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      Genome-Wide Identification and Characterization of Long Noncoding RNAs Involved in Chinese Wheat Mosaic Virus Infection of Nicotiana benthamiana

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          Recent studies have shown that a large number of long noncoding RNAs (lncRNAs) can regulate various biological processes in animals and plants. However, the roles of long non-coding RNAs (lncRNAs) in the interaction between plants and viruses is unclear, particularly for the Chinese wheat mosaic virus (CWMV) interaction. In this study, we used a deep RNA sequencing strategy to profile lncRNAs involved in the response to CWMV infection in Nicotiana benthamiana and analyzed differentially expressed lncRNAs that responded to CWMV infection, using a bioinformatics method. We identified 1175 new lncRNAs in N. benthamiana infected with CWMV, with 65 lncRNAs showing differential expression. These lncRNAs were mainly enriched in plant hormone signal transduction and other pathways according to GO and KEGG pathway enrichment analyses. In addition, differential expression of XLOC_006393 after CWMV infection may be the precursor of NbmiR168c, which can respond to CWMV infection by modulating the expression of its target gene NbAGO1. We believe that our study makes a significant contribution to the literature because these results provide a valuable resource for studying lncRNAs involved in CWMV infection and improving the understanding of the molecular mechanism of CWMV infection.

          Abstract

          Recent studies have shown that a large number of long noncoding RNAs (lncRNAs) can regulate various biological processes in animals and plants. Although lncRNAs have been identified in many plants, they have not been reported in the model plant Nicotiana benthamiana. Particularly, the role of lncRNAs in plant virus infection remains unknown. In this study, we identified lncRNAs in N. benthamiana response to Chinese wheat mosaic virus (CWMV) infection by RNA sequencing. A total of 1175 lncRNAs, including 65 differentially expressed lncRNAs, were identified during CWMV infection. We then analyzed the functions of some of these differentially expressed lncRNAs. Interestingly, one differentially expressed lncRNA, XLOC_006393, was found to participate in CWMV infection as a precursor to microRNAs in N. benthamiana. These results suggest that lncRNAs play an important role in the regulatory network of N. benthamiana in response to CWMV infection.

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          Most cited references48

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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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            RSEM: accurate transcript quantification from RNA-Seq data with or without a reference genome

            Background RNA-Seq is revolutionizing the way transcript abundances are measured. A key challenge in transcript quantification from RNA-Seq data is the handling of reads that map to multiple genes or isoforms. This issue is particularly important for quantification with de novo transcriptome assemblies in the absence of sequenced genomes, as it is difficult to determine which transcripts are isoforms of the same gene. A second significant issue is the design of RNA-Seq experiments, in terms of the number of reads, read length, and whether reads come from one or both ends of cDNA fragments. Results We present RSEM, an user-friendly software package for quantifying gene and isoform abundances from single-end or paired-end RNA-Seq data. RSEM outputs abundance estimates, 95% credibility intervals, and visualization files and can also simulate RNA-Seq data. In contrast to other existing tools, the software does not require a reference genome. Thus, in combination with a de novo transcriptome assembler, RSEM enables accurate transcript quantification for species without sequenced genomes. On simulated and real data sets, RSEM has superior or comparable performance to quantification methods that rely on a reference genome. Taking advantage of RSEM's ability to effectively use ambiguously-mapping reads, we show that accurate gene-level abundance estimates are best obtained with large numbers of short single-end reads. On the other hand, estimates of the relative frequencies of isoforms within single genes may be improved through the use of paired-end reads, depending on the number of possible splice forms for each gene. Conclusions RSEM is an accurate and user-friendly software tool for quantifying transcript abundances from RNA-Seq data. As it does not rely on the existence of a reference genome, it is particularly useful for quantification with de novo transcriptome assemblies. In addition, RSEM has enabled valuable guidance for cost-efficient design of quantification experiments with RNA-Seq, which is currently relatively expensive.
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              Long non-coding RNAs: insights into functions.

              In mammals and other eukaryotes most of the genome is transcribed in a developmentally regulated manner to produce large numbers of long non-coding RNAs (ncRNAs). Here we review the rapidly advancing field of long ncRNAs, describing their conservation, their organization in the genome and their roles in gene regulation. We also consider the medical implications, and the emerging recognition that any transcript, regardless of coding potential, can have an intrinsic function as an RNA.
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                Author and article information

                Journal
                Biology (Basel)
                Biology (Basel)
                biology
                Biology
                MDPI
                2079-7737
                17 March 2021
                March 2021
                : 10
                : 3
                : 232
                Affiliations
                [1 ]College of Plant Protection, Hunan Agricultural University, Changsha 410128, China; rancki@ 123456163.com (W.Z.); Huhdfs@ 123456163.com (H.H.); hnnydxluqisen@ 123456163.com (Q.L.); PengJ0310@ 123456163.com (P.J.); cln7471lcy@ 123456163.com (L.C.); cailinhu1952@ 123456163.com (C.H.)
                [2 ]State Key Laboratory for Quality and Safety of Agro-Products, Institute of Plant Virology, Ningbo University, Ningbo 315211, China; yangjian@ 123456nbu.edu.cn
                Author notes
                [* ]Correspondence: daily@ 123456hunau.net (L.D.); chenjianping@ 123456nbu.edu.cn (J.C.)
                [†]

                These authors contributed equally to this work.

                Article
                biology-10-00232
                10.3390/biology10030232
                8002735
                c395e6b6-b7fa-45c1-ad47-97e6165e634e
                © 2021 by the authors.

                Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ( http://creativecommons.org/licenses/by/4.0/).

                History
                : 20 January 2021
                : 11 March 2021
                Categories
                Article

                long non-coding rna,chinese wheat mosaic virus,microrna target,rna-sequencing

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