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      Omega-3 fatty acid desaturase gene family from two ω-3 sources, Salvia hispanica and Perilla frutescens: Cloning, characterization and expression

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          Abstract

          Omega-3 fatty acid desaturase (ω-3 FAD, D15D) is a key enzyme for α-linolenic acid (ALA) biosynthesis. Both chia ( Salvia hispanica) and perilla ( Perilla frutescens) contain high levels of ALA in seeds. In this study, the ω-3 FAD gene family was systematically and comparatively cloned from chia and perilla. Perilla FAD3, FAD7, FAD8 and chia FAD7 are encoded by single-copy (but heterozygous) genes, while chia FAD3 is encoded by 2 distinct genes. Only 1 chia FAD8 sequence was isolated. In these genes, there are 1 to 6 transcription start sites, 1 to 8 poly(A) tailing sites, and 7 introns. The 5’UTRs of PfFAD8a/ b contain 1 to 2 purine-stretches and 2 pyrimidine-stretches. An alternative splice variant of ShFAD7a/ b comprises a 5’UTR intron. Their encoded proteins harbor an FA_desaturase conserved domain together with 4 trans-membrane helices and 3 histidine boxes. Phylogenetic analysis validated their identity of dicot microsomal or plastidial ω-3 FAD proteins, and revealed some important evolutionary features of plant ω-3 FAD genes such as convergent evolution across different phylums, single-copy status in algae, and duplication events in certain taxa. The qRT-PCR assay showed that the ω-3 FAD genes of two species were expressed at different levels in various organs, and they also responded to multiple stress treatments. The functionality of the ShFAD3 and PfFAD3 enzymes was confirmed by yeast expression. The systemic molecular and functional features of the ω-3 FAD gene family from chia and perilla revealed in this study will facilitate their use in future studies on genetic improvement of ALA traits in oilseed crops.

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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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            SMART: recent updates, new developments and status in 2015

            SMART (Simple Modular Architecture Research Tool) is a web resource (http://smart.embl.de/) providing simple identification and extensive annotation of protein domains and the exploration of protein domain architectures. In the current version, SMART contains manually curated models for more than 1200 protein domains, with ∼200 new models since our last update article. The underlying protein databases were synchronized with UniProt, Ensembl and STRING, bringing the total number of annotated domains and other protein features above 100 million. SMART's ‘Genomic’ mode, which annotates proteins from completely sequenced genomes was greatly expanded and now includes 2031 species, compared to 1133 in the previous release. SMART analysis results pages have been completely redesigned and include links to several new information sources. A new, vector-based display engine has been developed for protein schematics in SMART, which can also be exported as high-resolution bitmap images for easy inclusion into other documents. Taxonomic tree displays in SMART have been significantly improved, and can be easily navigated using the integrated search engine.
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              Lipid biosynthesis.

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                Author and article information

                Contributors
                Role: ConceptualizationRole: Formal analysisRole: InvestigationRole: MethodologyRole: SoftwareRole: ValidationRole: Writing – original draftRole: Writing – review & editing
                Role: InvestigationRole: Validation
                Role: Investigation
                Role: Validation
                Role: Validation
                Role: Investigation
                Role: Investigation
                Role: Resources
                Role: ConceptualizationRole: Data curationRole: Formal analysisRole: Funding acquisitionRole: MethodologyRole: Project administrationRole: ResourcesRole: SoftwareRole: ValidationRole: Writing – review & editing
                Role: Editor
                Journal
                PLoS One
                PLoS ONE
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, CA USA )
                1932-6203
                19 January 2018
                2018
                : 13
                : 1
                : e0191432
                Affiliations
                [1 ] College of Agronomy and Biotechnology, Southwest University, Chongqing, China
                [2 ] Academy of Agricultural Sciences, Southwest University, Chongqing, China
                [3 ] Chongqing Engineering Research Center for Rapeseed, Southwest University, Chongqing, China
                [4 ] Chongqing Key Laboratory of Crop Quality Improvement, Southwest University, Chongqing, China
                [5 ] Engineering Research Center of South Upland Agriculture of Ministry of Education, Southwest University, Chongqing, China
                Huazhong University of Science and Technology, CHINA
                Author notes

                Competing Interests: The authors have declared that no competing interests exist.

                Author information
                http://orcid.org/0000-0001-6611-624X
                Article
                PONE-D-17-21893
                10.1371/journal.pone.0191432
                5774782
                29351555
                187530e3-4850-41d8-85bb-0c8340c0aa34
                © 2018 Xue et al

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 25 June 2017
                : 4 January 2018
                Page count
                Figures: 6, Tables: 3, Pages: 25
                Funding
                Funded by: National Key R&D Program of China
                Award ID: 2016YFD0100506
                Award Recipient :
                Funded by: Fundamental Research Funds for the Central Universities
                Award ID: XDJK2014D009
                Award Recipient :
                Funded by: Chongqing Research Program of Basic Research and Frontier Technology
                Award ID: cstc2015jcyjBX0143
                Award Recipient :
                Funded by: National Basic Research Program of China (973 Program)
                Award ID: 2015CB150201
                Award Recipient :
                This work was supported by Chongqing Research Program of Basic Research and Frontier Technology (cstc2015jcyjBX0143), National Key R&D Program of China (2016YFD0100506), Fundamental Research Funds for the Central Universities (XDJK2014D009), and National Basic Research Program of China (973 Program, 2015CB150201).
                Categories
                Research Article
                Biology and Life Sciences
                Computational Biology
                Genome Complexity
                Introns
                Biology and Life Sciences
                Genetics
                Genomics
                Genome Complexity
                Introns
                Biology and Life Sciences
                Plant Science
                Plant Anatomy
                Seeds
                Research and Analysis Methods
                Experimental Organism Systems
                Model Organisms
                Saccharomyces Cerevisiae
                Research and Analysis Methods
                Model Organisms
                Saccharomyces Cerevisiae
                Biology and Life Sciences
                Organisms
                Eukaryota
                Fungi
                Yeast
                Saccharomyces
                Saccharomyces Cerevisiae
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                Cell Biology
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                Custom metadata
                All cloned genes are available from NCBI database (accession numbers:KX610645-KX610649; KX610652-KX610656; KX880387-KX880395). Other data were uploaded as supplementary files.

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