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      Effects of Elevated CO 2 on Photosynthetic Accumulation, Sucrose Metabolism-Related Enzymes, and Genes Identification in Goji Berry ( Lycium barbarum L.)

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          Abstract

          Goji berry ( Lycium barbarum L.) exposure to elevated CO 2 (eCO 2) for long periods reduces their sugar and secondary metabolite contents. However, sugar accumulation in fruit depends on photosynthesis and photoassimilate partitioning. This study aimed to explore photosynthesis, sugar content, and sucrose metabolism-related enzyme activities in goji berry leaves and fruits under ambient and eCO 2 levels, and identify the genes encoding L. barbarum acid invertase ( LBAI), L. barbarum sucrose synthase ( LBSS), L. barbarum sucrose phosphate synthase ( LBSPS), and L. barbarum neutral invertase ( LBNI), based on transcriptome profiling. Further, the characterization of four identified genes was analyzed including subcellular localization and expression patterns. In plants grown under eCO 2 for 90 or 120 days, the expression of the above-mentioned genes changed significantly as the photosynthetic rate increased. In addition, leaf and fruit sugar contents decreased, and the activities of four sucrose metabolism-related enzymes increased in leaves, while acid and neutral invertase increased in fruits. Protein sequence analysis demonstrated that LBAI and LBNI contain a conservative structure domain belonging to the glycosyl hydrolases (Glyco_hydro) family, and both LBSS and LBSPS belonging to the sucrose synthase (Sucrose_synth) and glycosyltransferase (Glycos_transf) family. Subcellular localization analysis showed that LBAI, LBNI, and LBSS were all located in the nucleus, plasma membrane, and cytoplasm, while LBSPS was located in the plasma membrane. The expressions of LBAI, LBSPS, and LBNI were high in the stems, whereas LBSS was predominantly expressed in the fruits. Our findings provide fundamental data on photosynthesis and sugar accumulation trends in goji berries under eCO 2 exposure.

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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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            GenBank

            GenBank® (http://www.ncbi.nlm.nih.gov) is a comprehensive database that contains publicly available nucleotide sequences for almost 260 000 formally described species. These sequences are obtained primarily through submissions from individual laboratories and batch submissions from large-scale sequencing projects, including whole-genome shotgun (WGS) and environmental sampling projects. Most submissions are made using the web-based BankIt or standalone Sequin programs, and GenBank staff assigns accession numbers upon data receipt. Daily data exchange with the European Nucleotide Archive (ENA) and the DNA Data Bank of Japan (DDBJ) ensures worldwide coverage. GenBank is accessible through the NCBI Entrez retrieval system, which integrates data from the major DNA and protein sequence databases along with taxonomy, genome, mapping, protein structure and domain information, and the biomedical journal literature via PubMed. BLAST provides sequence similarity searches of GenBank and other sequence databases. Complete bimonthly releases and daily updates of the GenBank database are available by FTP. To access GenBank and its related retrieval and analysis services, begin at the NCBI home page: www.ncbi.nlm.nih.gov.
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              Database indexing for production MegaBLAST searches

              Motivation: The BLAST software package for sequence comparison speeds up homology search by preprocessing a query sequence into a lookup table. Numerous research studies have suggested that preprocessing the database instead would give better performance. However, production usage of sequence comparison methods that preprocess the database has been limited to programs such as BLAT and SSAHA that are designed to find matches when query and database subsequences are highly similar. Results: We developed a new version of the MegaBLAST module of BLAST that does the initial phase of finding short seeds for matches by searching a database index. We also developed a program makembindex that preprocesses the database into a data structure for rapid seed searching. We show that the new ‘indexed MegaBLAST’ is faster than the ‘non-indexed’ version for most practical uses. We show that indexed MegaBLAST is faster than miBLAST, another implementation of BLAST nucleotide searching with a preprocessed database, for most of the 200 queries we tested. To deploy indexed MegaBLAST as part of NCBI'sWeb BLAST service, the storage of databases and the queueing mechanism were modified, so that some machines are now dedicated to serving queries for a specific database. The response time for such Web queries is now faster than it was when each computer handled queries for multiple databases. Availability: The code for indexed MegaBLAST is part of the blastn program in the NCBI C++ toolkit. The preprocessor program makembindex is also in the toolkit. Indexed MegaBLAST has been used in production on NCBI's Web BLAST service to search one version of the human and mouse genomes since October 2007. The Linux command-line executables for blastn and makembindex, documentation, and some query sets used to carry out the tests described below are available in the directory: ftp://ftp.ncbi.nlm.nih.gov/pub/agarwala/indexed_megablast Contact: schaffer@helix.nih.gov Supplementary information: Supplementary data are available at Bioinformatics online.
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                Author and article information

                Contributors
                Journal
                Front Plant Sci
                Front Plant Sci
                Front. Plant Sci.
                Frontiers in Plant Science
                Frontiers Media S.A.
                1664-462X
                11 March 2021
                2021
                : 12
                : 643555
                Affiliations
                [1] 1School of Agriculture, Ningxia University , Yinchuan, China
                [2] 2College of Forestry, Nanjing Forestry University , Nanjing, China
                Author notes

                Edited by: Sergio Tombesi, Catholic University of the Sacred Heart, Italy

                Reviewed by: Tse-Min Lee, National Sun Yat-sen University, Taiwan; Anthony Guihur, University of Lausanne, Switzerland; Gerhard Fischer, National University of Colombia, Colombia

                *Correspondence: Bing Cao, bingcao2006@ 123456126.com

                This article was submitted to Plant Abiotic Stress, a section of the journal Frontiers in Plant Science

                Article
                10.3389/fpls.2021.643555
                7991576
                33777078
                7b060290-5375-457e-aa0d-19e2eb75f6fa
                Copyright © 2021 Ma, Xie, Ha, Cao and Song.

                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
                : 18 December 2020
                : 16 February 2021
                Page count
                Figures: 8, Tables: 0, Equations: 0, References: 62, Pages: 15, Words: 10752
                Funding
                Funded by: National Natural Science Foundation of China 10.13039/501100001809
                Award ID: 31660199
                Award ID: 31160172
                Categories
                Plant Science
                Original Research

                Plant science & Botany
                lycium barbarum l.,photosynthesis,sucrose metabolism-related enzymes,subcellular localization,gene expression patterns

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