPSCs) can be used to model accounts for a portion of the excess risk of CKD and genetic disease mechanisms in the native genomic ESKD among black patients (1,2). The APOL1 high-risk context and cell-type heterogeneity within the kid- genotype, defined as the presence of two risk alleles ney (5–9). Using CRISPR-Cas9–mediated genome (G1 or G2 coding variants), increases the risk of devel- editing, we engineered iPSCs homozygous for the oping CKD, but not all individuals with the high- G1 risk allele and differentiated these cells into risk genotype develop disease (3,4). Much remains three-dimensional (3D) kidney organoids. To eval- unknown regarding mechanisms and modifiers that uate cell type–specific effects of the APOL1 high- render the disease incompletely penetrant, and com- risk genotype, we also performed single-cell RNA plex interactions underlying these mechanisms are sequencing (scRNA-seq), which we and others have difficult to model outside APOL1’snativegenomic previously leveraged to uncover novel biology of locus. As such, current gaps in knowledge may not be how cell-specific phenotypes contribute to kidney fully addressed by induction of transgenic APOL1 development or disease in organoids and other expression in vivo or in vitro. Additionally, because models (10–14). Here we present the application APOL1 is widely expressed across different cell types, of genome-edited, iPSC-derived kidney organoids studying APOL1 risk variants solely within a specific and single-cell transcriptomics to profile APOL1- type of cell (e.g., podocytes) may not fully capture how mediated effects on kidneyorganoidsrelevantto these variants affect the kidney. disease processes.

1Division of Nephrology and Hypertension, Department of Medicine, Feinberg Cardiovascular and Renal Research Institute, Northwestern University Feinberg School of Medicine, Chicago, Illinois; 2Division of Nephrology, Department of Medicine, Kidney Research Institute, Institute for Stem Cell and Regenerative Medicine, University of Washington, Seattle, Washington; 3Department of Pathology, University of Washington, Seattle, Washington; 4Department of Biostatistics, Epidemiology, and Informatics, University of Pennsylvania, Philadelphia, Pennsylvania; and 5Section of Nephrology, Jesse Brown Veterans Affairs Medical Center, Chicago, Illinois

Correspondence: Dr. Jennie Lin, Northwestern University, 303 E Superior Street, Simpson Querrey Biomedical Research Center 8-405, Chicago, IL 60611. Email: [email protected] www.kidney360.org Vol 1 March, 2020 Copyright © 2020 by the American Society of Nephrology 203 204 KIDNEY360

Materials and Methods 10 mg/ml puromycin was added to iPSC culture to select iPSC Culture for cells expressing the donor plasmid (Supplemental iPSC lines previously derived from fibroblasts from a Figure 1A). Seven days later, iPSC colonies were evaluated non-African ancestry donor (1016SevA; Harvard Stem Cell for insertion of HDR template by PCR and Sanger sequenc- Institute) (15–18) and PBMCs from an African ancestry ing validation. After expansion of the successfully knocked-in donor (Penn134-61-26; WiCell) were maintained in feeder- colonies into separate lines, the piggyBac transposase expression free culture on 10-cm dishes coated with 0.5% Geltrex vector (Transposagen Bio) was introduced by electropo- (Gibco) in Modified Tenneille’s Special Recipe 1 (mTeSR1; ration. Additional screening of genotype was performed STEMCELL Technologies), supplemented with 1% penicil- to validate the puromycin cassette excision. lin/streptomycin (Gibco) and 0.02% Plasmocin (Invivogen). fi iPSCs were con rmed to be mycoplasma-free and below iPSC-Derived Kidney Organoid Differentiation passage 48. They were passaged using 1:3 Accutase (STEM- iPSCs were differentiated into kidney organoids follow- CELL Technologies). ing the previously published protocol by Freedman et al. (5) (Figure 1B). Briefly, iPSCs were dissociated with 1:3 Accu- tase and plated onto 24-well plates precoated with 0.5% CRISPR-Cas9 Genome Editing GelTrex in mTeSR1 supplemented with 10 mM Y-27632 APOL1 G1 risk variants (rs73885319 and rs60910145) ROCK Inhibitor (STEMCELL Technologies). After 24 hours, were introduced into the 1016SevA iPSC line through a another layer of GelTrex at 1.5% was added in mTeSR1 genomic footprint-free approach (Figure 1A, Supplemental media. At the end of day 4, the medium was replaced with fl Figure 1A) (19,20). Brie y, the homology-directed repair Advanced RPMI (Gibco) supplemented with 12 mM CHIR- (HDR) template containing the G1 variants was engineered 99021 and 10 ng/ml noggin (STEMCELL Technologies). using the MV-PGK-Puro-TK vector (Transposagen Bio), Approximately 60 hours later, the medium was changed referred to as the PMV vector, which houses a removable to Advanced RPMI with B27 (Gibco). Organoids were cul- fl puromycin selection cassette anked by two homology tured in this medium until collection at day 25. arms. The puromycin cassette is excisable by a piggyBac transposase, leaving only a “TTAA” sequence behind that Induction of APOL1 Expression and Endoplasmic Reticulum can be seamlessly introduced into a coding sequence by Stress carefully choosing sites where the change would be synon- Day 24 G0 and G1 kidney organoids in identically plated ymous. The G1 variants were engineered by two-step PCR wells of a 24-well plate were treated with IFN-g (25 ng/ml; of G0 genomic DNA (Supplemental Figure 1A, Supplemen- PeproTech) for 24 hours to induce APOL1 expression. This tal Table 1) to create the donor template for homology arm dose approximates previous in vitro IFN-g doses used for A, designed to flank the upstream portion of the puromycin macrophage activation (22,23). Endoplasmic reticulum (ER) selection cassette. Arm B, designed to flank the downstream stress was induced by adding 5 mM tunicamycin (Tocris) for end of the selection cassette, was amplified from G0 24 hours. genomic DNA by traditional PCR. Both arm A and arm B underwent separate TOPO TA cloning reactions (Invitro- gen) for insertion into a stable vector for subsequent sub- scRNA-seq cloning into the PMV vector. Stepwise sequential double We performed scRNA-seq on G0 and G1 day-25 kidney restriction-enzyme digests and homology-arm ligations organoids on the 1016SevA background. The organoids were performed on the PMV vector with the following pairs were treated with vehicle, IFN-g, or both IFN-g and tuni- of restriction enzymes: Not1-High Fidelity (HF) and Bbs1- camycin for 24 hours. Organoids were dissociated from the HF, Nco1-HF, and Bsa1-HF (New England Biolabs). The well with TrypLE Express (Gibco) and processed into single- ends of both homology arms bordering the cassette harbor cell suspension by gentle intermittent pipetting while incu- the TTAA piggyBac transposase cut sequence, thus allowing bating in a ThermoMixer (Eppendorf) for up to 15 minutes. 3 for the transposase to excise the cassette from both ends and Single-cell libraries were prepared using the 10 Genomics 9 leave behind the TTAA sequence in a scarless fashion (Sup- Chromium droplet-based platform and the Single Cell 5 3 plemental Figure 1B). To make this genome-editing event Library Construction Kit (10 Genomics), which was 9 footprint-free, we selected a codon site that would allow the chosen to increase read coverage over the 3 chemistry. TTAA nucleotide sequence to be knocked in without alter- At least three technical replicates (different wells from the ing the APOL1 amino acid sequence. We identified a leucine same experiment) were included in each prepared library, (an amino acid encoded by six different codons including with targeted cell recovery of 4000 cells per library. Each TTA) flanked by an adenine to be the site of cassette entry experimental condition was represented by at least two and excision (Supplemental Figure 1C). A guide RNA different libraries. These libraries were assessed for quality sequence with a suitable protospacer adjacent motif was control, pooled, and sequenced on the NovaSeq 6000 (Illu- found nearby the excision site (Figure 1A, Supplemental mina) through the University of Illinois Genomics Core. The Table 1) and cloned into gRNA_Cloning Vector (41824; libraries were processed for 150-bp paired-end reads, at an Addgene) (21). The donor template incorporates a point average sequencing depth of 114,000 reads per cell. mutation at the protospacer-adjacent-motif site to destroy it after HDR to prevent recutting. iPSCs were then electro- Immunofluorescence porated with the guide vector, hCas9 (41815; Addgene) Organoids were fixed in 4% paraformaldehyde for 15 (21), and the G1-PMV donor plasmid (control lines were minutes at room temperature. After fixing, samples were electroporated with the guide vector only). After 48 hours, washed in PBS, blocked in 5% donkey serum (Millipore)/ KIDNEY360 1: 203–215, March, 2020 Profiling APOL1 Risk Variants in Genome-Edited Kidney Organoids, Liu et al. 205

A APOL1 Puromycin Selection piggyBac TTAA transposase TTAA //

gRNA Protospacer PAM Footprint-free excision

* * TTAA Puro R TTAA Pro Val Gly Phe Phe Leu Val Glu Glu Lys Leu Asn Met Leu CCT GGGTA C TTTT CTTTT C GGGGGGG CA A AA C T AAA C A TTT G A rs73885319 rs60910145 G1 Variants Ser342Gly Ile384Met

HDR Donor Template

B mTeSR1 Advanced RPMI Y27632 GelTrex CHIR99021 B27

Single Cells Cavitated Spheroids Mesenchyme Tubular Organoids

Day 0 1 2 4.5 6 14

C DNA PODXL LTL E-Cad Merge G0 Day 21 100 µm G1 Day 21 100 µm

Figure 1. | Engineering APOL1 G1 kidney organoids from induced pluripotent stem cells. (A) Schematic summarizing the CRISPR-Cas9 approach to knocking in the G1 risk variants rs73885319 and rs60910145 into the 1016SevA line, including the chosen protospacer, homology- directed repair (HDR) donor template design leveraging the piggyBac transposon system, and Sanger sequencing validation of successful variant knock-in and selection cassette excision. (B) Overview of the Freedman kidney organoid differentiation protocol, with light microscopy of the 1016SevA line forming tubular organoids. (C) Confocal immunoﬂuorescence images of nephron markers in representative G0 and G1 organoids on day 21 of differentiation. E-Cad, E-cadherin; gDNA, genomic DNA; mTeSR1, Modiﬁed Tenneille’s Special Recipe 1. 206 KIDNEY360

0.3% Triton X-100/PBS for 1 hour at room temperature, Figure 1, A–C). Because CRISPR-mediated genome editing incubated overnight in 3% BSA (Millipore)/PBS with primary can occasionally induce chromosomal changes (28), we antibodies, washed, incubated with Alexa-Fluor secondary verified that our genome-edited iPSCs maintained a nor- antibodies (Invitrogen) and 49,6-diamidino-2-phenylindole, mal karyotype (Supplemental Figure 1, D and E). and washed into PBS for storage. Primary antibodies inclu- To model the G1 variants within a kidney context, we ded PODXL (AF1658, 1:500; R&D) and ECAD (ab11512, 1: differentiated the G0 and G1 1016SevA lines into kidney 500; Abcam). Stains included fluorescein-labeled LTL (FL- organoids using an adherent culture protocol we have pre- 1321, 1:500; Vector Labs). Fluorescence images were cap- viously established (Figure 1B)(5–7,13,14). Both G0 and G1 tured using an inverted Nikon epifluorescence Eclipse Ti or 1016SevA iPSC lines differentiated into kidney organoids A1R confocal microscope. without major structural differences, expressing markers of nephron structure including PODXL in glomerular epithelial cells, LTL in the proximal tubule, and E-cadherin in the Real-Time Quantitative PCR RNA was isolated from day-25 kidney organoids using distal tubule, in appropriately patterned and contiguous the PureLink Kit (Invitrogen). RNA was then reverse tran- segments (Figure 1C). scribed using the High-Capacity cDNA Reverse Transcrip- tion Kit (Applied Biosystems). Real-time quantitative PCR Single-Cell Transcriptomics of G0 and G1 Kidney Organoids (RT-qPCR) reactions for APOL1 (Hs01066280_m1; Thermo To discover if risk-variant APOL1 exerts cell-specific Fisher) and ACTB (Hs01060665_g1) were run in duplicate on effects in terms of APOL1 expression and function, we the QuantStudio 5 Real-Time PCR System (Applied Biosys- performed scRNA-seq on all cells collected from whole tems). Relative APOL1 expression was calculated using the wells of G0 and G1 organoids differentiated from the 2DD 2 CT method. Statistical significance was tested using 1016SevA line from three separate experiments. A total of two-way ANOVA in Graphpad (Prism). 67,337 cells across genotype and experimental conditions passed quality-control metrics (see Supplemental Methods, Immunoblot Supplemental References) and were analyzed using the fl Organoids were washed with PBS and lysed in RIPA integrated analysis work ow of Seurat version 3 (29) (Fig- buffer (Thermo Scientific) with protease inhibitor (Thermo ure 2, A and B), which was chosen to be the primary analysis Scientific) and benzonase nuclease (Thermo Scientific). Cell pipeline to improve normalization for batch effects and lysates were cleared by centrifugation for 10 minutes at evaluate differential expression across clusters. fi fi 14,000 3 g at 4°C. Proteins (20 mg) were heated at 95°C with To further con rm our ndings, we also analyzed the b-mercaptoethanol and then separated by SDS-PAGE data separately with an unsupervised deep-embedding (Invitrogen). Nitrocellulose membranes were blocked in algorithm for single-cell clustering (DESC) (X. Li et al., 5% nonfat milk in PBS with Tween 20 for 1 hour, incubated unpublished data; available at https://www.biorxiv.org/ in primary antibody overnight at 4°C, and then incubated content/10.1101/530378v1). Primary output of unsuper- with horseradish peroxidase–conjugated secondary anti-Ig vised clustering by Seurat yielded 14 clusters (Figure 2B, (1:5000; Abcam). The primary antibodies used in this study Supplemental Figure 3A), seven of which were determined were anti-APOL1 (HPA018885, 1:1000; Sigma) and anti–b- to consist of mesenchymal cells whereas the others included actin (#4970, 1:1000; Cell Signaling Technologies). Immuno- glomerular epithelial cells at early and more mature stages, blot signals were developed under chemiluminescence proximal and distal tubule, cycling cells, neurons, and endo- (Thermo Fisher) and digitally imaged (BioRad). thelial cells (Figure 2, C and D, Supplemental Figure 3A). Cell type was determined by marker genes previously used in our scRNA-seq studies to identify differentiated Bioinformatic Analyses cell types within human kidney organoids, based on Approach to bioinformatic analyses of scRNA-seq data direct comparison of known markers to tissue samples are presented in Supplemental Material. (Figure 2C) (13,14). The abundance of mesenchyme versus epithelial lineages in these whole-well differentiations is relatively high but within the expected range for patient- Results derived iPSC lines, which vary substantially in their effi- Generation of Genome-Edited, Risk-Variant Kidney ciency of differentiation from one individual to the next Organoids (7,14). These clusters were present in both G0 and G1 Using CRISPR-Cas9 genome editing, we engineered an organoids (Supplemental Figure 3B). Similar unsupervised iPSC line homozygous for the APOL1 G1 risk alleles, with clustering was also obtained using DESC (Supplemental the G0 control on an isogenic background from the Figure 4, A and B). 1016SevA line. Unlike previous cell lines used to study risk-variant APOL1 through transgenic expression (24–27), this engineered line houses the G1 variant at its native IFN-g Induces APOL1 Expression in G0 and G1 Kidney genomic locus under the control of APOL1’sendogenous Organoids regulatory elements. To increase HDR efficiency, the donor We next evaluated whether the organoids expressed template contained a puromycin selection cassette flanked APOL1. RT-qPCR on RNA from whole-well organoids dif- by 500-bp homology arms, one of which housed the G1 ferentiated from G0 and G1 1016SevA lines and the G0 variants rs73885319 and rs60910145 (Figure 1A). Success- Penn134-61-26 line revealed that organoids expressed little ful G1-variant knock-in and cassette removal were con- detectable APOL1 under standard culture conditions (Fig- firmed by Sanger sequencing (Figure 1A, Supplemental ure 3, A and B, Supplemental Figure 2), consistent with one KIDNEY360 1: 203–215, March, 2020 Profiling APOL1 Risk Variants in Genome-Edited Kidney Organoids, Liu et al. 207

A B N = 67,337 Mesenchyme Mesenchyme Mesenchyme Mesenchyme G0 Control Cycling G0 + IFN-γ Mesenchyme G0 + IFN-γ + Tunicamycin Early GEC G1 Control Tubule G1 + IFN-γ Neuron G1 + IFN-γ + Tunicamycin Mesenchyme GEC Undefined Mesenchyme Endothelial Cell

C D Glomerular Epithelial Cells

PODXLNPHS1SLC3A1LRP2DPP4TMEM176AWFDC2CLDN4TIE1 TOP2ACENPFPOSTNOSR1PAX2GAP43STMN2 N = 24,988

GEC Mesenchyme Early GEC Neuron PT, DT Early Glomerular Epithelial Cells EC

Cyc Cycling Cells Proximal and Proximal Distal Tubule Tubule M Distal Endothelial Tubule N Cells Undefined

Figure 2. | Overview of single-cell transcriptomics of G0 and G1 APOL1 organoids. (A and B) Uniform Manifold Approximation and Projection (UMAP) visualization of all whole-well G0 and G1 organoid cells profiled by single-cell RNA sequencing (scRNA-seq), integrated using Seurat version 3. (C) Violin plot of marker genes used for cluster identification of cell types, color coded according to labeling of nanodissected UMAP in (D), which separates out the main cell types seen in the organoid away from the extra mesenchyme captured in whole- well sequencing. Cyc, cycling; DT, distal tubule; EC, endothelial cells; GEC, glomerular epithelial cells; N, neuron; M, mesenchyme; PT, proximal tubule. study showing low levels in human kidneys in vivo (30). Gene Expression Signatures of G1 Kidney Organoids Are IFN-g has been implicated as a factor that may induce Specific to Cell Type APOL1 expression in transgenic mice, although whether In contrast to an inducible APOL1 risk-variant overex- this occurs in humans remains unclear (31). Robust APOL1 pression cell model (25), G1 kidney organoids did not expression (mean .4000-fold over ACTB, P50.004 by two- undergo appreciable cell death when APOL1 was expressed way ANOVA) was induced in both G0 and G1 organoids (Supplemental Figure 3B). To determine whether risk-variant when exposed to 25 ng/ml IFN-g for 24 hours (Figure 3A). APOL1 expression causes transcriptome-wide changes, we APOL1 protein expression was confirmed on immunoblot performed differential expression analysis using Seurat. of whole-well organoids, with the appearance of an When comparing G0 and G1 organoids exposed to IFN-g, approximately 40-kDa band, the expected size for APOL1, we found greater variance in gene expression patterns when only in the IFN-g samples (Figure 3B, Supplemental examining each cell type separately than when examining Figure 2). the whole organoid (Figure 4A). In IFN-g–stimulated orga- To identify which organoid cell types express APOL1, noids, very few genes differentially expressed between G0 and underlying effects of APOL1 risk variants on gene and G1 glomerular epithelial cells overlapped with genes expression, scRNA-seq was performed as described differentially expressed between G0 and G1 tubular cells above. As with the RT-qPCR and immunoblot assays, (Figure 4B). Indeed, the genes differentially expressed between scRNA-seq revealed that untreated organoids express little G0 and G1 glomerular epithelial cells stimulated with IFN-g detectable APOL1. However, exposure to IFN-g for 24 hours were enriched for biologic processes related to metabolic induced APOL1 expression across multiple cell types, function, whereas tubular cells stimulated with IFN-g including glomerular epithelial cells, endothelial cells, and exhibited differential (between G0 and G1) expression of tubular cells (Figure 3, C and D, Supplemental Figures 5 genes related to inflammation and protein targeting and and 6). processing (Figure 4C). 208 KIDNEY360

A B C Percent Expressed 20 P = 0.004 Average Expression 100000 40 10000 60 IFN-γ ——(+) (+) ) 1000 012 80 APOL1 Early 100 IFN-γ M PT, DT GEC EC GEC 10 β-Actin —

(over ACTB 1 G0 G1 0.1 (+) G0 Relative APOL1 mRNA 0.01 G1 G0 G1 G0 G1 G0 G1 G0 G1 G0 G1 Control IFN-γ

4 3 2 1

APOL1 Expression 0

Genotype G0 G1 G0 G1 IFN-γ ——(+) (+)

Figure 3. | IFN-g induces APOL1 expression in iPSC-derived kidney organoids. (A) Real-time quantitative PCR of RNA isolated from whole- well G0 and G1 organoids reveal low endogenous APOL1 expression but a .4000-fold induction of APOL1 mRNA relative to ACTB after 24 hours of 25 ng/ml IFN-g treatment (P50.004 by two-way ANOVA). (B) Immunoblot of APOL1 expression in G0 and G1 organoids with 25 ng/ml IFN-g for 24 hours. (C) Dot plot of APOL1 expression in G0 and G1 kidney organoids, with and without IFN-g treatment. Brighter red dots indicate stronger expression level across cells, and dot size reﬂects percentage of cells in a cluster expressing APOL1. (D) UMAP feature plots of nanodissected clusters show APOL1 expression (red dots) at baseline or when treated with 25 ng/ml IFN-g for 24 hours.

To visualize these cell type–specific gene expression pat- to alter stress response and cellular phenotypes in the high- terns induced by IFN-g, we generated normalized transcript risk genotype. ER stress was chosen because ubiquitin D, abundance on violin plots for each cluster (Figure 4, D and E). encoded by UBD, is involved in the ER stress response, and We first plotted genes previously identified by other studies risk-variant APOL1 appears to localize to the ER membrane to be potential modifiers of APOL1-mediated kidney disease. (36). Furthermore, ER stress is becoming an increasingly A large linkage disequilibrium block on chromosome 6 con- recognized driver of complex diseases, including CKD taining UBD and PPP1R18 may house disease-modulating (37–40). To induce ER stress, we treated organoids with genes (32,33), with visible differences between APOL1 gen- 5 mM tunicamycin for 24 hours and observed increased otypes in UBD and PPP1R18 expression in the tubule and expression of unfolded protein response genes EDEM1 and endothelial clusters (Figure 4D). CXCL11 was previously HSPA5 by RT-qPCR (Figure 5A). Likewise, select unfolded found to be upregulated in the glomeruli of patients with protein response and apoptosis genes exhibit a trend of APOL1-mediated kidney disease (24,33); it appears mildly differences in average cell type–cluster expression, as seen more abundant in G1 endothelial cells (Figure 4D). Novel on a heatmap of G0 and G1 glomerular epithelial cell genes such as ASS1 are specifically upregulated in IFN- clusters (Figure 5, B and C), although these genes did not stimulated G1 glomerular epithelial cells, whereas CD74 reach the statistical significance threshold established by the and JAG1 are markedly downregulated in G1 glomerular integrated workflow of Seurat. epithelial cells compared to G0 cells (Figure 4E). ER Stress Induces Greater Dedifferentiation of G1 ER Stress Induces Differential Expression of Stress Response Glomerular Epithelial Cells Genes in G1 Kidney Organoids Heatmap and violin plots of the podocyte markers in Having identified these cell type–specific differences in organoids treated with IFN-g and tunicamycin revealed G1 organoid gene expression, we next evaluated whether relatively decreased expression of PODXL, NPHS1,and introducing an additional stressor alters G1 cell phenotypes. POSTN in the G1 glomerular epithelial cell cluster, suggest- Because APOL1-mediated kidney disease is incompletely ing the G1 organoid may acquire a less differentiated state penetrant, others have proposed a “second-hit” hypothesis under stress (Figure 6, A and B). We also discovered that G1 that individuals carrying two APOL1 risk alleles develop organoids treated with both IFN-g and tunicamycin dem- disease after exposure to environmental or genetic modifiers onstrated less distinct cluster topology seen in partition- (34,35). We tested whether ER stress could provide a stimulus based graph abstraction (41). More specifically, G1 glomerular KIDNEY360 1: 203–215, March, 2020 Profiling APOL1 Risk Variants in Genome-Edited Kidney Organoids, Liu et al. 209

A 5 5 5

4 4 4

3 3 3

2 2 2 G1 Tubule G1 1 1 1

G1 Whole Organoid G1 Glomerular Epithelial Cells 12345 1234 5 1 2345 G0 Whole Organoid G0 Tubule G0 Glomerular Epithelial Cells

B Genes Upregulated in G1 C Gene Ontology of Cell Type Specific Differential Expression Tubule Glomerular Epithelial Cells Protein targeting to ER ATP metabolic process 84 7 70 Viral transcription Coupled electron transport RNA catabolism Protein targeting to ER

Genes Downregulated in G1 Up in G1 Proteasomal catabolism Cristae formation Developmental process ECM organization ECM organization Cell activation 111 18 95 Wound healing Regulated exocytosis

Down in G1 Cell adhesion Immune effector process

0 10203040 0 102030 Glomerular Epithelial Cells -log(p-value) -log(p-value) Tubule

D E

UBD ASS1

G0 G0 CD74 PPP1R18 G1 G1

CXCL11 JAG1

T GEC EC T GEC EC

Figure 4. | scRNA-seq reveals cell type–specific differential expression patterns between G0 and G1 organoids treated with IFN-g. (A) Scatterplots of G0 versus G1 organoid gene expression values across all cell types (left), among tubular cells (middle), and among glomerular epithelial cells (right). Greater variance is seen in the cell type–specific plots. (B) Venn diagrams show little overlap of expression patterns across cell types when comparing which genes are upregulated in G1 IFN-g stimulation over G0 IFN-g stimulation. There is similarly low overlap across cell types for genes downregulated in G1 IFN-g stimulation. (C) Gene Ontology of the differentially expressed genes within each cell type, with 2log(P-value) plotted for each biologic process. Metabolic (green), stress (pink), cell and organelle function (purple), collagen/matrix (gray). (D) Violin plots visualizing cell type–specific expression patterns of putative regulators (24,33,34) of APOL1 abundance. (E) Violin plots visualizing cell type–specific expression patterns of novel genes. ECM, extracellular matrix; ER, endoplasmic reticulum; T, tubule. epithelial cells became closer to the other cell types in stress have more cells scattered along trajectory paths be- spatial relationship, whereas G0 glomerular epithelial cells tween clusters, as well as a smaller proportion of mature still remained more distinct from the other cell clusters glomerular epithelial cells compared with early glomerular (Figure 6C). Trajectory inference of G0 and G1 organoid epithelial cells (Figure 6, E and F). Collectively, these find- glomerular epithelial cells (Figure 6D) revealed that G1 ings were consistent with potential dedifferentiation of G1 organoids, compared with G0 organoids, subjected to ER glomerular epithelial cells during stress. 210 KIDNEY360

A 30 P = 0.01 50 P = 0.01 G0 G0 G1 G1 40 ) ) 20 30

20 10 (over ACTB (over ACTB 10 Relative HSPA5 mRNA Relative EDEM1 mRNA

0 0 IFN-γ — (+) (+) — (+) (+) Tunicamycin — — (+) — — (+)

B C SYVN1 BAD 1.5 ERP44 BAK1 1 1 DNAJB9 0.5 BAX 0 PDIA4 0 BCL2 -0.5 -1 PDIA5 BCL10 -1 BIK PDIA6 -1.5 CASP1 HERPUD2 CASP3 HSPA5 CASP9 DDIT3 CRADD ERN1 DIABLO PPP1R15A FADD EDEM1 SERPINB9 GOSR2 TGFB1 GSK3A TGFB2 IGFBP1 TNFAIP8 HSP90B1 TRADD SEC31A G0 G1 γ SERP1 IFN- (+)(+) Tunicamycin (+) (+) G0 G1 G0 G1 IFN-γ (+) (+)(+)(+) Tunicamycin — — (+) (+)

Figure 5. | ER stress increases stress response in G1 kidney organoids. (A) Real-time quantitative PCR of RNA isolated from whole-well G0 and G1 organoids reveals increased unfolded protein response (UPR) gene expression (EDEM1, HSPA5) in G1 organoids exposed to both IFN-g and tunicamycin (P50.01 by two-way ANOVA). (B) Heatmap depicts relative average expression of UPR-relevant genes for G0 and G1 glomerular epithelial cells subjected to either IFN-g alone or both IFN-g and tunicamycin. (C) Heatmap depicts relative average expression of apoptosis- relevant genes for G0 and G1 glomerular epithelial cells subjected to both IFN-g and tunicamycin.

Discussion By expressing the G1 variants in their native genomic We have conducted profiling of genome-edited, iPSC- context, our approach circumvents challenges associated derived kidney organoids to detect the potential effect of with studying APOL1 in model organisms and trans- APOL1 risk variants on cellular phenotype and stress. With genic cell lines; for instance, transgenic overexpression our novel platform of integrating genome editing, 3D kid- that may introduce toxic nonphysiologic doses of APOL1 ney organoid culture, and single-cell transcriptomics, our protein. Because APOL1-mediated kidney disease dem- model system recapitulates IFN-induced APOL1 expression and increased cellular stress in risk-variant organoids sub- onstrates incomplete penetrance (42,43), the ideal model jected to a second hit of ER stress. This system also dem- system would allow for interrogation of native genomic onstrated that gene expressionsignaturesinrisk-variant regulators, including distal enhancer elements and cell- kidney organoids differ among cell types. specific long noncoding RNAs (44). Use of genome editing KIDNEY360 1: 203–215, March, 2020 Profiling APOL1 Risk Variants in Genome-Edited Kidney Organoids, Liu et al. 211

A GECEarly GEC GEC Early GEC B PODXL 2 PODXL 1.5 1 G0 NPHS1 G1 0.5 POSTN 0

G0 G1 G0 G1 G0 G1 G0 G1 IFN-γ — (+) (+) IFN-γ (+)(+) (+)(+) (+) (+) (+) (+) Tunicamycin — — (+) Tunicamycin ——— — (+) (+) (+) (+)

C Glomerular Epithelial Cells Early Glomerular Epithelial Cells Mesenchyme Cycling Cells Proximal and Distal Tubule Endothelial Cells Neurons

2 6 8 2

2 6 7

10 10

4 4 13

8 10 13 13

7 8 4

G0 and G1 Whole Organoids G0 Whole Organoids G1 Whole Organoids IFN-γ — (+) (+) Tunicamycin — (+) (+)

D E GECs

GECs Early GECs Mesenchyme Mesenchyme Early GECs G0 and G1 Control G0 IFN-γ + Tunicamycin G1 IFN-γ + Tunicamycin

CCyCyclingycling CCellsells

Endothelial CellsCells F 40% 34% 13% NNeuronseurons Proximal and GECs DiDistalstal TTubuleubule Early GECs

G0 and G1 G0 G1 IFN-γ — (+) (+) Tunicamycin — (+) (+)

Figure 6. | ER stress promotes dedifferentiation of GECs in G1 kidney organoids. (A) Heatmap depicts relative average expression of podocyte markers for G0 and G1 GECs and early GECs treated with either IFN-g alone or both IFN-g and tunicamycin. (B) Violin plots of PODXL expression in the GEC clusters of G0 and G1 organoids subjected to either IFN-g alone or both IFN-g and tunicamycin. (C) Partition-based graph abstraction (PAGA) (42) visualizes trajectory inference of all organoid single cells. The more mature GECs are connected to nonmesenchyme cell clusters in the topology of the control organoids. For G0 organoids subjected to both IFN-g and tunicamycin, the more mature glomerular cells are still more distant from the mesenchyme. PAGAvisualization of G1 organoids subjected to both IFN-g and tunicamycin reveals less distinct separation of GECs from early GECs and mesenchyme. (D) Trajectory inference UMAP of all sequenced organoids was created using Monocle3. The trajectory of the relationship among mesenchyme, early GECs, and more mature GECs is circled and taken forward to (E), where G1 organoids treated with both IFN-g and tunicamycin (red) have a relatively smaller proportion of GECs to early GECs compared with G0 organoids subjected to the same stressors (orange). (F) The relative number of GECs (black) to early GECs (white) is represented by the bar charts of G0 and G1 control organoids (left), G0 organoids treated with IFN-g and tunicamycin (middle), and G1 organoids treated with IFN-g and tunicamycin (right). 212 KIDNEY360

rather than transgenesis preserves these regulatory interac- and relative abundance of cell types did not differ between tions, including the response to IFN-g, and thus would facil- G0 and G1 organoids at baseline, the difference in this ratio itate validation of molecular modifiers of risk-variant APOL1 between stressed G0 and G1 organoids most likely repre- expression and function. sented a dedifferentiation process induced by injury repro- Another advantage afforded by our platform is the use of duced in data spanning technical replicates in experiments a G0 control on an isogenic background, made possible that were repeated. Although defining the exact mecha- through footprint-free CRISPR-Cas9 genome editing. Our nisms of this second hit in APOL1-mediated kidney dis- footprint-free method leaves no alterations to the amino acid ease is beyond the scope of this study, we demonstrate sequence of APOL1 protein and also does not leave behind that our model system is capable of capturing the subtler any additional DNA (such as loxP sites) that would poten- phenotype of cellular dedifferentiation. tially interfere with native noncoding regulation. Isogenic Our study also has limitations worth consideration. Our backgrounds, where the only difference is the knock-in or study did not include G2 variant organoids, although correction of the disease-associated DNA variants, elim- genome editing to create an isogenic G2 line is underway inates other variants as variables. Thus, this approach and will be important in future studies. Also, our proof- reduces the potential for genetic and epigenetic heterogeneity of-concept single-cell transcriptomics used iPSCs from that would be expected among risk-variant, patient-derived one parent line (1016SevA) from a healthy non-African iPSCs and age- and gender-matched, G0 patient–derived donor, so our work will require further validation from iPSCs as potential confounding modifiers of APOL1 expres- additional risk-variant APOL1 iPSC lines, preferably from sion and function. patients with APOL1-mediated kidney disease, with Because this platform uses 3D kidney organoids, we used matching isogenic genome-edited controls. In addition, scRNA-seq to detect differences in molecular signatures the 1016SevA iPSC line yields relatively immature glo- among cell types in risk-variant organoids. Single-cell tran- merular epithelial cells, which limits the conclusions that scriptomics revealed cell type–specific gene expression dif- can be drawn in terms of APOL1-mediated podocyte ferences between G0 and G1 organoids when APOL1 is biology. Although our data reveals a cell type–specific induced, with little overlap between glomerular epithelial molecular signature of G1 kidney organoids, further cells and tubular cells, suggesting that risk-variant APOL1 scRNA-seq and protein-level validation in organoids could potentially alter transcriptional programs in a cell derived from other iPSC lines that yield mature glomer- type–specific fashion. This result is concordant with find- ular epithelial cells would be needed to highlight disease- ings that human genetic variation exerts cell type–specific relevant cellular mechanisms. Another potential limitation effects in CKD (11) and with a prior finding that glomerular of our model system is the lack of detected APOL1 expres- and tubular compartments of APOL1-mediated FSGS biop- sion at baseline without IFN-g stimulation, a result sies exhibit distinct gene expression patterns (33). that is consistent with one prior study (30) but differs Furthermore, we demonstrated that additional stressors from a more recent study by Ma et al. (46) suggesting can lead to more pronounced dedifferentiation of glomer- baseline expression on immunohistochemistry. This per- ular epithelial cells in G1 organoids. Unlike prior models ceived difference in expression could be due to the altered (25,45), our model system does not lead to much cell death physiologic or maturation state of the kidney organoids in the G1 kidney organoids at 24 hours, nor does it activate in vitro compared to tissue in vivo, to differential sensitivities many proapoptotic genes, consistent with the concept that of the various methodologies applied, or to variation of another stressor is needed to induce a phenotype. We chose expression among different patients. It is nevertheless inter- ER stress as an experimental condition because previous esting and significant that APOL1 mRNA levels increase studies have indicated that risk-variant APOL1 may be upon IFN-g stimulation in organoids. Finally, the organoids regulated by UBD (32), a gene involved in the ER stress generated in this study did not have vascular flow, so response, and that risk-variant APOL1 localizes to the ER APOL1 expression and function in vasculature would not rather than to lipid droplets (36). Expression of risk-variant be fully captured despite the presence of endothelial-like APOL1 alone does not activate a significant unfolded pro- cells. Likewise, although we have previously reported that tein response (as seen in Figure 5B), but some differences can organoid tubules are capable of selective solute transport, be seen for DDIT3, EDEM1, ERN1, GSK3A,andERP44 similar to proximal tubules (5), the organoids generated in upon tunicamycin stimulation, consistent with a second-hit this study lack a blood vessel conduit for continuous reab- hypothesis. With these changes in gene expression, accurate sorptive flux, and may not recapitulate the full range of identification of cells attributed to the glomerular epithelial filtrate reabsorption or specialized ion exchange, a limita- cell cluster among experimental conditions is essential. In tion that may also affect transcriptional profiles and phe- this analysis, the glomerular epithelial cells were identified notype of the tubular cells in our experiments. using the integration workflow of Seurat, which identifies Despite these limitations, our model system, which com- conserved markers in clusters that are present in both con- bines the power of footprint-free genome editing with trol and stimulation conditions, decreasing the probability of organoid culture, provides a human-relevant platform cell type misclassification in the IFN-g and/or tunicamycin- with which future studies can be executed and provides treated organoids. With the cells appropriately assigned to new insight into the potential mechanisms of APOL1- the main glomerular epithelial cell cluster and early glo- mediated kidney disease in diverse kidney cell types. With merular epithelial cell cluster across experimental condi- the power of genome editing, evolving science, and scRNA- tions, we assessed dedifferentiation by the relative ratio of seq, this platform could launch larger-scale mechanistic and “early” glomerular epithelial cells compared with both early screening studies for APOL1-mediated kidney disease, ena- and more mature cells in total. Because the differentiation bling the identification of pathways that could be targeted KIDNEY360 1: 203–215, March, 2020 Profiling APOL1 Risk Variants in Genome-Edited Kidney Organoids, Liu et al. 213

therapeutically in high-risk populations to reduce the inci- Supplemental Figure 4. Scanpy visualization of organoid scRNA- dence of glomerular disease. seq analyzed with the DESC pipeline. Supplemental Figure 5. APOL1 mRNA expression induced by IFN-g. Data Sharing Supplemental Figure 6 Original uncropped images of Western All scRNA-seq data have been deposited in Gene Expression blots for APOL1 protein expression in wholewell kidney organoid Omnibus under accession number GSE135663. samples. Supplemental Table 1: Oligonucleotides. Supplemental Methods. Details of single-cell RNA-seq (scRNA- Acknowledgments seq) analyses. fi We thank Dr. Kiran Musunuru for his input on footprint-free Supplemental References. Speci c to text in this supplement. CRISPR-Cas9 genome editing. We appreciate the massively par- allel sequencing services provided by the University of Illinois References Genomics Core. 1. Genovese G, Friedman DJ, Ross MD, Lecordier L, Uzureau P, The views expressed in this article are those of the authors and do Freedman BI, Bowden DW, Langefeld CD, Oleksyk TK, Uscinski not necessarily reflect the position or policy of the Department of Knob AL, Bernhardy AJ, Hicks PJ, Nelson GW, Vanhollebeke B, Veterans Affairs or the United States Government. Winkler CA, Kopp JB, Pays E, Pollak MR: Association of trypa- nolytic ApoL1 variants with kidney disease in African Americans. Science 329: 841–845, 2010 2. Tzur S, Rosset S, Shemer R, Yudkovsky G, Selig S, Tarekegn A, Author Contributions Bekele E, Bradman N, Wasser WG, Behar DM, Skorecki K: B. Freedman and J. Lin conceptualized the study and provided Missense mutations in the APOL1 gene are highly associated with end stage kidney disease risk previously attributed to the MYH9 supervision; B. Chung, A. Dadi, J. Lin, E. Liu, and K. Smith were gene. Hum Genet 128: 345–350, 2010 responsible for data curation; E. Liu and B. Radmanesh were 3. Parsa A, Kao WHL, Xie D, Astor BC, Li M, Hsu C-Y, Feldman HI, responsible for formal analysis; M. Donnan, J. Himmelfarb, J. Lin, Parekh RS, Kusek JW, Greene TH, Fink JC, Anderson AH, Choi MJ, and E. Liu were responsible for funding acquisition; B. Chung, A. Wright JT Jr, Lash JP, Freedman BI, Ojo A, Winkler CA, Raj DS, Dadi, B. Freedman, J. Himmelfarb, J. Lin, E. Liu, B. Radmanesh, K. Kopp JB, He J, Jensvold NG, Tao K, Lipkowitz MS, Appel LJ; AASK Study Investigators; CRIC Study Investigators: APOL1 risk var- Smith, and D. Yi were responsible for the investigation; E. Liu and K. iants, race, and progression of chronic kidney disease. N Engl Smith were responsible for validation; B. Freedman, J. Himmelfarb, J Med 369: 2183–2196, 2013 J. Lin, E. Liu, B. Radmanesh, and K. Smith wrote the original draft; 4. Foster MC, Coresh J, Fornage M, Astor BC, Grams M, Franceschini M. Donnan, B. Freedman, J. Himmelfarb, B. Radmanesh, K. Smith, N, Boerwinkle E, Parekh RS, Kao WHL: APOL1 variants associate with increased risk of CKD among African Americans. J Am Soc and D. Yi were responsible for resources; B. Chung, A. Dadi, Nephrol 24: 1484–1491, 2013 J. Himmelfarb, and B. Radmanesh were responsible for visual- 5. Freedman BS, Brooks CR, Lam AQ, Fu H, Morizane R, ization; B. Chung and M. Li were responsible for methodology and Agrawal V, Saad AF, Li MK, Hughes MR, Werff RV, Peters DT, software; and all authors reviewed and edited the manuscript. Lu J, Baccei A, Siedlecki AM, Valerius MT, Musunuru K, McNagny KM, Steinman TI, Zhou J, Lerou PH, Bonventre JV: Disclosures Modelling kidney disease with CRISPR-mutant kidney organoids derived from human pluripotent epiblast sphe- B. Freedman is an inventor on patent applications related to roids. Nat Commun 6: 8715, 2015 kidney organoid differentiation and disease modeling and an 6. Kim YK, Refaeli I, Brooks CR, Jing P, Gulieva RE, Hughes MR, advisor for Chinook Therapeutics. J. Himmelfarb reports personal Cruz NM, Liu Y, Churchill AJ, Wang Y, Fu H, Pippin JW, Lin LY, fees from Gilead, personal fees from Maze Therapeutics, and per- Shankland SJ, Vogl AW, McNagny KM, Freedman BS: Gene- edited human kidney organoids reveal mechanisms of disease in sonal fees from Renalytix AI, outside the submitted work. B. Chung, podocyte development. Stem Cells 35: 2366–2378, 2017 A. Dadi, M. Donnan, M. Li, J. Lin, E. Liu, B. Radmanesh, K. Smith, 7. Cruz NM, Song X, Czerniecki SM, Gulieva RE, Churchill AJ, Kim and D. Yi have nothing to disclose. YK, Winston K, Tran LM, Diaz MA, Fu H, Finn LS, Pei Y, Himmelfarb J, Freedman BS: Organoid cystogenesis reveals a Funding critical role of microenvironment in human polycystic kidney disease. Nat Mater 16: 1112–1119, 2017 A portion of this work was supported by the National Institutes of 8. Cruz NM, Freedman BS: CRISPR gene editing in the kidney. Am Health (NIH) National Heart, Lung, and Blood Institute grant K08 J Kidney Dis 71: 874–883, 2018 HL135348 (to J. Lin), National Institute of Biomedical Imaging and 9. Lin J, Musunuru K: Genome engineering tools for building cel- Bioengineering grant U01 EB028892-01 (to B.S. Freedman), and NIH lular models of disease. FEBS J 283: 3222–3231, 2016 10. Park J, Shrestha R, Qiu C, Kondo A, Huang S, Werth M, Li M, National Institute of Diabetes and Digestive and Kidney Diseases Barasch J, Susztak K: Single-cell transcriptomics of the mouse grant UG3TR002158 (to J. Himmelfarb). kidney reveals potential cellular targets of kidney disease. Science 360: 758–763, 2018 Supplemental Material 11. 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