Candidate miRNAs from Oryza sativa for Silencing the Rice Tungro Viruses

Noor Amni Mohamed, Nik Muhammad Faris Nazmie Che Ngah, Azlan Abas, Noraini Talip, Murni Nazira Sarian, Hamizah Shahirah Hamezah, Sarahani Harun and Hamidun Bunawan ()
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Noor Amni Mohamed: Institute of Systems Biology, Universiti Kebangsaan Malaysia (UKM), Bangi 43600, Selangor, Malaysia
Nik Muhammad Faris Nazmie Che Ngah: Institute of Systems Biology, Universiti Kebangsaan Malaysia (UKM), Bangi 43600, Selangor, Malaysia
Azlan Abas: Center for Research in Development, Social and Environment (SEEDS), Faculty of Social Sciences and Humanities, Universiti Kebangsaan Malaysia (UKM), Bangi 43600, Selangor, Malaysia
Noraini Talip: Department of Biotechnology and Biological Sciences, Faculty of Science and Technology, Universiti Kebangsaan Malaysia (UKM), Bangi 43600, Selangor, Malaysia
Murni Nazira Sarian: Institute of Systems Biology, Universiti Kebangsaan Malaysia (UKM), Bangi 43600, Selangor, Malaysia
Hamizah Shahirah Hamezah: Institute of Systems Biology, Universiti Kebangsaan Malaysia (UKM), Bangi 43600, Selangor, Malaysia
Sarahani Harun: Institute of Systems Biology, Universiti Kebangsaan Malaysia (UKM), Bangi 43600, Selangor, Malaysia
Hamidun Bunawan: Institute of Systems Biology, Universiti Kebangsaan Malaysia (UKM), Bangi 43600, Selangor, Malaysia

Agriculture, 2023, vol. 13, issue 3, 1-14

Abstract: Rice tungro disease (RTD), caused by Rice tungro bacilliform virus (RTBV) and Rice tungro spherical virus (RTSV) is one of the most prominent viral diseases in Asian countries. This virus disease problem seems to have been accentuated in those countries by causing a series of outbreaks over the years after being first reported in International Rice Research Institute (IRRI), Philippines, in 1963. One of the effective ways to combat viruses is through RNA silencing. microRNA is an important player in the RNA silencing mechanism. Genome sequences analysis shows RTBV-SP isolate (8 Kb) is composed of four open reading frames (ORF 1, ORF 2, ORF 3, and ORF 4), meanwhile, RTSV-SP (12 Kb) consists of one open reading frame encoded by seven different polyproteins (P1, CP1, CP2, CP3, NTP, Pro, and Rep). Therefore, this study investigated possible rice-encoded miRNAs targeted on RTBV and RTSV using in silico analysis. Five bioinformatics tools were employed using five different prediction algorithms: miRanda, RNA22, RNAhybrid, Tapirhybrid, and psRNATarget. The results revealed each RTBV and RTSV can be silenced by three potentially best candidate rice-encoded miRNA. For RTBV, osa-miR5510 (accession no. MIMAT0022143), osa-miR3980a-3p (accession no. MIMAT0019676), and osa-miR3980b-3p (accession no. MIMAT0019678) are being predicted by all five algorithms. Meanwhile, for RTSV, three miRNAs predicted are osa-miR414 (accession no. MIMAT0001330), osa-miR5505 (accession no. MIMAT00221138) and osa-miR167a-3p (accession no. MIMAT0006780). The predicted data provide useful material for developing RTBV and RTSV-resistant rice varieties.

Keywords: rice tungro disease; bioinformatics; miRNA; Oryza sativa (search for similar items in EconPapers)
JEL-codes: Q1 Q10 Q11 Q12 Q13 Q14 Q15 Q16 Q17 Q18 (search for similar items in EconPapers)
Date: 2023
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