- Background: Circular RNAs (circRNAs) are a novel class of endogenous, non-coding RNAs that form covalently closed continuous loops and that are both highly conserved and abundant in the mammalian brain. - A role for circRNAs in sponging microRNAs (miRNAs) has been proposed, but the circRNA-miRNA-mRNA interaction networks in human brain cells have not been defined. - Given the putative miRNA regulatory function of circRNAs, we identified potential miRNA targets of circRNAs, and further, delineated circRNA-miRNA-mRNA networks using in silico methods. - Pathway analysis of the genes regulated by these miRNAs identified significantly enriched immune response pathways, which is consistent with the known function of astrocytes as immune sensors in the brain.. - Conclusions: In this study, we performed circRNA detection on cell-specific transcriptomic data and identified potential circRNA-miRNA-mRNA regulatory networks in PC astrocytes. - While we did not detect recurrent differentially expressed circRNAs in the context of healthy controls or AD, we report for the first time circRNAs and their potential regulatory impact in a cell-specific and region-specific manner in aged subjects. - These predicted regulatory network and pathway analyses may help provide new insights into transcriptional regulation in the brain.. - Though RNA circularization events were reported in the 1970s and 1990s [4–6], they were disregarded as molecular artifacts arising from aberrant splicing. - Furthermore, circRNAs are highly abundant in the mammalian brain, compared to other tissues such as lungs, heart, kidney, testis and spleen in humans, as well as in mouse neuronal cell lines [8], and are derived preferen- tially from neural genes [9].. - Given these data, it is likely that circRNAs regulate RNA and protein networks, especially in the brain, but the regulatory pathways are still unknown.. - In the present study, we characterized the expression and abundance of circRNAs in next generation RNA sequencing (RNAseq) data of human brain astrocytes. - Astrocytes, the most abundant glial cells, play several essential roles in the central nervous system, including homeostasis [19], immun- ity [20] and energy storage and metabolism [21, 22]. - Given the potential miRNA regulatory function of circRNAs, we then performed in silico identification of miRNA binding sites on the de- tected circRNAs, and further delineated putative circRNA- miRNA-mRNA networks in astrocytes. - Among the detected circRNA candidates, a total of 2331 cir- cRNAs were identified in the AD samples and 2425 in the ND samples by at least one of the algorithms (Fig. - Further- more, 548 circRNAs detected in our dataset were also re- ported in the four studies deposited in circBase [27]. - MiRNA target prediction and delineation of circRNA- miRNA-mRNA regulatory networks. - These interactions represent binding sites for miR- NAs on each circRNA candidate, predicted based on com- plementarity in the miRNA seed region (nucleotide positions 2–7 in the miRNA 5′-end). - 2398 miRNAs in the reference set were predicted to have binding sites in our input list of circRNAs. - Among these, a set of 612 circRNA-miRNA interaction pairs were predicted to contain over 100 putative interaction sites by the miRanda algorithm (Additional file 4: Table S3). - These 612 circRNA- miRNA interactions were predicted for six unique circRNAs and 448 unique miRNAs. - Using this information about miRNA target mRNAs, we delineated a putative low- stringency circRNA-miRNA-mRNA network consisting of ten circRNAs, 53 miRNAs and 255 genes (Additional file 6:. - Further, we used the same list of circRNAs de- tected in ten or more samples by at least one of the circRNA prediction algorithms, and increased the fil- tering stringency criteria to include circRNA-miRNA interactions with a miRanda match score >. - Using this strategy, we established a high-stringency circRNA-miRNA-mRNA interaction net- work with four circRNAs, 11 miRNAs and 49 genes (Fig. - This identification of impacted immune response pathways is consistent with the known function of astrocytes as immune sensors in the brain and aligns with our previous RNAseq study, which showed that im- mune system response pathways are impacted in AD PC. - hsa-miR-3923. - h s a - m i R p hsa-miR-620 hsa-miR-601. - hsa-miR-378j. - hsa-miR-4759 hsa-miR-3167. - hsa-miR-6079 h s a - m i R p hsa-miR-8087. - hsa-miR-6863 hsa-miR-3976. - hsa-miR-4635. - hsa-miR-1299 hsa-miR-1290 h s a - m i R p. - hsa-miR-944 h s a - m i R p. - h s a - m i R p hsa-miR-4513 h s a - m i R - 1 2 5 b - 2 - 3 p. - hsa-miR-4462 hsa-miR-4511. - hsa-miR-4254 hsa-miR-641. - hsa-miR-575. - hsa-miR-6780a-5p h s a - m i R p X . - h s a - m i R p hsa-miR-4491 h s a - m i R p. - hsa-miR-8076. - hsa-miR-135a-5p hsa-miR-4752. - hsa-miR-4657 h s a - m i R - 7 - 5 p. - hsa-miR-4308 h s a - m i R p. - hsa-miR-8060 h s a - m i R p h s a - m i R p. - hsa-miR-8056. - hsa-miR-4751 hsa-miR-9500. - hsa-miR-3661 hsa-miR-219a-5p. - hsa-miR-1270 hsa-miR-8083 h s a - m i R p. - hsa-miR-1246 h s a - m i R p. - hsa-miR-4439. - 2 circRNA-miRNA network. - a circRNA-miRNA interactions with 100 or more predicted binding sites. - The edge thickness in a and b is weighted by the number of binding sites predicted for the circRNA-miRNA interaction. - Though there were over 2000 circRNAs unique to each group, we did not observe them to be recurrent in the samples within their respective group. - 3 High stringency circRNA-miRNA-mRNA regulatory network. - Network of circRNA-miRNA-mRNA regulation for those circRNA-miRNA interactions predicted by both RNAHybrid and miRanda, with a miRanda match score >. - Table 1 circRNA-miRNA-mRNA network elements for those circRNA-miRNA interactions predicted by both miRanda and RNAHybrid, with a miRanda match score >. - X hsa-miR-139-5p 6 NOTCH1, STAMBP, TPD52. - hsa-miR-320a 2 METTL7A, PBX3, PLS1, SEC14L1, VCL, VIM, VOPP1, YPEL hsa-miR-320b 2 RTKN, VCL, VOPP1. - X hsa-miR-449a 1 BAZ2A, MFSD8, NOTCH1, TSN, ZNF551. - hsa-miR-125a-3p 1 ANKRD62, C15orf40, COL18A1, MFSD11, MPEG1, MUL1, TTC31, WDR12, ZNF641 X hsa-miR-125a-5p 1 CD34, MEGF9, PANX1, RIT1, TP53INP1. - hsa-miR-125a-5p 1 CD34, MEGF9, PANX1, RIT1, TP53INP1 X hsa-miR-324-5p 1 FOXO1, MEMO1, PSMD4, SMARCD2. - hsa-miR-142-3p 1 BTBD7, CLDN12, CPEB2, CSRP2, DAG1, KIF5B, PTPN23, WHAMM. - hsa-miR-133b 1 FAM160B1. - hsa-miR-448 1 DDIT4, PURG. - hsa-miR-339-5p 1 AXL, HLA-E, METTL7A, ZNF285, ZNRF3. - CircRNAs, which are abundant in the mammalian brain, represent a recent addition to the class of non- coding RNAs. - In this study, we detected astrocytic circRNAs using whole transcriptome RNAseq data obtained from the PC of AD and ND subjects, and outlined circRNA-miRNA-mRNA regulatory networks.. - We observe that the majority of identified circRNAs are unique in the AD or ND groups and are not recur- rent across the respective groups. - Interestingly, overexpression of CDR1as in zebrafish decreased the midbrain size, sug- gesting a functional role for CDR1as in the brain, while knockdown of CDR1as downregulated miR-7 targets in HEK293 cells [3]. - Due to the presence of a larger pool of transcripts, which are mostly linear RNAs, RNAseq may not have comprehensively captured all the cir- cRNAs in the samples. - To address this challenge, we describe an analysis of astrocytic circRNAs in RNAseq data from elderly individuals, and we delineate potential circRNA-miRNA-mRNA regulatory networks. - Given the role of astrocytes in signaling and synaptic modula- tion, and as immune sensors in the brain, the circRNAs we identified may be associated with such key functions.. - Further characterization using circRNA-enriched datasets will help us understand the atlas of circRNA expression in the context of specific cell types and conditions, including aging and AD. - Given the putative miRNA regulatory function of cir- cRNAs, we further performed in silico prediction of pu- tative miRNA binding sites on the ten most recurrent circRNAs, and further delineated a low- and high- stringency circRNA-miRNA-mRNA regulatory network.. - Pathway analysis on the genes from our low-stringency network revealed significantly impacted immune re- sponse pathways, which aligns with the known function of astrocytes as immune sensors in the brain. - While we did not detect circRNAs recurrently expressed in the context of healthy controls or Alzheimer’s, we are the first to report circRNAs and their potential regulatory impact in a cell-specific and region-specific manner in aged subjects. - Continued analyses such as these sets the foundation for circRNA characterization and under- standing their expression and regulatory networks in specific cell types and regions in the brain.. - All subjects were en- rolled in the BSHRI BBDP in Sun City, Arizona, and written informed consent for all aspects of the program, including tissue sharing, was obtained either from the subjects themselves prior to death or from their legally-appointed representative. - Raw sequencing data, in the form of basecall files (BCLs), were converted to FASTQ format using Illu- mina’s bcl2fastq conversion software and quality checked using FastQC [49]. - To eliminate variance in circRNA detection that could arise due to differences in the number of sequencing reads, all FASTQ files were down-sampled to reads using seqtk [50]. - In the second step, the thermodynamic stability of the resulting RNA duplex is estimated based on the high-scoring alignments from the first phase. - Only those circRNA-miRNA interactions pre- dicted by both the algorithms are used for our downstream network construction and analyses.. - From the list of commonly predicted circRNA- miRNA interactions, we filtered for those having a miRanda match score >. - circRNA-miRNA-mRNA network construction. - Using these data, we outlined a low-stringency circRNA-miRNA-mRNA regulatory network using cus- tom python scripts and visualized the network using cytoscape. - We further filtered for circRNA-miRNA in- teractions with miRanda match scores >. - 2) to outline a high-stringency circRNA-miRNA-mRNA network.. - 0.05, we performed pathway analysis using MetaCore GeneGO (v from Thompson Reuters to predict pathways that are commonly im- pacted in the AD and ND groups. - CircRNA-miRNA interactions with ≥ 100 predicted binding sites. - Low stringency circRNA-miRNA-mRNA regulatory network. - Network of circRNA-miRNA-mRNA regulation for those circRNA-miRNA interactions predicted by both RNAHybrid and miRanda, with miRanda match scores >. - The funders had no role in the study design, data collection and analysis, decision to publish, or preparation of the manuscript.. - All subjects were enrolled in the BSHRI BBDP in Sun City, Arizona, and written informed consent for all aspects of the program, including tissue sharing, was obtained either from the subjects themselves prior to death or from their legally-appointed representative. - Circular RNAs in the mammalian brain are highly abundant, conserved, and dynamically expressed. - Exon-intron circular RNAs regulate transcription in the nucleus. - Using circular RNA as a novel type of biomarker in the screening of gastric cancer. - Immune players in the CNS: the astrocyte.. - IL-4 in the brain: a cytokine to remember. - A landscape of circular RNA expression in the human heart
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