In Silico Identification of Sugarcane (Saccharum Officinarum L.) Genome Encoded MicroRNAs Targeting Sugarcane Bacilliform Virus

Overview

Journal PLoS One

Specialties General Medicine
Science

Date 2022 Jan 20

PMID 35051194

Authors

Muhammad Aleem Ashraf

Xiaoyan Feng

Xiaowen Hu

Fakiha Ashraf

Linbo Shen

Muhammad Shahzad Iqbal

Shuzhen Zhang

Affiliations

Soon will be listed here.

Abstract

Sugarcane bacilliform virus (SCBV) is considered one of the most economically damaging pathogens for sugarcane production worldwide. Three open reading frames (ORFs) are characterized in the circular, ds-DNA genome of the SCBV; these encode for a hypothetical protein (ORF1), a DNA binding protein (ORF2), and a polyprotein (ORF3). A comprehensive evaluation of sugarcane (Saccharum officinarum L.) miRNAs for the silencing of the SCBV genome using in silico algorithms were carried out in the present study using mature sugarcane miRNAs. miRNAs of sugarcane are retrieved from the miRBase database and assessed in terms of hybridization with the SCBV genome. A total of 14 potential candidate miRNAs from sugarcane were screened out by all used algorithms used for the silencing of SCBV. The consensus of three algorithms predicted the hybridization site of sof-miR159e at common locus 5534. miRNA-mRNA interactions were estimated by computing the free-energy of the miRNA-mRNA duplex using the RNAcofold algorithm. A regulatory network of predicted candidate miRNAs of sugarcane with SCBV-ORFs, generated using Circos-is used to identify novel targets. The predicted data provide useful information for the development of SCBV-resistant sugarcane plants.

Citing Articles

Computational identification and experimental validation of novel microRNAs along with their targets through RT-PCR approach.

Baqi A, Samiullah , Khan J, Sadiq A, Khan Y, Ali S Plant Signal Behav. 2025; 20(1):2452334.

PMID: 39874980 PMC: 11776470. DOI: 10.1080/15592324.2025.2452334.

identification of papaya genome-encoded microRNAs to target begomovirus genes in papaya leaf curl disease.

Srivastava A, Pandey V, Singh N, Marwal A, Shahid M, Gaur R Front Microbiol. 2024; 15:1340275.

PMID: 38605706 PMC: 11008722. DOI: 10.3389/fmicb.2024.1340275.

Developing new sugarcane varieties suitable for mechanized production in China: principles, strategies and prospects.

Que Y, Wu Q, Zhang H, Luo J, Zhang Y Front Plant Sci. 2024; 14:1337144.

PMID: 38259907 PMC: 10802142. DOI: 10.3389/fpls.2023.1337144.

Comprehensive insights into the regulatory mechanisms of lncRNA in alkaline-salt stress tolerance in rice.

Rehman O, Uzair M, Farooq M, Saleem B, Attacha S, Attia K Mol Biol Rep. 2023; 50(9):7381-7392.

PMID: 37450076 DOI: 10.1007/s11033-023-08648-2.

In Silico Identification of Cassava Genome-Encoded MicroRNAs with Predicted Potential for Targeting the ICMV-Kerala Begomoviral Pathogen of Cassava.

Ashraf M, Ali B, Brown J, Shahid I, Yu N Viruses. 2023; 15(2).

PMID: 36851701 PMC: 9963618. DOI: 10.3390/v15020486.

References

Huang Y, Zou Q, Song H, Song F, Wang L, Zhang G . A study of miRNAs targets prediction and experimental validation. Protein Cell. 2010; 1(11):979-86. PMC: 4875151. DOI: 10.1007/s13238-010-0129-4. View

Dai X, Zhao P . psRNATarget: a plant small RNA target analysis server. Nucleic Acids Res. 2011; 39(Web Server issue):W155-9. PMC: 3125753. DOI: 10.1093/nar/gkr319. View

Liu S, Zhou J, Hu C, Wei C, Zhang J . MicroRNA-Mediated Gene Silencing in Plant Defense and Viral Counter-Defense. Front Microbiol. 2017; 8:1801. PMC: 5611411. DOI: 10.3389/fmicb.2017.01801. View

Dai X, Zhuang Z, Zhao P . psRNATarget: a plant small RNA target analysis server (2017 release). Nucleic Acids Res. 2018; 46(W1):W49-W54. PMC: 6030838. DOI: 10.1093/nar/gky316. View

Loher P, Rigoutsos I . Interactive exploration of RNA22 microRNA target predictions. Bioinformatics. 2012; 28(24):3322-3. DOI: 10.1093/bioinformatics/bts615. View

Shweta , Akhter Y, Khan J . Genome wide identification of cotton (Gossypium hirsutum)-encoded microRNA targets against Cotton leaf curl Burewala virus. Gene. 2017; 638:60-65. DOI: 10.1016/j.gene.2017.09.061. View

Rosa C, Kuo Y, Wuriyanghan H, Falk B . RNA Interference Mechanisms and Applications in Plant Pathology. Annu Rev Phytopathol. 2018; 56:581-610. DOI: 10.1146/annurev-phyto-080417-050044. View

Ossowski S, Schwab R, Weigel D . Gene silencing in plants using artificial microRNAs and other small RNAs. Plant J. 2008; 53(4):674-90. DOI: 10.1111/j.1365-313X.2007.03328.x. View

Jabbar B, Iqbal M, Batcho A, Nasir I, Rashid B, Husnain T . Target prediction of candidate miRNAs from Oryza sativa for silencing the RYMV genome. Comput Biol Chem. 2019; 83:107127. DOI: 10.1016/j.compbiolchem.2019.107127. View

10.

Wang W, Galili G . Tuning the Orchestra: miRNAs in Plant Immunity. Trends Plant Sci. 2019; 24(3):189-191. DOI: 10.1016/j.tplants.2019.01.009. View

11.

Hirsch A . The use of RNAi-based screens to identify host proteins involved in viral replication. Future Microbiol. 2010; 5(2):303-11. PMC: 2864646. DOI: 10.2217/fmb.09.121. View

12.

Schwab R, Ossowski S, Riester M, Warthmann N, Weigel D . Highly specific gene silencing by artificial microRNAs in Arabidopsis. Plant Cell. 2006; 18(5):1121-33. PMC: 1456875. DOI: 10.1105/tpc.105.039834. View

13.

Kozomara A, Birgaoanu M, Griffiths-Jones S . miRBase: from microRNA sequences to function. Nucleic Acids Res. 2018; 47(D1):D155-D162. PMC: 6323917. DOI: 10.1093/nar/gky1141. View

14.

Gurjar A, Panwar A, Gupta R, Mantri S . PmiRExAt: plant miRNA expression atlas database and web applications. Database (Oxford). 2016; 2016. PMC: 4830907. DOI: 10.1093/database/baw060. View

15.

Niu Q, Lin S, Reyes J, Chen K, Wu H, Yeh S . Expression of artificial microRNAs in transgenic Arabidopsis thaliana confers virus resistance. Nat Biotechnol. 2006; 24(11):1420-8. DOI: 10.1038/nbt1255. View

16.

Lorenz R, Bernhart S, Honer Zu Siederdissen C, Tafer H, Flamm C, Stadler P . ViennaRNA Package 2.0. Algorithms Mol Biol. 2011; 6:26. PMC: 3319429. DOI: 10.1186/1748-7188-6-26. View

17.

John B, Enright A, Aravin A, Tuschl T, Sander C, Marks D . Human MicroRNA targets. PLoS Biol. 2004; 2(11):e363. PMC: 521178. DOI: 10.1371/journal.pbio.0020363. View

18.

Kozomara A, Griffiths-Jones S . miRBase: annotating high confidence microRNAs using deep sequencing data. Nucleic Acids Res. 2013; 42(Database issue):D68-73. PMC: 3965103. DOI: 10.1093/nar/gkt1181. View

19.

Iqbal M, Jabbar B, Nauman Sharif M, Ali Q, Husnain T, Nasir I . MCMV Silencing Concludes Potential Host-Derived miRNAs in Maize. Front Plant Sci. 2017; 8:372. PMC: 5368279. DOI: 10.3389/fpls.2017.00372. View

20.

Millar A, Lohe A, Wong G . Biology and Function of miR159 in Plants. Plants (Basel). 2019; 8(8). PMC: 6724108. DOI: 10.3390/plants8080255. View