Girish Kumar Gupta

Plant miRNAome and antiviral resistance: a retrospective view and prospective challenges.

MicroRNAs (miRNAs) are small regulatory RNAs that play a defining role in post-transcriptional gene silencing of eukaryotes by either mRNA cleavage or translational inhibition. Plant miRNAs have been implicated in innumerable growth and developmental processes that extend beyond their ability to respond to biotic and abiotic stresses. Active in an organism’s immune defence response, host miRNAs display a propensity to target viral genomes. During viral invasion, these virus-targeting miRNAs can be identified by their altered expression. All the while, pathogenic viruses, as a result of their long-term interaction with plants, have been evolving viral suppressors of RNA silencing (VSRs), as well as viral-encoded miRNAs as a counter-defence strategy. However, the gene silencing attribute of miRNAs has been ingeniously manipulated to down-regulate the expression of any gene of interest, including VSRs, in artificial miRNA (amiRNA)-based transgenics. Since we currently have a better understanding of the intricacies of miRNA-mediated gene regulation in plant–virus interactions, the majority of miRNAs manipulated to confer antiviral resistance to date are in plants. This review will share the insights gained from the studies of plant-virus combat and from the endeavour to manipulate miRNAs, including prospective challenges in the context of the evolutionary dynamics of the viral genome. Next generation sequencing technologies and bioinformatics analysis will further delineate the molecular details of host–virus interactions. The need for appropriate environmental risk assessment principles specific to amiRNA-based virus resistance is also discussed.

An intelligent multimedia interface for fuzzy-logic based inference in crops

The paper reports an interface designed for three subsystems-the knowledge acquisition subsystem with dynamic disease knowledge base, intelligent disease diagnosis subsystem with object-oriented intelligent-inference model and intelligent tutor for crop disease with audio-visual graphical user web-interface. The paper describes the design features; functionality and development of intelligent multimedia web interface. The results of its evaluation are also presented. A novel approach of rule promotion based on fuzzy logic is used in the system for drawing intelligent inferences for crop disease management. A text-to-speech (TTS) converter is used for providing capability of text-to-talking user interface. It provides the highly-effective interactive user interface on web for live interactions. It helps significantly and gives solutions of plant pathological problems in short spell. The application software is built using the Microsoft .NET framework, ASP.NET web-application framework provided in Visual Studio.NET. The Microsoft Speech SDK (5.1) is used to develop text to voice multimedia interface. The dynamic knowledge base is implemented using SQL server.

Molecular Diversity Analysis of Coat Protein Gene Encoded by Legume Begomoviruses and PCR Assay to Detect Yellow Mosaic Viruses Infecting Soybean in India

Aim: Coat protein (CP) genes encoded by Legume yellow mosaic viruses (LYMVs) were analysed to study molecular diversity and to devise effective PCR based assay to distinguish major Begomovirus species ( Mungbean yellow mosaic India virus and Mungbean yellow mosaic virus ) infecting soybean Design of the Study: All the known coat protein gene sequences encoded by begomoviruses causing yellow mosaic disease (YMD) in legumes were obtained from GenBank. YMD infected soybean leaf samples were collected from different parts of India during Kharif 2012 and species of virus infections identified using CP gene based primers in a PCR assay.

KMSCD: Knowledge management system for crop diseases

This paper presents a knowledge management system for crop disease. The aim of KMSCD is to provide a knowledge management tool for efficient knowledge acquisition, storage, knowledge engineering, processing and proper maintenance of knowledge that can be ultimately used by the diagnostic expert system. The development of the KMSCD simplifies the complete process of knowledge management by providing user-friendly interface to the domain expert for entering and storing the domain specific knowledge to solve the disease identification and control problem particularly for oilseeds crops. The system presently applies to the knowledge management of 25 prevalent diseases of three major oilseeds crops of India viz. soybean, groundnut and rapeseed mustard. The adopted development methodology and the experience acquired in the knowledge engineering and development of knowledge management system for crop disease are discussed in this paper.