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DC Field | Value | Language |
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dc.contributor.author | Vivek, A. T. | - |
dc.contributor.author | Kumar, Shailesh | - |
dc.date.accessioned | 2024-08-01T10:07:26Z | - |
dc.date.available | 2024-08-01T10:07:26Z | - |
dc.date.issued | 2024 | - |
dc.identifier.citation | Methods in Molecular Biology, 2812: 307-315 | en_US |
dc.identifier.isbn | 978-1-0716-3885-9 | - |
dc.identifier.isbn | 978-1-0716-3886-6 | - |
dc.identifier.other | https://doi.org/10.1007/978-1-0716-3886-6_17 | - |
dc.identifier.uri | https://link.springer.com/protocol/10.1007/978-1-0716-3886-6_17 | - |
dc.identifier.uri | http://223.31.159.10:8080/jspui/handle/123456789/1633 | - |
dc.description | Accepted date: 28 July 2024 | en_US |
dc.description.abstract | Plants have developed sophisticated defense mechanisms to combat viral infections, prominently utilizing Dicer-like enzymes (DCL) for generating virus-derived small interfering RNAs (vsiRNAs) through RNA interference (RNAi). This intrinsic mechanism effectively impedes virus replication. Exploiting their potential, vsiRNAs have become a major focus area for comprehensive viral investigations in plants, integrating both bioinformatics and experimental strategies. This chapter introduces an up-to-date computational workflow optimized for identifying and comprehensively annotating vsiRNAs with the utilization of small RNA sequencing (sRNA-seq) data collected from virus-infected plants. The workflow detailed in this chapter centers on known plant-targeting viruses, providing step-by-step guidance to enhance vsiRNA analysis, ultimately advancing the comprehension of plant-virus interactions. | en_US |
dc.language.iso | en_US | en_US |
dc.publisher | Springer Nature Publishing AG | en_US |
dc.subject | RNAs (vsiRNAs) | en_US |
dc.subject | sRNA-Seq Samples | en_US |
dc.title | Identification of virus-derived small interfering RNAs (vsiRNAs) from infected sRNA-Seq samples | en_US |
dc.type | Article | en_US |
Appears in Collections: | Institutional Publications |
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