Rice tungro disease is caused by a combination of two viruses: Rice tungro spherical virus and Rice tungro bacilliform virus (RTBV). This study was performed with the objective to decipher the molecular variability and evolution of RTBV isolates present in the tungro-affected states of Indian subcontinent. Phylogenetic analysis based on ORF-I, ORF-II, and ORF-IV sequences showed distinct divergence of Indian RTBV isolates into two groups; one consisted isolates from Hyderabad (Andhra Pradesh), Cuttack (Orissa), and Puducherry and another from West Bengal, Chinsura West Bengal, and Kanyakumari (Tamil Nadu). The results obtained from phylogenetic analysis were further supported with the single nucleotide polymorphisms (SNPs), insertion and deletion (INDELs) and evolutionary distance analysis. In addition, sequence difference count matrix revealed a maximum of 56 (ORF-I), 13 (ORF-II) and 73 (ORF-IV) nucleotides differences among all the Indian RTBV isolates taken in this study. However, at the protein level these differences were not significant as revealed by K (a)/K (s) ratio calculation. Sequence identity at nucleotide and amino acid level was 92-100 % (ORF-I), 96-100 % (ORF-II), 94-100 % (ORF-IV) and 86-100 % (ORF-I), 98-100 % (ORF-II) and 95-100 % (ORF-IV), respectively, among Indian isolates of RTBV. The divergence of RTBV isolates into two independent clusters of Indian and non-Indian was shown with the help of the data obtained from phylogeny, SNPs, and INDELs, evolutionary distance analysis, and conserved motifs analysis. The important role of ORF-I and ORF-IV in RTBV diversification and adaptation to different rice growing regions is also discussed.
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Sci Rep
December 2024
Information Technology Department, Faculty of Computers and Information, Mansoura University, Mansoura, 35516, Egypt.
The rice plant is one of the most significant crops in the world, and it suffers from various diseases. The traditional methods for rice disease detection are complex and time-consuming, mainly depending on the expert's experience. The explosive growth in image processing, computer vision, and deep learning techniques provides effective and innovative agriculture solutions for automatically detecting and classifying these diseases.
View Article and Find Full Text PDFPlant Methods
October 2024
Faculty of Engineering, Computing and Science, Swinburne University of Technology Sarawak Campus, Q5B, 93350, Kuching, Malaysia.
This study explores the application of Artificial Intelligence (AI), specifically Convolutional Neural Networks (CNNs), for detecting rice plant diseases using ARM Cortex-M microprocessors. Given the significant role of rice as a staple food, particularly in Malaysia where the rice self-sufficiency ratio dropped from 65.2% in 2021 to 62.
View Article and Find Full Text PDFMethods Mol Biol
July 2024
Agricultural Biotechnology Research Center, Academia Sinica, Taipei, Taiwan.
Phloem-specific promoter efficiently triggers graft-transmissible RNA interference (gtRNAi). We leveraged a phloem-specific promoter derived from the Rice tungro bacilliform virus, optimizing the RNAi mechanism's efficiency and specificity. Here, we detail the construction of phloem-specific promoter-based gtRNAi system and its application through grafting experiments, demonstrating its effectiveness in inducing tomato yellow leaf curl Thailand virus (TYLCHTV) resistance in non-transgenic scions.
View Article and Find Full Text PDFFront Plant Sci
January 2024
College of Artificial Intelligence, Nanjing Agricultural University, Nanjing, China.
Classification of rice disease is one significant research topics in rice phenotyping. Recognition of rice diseases such as , , , , and are a critical research field in rice phenotyping. However, accurately identifying these diseases is a challenging issue due to their high phenotypic similarity.
View Article and Find Full Text PDFVirus Genes
February 2024
Department of Plant Molecular Biology, University of Delhi South Campus, New Delhi, 110021, India.
Plant hosts and their viral pathogens are engaged in a constant cycle of defense and counter-defense as part of a molecular arms race, principal among them being the plant RNAi defense and the viral RNAi suppressor counter-defense. Rice tungro bacilliform virus (RTBV), member of the family Caulimoviridae, genus Tungrovirus, species Tungrovirus oryzae, infects rice in South- and Southeast Asia and causes severe symptoms of stunting, yellow-orange discoloration and twisting of leaf tips. To better understand the possible counter-defensive roles of RTBV against the host RNAi defense system, we explored the ability of the P4 protein of an Indian isolate of RTBV to act as a possible modulator of RNAi.
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