Multi-omic profiling of the developing human cerebral cortex at the single-cell level

Presenter:Cynthia Soto
Lieber Nov 6th, 2024

Human brain development spans from early embryogenesis through young adulthood, involving complex molecular changes as neurons differentiate, migrate, and form networks.
Disruptions to these processes by environmental or genetic factors may lead to neuropsychiatric disorders, necessitating a comprehensive view of developmental risk across all stages.
Prior studies have explored gene expression and epigenetic changes separately, this study combines single-cell gene expression and chromatin accessibility profiling across 45,549 cells at multiple developmental stages.

Background: Briefly introduce the significance of the human brain’s cellular complexity and the role of gene expression in development.

Role of CREs: Explain what cis-regulatory elements are and why their spatiotemporal activity is crucial for gene expression regulation during brain development.

Transcript

1. Multi-omic profiling of the developing human cerebral cortex at the single-cell level Cynthia S Cardinault Nov 06th, 2024 — Multiome meetings —
3. Background: Briefly introduce the significance of the human brain’s cellular complexity and the role of gene expression in development. Role of CREs: Explain what cis-regulatory elements are and why their spatiotemporal activity is crucial for gene expression regulation during brain development. Human brain development spans from early embryogenesis through young adulthood, involving complex molecular changes as neurons differentiate, migrate, and form networks. Disruptions to these processes by environmental or genetic factors may lead to neuropsychiatric disorders, necessitating a comprehensive view of developmental risk across all stages. Prior studies have explored gene expression and epigenetic changes separately, this study combines single-cell gene expression and chromatin accessibility profiling across 45,549 cells at multiple developmental stages. Introduction
4. Fig. 1. Joint single-cell profiling of RNA expression and chromatin accessibility of human neocortex Multi-omic profiling confirmed accurate cell type identification, validated by mixed-species samples where human and mouse cell reads were distinctly separated, ensuring reliable paired profiles. Simultaneously profiled gene expression and chromatin accessibility in 45,549 cortical nuclei across six broad developmental time points from fetus to adult.
5. From 45K (15%) of 53K cells met quality control and filtering criteria. (MGE)–derived and caudal ganglionic eminence (CGE)–derived inhibitory neuron subtypes were not distinguished in ATAC Various stromal cell types with smaller population sizes, including endothelial cells, pericytes, and vascular smooth muscle cells (VSMCs), were blended together in ATAC RNA showed insufficient power to identify progenitor cells, 20% fewer detected radial glia (RG) and intermediate progenitor cells (IPCs) Fig. 1. Joint single-cell profiling of RNA expression and chromatin accessibility of human neocortex
6. Independent RNA-seq and ATAC-seq clustering both identified major neocortical cell types with high congruence (ARI = 0.78). However, ATAC-seq better distinguished progenitor cell types (IPC), while RNA-seq lacked resolution for some cell types, like radial glia. Fig. 1. Joint single-cell profiling of RNA expression and chromatin accessibility of human neocortex
7. Results derived from joint analysis identified every cell type that was found in either single omic analyses while not losing power for detection of neural progenitors. 1736 by joint analysis versus 1743 by ATAC-seq alone versus 1427 by RNA-seq alone identified 28 clusters grouped into 15 cell types unaffected by donor or technical factors Found that most of the neural progenitors (91%), including the transient cell types of RG and IPCs, were only detected in the two early fetal samples. Fig. 1. Joint single-cell profiling of RNA expression and chromatin accessibility of human neocortex
8. Found 3 excitatory neuron (SATB2, SLC17A7, and NEUROD2) and 3 inhibitory neuron (GAD1 and GAD2), representing distinct fetal and postnatal stages Major glial cell types—OPCs, astrocytes, oligodendrocytes, microglia—and vascular cells like endothelial cells, pericytes, and VSMCs, were consistent with known developmental distinctions WNN identified 28 clusters grouped into 15 cell types unaffected by donor or technical factors Neural progenitor cells (NPCs) expressing PAX6 were distinguished into radial glia (RG) and intermediate progenitor cells (IPCs). Dot plot showing selected marker gene expression and chromatin-derived gene activity across cell types Fig. 1. Joint single-cell profiling of RNA expression and chromatin accessibility of human neocortex
9. GWAs approach found that over 80% of gene expression variance was linked to promoter and enhancer regions, indicating a strong association between transcriptional heterogeneity and chromatin dynamics. 56 genes for which >60% of the expression variance could be best explained by the inter–age group covariance. influence of promoter and enhancer adjusted for donor and age The pairwise relationships between NFR and gene expression led to identified 7291 significant peak-gene associations [within ±500 kb around TSSs], involving 3082 unique genes. As expected, these associations were enriched in the vicinity of TSSs, and the correlations decayed exponentially with distance. Fig. 2. Global and local characterization of cis regulation patterns.
10. Only 22% of the peak-gene links occur between an ATAC-seq peak and the nearest gene,indicating that most predicted regulatory interactions skip at least one gene along the linear genome. A subset of genes were associated with a relatively large number of peaks, suggesting orchestrated coregulation of the target gene activity by multiple factors that act upon a broad chromatin domain. Identified 364 domains of regulatory chromatin (DORCs) in which there are at least five significant peak-gene links associated with the same gene. “super-enhancers” Fig. 2. Global and local characterization of cis regulation patterns.
11. left: aggregated peak accessibility, right: linked gene expression) in the DORCs across 500 pseudobulk Validate the cell type specificity of DORC-gene links. GO analysis of the genes involved in the top decile of the peak-gene correlations in DORCs revealed strong enrichment of developmental processes in both neurons and glia Fig. 2. Global and local characterization of cis regulation patterns.
12. Developmental dynamics of gene regulation throughout corticogenesis and neuron differentiation 3A, 3B. Pseudotime trajectory analysis on various neuronal subtypes, with the radial glia (RG) cluster as the starting point. The respective cell counts for each lineage were: 14,146 for EN (posnatal samples) 5,728 for IN-MGE (inhibitory neurons) 4,904 for IN-CGE Trajectories corresponding to their developmental stages fetal neuronal populations mature postnatal neurons excitatory neuron (EN) inhibitory neuron (IN) progenitors Given the potentially tight regulation of DORC target genes during lineage commitment, they explored whether chromatin accessibility at DORCs precedes gene expression. Defined 55 neuron-specific DORCs (associated with at least five peaks). Residuals positive (46) across lineages reflected the lineage priming of cis-regulator y elements. Fig. 3. Trajectories of gene regulation during neuronal development.
13. deeper analysis into the peak-gene links on the EN lineage, including RG and IPC Found that the expression levels of over 87% of the linked genes (811 of 930) varied significantly along the pseudotime trajectory for the EN (posnatal) lineage. Grouped these genes into four clusters using k-means (km), each one corresponding to a different developmental period. Rows (genes) are clustered using k-means clustering (k = 4), and columns (cells) are ordered by pseudotime. The top 5 most differentially expressed genes in each cluster (km1/2/3/4) were annotated. gene expression DORC of peak-gene link Fig. 3. Trajectories of gene regulation during neuronal development. Km1 (beginning of the trajectory) Km2 (next early fetal period) Km3 (late fetal) Km4 (posnatal)
14. (E) Gene ontology analysis highlighted distinct biological activities at each stage: Km1 (beginning of the trajectory): cell fate specification, timing regulation of cell differentiation, and neural precursor cell proliferation. Km2 (next early fetal period): neuron migration, morphogenesis, synapse organization, and axonogenesis. Km3 (late fetal) and Km4) postnatal stages: excitatory neurons acquired the ability for neurotransmitter transport and regulation, indicating cell maturation. (G) Dynamic regulatory activities during the developmental transition of cell lineages is highly defined by the spatiotemporal patterning of TFs. Performed TF motif enrichment analysis in the different clusters Found TF motifs with an established function in cell differentiation and development enriched in the corresponding stages. Associated peak-gene links were enriched in motifs of neuronal TFs as NEUROD1, NEUROG2, and BHLHE22 Suggesting that the most active neurogenesis processes occur during these particular developmental periods. Fig. 3. Trajectories of gene regulation during neuronal development.
15. Cut-like homeobox 2 (CUX2) was identified as a neuron-specific DORC gene, regulated by the highest number (n = 21) of nearby putative enhancers (Fig. 3C), and as a marker for the second earliest stage in the EN (posnatal) lineage. (F) The binding motif for the TF NEUROD1 was strongly enriched in km2 chromatin accessible regions, and NEUROD1 activity was highly correlated with the CUX2 DORC chromatin accessibility state TF motif enrichment in km2 peaks plotted against Spearman correlation of TF motif activity with CUX2 DORC score Fig. 3. Trajectories of gene regulation during neuronal development.
16. Validate the predicted causal relationship between NEUROD1 and CUX2 by performing CRISPRi in cultured NPCs followed by RNAscope to directly image mRNAs in single cells Negative control experiment, in which cells were treated with a scrambled gRNA Quantified the frequency distribution of fluorescent dots per nucleus for both genes at week 2 after differentiation Found that NEUROD1 expression is more variable than CUX2 across the population, as measured by the fano factor. Inactivation of NEUROD 1 inactivation of CUX2 Fig. 4. Assessment of the relationship between NEUROD1 and CUX2 in differentiating NPCs.
17. (A) Significant colocalization of GWAS-derived common genetic variants with cell-specific open chromatin regions in snATAC-seq data and cell marker genes in snRNA-seq data. (B) Comparison between fetal and adult neuronal signals in selected neuropsychiatric disorders C) Subset of candidate causal genes for risk variants that either are prioritized in two disorders or show significantly altered expression along the developmental trajectory of the neuronal lineage Fig. 5. Mapping of risk variants associated with neuropsychiatric traits to causal genes using single cell–derived marker genes and peaks
18. ( C ) Nominate the candidate functional genes for disease-associated loci: 1) collected a set of 491 genome-wide significant variants associated with neuropsychiatric traits. 2) overlapped putative disease-relevant variants with the significant peak-gene associations 3) Found 97 loci, 7 linked to two disease traits simultaneously and 17 genes shown significant altered expression along the pseudotime trajectories. DCLK3 gene is predicted to be the causal gene for SCZ and BD GWAS risk variants (rs75968099 and rs75968099). Fig. 5. Mapping of risk variants associated with neuropsychiatric traits to causal genes using single cell–derived marker genes and peaks
19. Simultaneously profiled gene expression and chromatin accessibility in 45,549 cortical nuclei across six broad developmental time points from fetus to adult. The study found that in certain cell types, chromatin accessibility is closely linked to gene expression, forming specific regulatory patterns. During cell differentiation, chromatin at regulatory elements becomes accessible before genes are actively transcribed, indicating that these chromatin changes play a crucial role in guiding cells toward neuronal identities. The study mapped genetic loci linked to neuropsychiatric traits, specific to cell types and developmental stages, highlighting how gene regulation during brain development may influence neuropsychiatric disease. Summary