sensitivity of small rna-based detection of plant viruses

sensitivity of small rna-based detection of plant viruses

;Johanna Santala;Jari P. T. Valkonen
journal of magnetic resonance (san diego, calif : 1997) 2018 Vol. 9 pp. -
189
santala2018frontierssensitivity

Abstract

Plants recognize unrelated viruses by the antiviral defense system called RNA interference (RNAi). RNAi processes double-stranded viral RNA into small RNAs (sRNAs) of 21–24 nucleotides, the reassembly of which into longer strands in silico allows virus identification by comparison with the sequences available in databases. The aim of this study was to compare the virus detection sensitivity of sRNA-based virus diagnosis with the established virus species-specific polymerase chain reaction (PCR) approach. Viruses propagated in tobacco plants included three engineered, infectious clones of Potato virus A (PVA), each carrying a different marker gene, and an infectious clone of Potato virus Y (PVY). Total RNA (containing sRNA) was isolated and subjected to reverse-transcription real-time PCR (RT-RT-PCR) and sRNA deep-sequencing at different concentrations. RNA extracted from various crop plants was included in the reactions to normalize RNA concentrations. Targeted detection of selected viruses showed a similar threshold for the sRNA and reverse-transcription quantitative PCR (RT-qPCR) analyses. The detection limit for PVY and PVA by RT-qPCR in this study was 3 and 1.5 fg of viral RNA, respectively, in 50 ng of total RNA per PCR reaction. When knowledge was available about the viruses likely present in the samples, sRNA-based virus detection was 10 times more sensitive than RT-RT-PCR. The advantage of sRNA analysis is the detection of all tested viruses without the need for virus-specific primers or probes.

Citation

ID: 157270
Ref Key: santala2018frontierssensitivity
Use this key to autocite in SciMatic or Thesis Manager

References

Blockchain Verification

Account:
NFT Contract Address:
0x95644003c57E6F55A65596E3D9Eac6813e3566dA
Article ID:
157270
Unique Identifier:
10.3389/fmicb.2018.00939
Network:
Scimatic Chain (ID: 481)
Loading...
Blockchain Readiness Checklist
Authors
Abstract
Journal Name
Year
Title
5/5
Creates 1,000,000 NFT tokens for this article
Token Features:
  • ERC-1155 Standard NFT
  • 1 Million Supply per Article
  • Transferable via MetaMask
  • Permanent Blockchain Record
Blockchain QR Code
Scan with Saymatik Web3.0 Wallet

Saymatik Web3.0 Wallet