Circular RNAs in the human brain are tailored to neuron identity and neuropsychiatric disease

Little is known about circular RNAs (circRNAs) in specific brain cells and human neuropsychiatric disease. Here, we systematically identified over 11,039 circRNAs expressed in vulnerable dopamine and pyramidal neurons laser-captured from 190 human brains and non-neuronal cells using ultra-deep, total RNA sequencing. 1,526 and 3,308 circRNAs were custom-tailored to the cell identity of dopamine and pyramidal neurons and enriched in synapse pathways. 88% of Parkinson’s and 80% of Alzheimer’s disease-associated genes produced circRNAs. circDNAJC6, produced from a juvenile-onset Parkinson’s gene, was already dysregulated during prodromal, onset stages of common Parkinson’s disease neuropathology. Globally, addiction-associated genes preferentially produced circRNAs in dopamine neurons, autism-associated genes in pyramidal neurons, and cancers in non-neuronal cells. This study shows that circular RNAs in the human brain are tailored to neuron identity and implicate circRNA-regulated synaptic specialization in neuropsychiatric diseases.

followed by RNAseq (see Method and Supplementary Table 2).RNase R is a 3′ to 5′ exoribonuclease that digests all linear RNAs (including the tail of intron lariats), but not circular RNA structures 12,24 .
Paired RNase R treated and untreated RNAseq experiments were performed in six independent samples (see Method and Supplementary Fig. 2a).We rigorously required at least 20 unique reads per circular RNA in RNase R treated samples with at least two-fold enrichment compared to untreated samples in at least one pair (Supplementary Fig. 2a).Overall, out of the 111,419 circRNAs discovered in brain neurons, 11,039 met our stringent validation criteria; 48.0% of exon-derived circRNAs (e.g., 10,845 out of 22,593) and 0.22% of circular intronic RNAs (ciRNAs; 194 out of 88,826).These circRNAs were conservatively used for downstream analysis (Fig. 1a, validated circular RNAs in brain neurons).98.2% of the confirmed circular RNAs were exon-derived circRNAs, suggesting that our filtering strategy effectively removed false-positive or lowly expressed circular RNAs (e.g., intron lariats from splicing 25 ; Supplementary Fig. 2b-c).In total, we detected 6,699, 8,381, and 1,263 circRNAs in dopamine neurons, pyramidal neurons, and Betz cells, respectively (Fig. 1b).Genomic characteristics of circRNAs in the brain.We observed that many genes transcribe multiple (up to 36) neuronal circRNAs (Fig. 1c).For example, the AD-associated gene PICALM produces 25 distinct circular RNA isoforms (Supplementary Fig. 2d).The number of circular RNAs per gene was linearly correlated with the number of exons of the host gene (Supplementary Fig. 2e).Circularized exons were significantly longer than the average exons in the human genome (Supplementary Fig. 2e), and had significantly less overlapping RNA binding protein (RBP) binding activity (using ENCODE eCLIP data 26 ) than non-circularized exons (Fig. 1d).Similarly, the introns flanking circRNAs were longer and harbored more repetitive elements compared to the introns flanking non-circularized exons (Fig. 1e-f, see Methods).The host genes generating circRNAs are relatively more conserved (Fig. 1g).

Dopamine and pyramidal neurons express cell type-specific circRNAs in human brain.
To delineate circRNAs specifically expressed in each cell type, we further calculated the cell-specificity score of each circRNA based on the Jensen-Shannon distance of its expression profile similar as in Ref. 23 .
CircRNAs with a specificity score S ≥ 0.5 and mean expression > mean+s.d. of overall expression were defined as cell type-specific (see Methods).We focused our analysis of cell type-specificity on the control samples (i.e., 59 dopamine neuron samples, 43 pyramidal neuron samples, and 7 non-neuronal samples; excluding disease samples) to avoid confounding by disease state-driven changes.We identified 1,526, 3,308, and 4,860 circRNAs preferential expressed in dopamine neurons, pyramidal neurons, and non-neuronal cells, respectively (left panel of Fig. 2a, Supplementary Table 3).Cell type-preferential expression of five dopamine neuron-specific, five pyramidal neuron-specific, and one non-neuronspecific circRNA was confirmed in an independent set of substantia nigra and temporal cortex samples (e.g., the source regions for laser-captured dopamine and pyramidal neurons, respectively) using RNase R treatment and qPCR (Supplementary Fig. 3a).In total, 17 of 24 (70.8%)selected circRNAs showed consistent expression between preferential cell types and the source regions (Supplementary Table 4).
Circular RNAs rather than the linear RNAs expressed from 3,532 loci defined cell diversity and identity.3,532 genetic loci custom-tailored 1,526 cell type-specific circRNAs to the cell identity of dopamine neurons, 3,308 circRNAs to pyramidal neurons, and 4,860 cell type-specific circRNAs to nonneuronal cells, respectively (i.e., cell specificity score S < 0.5 and mean expression > mean + s.d.).Fig. 2a,b; Supplementary Table 3).Surprisingly, the expression profiles of linear RNAs (e.g., mRNAs and long non-coding RNAs) transcribed from these same loci did not meet criteria for cell-type specificity (Fig. 2c) (i.e., S ≥ 0.5 and mean expression > mean + s.d.) and cell-specificity scores of the linear transcripts were significantly lower than that of circRNAs (Fig. 2d).We observed the same trend even only considering the host gene with single circRNA (Supplementary Fig. 3c).Cell type-specificity of circRNAs was not explained by linear mRNA abundance from the corresponding loci.The abundance of total linear reads (i.e., spliced + unspliced reads) surrounding the back-splicing site only weakly correlated with the abundance of their associated circular reads (Spearman's rho = 0.10, see Supplementary Fig. 2f for detail).Interestingly, the circular-to-linear ratios of circRNAs were significantly higher in neurons vs. non-neuronal cells (Mann-Whitney test, P < 2.2 × 10 -16 , Fig. 2e).More research is needed to clarify whether this is modulated by distinct mechanisms regulating biogenesis, stability, and turnover of the circular RNAs, of their linear cognates, or both [27][28][29] .Interestingly, our data (Fig. 2a) suggest two types of cell type-specific circRNAs.First, some genetic host loci focus production of cell type-specific circRNAs onto a singular specific cell type (one locus producing one or more cell type-specific circRNAs specific to the same one cell type): These loci turn on circRNA production in one cell type and turn it off in the others e.g., 345 loci produce 400 circRNAs exclusively in dopamine neurons, 730 loci expressed 1,046 circRNAs exclusively in pyramidal neurons, and 1,191 loci expressed 2,222 circRNAs exclusively in non-neuronal cells.Second, some loci precisely tailor the production of cell type-specific circRNAs for multiple cell types (e.g., via alternative back-splicing or combinations of different sets of exons) to the requirements of multiple types of cells (one locus producing multiple cell type-specific circRNA for multiple cell types).Indeed, 306 super-host loci (Fig. 2a) tailored a diverse circRNAs portfolio specifically to dopamine neurons, pyramidal neurons, and non-neuronal cells via alternative back-splicing.These 306 super host loci expressed 478 distinct dopamine neuron-specific, 751 pyramidal neuron-specific, and 988 non-neuronal circRNA back-spliced variants (see Fig. 2a).RNA Binding Protein activity superimposed from the ENCODE eCLIP track 26 highlighted subsets of RBPs statistically associated with these types of cell type-specific circRNAs (Supplementary Fig. 4).These super-host loci included the LKS/RAB6-interacting/CAST family member 1 (ERC1) locus.ERC1 binds to the PD-linked RIM proteins 30,31 , to facilitate the docking of synaptic vesicles at the presynaptic active zone.The ERC1 locus expresses two distinct circRNAs, which we termed circERC1-1 and circERC1-2, where circERC1-1 is circularized between exon 16 and exon 19 and circERC1-2 is alternatively backspliced between exon 17 and exon 19 (see Fig. 2f).circERC1-1 was preferentially expressed in dopamine neurons (Fig. 2f-g); circERC1-2 was preferentially expressed in pyramidal neurons; neither was expressed in non-neuronal cells.Cell type-specific divergence of circERC1-1 and circERC1-2 was supported by qPCR with RNase R (Fig. 2g).circERC1-1 abundance was higher in substantia nigra (the region containing dopamine neurons) compared to the temporal cortex (the region containing pyramidal neurons).Neither was meaningfully expressed in non-neuronal cells, e.g., fibroblasts and white blood cells.
Thus, circRNA diversity provides finely tuned, cell type-specific information that is not explained by the corresponding linear RNAs from the same loci.
circRNAs are predominantly expressed from synapse machinery (Fig. 3).Unbiased pathway analysis of host loci revealed that cell type-specific neuronal circRNA production was clustered around synapse function and neuronal projection loci (Fig. 3), while in non-neuronal cells circRNA production clustered around cell cycle loci (Fig. 3).Thus, the host genes producing cell type-specific circRNAs in dopamine neurons vs. pyramidal neurons are actually representing similar synapse and neuronal projection-related pathways.While it is reasonable to infer clues for candidate pathway membership from host gene enrichment analyses, careful experimental evaluation of individual circRNAs per se will be needed to substantiate their mechanistic roles in synapse specialization and disease.See Supplementary Table 5 for full list of enriched functional terms.
Unbiased enrichment analysis using the gene-disease annotations defined in DisGeNET 35 (updated for PD and AD GWAS-implicated susceptibility genes from Refs. 30 , 32 ) showed that 20 neuropsychiatric diseases were statistically significantly enriched in circRNA loci compared to only three non-CNS diseases (Fig. 4c, Supplementary Fig. 2g, Supplementary Table 6) out of a total of 4,638 human diseases and traits.Enrichment analysis showed a diverse spectrum of links between cellular circRNA loci and disease.PD-and intellectual disability-associated loci were enriched in circRNAs expressed in all three cell types (Fig. 4c).Examples of such loci include circRNAs from KANSL1 gene (Fig. 4d), which was linked to PD by us 18 and others 36 as well as to neurodevelopmental disorders 37,38 .
The enrichment of PD in circRNA-producing loci from all cell types is consistent with the increasingly appreciated roles of cortical neurons 31 and immune cells 39,40 in the pathobiology of PD, beyond classic dopaminergic neurodegeneration.Ten addiction traits related to drug and substance abuse were enriched in circRNAs active in dopamine neurons (see an example of circRNAs from addiction-related genes PDE4B 41,42 and FTO 41,43 in Fig. 4e and Supplementary Fig. 5).Autism and bipolar disease were enriched in circRNA loci actively expressed in pyramidal neurons.By contrast, the oncologic diseases leukemia and adenocarcinoma of the large intestine were enriched in circRNAs specific to non-neuronal cells (see an example of circRNAs from the cancer-associated gene ATM 44 in Fig. 4f).Surprisingly, atrial fibrillation, a common cardiac arrhythmia, was enriched in circRNA loci active in pyramidal neurons pointing to a potential role of synaptic plasticity in cardiac innervation 45 .
We confirmed and evaluated circRNA expression from two of the implicated familial disease loci ---DNAJC6 and PSEN1 ---using a second method, qPCR with RNase R treatment.circPSEN1-2 is one of several circRNAs back-spliced from 4 exons of the familial AD gene PSEN1 (Supplementary Figs. 3, 4).It was highly expressed in brain neurons with over 100 unique back-splice junction reads.qPCR confirmed that circPSEN1 is >20-fold enriched in both temporal cortex and substantia nigra after RNase R treatment (Supplementary Fig. 3).
DNAJC6 plays a key role in uncoating the clathrin-coated synaptic vesicles 49 .circDNAJC6 produced from the locus was expressed highly in dopamine neurons, moderately in pyramidal neurons, but not in non-neuronal by lcRNAseq.Consistent with this, qPCR and RNase R treatment confirmed high expression in the substantia nigra, moderate expression in the temporal cortex, and minimal expression in the non-neuronal cells (Supplementary Fig. 3).Functionally, expression of circDNAJC6 and several other synapse-related circRNAs (labeled in orange in Fig. 4g) was altered at the earliest, prodromal Parkinson's disease stages in brainstem-confined Lewy body Braak stages 1-3 (P = 0.014 by Wald test, with covariates of sex, age, PMI, and RIN adjusted, Fig. 4g, Supplementary Table 7).By contrast, expression of the linear mRNA DNAJC6 was not affected (right panel of Fig. 4g).
We also explored whether circRNAs expression changes during with disease progression.In PDvulnerable dopamine neurons from 95 brains (with available neuropathology stages), 26 circRNAs (including DNAJC6) showed suggestive associations with progressive alpha-synuclein-positive Lewy body burden ---spanning brainstem-predominant, midbrain, and cortical stages of PD (e.g., based on the Unified Lewy Body Staging System 50 of 0, I, IIa, III, and IV, see Supplementary Table S1).

Discussion
Human brain cells custom tailor thousands of circRNAs to fit their cell identity.For many loci, which lacked diversity in linear mRNA expression, the corresponding "companion" circRNAs were cell type specific.Dopamine and pyramidal neurons prominently expressed circRNAs from synapse genes and non-neuronal cells prominently produced circRNAs from loci involved in cell cycle regulation.
The sheer number and diversity of circRNAs add a new class of components to the growing inventory of non-coding RNAs actively expressed in the human brain disease 18,51,52 , including enhancer RNAs 18 , microRNAs 33 , and long-non-coding RNAs 51 .Indeed, there is reason to hypothesize that this expanding regulatory network of non-coding RNAs may be a major contributor to the exceptional diversity and performance of human brain cells that cannot be explained by the surprisingly small number of protein-coding genes in the human genome which are similar in humans and worms 52 .The fact that circRNAs are predominantly expressed from synapse loci in human dopamine and pyramidal neurons raises the possibility that they encode as yet unknow important functions in synaptic functions of the human neuronal networks controlling quintessential human experiences: fine motor movements, motivation, reward, and higher cortical functions.This expands on a postulated role for circRNAs in synaptosomes 4,5 and synaptic plasticity 4 in animals.What could that function be?It could be regulation of transcription consistent with the literature 2,4,25,53,54 .Alternatively, circRNAs ---similar to some linear RNAs ---might be targeted to the synapse as local regulatory switches that control the translation or assembly of highly specialized synaptic machinery for each type of neuron 55 .Their circular conformation may confer functional advantages (e.g., longer half-life) or suit transport along axons.
Importantly, 61% of all synaptic circRNAs were linked to brain disorders.Synaptic dysfunction -----synaptopathy ---may be one of the earliest defects in these neurodegenerative and neuropsychiatric diseases [56][57][58][59][60][61] .For example, in both toxic and genetic animal models of PD, synaptic plasticity is disrupted during the early phases of dopaminergic dysfunction, much earlier than nigral cell death and the clinical manifestation of motor features 57 .Disease-linked circRNAs expression showed, in part, evidence of cell type bias: Addiction-associated genes prominently express circRNAs in dopamine neurons, autism genes express circRNAs predominantly in pyramidal neurons, and interestingly, PD GWAS-associated loci express circRNAs highly in non-neuronal cells as well as in neurons.Based on these and prior data 4,5,8,11,62 , we hypothesize that circRNAs may serve as finely tuned, special purpose RNA vehicles for the assembly of cell type-specific synapses and that their dysregulation may contribute to synaptopathies.
The mechanisms controlling the biogenesis of cell type-specific circRNAs could involve subsets of RNA binding proteins (e.g.8][29] and Supplementary Fig. 4).Much more work will be required to fully elucidate the kinetics and relation of circular and cognate linear RNA biogenesis, the involved regulators, and to reveal how this complex RNA machinery specifies neuron identity and synapses.
More generally, this study provides a unique catalog of circRNAs in two major types of human brain neurons that will be generally useful for decoding genome function in neuropsychiatric disease and for advancing the burgeoning field of RNA medicines and diagnostics [63][64][65] .scientific collaborator or on scientific advisory boards for Sanofi, Berg Health, Pfizer, Biogen, and has received grants from NIH, U.S. Department of Defense, APDA, ASAP, and MJFF.X.D. has received funding from NIH, APDA, and ASAP.The other authors declare no competing financial interests.f. circERC1-1 was preferentially expressed in dopamine neurons; circERC1-2 was preferentially expressed in pyramidal neurons; neither was expressed in non-neuronal cells.The genomic region visualized in the figure corresponds to chr12:1399017-1519619 (hg19), which comprises exons 16 to 19 of the ERC1 gene transcript ENST00000542302.g.Consistently, qPCR with RNase R indicated that circERC1-1 abundance was higher in substantia nigra (SN, the region containing dopamine neurons) compared to the temporal cortex (TC, the region containing pyramidal neurons), where circERC1-2 was higher in the temporal cortex.Neither was meaningfully expressed in non-neuronal cells, e.g., fibroblasts (FB) and white blood cells (PBMC).ERC1 mRNA is actually expressed higher in the non-neuronal cells than in the neuronal cells.N = 3 replicates were analyzed per sample.treatment and mock treatment RNAs were purified using RNeasy MinElute Cleanup kit (QIAGEN), an estimate of 15ng RNA was yielded after RNase R digestion (estimated and cannot be measured).Before the RNA-seq library preparation, about 10 ng of each the RNase digested and mock RNA samples were liner amplified to get enough amount of double-stranded cDNA with Ovation RNA-Seq System V2 kit (NuGen) according to the manufacture's instruction.After the linear amplification, ~600ng doublestranded cDNA samples were sonicated and applied to prepare the sequencing library using TruSeq RNA sample Preparation v2 kit (Illumina) following the manufacturer's instructions.Detailed characteristics of the samples used for RNase R experiment are shown in Supplementary Table 2.

RNA sequencing data analysis pipeline
RNA-seq raw files in FASTQ format were processed in a customized pipeline.For each sample, we first filtered out reads that failed vendor check or are too short (<15nt) after removing the low-quality ends or possible adaptor contamination by using fastq-mcf with options of "-t 0 -x 10 -l 15 -w 4 -q 10 -u".We then checked the quality using FastQC and generated k-mer profile using kpal 73 for the remaining reads.Reads were then mapped to the human genome (GRCh37/hg19) using Tophat 74 (v2.0.8) by allowing up to 2 mismatches and 100 multiple hits.Reads mapped to ribosomal RNAs or to the mitochondrial genome were excluded from downstream analysis.Gene expression levels were quantified using FPKM (Fragments Per Kilobase of transcript per Million mapped reads).Only uniquely mapped reads were used to estimate FPKM.To calculate normalized FPKM, we first ran Cuffquant 75 (v2.2.1) with default arguments for genes annotated in GENCODE (v19), and then ran Cuffnorm with parameters of "-total-hits-norm -library-norm-method quartile" on the CBX files generated from Cuffquant.

Sample QC based on RNA-seq data
We performed sample QC similar to 't Hoen PA et al. 76 .In brief, we ran k-mer profiling for filtered reads using kpal 73 and calculated the median profile distance for each sample.Samples with distances clearly different from the rest samples were marked as outliers (Supplementary Fig. 1c).We also calculated pair-wise Spearman correlations of gene expression quantification across samples and measured the outlier via hierarchical clustering (Supplementary Fig. 1b).Moreover, we tested for concordance between reported clinical sex and sex indicated by the expression of the female-specific XIST gene and male-specific Y-chromosome gene RPS4Y1 (Supplementary Fig. 1d).Samples from the first batch with a relatively low sequencing depth were also excluded.In addition to these samples used for cell typespecific transcriptome analyses, various additional control samples were analyzed (e.g., amplification controls, tissue homogenate), and technical replicates (Supplementary Fig. 1e).In the end, 197 out of 221 samples passed QC and are used for downstream analysis (Supplementary Fig. 1a).

Calling circular RNAs
We first extracted the chimerically aligned RNAseq reads using Tophat-fusion 21 and then called circRNAs using circExplorer (v2.0) 22 .CircExplorer has been reviewed with the best overall performance in balance of precision and sensitivity 19,20 .To identify circRNAs that are not back-spliced from a canonical exon border, we ran circExplorer2 with a customized gene annotation file and the "--lowconfidence" option.As in ref. 23 , circRNAs with at least two unique back-spliced reads in overall samples are categorized as "being expressed" and kept as circRNA candidates.CircRNA expression is quantified by normalized reads per million (RPM) at the back-splicing sites for each sample.

Cell specificity
The specificity score S is defined as  !,# = 1 − ( !,  + # ), where JSD is the Jensen-Shannon distance,  ! is the expression profile of a given circRNA c expressed as a density of ( + 1) , and  + # is the unit vector of 'perfect expression' in a particular cell type i (e.g.[1, 0, 0, 0, 0] for i=1).Like the ref. 23, a circRNA is defined as cell-type specific if its specificity score S ≥ 0.5 and mean expression in a cell type is larger than the mean + one standard deviation (s.d.) of overall expression.

circRNA-producing gene function enrichment analysis
Functional enrichment analysis of circRNA host genes was performed using the C5 gene sets (GO terms) implemented in the MSigDB database (version v7.2) using Fisher's exact test.Each gene set contains genes annotated to the same GO term.For each gene set, the Fisher's exact test was performed for k, K, N -K, n; where k is the number of circRNA host genes that are part of a GO term gene set; K is the total number of genes annotated to the same GO term gene set; N is the total number of all annotated human genes in GENCODE (v19); and n is the number of genes in the query set.The top 10 GO terms in each GO category (BP, MF, and CC) enriched in these circRNA host genes are further slimmed using a similar algorithm as the clusterProfile package 77 .The slimmed results are shown in Supplementary Table 5 (all with an FDR q value < 0.05).
We also evaluated whether there is a specific enrichment among circRNAs in genes associated with brain disorders.We used diseases in MeSH C10 (Nervous System Diseases) or F03 (Mental Disorders) for brain disorders, and associated diseases to genes using GenDisNet database.The diseasegene association was extracted from DisGeNet 78 (http://www.disgenet.org/)filtered with GDA score > 0.1.For all annotated protein-coding genes, we performed Fisher's exact test based on whether a gene is associated with a brain disorder and a gene hosts a circRNA (Supplementary Table 6).

AD and PD risk genes
The GWAS-derived AD risk genes we used in this study were extracted from Jansen et al. 32 , where they defined AD potential causal genes with four gene-mapping strategies (nearest, eQTL, chromatin interaction, and GWGAS).Gene symbols were extracted from their Table S13 and S18 and there are 217 uniquely mapped genes.The GWAS-derived PD risk genes we used in this study were extracted from Nalls et al. 30 , where they defined PD potential causal genes based on nearest position and QTL.Gene symbols were extracted from their Table S2 and there are 109 uniquely mapped genes.

Differentially expressed circRNAs
Similar to Dube et al. 8 , we first aggregated all circular RNA reads count from one gene into a gene-based count matrix, and then used that count matrix as input to perform differential expression analysis using the DEseq2 79 framework.Covariates of sex, age, PMI (post-mortem interval), and RIN (RNA integrity number) were included in the negative binomial (NB) based generalized linear model, and P values from the Wald test with covariates adjusted were reported.

Confirming circRNA expression by qPCR
Quantitative PCR was performed using SYBR Green Master Mix (Thermo Fisher) on an ABI 7900HT instrument (Applied Biosystems).The divergent primer pairs flanking the back-splice sit are designed using Prime3 online primer design web tool (http://bioinfo.ut.ee/primer3-0.4.0/primer3/) and shown in Supplementary Table 4.To confirm the expression of lcRNAseq-derived circRNAs in dopamine neurons and pyramidal neurons, relative abundances of target circRNAs were evaluated by qPCR in human substantia nigra or temporal cortex samples, as well as in human fibroblast and PBMC samples (shown in Supplementary Fig. 3).The human ubiquitin gene UBC was used as a reference to normalize RNA loading.Control samples lacking template and those lacking reverse transcriptase showed virtually no expression of these target circRNAs indicating that DNA contamination did not materially influence results.Expression values were analyzed using the comparative threshold cycle method 63 .All the quantitative PCR reactions were conducted in triplicate.Equal amplification efficiencies for target and reference transcripts were confirmed using melting curve analysis.

Figure Figure 1 .
Figure

Figure 2 .
Figure 2. Cell type-specificity of circular and linear transcripts diverges in human brain cells.a.The alluvial plot visualizes 3,532 genetic loci that custom-tailored cell type-specific circRNAs to the cell identity of dopamine neurons (DA), pyramidal neurons (PY), and non-neuronal cells (NN), respectively (i.e., cell specificity score S < 0.5 and mean expression > mean + s.d.).b,c.Expression heatmaps of cell type-specific circRNAs (b) and linear RNAs (c; e.g.mRNAs) from the corresponding loci in dopamine neurons (DA), pyramidal neurons of the temporal cortex (TCPY), pyramidal neurons of the motor cortex (MCPY), as well as peripheral blood mononuclear white blood cells (PBMC), and fibroblast (FB).Cell

Figure 3 .
Figure 3. circRNAs are predominantly expressed from synapse machinery.Unbiased pathway analysis of revealed that neuronal circRNA production was clustered around synapse function and neuronal projection loci, while in non-neuronal cells circRNA production clustered around cell cycle loci.Enriched Gene Ontology terms for the host genes of circRNAs specifically expressed in each cell type are shown.

Figure 4 .
Figure 4. CircRNAs are linked to neuropsychiatric disease.a. Histogram summarizing the number of circRNAs (y-axis) supported by increasing numbers of back-spliced reads (x-axis).Pie charts show the proportion of PD-risk genes (green), AD-risk genes (cyan), and synaptic genes (orange) expressing circRNAs.Examples of circRNAs for each of these three categories (colored dots) are highlighted.b.The AD GWAS locus PICALM produced 16 circRNAs in pyramidal neurons, 17 in dopamine neurons, and 12 in non-neuronal cells.c.Genes for addiction-associated traits (magenta font) preferentially produced circRNAs in dopamine neurons, autism-and bipolar-disease-associated genes (cyan font)