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      Characterization and analysis of CCR and CAD gene families at the whole-genome level for lignin synthesis of stone cells in pear ( Pyrus bretschneideri) fruit

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          ABSTRACT

          The content of stone cells has significant effects on the flavour and quality of pear fruit. Previous research suggested that lignin deposition is closely related to stone cell formation. In the lignin biosynthetic pathway, cinnamoyl-CoA reductase (CCR) and cinnamyl alcohol dehydrogenase (CAD), dehydrogenase/reductase family members, catalyse the last two steps in monolignol synthesis. However, there is little knowledge of the characteristics of the CCR and CAD families in pear and their involvement in lignin synthesis of stone cells. In this study, 31 CCRs and 26 CADs were identified in the pear genome. Phylogenetic trees for CCRs and CADs were constructed; key amino acid residues were analysed, and three-dimensional structures were predicted. Using quantitative real-time polymerase chain reaction (qRT-PCR), PbCAD2, PbCCR1, -2 and - 3 were identified as participating in lignin synthesis of stone cells in pear fruit. Subcellular localization analysis showed that the expressed proteins (PbCAD2, PbCCR1, -2 and -3) are found in the cytoplasm or at the cell membrane. These results reveal the evolutionary features of the CCR and CAD families in pear as well as the genes responsible for regulation of lignin synthesis and stone cell development in pear fruit.

          Abstract

          Summary: The characteristics of CCR and CAD families were systematically analyzed, and candidate members related to lignin synthesis and stone cell development were screened out in this study.

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          Most cited references 65

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

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          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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            MEGA5: molecular evolutionary genetics analysis using maximum likelihood, evolutionary distance, and maximum parsimony methods.

            Comparative analysis of molecular sequence data is essential for reconstructing the evolutionary histories of species and inferring the nature and extent of selective forces shaping the evolution of genes and species. Here, we announce the release of Molecular Evolutionary Genetics Analysis version 5 (MEGA5), which is a user-friendly software for mining online databases, building sequence alignments and phylogenetic trees, and using methods of evolutionary bioinformatics in basic biology, biomedicine, and evolution. The newest addition in MEGA5 is a collection of maximum likelihood (ML) analyses for inferring evolutionary trees, selecting best-fit substitution models (nucleotide or amino acid), inferring ancestral states and sequences (along with probabilities), and estimating evolutionary rates site-by-site. In computer simulation analyses, ML tree inference algorithms in MEGA5 compared favorably with other software packages in terms of computational efficiency and the accuracy of the estimates of phylogenetic trees, substitution parameters, and rate variation among sites. The MEGA user interface has now been enhanced to be activity driven to make it easier for the use of both beginners and experienced scientists. This version of MEGA is intended for the Windows platform, and it has been configured for effective use on Mac OS X and Linux desktops. It is available free of charge from http://www.megasoftware.net.
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              PlantCARE, a database of plant cis-acting regulatory elements and a portal to tools for in silico analysis of promoter sequences.

               M. Lescot (2002)
              PlantCARE is a database of plant cis-acting regulatory elements, enhancers and repressors. Regulatory elements are represented by positional matrices, consensus sequences and individual sites on particular promoter sequences. Links to the EMBL, TRANSFAC and MEDLINE databases are provided when available. Data about the transcription sites are extracted mainly from the literature, supplemented with an increasing number of in silico predicted data. Apart from a general description for specific transcription factor sites, levels of confidence for the experimental evidence, functional information and the position on the promoter are given as well. New features have been implemented to search for plant cis-acting regulatory elements in a query sequence. Furthermore, links are now provided to a new clustering and motif search method to investigate clusters of co-expressed genes. New regulatory elements can be sent automatically and will be added to the database after curation. The PlantCARE relational database is available via the World Wide Web at http://sphinx.rug.ac.be:8080/PlantCARE/.
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                Author and article information

                Journal
                Biol Open
                Biol Open
                bio
                biolopen
                Biology Open
                The Company of Biologists Ltd
                2046-6390
                15 November 2017
                15 November 2017
                15 November 2017
                : 6
                : 11
                : 1602-1613
                Affiliations
                [1 ]School of Life Science, Anhui Agricultural University , No. 130, Changjiang West Road, Hefei 230036, China
                [2 ]Horticultural Institute, Anhui Academy of Agricultural Sciences , Hefei, Anhui 230031, China
                Author notes
                [*]

                These authors contributed equally to this work

                []Author for correspondence ( ypcaiah@ 123456163.com )
                Article
                BIO026997
                10.1242/bio.026997
                5703608
                29141952
                © 2017. Published by The Company of Biologists Ltd

                This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution and reproduction in any medium provided that the original work is properly attributed.

                Product
                Funding
                Funded by: National Natural Science Foundation of China, http://dx.doi.org/10.13039/501100001809;
                Award ID: 31640068
                Funded by: Anhui Agriculture University, http://dx.doi.org/10.13039/501100006462;
                Award ID: 2017yjs-32
                Award ID: 201610364013
                Categories
                Research Article

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