Genome-wide characterization of 2-oxoglutarate and Fe(II)-dependent dioxygenase family genes in tomato during growth cycle and their roles in metabolism

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Abstract

Background

2-Oxoglutarate and Fe(II)-dependent dioxygenases (2ODDs) belong to the 2-oxoglutarate-dependent dioxygenase (2OGD) superfamily and are involved in various vital metabolic pathways of plants at different developmental stages. These proteins have been extensively investigated in multiple model organisms. However, these enzymes have not been systematically analyzed in tomato. In addition, type I flavone synthase (FNSI) belongs to the 2ODD family and contributes to the biosynthesis of flavones, but this protein has not been characterized in tomato.

Results

A total of 131 2ODDs from tomato were identified and divided into seven clades by phylogenetic classification. The Sl2ODDs in the same clade showed similar intron/exon distributions and conserved motifs. The Sl2ODDs were unevenly distributed across the 12 chromosomes, with different expression patterns among major tissues and at different developmental stages of the tomato growth cycle. We characterized several Sl2ODDs and their expression patterns involved in various metabolic pathways, such as gibberellin biosynthesis and catabolism, ethylene biosynthesis, steroidal glycoalkaloid biosynthesis, and flavonoid metabolism. We found that the Sl2ODD expression patterns were consistent with their functions during the tomato growth cycle . These results indicated the significance of Sl2ODDs in tomato growth and metabolism. Based on this genome-wide analysis of Sl2ODDs, we screened six potential FNSI genes using a phylogenetic tree and coexpression analysis. However, none of them exhibited FNSI activity.

Conclusions

Our study provided a comprehensive understanding of the tomato 2ODD family and demonstrated the significant roles of these family members in plant metabolism. We also suggest that no FNSI genes in tomato contribute to the biosynthesis of flavones.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12864-021-07434-3.

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Most cited references 54

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MEGA7: Molecular Evolutionary Genetics Analysis Version 7.0 for Bigger Datasets.

Sudhir Kumar, Glen Stecher, Koichiro Tamura (2016)

We present the latest version of the Molecular Evolutionary Genetics Analysis (Mega) software, which contains many sophisticated methods and tools for phylogenomics and phylomedicine. In this major upgrade, Mega has been optimized for use on 64-bit computing systems for analyzing larger datasets. Researchers can now explore and analyze tens of thousands of sequences in Mega The new version also provides an advanced wizard for building timetrees and includes a new functionality to automatically predict gene duplication events in gene family trees. The 64-bit Mega is made available in two interfaces: graphical and command line. The graphical user interface (GUI) is a native Microsoft Windows application that can also be used on Mac OS X. The command line Mega is available as native applications for Windows, Linux, and Mac OS X. They are intended for use in high-throughput and scripted analysis. Both versions are available from www.megasoftware.net free of charge.

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TBtools - an integrative toolkit developed for interactive analyses of big biological data

Chengjie Chen, Hao Chen, Yi Zhang … (2020)

The rapid development of high-throughput sequencing techniques has led biology into the big-data era. Data analyses using various bioinformatics tools rely on programming and command-line environments, which are challenging and time-consuming for most wet-lab biologists. Here, we present TBtools (a Toolkit for Biologists integrating various biological data-handling tools), a stand-alone software with a user-friendly interface. The toolkit incorporates over 130 functions, which are designed to meet the increasing demand for big-data analyses, ranging from bulk sequence processing to interactive data visualization. A wide variety of graphs can be prepared in TBtools using a new plotting engine ("JIGplot") developed to maximize their interactive ability; this engine allows quick point-and-click modification of almost every graphic feature. TBtools is platform-independent software that can be run under all operating systems with Java Runtime Environment 1.6 or newer. It is freely available to non-commercial users at https://github.com/CJ-Chen/TBtools/releases.

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MEME Suite: tools for motif discovery and searching

Timothy L. Bailey, Mikael Bodén, Fabian Buske … (2009)

The MEME Suite web server provides a unified portal for online discovery and analysis of sequence motifs representing features such as DNA binding sites and protein interaction domains. The popular MEME motif discovery algorithm is now complemented by the GLAM2 algorithm which allows discovery of motifs containing gaps. Three sequence scanning algorithms—MAST, FIMO and GLAM2SCAN—allow scanning numerous DNA and protein sequence databases for motifs discovered by MEME and GLAM2. Transcription factor motifs (including those discovered using MEME) can be compared with motifs in many popular motif databases using the motif database scanning algorithm Tomtom. Transcription factor motifs can be further analyzed for putative function by association with Gene Ontology (GO) terms using the motif-GO term association tool GOMO. MEME output now contains sequence LOGOS for each discovered motif, as well as buttons to allow motifs to be conveniently submitted to the sequence and motif database scanning algorithms (MAST, FIMO and Tomtom), or to GOMO, for further analysis. GLAM2 output similarly contains buttons for further analysis using GLAM2SCAN and for rerunning GLAM2 with different parameters. All of the motif-based tools are now implemented as web services via Opal. Source code, binaries and a web server are freely available for noncommercial use at http://meme.nbcr.net.

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Author and article information

Contributors

Rao Fu:

ORCID: http://orcid.org/0000-0001-8619-4616

rao@scu.edu.cn

Journal

Journal ID (nlm-ta): BMC Genomics

Journal ID (iso-abbrev): BMC Genomics

Title: BMC Genomics

Publisher: BioMed Central (London )

ISSN (Electronic): 1471-2164

Publication date (Electronic): 18 February 2021

Publication date PMC-release: 18 February 2021

Publication date Collection: 2021

Volume: 22

Electronic Location Identifier: 126

Affiliations

GRID grid.13291.38, ISNI 0000 0001 0807 1581, Key Laboratory of Bio-resource and Eco-environment of Ministry of Education, College of Life Sciences, , Sichuan University, ; No.24 South Section 1, Yihuan Road, Chengdu, China

Author information

Rao Fu http://orcid.org/0000-0001-8619-4616

Article

Publisher ID: 7434

DOI: 10.1186/s12864-021-07434-3

PMC ID: 7891033

PubMed ID: 33602133

SO-VID: b5fd489f-d53a-45ee-97e3-d18e9bd9b00d

License:

Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

History

Date received : 6 November 2020

Date accepted : 10 February 2021

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ScienceOpen disciplines: Genetics

Keywords: tomato,2-oxoglutarate and fe(ii)-dependent dioxygenase family,phylogenetics,expression profile,metabolism,growth cycle,flavone synthase

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ScienceOpen disciplines: Genetics

Keywords: tomato, 2-oxoglutarate and fe(ii)-dependent dioxygenase family, phylogenetics, expression profile, metabolism, growth cycle, flavone synthase

Genome-wide characterization of 2-oxoglutarate and Fe(II)-dependent dioxygenase family genes in tomato during growth cycle and their roles in metabolism

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Abstract

Background

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Conclusions

Supplementary Information

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Genome Integrity

Most cited references 54

MEGA7: Molecular Evolutionary Genetics Analysis Version 7.0 for Bigger Datasets.

TBtools - an integrative toolkit developed for interactive analyses of big biological data

MEME Suite: tools for motif discovery and searching

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