Functional Genomic Screen of Human Stem Cell Differentiation Reveals Pathways Involved in Neurodevelopment and Neurodegeneration

Functional genomic screen of human stem cell differentiation reveals pathways involved in neurodevelopment and neurodegeneration

Ying Zhanga,b, Vincent P. Schulzc, Brian D. Reeda, Zheng Wanga, Xinghua Pana,b, Jessica Marianib,d, Ghia Euskirchene, Michael P. Snydere, Flora M. Vaccarinob,d,f, Natalia Ivanovaa, Sherman M. Weissmana,b,1, and Anna M. Szekelya,b,g,1

bProgram in Neurodevelopment and Regeneration, dChild Study Center, and Departments of aGenetics, cPediatrics, fNeurobiology, and gNeurology, Yale University School of Medicine, New Haven, CT 06520; and eDepartment of Genetics, Stanford University, Stanford, CA 94305

Contributed by Sherman M. Weissman, May 24, 2013 (sent for review September 21, 2012)

Human embryonic stem cells (hESCs) can be induced and differ- advantage of dropout screens to decipher genes and pathways entiated to form a relatively homogeneous population of neuronal based on a more complex phenotype has not been exploited. We precursors in vitro. We have used this system to screen for genes and others have begun using next-generation sequencing for necessary for neural lineage development by using a pooled hu- quantitating shRNAs present in a cell population for dropout man short hairpin RNA (shRNA) library screen and massively shRNA screens (3, 11). Sequencing has a very wide dynamic range parallel sequencing. We confirmed known genes and identified for detecting shRNAs, and allows for the discovery of mutant several unpredicted genes with interrelated functions that were shRNAs that might confound analyses. ShRNA libraries should specifically required for the formation or survival of neuronal pro- also avoid off-target effects as well as ineffective shRNAs (12). genitor cells without interfering with the self-renewal capacity of Each individual shRNA should be infected into a minimum of > undifferentiated hESCs. Among these are several genes that have 300 cells so that the recovery of each shRNA will not be dis- been implicated in various neurodevelopmental disorders (i.e., brain torted because of the variation in the number of infected cells. fi malformations, mental retardation, and autism). Unexpectedly, a set We have developed an ef cient phenotype-based strategy using pooled shRNA libraries and massively parallel sequencing to GENETICS of genes mutated in late-onset neurodegenerative disorders and fi with roles in the formation of RNA granules were also found to identify genes that play a speci c role in the neural lineage de- interfere with neuronal progenitor cell formation, suggesting their velopment of hESCs. We demonstrate here the practicality of this screening approach and describe the unexpected finding that functional relevance in early neurogenesis. This study advances fi the feasibility and utility of using pooled shRNA libraries in com- several genes speci cally required for neural commitment and neural progenitor maintenance encode proteins that are associ- bination with next-generation sequencing for a high-throughput, ated with various forms of RNA granules and are implicated in unbiased functional genomic screen. Our approach can also be used distinct neurological disorders, including diseases presenting with with patient-specific human-induced pluripotent stem cell-derived late-onset neurodegeneration. neural models to obtain unparalleled insights into developmental and degenerative processes in neurological or neuropsychiatric Results disorders with monogenic or complex inheritance. Pooled Human shRNA Library Screen to Identify Genes of Neural Lineage Commitment in hESCs. We established and modified pro- pooled RNAi screening | high-throughput sequencing | cedures for high-throughput studies to expand hESCs and induce neural differentiation | RNA-binding proteins | a nearly uniform differentiation of these cells into NESTIN, Mendelian disorders of the nervous system SOX2, PAX6, and polysialylated neural cell adhesion molecule (PSA-NCAM)-positive neural precursors (NPCs) using the bone ur general aim is to identify genes and pathways of early morphogenic protein antagonist, noggin, and fibroblast growth Oneural differentiation that are relevant for the development factor 2 (FGF2) (1, 13). We used a commercial, pooled whole- and function of the human nervous system. In vitro differentia- genome lentiviral shRNA library developed by the Broad Insti- tion of human embryonic stem cells (hESCs) yielding develop- tute [The RNA1 Consortium (TRC)/Mission LentiPlex; Sigma] mentally competent neuronal progenitors is an attractive model to search for genes that promoted or limited neural commitment for these studies and several approaches for this have been de- and differentiation of hESCs (Fig. 1A). The full genome library veloped, including those by our group (1). is divided into 10 pools; we chose one pool containing 8,488 Large-scale loss-of-function analysis by RNA interference individual shRNAs targeting 1,801 genes (an average of four to (RNAi) using small hairpin (shRNA) or small interfering RNA five shRNAs per gene). The shRNA gene targets in this pool (siRNA) -mediated knockdown of genes is a powerful screening were diverse but enriched for transcription factors [P < 0.00001 – approach in mammalian cells (2 7). ShRNAs provide the oppor- by Gene Ontology (GO) categories]. The titration of the pLKO.1 tunity for long-term silencing by stable infection of cells main- shRNA virus infection was based on development of puromycin- tained under selection pressure. Furthermore, pooled libraries of resistant colonies. shRNAs can be efficiently used instead of arrayed individual clones. Screening experiments can be designed for detection of shRNAs that produce a desired effect in a cell (positive screens) Author contributions: N.I., S.M.W., and A.M.S. designed research; Y.Z., Z.W., J.M., G.E., or for the depletion of shRNA species that silence a necessary and A.M.S. performed research; X.P., M.P.S., and F.M.V. contributed new reagents/ana- gene (dropout screens). The abundance of shRNAs has been lytic tools; Y.Z., V.P.S., B.D.R., S.M.W., and A.M.S. analyzed data; and S.M.W. and A.M.S. measured by using barcodes and array hybridization (8, 9), but wrote the paper. this procedure is subject to cross-hybridization and nonlinear The authors declare no conflict of interest. responses. Most positive screens have been limited to studies of In the manuscript we indicate human genes by standard abbreviations listed by RefSeq cellular proliferation or survival because it is easier to analyze and NCBI/Gene. the recovered enriched shRNAs (10). For dropout screens it is 1To whom correspondence may be addressed. E-mail: [email protected] or sherman. critical to accurately measure the abundance of shRNAs that are [email protected]. retained in cells at the end of the experiment to determine which This article contains supporting information online at www.pnas.org/lookup/suppl/doi:10. shRNAs were depleted (8). In part because of this challenge, the 1073/pnas.1309725110/-/DCSupplemental.

www.pnas.org/cgi/doi/10.1073/pnas.1309725110 PNAS Early Edition | 1of6 Downloaded by guest on September 29, 2021 was performed (T1 through T5) (Fig. 1B). The shRNA-encoding inserts from each of the cell populations were recovered by a single-step PCR using sufﬁcient gDNA to faithfully represent the entire library pool (Fig. S1C). The PCR products were sub- jected to deep sequencing, yielding a minimum of 10 million postﬁlter reads per sample (Table S1) to quantify the frequencies of the various shRNA species.

Gene Target Identification. We developed a bioinformatics pipe- line for annotation and quantification of the sequence reads. Correct sequence initiation was higher than 99% and the number of the reads mapped to the library’s sequence database was higher than 96%. A small fraction of the shRNAs (1.7% of the genes in the pool) was not used because of difficulties with gene annotation using the National Center for Biotechnology Infor- mation Reference Sequence Database (release 56). At 48 h after infection (T0), more than 94.5% of initial shRNAs were detected. The absence of certain shRNAs could be because of defectiveness of the original viral library or early cellular toxicity of these shRNAs. The distribution of reads per shRNA followed an approximately Gaussian curve. Similar pat- terns were seen from pooled shRNA-infected PSA-NCAM–sorted cells and from undifferentiated cells grown for 4 wk (Fig. S1D). Approximately 15% of the shRNAs dropped out in the undifferentiated arm at 4 wk (T5), representing shRNAs that were either toxic or targeted genes that were needed for pluripotency and caused differentiation (into any lineage), preventing expansion of undifferentiated cells. Nonsilencing shRNA sequences seeded into the initial library pool were recovered at a similar abundance Fig. 1. Pooled shRNA library screen coupled with deep-sequencing to study in each group. These results indicate the effectiveness of the pro- genes involved in neural differentiation of hESCs. (A) In vitro screening tocol for infecting hESCs and for recovery of shRNA inserts. strategy. (B) Experimental schedule. (C) Distribution of normalized reads of The representation of all shRNAs was quantified as the ratio of shRNAs in PSA-NCAM–negative and PSA-NCAM–positive hESC-derived cells the number of reads for that shRNA to the total number of mapped after neural differentiation. Scatterplot of normalized reads per shRNA reads from that condition and this ratio was then log-transformed. between the two phenotypic populations is shown. The bold diagonal line Reads <100 were considered as background. A scatterplot of represents a ratio of 1 for the amount of shRNA from each of the two normalized reads per shRNA between PSA-NCAM–negative samples; the dotted lines show the cutoff of 1.7-fold changes on a log scale. and PSA-NCAM strong-positive cells after neural differentiation Representative genes whose corresponding shRNAs (at minimum two of showed that shRNAs targeting known genes essential for neural the four to five shRNAs per gene) were either Depleted (black circles) or fi Enriched (black triangles) in the PSA-NCAM strongly positive group vs. PSA- stem/progenitor cell maintenance and self-renewal, exempli ed by NCAM–negative cells, or fully absent in all PSA-NCAM sorted groups (black BMI1, are depleted in the PSA-NCAM strong-positive compared with the PSA-NCAM–negative group (Fig. 1C). Among the tar- diamonds) are shown. Nontargeting control shRNA (star) is also indicated. fi The x and y axes indicate log2 reads per million total reads. gets of signi cantly depleted shRNAs were a group of genes encoding components of RNA granules [TAR DNA binding protein (TARDBP), polyglutamine binding protein (PQBP1), A single-cell suspension of 1 × 108 undifferentiated H1 hESCs and TIA1 cytotoxic granule-associated RNA binding protein-like was infected with the library at a multiplicity of infection of 0.3 1 (TIAL1), see below] (16, 17). ASCL1 (MASH1), a transcription to obtain more than 300 single-copy infection events per shRNA. factor with critical roles in neuronal commitment and in fibroblast- A portion of the culture (5× 107 cells) was harvested 2 d after the neuron in vitro transdifferentiation was essential for hESC-derived infection (time 0, T0) and the remaining cells were propagated neural lineage development (18). Enrichment of shRNAs during for an additional 3 d under puromycin selection, then separated NPC generation is illustrated by shRNAs silencing ING5, a tumor into two large pools representing separate arms of the screen suppressor protein that inhibits growth of various cell types (19). (Fig. 1B). In one arm the infected cells were maintained as undifferentiated hESCs for an additional 4 wk and in the other arm Gene Target Classification. Gene hits were scored by criteria sim- the cells were induced to differentiate into NPCs by exposure to ilar to those used in other recent work (3, 20), according to noggin for 14 d, followed by plating the cells onto a polyornithine/ whether there was a progressive change of 1.7-fold of normalized fibronectin matrix, then culturing for an additional 2 wk with shRNA read abundance for at least two shRNAs targeting the a low concentration of FGF2. The cells were under puromycin given gene, with no shRNA showing a contradictory change, or selection throughout (Fig. 1B). At the end of neural differentia- whether shRNAs disappeared entirely from all cell phenotypes tion the NPC population was separated from undifferentiated after differentiation (Table S2). The 1.7-fold on the log2 plot cells (or cells acquiring nonneural fate) by preparative FACS represents almost two SDs, so that a point above 1.7-fold the using the cell-surface marker PSA-NCAM (14, 15). A mono- mean value has less than between a 5% and 6% chance of being clonal antibody against the two to eight linked neuraminic acid a result of chance. Based on this analysis the percentages of polymer (PSA) moiety specifically labels a spectrum of neural targeted genes with respect to all genes of the pooled library cells, making it possible to identify genes necessary for early were compared (Fig. 2A). ShRNAs targeting 4.2% of all genes neural differentiation. Based on the PSA-NCAM expression, the displayed a gradual depletion when PSA-NCAM strong-positive differentiated cells were binned into three groups: PSA-NCAM cells were compared with the PSA-NCAM–negative population absent, weak-positive, and strong-positive (Fig. S1 A and B). We (Depleted), but 7.4% of the gene targets were enriched in PSA- focused on the PSA-NCAM–negative and strong-positive groups. NCAM strong-positive cells (Enriched). Depleted hits may rep- The sorted cells (ranging from 4.6 × 105 to 4.9 × 106 cells for resent genes that normally function in hESC neural lineage fate each group) were collected and genomic DNA was prepared. In commitment, NPC maintenance, and differentiation, but could the undifferentiated arm of the screen a time-course experiment also include genes involved in cellular proliferation and survival.

2of6 | www.pnas.org/cgi/doi/10.1073/pnas.1309725110 Zhang et al. Downloaded by guest on September 29, 2021 Enrichment of NPCs may imply that the targeted gene nor- genes with known/presumed neural system-related functions may mally delays NPC generation or promotes early exit and terminal functionally interact or converge within the same cellular pathway neuronal differentiation, but may also include effects, such as de- in a significant manner (Fig. S2). pletion of essential genes for endoderm or mesoderm lineage The 74 genes whose shRNAs were depleted from the PSA- specification, leading to default neural differentiation. ShRNAs NCAM strong-positive cells compared with shRNA abundances in for nearly 20% of the genes were fully eliminated in both PSA- the PSA-NCAM–negative population (Depleted) (Figs. 1C and 2), NCAM–negative and weak or strong-positive cells (Absent), might be needed specifically for differentiation of neural precursor implying that these genes had essential roles in early neural cells but are less critical for general cellular growth. shRNAs for lineage specification, NPC survival, or general cellular survival. 60 of these genes were not significantly depleted in the undif- The quantitative analysis of shRNA reads used both individual ferentiated arm over 5 wk of cell growth (Table 1, Depleted, and data review and a statistical method (RIGER) designed for the Fig. S3). GO classification of the 74 gene targets showed significant TRC shRNA library (21, 22). We used the Second Best Rank enrichment for transcriptional repressors and for products associ- feature of RIGER, which requires that two different shRNAs ated with intracellular membrane-free organelles (Table 2). result in the same effect. The RIGER analysis displayed a good Among these targets were a number of genes with established concordance with the shRNA target hits obtained by our selec- roles in neural stem/progenitor cell self-renewal, neural fate de- tion strategy (Fig. 2B). Among the 74 gene hits reported by our termination, and neurogenesis (for example BMI1, NEUROD1, criteria to result in depletion in PSA-NCAM–positive cells, 42 MBD1, REST, HELT). Several of the 74 genes are implicated in were among the top 75 genes and all of the 74 genes were within disorders of the human nervous system, including childhood neu- the top 9% of genes categorized by RIGER analysis (Fig. 2B, rodevelopmental disorders, such as Autism spectrum disorders Upper). The RIGER ranking and our selection strategy also agreed (ASD), syndromic and nonsyndromic mental retardation (MR), and for genes whose shRNA was enriched in the PSA-NCAM–positive late-onset neurodegenerative processes, including frontotemporal cells (Fig. 2B, Lower). lobar degeneration (FTLD), amyotrophic lateral sclerosis (ALS), The undifferentiated arm of the screen confirmed if the gene and Huntington and Parkinson diseases (Table S4). Several genes hits detected were specific to neuronal differentiation. We com- within this group, including TARDBP, TIAL1, SIRT1, and PQBP1, pared the changes in shRNA representation during neural dif- which have recently been implicated in neurodegenerative diseases ferentiation with the abundance of those shRNAs in the un- (ALS/FTLD spectrum, SMA, Lewy Body Dementia, Parkinson differentiated cells and categorized each gene target by the disease, MR, respectively), are involved in mRNA trafficking,

described preset criteria (Table S2). We used the Fisher two- stability, and microRNA biogenesis, associated with various types GENETICS tailed exact test (23) to calculate the likelihood that the results of RNA granules or involved in protein misfolding (25, 26). Si- of measurements in these two conditions could have arisen by lencing of additional genes within these pathways (e.g., G3BP1, chance from two samples taken from the same pool. Gene targets TAF15, and SNRPB2) in our shRNA screen displayed different whose shRNA’s abundance changed significantly during neural PSA-NCAM phenotypes (Table S5), in line with the interaction differentiation were more likely unchanged in the pluripotent arm and differential regulation of RNA granule components (27). of the screen (Table 1). That is, the neural differentiation-specific The 354 genes whose shRNA disappeared entirely during neu- genes were significantly more prevalent (P < 0.0001) in the De- ral differentiation (Absent group) included target genes with pleted, Absent, and Enriched gene-target categories than in the fundamental general cellular functions. A significant decrease or Unchanged group. loss of their shRNAs was also seen in the undifferentiated hES cells (e.g., BUD31, POLR21, RAD52, PTTG1, among others). Target Genes Are Enriched for Components of RNA Granules and Ner- More than 100 of the 354 genes, many of them multifunctional vous System-Related Genes. We performed a systematic, manual transcriptional regulators, have key functions in the developing curation of the literature for genes to identify those related to or mature nervous system. About half of those genes showed nervous system functions, including neurogenesis, neural de- specificity for the neural differentiation arm of the screen, as the velopment, brain-specific functions, and nervous-system disorders. same shRNAs failed to interfere with the growth of undiffer- Therewasasignificant enhancement for nervous system-related entiated hESCs (Table S6). This group included not only targets genes in each category of genes whose shRNAs displayed changes where gene silencing might lead to loss of early neural fate (i.e., Depleted, Absent, or Enriched) (Table S3). Protein:protein commitment (e.g., HESX1, NEUROG3, SMAD6, EOMES), but interaction analysis by DAPPLE (Disease Association Protein- also genes involved in terminal neuronal specification or function Protein Link Evaluator) (24) of all genes that displayed gradual (e.g., FOXP1, ETV1, AKAP1 or ERCC6). Overall, these findings shRNA depletion during neuronal differentiation revealed that strongly support the biological validity of the screening approach.

Fig. 2. Quantitative analysis of the shRNA library screen following neural differentiation of hESCs. (A) Pie chart summary of the shRNA-targeted gene hits after neural differentiation of hESCs according to our selection strategy (Table S2). Unchanged category: all gene targets whose shRNAs abundances were not changed when comparing PSA-NCAM– negative and strong-positive cell fractions or whose pattern of change was ambiguous. Absent: gene targets whose shRNAs were absent in all PSA-NCAM sorted cell populations at the end of neural differentiation. Enriched and Depleted: genes whose shRNAs were enriched or depleted, respectively, in PSA-NCAM strong-positive cells vs. PSA-NCAM– negative cells at the end of neural differentiation. (B) Concordance of the manual classification and the RIGER ranking of gene targets. RIGER analysis of shRNA abundances recovered from PSA-NCAM strong- positive vs. negative cell populations after neural differentiation was performed. The figure shows overrepresentation of Depleted (Upper) and Enriched group (Lower) of genes selected by manual classification at the two extremes of the RIGER-ranked list of genes displayed in a 200-gene sliding window. The dotted line indicates the total overlap, expected by chance, between the genes we scored as depleted or enriched in the PSA-NCAM–positive cells and the entire set of ranked genes in the RIGER dataset. The x axis is the ranking order of genes by RIGER. The y axis is the fraction of genes.

Zhang et al. PNAS Early Edition | 3of6 Downloaded by guest on September 29, 2021 Table 1. Comparison of the relative abundance of neural compared with nonsilencing controls. This process validated differentiation-specific gene targets the PSA-NCAM–based phenotypic selection of the screen. Most of the shRNA-transduced cells had slower growth rates Gene hit categories Gene hit when we began NPC differentiation and this became more category Unchanged Absent Enriched pronounced when we transferred the cells into polyornithine/ fibronectin-coated surface, as illustrated with one of the shRNA’s Unchanged ———targeting TARDBP (Fig. 3C). When the infected cells were prop- Absent <0.0001 ——agated in pluripotent conditions, they grew comparably to the Enriched < 0.0001 < 0.0001 — nonsilencing control shRNA infection, except that one of the two Depleted < 0.0001 < 0.0001 0.854 LMO3 shRNAs caused rapid cell death in both undifferentiated and differentiated cells. Immunostaining experiments using the fi Gene hit categories were de ned as in Fig.2A, based on the quantitative more general neuronal stem/progenitor markers NESTIN and shRNA read analyses of PSA-NCAM–sorted cell phenotypes after neuronal fi SOX1 showed that cells differentiated into NPCs from hESCs as differentiation (Table S2 and SI Methods). Neural differentiation-speci c completely as the untreated culture (Fig. 3E) (control shRNA) genes were defined by the ratio of shRNA abundance in the PSA-NCAM– (1, 13). Furthermore, in most cases after targeting shRNAs the positive versus -negative cells at the end of neural differentiation (neural fi differentiation arm) with the requirement that their respective shRNA abun- cells preserved their de ning markers, NESTIN and SOX1, even dances did not change in cells infected by the same shRNA library pool and though the PSA-NCAM expression was decreased in these un- maintained in pluripotent culture conditions for the same duration (parallel sorted cultures (see Fig. 3 D and E for a representative example undifferentiated arm) (Fig. 1B). The relative proportion of these neural dif- of the TARDBP knockdown phenotype). For several of the ferentiation-specific gene targets was then compared between the different shRNAs, impaired proliferative capacity and survival might ex- phenotypic categories (as defined at the end of neural differentiation) by using plain the depletion of cells harboring the given shRNA. In one the Fisher two-tailed exact test for 2 × 2 contingency tables. The P values shown case, the infected cells failed to fully express all classic NPC in boldface indicate significant differences and show an enrichment of neural markers, suggesting the alternative of a perturbed fate specifi- differentiation specific genes in hits categories defined by changes in shRNA cation. To rule out cell-line specificity, similar experiments were abundance during neural differentiation. performed in a second hESC line, H9, and the results agreed with the H1 experiments (Fig. S4).

Screen Validation by Individual Gene Silencing. Intrigued by the Enrichment of Hits for Genes Implicated in Autism and Intellectual enrichment of target genes encoding components of RNA Disability. Among the unexpected findings of our unbiased shRNA granules and implicated in neurodegenerative disorders, we se- screen was an enrichment of gene hits the encoded proteins of lected a set of gene hits for further study from the Depleted which are integral parts of RNA granules, hence implicated in and Absent categories, including TARDBP, PQBP1, TIAL1, and normal neural commitment and neuronal progenitor differen- genes with proposed neuronal stem/progenitor cell functions, tiation of hESCs. Mutations of several of these and other genes such as BMI1, CCR4-NOT transcription complex, subunit 4 that emerged from the screen are associated with neurode- (CNOT4), and LIM domain only 3 (LMO3). Individual viral velomental and neurodegenerative disorders affecting higher shRNAs (two to three per gene) in the same vector backbone cortical functions. To evaluate if additional genes involved in were used. We followed the procedure for pooled shRNA library neurodevelopmental disorders were uncovered by this func- screening with cells cultured in two different conditions (plu- tional screen, we took advantage of independent, large scale, ripotent ES propagation vs. NPC differentiation). We monitored and reproduced genomic studies [genetic association, copy both the morphological features of the cells and the silencing of number variation (CNV) analysis, and whole exome sequencing] the respective genes by quantitative RT-PCR (qRT-PCR) along of human genotypes to decipher the genetic architecture of ASD with analysis of PSA-NCAM expression by immunofluorescence and nonsyndromic MR (SI Methods). The derived candidate gene and NCAM1 mRNA expression. Furthermore, we analyzed the set (representing de novo and recurrent single mutations and development of additional typical markers of neuronal progen- CNVs) was cross-referenced with the entire gene list targeted by itors, such as NESTIN and SOX1, by immunostaining. The ef- the viral pool and with the gene targets identified and classified ficiency of knockdown by the individual shRNAs is shown in Fig. in the neural differentiation arm of the screen (Fig. 2A). There 3A. Among 13 individual shRNAs tested, 10 showed substantial was an enrichment of ASD and nonsyndromic MR/intellectual knockdown (40–95%) both in cells grown as pluripotent hESCs disability gene targets among those genes whose shRNA abun- and in differentiated NPCs, and one shRNA showed knockdown dances were significantly changed during neural differentiation only in hESCs but not in the corresponding NPC. Because the (Table 3 and Table S7). This finding provides a functional cor- cell number decreased during differentiation, we had limited relate for the gene-mapping data and opens the possibility for numbers of cells for most of the shRNA targets and therefore detailed mechanistic studies related to the mutations and path- used a modified RT-PCR protocol amenable for small number of ways in these disorders. Furthermore, this result may provide a cells (20–5,000 per well) (28) (SI Methods). In a few cases we framework to integrate and harness independent, large-scale obtained fewer than 20 cells and were unable to accurately assess datasets from quite distinct genomic approaches. mRNA expression (Fig. 3 A and B, diamonds). We confirmed the effects of shRNAs on neural differentiation by Discussion measuring NCAM1 mRNA expression levels of cells differentiated There are technical difficulties in using hESCs and shRNA li- to NPCs using real time qRT-PCR (Fig. 3B).EightofnineshRNAs braries to study in vitro neural differentiation. The infective titer resulted in significantly decreased NCAM1 mRNA expression for standard lentiviral vectors may be lower in ES cells than in cells

Table 2. GO analysis of gene targets whose shRNAs became depleted during neuronal differentiation GO category Adjusted P value Example

Transcription corepressor activity P = 0.038 SIRT1, TLE1, CITD2 Nonmembrane-bounded organelle P = 0.035 PFDN5, GABPA, TARDBP, PQBP1, REST Intracellular nonmembrane-bounded organelle P = 0.035 PFDN5, GABPA, TARDBP, PQBP1, REST, TRIM28, ZNF44

A total of 74 genes were analyzed by Database for Annotation, Visualization and Integrated Discovery (DAVID) using the entire gene collection targeted by the shRNA pool as input.

4of6 | www.pnas.org/cgi/doi/10.1073/pnas.1309725110 Zhang et al. Downloaded by guest on September 29, 2021 Fig. 3. Target hit validation by individual confirmation. (A) Knockdown efficiency of individual shRNAs. Fold-differences in the mRNA expression of the respective gene targets after individual shRNAs- infection compared with nontargeting shRNA infection as control. The mRNA expression in cells at the end of neuronal differentiation (NPC, dark gray bars) or in cells maintained in pluripotent condition for the same time period (ESC, light gray bars) is shown. TATA box binding protein (TBP1) was used as internal control for the real-time qPCR experiments. The SEM represents results from three technical replicates and two biological replicates with additional replication in H9 cells (NPCs) (Fig. S4). Diamond symbols indicate conditions when only <20 cells were available for RNA extraction (SI Methods). (B)NCAM1 mRNA expression of individual shRNA-infected cells cultured in neural differentiation medium. The SEM represents results from three technical replicates and two biological replicates with additional replication in H9 cells. (Fig. S4). Diamond symbols indicate conditions when only <20 cells were available for RNA extraction (see SI Methods for quantitative mRNA GENETICS measurement in low cell numbers). (C) Representa- tive bright-field images display TARDBP-1 and nontargeting control shRNA-infected hESCs at various time points undergoing neural differentiation (Left) or when maintained in pluripotent condition for 4 wk (Right). (Magnification: 10×.) (D) Immunostaining for TARDBP (red) in nontargeting control and TARDBP-1 shRNA-infected cells derived by neural differentiation. TARDBP immunoreactivity was reduced by ∼50% in TARDBP-1 shRNA harboring cells. DAP1 indicate nuclei (blue). (E) Immunostaining for PSA-NCAM (green, Left) and SOX1/NESTIN (red/green, Right) expression after neural differentiation of nontargeting control and TARDBP-1 shRNA infected hESCs. (Scale bars, 10 μm.)

such as HEK293 or HeLa. The hESCs are grown in monolayers the gene product was needed for the differentiation or survival rather than in suspension cultures and the undifferentiated cells of neural cells. Most (12 of 13) of the shRNAs against dropout have to be manually selected for passage. The experiments have to genes that were retested permitted the undifferentiated ES cells be carried out for a longer time than is used for most large-scale (two different ES lines) to grow essentially normally, but produced shRNAscreens. The present work shows that these studies are fewer cells when cultured in low FGF environment to generate and feasible using cell-type specific, phenotype-based approaches, maintain neural progenitors. rather than lethality readout. The use of more cells, and libraries TIALl, TARDBP, and PQBP1 are an interesting group and with higher coverage (more shRNA species per gene) with inserts a number of other RNA granule components have emerged as that have been more extensively screened for effectiveness and altering NPC generation in our screen, including members of a lack of target effects will be of great value, and could increase the family of proteins that contain RNA binding domains and a patch fraction of true positive hits and the efficiency of subsequent fi of glutamine and asparagine rich amino acid sequences (prion- target veri cation. related domains) (29). Polyglutamine regions are associated with One of the observations from the present study is that many formation of prion-like structures in organisms from yeast to man. of the shRNA targets depleted in the more differentiated PSA- These proteins play a role in RNA splicing and export, control of NCAM–positive neural precursors permitted normal growth of undifferentiated hESCs, even when the gene expression was translation, and sequestering of RNA molecules, perhaps related substantially reduced, but became essential for differentiation to the ability of prion-related domains to form aggregates. De- and survival under conditions that induced neural differentiation. pletion of TARDBP both impairs stress granule formation (30) One caveat is that the differentiation procedure involves passaging and makes the cells more vulnerable to arsenite-mediated stress. of cells that might be stressful independent of neural differentia- PQBP1 is a polyglutamine tract binding protein that lacks an as- tion. Nevertheless, the specific enrichment for genes with known paragine and glutamine rich cluster but can also form nuclear neural system-related functions among the PSA-NCAM–positive inclusions and is a component of other RNA granule types, such dropouts indicates that a major part of the selection was directly as neuronal RNA granules and stress granules (31). The molecular related to neural differentiation. links to how mutations of these proteins lead to distinct neu- Depletion of shRNAs targeting a particular gene could arise ropathological changes are unresolved and their precise role in because of the shRNA promoted differentiation into some embryonic or adult neuronal stem/progenitor cell function in nonneuronal type of cell, or perhaps more commonly, because physiological (or pathological) conditions is unknown.

Zhang et al. PNAS Early Edition | 5of6 Downloaded by guest on September 29, 2021 Table 3. Enrichment of gene targets implicated in ASD and to either genetic or environmental disturbances during develop- nonsyndromic MR/intellectual disability ment or in adulthood, resulting in later-onset manifestations. If Gene hits categories these early genes are turned on as part of a defensive reaction to Gene hit neural damage, removing their proteins would make the cells category Unchanged Total changed Absent susceptible to injury. Another interesting conclusion of our study is that a number Unchanged ———of genes that have been implicated in terminal aspects of differ- Total changed 0.0186 ——entiation, maintenance of mature neurons, or late-onset neurologic Absent 0.0193 0.746 — disorders may also function at early stages of neural commitment Enriched + Depleted 0.0346 0.8875 0.8875 and specification. Mutations in these genes could have pleiotropic effects on the nervous system, depending on the genetic envi- The ASD and MR/ID-related gene list used for cross reference was compiled fi from the literature using recent, large-scale, reproduced genomic datasets ronment and the speci c mutation. from affected and control subjects (SI Methods). The relative proportion of ASD Overall, the approach to shRNA screening we describe here has and MR/ID-associated gene targets was estimated by comparing the number of impressive potential to uncover lineage-specific gene functions. In these gene hits with the total number of genes in the same phenotypic cate- particular, it should be valuable to conduct such screens in ES or gory at the end of neural differentiation. “Total changed ” group indicates all induced pluripotent cells bearing disease-specific mutations. Fur- genes whose shRNAs were absent, enriched or depleted at the end of neural ther, genetic interaction studies of combinations of shRNAs (32) differentiation; all other categories defined as described in Fig. 2A and Table 1. identified in these screens to delineate functional pathways in The Enriched and Depleted categories were combined for this analysis and neural differentiation and maintenance could be particularly together indicate those genes whose shRNA was differently represented in informative. PSA-NCAM–positive and -negative cells at the end of the differentiation. The relative proportion of the ASD- and MR/intellectual disability-related gene Methods targets in each category was then compared and statistical significance was calculated as described in Table 1. The values in bold indicate significant differ- HESCs (H1 and H9) were grown as described previously, and the large-scale fi ences. There was significant enrichment of ASD and nonsyndromic MR/ID gene differentiation performed after minor modi cations of the protocol of Wu targets among those genes whose shRNA abundances changed during neural et al. (1). Cells were harvested at times indicated in Fig. 1B and shRNA inserts differentiation. recovered by PCR of total genomic DNA, following procedures based on the method by Bassik M. et al. (11). shRNAs were quantitated by high- throughput sequencing. Hits for gene targets were classified and analyzed It is tempting to think that RNA granule genes are required using various methods, including RIGER (21). Additional details of the pri- specifically for normal human neural development, neural stem/ mary shRNA library screen, data analysis, and hit confirmation are described progenitor maintenance, and function. One may contemplate above and in the SI Methods.SeeTable S8 forprimersequencesforreal-time that perturbed interaction between these proteins (such as due to qPCR of validated target genes. mutations) and RNA granule dysfunction result in an early cellular vulnerability that can lead to neurological disease. The cellular role ACKNOWLEDGMENTS. We thank Michael Bassik and Jonathan Weissman of various genes implicated in ASD, MR, and neurodegenerative for comments on high-throughput sequencing. This work was supported by fi National Institutes of Health Grants 1P01GM099130-01 and U54HG006996 (to disorders is just emerging and very little is known of the speci c S.M.W.), R33 MH087879 (to F.M.V.); the Connecticut Innovations Stem Cell, effects at the level neural stem cells. Perhaps impairment of genes State of Connecticut (Z.W., N.I., F.M.V., and S.M.W.); and The Mallinckrodt used in early neural differentiation makes the CNS more vulnerable foundation (N.I.).

1. Wu JQ, et al. (2010) Dynamic transcriptomes during neural differentiation of human 16. Anderson P, Kedersha N (2009) RNA granules: Post-transcriptional and epigenetic embryonic stem cells revealed by short, long, and paired-end sequencing. Proc Natl modulators of gene expression. Nat Rev Mol Cell Biol 10(6):430–436. Acad Sci USA 107(11):5254–5259. 17. Thomas MG, Loschi M, Desbats MA, Boccaccio GL (2011) RNA granules: The good, the 2. Kessler JD, et al. (2012) A SUMOylation-dependent transcriptional subprogram is bad and the ugly. Cell Signal 23(2):324–334. required for Myc-driven tumorigenesis. Science 335(6066):348–353. 18. Vierbuchen T, et al. (2010) Direct conversion of fibroblasts to functional neurons by 3. Zuber J, et al. (2011) RNAi screen identifies Brd4 as a therapeutic target in acute defined factors. Nature 463(7284):1035–1041. myeloid leukaemia. Nature 478(7370):524–528. 19. Guerillon C, Larrieu D, Pedeux R (2013) ING1 and ING2: Multifaceted tumor sup- 4. Ketela T, et al. (2011) A comprehensive platform for highly multiplexed mammalian pressor genes. Cell Mol Life Sci, 10.1007/s00018-013-1270-z. functional genetic screens. BMC Genomics 12:213. 20. Chen T, et al. (2012) An RNA interference screen uncovers a new molecule in stem cell 5. Moshkovich N, et al. (2011) RNAi-independent role for Argonaute2 in CTCF/CP190 self-renewal and long-term regeneration. Nature 485(7396):104–108. chromatin insulator function. Genes Dev 25(16):1686–1701. 21. Luo B, et al. (2008) Highly parallel identification of essential genes in cancer cells. Proc 6. Panda D, et al. (2011) RNAi screening reveals requirement for host cell secretory Natl Acad Sci USA 105(51):20380–20385. pathway in infection by diverse families of negative-strand RNA viruses. Proc Natl 22. Barbie DA, et al. (2009) Systematic RNA interference reveals that oncogenic KRAS- Acad Sci USA 108(47):19036–19041. driven cancers require TBK1. Nature 462(7269):108–112. 7. Boettcher M, et al. (2010) Decoding pooled RNAi screens by means of barcode tiling 23. Fisher RA (1944) Statistical Methods for Research Workers (Oliver and Boyd, Edinburgh). arrays. BMC Genomics 11:7. 24. Rossin EJ, et al.; International Inflammatory Bowel Disease Genetics Constortium 8. Schlabach MR, et al. (2008) Cancer proliferation gene discovery through functional (2011) Proteins encoded in genomic regions associated with immune-mediated dis- genomics. Science 319(5863):620–624. ease physically interact and suggest underlying biology. PLoS Genet 7(1):e1001273. 9. Paddison PJ, et al. (2004) A resource for large-scale RNA-interference-based screens in 25. Dewey CM, et al. (2012) TDP-43 aggregation in neurodegeneration: are stress gran- mammals. Nature 428(6981):427–431. ules the key? Brain Res 1462:16–25. 10. Westbrook TF, et al. (2005) A genetic screen for candidate tumor suppressors iden- 26. Budini M, et al. (2012) Cellular model of TAR DNA-binding protein 43 (TDP-43) ag- tifies REST. Cell 121(6):837–848. gregation based on its C-terminal Gln/Asn-rich region. J Biol Chem 287(10):7512–7525. 11. Bassik MC, et al. (2009) Rapid creation and quantitative monitoring of high coverage 27. McDonald KK, et al. (2011) TAR DNA-binding protein 43 (TDP-43) regulates stress granule shRNA libraries. Nat Methods 6(6):443–445. dynamics via differential regulation of G3BP and TIA-1. Hum Mol Genet 20(7):1400–1410. 12. Kaelin WG, Jr. (2012) Molecular biology. Use and abuse of RNAi to study mammalian 28. Pan X, et al. (2012) Two methods for full-length RNA-seq for low quantities of cells gene function. Science 337(6093):421–422. and single cells. Proc Natl Acad Sci USA 110(2):594–599. 13. Wu H, et al. (2007) Integrative genomic and functional analyses reveal neuronal 29. King OD, Gitler AD, Shorter J (2012) The tip of the iceberg: RNA-binding proteins with subtype differentiation bias in human embryonic stem cell lines. Proc Natl Acad Sci prion-like domains in neurodegenerative disease. Brain Res 1462:61–80. USA 104(34):13821–13826. 30. Aulas A, Stabile S, Vande Velde C (2012) Endogenous TDP-43, but not FUS, contributes 14. Gascon E, Vutskits L, Kiss JZ (2007) Polysialic acid-neural cell adhesion molecule in to stress granule assembly via G3BP. Mol Neurodegener 7:54. brain plasticity: From synapses to integration of new neurons. Brain Res Brain Res Rev 31. Kunde SA, et al. (2011) The X-chromosome-linked intellectual disability protein 56(1):101–118. PQBP1 is a component of neuronal RNA granules and regulates the appearance of 15. Pruszak J, Sonntag KC, Aung MH, Sanchez-Pernaute R, Isacson O (2007) Markers and stress granules. Hum Mol Genet 20(24):4916–4931. methods for cell sorting of human embryonic stem cell-derived neural cell populations. 32. Bassik MC, et al. (2013) A systematic mammalian genetic interaction map reveals Stem Cells 25(9):2257–2268. pathways underlying ricin susceptibility. Cell 152(4):909–922.

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