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

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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 us- ing 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 undif- ferentiated 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.
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