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Region-specific expression of circular RNAs in the mouse brain
Accepted Manuscript Title: Region-specific expression of circular RNAs in the mouse brain Authors: Bei Jun Chen, Belinda Yang, Michael Janitz PII: DOI: Reference:
S0304-3940(17)30995-3 https://doi.org/10.1016/j.neulet.2017.12.022 NSL 33294
To appear in:
Neuroscience Letters
Received date: Revised date: Accepted date:
3-11-2017 4-12-2017 10-12-2017
Please cite this article as: Bei Jun Chen, Belinda Yang, Michael Janitz, Region-specific expression of circular RNAs in the mouse brain, Neuroscience Letters https://doi.org/10.1016/j.neulet.2017.12.022 This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.
Region-specific expression of circular RNAs in the mouse brain Bei Jun Chen1, Belinda Yang1, and Michael Janitz1,2# 1
School of Biotechnology and Biomolecular Sciences, University of New South Wales,
Sydney, NSW 2052, Australia 2
Paul-Flechsig-Institute for Brain Research, University of Leipzig, Leipzig, Germany
Highlights
Circular RNAs show distinct expression pattern in hippocampus and prefrontal cortex
CircRNAs are expressed independently from their linear RNA counterparts
CircRNAs are expressed more abundantly in the hippocampus
Specific hotspot genes express numerous circRNA isoforms in different brain regions
Abstract Circular RNAs (circRNAs) are abundant in mammalian brain and their expression is regulated in a tissue- and developmental stage-specific manner. Mammalian brain is the most transcriptionally complex organ. While many studies have extensively studied linear transcriptome and its biological functions in the brain, the circular transcriptome remains largely unexplored. This study focused on investigation of circRNA expression patterns in the mammalian brain regions critical for cognitive and memory functions and performed comparative analysis with the linear transcriptome. Altogether our study showed that circular and linear RNAs have independent expression patterns despite being derived from the same genomic locus, and that circular transcriptomes from different brain region have distinct characteristics in terms of transcript abundance and composition.
Introduction Circular RNA (circRNA) is widely present in the eukaryotic tree of life and has high diversity and expression across various mammalian tissues and cell types, particularly within the brain [1, 2]. Previously considered as splicing artefacts with no relevant biological function, circRNA was first observed in early 1990s [3, 4] and only recently recognized as an important molecule in the RNA world: a good body of evidence has shown that its expression is regulated in a tissue- and developmental stage-specific manner [5-7]. CircRNA is formed by a unique backsplicing event, during which the downstream 5’ splice site of an exon
1
covalently joins to the upstream 3’ splice site of either the same or another exon [8, 9]. Backsplicing results in the formation of a single-stranded loop structure that lacks a 5’ cap and a 3’ polyadenylated tail, which gives circRNA resistance to exonuclease degradation and consequently its high stability [10].
The hippocampus (HC) and prefrontal cortex (PFC) are brain regions involved in memory formation and learning in humans and other mammals [11-14]. The HC closely and functionally links to the PFC as they both contribute to memory storage, however the HC has a more specific role in long-term memory formation and learning whilst the PFC as a greater behavioural role [11-14]. Mouse model studies show that HC functions as an integrated base to coordinate interactions with other brain regions to generate and consolidate social recognition memory [15]. Moreover, the HC forms cohesive memories of individual events whilst linking it to the context of occurrence and these memories can then be retrieved by the PFC [16]. PFC is a highly evolved brain region that serves a role in cognitive control and behaviour as it directs a wide range of neural processes through its connections to other brain regions [17]. Within humans, the PFC is connected to the cortical and subcortical regions of the brain to assist in its executive functions of performing goal-directed patterns of behaviour [18].
Despite findings that circRNAs are abundant within the neuronal tissue and enriched in synapses [19], currently investigations of circular transcriptomes of the HC and PFC are lacking. Using a combined and paralleled computational pipeline (Figure S1), we assessed genome-wide expression of circRNAs in HC and PFC of the mouse brain and report here the specific circRNA expression patterns in these two brain regions. To our best knowledge this is the first paper reporting such findings.
Material and Methods
Material Previously published RNA-seq datasets (4 single-end read FASTQ files each for HC and PFC) used in this study were obtained from the GEO database with the accession number GSE61401 [20].
Methods 2
Figure S1 illustrates the experimental pipelines we used for computational analysis.
Linear transcriptome analysis: read mapping, transcript assembly, and differential testing A total of ~120 million reads from 8 samples including 4 from HC and 4 from PFC were analysed. Reads were first mapped to the mouse reference genome build mm10 (http://genome.ucsc.edu/cgi-bin/hgGateway?db=mm10) using TopHat with default parameters that allow a maximum mismatch number of 2 [21]. The aligned reads were then assembled into transcripts using Cufflinks [22], abundance was measured as Fragments Per Kilobase of transcripts per Million fragments mapped (FPKM) and normalized across all samples, using the gencode M13 annotation the assembly guide. Genes with FPKM ≥ 1 in at least one region were considered as expressed. Differential testing of gene expression in the two brain regions was carried out by Cuffdiff which calculated q values after false discovery correction based on the p values generated by t-test [23]. Changes in expression with a q value less than 0.05 were considered statistically significant.
Circular transcriptome analysis: read mapping, transcript assembly, and differential testing The same set of FASTQ files from the 8 samples described above were first mapped to the mouse reference genome mm10 using BWA MEM (http://bio-bwa.sourceforge.net/), only alignments with a score of at least 19 bp were reported. CircRNA detection and quantification were then performed using CIRI (version 2.05) which determines circRNAs by the presence of paired chiastic clipping signals where two segments of a junction read were mapped to the reference genome (mm10) in a reversed order [24, 25], using gencode M13 as the annotation reference. We used the Student t-test for gene expression differential testing, genes with p values less than 0.05 were reported as differentially expressed.
Pathway analysis of differentially expressed linear and circular RNAs An R package, ClusterProfiler [26], was used for pathway analysis for linear and circular transcriptomes. In both cases only annotated and differentially expressed genes were used as the input lists.
Expression profiling of human orthologues of the three differentially expressed mouse circRNAs
3
We used GTEx Portal (https://www.gtexportal.org/home/) to examine the expression of human orthologues for the three differentially expressed mouse circRNAs: RUNX1T1, PDE5A, and RTN4 amongst 53 various tissues from different regions of the human body.
Results Linear transcriptome profiles in HC and PFC Analysis of transcriptome profiles in hippocampus (HC) and prefrontal cortex (PFC) revealed the expression of 16,987 genes expressed across two regions (Table 1). Out of the 16,987 expressed genes, 948 (q < 0.05) genes were significantly differentially expressed across HC and PFC, encompassing 678 annotated protein-coding genes. The 948 differentially expressed genes are listed in Table S1. Pathway analysis revealed that enriched GO terms such as single-organism behaviour, regulation of system processes, learning or memory, cognition, and axon development were associated with differentially expressed linear RNAs (Figure S2).
Circular transcriptome profiles in HC and PFC Our computational pipeline discovered 1,809 and 1,097 circRNAs expressed by HC and PFC respectively. There were 2,459 circRNAs expressed across the two regions. As depicted in Table 1, 14.5% of all expressed genes in HC and PFC also produced circular transcripts. The majority of circRNAs were transcribed from exons of known genes, accounting for 89% of circRNAs found in HC and PFC (Figure 1). A small proportion of circRNAs aligned to introns and intergenic regions of the genome. Circular hotspots are genes that produce 10 or more circular isoforms per locus; there were two such hotspot genes discovered in the HC but not the PFC region: Thymoma viral proto-oncogene three (Akt3) and Arginine glutamic acid dipeptide repeats (Rere) produced 11 and 12 isoforms, respectively in HC transcriptome. The observed hotspot gene expression specificity for hippocampal tissue might be related to much higher overall number of circRNAs expressed in this brain region as compared to the prefrontal cortex. Secondly, distinct function of the hippocampus in the consolidation of information from short-term memory to long-term memory and in spatial memory might require more intensive generation of stable RNA molecules such as circRNAs. Most of the genes expressed a single circular transcript, independent of tissue origin (Figure 2). For differential testing, we used Student t-test which reported three differentially expressed circRNAs (p values < 0.05): Runt-related transcription factor 1 (Runx1t1), Phosphodiesterase 5a (Pde5a), and Reticulon 4 (Rtn4). The linear transcripts for these three genes were not 4
differentially expressed across the two regions. Table 2 lists the expression levels of linear and circular Runx1t1, Pde5a, and Rtn4 while Figure 3 presents the expression values in the boxplot format. For all three genes both linear and circular transcript expressions were higher in the PFC region. Enriched GO terms including dendrite development, regulation of cell morphogenesis, dendrite morphogenesis, synapse organization, axonogenesis, and axon development were found to be associated with circRNAs that showed dissimilar regulations in the two regions (Figure S2). Experimental validation, using RT-qPCR and independent RNA sample set, of the three differentially expressed circRNAs between hippocampus and frontal cortex corroborated outcomes of the RNA-Seq data analysis (Figure S3).
Expression profiling of human orthologues of the three differentially expressed mouse circRNAs The expression of RUNX1T1 is highest in the cerebellar hemisphere and cerebellum of the brain with a median RPKM of 13.7 and 10.2, respectively. In contrast, PDE5A shows the highest expression in the artery and esophagus tissues ranging from 21.4-25.6 RPKM with insignificant expressions in all 13 brain regions. RTN4 has the most abundant expression amongst brain regions with the highest median expression of 111.56 in the frontal cortex (Figure S4).
Discussion In the current study, we found that only 14.5% of linear RNA-expressing loci produced circular transcripts, revealing a lower abundance of circular transcriptome as compared to the linear transcriptome. Several studies have identified the low abundance of circRNAs encompassing 0.1% to 10% of linear RNAs [5, 27, 28]. In our case the higher ratio might be explained by circRNA’s high abundance within neuronal tissue [19]. We also observed an overall overexpression of circRNAs in the HC: when measured against the linear RNAs, 6.9% of genes expressed circRNAs in the PFC and 11.3% in HC. CircRNA is resistant to exonuclease degradation and could accumulate within non-proliferating cells and slower turnover rate neurons [27], therefore its overexpression in the HC may be related to latter’s function in learning and long-term memory formation.
Three circRNAs: Runx1t1, Pde5a, and Rtn4 displayed significant differential expression across HC and PFC regions while the changes of expression values in their linear counterparts remained insignificant. All of the three circRNAs had up-regulated expressions 5
in the PFC region. Furthermore, these three circRNAs exhibited more inter-individual variability when compared to the linear transcripts; the same pattern of heterogeneity in expression was also observed in our previous study of human brain [7]. Runx1t1 encodes Runt-related transcript factor 1, Runx1t1-knockdown study showed that it promotes neural differentiation of hippocampal neural stem cells (NSC); the number of NSCs differentiated into MAP-2 positive neurons correlated to the level of Runx1t1 expression [29]. In another study the up-regulation of RUNX1T1 was observed from Alzheimer’s brain samples in the HC region [30]. In addition, human RUNX1T1 has significantly enriched expression in the cerebellar hemisphere and cerebellum of the brain compared to other tissues (Figure S3), suggesting its possible brain-specific functions. The product of the Pde5a gene is a cGMPspecific phosphodiesterase. In animal Alzheimer’s model inhibition of Pde5a improved memory performance and cognitive functions while in dystropin-deficient mice inhibition of PDE5A restored their neurobehavioral social deficits [31, 32]. These studies showed that PDE5A exerts its effect in neurobiology possibly via its regulation of cGMPs which are widely distributed throughout the brain [31]. Rtn4 encodes a Nogo protein which is an inhibitor of axonal sprouting in adult CNS. Genetic deletion of Rtn4 inhibited supposedly aberrant neuritic sprouting in Alzheimer’s mice model and consequently ameliorated behavioral and neuropathological symptoms in the mice [33]. Altogether, studies have shown that these three genes that give rise to the differentially expressed circRNAs in our study are implicated in either hippocampal function or the neuropathology of Alzheimer’s disease, however the exact function and mechanism of action of these circRNAs need to be further investigated. Possible modes of action for these circRNAs might comprise interactions with proteins or other RNAs, such as microRNAs, leading to physical and functional depletion of the target molecules. Examples of such indirect mechanism of action have already been shown for several circRNAs (reviewed in [8]). Another functional relevance could stem from increased stability of circular transcripts, and their resistance to exonucleolytic hydrolysis, which can be important for long-term memory maintenance. Differentially expressed linear and circular RNAs were associated with different and unique GO terms for each region-specific transcriptome: while linear RNA had association with more general GO terms such as learning, memory, and cognition, circRNA were more related to neuronal-specific GO terms related to the physiology and development of neurons, specifically synapses and dendrites, possibly due to its enrichment in synapses [19, 34].
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In contrast with our previously published human study where more than 20 circular hotspot genes were discovered [7], in the current study only two such genes: Akt3 and Rere were identified in the HC samples and they both had lower numbers of linear isoforms. It has been proposed that two splicing mechanisms, executed by two separate sets of transcription factors, may regulate linear and circular RNA alternative splicing independently [35, 36]. Akt3 and Rere both participate in signalling pathways and may have brain-related functions. Akt3 encodes protein kinase B gamma, and disruption of Akt3 resulted in reduced brain volumes and higher seizure threshold in adult mice [37-39]. Interestingly, a specific missense mutation of Akt3 caused enlarged hippocampus and lowered seizure threshold in mice [39]. Rere encodes a nuclear receptor coregulator known as Atrophin 2 which has been found to regulate embryonic brain development [40]. Overall, the region-specific variation in circular transcript splicing of these two hotspot genes with established brain functions indicates that not only copy number, as observed in the three differentially expressed circRNAs, but also composition of circular transcripts are subject to tissue- or cell-specific regulation, further revealing the complexity of circular transcriptome regulation.
Conclusions In the current study we described characteristics of circular transcriptome in HC and PFC, identified three differentially expressed circRNAs: Runx1t1, Pde5a, and Rtn4, together with two hotspot genes: Akt3 and Rere. We showed that circular transcriptomes derived from HC and PFC have distinct patterns in terms of transcript copy number and composition. Future studies may address further characterization of specific circRNAs identified in this study, preferably through functional studies such as RNA interference or expression manipulation. With more defined molecular function, circRNAs have the great potential to serve as disease biomarkers or drug targets, especially in complex neurodegenerative diseases of the brain.
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Table 1: Metrics of transcriptomes in mouse hippocampus and prefrontal cortex. Region No. of circular RNAs No. of linear RNAs Percentage of expressed expressed expressed circular to linear RNAs Hippocampus 1,809 16,026 11.3 Prefrontal cortex 1,097 15,801 6.9 Combined 2,459 16,987 14.5 Table 2: Expression levels of linear and Circular Runx1t1, Pde5a, and Rtn4 Circular* Linear^ Gene # HC PFC log2FC p value HC PFC log2FC# p value Runx1t1 1.55 4.76 1.62 0.022 14.85 24.20 0.70 0.070 Pde5a 0.63 3.72 2.56 0.039 6.88 7.38 0.10 0.875 Rtn4 1.53 4.60 1.59 0.040 230.59 359.34 0.64 0.018 HC: Hippocampus; PFC: Prefrontal cortex; * : Expression level counted in Count Per Thousand (CPT); ^ : Expression level counted in Fragments Per Kilobase of transcripts per Million fragments mapped (FPKM); # : log2(fold change).
Figure 1: Distribution and classification of expressed circRNAs in the HC and PFC according to genomic origins.
Figure 2: Quantification of genes expressing a distinct number of circRNA isoforms.
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Figure 3: The expression patterns of differentially expression of (A) circRNAs and (B) their linear counterparts.
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S0304-3940(17)30995-3 https://doi.org/10.1016/j.neulet.2017.12.022 NSL 33294
To appear in:
Neuroscience Letters
Received date: Revised date: Accepted date:
3-11-2017 4-12-2017 10-12-2017
Please cite this article as: Bei Jun Chen, Belinda Yang, Michael Janitz, Region-specific expression of circular RNAs in the mouse brain, Neuroscience Letters https://doi.org/10.1016/j.neulet.2017.12.022 This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.
Region-specific expression of circular RNAs in the mouse brain Bei Jun Chen1, Belinda Yang1, and Michael Janitz1,2# 1
School of Biotechnology and Biomolecular Sciences, University of New South Wales,
Sydney, NSW 2052, Australia 2
Paul-Flechsig-Institute for Brain Research, University of Leipzig, Leipzig, Germany
Highlights
Circular RNAs show distinct expression pattern in hippocampus and prefrontal cortex
CircRNAs are expressed independently from their linear RNA counterparts
CircRNAs are expressed more abundantly in the hippocampus
Specific hotspot genes express numerous circRNA isoforms in different brain regions
Abstract Circular RNAs (circRNAs) are abundant in mammalian brain and their expression is regulated in a tissue- and developmental stage-specific manner. Mammalian brain is the most transcriptionally complex organ. While many studies have extensively studied linear transcriptome and its biological functions in the brain, the circular transcriptome remains largely unexplored. This study focused on investigation of circRNA expression patterns in the mammalian brain regions critical for cognitive and memory functions and performed comparative analysis with the linear transcriptome. Altogether our study showed that circular and linear RNAs have independent expression patterns despite being derived from the same genomic locus, and that circular transcriptomes from different brain region have distinct characteristics in terms of transcript abundance and composition.
Introduction Circular RNA (circRNA) is widely present in the eukaryotic tree of life and has high diversity and expression across various mammalian tissues and cell types, particularly within the brain [1, 2]. Previously considered as splicing artefacts with no relevant biological function, circRNA was first observed in early 1990s [3, 4] and only recently recognized as an important molecule in the RNA world: a good body of evidence has shown that its expression is regulated in a tissue- and developmental stage-specific manner [5-7]. CircRNA is formed by a unique backsplicing event, during which the downstream 5’ splice site of an exon
1
covalently joins to the upstream 3’ splice site of either the same or another exon [8, 9]. Backsplicing results in the formation of a single-stranded loop structure that lacks a 5’ cap and a 3’ polyadenylated tail, which gives circRNA resistance to exonuclease degradation and consequently its high stability [10].
The hippocampus (HC) and prefrontal cortex (PFC) are brain regions involved in memory formation and learning in humans and other mammals [11-14]. The HC closely and functionally links to the PFC as they both contribute to memory storage, however the HC has a more specific role in long-term memory formation and learning whilst the PFC as a greater behavioural role [11-14]. Mouse model studies show that HC functions as an integrated base to coordinate interactions with other brain regions to generate and consolidate social recognition memory [15]. Moreover, the HC forms cohesive memories of individual events whilst linking it to the context of occurrence and these memories can then be retrieved by the PFC [16]. PFC is a highly evolved brain region that serves a role in cognitive control and behaviour as it directs a wide range of neural processes through its connections to other brain regions [17]. Within humans, the PFC is connected to the cortical and subcortical regions of the brain to assist in its executive functions of performing goal-directed patterns of behaviour [18].
Despite findings that circRNAs are abundant within the neuronal tissue and enriched in synapses [19], currently investigations of circular transcriptomes of the HC and PFC are lacking. Using a combined and paralleled computational pipeline (Figure S1), we assessed genome-wide expression of circRNAs in HC and PFC of the mouse brain and report here the specific circRNA expression patterns in these two brain regions. To our best knowledge this is the first paper reporting such findings.
Material and Methods
Material Previously published RNA-seq datasets (4 single-end read FASTQ files each for HC and PFC) used in this study were obtained from the GEO database with the accession number GSE61401 [20].
Methods 2
Figure S1 illustrates the experimental pipelines we used for computational analysis.
Linear transcriptome analysis: read mapping, transcript assembly, and differential testing A total of ~120 million reads from 8 samples including 4 from HC and 4 from PFC were analysed. Reads were first mapped to the mouse reference genome build mm10 (http://genome.ucsc.edu/cgi-bin/hgGateway?db=mm10) using TopHat with default parameters that allow a maximum mismatch number of 2 [21]. The aligned reads were then assembled into transcripts using Cufflinks [22], abundance was measured as Fragments Per Kilobase of transcripts per Million fragments mapped (FPKM) and normalized across all samples, using the gencode M13 annotation the assembly guide. Genes with FPKM ≥ 1 in at least one region were considered as expressed. Differential testing of gene expression in the two brain regions was carried out by Cuffdiff which calculated q values after false discovery correction based on the p values generated by t-test [23]. Changes in expression with a q value less than 0.05 were considered statistically significant.
Circular transcriptome analysis: read mapping, transcript assembly, and differential testing The same set of FASTQ files from the 8 samples described above were first mapped to the mouse reference genome mm10 using BWA MEM (http://bio-bwa.sourceforge.net/), only alignments with a score of at least 19 bp were reported. CircRNA detection and quantification were then performed using CIRI (version 2.05) which determines circRNAs by the presence of paired chiastic clipping signals where two segments of a junction read were mapped to the reference genome (mm10) in a reversed order [24, 25], using gencode M13 as the annotation reference. We used the Student t-test for gene expression differential testing, genes with p values less than 0.05 were reported as differentially expressed.
Pathway analysis of differentially expressed linear and circular RNAs An R package, ClusterProfiler [26], was used for pathway analysis for linear and circular transcriptomes. In both cases only annotated and differentially expressed genes were used as the input lists.
Expression profiling of human orthologues of the three differentially expressed mouse circRNAs
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We used GTEx Portal (https://www.gtexportal.org/home/) to examine the expression of human orthologues for the three differentially expressed mouse circRNAs: RUNX1T1, PDE5A, and RTN4 amongst 53 various tissues from different regions of the human body.
Results Linear transcriptome profiles in HC and PFC Analysis of transcriptome profiles in hippocampus (HC) and prefrontal cortex (PFC) revealed the expression of 16,987 genes expressed across two regions (Table 1). Out of the 16,987 expressed genes, 948 (q < 0.05) genes were significantly differentially expressed across HC and PFC, encompassing 678 annotated protein-coding genes. The 948 differentially expressed genes are listed in Table S1. Pathway analysis revealed that enriched GO terms such as single-organism behaviour, regulation of system processes, learning or memory, cognition, and axon development were associated with differentially expressed linear RNAs (Figure S2).
Circular transcriptome profiles in HC and PFC Our computational pipeline discovered 1,809 and 1,097 circRNAs expressed by HC and PFC respectively. There were 2,459 circRNAs expressed across the two regions. As depicted in Table 1, 14.5% of all expressed genes in HC and PFC also produced circular transcripts. The majority of circRNAs were transcribed from exons of known genes, accounting for 89% of circRNAs found in HC and PFC (Figure 1). A small proportion of circRNAs aligned to introns and intergenic regions of the genome. Circular hotspots are genes that produce 10 or more circular isoforms per locus; there were two such hotspot genes discovered in the HC but not the PFC region: Thymoma viral proto-oncogene three (Akt3) and Arginine glutamic acid dipeptide repeats (Rere) produced 11 and 12 isoforms, respectively in HC transcriptome. The observed hotspot gene expression specificity for hippocampal tissue might be related to much higher overall number of circRNAs expressed in this brain region as compared to the prefrontal cortex. Secondly, distinct function of the hippocampus in the consolidation of information from short-term memory to long-term memory and in spatial memory might require more intensive generation of stable RNA molecules such as circRNAs. Most of the genes expressed a single circular transcript, independent of tissue origin (Figure 2). For differential testing, we used Student t-test which reported three differentially expressed circRNAs (p values < 0.05): Runt-related transcription factor 1 (Runx1t1), Phosphodiesterase 5a (Pde5a), and Reticulon 4 (Rtn4). The linear transcripts for these three genes were not 4
differentially expressed across the two regions. Table 2 lists the expression levels of linear and circular Runx1t1, Pde5a, and Rtn4 while Figure 3 presents the expression values in the boxplot format. For all three genes both linear and circular transcript expressions were higher in the PFC region. Enriched GO terms including dendrite development, regulation of cell morphogenesis, dendrite morphogenesis, synapse organization, axonogenesis, and axon development were found to be associated with circRNAs that showed dissimilar regulations in the two regions (Figure S2). Experimental validation, using RT-qPCR and independent RNA sample set, of the three differentially expressed circRNAs between hippocampus and frontal cortex corroborated outcomes of the RNA-Seq data analysis (Figure S3).
Expression profiling of human orthologues of the three differentially expressed mouse circRNAs The expression of RUNX1T1 is highest in the cerebellar hemisphere and cerebellum of the brain with a median RPKM of 13.7 and 10.2, respectively. In contrast, PDE5A shows the highest expression in the artery and esophagus tissues ranging from 21.4-25.6 RPKM with insignificant expressions in all 13 brain regions. RTN4 has the most abundant expression amongst brain regions with the highest median expression of 111.56 in the frontal cortex (Figure S4).
Discussion In the current study, we found that only 14.5% of linear RNA-expressing loci produced circular transcripts, revealing a lower abundance of circular transcriptome as compared to the linear transcriptome. Several studies have identified the low abundance of circRNAs encompassing 0.1% to 10% of linear RNAs [5, 27, 28]. In our case the higher ratio might be explained by circRNA’s high abundance within neuronal tissue [19]. We also observed an overall overexpression of circRNAs in the HC: when measured against the linear RNAs, 6.9% of genes expressed circRNAs in the PFC and 11.3% in HC. CircRNA is resistant to exonuclease degradation and could accumulate within non-proliferating cells and slower turnover rate neurons [27], therefore its overexpression in the HC may be related to latter’s function in learning and long-term memory formation.
Three circRNAs: Runx1t1, Pde5a, and Rtn4 displayed significant differential expression across HC and PFC regions while the changes of expression values in their linear counterparts remained insignificant. All of the three circRNAs had up-regulated expressions 5
in the PFC region. Furthermore, these three circRNAs exhibited more inter-individual variability when compared to the linear transcripts; the same pattern of heterogeneity in expression was also observed in our previous study of human brain [7]. Runx1t1 encodes Runt-related transcript factor 1, Runx1t1-knockdown study showed that it promotes neural differentiation of hippocampal neural stem cells (NSC); the number of NSCs differentiated into MAP-2 positive neurons correlated to the level of Runx1t1 expression [29]. In another study the up-regulation of RUNX1T1 was observed from Alzheimer’s brain samples in the HC region [30]. In addition, human RUNX1T1 has significantly enriched expression in the cerebellar hemisphere and cerebellum of the brain compared to other tissues (Figure S3), suggesting its possible brain-specific functions. The product of the Pde5a gene is a cGMPspecific phosphodiesterase. In animal Alzheimer’s model inhibition of Pde5a improved memory performance and cognitive functions while in dystropin-deficient mice inhibition of PDE5A restored their neurobehavioral social deficits [31, 32]. These studies showed that PDE5A exerts its effect in neurobiology possibly via its regulation of cGMPs which are widely distributed throughout the brain [31]. Rtn4 encodes a Nogo protein which is an inhibitor of axonal sprouting in adult CNS. Genetic deletion of Rtn4 inhibited supposedly aberrant neuritic sprouting in Alzheimer’s mice model and consequently ameliorated behavioral and neuropathological symptoms in the mice [33]. Altogether, studies have shown that these three genes that give rise to the differentially expressed circRNAs in our study are implicated in either hippocampal function or the neuropathology of Alzheimer’s disease, however the exact function and mechanism of action of these circRNAs need to be further investigated. Possible modes of action for these circRNAs might comprise interactions with proteins or other RNAs, such as microRNAs, leading to physical and functional depletion of the target molecules. Examples of such indirect mechanism of action have already been shown for several circRNAs (reviewed in [8]). Another functional relevance could stem from increased stability of circular transcripts, and their resistance to exonucleolytic hydrolysis, which can be important for long-term memory maintenance. Differentially expressed linear and circular RNAs were associated with different and unique GO terms for each region-specific transcriptome: while linear RNA had association with more general GO terms such as learning, memory, and cognition, circRNA were more related to neuronal-specific GO terms related to the physiology and development of neurons, specifically synapses and dendrites, possibly due to its enrichment in synapses [19, 34].
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In contrast with our previously published human study where more than 20 circular hotspot genes were discovered [7], in the current study only two such genes: Akt3 and Rere were identified in the HC samples and they both had lower numbers of linear isoforms. It has been proposed that two splicing mechanisms, executed by two separate sets of transcription factors, may regulate linear and circular RNA alternative splicing independently [35, 36]. Akt3 and Rere both participate in signalling pathways and may have brain-related functions. Akt3 encodes protein kinase B gamma, and disruption of Akt3 resulted in reduced brain volumes and higher seizure threshold in adult mice [37-39]. Interestingly, a specific missense mutation of Akt3 caused enlarged hippocampus and lowered seizure threshold in mice [39]. Rere encodes a nuclear receptor coregulator known as Atrophin 2 which has been found to regulate embryonic brain development [40]. Overall, the region-specific variation in circular transcript splicing of these two hotspot genes with established brain functions indicates that not only copy number, as observed in the three differentially expressed circRNAs, but also composition of circular transcripts are subject to tissue- or cell-specific regulation, further revealing the complexity of circular transcriptome regulation.
Conclusions In the current study we described characteristics of circular transcriptome in HC and PFC, identified three differentially expressed circRNAs: Runx1t1, Pde5a, and Rtn4, together with two hotspot genes: Akt3 and Rere. We showed that circular transcriptomes derived from HC and PFC have distinct patterns in terms of transcript copy number and composition. Future studies may address further characterization of specific circRNAs identified in this study, preferably through functional studies such as RNA interference or expression manipulation. With more defined molecular function, circRNAs have the great potential to serve as disease biomarkers or drug targets, especially in complex neurodegenerative diseases of the brain.
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Table 1: Metrics of transcriptomes in mouse hippocampus and prefrontal cortex. Region No. of circular RNAs No. of linear RNAs Percentage of expressed expressed expressed circular to linear RNAs Hippocampus 1,809 16,026 11.3 Prefrontal cortex 1,097 15,801 6.9 Combined 2,459 16,987 14.5 Table 2: Expression levels of linear and Circular Runx1t1, Pde5a, and Rtn4 Circular* Linear^ Gene # HC PFC log2FC p value HC PFC log2FC# p value Runx1t1 1.55 4.76 1.62 0.022 14.85 24.20 0.70 0.070 Pde5a 0.63 3.72 2.56 0.039 6.88 7.38 0.10 0.875 Rtn4 1.53 4.60 1.59 0.040 230.59 359.34 0.64 0.018 HC: Hippocampus; PFC: Prefrontal cortex; * : Expression level counted in Count Per Thousand (CPT); ^ : Expression level counted in Fragments Per Kilobase of transcripts per Million fragments mapped (FPKM); # : log2(fold change).
Figure 1: Distribution and classification of expressed circRNAs in the HC and PFC according to genomic origins.
Figure 2: Quantification of genes expressing a distinct number of circRNA isoforms.
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Figure 3: The expression patterns of differentially expression of (A) circRNAs and (B) their linear counterparts.
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