Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2023 Aug 28;3(9):100399.
doi: 10.1016/j.xgen.2023.100399. eCollection 2023 Sep 13.

Multiple genes in a single GWAS risk locus synergistically mediate aberrant synaptic development and function in human neurons

Affiliations

Multiple genes in a single GWAS risk locus synergistically mediate aberrant synaptic development and function in human neurons

Siwei Zhang et al. Cell Genom. .

Abstract

The mechanistic tie between genome-wide association study (GWAS)-implicated risk variants and disease-relevant cellular phenotypes remains largely unknown. Here, using human induced pluripotent stem cell (hiPSC)-derived neurons as a neurodevelopmental model, we identify multiple schizophrenia (SZ) risk variants that display allele-specific open chromatin (ASoC) and are likely to be functional. Editing the strongest ASoC SNP, rs2027349, near vacuolar protein sorting 45 homolog (VPS45) alters the expression of VPS45, lncRNA AC244033.2, and a distal gene, C1orf54. Notably, the transcriptomic changes in neurons are associated with SZ and other neuropsychiatric disorders. Neurons carrying the risk allele exhibit increased dendritic complexity and hyperactivity. Interestingly, individual/combinatorial gene knockdown shows that these genes alter cellular phenotypes in a non-additive synergistic manner. Our study reveals that multiple genes at a single GWAS risk locus mediate a compound effect on neural function, providing a mechanistic link between a non-coding risk variant and disease-related cellular phenotypes.

Keywords: CRISPR-Cas9 gene editing; CROP-seq; GWAS; Micro-C; allele-specific open chromatin; chromatin accessibility; common risk variants; human iPS cells; isogenic; neuron; neuropsychiatric disorders; noncoding variants; scRNA-seq; schizophrenia; synergistic.

PubMed Disclaimer

Conflict of interest statement

The authors declare no competing interests.

Figures

None
Graphical abstract
Figure 1
Figure 1
Allele-specific open chromatin (ASoC) mapping in NGN2-Glut identifies strong ASoC at the SZ-associated VPS45 locus (A) The strategy of generating NGN2-glutamatergic excitatory neurons from hiPSCs for bulk ATAC-seq and RNA-seq analysis. (B) Circus plot showing SZ-credible-risk SNPs that exhibited ASoC (FDR <0.05) in NGN2-Glut, iN-Glut, or both. (C) Allelic ratio correlation of SZ-associated ASoC SNPs (FDR <0.05) in iN-Glut and NGN2-Glut, n = 26. (D) Cell-type-specific and allele-specific ATAC-seq read pile-ups flanking ASoC SNP rs2027349 at the SZ-associated VPS45 locus. The top track shows the PGC3 SZ GWAS probabilities of all the SNPs in this region. Aquamarine, total reads that contain rs2027349; dark blue, reads containing reference allele (G); dark red, reads containing alternative allele (A).
Figure 2
Figure 2
Multiplex CRISPRi combined with scRNA-seq in NGN2-Glut identifies regulatory sequences flanking SZ-associated ASoC SNPs (A) Modified CROP-seq approach to screen cis-targets of the 20 SNP sites in NGN2-Glut. Two iPSC lines (CD0000009, CD0000011) were used. (B) Uniform Manifold Approximation and Projection (UMAP) plot showing the 11 clusters of the 10,247 cells used in the scRNA-seq analysis. (C) UMAP plot showing the normalized expression of MAP2. (D) UMAP plot showing the expression pattern of glutamatergic markers SLC17A7 (vGlut1) and SLC17A6 (vGlut2). (E) Violin plots showing expression of neuron-specific markers. (F) Gene track-expression plot showing the cis effects of CROP-seq gRNAs targeting rs2027349 (VPS45 site). ∗FDR <0.05. (G) Same as (F), but for three CROP-seq gRNAs targeting rs7148456 (BAG5 site). (H) UMAP plot showing cells assigned to one of the three VPS45 gRNAs (red) or control gRNAs (targeting GFP; blue). (I) The effects of VPS45 gRNAs on the expression level of VPS45. Kruskal-Wallis test (non-parametric) was used (shown are Dunn’s multiple comparisons adjusted p; ∗∗∗p < 0.001). (J) Top 10 enriched GO terms of genes up- or downregulated by ASoC-targeting gRNA-2 at the rs2027349 locus (VPS45). Red line, FDR 0.05.
Figure 3
Figure 3
CRISPR-Cas9 editing of rs2027349 in NGN2-Glut cis-regulates multiple genes and leads to disease-relevant transcriptomic changes (A) CRISPR-Cas9 editing of rs2027349, neuron differentiation, and experiment details. (B) cis effects of rs2027349 genotypes on local gene expression within a 500 kb window of rs2027349. The genotype (GG) was used as the baseline. Two or three clones per genotype of two iPSC lines were used. (C) Changing G to A (rs2027349) significantly increases the expression of VPS45 transcript ENST00000369130.3. Kruskal-Wallis (non-parametric) test; ∗∗∗p < 0.001. (D) Volcano plot showing differential expression of genes (n = 14,999) in NGN2-Glut after rs2027349 editing. Some DEGs (FDR <0.05) highlighted are also SZ-risk genes. The p values were derived from a combinational analysis of all three genotypes (AA, AG, and GG). −log2FC was between AA and GG neurons. (E) Sunburst plot showing strong enrichment of synapse-related ontology terms among the downregulated DEGs in AA neurons (SynGO31). (F) MAGMA gene-set GWAS enrichment analysis of DEGs for neuropsychiatric disorders/traits shows high SZ and neuroticism enrichment. (G) Upset plot showing the overlap of the DEGs from rs2027349 editing (AA vs. GG neurons) against a list of DEGs associated with five neuropsychiatric disorders in post-mortem brains. Red connections emphasize genes related to SZ. (H) An xy scatterplot showing the correlation of the log2FC of DEG sets in (G). Shown are corresponding ρ and p values.
Figure 4
Figure 4
CRISPR-Cas9 editing of rs2027349 at VPS45 locus alters neuron development in NGN2-Glut (A) Representative traces of dendrites from rs2027349 AA, AG, and GG neurons. Scale bar: 100 μm. (B) Sholl analysis of rs2027349 AA (n = 97), AG (n = 47), and GG (n = 101) neurons. Marked data points indicate significant distance differences between the AA and the GG genotypes (two-way repeated-measures ANOVA with Šídák multiple test correction). Data were from three independent experiments. (C) Representative images of GFP-labeled dendrites of NGN2-Glut neurons and synaptic puncta labeled with post-synaptic density 95 (PSD-95, DLG4) and Synapsin I (SYN1); scale bar: 5 μm. (D–F) Punctum density of PSD-95, SYN1, and PSD-95+/SYN1+, respectively. Each dot represents synaptic density from one neuron (AA, n = 77; GG, n = 75; AG, n = 39). Data were from two independent experiments (Kruskal-Wallis test, non-parametric); ∗p < 0.05; ∗∗p < 0.01; ∗∗∗∗p < 0.0001. Data were from two clones per genotype of donor line CD0000011. Consistent results for the second donor (CD0000012) are shown in Figure S6.
Figure 5
Figure 5
CRISPR-Cas9 editing of rs2027349 alters neural network and electrophysiological activity in NGN2-Glut (A and B) Example raster plots of neuronal firing events in MEA. (C and D) Mean firing rate and burst numbers in day 50, 53, and 56 NGN2-Glut with different rs2027349 genotypes from two independent experiments. Each point represents one replicate. Kruskal-Wallis (non-parametric) test; ∗∗∗p < 0.001. (E) Representative two-photon pseudo-color Ca2+ imaging time-series images showing a neuron and its firing activities in a 275 s span; scale bar: 20 μm. (F and G) Representative neuron firing signals from five cells of genotype AA (F) or GG (G). (H–J) Ca2+ transient frequency and amplitudes in AA (n = 124) and GG (n = 166) neurons from two independent experiments. (H) Cumulative probability plot of Ca2+ transient interevent intervals (IEIs) in AA and GG neurons, two-sample KS test, two-tailed; p < 0.001. (I) Violin and boxplot showing the distribution of Ca2+ transient frequency in AA and GG neurons. Yellow point indicates the mean. Student’s t test (non-parametric, two-tailed); ∗∗∗p < 0.001. (J) Violin and boxplot showing the amplitude (dF/F0) distribution in AA and GG neurons. Yellow point indicates the mean. Student’s t test (non-parametric, two-tailed); ∗p < 0.05. Data were obtained from two clones per genotype of donor line CD0000011. Consistent results for the second donor (CD0000012) are shown in Figure S6.
Figure 6
Figure 6
VPS45, AC244033.2 (lncRNA), and C1orf54 interactively altered neural phenotypes in NGN2-Glut at the rs2027349 locus (A–C) Box-whisker plots showing that shRNA-mediated single and triple KD in AA neurons reversed the gene expression patterns to GG neurons. GAPDH was the endogenous control for normalization in qPCR assay. AA_EGFP_KD was used as the control for all. Saltire mark indicates the mean. Kruskal-Wallis test (non-parametric). For individual KD, two clones per donor line (CD0000011) and three biological replicates per clone were used. For triple KD, three biological replicates from one clone were used. (D) Sholl analysis of individual KDs; refer to Figure S7B for statistics. Two clones per genotype from two independent experiments were used. (E) Calcium imaging analysis of neuron firing frequency for gene KD. Kruskal-Wallis (non-parametric) test with Dunn’s multiple comparisons and adjusted p values. n = 181, 245, 229, 276, and 152 neurons. One or two clones per genotype from two independent experiments were used. ∗∗∗∗p < 0.0001. (F) Hierarchical clustering of log2FC for neurodevelopmental genes downregulated in rs2027349-edited GG neurons and their expression changes in each shRNA KD in AA neurons. (G) Enrichment of the up-/downregulated genes in each shRNA KD in AA neurons among the neurodevelopmental (i.e., neuron differentiation related) genes downregulated in rs2027349-edited GG neurons. (H) Same as (F), using synaptic genes upregulated in GG neurons. (I) Same as (G), examining the enrichment among synaptic genes upregulated in GG neurons. In (G) and (I), Fisher’s exact test (two-tailed) was used to estimate the enrichment; OR, odds ratio, ∗∗∗p < 0.001. (J) Summary of the correlations from linear regression model fitting. Whiskers, ±95% CI; fill, −log10p. (K) Pie chart showing the number and proportions of genes in each synergistic category in the combinatorial vs. the additive model. (L) Competitive GSEA of DEGs in “more upregulated” (more.up) and “more downregulated” (more.down) categories based on 698 curated neural gene sets and stratified by eight neural categories. (M and N) Bar plots of overrepresentation analysis in (L) using a hypergeometric test of the gene sets at FDR <0.05 and ranked by FDR value. Red lines, FDR 0.05.
Figure 7
Figure 7
Long-range chromatin interactions and changes in local chromatin accessibility contribute to the cis effect of rs2027349 on multiple genes (A) ATAC-seq and Capture Hi-C data from human brain tissue and Micro-C data from NGN2-Glut neurons. Orange arcs show the multiple long-range interactions between the rs2027349 locus and several high-accessibility sites (ATAC-seq peaks) in proximity. Bold arcs (red in hippocampal DG neurons and blue in NGN2-Glut neurons) indicate the site-specific interaction between rs2027349 and the promoter region of C1orf54. (B) CRISPR-Cas9 editing of rs2027349 altered both local and remote chromatin accessibility. Note the higher regional OCR peaks (normalized pile-up intensity) on the rs2027349 locus and regions proximal to the C1orf54 gene in AA neurons. ATAC-seq data were from two clones per genotype of line CD0000011.

References

    1. GTEx Consortium The GTEx Consortium atlas of genetic regulatory effects across human tissues. Science. 2020;369:1318–1330. doi: 10.1126/science.aaz1776. - DOI - PMC - PubMed
    1. Demontis D., Walters R.K., Martin J., Mattheisen M., Als T.D., Agerbo E., Baldursson G., Belliveau R., Bybjerg-Grauholm J., Bækvad-Hansen M., et al. Discovery of the first genome-wide significant risk loci for attention deficit/hyperactivity disorder. Nat. Genet. 2019;51:63–75. doi: 10.1038/s41588-018-0269-7. - DOI - PMC - PubMed
    1. Grove J., Ripke S., Als T.D., Mattheisen M., Walters R.K., Won H., Pallesen J., Agerbo E., Andreassen O.A., Anney R., et al. Identification of common genetic risk variants for autism spectrum disorder. Nat. Genet. 2019;51:431–444. doi: 10.1038/s41588-019-0344-8. - DOI - PMC - PubMed
    1. Howard D.M., Adams M.J., Clarke T.K., Hafferty J.D., Gibson J., Shirali M., Coleman J.R.I., Hagenaars S.P., Ward J., Wigmore E.M., et al. Genome-wide meta-analysis of depression identifies 102 independent variants and highlights the importance of the prefrontal brain regions. Nat. Neurosci. 2019;22:343–352. doi: 10.1038/s41593-018-0326-7. - DOI - PMC - PubMed
    1. Mullins N., Forstner A.J., O'Connell K.S., Coombes B., Coleman J.R.I., Qiao Z., Als T.D., Bigdeli T.B., Børte S., Bryois J., et al. Genome-wide association study of more than 40,000 bipolar disorder cases provides new insights into the underlying biology. Nat. Genet. 2021;53:817–829. doi: 10.1038/s41588-021-00857-4. - DOI - PMC - PubMed

LinkOut - more resources