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CircPrimer: a software for annotating circRNAs and determining the specificity of circRNA primers

BMC Bioinformatics volume 19, Article number: 292 (2018) Cite this article

Abstract

Background

Since circular RNAs (circRNAs) post-transcriptionally regulate gene expression, they have attracted increasing attention. However, there is no existing tool to annotate and extract spliced sequences for circRNAs and no tool to determine the specificity of circRNA primers.

Results

In this study, we present circPrimer, which allows users to search, annotate, and visualize circRNAs. Additionally, circPrimer enables users to extract the spliced sequences and genomic sequences of any circRNA, including novel circRNAs. Furthermore, circPrimer help users to design primers for circRNAs and to determine the specificity of the circRNA primers.

Conclusions

CircPrimer is a user-friendly tool for exploring circRNAs that does not require special user skills.

Background

Circular RNAs (circRNAs) are a large class of regulatory RNAs that were identified in the early 1990s, and in the following years, they were considered to be molecular flukes or products of aberrant RNA splicing [1, 2]. Recently, with advances in high-throughput RNA sequencing (RNA-seq) technology, circRNAs were revealed to post-transcriptionally regulate gene expression and have gained increasing attention [2]. CircRNAs may exert their functions by serving as miRNA sponges [3,4,5], binding proteins [6], coding proteins [7, 8], modulating the transcriptional activity of RNA Pol II [9], and competing with linear splicing [10]. CircRNAs also serve as potential biomarkers for cancer detection and therapy [11,12,13].

To identify circRNAs from high-throughput RNA-seq data, a number of tools have been developed. In 2012, Salzman et al. developed a computational method to look for circRNAs in RNA-seq datasets [14]. Next, Find_circ [15], MapSplice2 [16], Segemehl [17], circExplorer [18], circRNA_finder [19], CIRI [20], ACFS [21], KNIFE [22], NCLscan [23], DCC [24] and UROBORUS [25] were developed in succession. With the increasing number of circRNAs identified using these tools, several databases have been established to collect and organize the circRNA sequences and information. For example, CircBase merged and unified several data sets of circRNAs into a standardized database, where investigators can search, browse and download genomic annotations of circRNAs [26]. CSCD (Cancer-specific circRNAs database), a database developed for cancer-specific circRNAs, collected the available RNA-seq datasets from 87 cancer cell line samples [27]. However, there is no existing tool to annotate and extract spliced sequences for circRNAs. Since circRNAs derived from the same parental gene may share the same sequence, divergent primers for one of these circRNAs may also amplify others. Furthermore, a previously reported tool named CircInteractome [28] was unable to generate a template for a novel circRNA or design primers with one primer spanning the spliced junction. To date, no tools have checked the specificity of circRNA primers. In present study, we introduced a tool that not only searched and annotated circRNAs but also helped users to design primers and determinthe specificity of the primers.

Implementation

CircPrimer is written in delphi. The circRNAs from Homo sapiens were downloaded from circBase and were imported into a local database. RefSeq GTF files, hg19 and hg38, were downloaded from UCSC (http://genome.ucsc.edu/) [29]. The RefSeq GTF files, GRCh37.75 and GRCh38.90, were downloaded from Ensemble (ftp://ftp.ensembl.org/pub) [30]. To annotate a circRNA, we first searched the RefSeq GTF files for transcripts with a genomic location containing the genomic location of the circRNA. Next, the transcripts were scored as following: If the start position of the circRNA exactly matched the 5′ end of an exon in the transcript, 3 points were assigned; If the end position of the circRNA exactly matched the 3′ end of an exon, another 3 points were assigned. If one boundary of the circRNA was located on an exon but did not exactly match the end of this exon, 2 points were assigned (2 points for each boundary); otherwise, 0 point was assigned. The transcript with highest sum score was extracted and defined as the parental gene of this circRNA. If two or more transcripts were obtained, the longest one was extracted.

Since Gao et al. suggested that only 2.7–4.3% circRNAs were alternatively spliced [31], we used the following method to predict the spliced sequences of the circRNAs. We first extracted the genomic sequence from UCSC according to the genomic location of the circRNA. Next, the circRNA was annotated using the method described above. According to the annotated result, the intron sequences were removed from the genomic sequence of the circRNA. Nevertheless, if one or two boundaries of the circRNA were located in an intron, the intron sequence from the start position of this circRNA to the first exon or the intron sequence from the last exon to the end position was retained.

To design primers for circRNAs, sequences can easily be searched and obtained. The template can be generated for primer3 [32] to design divergent primers or primers with one primer spanning the spliced junction.

To check the primer specificity, sequences in the circBase were searched to show that the potential circRNAs could be amplified by the primers. The position of the primer on the circRNA can also be shown visually.

Results

Data input

The CircRNA ID (e.g., hsa_circ_0000007), genomic location (e.g., chr1:1735857–1,737,977), gene symbol, or a file path of the text file (one genomic location per line) can be input into the circRNA field, depending on the function that the users will use. To input a file path, users press the Ctrl key and later double click the circRNA field to show the open file dialog. The chromosome, the start and end coordinates, and the strand orientation can be separated with any non-numeric character, except ‘,’.

Searching circRNAs in circBase

The CircRNA ID, genomic location, and gene symbol are the accepted data for searching circRNAs in the circBase. After inputting the data into the circRNA field and clicking the “circBase” button, the circRNAs are listed at the right of the main form (Fig. 1a), if one or more circRNAs are obtained. When clicking one of the listed circRNAs, the sequence of this circRNA is shown in the field ‘circRNA SEQ.’ If ‘Annotate circRNA when click’ is checked, a form is presented to show the annotated result of this circRNA (Fig. 1b). It should be noted is that RefGene ‘GRCh37.75’ or ‘hg19’ should be chosen before clicking a circRNA to annotate the circRNA because the circRNAs in circBase were mapped to the hg19 human genome. Users can save the search results in fasta format by using the right-click list menu.

Fig. 1
figure 1

Searching and annotating circRNA using circPrimer. a Search results for gene symbol, FBXW7; b Annotation result for has_circ_0001451. CDS, coding sequence; UTR, untranslated region

Full size image

Annotating a circRNA

The CircRNA ID and genomic location are the accepted data for annotating a circRNA. After inputting the data to the circRNA field and clicking the ‘Annotate’ button, a form is presented to show the annotated result of the circRNA. The data presented in the figure are extracted from circBase or are annotated according to the selected RefSeq GTF file. To distinguish the different data sources, the blue text indicates the information from circBase, and the black text indicates the annotated results. There are two reasons for when there is difference between the data from circBase and the annotated results. The first reason is that the user did not select the right refGene version. As mentioned above, RefGene ‘GRCh37.75’ or ‘hg19’ should be chosen when annotating a circRNA in circBase. The other reason is that there might be a mistake in the circBase data or our annotated results. For example, Yang et al. reported that [33] the sequence and the length of the sequence of hsa_circ_0001451 were different from those in circBase. After annotating hsa_circ_0001451 using circPrimer, we found that circPrimer obtained the same sequence that Yang et al. reported, and the sequence in the circBase was the genomic sequence of hsa_circ_0001451. Therefore, when users find a difference, they should confirm the sequence using an experimental method. When the genomic location of a novel circRNA is inputted, all of the presented data are annotated by circPrimer, and only the genomic location, gene symbol and sequence length are presented on the top-left of the figure.

Extracting a spliced sequence

The CircRNA ID, chromosome location, and a file path are the accepted data. After inputting the circRNA ID or chromosome location and later clicking the ‘UCSC RNA’ button, the spliced sequence of the circRNA is shown in the ‘circRNA SEQ’ field. When inputting a file path for a file with multiple chromosome locations, a circRNA list will be presented at the right of the main form. Users can annotate a circRNA or export the circRNAs in fasta format using the method mentioned above. It should be noted that no matter which data is input, the sequence is not obtained from circBase but is extracted from the UCSC web site according to the annotated results.

Extracting the genomic sequence

The CircRNA ID, chromosome location, and a file path are the accepted data. After inputting the circRNA ID or chromosome location and subsequently clicking the “UCSC DNA” button, the genomic sequence of the circRNA is shown in the “circRNA SEQ” field. If you input a file path of a file with multiple chromosome locations, a text file in fasta format will be saved in the root directory of the application.

Designing and checking primers

Designing specific primers for the quantification of circRNAs is challenging and prone to errors, since the mature circRNA sequences after splicing are not readily available in many cases, and the primers must be divergent and must span the junction.

Users can easily obtain the spliced sequence of a circRNA using circPrimer, and it does not matter of the circRNA is a novel or already known. After obtaining the spliced sequence, depending on the users’ selection, circPrimer generates a template for designing divergent primers or primers with one primer spanning the spliced junction. Users just paste the generated template into Primer3 to design primers for polymerase chain reaction (PCR). To check the specificity of the circRNA primers, users check “Check Primer” to show the panel “Check Primer” and the input the primers and, finally, click the “check” button to start the checking process.

The reason for designing the primers with one primer spanning the splicing junction is that the divergent primer may not be specific enough to amplify the target circRNA. As shown in Fig. 2a, the divergent primers designed for hsa_circ_0020707 amplify 4 circRNAs, which are derived from same parental gene (i.e., RPLP2) and share the same sequence (Fig. 2c and d). If one of the primers spans the spliced junction of the circRNA, the amplification could be more specific than the divergent primers (Fig. 2b, c and e). However, when five or more bases located in the 3′ end of a primer span the spliced junction, these types of primers have the possibility to amplify the parental gene of the circRNA.

Fig. 2
figure 2

Checking the specificity of circRNA primers. a Checking the specificity of divergent primers for has_circ_0020707, a circRNA derived from RPLP2. Length, polymerase chain reaction (PCR) product size; F0R, primer characteristic (1, convergent primer; 0, divergent primer; F + No., forward primer spanning the spliced junction [No. represents the base count spanned by the primer]; and R + No., reverse primer spanning the spliced junction). b Checking the specificity of primers, with one primer spanning the spliced junction. c Localization of the divergent primers in has_circ_0020707. d Localization of the divergent primers in has_circ_0020706, which is also derived from RPLP2. e Localization of the primers, with the forward primer spanning the spliced junction of has_circ_0020707

Full size image

At the present time, there is no tool to directly design primers for circRNA. The previously reported tool, CircInteractome, also used Primer3 or the NCBI Primer Design tool to design primers for circRNA [28]. However, CircInteractome is unable to generate a template for a novel circRNA or to check the specificity of the primers.

Conclusions

We developed a user-friendly tool to annotate circRNAs that does not require any special user skills. With this tool, users can easily search circRNAs and annotate circRNAs visually. Users can extract the spliced sequences and genomic sequences of any circRNA, including novel circRNAs. Furthermore, circPrimer helps users to design primers for circRNAs and to determine the specificity of the circRNA primers.

Availability and requirements

Project name: circPrimer

Project home page: http://www.bioinf.com.cn/

Operating system(s): Window

Programming language: Delphi

Other requirements: Internet connectivity

License: GNU General Public License version 3.0 (GPL-3.0)

Any restrictions to use by non-academics: None

Abbreviations

circRNA:

Circular RNA

CSCD:

Cancer-specific circRNAs database

RNA-seq:

RNA sequencing

References

  1. Qu S, Yang X, Li X, Wang J, Gao Y, Shang R, Sun W, Dou K, Li H. Circular RNA: a new star of noncoding RNAs. Cancer Lett. 2015;365(2):141–8.

    Article  PubMed  CAS  Google Scholar 

  2. Rong D, Tang W, Li Z, Zhou J, Shi J, Wang H, Cao H. Novel insights into circular RNAs in clinical application of carcinomas. OncoTargets and therapy. 2017;10:2183–8.

    Article  PubMed  PubMed Central  Google Scholar 

  3. Zheng Q, Bao C, Guo W, Li S, Chen J, Chen B, Luo Y, Lyu D, Li Y, Shi G, et al. Circular RNA profiling reveals an abundant circHIPK3 that regulates cell growth by sponging multiple miRNAs. Nat Commun. 2016;7:11215.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  4. Hansen TB, Jensen TI, Clausen BH, Bramsen JB, Finsen B, Damgaard CK, Kjems J. Natural RNA circles function as efficient microRNA sponges. Nature. 2013;495(7441):384–8.

    Article  PubMed  CAS  Google Scholar 

  5. Wan L, Zhang L, Fan K, Cheng ZX, Sun QC, Wang JJ. Circular RNA-ITCH suppresses lung Cancer proliferation via inhibiting the Wnt/beta-catenin pathway. Biomed Res Int. 2016;2016:1579490.

    PubMed  PubMed Central  Google Scholar 

  6. Du WW, Yang W, Liu E, Yang Z, Dhaliwal P, Yang BB. Foxo3 circular RNA retards cell cycle progression via forming ternary complexes with p21 and CDK2. Nucleic Acids Res. 2016;44(6):2846–58.

    Article  PubMed  PubMed Central  Google Scholar 

  7. Legnini I, Di Timoteo G, Rossi F, Morlando M, Briganti F, Sthandier O, Fatica A, Santini T, Andronache A, Wade M, et al. Circ-ZNF609 Is a Circular RNA that Can Be Translated and Functions in Myogenesis. Mol Cell. 2017;66(1):22–37.e29.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  8. Yang Y, Fan X, Mao M, Song X, Wu P, Zhang Y, Jin Y, Yang Y, Chen LL, Wang Y, et al. Extensive translation of circular RNAs driven by N(6)-methyladenosine. Cell Res. 2017;27(5):626–41.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  9. Zhang Y, Zhang XO, Chen T, Xiang JF, Yin QF, Xing YH, Zhu S, Yang L, Chen LL. Circular intronic long noncoding RNAs. Mol Cell. 2013;51(6):792–806.

    Article  PubMed  CAS  Google Scholar 

  10. Ashwal-Fluss R, Meyer M, Pamudurti NR, Ivanov A, Bartok O, Hanan M, Evantal N, Memczak S, Rajewsky N, Kadener S. circRNA biogenesis competes with pre-mRNA splicing. Mol Cell. 2014;56(1):55–66.

    Article  PubMed  CAS  Google Scholar 

  11. Li Y, Zheng Q, Bao C, Li S, Guo W, Zhao J, Chen D, Gu J, He X, Huang S. Circular RNA is enriched and stable in exosomes: a promising biomarker for cancer diagnosis. Cell Res. 2015;25(8):981.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  12. Xu H, Gong Z, Shen Y, Fang Y, Zhong S. Circular RNA expression in extracellular vesicles isolated from serum of patients with endometrial cancer. Epigenomics. 2018;10(2):187–97.

    Article  PubMed  CAS  Google Scholar 

  13. Wang F, Nazarali AJ, Ji S. Circular RNAs as potential biomarkers for cancer diagnosis and therapy. Am J Cancer Res. 2016;6(6):1167–76.

    PubMed  PubMed Central  CAS  Google Scholar 

  14. Salzman J, Gawad C, Wang PL, Lacayo N, Brown PO. Circular RNAs are the predominant transcript isoform from hundreds of human genes in diverse cell types. PLoS One. 2012;7(2):e30733.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  15. Memczak S, Jens M, Elefsinioti A, Torti F, Krueger J, Rybak A, Maier L, Mackowiak SD, Gregersen LH, Munschauer M, et al. Circular RNAs are a large class of animal RNAs with regulatory potency. Nature. 2013;495(7441):333–8.

    Article  PubMed  CAS  Google Scholar 

  16. Wang K, Singh D, Zeng Z, Coleman SJ, Huang Y, Savich GL, He X, Mieczkowski P, Grimm SA, Perou CM, et al. MapSplice: accurate mapping of RNA-seq reads for splice junction discovery. Nucleic Acids Res. 2010;38(18):e178.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  17. Hoffmann S, Otto C, Doose G, Tanzer A, Langenberger D, Christ S, Kunz M, Holdt LM, Teupser D, Hackermuller J, et al. A multi-split mapping algorithm for circular RNA, splicing, trans-splicing and fusion detection. Genome Biol. 2014;15(2):R34.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  18. Zhang XO, Wang HB, Zhang Y, Lu X, Chen LL, Yang L. Complementary sequence-mediated exon circularization. Cell. 2014;159(1):134–47.

    Article  PubMed  CAS  Google Scholar 

  19. Westholm JO, Miura P, Olson S, Shenker S, Joseph B, Sanfilippo P, Celniker SE, Graveley BR, Lai EC. Genome-wide analysis of drosophila circular RNAs reveals their structural and sequence properties and age-dependent neural accumulation. Cell Rep. 2014;9(5):1966–80.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  20. Gao Y, Wang J, Zhao F. CIRI: an efficient and unbiased algorithm for de novo circular RNA identification. Genome Biol. 2015;16:4.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  21. You X, Vlatkovic I, Babic A, Will T, Epstein I, Tushev G, Akbalik G, Wang M, Glock C, Quedenau C, et al. Neural circular RNAs are derived from synaptic genes and regulated by development and plasticity. Nat Neurosci. 2015;18(4):603–10.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  22. Szabo L, Morey R, Palpant NJ, Wang PL, Afari N, Jiang C, Parast MM, Murry CE, Laurent LC, Salzman J. Statistically based splicing detection reveals neural enrichment and tissue-specific induction of circular RNA during human fetal development. Genome Biol. 2015;16:126.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  23. Chuang TJ, Wu CS, Chen CY, Hung LY, Chiang TW, Yang MY. NCLscan: accurate identification of non-co-linear transcripts (fusion, trans-splicing and circular RNA) with a good balance between sensitivity and precision. Nucleic Acids Res. 2016;44(3):e29.

    Article  PubMed  CAS  Google Scholar 

  24. Cheng J, Metge F, Dieterich C. Specific identification and quantification of circular RNAs from sequencing data. Bioinformatics. 2016;32(7):1094–6.

    Article  PubMed  CAS  Google Scholar 

  25. Song X, Zhang N, Han P, Moon BS, Lai RK, Wang K, Lu W. Circular RNA profile in gliomas revealed by identification tool UROBORUS. Nucleic Acids Res. 2016;44(9):e87.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  26. Glazar P, Papavasileiou P, Rajewsky N. circBase: a database for circular RNAs. RNA. 2014;20(11):1666–70.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  27. Xia S, Feng J, Chen K, Ma Y, Gong J, Cai F, Jin Y, Gao Y, Xia L, Chang H, et al. CSCD: a database for cancer-specific circular RNAs. Nucleic Acids Res. 2018;46(D1):D925–9.

    Article  PubMed  Google Scholar 

  28. Dudekula DB, Panda AC, Grammatikakis I, De S, Abdelmohsen K, Gorospe M. CircInteractome: a web tool for exploring circular RNAs and their interacting proteins and microRNAs. RNA Biol. 2016;13(1):34–42.

    Article  PubMed  Google Scholar 

  29. Casper J, Zweig AS, Villarreal C, Tyner C, Speir ML, Rosenbloom KR, Raney BJ, Lee CM, Lee BT, Karolchik D, et al. The UCSC genome browser database: 2018 update. Nucleic Acids Res. 2018;46(D1):D762–9.

    PubMed  Google Scholar 

  30. Zerbino DR, Achuthan P, Akanni W, Amode MR, Barrell D, Bhai J, Billis K, Cummins C, Gall A, Giron CG, et al. Ensembl 2018. Nucleic Acids Res. 2018;46(D1):D754–61.

    Article  PubMed  Google Scholar 

  31. Gao Y, Wang J, Zheng Y, Zhang J, Chen S, Zhao F. Comprehensive identification of internal structure and alternative splicing events in circular RNAs. Nat Commun. 2016;7:12060.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  32. Untergasser A, Cutcutache I, Koressaar T, Ye J, Faircloth BC, Remm M, Rozen SG. Primer3--new capabilities and interfaces. Nucleic Acids Res. 2012;40(15):e115.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  33. Yang Y, Gao X, Zhang M, Yan S, Sun C, Xiao F, Huang N, Yang X, Zhao K, Zhou H, et al. Novel Role of FBXW7 Circular RNA in Repressing Glioma Tumorigenesis. J Natl Cancer Inst. 2018;110(3):djx166.

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Acknowledgments

We are grateful to all members in Center of Clinical Laboratory Science, Jiangsu Cancer Hospital for their participation in the testing of the program and their valuable feedback and suggestions.

Funding

This study was funded by the National Natural Science Foundation of China (grant number 81602551), the Young Talents Program of Jiangsu Cancer Hospital (grant number 2017YQL-10), Jiangsu Provincial Women and Children Health Research Project (grant number F201762), and Jiangsu Province six talent peak personal training project (grant number 2016-WSW-086). The funding body played no role in the design of the study or the collection, analysis, and interpretation of the data or in writing the manuscript.

Availability of data and materials

CircPrimer can be downloaded from http://www.bioinf.com.cn/. Users can also send an email to circPrimer@bioinf.com.cn to obtain the lasted version of circPrimer.

Author information

Author notes

  1. Shanliang Zhong and Jinyan Wang contributed equally to this work.

Authors and Affiliations

  1. Center of Clinical Laboratory Science, Jiangsu Cancer Hospital & Jiangsu Institute of Cancer Research & The Affiliated Cancer Hospital of Nanjing Medical University, Nanjing, 210009, China

    Shanliang Zhong

  2. Department of General Surgery, The Affiliated Cancer Hospital of Nanjing Medical University, Nanjing, 210009, China

    Jinyan Wang & Qian Zhang

  3. Department of Radiation Oncology, Jiangsu Cancer Hospital & Jiangsu Institute of Cancer Research & The Affiliated Cancer Hospital of Nanjing Medical University, Nanjing, 210009, China

    Hanzi Xu

  4. Department of Medical Oncology, Jiangsu Cancer Hospital & Jiangsu Institute of Cancer Research & The Affiliated Cancer Hospital of Nanjing Medical University, Baiziting 42, Nanjing, 210009, China

    Jifeng Feng

Authors
  1. Shanliang Zhong
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Contributions

JF carried out the programming tasks. SZ designed the application. JW and QZ tested the software. SZ and HX wrote the manuscript. All of the authors approved the final version of the manuscript.

Corresponding author

Correspondence to Jifeng Feng.

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Zhong, S., Wang, J., Zhang, Q. et al. CircPrimer: a software for annotating circRNAs and determining the specificity of circRNA primers. BMC Bioinformatics 19, 292 (2018). https://doi.org/10.1186/s12859-018-2304-1

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BMC Bioinformatics

ISSN: 1471-2105

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