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. 2020 Mar;30(3):375-391.
doi: 10.1101/gr.255463.119. Epub 2020 Mar 3.

Genome-wide, Integrative Analysis of Circular RNA Dysregulation and the Corresponding Circular RNA-microRNA-mRNA Regulatory Axes in Autism

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Free PMC article

Genome-wide, Integrative Analysis of Circular RNA Dysregulation and the Corresponding Circular RNA-microRNA-mRNA Regulatory Axes in Autism

Yen-Ju Chen et al. Genome Res. .
Free PMC article

Abstract

Circular RNAs (circRNAs), a class of long noncoding RNAs, are known to be enriched in mammalian neural tissues. Although a wide range of dysregulation of gene expression in autism spectrum disorder (ASD) have been reported, the role of circRNAs in ASD remains largely unknown. Here, we performed genome-wide circRNA expression profiling in postmortem brains from individuals with ASD and controls and identified 60 circRNAs and three coregulated modules that were perturbed in ASD. By integrating circRNA, microRNA, and mRNA dysregulation data derived from the same cortex samples, we identified 8170 ASD-associated circRNA-microRNA-mRNA interactions. Putative targets of the axes were enriched for ASD risk genes and genes encoding inhibitory postsynaptic density (PSD) proteins, but not for genes implicated in monogenetic forms of other brain disorders or genes encoding excitatory PSD proteins. This reflects the previous observation that ASD-derived organoids show overproduction of inhibitory neurons. We further confirmed that some ASD risk genes (NLGN1, STAG1, HSD11B1, VIP, and UBA6) were regulated by an up-regulated circRNA (circARID1A) via sponging a down-regulated microRNA (miR-204-3p) in human neuronal cells. Particularly, alteration of NLGN1 expression is known to affect the dynamic processes of memory consolidation and strengthening. To the best of our knowledge, this is the first systems-level view of circRNA regulatory networks in ASD cortex samples. We provided a rich set of ASD-associated circRNA candidates and the corresponding circRNA-microRNA-mRNA axes, particularly those involving ASD risk genes. Our findings thus support a role for circRNA dysregulation and the corresponding circRNA-microRNA-mRNA axes in ASD pathophysiology.

Figures

Figure 1.
Figure 1.
Identification of DE-circRNAs in the ASD cortex samples. (A) Comparison of normalized numbers of circRNAs in ASD and non-ASD control samples from different brain regions: (FC) frontal cortex, (TC) temporal cortex, (CV) cerebellar vermis. P-values were determined using two-tailed Wilcoxon rank-sum test. (B) Flowchart of the overall approach. To minimize potentially spurious events, only the circRNAs (1060 circRNAs) that were detected to be expressed in >50% of the samples examined are considered for the following analyses. (C) Comparisons of the 1060 circRNAs and the human/mouse circRNAs collected in well-known databases (i.e., circBase/CIRCpedia). (D) Principal component plots of circRNA expression profiles of the 1060 circRNAs in samples from FC, TC, and CV. (PC1/PC2) First and second principal components. (E) circRNA expression fold changes (>0 if higher in ASD; <0 if lower in ASD) between ASD and non-ASD control cortex samples, plotted against the percentile rank of mean expression levels of the 1060 circRNAs across 134 cortex samples used for differential expression analysis. The identified up-regulated (22) and down-regulated (38) circRNAs in the ASD cortex samples (LME model, P < 0.05 and |log2(fold change)| ≥ 0.5) are highlighted in red and green, respectively. (F) Comparison of circRNA expression fold changes in the FC and TC samples. The black line represents the regression line between fold changes in the FC and TC for the 60 DE-circRNAs. The Pearson correlation coefficient (R) and P-value are shown. (G) Comparison of circRNA expression fold changes in a small number of samples and all 134 samples combined: (left) samples with no Chromosome 15q11-13 duplication syndrome; (middle) samples with RIN ≥ 5; (right) samples with PMI ≤ 30 h). The black lines represent the regression lines between fold changes in the corresponding small number of samples and all samples combined for the 60 DE-circRNAs. (H) PCA based on the 60 DE-circRNAs. (I) Dendrogram representing hierarchical clustering of 134 cortex samples based on the 60 identified DE-circRNAs. Information on diagnosis, age, brain bank, PMI, brain region, sex, and RIN is indicated with color bars below the dendrogram according to the legend on the right. Heat map on the bottom represents scaled expression levels (color-coded according to the legend below the heat map) for the 60 DE-circRNAs.
Figure 2.
Figure 2.
Dysregulation of circRNA coexpression networks in ASD cortex. (A) Dendrogram of circRNA coexpression modules defined in 134 cortex samples. Consensus module color bar shows assignment based on 1000 rounds of bootstrapping. Diagnosis and potential confounders (age, sex, region, RIN) are treated as numeric variables to calculate their Pearson correlation coefficients with expression level for each circRNA. (B) Pearson's correlation between distinct covariates and module eigengenes in 134 cortex samples. (C) circRNAs are plotted according to their circRNA expression correlations; the circRNAs in violet and darkred modules are all plotted, but the circRNAs in the turquoise module are plotted with only kME ≥ 0.5 due to the sizable number of circRNAs. Node size is proportional to connectivity, and edge thickness is proportional to the absolute correlation between two circRNAs. (D,E) Module preservation defined in ASD samples only in non-ASD samples (CTL samples) (D, left), CTL samples only in ASD samples (D, right), TC samples only in FC samples (E, left), or FC samples only in TC samples (E, right).
Figure 3.
Figure 3.
Identification of ASD-associated circRNA-miRNA-mRNA regulatory interactions based on the 73 cortex samples overlapped with the samples examined in a previous miRNA study (Wu et al. 2016). (A) Schematic diagram representing the ASD-associated circRNA-miRNA-mRNA axes that satisfied our criteria (see the text). “−” represents the negative correlation between the expression of circRNAs and miRNAs and between the expression of miRNAs and mRNAs. “+” represents the positive correlation between the expression of circRNAs and mRNAs. The correlations are performed by Spearman's correlation tests. (B,C) Enrichment analyses of phenotype ontology (B) and 14 groups of gene list (C) among the target genes of the identified ASD-associated circRNA-miRNA-mRNA axes. The red dashed lines represent FDR Bonferroni-corrected P-values for enrichments with FDR < 0.05. For C, the P-values of gene enrichment analyses are determined using two-tailed Fisher's exact test (left) and empirical gene enrichment analysis (right), respectively. Top SFARI genes represent the genes with top ASD genetic risk factors from the SFARI database (score = 1–3 and syndromic). For the left panel, the enrichment odds ratios with FDR < 0.05 are provided in parentheses. For the right panel, the arrow represents FDR Bonferroni-corrected P-values for enrichments with FDR < 0.05. (D) The four categories of up-regulated (top) and down-regulated (bottom) circRNA-involved ASD-associated circRNA-miRNA-mRNA interactions. The Venn diagrams represent the overlap between the four categories of interactions, on which the numbers represent the numbers of target genes and the numbers of the corresponding circRNA-miRNA-mRNA interactions are shown in parentheses. A summary table representing the total number of interactions for each category is also provided (bottom right). (E) The 356 up-regulated circRNA-involved circRNA-miRNA-mRNA interactions plotted by the Cytoscape package.
Figure 4.
Figure 4.
Experimental validation of the back-spliced junction of an up-regulated circRNA (circARID1A) and the corresponding circRNA-miRNA regulatory axis. (A) Validation of the NCL junction of circARID1A. (Top and middle) The schematic diagrams displaying seven predicted target sites of one single down-regulated miRNA (miR-204-3p) on the circle of circARID1A (top) and the designed divergent primers around the NCL junction of circARID1A (middle). (Bottom) Comparisons of two different RTase products (MMLV- and AMV-derived products) of circARID1A in TC/FC samples and four types of neuronal cell lines (hNPC [or ReN], NHA, SH-SY5Y, and U118), followed by Sanger sequencing the RT-PCR amplicons for the NCL event in the TC. (ReN) ReNcell VM. (B) Experimental validation of the circRNA (or back-spliced) junction of circARID1A. The figure shows the expression fold changes (as determined by qRT-PCR) for circARID1A, ARID1A mRNA, and GAPDH (negative control) in the indicated tissues/cell lines before and after RNase R treatment. (C) Experimental examination of the evolutionary conservation of circARID1A across the brains of vertebrate species from primates to chicken. Comparison of MMLV- and AMV-derived-RTase products (left) and the corresponding sequence chromatograms (right) for the circARID1A event in the brains of the indicated six species are shown. (D) Comparison of the expression profiles of circARID1A and its corresponding colinear mRNA counterpart in 10 normal human tissues. The expression levels of brain are used to normalize the relative expression values of the other tissues. (E) The relative expression of circARID1A and its corresponding colinear mRNA counterpart in 10 normal human tissues. (F) qRT-PCR analysis of the subcellular fractionation location for circARID1A and ARID1A mRNA. GAPDH and RNU6-1 snRNA are examined as a cytosol marker and a nucleus marker, respectively. The expression levels in nucleus are used to normalize the relative expression values in cytoplasm. (G,H) qRT-PCR analyses of the correlations between the expression of circARID1A and miR-204-3p after circARID1A knockdown (G) or overexpression (H) in various human neuronal cell lines. The top panels of G and H represent that circARID1A knockdown (G) or overexpression (H) did not significantly affect the ARID1A mRNA expression. (I) Luciferase reporter assay for the luciferase activity of GLuc-circARID1A in ReN, NHA, SH-SY5Y, and U118 cells transfected with miR-204-3p mimic and a scramble mimic (the negative control) to validate the binding between circARID1A and miR-204-3p. The entire circle sequence of circARID1A was cloned into the downstream region of the GLuc gene (i.e., GLuc-circARID1A; top). The luciferase activity of GLuc was normalized with secreted alkaline phosphatase (SEAP). (J) qRT-PCR analysis of the expression level of circARID1A in ReN and NHA cells after transfection with scramble and miR-204-3p mimics: (NC) negative control; (KD) knockdown; (OE) overexpression. All the qRT-PCR data are the means ±SD of three experiments. P-values are determined using two-tailed t-test. Significance: (*) P-value < 0.05; (***) P-value < 0.001; (NS) not significant.
Figure 5.
Figure 5.
Experimental validation of the circARID1A regulatory role of miR-204-3p sponges and the corresponding circRNA-miRNA-mRNA regulatory interactions. (A) Schematic diagram representing the circARID1A-miR-204-3p regulatory axis and its corresponding targets (171 genes, including 12 ASD risk genes, two FMR1 targets, 102 ELAVL1 targets, and five RBFOX1 targets). (BD) Microarray analysis of the target mRNA log2(fold change) in response to circARID1A knockdown, circARID1A overexpression, and miR-204-3p overexpression, respectively. (B) Distribution of the target mRNA log2(fold change) in response to circARID1A knockdown, circARID1A overexpression, and miR-204-3p overexpression. P-values are determined using one-tailed (circARID1A knockdown vs. circARID1A overexpression and circARID1A overexpression vs. miR-204-3p overexpression) or two-tailed (circARID1A knockdown vs. miR-204-3p overexpression) t-test. Significance: (*) P-value < 0.05; (**) P-value < 0.01; (NS) not significant. (C) The correlations between mRNA fold changes after circARID1A knockdown, circARID1A overexpression, and miR-204-3p overexpression. The Pearson correlation coefficient (R) and P-value are shown. (D) Heat map of the 12 ASD risk mRNA log2(fold change) in response to circARID1A knockdown, circARID1A overexpression, and miR-204-3p overexpression, respectively. The gene symbols highlighted in blue represent that the genes are also ELAVL1 targets. (E) qRT-PCR analyses of ASD risk gene expression in NHAs (top) and hNPCs (ReN cells) (bottom) after circARID1A knockdown, miR-204-3p mimics, and miR-204-3p mimics with circARID1A expression vector (p-circARID1A), respectively. (NC) Negative control. P-values are determined using two-tailed t-test. Significance: (*) P-value < 0.05; (**) P-value < 0.01; (***) P-value < 0.001. (F) Imaging of immunostained ReN cells after 2 wk of differentiation. Immunostaining shows undifferentiated (top) and differentiated (bottom) ReN cells with the cell proliferation marker MKI67 (left), the neuronal marker TUBB3 (middle), and the mature glial cell marker GFAP (right). Nuclei are stained with DAPI (blue). (Scale bar) 100 μm; (GFAP) glial fibrillary acidic protein. (G) Relative expression of circARID1A and two ASD risk genes (NLGN1 and STAG1) during hNPC differentiation. The Pearson correlation coefficients (R) between the expression of circARID1A and the two ASD risk genes and P-values are shown in parentheses. All the qRT-PCR data are the means ±SD of three experiments.

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