Massively parallel disruption of enhancers active in human neural stem cells

Abstract

Changes in gene regulation have been linked to the expansion of the human cerebral cortex and to neurodevelopmental disorders, potentially by altering neural progenitor proliferation. However, the effects of genetic variation within regulatory elements on neural progenitors remain obscure. We use sgRNA-Cas9 screens in human neural stem cells (hNSCs) to disrupt 10,674 genes and 26,385 conserved regions in 2,227 enhancers active in the developing human cortex and determine effects on proliferation. Genes with proliferation phenotypes are associated with neurodevelopmental disorders and show biased expression in specific fetal human brain neural progenitor populations. Although enhancer disruptions overall have weaker effects than gene disruptions, we identify enhancer disruptions that severely alter hNSC self-renewal. Disruptions in human accelerated regions, implicated in human brain evolution, also alter proliferation. Integrating proliferation phenotypes with chromatin interactions reveals regulatory relationships between enhancers and their target genes contributing to neurogenesis and potentially to human cortical evolution.

Keywords: CP: Genomics; CP: Neuroscience; enhancers; gene regulation; human accelerated regions; human neural stem cells; neurodevelopment; neurodevelopmental disorders.

Figure 1.. Identifying genes and enhancers that alter human neural stem cell (hNSC) proliferation following genetic disruption

(A) Top: summary of conserved regions within enhancers, genes, and background control regions targeted in the sgRNA-Cas9 genetic screen. Putative TFBSs within enhancers were identified based on the 46-species Placental Mammal PhastCons element annotation (GRCh37/hg19; STAR Methods). Each PhastCons element was divided into approximately 30-bp conserved regions and targeted for genetic disruption by sgRNAs. Genes were targeted based on evidence of expression in hNSCs. Genomic background controls are non-coding regions with no detectable evidence of regulatory activity based on epigenetic signatures (STAR Methods). Bottom: schematic transduction of sgRNA-Cas9 lentiviral libraries into hNSCs at a low MOI (~0.3) to ensure that cells were infected by a single virion, and, on average, 1,000 cells were infected per sgRNA. Changes in the abundance of each sgRNA over time and classification of proliferation phenotypes was carried out as described in the main text. (B and C) Scatterplots illustrating beta scores (β) for two biological replicates resulting from genetic disruption of genes (B) and conserved regions within enhancers (C), measured at 12 cell divisions following transduction. Each point shows the effect of individual sgRNAs assigned to a protein-coding gene or conserved region within an enhancer relative to non-targeting controls for each biological replicate, as indicated in the legend shown in (B). Gene and enhancer disruptions affecting proliferation in regions with known biological roles in NSCs are identified by name (orange). Examples of genes were selected based on NSC maintenance or association with neurodevelopmental disorders. Enhancer examples were selected based on evidence of a regulatory interaction with genes with roles in chromatin modification and association with neurodevelopmental disorders or their identification as an HAR or HGE. Spearman correlations between replicates for gene (B) and conserved-region disruptions (C) are shown at the bottom left. (D) Distribution of proliferation phenotypes resulting from disruption of genomic background control regions (light gray), enhancers (red) and genes (dark gray) at 4, 8, and 12 cell divisions. Boxplots illustrate the lower (25th percentile), middle (50th percentile), and upper (75th percentile) of beta scores for each category. Each point shows the jointly modeled effect across biological replicates for all sgRNAs assigned to a protein-coding gene or conserved region within an enhancer relative to non-targeting controls. Error bars indicate an estimated 95% confidence interval. *p < 2.2 × 10^–16, Mann-Whitney U test.

Figure 2.. Characterization of gene proliferation phenotypes

(A) Left: principal-component analysis (PCA) of all gene disruptions, with a 2D density overlay illustrating the distribution of proliferation-decreasing (blue), neutral (gray), and proliferation-increasing (green) phenotypes and individual gene disruptions (orange) with biological roles in the maintenance of NSCs or human neurodevelopment; see text for details. Right: temporal dynamics captured by PCA shown at 4, 8, and 12 cell divisions. (B) Top: histogram of proliferation scores obtained from PCA for gene disruptions (black) and genomic background controls (gray). Bottom: partitioning of all gene disruptions that decrease proliferation into severe (top 25%) and strong (top 50%) categories. (C) Fold enrichment of GO biological processes and risk gene sets within the partitions shown in (B). n.s., not significant. Hypergeometric BH-corrected p values are as follows: *p < 0.05, **p < 0.005, ***p < 0.0005. (D) FGF signaling pathway (Reactome: R-HSA-1226099); see text for details. Genes disrupted within this pathway are shown in black, and a significant subset (BH-corrected p = 2.8 × 10⁻²) results in proliferation phenotypes (red).

Figure 3.. Characterization of enhancer proliferation phenotypes

(A) Left: PCA of all gene disruptions with a 2D density overlay illustrating the distribution of proliferation-decreasing (blue), neutral (gray), and proliferation-increasing (green) phenotypes and individual conserved region disruptions (orange) with biological roles in the maintenance of NSCs or human neurodevelopment; see text for details. Right: temporal dynamics captured by PCA shown at 4, 8, and 12 cell divisions. (B) Top: histogram of proliferation scores obtained from PCA for enhancer disruptions (black) and genomic background controls (gray). Bottom: partitioning of all enhancer disruptions that decrease proliferation into severe (top 25%) and strong (top 50%) categories. (C) Top: genomic alignments for human, chimpanzee, and mouse for a conserved region within an HAR enhancer (HACNS96). Human-specific substitutions (red) indicate genetic changes occurring within the conserved regions targeted for genetic disruption in the screen. Bottom: examples of deletion alleles introduced by Cas9 in this locus, determined by long-read amplicon resequencing and alignment to the reference genome (GRCh37/hg19). (D) Predicted TFBSs were obtained from the JASPAR 2018 TFBS prediction database and are significantly enriched in proliferation-altering enhancer disruptions within the partitions shown in (B). Hypergeometric BH-corrected p values are as follows: *p < 0.05, **p < 0.005, ***p < 0.0005.

Figure 4.. Frequency of proliferation-altering disruptions in enhancers, HARs, and HGEs

(A) The number of disrupted conserved regions leading to a proliferation phenotype within each enhancer (left, shown in gray) or in each HAR or HGE (right, shown in red). (B) The proportion of proliferation-altering disruptions compared with all targeted sites in all enhancers (gray) and HARs or HGEs (red). The dashed line indicates the mean density of proliferation phenotypes within all enhancers in the screen. (C) The total number of conserved regions disrupted within each enhancer (x axis) compared with the cumulative proliferation phenotype burden within each enhancer (y axis). Mutation-sensitive enhancers identified by permutation analysis (see D and main text for details) are labeled based on the most proximal gene. HARs and HGEs are labeled in red. The results of the permutation analysis, including the number of disrupted sites with a phenotype compared with the total number of targeted sites and the enrichment p values, are provided in Table S11. (D) A mutation-sensitive enhancer near SPRY2, a regulator of the FGF signaling pathway. Top: genomic coordinates indicate position on the reference genome (GRCh37/hg19). Three enhancers (i, ii, and iii), shown by the extent of H3K27ac marking (light blue bars) in hNSCs, were disrupted in this locus. Enhancer iii includes a significant excess of proliferation-altering enhancer disruptions. Bottom: H3K27ac signal profile (light blue), mammalian PhastCons elements (orange bars), and corresponding conserved regions that have either neutral effects (gray bars) or proliferation-decreasing phenotypes (dark blue bars) when disrupted in the screen are shown for enhancer iii. The signal track at the bottom displays normalized beta scores (gray) at 12 cell divisions averaged across a sliding window.

Figure 5.. Identifying target genes of enhancers contributing to hNSC proliferation using chromatin contact maps

(A) Chromatin contact maps of human neural precursor cells were used to identify interactions between enhancers and genes that, when disrupted, result in a proliferation phenotype. For each enhancer-gene pair, the absolute value of the gene proliferation score (x axis) and the absolute value of the strongest proliferation score within the enhancer (y axis) is shown. Highlighted genes have known roles in NSC biology or are associated with risk for developmental disorders. Interactions between HARs or HGEs and target genes are labeled in red. (B) An example of an enhancer (boxed) regulating a single target gene associated with microcephaly. Top: the genomic coordinates (in GRCh37/hg19) of the enhancer are shown relative to the two detected target genes. Chromatin contacts are shown as black arcs. Bottom: the effects of enhancer and target gene disruptions on hNSC proliferation at 4, 8, and 12 cell divisions. (C) An example of an enhancer (boxed) regulating multiple target genes with roles in hNSC proliferation (labeled as in B). (D) An example of a human gain enhancer (HGE; boxed) interacting with the nearby gene NSL1 (labeled as in B).

Figure 6.. Progenitor-type-specific expression of gene hits in the developing human cortex

(A) Left: UMAP representation of the developing human cortex single-cell gene expression atlas used for our analysis. Five cortical progenitor types are annotated: outer radial glia (ORG) cells in G1/S phase, intermediate progenitor cells (IPCs) in G1/S or G2/M phase, and radial glia (RG) in G1/S or G2/M phase. Right: heatmaps showing the average scaled expression for genes with proliferation phenotypes that exhibit progenitor-type-specific expression patterns. Three clusters are presented: one with genes showing ORG-biased expression (129 genes, cluster 2 in Table S13), one with genes showing G2/M-biased expression (145 genes, cluster 6 in Table S13), and one with genes showing IPC-biased expression (68 genes, cluster 1 in Table S13). The proliferation phenotype for each gene at 4, 8, and 12 cell divisions is shown above each heatmap. The inferred cell cycle phase for each progenitor cell type is shown on the right, as is the average expression of all genes in each cluster. See the legend at the bottom right for details. (B) Left: UMAP representation of cortical progenitors in the developing human cortex gene expression atlas with other cell types removed. Progenitor cell types and inferred cell cycle phases are labeled and colored as in (A). Right: UMAP representations displaying the scaled density of expression for individual genes in each cluster shown in (A).