Abstract
With the innovative knowledge and bioinformatics tools in the identification and characterization of noncoding RNAs, circular RNA (circRNA) is added as a new member to the noncoding RNAs family. CircRNA enrichment by rRNA depletion/RNase R or poly-A removal/RNase R treatment followed by NGS analysis is the most frequently adopted method for circular RNA identification and characterization. In this chapter, we describe the multiple displacement amplification (MDA) as a convenient method to augment the identification of even the abysmally expressed circular RNAs at low sequencing depth. Total RNA, extracted at three different developmental stages of rice, is subjected to RiboMinus and RNase R treatment to deplete the linear RNAs. The enriched circular RNAs are reverse transcribed with random hexamers. The resulting cDNA is subjected to phi29 DNA polymerase amplification using exo-resistant random pentamers to yield high molecular weight dsDNA product, followed by Illumina sequencing at ten million paired end reads per sample. The sequence analysis yielded a promising number of circRNAs with the appreciable inclusion of differentially regulated and minimally expressed circRNAs at a comparatively reduced cost.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Lu T, Cui L, Zhou Y et al (2015) Transcriptome-wide investigation of circular RNAs in rice. RNA 21(12):2076–2087. https://doi.org/10.1261/rna.052282.115
Darbani B, Noeparvar S, Borg S (2016) Identification of circular RNAs from the parental genes involved in multiple aspects of cellular metabolism in barley. Front Plant Sci 7:776. https://doi.org/10.3389/fpls.2016.00776
Tan J, Zhou Z, Niu Y et al (2017) Identification and functional characterization of tomato CircRNAs derived from genes involved in fruit pigment accumulation. Sci Rep 7(1):8594. https://doi.org/10.1038/s41598-017-08806-0
Wang Y, Yang M, Wei S et al (2017) Identification of circular RNAs and their targets in leaves of Triticum aestivum L. under dehydration stress. Front Plant Sci 7:2024. https://doi.org/10.3389/fpls.2016.02024
Wang Y, Wang Q, Gao L et al (2017) Integrative analysis of circRNAs acting as ceRNAs involved in ethylene pathway in tomato. Physiol Plant 161(3):311–321. https://doi.org/10.1111/ppl.12600
Wang J, Lin J, Wang H et al (2018) Identification and characterization of circRNAs in Pyrus betulifolia Bunge under drought stress. PLoS One 13(7):e0200692. https://doi.org/10.1371/journal.pone.0200692
Zhu Y, Jia J, Yang L et al (2019) Identification of cucumber circular RNAs responsive to salt stress. BMC Plant Biol 19:164. https://doi.org/10.1186/s12870-019-1712-3
Ashwal-Fluss R, Meyer M, Pamudurti NR et al (2014) circRNA biogenesis competes with pre-mRNA splicing. Mol Cell 56(1):55–66. https://doi.org/10.1016/j.molcel.2014.08.019
Conn VM, Hugouvieux V, Nayak A et al (2017) A circRNA from SEPALLATA3 regulates splicing of its cognate mRNA through R-loop formation. Nat Plants 3:17053. https://doi.org/10.1038/nplants.2017.53
Cheng J, Zhang Y, Li Z et al (2018) A lariat-derived circular RNA is required for plant development in Arabidopsis. Sci China Life Sci 61:204–213. https://doi.org/10.1007/s11427-017-9182-3
Wang Y, Xiong Z, Li Q et al (2019) Circular RNA profiling of the rice photo-thermosensitive genic male sterile line Wuxiang S reveals circRNA involved in the fertility transition. BMC Plant Biol 19:340. https://doi.org/10.1186/s12870-019-1944-2
Ye CY, Chen L, Liu C et al (2015) Widespread noncoding circular RNAs in plants. New Phytol 208:88–95. https://doi.org/10.1111/nph.13585
Jeck WR, Sharpless NE (2014) Detecting and characterising circular RNAs. Nat Biotechnol 32:453–461. https://doi.org/10.1038/nbt.2890
Guria A, Kumar KVV, Srikakulum N et al (2019) Circular RNA profiling by Illumina sequencing via template-dependent multiple displacement amplification. Biomed Res Int 2019:2756516. https://doi.org/10.1155/2019/2756516
Vijayachandra K, Palanichelvam K, Veluthambi K (1995) Rice scutellum induces Agrobacterium tumefaciens vir genes and T-strand generation. Plant Mol Biol 29:125–133. https://doi.org/10.1007/BF00019124
Wang W, Ren Y, Lu Y et al (2017) Template-dependent multiple displacement amplification for profiling human circulating RNA. BioTechniques 63(1):21–27. https://doi.org/10.2144/000114566
Gao Y, Zhang J, Zhao F (2018) Circular RNA identification based on multiple seed matching. Brief Bioinform 19(5):803–810. https://doi.org/10.1093/bib/bbx014
Zhang XO, Wang HB, Zhang Y et al (2014) Complementary sequence-mediated exon circularization. Cell 159:134–147. https://doi.org/10.1016/j.cell.2014.09.001
Gao Y, Wang J, Zhao F (2015) CIRI: an efficient and unbiased algorithm for de novo circular RNA identification. Genome Biol 16:4. https://doi.org/10.1186/s13059-014-0571-3
Chen L, Yu Y, Zhang X et al (2016) PcircRNA_finder: a software for circRNA prediction in plants. Bioinformatics 32:3528–3529. https://doi.org/10.1093/bioinformatics/btw496
Cheng J, Metge F, Dieterich C (2016) Specific identification and quantification of circular RNAs from sequencing data. Bioinformatics 32:1094–1096. https://doi.org/10.1093/bioinformatics/btv656
https://www.rna-seqblog.com/rpkm-fpkm-and-tpm-clearly-explained/. Accessed 29 July 2020
Livak KJ, Schmittgen TD (2001) Analysis of relative gene expression data using real-time quantitative PCR and the 2(-Delta C(T)) method. Methods 25(4):402–408. https://doi.org/10.1006/meth.2001.1262
Bolser D, Staines DM, Pritchard E et al (2016) Ensembl plants: integrating tools for visualizing, mining, and analyzing plant genomics data. In: Edwards D (ed) Plant bioinformatics. Methods in molecular biology, vol 1374. Humana Press, New York, NY. https://doi.org/10.1007/978-1-4939-3167-5_6
Dai X, Zhuang Z, Zhao PX (2018) psRNATarget: a plant small RNA target analysis server (2017 release). Nucleic Acids Res 46(W1):W49–W54. https://doi.org/10.1093/nar/gky316
Kozomara A, Birgaoanu M, Griffiths-Jones S (2019) miRBase: from microRNA sequences to function. Nucleic Acids Res 47(D1):D155–D162. https://doi.org/10.1093/nar/gky1141
Varkonyi-Gasic E, Wu R, Wood M et al (2007) Protocol: a highly sensitive RT-PCR method for detection and quantification of microRNAs. Plant Methods 3:12. https://doi.org/10.1186/1746-4811-3-12
Kramer MF (2011) Stem-loop RT-qPCR for miRNAs. Curr Protoc Mol Biol . Chapter 15:Unit15.10-15.10. https://doi.org/10.1002/0471142727.mb1510s95
Chen C, Ridzon DA, Broomer AJ et al (2005) Real-time quantification of microRNAs by stem-loop RT-PCR. Nucleic Acids Res 33(20):e179. https://doi.org/10.1093/nar/gni178
Marcial-Quino J, Gómez-Manzo S, Fierro F et al (2016) Stem-loop RT-qPCR as an efficient tool for the detection and quantification of small RNAs in Giardia lamblia. Genes 7(12):131. https://doi.org/10.3390/genes7120131
Chen J, Lozach J, Garcia EW et al (2008) Highly sensitive and specific microRNA expression profiling using BeadArray technology. Nucleic Acids Res 36(14):e87. https://doi.org/10.1093/nar/gkn387
Yang LH, Wang SL, Tang LL et al (2014) Universal stem-loop primer method for screening and quantification of microRNA. PLoS One 9(12):e115293. https://doi.org/10.1371/journal.pone.0115293
Acknowledgments
We acknowledge the fund granted from the Science and Engineering Research Board (SERB) (Ref. No. EEQ/2018/000067, SB/EMEQ-070/2013 to GP and EMR/2016/000945 to SN). PS is a recipient of Lady Tata Memorial Trust (LTMT) Junior Research Scholarship (2019-2020). Financial assistance was provided to AG by Department of Biotechnology (DBT) (Ref. No. BT/PR23641/BPA/118/309/2017, BT/PR2061/AGR/36/707/2011) and grants from BT/PR6466/COE/34/16/2012. The equipment grants from Department of Science and Technology—Promotion of University Research and Scientific Excellence (DST-PURSE), University Grant Commission—Special Assistance Programme (UGC-SAP) are gratefully acknowledged.
Author information
Authors and Affiliations
Corresponding authors
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2021 The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature
About this protocol
Cite this protocol
Guria, A., Sharma, P., Natesan, S., Pandi, G. (2021). Identification of Circular RNAs by Multiple Displacement Amplification and Their Involvement in Plant Development. In: Vaschetto, L.M. (eds) Plant Circular RNAs. Methods in Molecular Biology, vol 2362. Humana, New York, NY. https://doi.org/10.1007/978-1-0716-1645-1_4
Download citation
DOI: https://doi.org/10.1007/978-1-0716-1645-1_4
Published:
Publisher Name: Humana, New York, NY
Print ISBN: 978-1-0716-1644-4
Online ISBN: 978-1-0716-1645-1
eBook Packages: Springer Protocols