Dataset Information

In silico prediction of cotton (Gossypium hirsutum) encoded microRNAs targets in the genome of Cotton leaf curl Allahabad virus.

ABSTRACT: Cotton leaf curl Allahabad virus (CLCuAV) belongs to genus Begomovirus, family Geminiviridae. It has single stranded monopartite DNA genome transmitted by whitefly (Bemisia tabaci). MicroRNAs (miRNAs) belong to class of endogeneous small RNAs which suppress expression of genes following cleavage or translational inhibition of target messenger RNAs. They are demonstrated to be involved in a number of plant processes such as, development, biotic and abiotic stresses. Employing in silico approach, high scoring miRNA-target pairs satisfying rules of minimum free energy and maximum complementarity were selected to investigate if they possess the potential to bind the genome CLCuAV. Our results revealed that miRNA species viz., ghr-miR2950 can target all the viral genes, ghr-miR408 targets overlapping transcripts of AC1 and AC2 genes; while ghr-miR394 and ghr-miR395a and miR395d could bind overlapping transcripts of AC1 and AC4 genes. This is the first report of prediction of cotton miRNAs which have the potential to target CLCuAV genes including AC1 and AC4, involved in viral replication and gene silencing suppression, respectively.

SUBMITTER: Shweta

PROVIDER: S-EPMC4070032 | biostudies-literature | 2014

REPOSITORIES: biostudies-literature

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In silico prediction of cotton (Gossypium hirsutum) encoded microRNAs targets in the genome of Cotton leaf curl Allahabad virus.

Shweta Khan Jawaid A JA

Bioinformation 20140520 5

Cotton leaf curl Allahabad virus (CLCuAV) belongs to genus Begomovirus, family Geminiviridae. It has single stranded monopartite DNA genome transmitted by whitefly (Bemisia tabaci). MicroRNAs (miRNAs) belong to class of endogeneous small RNAs which suppress expression of genes following cleavage or translational inhibition of target messenger RNAs. They are demonstrated to be involved in a number of plant processes such as, development, biotic and abiotic stresses. Employing in silico approach, ...[more]

PMID: 24966530

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Project description:Cotton is a commercial and economically important crop that generates billions of dollars in annual revenue worldwide. However, cotton yield is affected by a sap-sucking insect Bemisia tabaci (whitefly), and whitefly-borne cotton leaf curl disease (CLCuD). The causative agent of devastating CLCuD is led by the viruses belonging to the genus Begomovirus (family Geminiviridae), collectively called cotton leaf curl viruses. Unfortunately, the extensively cultivated cotton (Gossypium hirsutum) species are highly susceptible and vulnerable to CLCuD. Yet, the concomitant influence of whitefly and CLCuD on the susceptible G. hirsutum transcriptome has not been interpreted. In the present study we have employed an RNA Sequencing (RNA-Seq) transcriptomics approach to explore the differential gene expression in susceptible G. hirsutum variety upon infection with viruliferous whiteflies. Comparative RNA-Seq of control and CLCuD infected plants was done using Illumina HiSeq 2500. This study yielded 468 differentially expressed genes (DEGs). Among them, we identified 220 up and 248 downregulated DEGs involved in disease responses and pathogen defense. We selected ten genes for downstream RT-qPCR analyses on two cultivars, Karishma and MNH 786 that are susceptible to CLCuD. We observed a similar expression pattern of these genes in both susceptible cultivars that was also consistent with our transcriptome data further implying a wider application of our global transcription study on host susceptibility to CLCuD. We next performed weighted gene co-expression network analysis that revealed six modules. This analysis also identified highly co-expressed genes as well as 55 hub genes that co-express with ≥ 50 genes. Intriguingly, most of these hub genes are shown to be downregulated and enriched in cellular processes. Under-expression of such highly co-expressed genes suggests their roles in favoring the virus and enhancing plant susceptibility to CLCuD. We also discuss the potential mechanisms governing the establishment of disease susceptibility. Overall, our study provides a comprehensive differential gene expression analysis of G. hirsutum under whitefly-mediated CLCuD infection. This vital study will advance the understanding of simultaneous effect of whitefly and virus on their host and aid in identifying important G. hirsutum genes which intricate in its susceptibility to CLCuD.

Project description:Papaya leaf curl disease (PaLCuD) is widespread and classified in the genus begomovirus (Geminiviridae), disseminated by the vector whitefly Bemisia tabaci. RNA interference (RNAi)-based antiviral innate immunity stands as a pivotal defense mechanism and biological process in limiting viral genomes to manage plant diseases. The current study aims to identify and analyze Carica Papaya locus-derived capa-microRNAs with predicted potential for targeting divergent begomovirus species-encoded mRNAs using a 'four integrative in silico algorithms' approach. This research aims to experimentally activate the RNAi catalytic pathway using in silico-predicted endogenous capa-miRNAs and create papaya varieties capable of assessing potential resistance against begomovirus species and monitoring antiviral capabilities. This study identified 48 predicted papaya locus-derived candidates from 23 miRNA families, which were further investigated for targeting begomovirus genes. Premised all the four algorithms combined, capa-miR5021 was the most anticipated miRNA followed by capa-miR482, capa-miR5658, capa-miR530b, capa-miR3441.2, and capa-miR414 'effective' papaya locus-derived candidate capa-miRNA and respected putative binding sites for targets at the consensus nucleotide position. It was predicted to bind and target mostly to AC1 gene of the complementary strand and the AV1 gene of the virion strand of different begomovirus isolates, which were associated with replication-associated protein and encapsidation, respectively, during PaLCuD. These miRNAs were also found targeting betaC1 gene of betasatellite which were associated with retardation in leaf growth and developmental abnormalities with severe symptoms during begomovirus infection. To validate target prediction accuracy, we created an integrated Circos plot for comprehensive visualization of host-virus interaction. In silico-predicted papaya genome-wide miRNA-mediated begomovirus target gene regulatory network corroborated interactions that permit in vivo analysis, which could provide biological material and valuable evidence, leading to the development of begomovirus-resistant papaya plants. The integrative nature of our research positions it at the forefront of efforts to ensure the sustainable cultivation of papaya, particularly in the face of evolving pathogenic threats. As we move forward, the knowledge gained from this study provides a solid foundation for continued exploration and innovation in the field of papaya virology, and to the best of our knowledge, this study represents a groundbreaking endeavor, undertaken for the first time in the context of PaLCuD research.

Dataset Information

In silico prediction of cotton (Gossypium hirsutum) encoded microRNAs targets in the genome of Cotton leaf curl Allahabad virus.

Publications

In silico prediction of cotton (Gossypium hirsutum) encoded microRNAs targets in the genome of Cotton leaf curl Allahabad virus.

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