CHD8 Dosage Regulates Transcription in Pluripotency and Early Murine Neural Differentiation

CHD8 dosage regulates transcription in pluripotency and early murine neural differentiation

Sabina Sooda,b,1, Christopher M. Webera,b,1, H. Courtney Hodgesc,d, Andrey Krokhotine, Aryaman Shalizia,b, and Gerald R. Crabtreea,b,e,2

aDepartment of Pathology, Stanford University School of Medicine, Stanford, CA 94305; bDepartment of Developmental Biology, Stanford University School of Medicine, Stanford, CA 94305; cDepartment of Molecular and Cellular Biology, Baylor College of Medicine, Houston, TX 77030; dCenter for Precision Environmental Health, Baylor College of Medicine, Houston, TX 77030; and eHoward Hughes Medical Institute, Chevy Chase, MD 20815

Contributed by Gerald R. Crabtree, July 7, 2020 (sent for review December 16, 2019; reviewed by Bradley E. Bernstein and Gordon L. Hager) The chromatin remodeler CHD8 is among the most frequently mu- Here, we utilized mouse embryonic stem cells (ESCs) and dif- tated genes in autism spectrum disorder (ASD). CHD8 has a dosage- ferentiation into neural progenitor cells (NPCs) as a model system sensitive role in ASD, but when and how it becomes critical to human to study the role of CHD8 in early embryonic gene regulation and social function is unclear. Here, we conducted genomic analyses of control of genome-wide accessibility. We created both homozygous heterozygous and homozygous Chd8 mouse embryonic stem cells and heterozygous Chd8 deletions, enabling us to characterize the and differentiated neural progenitors. We identify dosage-sensitive effect of gene dosage on these important processes. We demon- CHD8 transcriptional targets, sites of regulated accessibility, and an strate that CHD8 has a dosage-sensitive effect on transcriptional unexpected cooperation with SOX transcription factors. Collectively, regulation in ESCs and upon differentiation into NPCs that is our findings reveal that CHD8 negatively regulates expression of consistent with premature neuronal differentiation. Surprisingly, we neuronal genes to maintain pluripotency and also during differenti- find that CHD8 directly associates with SOX2 to maintain acces- ation. Thus, CHD8 is essential for both the maintenance of pluripo- sibility in support of the pluripotency gene network. Collectively, we tency and neural differentiation, providing mechanistic insight into demonstrate an essential role for CHD8 in regulating the accessible its function with potential implications for ASD. chromatin landscape and gene expression, providing insight into the function of CHD8 with potential implications for ASD. autism spectrum disorder (ASD) | chromatin remodeling | pluripotency | GENETICS neural progenitors | chromodomain helicase DNA-binding protein 8 (CHD8) Results Dosage-Sensitive Effects of CHD8 Deletion on Transcription in ESCs. ynamic regulation of chromatin structure is required to en- We were particularly motivated to study CHD8 gene dosage in Dsure rapid transcriptional responses during development and pluripotency and in neurogenesis because it is one of the most to maintain these programs in order to safeguard cellular identity. highly constrained genes in the human genome (19) and is hap- Central to these regulatory processes are chromatin-remodeling loinsufficient for human neurodevelopment and human social ′ enzymes, which hydrolyze adenosine 5 -triphosphate (ATP) to behavior, as indicated by its role in ASD. Consistent with these modify chromatin structure and DNA accessibility by reposition- observations, CHD8 has a very high probability of being intolerant ing, editing, or evicting nucleosomes (1). There are four major to the loss of function of a single allele in humans (Fig. 1A). subfamilies of ATP-dependent nucleosome remodelers classified Previous work has shown that CHD8 expression at embryonic day by phylogenetic relationships and distinct functional activities (2). 12.5 (E12.5) is ∼10-fold higher compared to the adult, and Chd8 Of these, the chromodomain helicase DNA-binding (CHD) class of remodelers is of particular interest because it is implicated in Significance human diseases. In mammals, there are nine CHD family members, each containing two tandemly arranged chromodomains The chromatin remodeler CHD8 is one of the most frequently upstream of their catalytic SNF2 helicase domain that are involved mutated genes in autism spectrum disorder (ASD), but the in nucleosome spacing and histone variant H3.3 incorporation (3, mechanistic basis remains unclear. Here, we identify dosage- 4). Individual CHD family members are frequently inactivated in sensitive roles for CHD8 in the regulation of transcription and ’ specific human diseases, including Hodgkin slymphoma(CHD3), define CHD8’s role in regulating genome-wide accessibility. neuroblastoma (CHD5), CHARGE syndrome (CHD7), and au- Importantly, we present new results that help to define the tism spectrum disorder (ASD) (CHD8) (5). CHD8 is of particular molecular function of CHD8 both in the context of pluripotency interest because it is one of the most commonly mutated genes in and in neural differentiation with implications for its role in ASD (6), but the mechanistic basis remains unclear. ASD. By determining the execution point at which mutations in CHD8 regulates important developmental pathways and is Chd8 might contribute to the disease, we hope to discover the essential during embryogenesis. For example, CHD8 inhibits potential for therapeutic approaches. β-catenin and Wnt-signaling pathways as well as p53-dependent transactivation, preventing widespread apoptosis (7–9). Consis- Author contributions: S.S., C.M.W., and G.R.C. designed research; S.S., C.M.W., and A.S. tent with a specific role in neurodevelopmental disorders, CHD8 performed research; S.S. and C.M.W. contributed new reagents/analytic tools; S.S., C.M.W., H.C.H., A.K., and A.S. analyzed data; and S.S., C.M.W., and G.R.C. wrote targets pathways associated with ASD and intellectual disability the paper. – +/− (10 13). Additionally, Chd8 and CHD8 knockdown mouse Reviewers: B.E.B., Harvard Medical School and Broad Institute; and G.L.H., National models recapitulate some ASD-like behavioral phenotypes, sug- Cancer Institute. gesting a causal role in promoting ASD etiology (14–17). While The authors declare no competing interest. these studies have demonstrated that CHD8 is a critical tran- Published under the PNAS license. scriptional regulator during neurogenesis, there are discrepancies 1S.S. and C.M.W. contributed equally to this work. regarding CHD8’s role in cell cycle exit (18); moreover, it remains 2To whom correspondence may be addressed. Email: [email protected]. unclear how CHD8 is targeted to its chromatin sites, the down- This article contains supporting information online at https://www.pnas.org/lookup/suppl/ stream effect of its recruitment on accessibility, and how these doi:10.1073/pnas.1921963117/-/DCSupplemental. biochemical activities regulate transcription.

www.pnas.org/cgi/doi/10.1073/pnas.1921963117 PNAS Latest Articles | 1of10 Downloaded by guest on September 30, 2021 knockout mice arrest at E7.5, implying an essential role for CHD8 sequencing (RNA-seq) to characterize the effect of CHD8 de- during the neural progenitor stage (20). Thus, we generated single letion on gene expression changes over the approximately five or double allelic Chd8 deletions in mouse ESCs, a well-studied passages required to generate the mutant ESC lines (SI Appen- and context-relevant model system. Using a single guide RNA dix, Fig. S1B). As expected, there were significantly more differ- (sgRNA), we targeted CRISPR-Cas9 to exon 12, which includes entially expressed genes (DEGs) upon homozygous CHD8 deletion the ATPase/helicase domain (Fig. 1B) (21). Single or double de- (709 up-regulated and 673 down-regulated) compared to hetero- letion clones were validated by Sanger sequencing and Western zygous deletion (162 up-regulated and 110 down-regulated genes) − blotting, which confirmed that CHD8 protein level was reduced to (Fig. 1E). Interestingly, the Chd8+/ DEGs showed substantial − − − − − ∼50% in the Chd8+/ line and was undetectable in the Chd8 / overlap with Chd8 / for both increased (77.8% overlap, 126 of cell line, enabling investigation into CHD8 dosage. 162) and decreased (78.2% overlap, 86 of 110) genes, confirming Consistent with previous results (22), CHD8 knockout cells that CHD8 activity is dosage sensitive (haploinsufficient) in ESCs. − − proliferated at a significantly slower rate, with a doubling time Consistent with this finding, many DEGs in the Chd8 / ESCs − that was twice as long as wild-type (WT) and Chd8+/ cells exhibited moderate dosage-sensitive expression changes when a (Fig. 1C; n = 3, P < 0.05). The decreased proliferation rate was single allele of CHD8 was deleted (Fig. 1F). not due to cell cycle arrest (SI Appendix, Fig. S1A). To assay the To identify the key regulatory pathways controlled by CHD8, effect of CHD8 deletion on pluripotency, we stained cells for we conducted gene ontology (GO) term analysis of biological alkaline phosphatase (Fig. 1D). While all genotypes stained with processes on DEGs (Fig. 1G). Genes that were up-regulated in − − − − similar intensity, the Chd8 / cells did not form colonies like Chd8 / were enriched for processes associated with nervous − the WT and Chd8+/ cells (2i growth conditions), indicative of system development, neurogenesis, and cell cycle (P < 0.01 for all − compromised pluripotency. To explore this result, we used RNA terms), whereas Chd8+/ did not show significant GO enrichment.

Fig. 1. Dosage-sensitive effect of CHD8 deletion on transcription in ESCs. (A) The gnomAD human gene constraint scores (missense and probability of in- tolerance to heterozygous pLoF variation [pLI] for all genes with CHD8 labeled). (B) Schematic showing the CHD8 CRISPR-mediated deletion approach and − − − − − − Western blot of CHD8 levels in Chd8+/ and Chd8 / ESC lines. (C) Doubling time of WT, Chd8+/ , and Chd8 / cells. Asterisks denote P < 0.05 (*). Values are − − − expressed as the mean ± SE, n = 3. (D) Alkaline phosphatase staining of WT, Chd8+/ , and Chd8 / ESCs in 2i media. Magnification: 200×.(E) Venn diagrams − − − depicting overlap of DEGs in Chd8+/ and Chd8 / ESCs. Genes with increased expression are on top, and genes with decreased expression are on the bottom (FDR < 0.05). (F) Heatmap showing dosage-sensitive transcriptional response for genes that are differentially expressed in Chd8−/−.(G) GO terms for DEGs (padj < 0.05).

2of10 | www.pnas.org/cgi/doi/10.1073/pnas.1921963117 Sood et al. Downloaded by guest on September 30, 2021 − − − In contrast, the Chd8+/ and Chd8 / ESCs showed reduced ex- with CHD8 levels (Fig. 2G), confirming that the observed tran- pression of genes enriched for suppression of apoptotic process, scription changes result in changes to protein levels. Collectively, cellular component biogenesis, and regulation of developmental these results reveal that CHD8 is required at full dosage to in- process (P < 0.01 for all terms). Gene set enrichment analysis hibit transcription of late differentiation genes and transcription (GSEA) showed significant enrichment for pathways indicative of factors, such that its inactivation causes cells to differentiate derepressed transforming growth factor beta (TGFβ) signaling (SI beyond NPCs toward a more mature neuronal cell type. Appendix,Fig.S1D; FDR-adjusted P = 0.007). TGFβ plays a central role in tissue morphogenesis, and stimulation with TGFβ CHD8 Regulates Accessibility at Key Regions in ESCs and during causes neural stem cells to lose multipotency and differentiate Differentiation to NPCs. Chromatin remodelers are important reg- along the neuronal lineage (23, 24). On the other hand, CHD8 ulators of genomic accessibility. To investigate the role of CHD8 knockout showed enrichment of genes up-regulated upon inacti- in regulating the accessible chromatin landscape in mutant ESCs vation of lysine-specific histone demethylase 1 (LSD1/KDM1A) and NPCs, we performed Assay for Transposase-Accessible = Chromatin with high-throughput sequencing (ATAC-seq) (31). (FDR-adjusted P 0.003), which demethylates monomethylated − and dimethylated histone H3 lysine 4 (H3K4me1 and H3K4me2) In contrast to transcriptional changes, we found that Chd8+/ had and is critical for mouse embryonic development beyond E6.5 a modest effect on accessibility in both ESCs (two increased and (25). Collectively, our results reveal that CHD8 is required to three decreased sites) and NPCs (86 increased and 40 decreased repress neural differentiation but not for maintenance of the core sites), considering the number of called peaks (n = 93,093 and 43,190, respectively) (SI Appendix, Figs. S2A and S3A). This was pluripotency network OSKM (Oct4, Sox2, Klf4,andc-Myc)and − has a modest dosage-sensitive role in transcription. somewhat surprising, since Chd8+/ mutation resulted in many more DEGs, yet other studies have noted a less than deterministic CHD8 Knockout Results in Up-Regulation of Neuronal Genes and Sox relationship between accessibility (ATAC-seq) and transcription TFs upon Differentiation into NPCs. Having characterized the role (32). Nonetheless, we found that a fraction of DEGs had differ- − − − of CHD8 in ESCs, we differentiated Chd8+/ and Chd8 / ESCs ential accessibility at their promoter (ESC = 14.7% and NPC = into self-renewing NPCs to define the role of CHD8 in a disease- 10.2%) (SI Appendix,Fig.S3D and E). This lack of a strong relevant context (Fig. 2A). Additionally, neural induction is the haploinsufficient effect on accessibility is further reflected in the default differentiation pathway in early vertebrate embryos (26) heat map clustering and principal component analysis, which − and can be faithfully driven in vitro with autocrine signaling showed that the accessibility states of WT and Chd8+/ cells are − − pathways (27). To define the genes regulated by CHD8 upon more similar to each other than to Chd8 / cells (SI Appendix, Fig. +/− differentiation, we conducted RNA-seq in the Chd8 and S2 B and C). Similarly, mSWI/SNF or BAF complexes are also GENETICS − − Chd8 / NPCs (SI Appendix, Fig. S1C). We found that, upon haploinsufficient in human disease and generate accessibility, yet differentiation, there were many more DEGs compared to ESCs heterozygous deletion in ESCs produced subtle changes in ac- (∼1.5-fold), but, similar to ESCs, there was substantial overlap cessibility measured by ATAC-seq (33). − − − − − between Chd8+/ and Chd8 / NPCs for both increased (76.5% Chd8 / ESCs and NPCs had considerably more accessibility overlap, 297 of 388) and decreased (76.1% overlap, 305 of 401) changes (ESCs: 1,522 increased and 2,927 decreased sites; NPCs: DEGs (Fig. 2B) with a similar dosage-sensitive response to ESCs 4,313 increased and 1,465 decreased sites). Surprisingly, the − − (Fig. 2C). GO term analysis of genes with increased expression in overall effect of Chd8 / on the direction of accessibility changes CHD8 mutants revealed significant enrichment for terms asso- was opposite in ESCs compared to NPCs, such that the majority ciated with brain development, such as neuron differentiation, of sites became less accessible in ESCs and more accessible in axonogenesis, and corpus callosum morphogenesis (Fig. 2D; P < NPCs upon loss of CHD8 (Fig. 3 A and C). This suggests that 0.003 for all terms). In human ASD patients with disruptive CHD8 primarily functions to promote accessibility in the context mutations in CHD8, corpus callosum hypogenesis is a prevalent of maintaining pluripotency but represses accessibility during phenotype (28). In contrast, genes with decreased expression in differentiation, likely reflecting differentiation slightly beyond − − − both Chd8+/ and Chd8 / showed significant enrichment for the NPC state. We next sought to determine whether CHD8 has embryogenesis terms, such as epithelial tube and embryonic pla- a direct role in regulating accessibility at the changed sites. We centa morphogenesis (P < 0.0001 for all terms). Genes showing reasoned that defining CHD8 localization in ESCs would be most − − reduced expression in Chd8 / NPCs were associated with GO appropriate, considering that differentiation following CHD8 de- terms for cell cycle and suppression of apoptotic process, similar letion induced the up-regulation of many neurogenic transcription to ESCs. GSEA showed a significant enrichment of p53 target factors and resulted in a greater change to cellular identity, which genes in neuroepithelium (FDR-adjusted P < 0.0001), an impor- likely resulted in accessibility changes that are independent of tant regulator of cell cycle and apoptosis (SI Appendix, Fig. S1D), CHD8 remodeling activity. We conducted CHD8 chromatin im- consistent with previous results (8, 20). Many of the most signifi- munoprecipitation sequencing (ChIP-seq) in ESCs and observed a − − − cantly up-regulated genes in Chd8+/ and Chd8 / NPCs are in- striking enrichment at differential accessibility sites (SI Appendix, volved in later stages of neuronal development, including Ascl1 [a Fig. S3B). Thus, CHD8 deletion in ESCs and NPCs resulted in central driver of neural reprogramming (29)], Dcx, Map2, Nefm, many reproducible accessibility changes that are consistent with Neurod4,andNeurog1 (Fig. 2 E and F). Additionally, we found being direct targets of CHD8. − − − that Sox3 is derepressed in both Chd8+/ and Chd8 / NPCs, and We next analyzed the genomic annotations of differentially − − several other Sox TF members (Sox2, Sox7, and Sox11) became accessible sites in Chd8 / ESCs. We found that the sites that lost − − derepressed in the Chd8 / cells (SI Appendix,Fig.S5C). SOX accessibility were highly enriched for enhancers and super- proteins act in a sequential manner during neurogenesis to select enhancers (Fig. 3B;Log2 enrichment = 3.64 and 3.41, respec- neural genes in ESCs for later activation in NPCs or neurons (30). tively). In contrast, sites that gained accessibility were enriched at We confirmed these transcriptional changes by immunofluo- CpG islands, 5′ untranslated regions, and promoters (Log2 en- rescence (IF) staining of the NPC cultures (Fig. 2G). WT and richment = 4.37, 3.93, and 3.22, respectively) but were depleted at both mutant Chd8 lines stained positive for Nestin, a neural stem intergenic regions (Log2 enrichment = −1.24). To determine − − − cell marker; however, Chd8+/ and Chd8 / NPCs showed whether specific genomic marks or factors were associated with stronger staining for immature (DCX, NEUROD1, and TuJ1) the CHD8-induced accessibility changes, we leveraged the wealth and mature (MAP2A) neurons, as well radial glia (Pax6). In- of available ChIP-seq datasets in ESCs. We conducted Lasso terestingly, DCX, NEUROD1, MAP2a, PAX6, and TUJ1 multivariate regression (34, 35) for our ATAC-seq datasets and found staining seemed to show a dose-dependent negative correlation the strongest positive association between increased accessibility sites

Sood et al. PNAS Latest Articles | 3of10 Downloaded by guest on September 30, 2021 Fig. 2. CHD8 deletion results in up-regulation of neuronal genes and Sox TFs during differentiation into NPCs. (A) Schematic showing the differentiation of WT, Chd8+/−, and Chd8−/− ESCs into NPCs. (B) Venn diagrams depicting overlap of DEGs in Chd8+/− and Chd8−/− NPCs. Genes with increased gene expression are on top, and genes with decreased expression are on bottom (FDR < 0.05). (C) Heatmap showing dosage sensitive transcriptional response for genes that − − − − − are differentially expressed in Chd8 / .(D) GO terms for DEGs. (E and F) Volcano plots of RNA-seq data for CHD8+/ and CHD8 / . DEGs are highlighted in red (FDR < 0.05), and genes involved with mature neuronal development and Sox TFs are labeled. Genes labeled with yellow background were stained by IF in G. (G) Representative IF staining of day 8 NPCs, with antibodies listed on left side and respective genotypes on top (n = 2 biological replicates with similar results). Magnification: 200×.

4of10 | www.pnas.org/cgi/doi/10.1073/pnas.1921963117 Sood et al. Downloaded by guest on September 30, 2021 GENETICS

Fig. 3. CHD8 regulates accessibility at key regions in ESCs and during differentiation to NPCs. (A) Percentage of increased (blue) and decreased (orange) − − − − peaks for Chd8 / ESCs. (B) Genomic annotation enrichment for increased and decreased sites for Chd8 / ESC ATAC-seq datasets. (C) Percentage of increased − − − − − (blue) and decreased (orange) peaks for Chd8 / NPCs. (D) Genomic annotation enrichment for increased and decreased sites for Chd8+/ and Chd8 / NPC ATAC-seq datasets. (E) Genome tracks showing gain of accessibility at Grb10 locus in ESCs. (F) Genome tracks showing loss of accessibility at Basp1 locus in NPCs.

and LSD1, H3K4me2, H3K4me3, and H3K27me3 ChIP signal (SI direct interaction (7, 20). Our data suggest that CHD8 executes Appendix,Fig.S3C). This suggests that the chromodomain, which these roles by directly repressing genomic accessibility, perhaps binds dimethylated histone H3K4 (22), likely targets CHD8 to render through histone H1 recruitment or nucleosome movement. In these sites less accessible. Bivalent genes that contain both H3K4me3 contrast, accessibility was most reduced at pluripotency factor and H3K27me3 play an important role in cell differentiation (36, 37), sequence motifs including Oct4 (Pou5f1), Sox2, and Esrrb when and these general changes can be seen in a representative browser CHD8 was deleted in ESCs. This result is somewhat surprising snapshot for Grb10 (Fig. 3E). In NPCs, we found that both decreased considering that these pluripotency factors extensively autor- and increased sites were enriched at CpG islands, promoters, and egulate each other (39) and were not differentially expressed in − − enhancers but were depleted at intergenic regions and transcription Chd8 / ESCs (SI Appendix, Fig. S5B). Yet, CHD8 ChIP local- termination sites (Fig. 3D). The accessibility changes in NPCs share ization was strongly biased toward promoters and enriched for genomic features similar to ESCs. These changes can be observed in binding OCT4−Sox2−TCF−Nanog and Ctcf motifs, supporting a representative browser tracks at the Basp1 gene,which,despitevery direct role in regulating genomic accessibility (SI Appendix, Fig. subtle genome-wide changes, appears to exhibit a dosage-sensitive S5 E and F). CHD8 and Sox2 regulate a significant number of effect on accessibility during NPC differentiation (Fig. 3F). We next overlapping genes (40) (SI Appendix, Fig. S5G; P value = 0.0045), analyzed the pathway and ontology of genes nearest to differentially yet none of the characteristic trophectoderm differentiation mark- accessible peaks (SI Appendix,Fig.S4). Consistent with the examples ers seen in the SOX2 knockdown cells were also up-regulated in the − − shown, we find strong enrichment for pathways like Wnt signaling and Chd8 / ESCs, suggesting the overall effect of these accessibility GO terms, such as development and neurogenesis. Thus, CHD8 changes does not phenocopy SOX2 loss. To further determine regulates chromatin accessibility at the promoters of important reg- whether transcription factors are physically bound to these differ- ulators of embryonic development and cell differentiation. entially accessible sites, we leveraged existing ChIP-seq datasets of known developmental regulatory and pluripotency factors. Consis- CHD8 Cooperates with Sox TFs to Regulate Accessibility and tent with a direct role for CHD8 in cooperating with these factors to Transcription. Chromatin-remodeling enzymes lack sequence- generate accessibility, we observed that the decreased accessibility − − specific DNA-binding domains, so we next sought to investi- sites were strongly enriched for these factors in Chd8 / ESCs, in- gate a potential cooperation between CHD8 and transcription cluding SOX2, NANOG, and OCT4 (SI Appendix,Fig.S5A). In − − factors. Using chromVAR (38), we defined the sequence motifs contrast, increased accessibility sites in Chd8 / ESCs were strongly with the highest deviation in accessibility across genotypes. This depleted where these factors bind. analysis revealed that accessibility increased at sequence motifs To characterize the types of accessibility changes at these for p53 and Ctcf when CHD8 is deleted in ESCs (Fig. 4A). motifs, we calculated changes in flanking accessibility (FA) and CHD8 has previously been shown to antagonize p53-mediated footprint depth (FPD) upon Chd8 deletion for a set of 579 apoptosis and to support CTCF insulator function through a transcription factors. We modified the BaGplot approach (42) to

Sood et al. PNAS Latest Articles | 5of10 Downloaded by guest on September 30, 2021 Fig. 4. CHD8 cooperates with Sox TFs to regulate accessibility and transcription. (A) Heatmap representation of ATAC-seq chromVAR bias-corrected deviations in the 50 most variable TF motifs across ESC WT and Chd8−/− ATAC-seq replicates. (B) Heatmap representation of ATAC-seq chromVAR bias-corrected deviations in the 50 most variable TF motifs across NPC WT and Chd8−/− ATAC-seq replicates. (C) Western blot showing co-IP of CHD8 with SOX2 in ESCs (antibodies used are the following: SOX2 A: sc-365823; SOX2 B: AB5603). (D) Heat map displaying CHD8 ChIP-seq at SOX2 peaks (41) (Left) and SOX2 ChIP-seq at CHD8 peaks (Right).

visualize changes in FA and FPD (SI Appendix, Fig. S6A). The accessibility independent of CHD8 remodeling activity. We con- outliers in the bagplot represent transcription factors with the firmed accessibility changes in Sox family motifs using bagplot (SI greatest changes in FA and FPD as compared to the average. We Appendix,Fig.S6C), where Sox TFs appear as a single cluster near found that the Oct4:Sox2 binding motif is one of the strongest the fence border. Interestingly, the Oct4:Sox2 motif, which is one outliers and that the Ctcf motif appeared at the fence border, of the outliers in ESCs, does not come up in the Sox cluster in which confirm results from the chromVAR analysis. In addition, NPCs. Remarkably, outlier TFs in bagplot also include the family among outliers, we found other transcription factors important of Retinoid X Receptors (Rxra, Rxrb, Rxrg), known regulators of for maintenance of the ESC pluripotent state, such as Gbx2 (43), neural cell fate specification (48), and the Gata TF family. Gata Mybl2 (44), Zscan4 (45), Foxd3 (46), and Smad3 (47). We found TFs play a crucial role in cell fate determination (49); in partic- that these transcription factors either directly interact with each ular, Gata2 determines the choice between GABAergic and glu- other or have correlated expression, which suggests their func- tamatergic interneuron specification (50). GATA2 and RXRA are tional relationship (SI Appendix, Fig. S6B). Thus, CHD8 facili- functionally related (SI Appendix,Fig.S6D) and have been shown tates pluripotency by cooperatively generating accessibility at to interact in hematopoietic progenitors (51). sites that are bound by pluripotency transcription factors. Since CHD8 deletion did not significantly affect Sox2 ex- − − We anticipated that NPCs differentiated from Chd8 / ESCs pression in ESCs but did result in the loss of accessibility at Sox2 would show enrichment of sequence motifs for the many neuro- binding motifs, we sought to determine whether the reliance on − − genic TFs that were strongly derepressed by Chd8 / (e.g., Ascl1). CHD8 for accessibility at these sites was mediated by a direct Instead, the most strongly enriched motifs were nearly exclusive to protein−protein interaction. We immunopurified SOX2 from the Sox TF family (Fig. 4B). We considered that CHD8 might ESCs using two different antibodies, and, in both cases, we ob- have a dual role in mediating accessibility for SOX2 in ESCs and served clear CHD8 co-immunoprecipitation (co-IP) that was not repressing the Sox family of TFs in NPCs. However, it is more seen with IgG control antibodies (Fig. 4C). We also tested SOX3 likely that the increased accessibility we observed is due to strong from NPCs and detected a weaker co-IP signal, but considering − − up-regulation of a few Sox TF genes (Sox2, Sox3, Sox7,andSox11) that Sox3 is up-regulated in the Chd8 / NPCs, we cannot deter- − − in Chd8 / NPCs (SI Appendix,Fig.S5C), which exhibit pioneer mine whether this interaction facilitates repression (SI Appendix, activity and are able to outcompete nucleosomes to generate Fig. S4D). We reasoned that, if CHD8 is being physically targeted

6of10 | www.pnas.org/cgi/doi/10.1073/pnas.1921963117 Sood et al. Downloaded by guest on September 30, 2021 to SOX2 binding sites to facilitate accessibility, then there should requirement for remodeling (52, 53). Despite this, our data re- be substantial overlap between them. To test this hypothesis, we veal that maintenance of accessibility at these motifs depends, at plotted CHD8 occupancy at SOX2 binding sites (41) and plotted least in part, on the activity of CHD8. It is intriguing that CHD8 SOX2 at CHD8 binding sites. Consistent with direct targeting by has a dual role in maintaining accessibility at pluripotency motifs SOX2, we found extensive colocalization (Fig. 4D). Thus, CHD8 while repressing accessibility at Ctcf and p53 motifs. Previously, both positively and negatively regulates accessibility through co- CHD8 has been shown to load H1 as a mechanism of repression operation with transcription factors and, indirectly, by maintaining (20), and our findings suggest that this could potentially be one their repression. mechanism by which CHD8 represses accessibility. It is likely, then, that local cooperative interactions determine whether Discussion CHD8 promotes or represses genomic accessibility. For example, Here, we investigated the role of CHD8 in the maintenance of CHD8 likely mediates accessibility through cooperative action of pluripotency and during differentiation into NPCs (Fig. 5). Uti- OCT4, SOX2, ESRRB, histone modifications, and perhaps other lizing heterozygous and homozygous genetic deletions, we showed transcriptional activators to facilitate transcription initiation. In that CHD8 primarily functions to repress cell differentiation and contrast, CHD8 likely represses accessibility at p53 motifs and nervous system development pathways in addition to previously Ctcf binding sites through sampling-based mechanisms, direct implicated pathways, such as p53 and the cell cycle. We demon- recruitment, and perhaps loading of histone H1 (7). Future strated that CHD8 is a dosage-sensitive repressor of neuronal studies are needed to distinguish the precise mechanisms that tip pathways that results in premature differentiation when inacti- the balance between promoting accessibility and repression. vated. Finally, we defined the role of CHD8 in regulating genome- Of the nine members of the CHD family, CHD7 and CHD8 wide accessibility. In ESCs, CHD8 represses accessibility at p53/ have been shown to play vital roles in neurodevelopment (54). Ctcf motifs, while maintaining accessibility at pluripotency motifs, Heterozygous mutations in CHD7 and CHD8 result in neuro- at least in part, through a new, direct protein−protein interaction developmental disorders, such as CHARGE syndrome and ASD, with SOX2, whereas, in NPCs, CHD8 represses accessibility of Sox respectively. Previously, CHD7 has been shown to physically motifs, which could be mediated through a direct interaction or as interact with SOX2 and regulate neurogenesis in NSCs (55). a downstream consequence of derepressing the transcription fac- Additionally, in oligodendroglia, CHD7 and CHD8 appear to tors that bind these motifs. Interestingly, these effects were largely cooperate with SOX10 to activate stage-specific genes (56). Our dosage insensitive, suggesting that loss of a single allele of CHD8 finding that CHD8 also physically associates with SOX2/3 sug- compromises transcription to a greater degree than accessibility. gests that there might be conserved functional interplay between GENETICS However, we did find a small but consistent set of differentially other CHD family members, and perhaps other SOX TFs in accessible peaks that were dosage sensitive during early neural neural cell types as a general principle. differentiation, so it is possible that CHD8 exerts a stronger One of the significant questions relating to the pathogenesis of haploinsufficient effect during complete neurogenesis. ASD has been the execution point at which mutated genes How, then, does CHD8 regulate transcription and accessibility contribute to the disease. The significance of this question de- at specific genomic loci? We found that CHD8 repressed ac- rives from the potential for therapeutic approaches after ASD is cessibility in ESCs at sites enriched for H3K4me2/3 and pro- diagnosed. Our studies support work indicating that the execu- moted accessibility at loci bound by pluripotency factors, tion point for CHD8 might be quite early and dosage dependent. suggesting two dominant modes of recruitment: 1) binding to Furthermore, we find that CHD8 is bound to many other ASD posttranslational modifications on chromatin and 2) interaction risk genes, consistent with other studies (10). Given our unique findings demonstrating the importance of CHD8 in regulating with transcription factors, like SOX2. A well-established pioneer genome-wide accessibility and transcription of critical genes in factor, SOX2 is able to bind nucleosomal DNA without the pluripotency and neuronal differentiation, studies are needed in − − Chd8 / mouse models and in vitro to further examine the mechanisms described here. Methods Culturing of Mouse Embryonic Stem Cells. TC1 ESCs were cultured on 0.1%

gelatin-coated plates at 37 °C with 5% CO2 in 2i media: Dulbecco’s modified Eagle Medium/Nutrient Mixture F-12 (DMEM/F12), Neurobasal Medium, 3% fetal bovine serum (FBS), N2 and B27 supplements, 100× penicillin/streptomycin, 2 mM GlutaMAX, 0.1 mM minimal essential media non-essential amino acids, Hepes, Sodium Pyruvate, 0.1 mM β-mercaptoethanol, and 1,000 U/mL leukemia inhibitory factor. The complete 2i media was made with 1 μM PD0325901 and 3 μM CHIR99021. ES cells were passaged every 2 d.

Generation of CRISPR Cell Lines. Low-passage TC1(129) mouse ESCs were thawed onto mouse embryonic fibroblast (MEF)-coated dishes and passaged once on gelatin-coated dishes before transfection. Then 2 M cells were nucleofected (Lonza #VVPH-1001, A-013 program) with 8 μg PX459V2.0 (Addgene #62988) containing sgRNA targeting CHD8 exon 12 that was published previously (5′-ACGCTCCCAGTTAGTAATGG-3′) (21). Following transfection, 0.5 M cells were seeded onto 6-cm dishes coated with DR4 MEFs and cultured for 24 h before puromycin selection (1.0 μg/mL, 1.25 μg/mL, or 1.5 μg/mL) for 48 h. Single colonies were manually picked, dissociated with trypsin, and expanded on MEFs. Colonies containing heterozygous and homozygous insertions were confirmed by PCR and Western blotting.

Neural Differentiation Protocol. Neural differentiation of ESCs was performed as previously described by Abranches et al. (27). In brief, ESCs were main- tained using standard conditions in media containing DMEM, 15% ES-sure Fig. 5. Model summarizing findings. FBS, 100× penicillin/streptomycin, 2 mM GlutaMAX, 0.1 mM MEM-NEAA,

Sood et al. PNAS Latest Articles | 7of10 Downloaded by guest on September 30, 2021 Hepes, Sodium Pyruvate, 0.1 mM β-mercaptoethanol, and 1,000 U/mL LIF. To centered at the true fragment ends. The density of pseudofragments was start the differentiation protocol, ESCs were plated at 1 × 104/cm2 on 0.1% used to perform peak calling by MACS 2.1.1 (58). All peaks from control and gelatin-coated plates in N2B27 media: DMEM/F12, Neurobasal Medium, N2 mutant datasets within ± 1 kb were merged for differential analysis, and and B27 supplements, 100× penicillin/streptomycin, 2 mM GlutaMAX, 0.1 mM peaks were discarded if they were below a threshold of 10 RPM in at least MEM-NEAA, Hepes, Sodium Pyruvate, and 0.1 mM β-mercaptoethanol. The one dataset to remove low-quality peak calls. The mean read density in the N2B27 media was changed every other day. On day 4, cells were dissociated 100-bp window 8 kb away from each peak was used to obtain the back- with Accutase and plated at 2 × 104/cm2 on laminin-coated plates in N2B27 ground density of ATAC-seq signal. This background density was subtracted media supplemented with 5 ng/mL of epidermal growth factor (EGF) and basic from the overall read density within each peak in each dataset. Differential fibroblast growth factor (bFGF). peak calling was performed by comparing the total number of background- adjusted reads overlapping each of the resulting peaks for each dataset. Western Blot. Cells were lysed for 30 min at 4 °C in radioimmunoprecipitation Using the summed number of background-adjusted reads at the top 5% of assay buffer (RIPA) buffer (50 mM Tris·HCl pH 8.0, 150 mM NaCl, 0.1% so- highest read-density sites as size factors, differential peak calls were made dium dodecyl sulfate [SDS], 0.5% sodium deoxycholate, 1% Nonidet P-40) using DESeq2 (59), which accounts for individual site variances across all supplemented with 1 mM dithiothreitol (DTT), 0.5 mM phenylmethylsulfonyl replicates to make differential peak calls. The default use of maximum a fluoride (PMSF), 1 mM protease inhibitor mixture (Roche), and 1:200 ben- posteriori estimation using a zero-mean normal prior (Tikhonov–Ridge zonase (Sigma-Aldrich). Lysates were centrifuged at maximum speed regularization) was used to calculate log2-fold changes. The Benjamini– (14,000 × g), and total protein concentration was measured by Bradford Hochberg procedure was used to calculate FDR-corrected P values, and dif- assay (Bio-Rad). Extracts were mixed with Laemmli sample buffer containing ferential calls were made by requiring fold changes of >1.5-fold in either 50 mM DTT and loaded onto a 4 to 12% Bis-Tris SDS/polyacrylamide gel direction and FDR-corrected P < 0.10. The mean values across both replicates electrophoresis (Thermo Fisher Scientific). Protein was transferred to Protran from each condition are the RPM values in the genome tracks. Bwtool (60) 0.1-mm nitrocellulose membrane (Thermo Fisher Scientific) and blocked in was used to compute mean density profiles by calculating the mean base 5% milk/Tris-buffered saline, 0.1% Tween-20 Detergent (TBST). Blots were pair coverage across all replicates for a given condition. Bedtools (61) was then probed with primary antibodies followed by staining with used to determine overlap of peaks. fluorescence-conjugated secondary antibodies (Li-Cor), and bands were detected using an Odyssey CLX imaging system (Li-Cor). ChIP-seq Library Preparation. As previously described, ChIP libraries were independently prepared from separately cultured samples in duplicate (33, Preparation of Nuclear Extracts for Immunoprecipitation. ESCs were dissoci- 62–64). Briefly, 10 million to 30 million cells were fixed in 1% formaldehyde ated with trypsin, and NPCs were dissociated with Accutase and washed with for 10 min to 12 min at room temperature. Cross-linking was stopped with PBS. Cells were lysed on ice in Buffer A (25 mM Hepes [pH 7.6], 5 mM MgCl2, the addition of glycine to 125 mM to quench excess formaldehyde. Cells 25 mM KCl, 0.05 mM EDTA, 10% glycerol, 0.1% Nonidet P-40), supplemented were washed and centrifuged, and pellet was flash frozen in liquid nitrogen. with 1 mM DTT, 0.5 mM PMSF, 1 mM protease inhibitor mixture (Roche). Thawed pellets were then resuspended in NP Rinse 1 buffer (50 mM Hepes- Nuclei were centrifuged (500 × g) and resuspended in Buffer C (10 mM KOH, pH 8.0, 140 mM NaCl, 1 mM EDTA, pH 8.0, 10% glycerol, 0.5% Nonidet Hepes [pH 7.6], 3 mM MgCl2, 100 mM KCl, 0.1 mM EDTA, 10% glycerol), P-40, 0.25% Triton X-100) and incubated on ice for 10 min. Isolated nuclei supplemented with 1 mM DTT, 0.5 mM PMSF, 1 mM protease inhibitor were washed once with NP Rinse 2 buffer (10 mM Tris·HCl, pH 8.0, 1 mM mixture (Roche). Nuclei were lysed with the addition of ammonium sulfate EDTA, pH 8.0, 0.5 mM EGTA, pH 8.0, 200 mM NaCl) and twice with Covaris to a final concentration of 0.3 M, and ultracentrifugation (100,000 × g) was Shearing buffer (0.1% SDS, 1 mM EDTA, pH 8.0, 10 mM Tris·HCl, pH 8.0) to used to separate the soluble nuclear proteins from the insoluble chromatin remove salt. Pellets were resuspended in 0.9 mL of Covaris Shearing buffer fraction. Soluble nuclear proteins were precipitated with the addition of with 1 mM protease inhibitor mixture (Roche) and sonicated for 10 min to 0.3 mg/mL ammonium sulfate for 20 min on ice, and proteins were isolated 12 min in a Covaris E220 sonicator. This generated chromatin fragments by ultracentrifugation (100,000 × g). Nuclear extract was stored at −80 °C for between 200 bp and 1,000 bp in length which were then immunoprecipi- later use in IP assays. tated with FLAG M2 antibody (endogenous C terminus of CHD8 was tagged) bound to Protein G Dynabeads (Life Technologies) in ChIP buffer (50 mM Immunoprecipitation Assays. Nuclear extracts obtained from ESCs or NPCs Hepes-KOH, pH 7.5, 300 mM NaCl, 1 mM EDTA, pH 8.0, 1% Triton X-100, were resuspended in IP Buffer (150 mM NaCl, 50 mM Tris [pH 7.5], 1 mM EDTA, 0.1% DOC, 0.1% SDS) overnight at 4 °C. The next day, the beads were 10% glycerol, 0.5% Triton X-100), supplemented with 1 mM DTT, 0.5 mM washed four times with ChIP buffer, once with DOC buffer (10 mM Tris·HCl, PMSF, 1 mM protease inhibitor mixture (Roche). Bradford assays were used pH 8.0, 250 mM LiCl, 0.5% Nonidet P-40, 0.5% DOC, 1 mM EDTA, pH 8.0), to determine protein concentration, which was adjusted to 300 μg for each and once with Tris-EDTA (TE) buffer. Libraries were constructed on beads by IP. Samples were incubated with 5 μg of antibody and Protein A Dynabeads ChIPmentation (65). Sequencing was performed single-end on the Illumina (Thermo Fisher) rotating overnight at 4 °C. The following day, the magnetic HiSeq2000 sequencer. beads were washed three times with 1 mL per wash of IP Buffer at room temperature and then resuspended in 20 μLof2× loading buffer (LDS, Processing of ChIP-seq Data. The following techniques were applied uniformly Thermo Fisher) with 10 mM DTT for subsequent immunoblot analysis. to all datasets as previously described (33). Processing of single-end ChIP-seq reads was performed by mapping to the mm9 reference mouse genome ATAC Library Preparation. ATAC libraries were independently prepared from using Bowtie 2.1.0 (57). Reads that contained more than a single mismatch separately cultured samples in duplicate as described previously (31). Briefly, and duplicates were discarded, leaving only unique reads. By comparing to we dissociated cells with Accutase (Life Technologies) and obtained nuclei input samples for each cell type, peak calling was performed by MACS 2.1.1 from 50,000 viable cells by resuspending cells in 0.5 mL of lysis buffer (0.1% (58) for all analyses. The mean values across both replicates from each Tween-20 in RSB buffer [10 mM Tris·HCl, pH 7.4, 10 mM NaCl, 3 mM MgCl2]) condition are the RPM values in the genome tracks. Bwtool (60) was used to and incubated them for 10 min on ice. Nuclei were pelleted by centrifuga- compute mean genome track densities. tion for 10 min at 500 × g, resuspended in 50 μL of transposition mix (1× Tagmentation DNA buffer, 2.5 μL Tagment DNA enzyme [Illumina]), and RNA-seq Library Preparation and Data Analysis. Cells were dissociated with incubated for 30 min at 37 °C. DNA was purified with a MinElute PCR pu- Accutase, washed with PBS, and immediately resuspended in Trisure (Bioline rification kit (Qiagen), and libraries were amplified by PCR with barcoded # BIO-38033). Total RNA was isolated following manufacturer’s guidelines Nextera primers (Illumina). For sequencing, libraries were size-selected with and digested with DNaseI (Thermo Fisher #18068015), and digestion reac- Agencourt AMPure XP (Beckman Coulter) for fragments between ∼50 bp tion was cleaned up with acid-phenol:chloroform. RNA sequencing libraries and 1,000 bp in length according to the manufacturer’s instructions. Li- were made from 1 μg of RNA (RIN > 9) using the SMARTer kit (Takara Bio # braries were sequenced using paired-end reads on the Illumina HiSeq2000 634874) which produces stranded libraries from ribosomal RNA-depleted sequencer. total RNA. Libraries were amplified with 12 PCR cycles and quantified with Qubit, and size distribution was determined by Bioanalyzer. Libraries were Processing of ATAC-seq Data. The following techniques were applied uni- sequenced on an Illumina Nextseq, and the first three bases were trimmed formly to all datasets as previously described. Processing of paired-end reads with cutadapt (66) before quantification. Transcript abundances were was performed by mapping to the mm9 reference mouse genome using quantified by Kallisto (67) using the University of California Santa Cruz Bowtie 2.1.0 (57). Only high-quality unique reads were kept, while duplicate Genome Browser transcript tables for the mm9 genome assembly. fragments and reads with mapping quality of <10 were discarded. Two Transcript-level abundance estimates from Kallisto and gene-level count pseudofragments were generated for each fragment and occupied 200 bp matrices were created using Tximport (68). Differential expression analysis

8of10 | www.pnas.org/cgi/doi/10.1073/pnas.1921963117 Sood et al. Downloaded by guest on September 30, 2021 was conducted with DESeq2 version 1.22.2 (59) using default parameters, visualization technique from the BagFoot package (42) to present changes in after prefiltering genes with low counts (rowSums > 10). Differential calls FPD and FA across conditions as a bagplot plot. In brief, the bagplot is de- were made by requiring FDR-corrected P < 0.05. GO and pathway analysis fined by its median point, the bag and the fence. The bag is constructed was conducted using the PANTHER classification system (69). around median point and contains about 50% of all points. The fence is obtained by inflating the bag by factor 3. STRING (73) was used to evaluate GSEA. As described previously, a list of Refseq transcripts was prepared based transcription factor mutual associations such as direct interaction or on the output of DESeq2 from RNA-seq data, which was used to perform coexpression.

GSEA (33). RefSeq genes, ranked by log2-fold change, were imported into the GSEA application created by the Broad Institute. Enrichment plots and Public Datasets Analyzed in This Study. Read densities were obtained from FDR-corrected P values were obtained directly from the modified publicly available National Center for Biotechnology Information Gene Ex- Kolmogorov–Smirnov test performed by the GSEA application. pression Omnibus datasets. For each of these chromatin feature datasets, read fragments were extended to 200 bp from the 3′ end, and base pair Genome Annotation Enrichment. Enrichment for overlap with genomic an- coverage was determined using Bedtools (61). notations was performed as previously described by comparing the frequency that each peak fell into basic genomic annotations (33). This was separately Antibodies Used in This Study. Antibodies used in this study are mouse a-FLAG determined for each group of differential peak call described above. M2 (1:1,000, Sigma-Aldrich), rabbit a-CHD8 (1:2,500, Novus Biologicals HOMER was used to calculate enriched GO terms and log enrichment of #NB100-60417; 1:2,000, Novus Biologicals #NB100-60418), mouse a-TBP genomic annotation overlap for each group of sites (70). (1:2,000, Abcam #ab818), rabbit a-DCX (1:200, CST #4604S), mouse a-Nestin (1:200, #MAB353), mouse a-Tuj1 (1:200, BioLegend #801201), rabbit Lasso Multivariate Regression. Lasso multivariate regression (35) was per- a-Pax6 (1:200, BioLegend #901301), rabbit a-NeuroD1 (1:200, Proteintech formed as previously described (33). Briefly, the fold change in ATAC-seq #12081-1-AP), and mouse a-Map2a (1:200, M9942). read density was related to a linear combination of 111 individual chromatin features, Alkaline Phosphatase. ESCs were cultured in 6-cm plates for 4 d and fixed with 4% paraformaldehyde. Reagents were prepared according to the protocol log fc = β x + β x + ... + β x . 2 1 1 2 2 n n included in the Alkaline Phosphatase Detection Kit (Sigma-Aldrich, #SCR004). The number of reads within ±3 kb from the center of each ATAC peak was Briefly, dishes were incubated in stain solution at room temperature in the summed for each of the 111 chromatin features from previously published dark for 15 min. The AP-expressing cells were stained red.

datasets. At each site, the summed read count was log10 transformed and scaled to unit variance across all sites (xi). The R package “glmnet” (71) was IF. NPCs were fixed in 4% paraformaldehyde for 15 min, blocked, and per- used to perform the Lasso regression with the default mixing penalty pa- meabilized with 3% normal donkey serum and 0.25% Triton in TBS.

rameter α = 1. Values for the restricted parameter (λ=∑iβi) were obtained They were then incubated with primary antibodies ON at 4 °C followed GENETICS − − − for the Chd8+/ and Chd8 / ESCs and NPCs by 10-fold cross-validation with by secondary goat anti-rabbit or anti-mouse antibodies (Invitrogen) and the minimal value selected that provided the lowest mean cross-validation DAPI, washed with TBS, and imaged on a Keyence BZ-X710 fluorescent error. microscope.

chromVAR. The chromVAR was performed similarly to that previously de- Data Availability. All sequencing data have been deposited in Gene Expression scribed (38). Briefly, normalized peaks were filtered to only include peaks Omnibus (accession number GSE155218). containing one fragment across all samples. Peaks were matched to mouse_pwms_v1 motifs, and the top 50 most variable motifs across the ACKNOWLEDGMENTS. We thank the Genome Aggregation Database samples were calculated and plotted. (gnomAD) and the groups that provided exome and genome variant data to this resource. A full list of contributing groups can be found at https:// FPD and FA Calculation. We used vertebrate subset of JASPAR CORE motif gnomad.broadinstitute.org/about. We are grateful to Thomas Edlund from database accounting for 579 motifs in total (72). TF FPD and FA were defined Umeå University in Sweden for kindly sharing the Sox3 antibody and to as FPD = log (N =N ) and FA = log (N =N ), where N , Wendy Wenderski for critical comments on the manuscript. We thank 2 MOTIF FLANK 2 FLANK BG MOTIF V. Natu, D. Wagh, and J. Coller at the Stanford Functional Genomics Facility NFLANK, and NBG are average number of Tn5 inserts calculated in [−5 bp, − − − − for their help with sequencing. S.S. is supported by NSF Graduate Research +5 bp], [ 55 bp, 6 bp] U [6 bp, 55 bp] and [ 200 bp, 250 bp] U [200 bp, 250 Fellowship 2013169249 and the National Institute of Mental Health (Pro- bp] intervals around motif center, respectively. Only motifs found within gram F31-MH111157). G.R.C. is supported by Howard Hughes Medical Insti- ATAC-seq peaks were used in calculations. The positions of the Tn5 inserts tute, NIH Grant R37 NS046789 and the Simons Foundation Autism Research were defined as the first base pair in the sequencing read offset by 4 bp Initiative Grant 306063. C.M.W. is supported by the Walter V. and Idun Berry & (by −5 bp) for reads aligned to + (to −) strand (31). We accommodated the GSK Sir James Black Fellowship. H.C.H. is supported by NIH Grant R00CA187565.

1. G. J. Narlikar, R. Sundaramoorthy, T. Owen-Hughes, Mechanisms and functions of 11. A. Sugathan et al., CHD8 regulates neurodevelopmental pathways associated with ATP-dependent chromatin-remodeling enzymes. Cell 154, 490–503 (2013). autism spectrum disorder in neural progenitors. Proc. Natl. Acad. Sci. U.S.A. 111, 2. C. R. Clapier, J. Iwasa, B. R. Cairns, C. L. Peterson, Mechanisms of action and regulation E4468–E4477 (2014). of ATP-dependent chromatin-remodelling complexes. Nat. Rev. Mol. Cell Biol. 18, 12. B. Wilkinson et al., The autism-associated gene chromodomain helicase DNA-binding 407–422 (2017). protein 8 (CHD8) regulates noncoding RNAs and autism-related genes. Transl. Psy- 3. A. Y. Konev et al., CHD1 motor protein is required for deposition of histone variant chiatry 5, e568 (2015). H3.3 into chromatin in vivo. Science 317, 1087–1090 (2007). 13. F. Zahir et al., Novel deletions of 14q11.2 associated with developmental delay, 4. J. A. Micucci, E. D. Sperry, D. M. Martin, Chromodomain helicase DNA-binding pro- cognitive impairment and similar minor anomalies in three children. J. Med. Genet. teins in stem cells and human developmental diseases. Stem Cells Dev. 24, 917–926 44 , 556–561 (2007). (2015). 14. A. L. Gompers et al., Germline Chd8 haploinsufficiency alters brain development in 5. C. G. A. Marfella, A. N. Imbalzano, The Chd family of chromatin remodelers. Mutat. mouse. Nat. Neurosci. 20, 1062–1073 (2017). Res. 618,30–40 (2007). 15. Y. Katayama et al., CHD8 haploinsufficiency results in autistic-like phenotypes in mice. 6. S. Banerjee-Basu, A. Packer, SFARI Gene: an evolving database for the autism research Nature 537, 675–679 (2016). community. Dis. Model Mech. 3, 133–135, 10.1242/dmm.005439 (2010). 16. R. J. Platt et al., Chd8 mutation leads to autistic-like behaviors and impaired striatal 7. K. Ishihara, M. Oshimura, M. Nakao, CTCF-dependent chromatin insulator is linked to circuits. Cell Rep. 19, 335–350 (2017). epigenetic remodeling. Mol. Cell 23, 733–742 (2006). 17. P. Suetterlin et al., Altered neocortical gene expression, brain overgrowth and 8. M. Nishiyama et al., Early embryonic death in mice lacking the beta-catenin-binding functional over-connectivity in chd8 haploinsufficient mice. Cereb. Cortex 28, protein Duplin. Mol. Cell. Biol. 24, 8386–8394 (2004). 2192–2206 (2018). 9. B. A. Thompson, V. Tremblay, G. Lin, D. A. Bochar, CHD8 is an ATP-dependent chro- 18. M. W. Breuss, J. G. Gleeson, When size matters: CHD8 in autism. Nat. Neurosci. 19, matin remodeling factor that regulates beta-catenin target genes. Mol. Cell. Biol. 28, 1430–1432 (2016). 3894–3904 (2008). 19. K. J. Karczewski et al., The mutational constraint spectrum quantified from variation 10. J. Cotney et al., The autism-associated chromatin modifier CHD8 regulates other in 141,456 humans. Nature 581, 434–443 (2020). autism risk genes during human neurodevelopment. Nat. Commun. 6, 6404 20. M. Nishiyama et al., CHD8 suppresses p53-mediated apoptosis through histone H1 (2015). recruitment during early embryogenesis. Nat. Cell Biol. 11, 172–182 (2009).

Sood et al. PNAS Latest Articles | 9of10 Downloaded by guest on September 30, 2021 21. C. Shen et al., NSD3-Short is an adaptor protein that couples BRD4 to the CHD8 48. Z. Simandi et al., RXR heterodimers orchestrate transcriptional control of neuro- chromatin remodeler. Mol. Cell 60, 847–859 (2015). genesis and cell fate specification. Mol. Cell. Endocrinol. 471,51–62 (2018). 22. M. Rodríguez-Paredes, M. Ceballos-Chávez, M. Esteller, M. García-Domínguez, J. C. 49. M. Tremblay, O. Sanchez-Ferras, M. Bouchard, GATA transcription factors in devel- Reyes, The chromatin remodeling factor CHD8 interacts with elongating RNA poly- opment and disease. Development 145, dev164384 (2018). merase II and controls expression of the cyclin E2 gene. Nucleic Acids Res. 37, 50. K. Joshi, S. Lee, B. Lee, J. W. Lee, S. K. Lee, LMO4 controls the balance between ex- 2449–2460 (2009). citatory and inhibitory spinal V2 interneurons. Neuron 61, 839–851 (2009). 23. R. Fueyo et al., Lineage specific transcription factors and epigenetic regulators me- 51. S. Tsuzuki et al., Cross talk between retinoic acid signaling and transcription factor β – diate TGF -dependent enhancer activation. Nucleic Acids Res. 46, 3351 3365 (2018). GATA-2. Mol. Cell. Biol. 24, 6824–6836 (2004). 24. G. Plasari et al., Nuclear factor I-C links platelet-derived growth factor and trans- 52. A. Soufi, G. Donahue, K. S. Zaret, Facilitators and impediments of the pluripotency forming growth factor beta1 signaling to skin wound healing progression. Mol. Cell. reprogramming factors’ initial engagement with the genome. Cell 151, 994–1004 – Biol. 29, 6006 6017 (2009). (2012). 25. C. T. Foster et al., Lysine-specific demethylase 1 regulates the embryonic tran- 53. A. Soufi et al., Pioneer transcription factors target partial DNA motifs on nucleosomes scriptome and CoREST stability. Mol. Cell. Biol. 30, 4851–4863 (2010). to initiate reprogramming. Cell 161, 555–568 (2015). 26. I. Muñoz-Sanjuán, A. H. Brivanlou, Neural induction, the default model and embry- 54. J. V. Goodman, A. Bonni, Regulation of neuronal connectivity in the mammalian onic stem cells. Nat. Rev. Neurosci. 3, 271–280 (2002). brain by chromatin remodeling. Curr. Opin. Neurobiol. 59,59–68 (2019). 27. E. Abranches et al., Neural differentiation of embryonic stem cells in vitro: A road 55. E. Engelen et al., Sox2 cooperates with Chd7 to regulate genes that are mutated in map to neurogenesis in the embryo. PLoS One 4, e6286 (2009). human syndromes. Nat. Genet. 43, 607–611 (2011). 28. C. Zhao et al., Dual requirement of CHD8 for chromatin landscape establishment and 56. C. Marie et al., Oligodendrocyte precursor survival and differentiation requires histone methyltransferase recruitment to promote CNS myelination and repair. Dev. chromatin remodeling by Chd7 and Chd8. Proc. Natl. Acad. Sci. U.S.A. 115, Cell 45, 753–768.e8 (2018). – 29. O. L. Wapinski et al., Hierarchical mechanisms for direct reprogramming of fibroblasts E8246 E8255 (2018). to neurons. Cell 155, 621–635 (2013). 57. B. Langmead, C. Trapnell, M. Pop, S. L. Salzberg, Ultrafast and memory-efficient 30. M. Bergsland et al., Sequentially acting Sox transcription factors in neural lineage alignment of short DNA sequences to the human genome. Genome Biol. 10, R25 development. Genes Dev. 25, 2453–2464 (2011). (2009). 31. J. D. Buenrostro, P. G. Giresi, L. C. Zaba, H. Y. Chang, W. J. Greenleaf, Transposition of 58. Y. Zhang et al., Model-based analysis of ChIP-seq (MACS). Genome Biol. 9, R137 native chromatin for fast and sensitive epigenomic profiling of open chromatin, DNA- (2008). binding proteins and nucleosome position. Nat. Methods 10, 1213–1218 (2013). 59. M. I. Love, W. Huber, S. Anders, Moderated estimation of fold change and dispersion 32. S. L. Klemm, Z. Shipony, W. J. Greenleaf, Chromatin accessibility and the regulatory for RNA-seq data with DESeq2. Genome Biol. 15, 550 (2014). epigenome. Nat. Rev. Genet. 20 , 207–220 (2019). 60. A. Pohl, M. Beato, bwtool: A tool for bigWig files. Bioinformatics 30, 1618–1619 33. H. C. Hodges et al., Dominant-negative SMARCA4 mutants alter the accessibility (2014). landscape of tissue-unrestricted enhancers. Nat. Struct. Mol. Biol. 25,61–72 (2018). 61. A. R. Quinlan, I. M. Hall, BEDTools: A flexible suite of utilities for comparing genomic 34. B. Z. Stanton et al., Smarca4 ATPase mutations disrupt direct eviction of PRC1 from features. Bioinformatics 26, 841–842 (2010). chromatin. Nat. Genet. 49, 282–288 (2017). 62. A. Barski et al., High-resolution profiling of histone methylations in the human ge- 35. R. Tibshirani, Regression shrinkage and selection via the Lasso. J. R. Stat. Soc. B 58, nome. Cell 129, 823–837 (2007). 267–288 (1996). 63. W. Jin et al., Genome-wide detection of DNase I hypersensitive sites in single cells and 36. B. E. Bernstein et al., A bivalent chromatin structure marks key developmental genes FFPE tissue samples. Nature 528, 142–146 (2015). in embryonic stem cells. Cell 125, 315–326 (2006). 64. B. L. Kidder, K. Zhao, Efficient library preparation for next-generation sequencing 37. A. Meissner et al., Genome-scale DNA methylation maps of pluripotent and differ- analysis of genome-wide epigenetic and transcriptional landscapes in embryonic stem – entiated cells. Nature 454, 766 770 (2008). cells. Methods Mol. Biol. 1150,3–20 (2014). 38. A. N. Schep, B. Wu, J. D. Buenrostro, W. J. Greenleaf, chromVAR: Inferring 65. C. Schmidl, A. F. Rendeiro, N. C. Sheffield, C. Bock, ChIPmentation: Fast, robust, low- transcription-factor-associated accessibility from single-cell epigenomic data. Nat. input ChIP-seq for histones and transcription factors. Nat. Methods 12, 963–965 Methods 14, 975–978 (2017). (2015). 39. R. A. Young, Control of the embryonic stem cell state. Cell 144, 940–954 (2011). 66. M. Martin, Cutadapt removes adapter sequences from high-throughput sequencing 40. S. Masui et al., Pluripotency governed by Sox2 via regulation of Oct3/4 expression in reads. EMBnet.J. 17, 3 (2011). mouse embryonic stem cells. Nat. Cell Biol. 9, 625–635 (2007). 67. N. L. Bray, H. Pimentel, P. Melsted, L. Pachter, Near-optimal probabilistic RNA-seq 41. W. A. Whyte et al., Master transcription factors and mediator establish super- quantification. Nat. Biotechnol. 34, 525–527 (2016). enhancers at key cell identity genes. Cell 153, 307–319 (2013). 68. C. Soneson, M. I. Love, M. D. Robinson, Differential analyses for RNA-seq: Transcript- 42. S. Baek, I. Goldstein, G. L. Hager, Bivariate genomic footprinting detects changes in level estimates improve gene-level inferences. F1000 Res. 4, 1521 (2015). transcription factor Activity. Cell Rep. 19, 1710–1722 (2017). 69. H. Mi et al., Protocol Update for large-scale genome and gene function analysis with 43. M. Wang, L. Tang, D. Liu, Q. L. Ying, S. Ye, The transcription factor Gbx2 induces – expression of Kruppel-like factor 4 to maintain and induce naïve pluripotency of the PANTHER classification system (v.14.0). Nat. Protoc. 14, 703 721 (2019). embryonic stem cells. J. Biol. Chem. 292, 17121–17128 (2017). 70. S. Heinz et al., Simple combinations of lineage-determining transcription factors 44. J. Musa, M. M. Aynaud, O. Mirabeau, O. Delattre, T. G. Grünewald, MYBL2 (B-myb): A prime cis-regulatory elements required for macrophage and B cell identities. Mol. Cell – central regulator of cell proliferation, cell survival and differentiation involved in 38, 576 589 (2010). tumorigenesis. Cell Death Dis. 8, e2895 (2017). 71. J. H. Friedman, T. Hastie, R. Tibshirani, Regularization paths for generalized linear 45. T. Amano et al., Zscan4 restores the developmental potency of embryonic stem cells. models via coordinate descent. J. Stat. Software 33, 22 (2010). Nat. Commun. 4, 1966 (2013). 72. A. Khan et al., JASPAR 2018: Update of the open-access database of transcription 46. J. L. Plank, M. T. Suflita, C. L. Galindo, P. A. Labosky, Transcriptional targets of Foxd3 factor binding profiles and its web framework. Nucleic Acids Res. 46, D260–D266 in murine ES cells. Stem Cell Res. (Amst.) 12, 233–240 (2014). (2018). 47. X. Shi et al., TGF-β/Smad3 stimulates stem cell/developmental gene expression and 73. C. von Mering et al., STRING: Known and predicted protein-protein associations, in- vascular smooth muscle cell de-differentiation. PLoS One 9, e93995 (2014). tegrated and transferred across organisms. Nucleic Acids Res. 33, D433–D437 (2005).

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