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      Transcriptome and Flavonoids Metabolomic Analysis Identifies Regulatory Networks and Hub Genes in Black and White Fruits of Lycium ruthenicum Murray

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          Abstract

          Lycium ruthenicum Murry. is a highly nutritional cash crop due to its fruit abundant anthocyanins. To understand the complex metabolic networks underlying the color formation in black and white fruits of L. ruthenicum, we conducted transcriptome and flavonoid metabolic profiling to identify the candidate genes possibly involved in flavonoid biosynthesis. As a result, 147 flavonoids were identified and there was almost no anthocyanin in white fruits, while luteolin, kaempferol, and quercetin derivatives showed markedly higher abundance. Furthermore, applying weighted gene co-expression network analyses, 3 MYB, 2 bHLH, 1WRKY and 1 NAC transcription factor, associated with anthocyanin biosynthesis were identified. A bHLH transcription factor, LrAN1b showed the greatest correlations with anthocyanin accumulation with no expression in white fruits. In addition, gene function analysis and qRT-PCR experiments identified a new activated anthocyanin MYB transcription factor designed as LrAN2-like. Yeast two-hybrid and transient tobacco overexpression experiments showed that LrAN1b could interact with LrAN2-like and LrAN11 to form MBW complex to activate the anthocyanin pathway. The yeast one-hybrid experiment indicated that LrAN2-like bonded anthocyanin structural gene LrDFR and LrANS promoters. Heterologous expression of LrAN1b in tobacco can significantly increase the anthocyanin content of tobacco florals and capsules, and activate anthocyanin synthesis related genes. Taken together, an anthocyanin regulatory network model in L. ruthenicum fruit was proposed firstly and we speculate that the white fruit phenotype was due to abnormal expression of LrAN1b. The findings provide new insight into the underlying mechanism of flavonoids, laying the foundation for future functional and molecular biological research in L. ruthenicum.

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          Automated genome annotation and pathway identification using the KEGG Orthology (KO) as a controlled vocabulary.

          High-throughput technologies such as DNA sequencing and microarrays have created the need for automated annotation of large sets of genes, including whole genomes, and automated identification of pathways. Ontologies, such as the popular Gene Ontology (GO), provide a common controlled vocabulary for these types of automated analysis. Yet, while GO offers tremendous value, it also has certain limitations such as the lack of direct association with pathways. We demonstrated the use of the KEGG Orthology (KO), part of the KEGG suite of resources, as an alternative controlled vocabulary for automated annotation and pathway identification. We developed a KO-Based Annotation System (KOBAS) that can automatically annotate a set of sequences with KO terms and identify both the most frequent and the statistically significantly enriched pathways. Results from both whole genome and microarray gene cluster annotations with KOBAS are comparable and complementary to known annotations. KOBAS is a freely available stand-alone Python program that can contribute significantly to genome annotation and microarray analysis.
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            Flavonoids: biosynthesis, biological functions, and biotechnological applications

            Flavonoids are widely distributed secondary metabolites with different metabolic functions in plants. The elucidation of the biosynthetic pathways, as well as their regulation by MYB, basic helix-loop-helix (bHLH), and WD40-type transcription factors, has allowed metabolic engineering of plants through the manipulation of the different final products with valuable applications. The present review describes the regulation of flavonoid biosynthesis, as well as the biological functions of flavonoids in plants, such as in defense against UV-B radiation and pathogen infection, nodulation, and pollen fertility. In addition, we discuss different strategies and achievements through the genetic engineering of flavonoid biosynthesis with implication in the industry and the combinatorial biosynthesis in microorganisms by the reconstruction of the pathway to obtain high amounts of specific compounds.
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              HMDB 3.0—The Human Metabolome Database in 2013

              The Human Metabolome Database (HMDB) (www.hmdb.ca) is a resource dedicated to providing scientists with the most current and comprehensive coverage of the human metabolome. Since its first release in 2007, the HMDB has been used to facilitate research for nearly 1000 published studies in metabolomics, clinical biochemistry and systems biology. The most recent release of HMDB (version 3.0) has been significantly expanded and enhanced over the 2009 release (version 2.0). In particular, the number of annotated metabolite entries has grown from 6500 to more than 40 000 (a 600% increase). This enormous expansion is a result of the inclusion of both ‘detected’ metabolites (those with measured concentrations or experimental confirmation of their existence) and ‘expected’ metabolites (those for which biochemical pathways are known or human intake/exposure is frequent but the compound has yet to be detected in the body). The latest release also has greatly increased the number of metabolites with biofluid or tissue concentration data, the number of compounds with reference spectra and the number of data fields per entry. In addition to this expansion in data quantity, new database visualization tools and new data content have been added or enhanced. These include better spectral viewing tools, more powerful chemical substructure searches, an improved chemical taxonomy and better, more interactive pathway maps. This article describes these enhancements to the HMDB, which was previously featured in the 2009 NAR Database Issue. (Note to referees, HMDB 3.0 will go live on 18 September 2012.).
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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
                14 August 2020
                2020
                : 11
                : 1256
                Affiliations
                [1] 1 Key Laboratory of Bio-Resources and Eco-Environment of Ministry of Education, College of Life Sciences, Sichuan University , Chengdu, China
                [2] 2 Institute of Wolfberry Engineering Technology, Ningxia Academy of Agriculture and Forestry Sciences , Yinchuan, China
                [3] 3 National Wolfberry Engineering Technology Research Center , Yinchuan, China
                Author notes

                Edited by: Cristina Garcia-Viguera, Consejo Superior de Investigaciones Científicas (CSIC), Spain

                Reviewed by: Shouchuang Wang, Hainan University, China; Atsushi Fukushima, RIKEN, Japan

                *Correspondence: Youlong Cao, youlongchk@ 123456163.com ; Lin Tang, tangl666@ 123456126.com

                †These authors have contributed equally to this work

                This article was submitted to Plant Metabolism and Chemodiversity, a section of the journal Frontiers in Plant Science

                Article
                10.3389/fpls.2020.01256
                7456873
                7de2a9c4-c4d2-4b4f-8b17-7ed726a435ca
                Copyright © 2020 Li, Fan, Qin, Dai, Li, Li, Wang, Yin, Chen, Qin, Cao and Tang

                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
                : 02 May 2020
                : 30 July 2020
                Page count
                Figures: 10, Tables: 0, Equations: 0, References: 72, Pages: 19, Words: 10654
                Funding
                Funded by: National Natural Science Foundation of China 10.13039/501100001809
                Categories
                Plant Science
                Original Research

                Plant science & Botany
                anthocyanin,fruits,flavonoid,lycium ruthenicum,metabolic profiling,transcriptome

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