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      Transcriptomic Changes of Bemisia tabaci Asia II 1 Induced by Chilli Leaf Curl Virus Trigger Infection and Circulation in Its Vector

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          Abstract

          Bemisia tabaci (Hemiptera: Aleyrodidae) is a highly efficient vector in the spread of chilli leaf curl virus (ChiLCV, Begomovirus) which is a major constraint in the production of chilli in South Asia. Transcriptome analysis of B. tabaci post-6 h acquisition of ChiLCV showed differential expression of 80 (29 upregulated and 51 downregulated) genes. The maximum number of DEGs are categorized under the biological processes category followed by cellular components and molecular functions. KEGG analysis of DEGs showed that the genes are involved in the functions like metabolism, signaling pathways, cellular processes, and organismal systems. The expression of highly expressed 20 genes post-ChiLCV acquisition was validated in RT-qPCR. DEGs such as cytosolic carboxypeptidase 3, dual-specificity protein phosphatase 10, 15, dynein axonemal heavy chain 17, fasciclin 2, inhibin beta chain, replication factor A protein 1, and Tob1 were found enriched and favored the virus infection and circulation in B. tabaci. The present study provides an improved understanding of the networks of molecular interactions between B. tabaci and ChiLCV. The candidate genes of B. tabaci involved in ChiLCV transmission would be novel targets for the management of the B. tabaci-begomovirus complex.

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          Analysis of relative gene expression data using real-time quantitative PCR and the 2(-Delta Delta C(T)) Method.

          The two most commonly used methods to analyze data from real-time, quantitative PCR experiments are absolute quantification and relative quantification. Absolute quantification determines the input copy number, usually by relating the PCR signal to a standard curve. Relative quantification relates the PCR signal of the target transcript in a treatment group to that of another sample such as an untreated control. The 2(-Delta Delta C(T)) method is a convenient way to analyze the relative changes in gene expression from real-time quantitative PCR experiments. The purpose of this report is to present the derivation, assumptions, and applications of the 2(-Delta Delta C(T)) method. In addition, we present the derivation and applications of two variations of the 2(-Delta Delta C(T)) method that may be useful in the analysis of real-time, quantitative PCR data. Copyright 2001 Elsevier Science (USA).
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            KAAS: an automatic genome annotation and pathway reconstruction server

            The number of complete and draft genomes is rapidly growing in recent years, and it has become increasingly important to automate the identification of functional properties and biological roles of genes in these genomes. In the KEGG database, genes in complete genomes are annotated with the KEGG orthology (KO) identifiers, or the K numbers, based on the best hit information using Smith–Waterman scores as well as by the manual curation. Each K number represents an ortholog group of genes, and it is directly linked to an object in the KEGG pathway map or the BRITE functional hierarchy. Here, we have developed a web-based server called KAAS (KEGG Automatic Annotation Server: http://www.genome.jp/kegg/kaas/) i.e. an implementation of a rapid method to automatically assign K numbers to genes in the genome, enabling reconstruction of KEGG pathways and BRITE hierarchies. The method is based on sequence similarities, bi-directional best hit information and some heuristics, and has achieved a high degree of accuracy when compared with the manually curated KEGG GENES database.
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              Evolution, Weighting, and Phylogenetic Utility of Mitochondrial Gene Sequences and a Compilation of Conserved Polymerase Chain Reaction Primers

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                Author and article information

                Contributors
                Journal
                Front Microbiol
                Front Microbiol
                Front. Microbiol.
                Frontiers in Microbiology
                Frontiers Media S.A.
                1664-302X
                28 April 2022
                2022
                : 13
                : 890807
                Affiliations
                [1] 1Advanced Centre for Plant Virology, Indian Agricultural Research Institute , New Delhi, India
                [2] 2Division of Entomology, Indian Agricultural Research Institute , New Delhi, India
                [3] 3Centre for Agricultural Bioinformatics, Indian Agricultural Statistics Research Institute , New Delhi, India
                Author notes

                Edited by: Sean Michael Prager, University of Saskatchewan, Canada

                Reviewed by: Susheel Kumar, National Botanical Research Institute (CSIR), India; Rajarshi Kumar Gaur, Deen Dayal Upadhyay Gorakhpur University, India

                This article was submitted to Virology, a section of the journal Frontiers in Microbiology

                Article
                10.3389/fmicb.2022.890807
                9096263
                35572639
                1fab1e50-4c29-4c96-8b0a-57434875abe0
                Copyright © 2022 Nekkanti, Chakraborty, Ghosh, Iquebal, Jaiswal and Baranwal.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

                History
                : 06 March 2022
                : 25 March 2022
                Page count
                Figures: 4, Tables: 2, Equations: 0, References: 82, Pages: 14, Words: 9738
                Categories
                Microbiology
                Original Research

                Microbiology & Virology
                chilcv,silverleaf whitefly,rna-seq,transcriptome,rt-qpcr,virus-vector relationship

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