A CRISPR-Based Screen for Hedgehog Signaling Provides Insights Into Ciliary Function and Ciliopathies

Articles https://doi.org/10.1038/s41588-018-0054-7

A CRISPR-based screen for Hedgehog signaling provides insights into ciliary function and ciliopathies

David K. Breslow 1,2,7*, Sascha Hoogendoorn 3,7, Adam R. Kopp2, David W. Morgens4, Brandon K. Vu2, Margaret C. Kennedy1, Kyuho Han4, Amy Li4, Gaelen T. Hess4, Michael C. Bassik4, James K. Chen 3,5* and Maxence V. Nachury 2,6*

Primary cilia organize Hedgehog signaling and shape embryonic development, and their dysregulation is the unifying cause of ciliopathies. We conducted a functional genomic screen for Hedgehog signaling by engineering antibiotic-based selection of Hedgehog-responsive cells and applying genome-wide CRISPR-mediated gene disruption. The screen can robustly identify factors required for ciliary signaling with few false positives or false negatives. Characterization of hit genes uncovered novel components of several ciliary structures, including a protein complex that contains δ-tubulin and ε-tubulin and is required for centriole maintenance. The screen also provides an unbiased tool for classifying ciliopathies and showed that many congenital heart disorders are caused by loss of ciliary signaling. Collectively, our study enables a systematic analysis of ciliary function and of ciliopathies, and also defines a versatile platform for dissecting signaling pathways through CRISPR-based screening.

he primary cilium is a surface-exposed microtubule-based approach. Indeed, most studies to date have searched for genes that compartment that serves as an organizing center for diverse either intrinsically affect cell growth or affect sensitivity to applied Tsignaling pathways1–3. Mutations affecting cilia cause ciliopa- perturbations16–23. thies, a group of developmental disorders including Joubert syn- Here, we engineered a Hh-pathway-sensitive reporter to enable drome, Meckel syndrome (MKS), nephronophthisis (NPHP), and an antibiotic-based selection platform. Combining this reporter Bardet–Biedl Syndrome. The defining symptoms of ciliopathies with a single guide RNA (sgRNA) lentiviral library targeting the include skeletal malformations, mental retardation, sensory defects, mouse genome, we conducted a CRISPR-based screen that system- obesity, and kidney cysts, and are thought to arise from misregu- atically identified ciliary components, Hh-signaling machinery, and lation of ciliary signaling pathways. Advances in human genetics ciliopathy genes with few false positives or false negatives. We fur- have led to the identification of more than 90 ciliopathy-associated ther show that previously uncharacterized hits encode new compo- genes4. However, the molecular basis for many ciliopathy cases nents of cilia and centrioles and also include novel ciliopathy genes. remains undiagnosed5, and critical aspects of cilium assembly and function remain poorly understood. Results A leading paradigm for ciliary signaling is the vertebrate Development of a Hh-pathway reporter for pooled screening. Hedgehog (Hh) pathway, which plays key roles in embryonic devel- Pooled functional screening requires the ability to enrich or deplete opment and in cancers such as medulloblastoma and basal cell mutants that exhibit a desired phenotype. Because ciliary signaling carcinoma6,7. Primary cilia are required for Hh-signaling output3, is not intrinsically linked to such a selectable phenotype, we engi- and all core components of the Hh-signaling machinery—from the neered a reporter that converts Hh signaling into antibiotic resis- receptor PTCH1 to the GLI transcriptional effectors—dynamically tance (Fig. 1a,b). This transcriptional reporter was introduced into localize to cilia during signal transduction. mouse NIH-3T3 fibroblasts, a cell line widely used to study Hh sig- Efforts to systematically identify genes needed for cilium assem- naling and cilium biology24, and these cells were then modified to bly or Hh signaling have been reported, but those studies have express Cas9-BFP (and are denoted 3T3-[Shh-BlastR;Cas9] cells). relied on arrayed short interfering RNA (siRNA) libraries and hence To validate our reporter cell line, we virally introduced sgRNAs exhibit the high rates of false positives and false negatives charac- targeting regulators of the Hh pathway (Supplementary Table 1). teristic of such screens8–11. Recently, genome-wide screening using The transmembrane receptor SMO and intraflagellar transport (IFT) CRISPR–Cas9 for gene disruption has emerged as a powerful tool complex subunit IFT88 are required for Hh signaling, whereas SUFU for functional genomics12–15. However, the pooled screening format and GLI3 restrain Hh-pathway activity (Fig. 1c, left). As expected, used in those studies requires a means to select for/against, or oth- sgRNAs targeting Smo or Ift88 severely decreased Sonic Hedgehog erwise isolate, cells exhibiting the desired phenotype, a requirement N-terminal domain (ShhN)-induced blasticidin resistance, whereas that has limited the scope of biological applications amenable to this deleting Gli3 potentiated blasticidin resistance, and targeting Sufu led

1Department of Molecular, Cellular and Developmental Biology, Yale University, New Haven, CT, USA. 2Department of Molecular and Cellular Physiology, Stanford University School of Medicine, Stanford, CA, USA. 3Department of Chemical and Systems Biology, Stanford University School of Medicine, Stanford, CA, USA. 4Department of Genetics, Stanford University School of Medicine, Stanford, CA, USA. 5Department of Developmental Biology, Stanford University School of Medicine, Stanford, CA, USA. 6Present address: Department of Ophthalmology, UCSF, San Francisco, CA, USA. 7These authors contributed equally: David K. Breslow and Sascha Hoogendoorn. *e-mail: [email protected]; [email protected]; [email protected]

a b –ShhN 100 +ShhN

50 8× Gli-BS Pmin BlastR Relative viability (%)

0 c SHH 0.11.0 10.0 DMSO Blasticidin (μg/ml) Positive regulators PTCH1 Negative regulators 150 –ShhN SMO 100 +ShhN

( μ g/ml ) 50 PKA 50 15 SUFU GLI2/3R 10 GLI2/3FL GLI2/3A 5 Blasticidin IC

GLI1 Target genes 0 sgRNA: – Ctrl Sufu Gli3 Ift88 Smo-1 d sgRNA library (10 sgRNAs/gene) Gene A (positive Hh-pathway regulator) sgRNAs Gene B (negative Hh-pathway regulator) sgRNAs Gene C (noncilia/Hh-pathway gene) sgRNAs Control sgRNAs sgRNA lentivirus Two rounds signaling & blasticidin selection Selected

Unselected Unselected 3T3-[Shh-BlastR;Cas9] cells sgRNA-infected cells Quantify sgRNAs by deep sequencing

e Unselected +blasticidin f Other sgRNAs Other sgRNAs 125 1.00 100 79.8 Smo sgRNA-2 99.5 Smo sgRNA-2 20.2 100 0.48 80 75 60 0.10 40 50 –blasticidin

Relative frequency 20 25

Relative % Sm o sgRNA-2 +blasticidin 0.01 0 0 0 1 2 101 102 103 104 105 101 102 103 104 105 Rounds of signaling GFP GFP & selection

Fig. 1 | Development of a Hedgehog-pathway reporter-based screening strategy. a, A transcriptional reporter combining eight copies of the GLI binding sequence (8×Gli-BS) with a minimal promoter (Pmin) to convert Hh signals into blasticidin resistance. b, Blasticidin resistance was assayed across a range of concentrations in stimulated (+ShhN) and unstimulated (–ShhN) 3T3-[Shh-BlastR;Cas9] cells. DMSO, dimethylsulfoxide control. Representative curves of 5 independent experiments performed in duplicate. c, Overview of the Hh pathway, with key negative and positive regulators shown in red and green, respectively (left). Effects of control sgRNAs on blasticidin resistance in stimulated and unstimulated 3T3-[Shh-BlastR;Cas9] cells (right). Bars show mean half-maximal inhibitory concentration (IC50) values, and circles show IC50 values from n = 2 (for gene-targeting sgRNAs) or 5 (for no sgRNA and negative- control (Ctrl) sgRNA) independent experiments performed in duplicate. d, Overview of the screening strategy. Cells receiving a negative-control sgRNA, a positive-regulator-targeting sgRNA, and a negative-regulator-targeting sgRNA are gray, green, and red, respectively. e, Flow cytometry histograms of cell mixtures showing the fraction of GFP-positive (Smo sgRNA-2, green) cells relative to cells expressing other library sgRNAs (blue) either in the absence of selection (left) or after two rounds of signaling and selection (right). Representative results from three independent experiments. f, Quantification of cell depletion in e. to ligand-independent blasticidin resistance (Fig. 1c, right). These We next tested the suitability of our reporter cells for pooled effects on blasticidin resistance were paralleled by concordant changes screening, which involves quantifying sgRNAs in blasticidin- in endogenous-pathway outputs, including GLI1 expression and selected and unselected cell pools to identify sgRNAs that con- changes in GLI3 processing (Supplementary Fig. 1a). Additionally, fer a selective advantage or disadvantage (Fig. 1d). We mimicked western blotting confirmed a loss of target-protein expression for screening conditions by mixing GFP-marked cells expressing a Gli3, Ift88, and Sufu sgRNAs (Supplementary Fig. 1a,b). Smo sgRNA with mCherry-marked cells expressing a portion of

Nature Genetics | VOL 50 | MARCH 2018 | 460–471 | www.nature.com/naturegenetics 461 © 2018 Nature America Inc., part of Springer Nature. All rights reserved. Articles NaTuRe GeneTICS our genome-wide sgRNA library. Flow cytometry showed that the P = 9.6 × 10−61, and the Smoothened signaling pathway, with fraction of Smo sgRNA-transduced cells decreased by >12-fold and P < 3.6 × 10−32) as well as some novel categories, thereby indicating by >50-fold after one and two rounds of signaling and selection, new avenues for future investigation (Fig. 2d and Supplementary respectively, thus indicating that our strategy is suitable for pooled Table 5). In some cases, corroborating reports supported these new screening (Fig. 1e,f). connections: mouse mutants for two hit genes that enable diphthamide modification have been found to exhibit Hh-pathway- Genome-wide screening. We conducted our genome-wide screen related phenotypes such as polydactyly29,30, and DPH1 mutations by using a newly developed mouse sgRNA library25. Key features of likewise cause a syndrome with ciliopathy-like features31. this library are the use of ten sgRNAs per gene and the inclusion of We next sought to use reference sets of expected hit and non- >10,000 negative-control sgRNAs that are either nontargeting or that hit genes to quantitatively assess screen performance. We curated a target ‘safe’ sites with no predicted functional role (Supplementary set of ciliogenesis reference genes8 to generate a list of 130 expected Fig. 2a). We lentivirally transduced 3T3-[Shh-BlastR;Cas9] cells hits; for expected nonhits, we used 1,386 olfactory-receptor and with this library at a low multiplicity of infection and maintained vomeronasal-receptor genes (Supplementary Table 3). We then cal- sufficient cell numbers to ensure ~1,000× coverage of the library. culated precision-recall and receiver operating characteristic (ROC) Cells were next exposed to ShhN for 24 h to fully stimulate Hh sig- curves (Fig. 3a) from the P values generated by casTLE. Both per- naling, split into separate blastidicin-selected and unselected pools, formance metrics showed a high area under the curve (0.802 for and then subjected to a second cycle of signaling and selection precision recall, 0.892 for ROC), thus demonstrating that our screen before sgRNA quantification by deep sequencing (Fig. 1d). Genes detects hits with high sensitivity and precision (Fig. 3a). affecting ciliary signaling were identified by comparing sgRNAs in Using a second means of evaluation, we compared the ability of the blastidicin-selected versus unselected cell pools, whereas genes our screen and of three related screens to detect expected hit genes. affecting proliferation were identified by comparing the plasmid These studies used arrayed, siRNA-based screening to study either sgRNA library to the sgRNA population after 15 d of growth in Hh signaling, by using a luciferase reporter10, or ciliogenesis, by the absence of blasticidin. For statistical analysis, a maximum-like- using microscopy-based measures of ciliary markers8,9. Although lihood method termed casTLE26 was used to determine a P value there were notable differences among the screens (for example, for each gene on the basis of the changes in sgRNA abundance. In Roosing et al. incorporated gene expression data to score hits8), addition, the casTLE method estimates the apparent strength of the they each defined a number of hit genes similar to that defined by phenotype (effect size) caused by knockout of a given gene. our screen. Overall, we detected most expected hits across functional categories ranging from Hh-pathway components to ciliop- Assessment of screen performance. We first assessed our ability to athy genes. Furthermore, even though our screen was focused on detect genes affecting growth. This readout was independent of our Hh signaling, we detected a greater fraction of ciliary hits than did reporter-based selection strategy and enabled comparisons to other the ciliogenesis screens across categories including IFT subunits, proliferation-based screens. Using reference positive and negative ciliary motors, and nearly all classes of ciliopathy genes (Fig. 3b,c, essential gene sets27, we found that our screen identified >90% of Supplementary Fig. 3a and Supplementary Table 4). Indeed, among essential genes with a 5% false discovery rate (FDR) (Supplementary the 88 genes encompassed by the categories shown in Fig. 3b Fig. 2b and Supplementary Tables 2 and 3). This performance vali- (except for NPHP-specific genes; described below), we detected dated the design of our sgRNA library and is comparable to that 65 as hits, thus indicating that our screen approached saturation seen with other recently described libraries18,20. (Fig. 3c). Interestingly, few hits were found for genes mutated We next evaluated the ability of our screen to identify genes exclusively in NPHP, thereby raising the possibility that the patho- known to participate in ciliary Hh signaling. Initial inspection of physiology of NPHP may be distinct from that of other ciliopathies screen results for Smo, Ift88, Gli1, Gli3, and Sufu identified sev- (Supplementary Note). eral sgRNAs targeting each gene that were depleted or enriched as In a final assessment of our screening platform, we evaluated expected after blasticidin selection (Fig. 2a). Virtually all known reproducibility across replicate screens. We observed high concor- Hh-signaling components were among the top hits, including the dance among hits for the 95 genes measured in two different batches positive regulators Smo, Grk2, Kif7, Prkar1a, Gli1, and Gli2 and the of the screen, such that 50 of 54 screen hits also scored as hits in the negative regulators Ptch1, Adcy6, Gsk3b, Sufu, and Gli3 (Fig. 2b second batch (Supplementary Fig. 3b). Similarly, strong overlap in and Supplementary Table 4). Our screen also recovered hits that hits was found for 263 genes that were screened in parallel using encompassed nearly all functional and structural elements of cilia, two similar but distinct activators of Hh signaling: PTCH1 ligand thus highlighting the diverse features of cilia needed for signaling (ShhN) and SMO agonist (SAG) (Supplementary Fig. 3c). This (Fig. 2c). For example, several hits encoded components of the reproducibility made it possible to pinpoint genes acting at specific basal body, which nucleates the cilium; the transition fibers, which steps in Hh signal transduction. For example, Gas1 was a hit in the anchor the basal body to the cell surface; the transition zone, which ShhN screen but not in the SAG screen, a result in agreement with gates protein entry into the cilium; the motors that mediate intra- GAS1’s known function as a Shh co-receptor32,33. ciliary transport; and the IFT complexes, which traffic ciliary car- gos (Fig. 2c and Supplementary Table 4). We observed no apparent Identification of new ciliary components. To further establish the correlation between growth and signaling phenotypes, thus indicat- value of our screen, we next set out to characterize six previously ing that our antibiotic selection strategy was not biased by general unstudied hit genes. We first focused on Fam92a and Ttc23 because effects on proliferation (Supplementary Fig. 2c). their gene products contain domains associated with membrane In total, we obtained 472 hits at a 10% FDR and 969 hits at a 20% trafficking. For Fam92a, we generated mutant cell pools by using FDR, and 92% of these hits led to decreased rather than increased individually cloned sgRNAs, then confirmed by sequencing that signaling (Fig. 2b). This asymmetry indicates that, under the satu- most cells contained likely null alleles34. Indeed, a high rate of muta- rating level of ShhN used here, many genes are required to sustain genesis was observed for all genes characterized here and below high-level signaling, whereas fewer genes act to restrain pathway (Supplementary Fig. 4a). Fam92a disruption caused a strong defect output. Gene ontology (GO)-term analysis with the Database for in inducible blasticidin resistance (Supplementary Fig. 4b). This Annotation, Visualization and Integrated Discovery (DAVID)28 defect was also seen for induction of luciferase from a GLI-binding- showed that the top 472 hit genes were enriched in expected site reporter and was rescued by sgRNA-resistant Fam92a (Fig. 4a), functional categories (for example, cilium morphogenesis, with thus indicating that the phenotype is specific and independent of

ab 15 All sgRNAs Nontargeting SmoGGrk2 li1 Smo 5 Gli2 Gli1 Sufu Ift88 Prkar1a Kif7 Sufu 4 10 Gli3 Gli3 10% FDR 3 (n = 472)

Ptch1 Gsk3b

–log( P value) 2 5 Adcy6 20% FDR (n = 969) (sgRNA counts; +blasticidin)

2 1 Nonhit log (n = 19,929) 0 0 –6 –4 –2 024 6 Effect size 0510 15 Depleted Enriched log2(sgRNA counts; no blasticidin)

c Kinesin II BBSome KIF3A IFT dynein BBS BBS4 KIFAP3 IFT-B DYNC2LI1 BBS10 BBS5 KIF3B TRAF3IP1 CLUAP1 IFT20 DYNLL1 MKKS BBS2 IFT80 IFT57 IFT52 WDR34 ARL6 BBS9 IFT81 IFT27 TTC30B DYNC2H1 LZTFL1 BBS7 IFT88 HSPB11 IFT46 DYNLT1 BBS12 BBS1 A IFT172 TTC26 IFT74 WDR60 TTC8 TCTEX1D2 IFT-A Hit percentile B B Other cilia/trafficking WDR19 99.5 A WDR35 99 ARL3 CEP104 EvC zone ICK ARMC9 TTC21B 98 EVC IFT122 ARL13B TXNDC15 EVC2 97 CDK20 INPP5E IFT140 TTC23 TULP3 96 RAB23 TRAPPC11 EFCAB7 IFT43 95 IQCE Transition zone Centrosome B9D2 MKS1 CC2D2A FUZ RSG1 KIAA0753 TMEM107 FAM92A TCTN3 RABL2A TEDC2 KATNB1 TMEM216 CBY1 TMEM67 FOPNL TTBK2 TUBE1 TMEM231 TCTN2 TCTN1 CEP19 TUBD1 CEP295 B9D1 TMEM17 RPGRIP1L OFD1 CEP44 CEP162 Distal CEP83 C5orf42 CEP120 MIB1 SCLT1 TEDC1 CEP76 CEP192 appendage FBF1 C2CD3 FGFR1OP CEP97 PIBF1 WDPCP SASS6

d Diphthamide GPI-anchor Endolysosomal Ubiquitin related Mediator biosynthesis biosynthesis trafficking Top 100 hits: other ZFP598 SOCS3 TRAF3 MED26 DPH1 PIGV PIGA RAB34 BLOC1S1 CAPZB CCNT1 ELOC CAND1 LRRC41 MED25 DPH2 PIGM PIGF VPS41 VPS11 CFL1 SGF29 STUB1 FBXO11 USP8 MED7 DNAJC24 PGAP2 PIGW VPS39 RAB7A PAXIP1 SAP18B KCTD10 MYLIP TRIM24 MED12 DPH5 GPAA1 PIGL HGS VPS33A ASCC2 MLLT3 CUL3 RFWD2 UBE2A MED30 PIGT PIGC VPS16 SNAPIN FLCN CBFB USP5 UBE2M UBA6 MED31 PIGK PIGO CHMP5 BLOC1S2 UBAP1 IREB2 FBXO28 RBX1 KEAP1 MED19 PIGU VPS18 TSC2 LCMT1 UBE2L3 KLHL9 USP9X MED27 GAS1 PPP2R3C UBE2F VPRBP UBR5 MED1 DOT1L TRNAU1AP NOSIP HUWE1 SETD1B

Fig. 2 | Overview of genome-wide-screen results. a, Scatter plot showing log2 of normalized sgRNA counts in selected versus unselected cell pools, with sgRNAs targeting select genes highlighted. b, Volcano plot of casTLE P values versus effect sizes for all genes (after filtering; Methods), with select Hh-pathway components highlighted. Green area indicates a P-value cutoff corresponding to 10% FDR; combined green and yellow areas indicate 20% FDR, and the number of genes in each area is indicated (n). c, Schematic illustration of a primary cilium, with known structural features and select protein products of hit genes shown. Proteins shown are grouped by protein-complex membership or localization, and select newly identified hits are in bold and italics. d, For the indicated categories, proteins encoded by the hit genes identified are listed in order of statistical confidence. In addition to select GO terms enriched among screen hits, the top 100 hits not otherwise listed in a–c are shown. the blasticidin-based readout. Notably, ciliogenesis was severely work was in progress, another group independently established decreased in Fam92a-knockout cell pools (Fig. 4b). To gain further FAM92A as a transition-zone protein that interacts with CBY1 and insight into Fam92a function, we identified FAM92A-associated promotes ciliogenesis38. proteins from cells expressing FAM92A-LAP (S-tag-HRV3C-GFP To characterize the TPR-domain-containing protein TTC23, we localization and affinity-purification tag). The FAM92A-LAP puri- identified TTC23-interacting proteins through affinity purifica- fication specifically recovered CBY1 and DZIP1L, which are compo- tion and mass spectrometry. Notably, the most prominent TTC23- nents of the transition zone35–37 (Fig. 4c and Supplementary Table 6). associated proteins were IQCE and EFCAB7, which localize to a In agreement with this finding, we detected FAM92A localization at proximal region of the cilium known as the Ellis–van Creveld (EvC) the transition zone by using a validated antibody (Supplementary zone39,40 (Fig. 4e and Supplementary Table 6). Although the four Fig. 4c,d) and the FAM92A-LAP cell line (Fig. 4d). While this known EvC-zone proteins are dispensable for cilium assembly, they

a 1.0 1.0 We first examined Txndc15, which encodes a thioredoxin-domain- containing transmembrane protein. A previous analysis of patients 0.8 0.8 with MKS identified a family with a TXNDC15 mutation; however, 42 0.6 0.6 a coincident EXOC4 variant was favored as the causative mutation . We analyzed Txndc15-knockout cells by using luciferase reporter 0.4 0.4 Precision assays and found a clear defect in Hh signaling. Furthermore, wild-

0.2 AUC = 0.802 True-positive rate 0.2 AUC = 0.892 type Txndc15 rescued this defect, whereas the mutant allele found in people with MKS behaved like a null allele (Fig. 5a). We also 0 0 0 0.2 0.4 0.6 0.8 1.0 00.2 0.40.6 0.8 1.0 found that cilia in Txndc15-knockout cells, as compared with con- Recall False-positive rate trol cells, exhibited greater variability in length and lower levels of b the ciliary GTPase ARL13B (Fig. 5b and Supplementary Fig. 5a,b). Ciliary motors IFT complexes Core Hh pathway SRTD/JATD genes Thus, TXNDC15 is likely to be a novel MKS gene. In agreement n = 9 n = 24 n = 7 n = 14 with our findings, a recent follow-up study has identified TXNDC15 10% FDR hit 20% FDR hit mutations in additional families with MKS and has characterized Nonhit ciliary defects resulting from TXNDC15 disruption43. ND Our observation of Armc9 as a screen hit raises the possibility that it may also be a ciliopathy gene. Recently, Kar et al. reported BBS genes MKS genes OFD genes Joubert genes NPHP genes that individuals with a homozygous mutation in ARMC9 exhibit n = 22 n = 11 n = 15 n = 29 n = 9 mental retardation, polydactyly, and ptosis, but a diagnosis of Bardet–Biedl syndrome was disfavored44,45. We found that cilia from Armc9-mutant cells were short and exhibited lower levels of acetylated and polyglutamylated tubulin than did control cells (Fig. 5c and Supplementary Fig. 5c). Furthermore, triple-FLAG-tagged (3×FLAG) ARMC9 localized to the proximal region in cilia when c Core cilia/ciliopathy genes it was stably expressed in IMCD3 or NIH-3T3 cells (Fig. 5d,e and n = 88 Supplementary Fig. 5d). Notably, stimulation of Hh signaling in IMCD3 cells led to redistribution of ARMC9 toward the ciliary tip within 6 h, then a gradual return to its original proximal location, thus suggesting that ARMC9 might become ectocytosed from the cilium tip at later time points46,47 (Fig. 5d,e). This change in local- This study Ref. 8 Ref. 9 Ref. 10 ization was due to Hh signaling, because it was blocked by the (ciliogenesis) (ciliogenesis) (Hh signaling) SMO inhibitor vismodegib (Supplementary Fig. 5e). Furthermore, Armc9-mutant NIH-3T3 cells, compared with control cells, exhib- Fig. 3 | Evaluation of screen performance. a, Assessment of screen ited less ciliary accumulation of GLI2 and GLI3 (but not SMO) performance by using 130 positive and 1,386 negative reference genes, as after pathway activation, thus suggesting that ARMC9 participates determined by precision-recall (left) and ROC curves (right), with the area in the trafficking and/or retention of GLI proteins at the ciliary tip under each curve (AUC) shown. Dashed lines indicate the performance of (Fig. 5f and Supplementary Fig. 5f–h). Collectively, these findings a random classification model. b, Analysis of hit-gene detection for select demonstrate that ARMC9 is a ciliary signaling factor and suggest gene categories (n = number of genes in each category), with the fraction that ARMC9 is a novel ciliopathy gene. Indeed, a recent study has of hits detected at 10% or 20% FDR, not detected, or not determined (ND) confirmed that ARMC9 is mutated in Joubert syndrome and has shown; details in Supplementary Table 3. The NPHP category includes reported that loss of the zebrafish ortholog disrupts cilium assembly genes mutated exclusively in NPHP and not other ciliopathies. SRTD, short and function48. That study has further demonstrated that ARMC9 rib thoracic dysplasia, JATD, Jeune asphyxiating thoracic dysplasia, BBS, localizes to centrioles in RPE cells, whereas we found that ARMC9- Bardet–Biedl syndrome; OFD, oral–facial–digital syndrome. c, Hit-gene FLAG localized to cilia (Fig. 5d,e and Supplementary Fig. 5d) and identification, compared for the indicated datasets. Pie charts show the was present in the ciliary proteome (D. Mick and M.V.N., unpub- fraction of genes detected as hits across all genes included in b, except the lished data). Although the basis for these differing observations NPHP-specific category; details among individual categories are shown in warrants further investigation, these data together show an impor- Supplementary Fig. 3a. tant role for ARMC9 in ciliary signaling. Our evidence that syndromes based on ARMC9 (and DPH1) probably represent unrecognized ciliopathies led us to ask whether are all important for Hh signaling. Furthermore, mutations that our screen might help classify other genetic disorders as ciliopa- affect the EvC-zone proteins EVC and EVC2 cause the ciliopathy thies. In support of this possibility, CWC27, which encodes a pepti- Ellis–van Creveld syndrome39–41. In agreement with TTC23 being a dylprolyl isomerase, and INTS1 and INTS8, which encode subunits new EvC-zone component, TTC23-LAP colocalized with EVC and of the Integrator, are orthologs of screen hits for which patient IQCE at the EvC zone (Fig. 4f and Supplementary Fig. 4e). Although mutations have recently been described49. Some canonical ciliopa- Ttc23 knockout had no effect on cilium assembly, mutant cells, thy symptoms are present in these patients, and thus these disorders compared with control cells, exhibited lower blasticidin resistance may stem from altered ciliary signaling (Supplementary Note). and less localization of IQCE and EVC to the EvC zone (Fig. 4g and These cases of individual disorders that can now be classified as Supplementary Fig. 4b,f–h). Similarly, Iqce RNA interference led to likely ciliopathies led us to ask whether systematic efforts to map decreased localization of TTC23-LAP to the EvC zone (Fig. 4h). disease genes might show broader commonalities with our screen Together these results establish TTC23 as a novel EvC-zone compo- hits. We found that human orthologs of the screen hits Ankrd11, nent that participates in Hh signaling. Cdk13, Chd4, Foxp1, Kmt2d, and Prkd1 were all identified in an exome-sequencing study of patients with congenital heart defects Identification of novel disease genes. Because most ciliopathy genes (CHD)50,51. The significant overlap in these two unbiased datasets were hits in the screen, we asked whether uncharacterized hit genes (P = 6.11 × 10−4) indicates that defective ciliary signaling may be might be mutated in ciliopathies of previously unknown etiology. a prevalent cause of CHDs. Moreover, mutations in these genes

a 10 e NSAF sgRNA: (spectra Coverage Screen rank Protein per 100 aa) (%) (percentile) 8 Ctrl TTC23-LAP 64.3 60 99.0 Fam92a-1 IQCE 28.6 55 97.1 Fam92a-2 6 EFCAB7 18.5 50 97.6

f 4 ARL13B TTC23-LAP 2 IQCE Hh response (fold induction) DNA

0 cDNA GFP Fam92a GFP Fam92a SAG – + BaseTip

b Ctrl sgRNA 100 ARL13B TTC23-LAP FAM92A 50 DNA % ciliated cells 0 – BaseTip sgRNA: -2 Ctrl Fam92a sgRNA-2 Fam92a-1Fam92a g n: 299 344 402 10 ARL13B γ-tubulin Ac-tubulin 5 DNA

0 Ciliary IQCE fluorescence (AU) c NSAF sgRNA: Ctrl Ttc23-1 Ttc23-2 (spectra Coverage Screen rank Protein per 100 aa) (%) (percentile) h TTC23 (GFP) IQCE FAM92A-LAP 38.9 50 99.8 CBY1 11.0 50 99.7 40 20 DZIP1L2.1 10 90.2 20 10 d Ciliary GFP(AU)

FAM92A Ciliary IQCE (AU) 0 0 ARL13B siRNA: Ctrl Iqce Ctrl Iqce γ-tubulin DNA

Ctrl Iqce siRNA: TTC23 (GFP) IQCE ARL13B DNA

Fig. 4 | FAM92A and TTC23 as transition-zone and EvC-zone components. a, Induction of Hh-pathway luciferase reporter, shown for cells transduced with the indicated sgRNAs, transfected with plasmids encoding Fam92a-3×FLAG (Fam92a) or GFP-FKBP (GFP). Cells were untreated or stimulated with SAG. Bars show means of 4 replicate measurements (circles); one of two representative experiments. b, Analysis of cilia in 3T3-[Shh-BlastR;Cas9] cells transduced with the indicated sgRNAs. Bars show mean percentage of ciliated cells; dots show ciliated percentage in each of two independent experiments (>200 cells analyzed per data point). Ac, acetylated. Scale bars, 5 μm. c, Mass spectrometry analysis of FAM92A-associated proteins purified from IMCD3 cells. Normalized spectral abundance factor (NSAF), the percentage of each protein covered by identified peptides, and the percentile rank of corresponding genes in the screen are indicated. d, FAM92A localizes to the transition zone of IMCD3 cells, distal to centrioles (γ-tubulin) and proximal to the ciliary membrane (ARL13B). One of two independent experiments (five fields of view each). Scale bars, 5 μm and 1 μm (insets). e, Mass spectrometry analysis of TTC23-associated proteins purified from IMCD3 cells. f, TTC23-LAP colocalizes with IQCE, distal to FAM92A, in IMCD3 cells. Line plots show normalized intensity along the length of the cilium; tick marks are 1-μm intervals. Representative images shown from two independent experiments (five fields of view each). Scale bars, 5 μm and 1 μm (insets). g, Median ± interquartile range of ciliary IQCE levels, shown for cells transduced with the indicated sgRNAs; one of two independent experiments. AU, arbitrary units. h, Ciliary TTC23-LAP and IQCE signals, analyzed after introduction of Iqce-targeting or control (Ctrl) siRNAs. The median (center line), interquartile range (box boundaries), 10–90% percentile range (whiskers), and outliers are plotted for n = 390 (Ctrl) and n = 300 (Iqce) cilia. One of two (IQCE) or four (GFP) replicate experiments. Scale bars, 1 μm.

a p.Ser225_His229del d +ShhN +ShhN 1 360 * –ShhN (6 h) (30 h) TXNDC15 Thioredoxin TMD

35 ARMC9- 30 sgRNA: 3×FLAG Ctrl 25 Txndc15-1 ARL13B 20 Txndc15-2 15 Ninein

10 e 5 0.10 –ShhN (n = 512) Hh response (fold induction) 6 h ShhN (n = 559) 0 0.08 30 h ShhN (n = 624) cDNA GFP Tx-WTTx-mut GFP Tx-WTTx-mut 0.06 ShhN – + 0.04

0.02 b No cilium

Txndc15 sgRNA-2 Normalized fluorescence Distorted cilium 0.00 ARL13B Normal cilium 0.10.2 0.30.4 0.50.6 0.70.8 0.91.0 A 100 Ac-tubulin Relative distance from base to tip DNA γ-tubulin –ShhN +ShhN 50 f B % cells 100 Experiment 1 0 Experiment 2 – sgRNA: -1 -2 Ctrl Experiment 3

Txndc15Txndc15 50

A (normal): B (distorted): Tip GLI3 fluorescence (%) 0 sgRNA: Ctrl Armc9-1 Armc9-2 Ctrl Armc9-1 Armc9-2

c Ctrl sgRNA Armc9 sgRNA-1 g DPH1 CHD4 Meckel CDK13 FOXP1 PRKD1 Jouber t Alström KMT2D ARMC9 CWC2 7 TXNDC15 ANKRD11 Bardet–Biedl INTS1/INTS8 Senior–Løken ARL13B Ellis–van Crevel d Ac-tubulin Renal disease DNA Developmental delay -tubulin γ Obesity Digital anomalies 8 n = 332 335 477 302 Retinopathy Skeletal dysplasia 6 Heart defects 4 Craniofacial defects Canonical Proposed ciliopathy genes ciliopathies 2

Cilium length ( µ m) Phenotype prevalence: High Medium Low 0 sgRNA: – Ctrl Armc9-1Armc9-2

Fig. 5 | Insights into ciliopathies from previously uncharacterized screen hits. a, TXNDC15, with transmembrane domain (TMD), thioredoxin domain, and MKS-associated mutation indicated (top). Luciferase reporter levels measured for cells transduced with the indicated sgRNAs and transfected with plasmids encoding GFP-FKBP (GFP), wild-type Txndc15-3×FLAG (Tx-WT), or mutant Txndc15-3×FLAG (Tx-mut). Bars show means of 3 replicates (circles); one of two representative experiments. b, Cilia were analyzed in 3T3-[Shh-BlastR;Cas9] cells transduced with the indicated sgRNAs. Bars in graph show percentages of cells with normal, distorted, or absent cilia. Each bar per condition represents an independent experiment with >200 cells counted. Scale bars, 5 μm and 1 μm (insets). c, Cilia analyzed in 3T3-[Shh-BlastR;Cas9] cells transduced with the indicated sgRNAs. Representative images are shown at top. At bottom, median cilium length (center line), interquartile range (box boundaries), 10–90% percentile range (whiskers), and outliers are plotted. One of three independent experiments. Scale bars, 5 μm. d, Analysis of ARMC9-3×FLAG localization relative to centrioles (ninein) and ciliary membrane (ARL13B), shown for IMCD3 cells treated as indicated. Scale bar, 1 μm. e, ARMC-3×FLAG intensity along the length of the cilium from base (position 0) to tip (position 1.0), measured for IMCD3 cells treated as indicated. The mean ± s.d. were plotted after the total intensity in each cilium was normalized to 1.0; one of three representative experiments. f, Fluorescence intensity of GLI3 at the cilium tip, measured for the indicated cells in the presence or absence of ShhN. Mean ± s.e.m. are shown for each of n = 3 independent experiments (at least 250 cilia analyzed per condition). g, Table showing select clinical features in canonical ciliopathies and their observation in the context of specific mutations and syndromes. Colors indicate high (red), moderate (orange), and low (yellow) prevalence.

466 Nature Genetics | VOL 50 | MARCH 2018 | 460–471 | www.nature.com/naturegenetics © 2018 Nature America Inc., part of Springer Nature. All rights reserved. NaTuRe GeneTICS Articles a c and coimmunoprecipitation, and moreover we found that TEDC1 TEDC1-6×Myc ++– and TEDC2 mutually stabilized each other’s expression (Fig. 6c and TagRFP-6×Myc – +– Supplementary Fig. 6b). In further support of our data, two large- TEDC2-3×FLAG – ++ MW scale proteomic datasets have also identified interactions among TagRFP-3×FLAG + –– (kDa) TED-complex proteins71,72. Input 60 WB: Myc 50 To functionally characterize Tedc1 and Tedc2, we examined TEDC2-LAP Centrin2 mutant cell pools and found that they were almost completely γ-tubulin DNA FLAG IP 60 devoid of centrioles, as assessed by staining with antibodies to cen- WB: Myc 50 trin, ninein, polyglutamylated tubulin or -tubulin (Fig. 7a,c,d). b NSAF γ (spectra Coverage Screen rank 60 Mutant cells also lacked cilia (Fig. 7a) and had strong defects in Hh Protein per 100 aa) (%) (percentile) Input 50 signaling (Supplementary Fig. 6c,d). Notably, centrioles and cilia WB: FLAG 40 TEDC2-LAP 46.8 76 99.5 were restored in Tedc1-mutant cells after introduction of sgRNA- TEDC1 47.1 73 99.8 TUBE1 32.661 98.7 60 resistant TEDC1-3×FLAG (Supplementary Fig. 6e,f), which also TUBD1 30.360 99.4 FLAG IP 50 localized to centrioles (Supplementary Fig. 6g). TUBB5 14.454 Lethal WB: FLAG 40 TUBA1B 12.955 Lethal We noted that Tedc1 and Tedc2 mutants exhibited a mild growth CENPJ 4.0 35 85.2 defect (Supplementary Table 3), which is consistent with recent evidence that NIH-3T3 cells lacking centrioles proliferate at a reduced Fig. 6 | TEDC1 and TEDC2 form a tetrameric complex with δ-tubulin and rate73. In contrast, in other cell types, a p53-dependent arrest pre- ε-tubulin. a, IMCD3 cells stably expressing TEDC2-LAP, immunostained vents growth in the absence of centrioles. These observations with antibodies to centrin2 and γ-tubulin to visualize centrioles. Scale prompted us to investigate whether the varying effects of Tedc1 or bars, 5 μm and 2 μm (insets). Representative images are shown for three Tedc2 disruption on proliferation across different cell types could independent experiments. b, Mass spectrometry analysis of TEDC2- enable predictive identification of genes with similar function. We associated proteins purified from IMCD3 cells, showing TEDC1, ε-tubulin, therefore examined a collection of CRISPR-based growth screens δ-tubulin in nearly stoichiometric amounts, as well as α/β-tubulin and conducted in 33 different human cell lines and used hierarchical CENPJ. For each protein, the NSAF, the percentage of the protein covered clustering to group genes on the basis of their cell-type-specific by identified peptides, and the percentile rank of the corresponding gene in growth phenotypes74. This unbiased approach placed TEDC1, the screen dataset are indicated. c, Binding of TEDC1 and TEDC2, assessed TEDC2, and TUBE1 in a single cluster (Fig. 7b and Supplementary via coimmunoprecipitations performed in HEK293T cells transfected Table 7), thus suggesting that they share highly similar functions. with plasmids encoding the indicated proteins. Recovered proteins were Although TUBD1 was not found in this cluster, this absence was analyzed by western blotting (WB). Representative blots are shown for two probably due to ineffective targeting of TUBD1 by the sgRNA independent experiments. IP, immunoprecipitation; MW, molecular weight. library used. Indeed, although other CRISPR screens have reported Additional data in Supplementary Fig. 6b and Supplementary Fig. 8. pronounced growth defects for TUBD1 mutants18,25, ref. 74 did not. To better understand the basis for centriole loss in Tedc1 and Tedc2 mutants, we examined cells at different stages of the cell cycle. appear to cause bona fide ciliopathies, because affected patients Whereas mutant cells typically had zero or one centriole in inter- also exhibit ciliopathy symptoms including craniofacial abnormali- phase, nearly all mitotic cells had excess centrioles (more than four), ties and developmental delay (ANKRD11, CDK13, CHD4, FOXP1, a result suggestive of de novo centriole formation before mitotic KMT2D, and PRKD1), dysgenesis of the corpus callosum (CDK13), entry (Fig. 7c,d and Supplementary Fig. 6h). In contrast, cells exit- polydactyly (CHD4), obesity (ANKRD11), and craniofacial malfor- ing mitosis showed significantly fewer centrioles than did control mations (ANKRD11 and KMT2D)4,50,52 (Fig. 5g). cells (Fig. 7d). Together, these observations suggest that Tedc1 and Tedc2 are dispensable for centriole biogenesis but are required for A new protein complex for centriole stability. Because our screen centriole stability, and newly generated centrioles are rapidly lost as hits include genes encoding the centriolar proteins CEP19, CEP44, cells exit mitosis. In further support of a shared function of TED- CEP120, and CEP295 (refs 53–62), we considered whether other hits complex components, TUBE1- and TUBD1-deficient human cells might also have centriolar functions. Indeed, the protein encoded have recently been shown to have a similar phenotype75. by uncharacterized hit 1600002H07Rik (human C16orf59; official symbol TEDC2) localized to centrioles in IMCD3 cells (Fig. 6a). We Discussion performed affinity purifications and found that 1600002H07Rik- Here we presented a functional screening platform that pairs a path- LAP copurified with the uncharacterized protein 4930427A07Rik way-specific selectable reporter with genome-wide CRISPR-based (human C14orf80) and the distant α/β-tubulin relatives ε-tubulin gene disruption. Applying these technologies to cilium-dependent (TUBE1) and δ-tubulin (TUBD1) (Fig. 6b). All four of the genes Hh signaling, we obtained a comprehensive portrait of cilium biol- encoding these proteins were hits in our screen, and ε-tubulin and ogy that identified hit genes with high sensitivity and specificity. δ-tubulin have previously been linked to centriole assembly and main- Several factors probably contributed to the quality of our screen, tenance63–67. We have therefore renamed 4930427A07Rik (C14orf80) including the pooled screening format, the use of CRISPR for gene and 1600002H07Rik (C16orf59) as Tedc1 and Tedc2, respectively, disruption, and a newly designed sgRNA library (Supplementary because of their association with a tubulin epsilon and delta complex. Note). Furthermore, our use of a selectable pathway reporter makes Our mass spectrometry analysis of TEDC2-associated proteins this technology applicable to virtually any process with a well- showed approximately stoichiometric amounts of TEDC1, TEDC2, defined transcriptional response. ε-tubulin, and δ-tubulin, as seen by comparison of the normalized Our pooled CRISPR-based screening approach enabled us to spectral abundance factors (Fig. 6b and Supplementary Table 6). We generate a rich dataset that should be a valuable resource for dis- also recovered lower amounts of α/β-tubulin and CENPJ, a centrio- secting ciliary signaling, defining ciliopathy genes, and discover- lar regulator of microtubule dynamics68–70. We confirmed copurifica- ing potential therapeutic targets in Hh-driven cancers. Although tion of TUBD1 and TUBE1 with TEDC2 by western blotting, and we siRNA-based screens have contributed to understanding of cilia readily detected these proteins in our TEDC2-LAP purification but and Hh signaling, these datasets have drawbacks of false positives not in a control purification (Supplementary Fig. 6a). The interaction or false negatives that limit their utility. Roosing et al.8 improved between TEDC1 and TEDC2 was also detected by cotransfection their ciliogenesis-screen results by using reference gene sets to help

a WT Tedc1 sgRNA-1 Tedc1 sgRNA-2

GT335 Ninein DNA

Ctrl sgRNA Tedc2 sgRNA-1 Tedc2 sgRNA-2

b CAL120 HCC44 K562D HS294T PANC0327 A375 LNCAP G402 NCIH1373 PATU8902 CADOES1 TC32 RDES EW8 EWS502 BXPC3 T47D CORL105 HT29 NCIH2009 PANC0813 SU8686 PANC1 PATU8988T MHHES1 A673 COLO741 MEWO L33 PC3 TC71 SKES1 TOV112D –2.00 –1.33 –0.67 0.00 0.67 1.33 2.00

TEDC2 TEDC1 TUBE1 c d Ctrl sgRNA

Prophase to Late cytokinesistelophase/ Interphase early telophase Centrin3 ** -tubulin ** γ *** ** DNA *** * ** 100

Tedc1 sgRNA-1 80 Centriole # ≥5 60 3 or 4 2 % of cells 40 1 0 20 Tedc2 sgRNA-2

sgRNA (n): -1 (33) -1 (249) Ctrl (18) Ctrl (37) Ctrl (242) edc1 edc2-2 (27) edc1-1edc2 (52)-2 (55) edc1 edc2-2 (255) T T T T T T

Fig. 7 | The TED complex is required for centriole stability. a, Cells transduced with the indicated sgRNAs were stained with antibodies to ninein (centrioles) and polyglutamylated tubulin (GT335, centrioles and cilia). Scale bar, 5 μm. One of three representative experiments. b, Hierarchical clustering of relative growth scores across the indicated cell lines, revealing that TEDC1, TEDC2, and TUBE1 share a similar pattern of relative fitness. Blue and red shading indicate decreased and increased proliferation, respectively, relative to the average behavior across all cell lines. c, For cells transduced with the indicated sgRNAs, centrioles were visualized by staining with antibodies to centrin3 and γ-tubulin. Insets show centrin3 staining in mitotic cells, marked by yellow arrowheads. Scale bars, 5 μm and 2 μm (insets). Additional data in Supplementary Fig. 6h. One of three representative experiments. d, Centrioles marked by centrin3 and γ-tubulin were counted in cells at the indicated cell-cycle stages. Statistically significant differences in centriole counts are shown for select conditions (*P < 1 × 10−6; **P < 1 × 10−10; ***P < 1 × 10−60, determined by two-sided Fisher’s exact test). Numbers of cells are shown in parentheses.

classify hits and by integrating gene expression datasets with their always be available, or on a priori definition of hits, which could microscopy-based screen data. Our approach achieved high perfor- bias discovery of new hit classes. Our screens are also highly repro- mance without dependence on other data sources, which may not ducible, thereby enabling comparative screening approaches that

468 Nature Genetics | VOL 50 | MARCH 2018 | 460–471 | www.nature.com/naturegenetics © 2018 Nature America Inc., part of Springer Nature. All rights reserved. NaTuRe GeneTICS Articles should be instrumental in uncovering novel factors acting at spe- Because CENPJ is a microcephaly gene80,81, TED-complex components cific steps in Hh signaling. Modifications to our screening strategy, are potential candidate genes for this neurodevelopmental disorder. such as performing screens in other cell lines or in unstimulated (or In summary, we developed a functional screening platform that weakly stimulated) cells, may better replicate certain in vivo signal- provides a resource for investigating long-standing questions in Hh ing modalities and may have improved sensitivity for identifying signaling and primary cilia biology. By further applying these tools, negative regulators of Hh signaling. it may become possible to systematically define vulnerabilities in The value of our screen was demonstrated by the discovery of Hh-pathway-driven cancers, to identify modifiers of Hh-pathway- new genes that participate in ciliary signaling and new candidate inhibiting chemotherapeutics, and to search for suppressors of cil- ciliopathy genes. Although the precise roles of FAM92A at the tran- iopathies that may inform treatment. Integrating this functional sition zone and TTC23 at the EvC zone will require further study, genomic approach with complementary insights from proteomics our screen demonstrates that new components remain to be identi- and human genetics promises a rich tool kit for understanding cili- fied, even for well-studied ciliary structures. Similarly, our analyses ary signaling in health and disease. of TXNDC15, ARMC9, CWC27, DPH1, INTS6, INTS10, ANKRD11, CDK13, CHD4, FOXP1, PRKD1, and KTM2D illustrated that screen Methods hits can help to identify a ciliopathy-causing gene from among a Methods, including statements of data availability and any asso- short list of variants, as is frequently the case in studies involving ciated accession codes and references, are available at https://doi. small pedigrees, and to classify new genetic syndromes as disor- org/10.1038/s41588-018-0054-7. ders of ciliary signaling. With the exception of TXNDC15, all of the aforementioned genes had been previously linked to disease with- Received: 27 June 2017; Accepted: 22 December 2017; out a potential role for cilia described (for example, KMT2D and Published online: 19 February 2018 Kabuki syndrome, MIM 147920; ANKRD11 and KBG syndrome, MIM 148050; and DPH1 and Loucks–Innes syndrome, MIM References 616901). 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Human mutations in integrator complex subunits link P. Beachy (Stanford) for NIH-3T3 cells, 8×Gli-luciferase reporter plasmid, and transcriptome integrity to brain development. PLoS Genet. 13, e1006809 (2017). ShhN-producing HEK293T cells; K. Anderson (Sloan Kettering) for antibody to 52. Sollis, E. et al. Identifcation and functional characterization of de novo SMO; G. Crabtree, K. C. Garcia, and A. Pyle for use of plate readers; N. Dimitrova FOXP1 variants provides novel insights into the etiology of for microscope use; C. Bustamante for use of an Illumina sequencer; R. Rohatgi neurodevelopmental disorder. Hum. Mol. Genet. 25, 546–557 (2016). (Stanford) for antibodies to EVC and IQCE and NIH-3T3 FlpIn cells; P. Jackson 53. Comartin, D. et al. CEP120 and SPICE1 cooperate with CPAP in centriole (Stanford) for IMCD3 FlpIn cells; J. Wang and T. Stearns (Stanford) for sharing elongation. Curr. Biol. 23, 1360–1366 (2013). unpublished results and cDNA for Cby1; and M. Scott for helpful discussions. 54. Lin, Y. N. et al. CEP120 interacts with CPAP and positively regulates centriole This project was supported by NIH Pathway to Independence Award K99/R00 elongation. J. Cell Biol. 202, 211–219 (2013). HD082280 (D.K.B.), Damon Runyon Dale F. Frey Award DFS-11-14 (D.K.B.),

470 Nature Genetics | VOL 50 | MARCH 2018 | 460–471 | www.nature.com/naturegenetics © 2018 Nature America Inc., part of Springer Nature. All rights reserved. NaTuRe GeneTICS Articles a seed grant from the Stanford Center for Systems Biology (D.K.B., S.H., and expertise, the genome-wide sgRNA library, and software for screen data analysis. G.T.H.) and Stanford ChEM-H (M.C.B.), an NWO Rubicon Postdoctoral Fellowship D.K.B. conducted the genome-wide screen and screen data analysis with assistance (S.H.), National Science Foundation Graduate Research Fellowship DGE-114747 from S.H. and A.R.K.; D.K.B., S.H., A.R.K., and M.C.K. functionally characterized hit (D.W.M.), a Walter V. and Idun Berry Award (K.H.), and NIH T32 HG000044 genes of interest, analyzed data, and prepared figures. D.K.B., S.H., J.K.C., and M.V.N. (G.T.H.), DP2 HD084069 (M.C.B.), R01 GM113100 (J.K.C.), and R01 GM089933 wrote the manuscript with assistance from M.C.B.; D.K.B., S.H., G.T.H., M.C.B., J.K.C. (M.V.N.). Cell sorting/flow cytometry was done on instruments in the Stanford and M.V.N. provided funding for the project. Shared FACS Facility, including an instrument supported by NIH shared instrument grant S10RR025518. Mass spectrometry analyses were conducted in the Vincent Competing interests Coates Foundation Mass Spectrometry Laboratory, Stanford University Mass The authors declare no competing interests. Spectrometry and the Stanford Cancer Institute Proteomics/Mass Spectrometry Shared Resource; these centers are supported by Award S10 RR027425 from the National Center for Research Resources and NIH P30 CA124435, respectively. We Additional information thank C. Carstens, B. Borgo, P. Sheffield, and L. Bruhn of Agilent Technologies for Supplementary information accompanies this paper at https://doi.org/10.1038/s41588- cilia-focused oligonucleotide sublibraries. 018-0054-7. Reprints and permissions information is available at www.nature.com/reprints. Author contributions Correspondence and requests for materials should be addressed to D.K.B. or D.K.B., S.H., J.K.C., and M.V.N. conceived the project with advice from M.C.B.; D.K.B. J.K.C. or M.V.N. and S.H. developed the Hh-pathway reporter screening strategy with assistance from Publisher's note: Springer Nature remains neutral with regard to jurisdictional claims in B.K.V.; and D.W.M., K.H., A.L., G.T.H., and M.C.B. provided functional genomics published maps and institutional affiliations.

Methods Stable cell lines for affinity purification and localization studies were generated Experimental models and subject details. Cell lines and cell culture. NIH-3T3 with the FlpIn system (Life Technologies) with IMCD3 FlpIn or NIH-3T3 and HEK293T cells were grown in high-glucose, pyruvate-supplemented DMEM FlpIn cells. Plasmids encoding genes of interest in the pEF5B/FRT-DEST-LAP (Gibco) with 10% fetal bovine serum (FBS), 2 mM glutamine, 10 U/ml penicillin, (or 3×FLAG) vector were transfected into FlpIn cells together with pOG44 Flp and 10 μg/ml streptomycin (Gemini Bio-Products). NIH-3T3 FlpIn cells (gif from recombinase (Life Technologies) with X-tremegene 9 (Roche). Recombined cell R. Rohatgi) were grown in the same medium supplemented with nonessential pools were obtained after selection with blasticidin (Sigma Aldrich). amino acids (Gibco). Light-II NIH-3T3 cells24 were grown in the same medium Rescue of Tedc1-mutant cells was performed by lentiviral transduction with except with 10% bovine calf serum (ATCC), and IMCD3 cells were grown in a construct expressing sgRNA-resistant mouse TEDC1-3×Flag-T2A-GFP. This DMEM/F12 medium (Gibco) with FBS, glutamine, penicillin, and streptomycin construct was expressed from the Pgk promoter, and cells were analyzed 7–14 d additives. Serum starvation was done with medium with 0.5% FBS for NIH-3T3 after transduction. cells, 0.5% calf serum for Light-II NIH-3T3 cells, and 0.2% FBS for IMCD3 cells. IMCD3 FlpIn cells were provided by P. Jackson. NIH-3T3 cells were obtained Blasticidin reporter assays. 3T3-[Shh-BlastR;Cas9] cells were seeded for signaling from ATCC. HEK239T-EcR-ShhN cells were provided by P. Beachy. Cells were and grown to near confluence. Growth medium was replaced with serum- confrmed to be mycoplasma free with the MycoAlert system (Lonza). starvation medium with or without pathway agonist (ShhN conditioned medium or 250 nM SAG, synthesized as previously described83,84). After 24 h, cells were Method details. DNA cloning. Individual sgRNAs were cloned by ligating passaged at an ~1:6 dilution into medium with 10% FBS, and 5 h later were annealed oligonucleotides into pMCB306 or pMCB320 digested with BstXI and subjected to selection with blasticidin (blasticidin S hydrochloride, Sigma Aldrich) Bpu1102I (Fermentas FastDigest enzymes, Termo Fisher). Ligated products for 4 d. Relative viability was determined with the CellTiter-Blue assay (Promega) were transformed into Mach1-T1 competent cells (Termo Fisher), and recovered with a SpectraMax Paradigm (Molecular Devices) or Infinite M1000 (Tecan) plasmids were verifed by sequencing. plate reader. Cilia-focused sgRNA libraries were cloned from oligonucleotide pools (Agilent) as previously described25. Briefly, oligonucleotides were amplified with Genome-wide screening. Owing to the large number of cells required, we conducted primer sequences common to each sublibrary, digested with BstXI and Bpu1102I, the screen in four batches with subsets of the library containing ~45,000–70,000 25 ligated into pMCB320, and transformed into Endura competent cells (Lucigen). sgRNAs (Supplementary Fig. 2a). For each batch, lentivirus was produced and DNA was isolated with a Plasmid Plus Giga kit (Qiagen). titered as described above. 3T3-[Shh-BlastR;Cas9] cells were grown in 15-cm plates Individual cDNAs were amplified from mouse cDNA or commercially available and transduced at a multiplicity of infection of ~0.3 in sufficient numbers such that sources (Dharmacon) and cloned into Gateway Entry vectors via BP-clonase- there was a ~500:1 ratio of transduced cells to sgRNA library elements. Cells were mediated recombination (Thermo Fisher) or with isothermal assembly. Mutations selected with puromycin for 5 d, grown for 3 d without puromycin, and then plated to introduce resistance to sgRNA-directed cleavage were introduced by isothermal for signaling, and a ~1,000:1 ratio of cells to sgRNAs was maintained during these assembly. Plasmids for expression of tagged genes of interest were generated from and all subsequent steps. After cells reached confluence, signaling was initiated Entry vectors through LR-clonase-mediated recombination (Thermo Fisher) into by addition of serum-starvation medium containing ShhN. After 24 h, cells were Destination vectors encoding C-terminal LAP, 3×FLAG, or 6×Myc tags. passaged, allowed to adhere, and then subjected to blasticidin selection for 4 d at The plasmid pHR-Pgk-Cas9-BFP was cloned through digestion of pHR- 5 μg/ml, a concentration that we found sufficient to achieve strong enrichment/ SFFV-Cas9-BFP16 and replacement of the SFFV promoter with the Pgk promoter depletion of hits without causing sgRNA library bottlenecks due to excess cell amplified from pEFB/FRT-pCrys-APGpr161NG3-NsiI-pPgk-BirA-ER46. The plasmid death. After passaging cells to blasticidin-free medium, a ‘T1’ sample was harvested pGL-8×Gli-Bsd-T2A-GFP-Hyg was generated in the pGL4.29-[luc2P/CRE/Hygro] (1,000-fold more cells than sgRNAs), and the remaining cells were passaged once vector (Promega) through replacement of the CRE response element with 8×Gli more before seeding for a second round of signaling and selection. The final binding sites amplified from pGL3-8×Gli-Luc (P. Beachy) and of Luc2P with Bsd- ‘T2’ cell sample was collected after a 4-d blasticidin selection and one additional T2A-GFP amplified from pEF5B-FRT-DEST-LAP82. passage in the absence of blasticidin. Unselected control cells were also propagated through the entire experiment and harvested at equivalent time points. Virus production and cell transduction. VSVG-pseudotyped lentiviral particles Screens with the cilia/Hh pathway-focused library were conducted as above were produced by cotransfection of HEK293T cells with a lentiviral vector and except that a variant blasticidin reporter cell line was used, in which Cas9-BFP was appropriate packaging plasmids (pMD2.G, pRSV-Rev, and pMDLg/RRE for expressed with the shortened EF1α promoter. Because some Cas9-negative cells sgRNAs expressed in pMCB320 or pMCB306; pCMV-ΔR-8.91 and pCMV- accumulated during the experiment, the final blasticidin-selected and unselected VSVG for Pgk-Cas9-BFP). After transfection with polyethyleneimine (linear, cells were FACS-sorted for BFP expression. MW ~25,000, Polysciences), virus-containing supernatant was collected 24 h To process cell samples for sgRNA sequencing, genomic DNA was isolated later and filtered through a 0.45-μm cellulose acetate filter. For sgRNA libraries, a with QiaAmp DNA Blood Maxi or QiaAmp DNA mini kits (Qiagen). Genomic second harvest of viral medium was performed 24 h after the initial harvest. For DNA was then amplified with Herculase II polymerase (Agilent) as previously 16 Cas9-containing virus, lentiviral particles were concentrated 20-fold with Lenti-X described , first with outer primers to amplify the sgRNA cassette, then with inner Concentrator (Clontech). primers to amplify a portion of the initial PCR product while introducing sample- Cells were transduced by addition of viral supernatants diluted to an specific barcodes and adapters for Illumina sequencing (Supplementary Table 9). appropriate titer in growth medium containing 4 μg/ml polybrene (Sigma Aldrich). Gel-purified PCR products were quantified with a Qubit 2.0 fluorometer with the After a 24-h incubation at 37 °C, virus-containing medium was removed; after an dsDNA HS kit (Thermo Fisher) and pooled for sequencing. Deep sequencing was additional 24 h, cells were passaged and, when appropriate, selection for transduced performed on a NextSeq 500 sequencer with high-output v2 kits (Illumina) to cells was commenced by addition of 2.0 μg/ml puromycin (Invivogen). Multiplicity obtain an ~500-fold excess of reads to sgRNA library elements. Sequencing of infection was determined by flow cytometry. was performed with a custom primer to read the sgRNA protospacer (Supplementary Table 9). ShhN production and titering. ShhN-containing conditioned medium was produced in HEK239T-EcR-ShhN cells. Cells were grown to 80% confluence, Cas9-induced mutation analysis by sequencing. Genomic DNA from sgRNA- the medium was changed to DMEM with 2% FBS, and conditioned medium was transduced cell pools was extracted with a QIAamp DNA Mini kit (Qiagen) and collected after 48 h and filtered through a 0.22-μm filter (EMD Millipore). The amplified with primers flanking the sgRNA target site (Supplementary Table 1). titer of ShhN was determined with NIH-3T3 Light-II reporter cells (‘Luciferase Gel-purified PCR products were subjected to Sanger sequencing, and the reporter assays’ section), and a concentration approximately twofold greater than resulting chromatograms were analyzed with tracking of indels by sequence 34 the minimum dilution needed for full induction was used for further experiments decomposition (TIDE) . (typically 1:12.5). Luciferase reporter assays. Luciferase reporter assays were conducted with 3T3- Flow cytometry and fluorescence-activated cell sorting. Flow cytometry analyses [Shh-BlastR;Cas9] cells cotransfected with pGL3-8×Gli-Firefly-luciferase and were conducted with a FACSScan instrument (Becton Dickinson) outfitted with pGL3-SV40-Renilla-luciferase. One day after plating, cells were transfected with lasers provided by Cytek Biosciences. FACS was performed with FACSAria II cell Mirus TransIT-2020 (Mirus Bio) with luciferase plasmids and either control GFP- 85 sorters (Becton Dickinson). Flow cytometry and FACS data were analyzed with encoding plasmid (pEF5B-FRT-GFP-FKBP) or a plasmid encoding a gene of FlowJo (Treestar). interest. Nearly confluent cells were switched to serum-starvation medium with or without pathway agonist 24 h later and were allowed to signal for 24–30 h. Generation of stable cell lines. The 3T3-[Shh-BlastR;Cas9] reporter cell line was Alternatively, luciferase assays for titering ShhN-conditioned medium were generated by transfection of NIH-3T3 cells with pGL-8×Gli-Bsd-T2A-GFP- performed with the NIH-3T3 Light-II cell line, which has stably integrated versions Hyg, using Lipofectamine 2000 (Thermo Fisher). After selection for hygromycin- of GLI-driven firefly luciferase and constitutively expressed Renilla luciferase. After resistant cells, clonal isolates were obtained by limiting dilution and tested for signaling, cells were lysed in lysis buffer (12.5 mM Tris, pH 7.4, 4% glycerol, 0.5% SAG-induced blastidicin resistance. Pgk-Cas9-BFP was introduced lentivirally, Triton X-100, 0.5 mg/ml BSA, 1 mM EGTA, and 1 mM DTT) and a dual-luciferase and this was followed by three rounds of FACS sorting for high-level measurement was performed with a Modulus microplate luminometer BFP expression. (Turner Biosystems).

Immunofluorescence and localization studies. IMCD3 FlpIn or 3T3-[Shh- concentrator. Peptide pools were reconstituted and injected onto a C18 reversed- BlastR;Cas9] cells were plated on acid-washed 13-mm round #1.5 coverslips phase analytical column, ~20 cm in length, pulled and packed in house. The UPLC (additionally coated with poly-l-lysine for NIH-3T3 cells). After 24 h, cells were was a NanoAcquity or M-Class column (Waters), operated at 450 nl/min with transfected as needed with siRNAs (Supplementary Table 9) with Lipofectamine a linear gradient from 4% mobile phase B to 45% B. Mobile phase A consisted RNAiMAX (Thermo Fisher) or with plasmids with Fugene 6 (Promega). Where of 0.2% formic acid in water; mobile phase B consisted of 0.2% acetic acid in indicated, cells were serum starved for 24 h and treated with ShhN or 1 μM acetonitrile. The mass spectrometer was an Orbitrap Elite or Fusion (Thermo vismodegib (Chemietek) before fixation with 4% paraformaldehyde, ice-cold Fisher) set for data-dependent acquisition, selecting and fragmenting the 15 most methanol, or both in succession. For GLI2/GLI3/SMO trafficking assays, cells intense precursor ions in the ion trap, where the exclusion window was set at 45 s, were serum-starved for 20 h, then incubated 5–6 h in the presence or absence of and multiple charge states of the same ion were allowed. ShhN conditioned medium. For analysis of TEDC2-LAP localization, cells were preextracted before methanol fixation via a 1-min exposure to PHEM buffer Quantifcation and statistical analysis. Analysis of CRISPR-based screens. 26 (60 mM PIPES, 25 mM HEPES, 4 mM MgSO4, and 10 mM EGTA, pH 7.0) with CRISPR-based screens were analyzed as previously described , and data from 0.2% Triton X-100. each screen batch were processed separately. To determine the sgRNA counts Fixed coverslips were blocked with PBS with 3% BSA and 5% normal donkey in each sample, raw sequencing reads were trimmed to the 3′-most 17 nt of serum, permeabilized with PBS with 0.1% Triton X-100, and then incubated with each protospacer and aligned to expected sgRNA sequences. Tis alignment the appropriate primary antibodies (Supplementary Table 10) and secondary was carried out with the makeCounts script in the casTLE sofware package26, antibodies (Jackson ImmunoResearch). Coverslips were either stained with which uses Bowtie86 to perform alignment with zero mismatches tolerated. Te Hoechst DNA dye and mounted on slides with Fluoromount-G mounting medium analyzeCounts script (v0.7 and v1.0) of casTLE was then used to identify genes (Electron Microscopy Sciences) or directly mounted with ProLong Gold antifade exhibiting signifcant enrichment or depletion and to estimate the phenotypic reagent with DAPI (Life Technologies). efect size for each gene. Tis method uses an empirical Bayesian approach to Coverslips were imaged at 60× or 63× magnification with one of the following score genes according to the log-likelihood ratio that a gene’s observed change microscope systems: an Axio Imager.M1 (Carl Zeiss) equipped with SlideBook in sgRNA counts is drawn from a model of gene efect versus the distribution of software, an LED light source (Intelligent Imaging Innovations), and a Prime negative-control sgRNAs. An expected negative score distribution is obtained by 95b sCMOS camera (Photometrics); an Axio Imager.M1 (Carl Zeiss) equipped random permutation of gene-targeting sgRNA fold-change values and used to with SlideBook software, a Lambda XL light source (Sutter instruments), and determine a P value for each gene. Notably, the use of 100,000 permutations leads a CoolSNAP HQ2 CCD camera (Photometrics); an Axio Imager.M2 equipped to a minimum reported P value of 1 × 10–5 (200,000 permutations were used for with ZEN software, an X-Cite 120 LED light source (Excelitas), and an Axiocam comparative screening in Supplementary Fig. 3c, with minimum P value of 503 mono camera (Carl Zeiss); or a DeltaVision Elite imaging system equipped 5 × 10–6). For each gene, the casTLE algorithm also estimates the magnitude of the with SoftWoRx software, an LED light source, and an sCMOS camera (Applied phenotype resulting from complete gene inactivation. Tis value is output as the Precision). Z stacks were acquired at intervals of 250–500 nm and deconvolved as efect size and is accompanied by an estimated range of efect sizes compatible with needed with Slidebook 6.0 or SoftWoRx software. each gene’s sgRNA data. Genes targeted by our sgRNA library that lacked an NCBI identifier Cotransfection and coimmunoprecipitation. HEK293T cells were cotransfected with or that severely affected growth (casTLE effect size ≤–2.5 and casTLE P Tedc1, Tedc2 or TagRFP plasmids with Fugene 6, collected after 48 h, and lysed on value <0.005) were not considered for further analysis but are included in ice in Co-IP buffer (50 mM Tris, pH 7.4, 150 mM NaCl, 1% Triton X-100, 1 mM Supplementary Table 3. Negative and positive reference genes were defined DTT) supplemented with protease inhibitors. Lysates were centrifuged at 20,000 g for growth and signaling phenotypes with previously defined gene sets8, 27 for 20 min, and FLAG-tagged proteins were captured by incubation for 2 h with (Supplementary Table 3). Precision-recall and ROC curves were computed in anti-FLAG M2 antibody (Sigma Aldrich) and Protein G Sepharose 4 Fast Flow Matlab (Mathworks). Hit genes at 10% and 20% FDR cutoffs were defined with (GE Healthcare). After four washes of resin with Co-IP buffer, bound proteins were the precision-recall threshold values at precision of 0.9 and 0.8, thus yielding eluted by incubation at 95 °C in lithium dodecyl sulfate–based gel loading buffer. P-value cutoffs of 0.0163 and 0.0338, respectively. Ciliopathy-associated genes were defined from OMIM. Functional category enrichment analysis for 10% FDR Western blotting. Lysates from 3T3-[Shh-BlastR;Cas9] cells were prepared in SDS hits was performed with the DAVID website’s functional annotation chart tool sample buffer (50 mM Tris HCl, pH 6.8, 8% (vol/vol) glycerol, 2% (wt/vol) SDS, with all mouse genes as the background28. A second analysis was performed with 100 mM DTT, and 0.1 mg/ml bromophenol blue), boiled and sonicated. Samples human homologs of 10% FDR hits with all human genes as the background. The were loaded onto a 4–15% Criterion TGX Stainfree gel (Bio-Rad), run for 25 min significance of overlap between the top 15 genes associated with CHD reported at 300 V in Tris–glycine–SDS buffer (Bio-Rad), and transferred onto a PVDF by Sifrim et al.50 and P values from functional screening was assessed with the membrane with a Transblot Turbo system (Bio-Rad). Membranes were blocked in Kolmogorov–Smirnov test. 1:1 PBS/SeaBlock (Thermo Scientific) for 1 h at room temperature, then incubated with the indicated primary antibody (Supplementary Table 10) for 16 h at 4 °C. Quantification of Hh signaling assays. Blasticidin-based inhibition of cell growth After incubation with HRP-conjugated secondary antibody or HRP–Protein was determined by normalizing raw CellTiter-Blue fluorescence such that growth

A (Jackson ImmunoResearch), blots were developed with Supersignal West Femto in the absence of blasticidin corresponded to 100% growth. The IC50 for blasticidin Maximum Sensitivity Substrate (Thermo Fisher) and imaged on a ChemiDoc MP was determined with Prism 7.0 (GraphPad Software). (Bio-Rad). Membranes were stripped with Restore Western Blot stripping buffer Dual-luciferase data were analyzed by first subtracting background signal (Thermo-Fisher) and reprobed as described. such that cells without luciferase gave readings of zero. Firefly/Renilla (8×Gli/ For analysis of immunoprecipitations, western blotting was performed as constitutive) ratios were then calculated and normalized such that unstimulated described above, except samples were separated in 4–12% Bis-Tris PAGE gels control cells had a value equal to 1. (Invitrogen) with MOPS running buffer, transferred to PVDF membranes with a Criterion Blotter system (Bio-Rad), developed with ECL or ECL 2 Quantification of fluorescence microscopy images. Microscopy images were analyzed chemiluminescence detection kits (Pierce), and imaged on a Chemidoc Touch with Fiji ImageJ software (National Institutes of Health) and a custom Matlab system (Bio-Rad). (Mathworks) script. Local background subtraction was performed on all images before analysis. To determine ciliary frequency, cells were manually scored for Large-scale affinity purification and mass spectrometry. Affinity purifications were the presence or absence of a cilium with ARL13B and acetylated tubulin as ciliary conducted as previously described82. Briefly, an ~500–1,000 μl packed-cell volume markers. For analyses of ciliary length and intensity of ciliary markers, the ARL13B was lysed in LAP purification buffer containing 0.3% NP-40. Lysate was cleared and/or acetylated tubulin channels were used to create a ciliary mask. This mask sequentially at 16,000 g and 100,000 g before incubation with anti-GFP antibody was then used to determine cilium length and to measure ciliary signal in other coupled to Protein A resin. After protein capture and washes, bound LAP-tagged channels. The γ-tubulin or ninein signal (staining centrioles) was used to orient proteins were eluted by incubation with HRV3C protease. For mass spectrometry cilia from base to tip. Tip fluorescence for GLI2 and GLI3 was defined as the analysis ‘A’ (Supplementary Table 6), eluted proteins were further purified by summed fluorescence in the distal-most five pixels of each cilium. For ARMC9-3× capture on S-Protein agarose and eluted at 95 °C in lithium dodecyl sulfate–based FLAG localization, the ciliary fluorescence of each cilium was normalized to 1, and gel loading buffer. each axoneme was divided into 20 equal-distance bins. For protein analysis by mass spectrometry, gel slices containing affinity- Differences in cilium length distribution were tested for significance with the purified proteins were washed with 50 mM ammonium bicarbonate, then Kolmogorov–Smirnov test in Matlab. Line plots of fluorescence intensity along reduced with DTT (5 mM) and alkylated with propionamide (10 mM). Gel slices cilia were generated in ImageJ. were further washed with an acetonitrile-ammonium bicarbonate buffer until Centriole-count measurements were done manually with γ-tubulin and all stain was removed. 120 ng of trypsin/LysC (Promega) reconstituted in 0.1% centrin3 staining to guide centriole calling. Cell-cycle stage was determined on the ProteaseMAX (Promega) with 50 mM ammonium bicarbonate was added to basis of DNA morphology, and statistical significance was determined with two- each gel band; after 30 min, 20 μl of additional 50 mM ammonium bicarbonate in sided Fisher’s exact test calculated in Stata 14.2 (StataCorp). Cell counts for each of 0.1% ProteaseMAX was added. Digestion was then allowed to occur overnight at the five centriole-number categories were used for statistical comparisons 37 °C. Peptides were extracted from the gels in duplicate, then dried in a SpeedVac between genotypes.

Analysis of mass spectrometry data. MS/MS data were analyzed with both Preview and References Byonic v2.10.5 (ProteinMetrics). All data were first analyzed in Preview to provide 82. Liew, G. M. et al. Te intrafagellar transport protein IFT27 promotes recalibration criteria if necessary and were then reformatted to MGF format before full BBSome exit from cilia through the GTPase ARL6/BBS3. Dev. Cell 31, analysis with Byonic. Data were searched at 12-p.p.m. mass tolerances for precursors, 265–278 (2014). with 0.4-Da fragment mass tolerances assuming up to two missed cleavages and 83. Frank-Kamenetsky, M. et al. Small-molecule modulators of Hedgehog allowing for fully specific and ragged tryptic peptides. The database used was UniProt signaling: identifcation and characterization of Smoothened agonists and for Mus musculus, downloaded on 25 October 2016. These data were validated at a 1% 87 antagonists. J. Biol. 1, 10 (2002). FDR with typical reverse-decoy techniques . The resulting identified peptide spectral 84. Chen, J. K., Taipale, J., Young, K. E., Maiti, T. & Beachy, P. A. Small molecule matches and assigned proteins were then exported for further analysis with Matlab modulation of Smoothened activity. Proc. Natl. Acad. Sci. USA 99, (MathWorks) to provide visualization and statistical characterization. 14071–14076 (2002). 85. Breslow, D. K., Koslover, E. F., Seydel, F., Spakowitz, A. J. & Nachury, M. V. Analysis of CRISPR growth-screen datasets. Gene-level growth phenotype An in vitro assay for entry into cilia reveals unique properties of the soluble data74 were downloaded from the Achilles website. Hierarchical clustering with difusion barrier. J. Cell Biol. 203, 129–147 (2013). uncentered correlation and average linkage settings was performed with Cluster 3.0 86. Langmead, B., Trapnell, C., Pop, M. & Salzberg, S. L. Ultrafast and software88, and clustered data were visualized in Java Treeview89. memory-efcient alignment of short DNA sequences to the human genome. Genome Biol. 10, R25 (2009). Phylogenetic analysis. Homologs for Tubd1 and Tube1 were either previously described90 or identified with protein BLAST. Homologs for Tedc1 and Tedc2 87. Elias, J. E. & Gygi, S. P. Target-decoy search strategy for increased confdence were identified with iterative searches with PSI-BLAST91. To analyze sequence in large-scale protein identifcations by mass spectrometry. Nat. Methods 4, divergence, homolog sequences were first aligned with Clustal Omega92. 207–214 (2007). Phylogenetic trees were generated via neighbor joining with distance correction 88. de Hoon, M. J., Imoto, S., Nolan, J. & Miyano, S. Open source clustering with Simple Phylogeny92 and visualized with Unrooted93. sofware. Bioinformatics 20, 1453–1454 (2004). 89. Saldanha, A. J. Java Treeview: extensible visualization of microarray data. Code availability. Software used for casTLE analysis can be found at Bioinformatics 20, 3246–3248 (2004). http://bitbucket.org/dmorgens/castle/. Matlab scripts for quantification of cilium 90. Turk, E. et al. Zeta-tubulin is a member of a conserved tubulin module and is intensities and length are available upon request. a component of the centriolar basal foot in multiciliated cells. Curr. Biol. 25, 2177–2183 (2015). Life Sciences Reporting Summary. Further information on experimental design is 91. Altschul, S. F. et al. Gapped BLAST and PSI-BLAST: a new generation of available in the Life Sciences Reporting Summary. protein database search programs. Nucleic Acids Res. 25, 3389–3402 (1997). Data availability. The data supporting the findings of this study are available 92. Li, W. et al. Te EMBL-EBI bioinformatics web and programmatic tools within the paper and its Supplementary Information files, with the exception of framework. Nucleic Acids Res. 43, W580–W584 (2015). raw Illumina sequencing data and sequencing-based analysis of CRISPR-induced 93. Perrière, G. & Gouy, M. WWW-query: an on-line retrieval system for mutations, which are available upon request. biological sequence banks. Biochimie 78, 364–369 (1996).

David K. Breslow, James K. Chen, Corresponding author(s): Maxence V. Nachury Initial submission Revised version Final submission Life Sciences Reporting Summary Nature Research wishes to improve the reproducibility of the work that we publish. This form is intended for publication with all accepted life science papers and provides structure for consistency and transparency in reporting. Every life science submission will use this form; some list items might not apply to an individual manuscript, but all fields must be completed for clarity. For further information on the points included in this form, see Reporting Life Sciences Research. For further information on Nature Research policies, including our data availability policy, see Authors & Referees and the Editorial Policy Checklist.

` Experimental design 1. Sample size Describe how sample size was determined. The main sample size consideration was the number of cells used for our pooled screen. This was determined based on the level of variation and statistical power seen in other pooled screens. The 1000-fold excess of cells to library sgRNAs led to strong statistical significance for hit genes and matches or exceeds that in many other pooled screens. 2. Data exclusions Describe any data exclusions. A subset of genes were excluded from part of our analyses because they likely represent mis-annotated genes (no NCBI identifier found) or because strong deleterious effects on growth precluded robust measurement of signaling phenotypes. This issue is explained further in the Methods; the full data are also included in Supp. Table 3. 3. Replication Describe whether the experimental findings were No attempts at replication failed. All replication experiments confirmed initial reliably reproduced. findings. 4. Randomization Describe how samples/organisms/participants were Randomization was not performed because it was not relevant to our experimental allocated into experimental groups. design. Statistical significance of screen results was determined by scoring 10- sgRNA artificial genes created by randomization of our data. 5. Blinding Describe whether the investigators were blinded to Blinding was not practical or relevant to our study. The pooled screen is effectively group allocation during data collection and/or analysis. blinded; follow-up experiments led to sufficiently strong and consistent results that blinding was effectively precluded. Note: all studies involving animals and/or human research participants must disclose whether blinding and randomization were used. June 2017

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The exact sample size (n) for each experimental group/condition, given as a discrete number and unit of measurement (animals, litters, cultures, etc.) A description of how samples were collected, noting whether measurements were taken from distinct samples or whether the same sample was measured repeatedly A statement indicating how many times each experiment was replicated The statistical test(s) used and whether they are one- or two-sided (note: only common tests should be described solely by name; more complex techniques should be described in the Methods section) A description of any assumptions or corrections, such as an adjustment for multiple comparisons The test results (e.g. P values) given as exact values whenever possible and with confidence intervals noted A clear description of statistics including central tendency (e.g. median, mean) and variation (e.g. standard deviation, interquartile range) Clearly defined error bars

See the web collection on statistics for biologists for further resources and guidance.

` Software Policy information about availability of computer code 7. Software Describe the software used to analyze the data in this Software used for analysis of screen sequencing data includes Bowtie (ref. 87) and study. the casTLE algorithm (https://bitbucket.org/dmorgens/castle, also ref. 26). Custom Matlab scripts for cilia image analysis are available upon request.

For manuscripts utilizing custom algorithms or software that are central to the paper but not yet described in the published literature, software must be made available to editors and reviewers upon request. We strongly encourage code deposition in a community repository (e.g. GitHub). Nature Methods guidance for providing algorithms and software for publication provides further information on this topic.

` Materials and reagents Policy information about availability of materials 8. Materials availability Indicate whether there are restrictions on availability of There are no restrictions on availability of materials. unique materials or if these materials are only available for distribution by a for-profit company. 9. Antibodies Describe the antibodies used and how they were validated Antibody sources are in Supplementary Table 10. FAM92A Ab was validated in for use in the system under study (i.e. assay and species). Supplementary Fig. 4d. SUFU, GLI3, GLI1, and IFT88 antibodies were validated using WB analysis of KO cells (Supp. Fig. 1 and data not shown). Antibodies to TUBD1 and TUBE1 were validated by the Human Protein Atlas using Western blotting and protein arrays, and we detect a band of expected MW specifically in samples confirmed to contain the antigen by mass spectrometry. IQCE and EVC specificity were validated by RNAi in Fig. 4h and in refs. 39-40. CBY1 8-2 antibody was validated in PMID 21529289 and 25103236. SMO Ab was validated for immunofluorescence in PMID 21552265. GLI2 Ab was validated in KO cells in PMID 26193634. All other antibodies are extensively used in the field and have been used in dozens or more publications. June 2017

2 10. Eukaryotic cell lines nature research | life sciences reporting summary a. State the source of each eukaryotic cell line used. All cell lines are described in the Methods. All were obtained form ATCC, except for IMCD3 FlpIn cells, provided by Peter Jackson (originally obtained form Invitrogen), HEKT293-EcR-ShhN cells from Philip Beachy, LightII NIH-3T3 cells generated by the Chen lab, and NIH-3T3 FlpIn cells provided by Rajat Rohatgi.

b. Describe the method of cell line authentication used. None of the cell lines used have been authenticated. Nearly all cell lines used were murine in origin and few tests are available for authentication of mouse cell lines.

c. Report whether the cell lines were tested for All cell lines were confirmed negative for mycoplasma. mycoplasma contamination.

d. If any of the cell lines used are listed in the database None of the cell lines used are commonly misidentified. of commonly misidentified cell lines maintained by ICLAC, provide a scientific rationale for their use.

` Animals and human research participants Policy information about studies involving animals; when reporting animal research, follow the ARRIVE guidelines 11. Description of research animals Provide details on animals and/or animal-derived N/A materials used in the study.

Policy information about studies involving human research participants 12. Description of human research participants Describe the covariate-relevant population N/A characteristics of the human research participants. June 2017

3 June 2017 nature research | flow cytometry reporting summary 1 Final submission Revised version David K. Breslow, James K. Chen, James K. K. Breslow, David V. Nachury Maxence Initial submission Corresponding author(s): Corresponding The only gating performed was using FSC/SSC data to select live single cells The only gating performed was using FSC/SSC Adherent cultured cell lines were analyzed following trypsinization and Adherent cultured cell lines were analyzed Flowjo (Treestar) was used for data collection and analysis. Flowjo (Treestar) was used for data collection No sorting data is included. resuspension in PBS. cytometry data. (for Fig. 1e). A figure depicting this standard gating is not included but will (for Fig. 1e). A figure depicting this standard be provided if needed.

identical markers).

populations within post-sort fractions. the flow cytometry data. Methodological details Data presentation 4. A numerical value for number of cells or percentage (with statistics) is provided. for number of cells or percentage (with 4. A numerical value 2. The axis scales are clearly visible. Include numbers along axes only for bottom left plot of group (a 'group' is an analysis of (a 'group' is an analysis axes only for bottom left plot of group clearly visible. Include numbers along 2. The axis scales are plots. plots with outliers or pseudocolor 3. All plots are contour 1. The axis labels state the marker and fluorochrome used (e.g. CD4-FITC). the marker and fluorochrome used 1. The axis labels state Tick this box to confirm that a figure exemplifying the gating strategy is provided in the Supplementary Information. Tick this box to confirm that a figure exemplifying

9. Describe the gating strategy used. 8. Describe the abundance of the relevant cell 8. Describe the abundance of the relevant

7. Describe the software used to collect and analyze 7. Describe the software used to collect 6. Identify the instrument used for data collection.6. Identify the instrument used for data was used for collection of collection of flow A FACScan cytometer

5. Describe the sample preparation. For all flow cytometry data, confirm that: For all flow cytometry

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Form fields will expand as needed. Please do not leave fields blank. Please do not will expand as needed. Form fields Flow Cytometry Reporting Summary Reporting Cytometry Flow