CGD: a multi-omics database for Chrysanthemum genomic and biological research

Abstract

Asteraceae is the largest family of dicotyledons and includes Chrysanthemum and Helianthus, two important genera of ornamental plants. The genus Chrysanthemum consists of more than 30 species and contains many economically important ornamental, medicinal, and industrial plants. To more effectively promote Chrysanthemum research, we constructed the CGD, a Chrysanthemum genome database containing a large amount of data and useful tools. The CGD hosts well-assembled reference genome data for six Chrysanthemum species. These genomic data were fully annotated by comparison with various protein and domain data. Transcriptome data for nine different tissues, five flower developmental stages, and five treatments were subsequently added to the CGD. A fully functional ‘RNA data’ module was designed to provide complete and visual expression profile data. In addition, the CGD also provides many of the latest bioinformatics analysis tools, such as the efficient sgRNA search tool for Chrysanthemum. In conclusion, the CGD provides the latest, richest, and most complete multi-omics resources and powerful tools for Chrysanthemum. Collectively, the CGD will become the central gateway for Chrysanthemum genomics and genetic breeding research and will aid in the study of polyploid evolution.

Acknowledgements

This research was funded by the Forestry Science and Technology Innovation and Promotion Project in Jiangsu Province (LYKJ [2023]22), Jiangsu Province Innovation Capacity Construction Program (BM2022008-02), the National Natural Science Foundation of China (32072609, 32172609), the Achievement Transformation Fund project of Hainan Research Institute of Nanjing Agricultural University (NAUSY-CG-YB04), the ‘Blue Project’ of Jiangsu Higher Education Institutions and a project Funded by the Priority Academic Program Development of Jiangsu Higher Education Institutions.

Data availability

All the data hosted in the CGD are freely available at (http://210.22.121.250:8880/asteraceae/homePage).

Conflict of interest statement

The authors declare that they have no conflict of interest.

Supplementary data

Supplementary data is available at Horticulture Research online.

References

[1] The Angiosperm Phylogeny Group, Chase MW, Christenhusz MJM. et al. An update of the angiosperm phylogeny group classification for the orders and families of flowering plants: APG IV. Bot J Linn Soc. 2016; 181:1-20

[2] Chen J, Wang C, Zhao H. et al. The Origin of Garden Chrysanthemum. Hefei: Anhui Science & Technology Publishing House; 2012:

[3] Anderson NO. Flower Breeding and Genetics: Issues, Challenges and Opportunities for the 21st Century. Dordrecht: Springer, 2006

[4] Ohmiya A. Molecular mechanisms underlying the diverse array of petal colors in chrysanthemum flowers. Breed Sci. 2018; 68:119-27

[5] Boase MR, Miller R, Deroles SC. Chrysanthemum systematics, genetics, and breeding. Plant Breeding Rev. 2010; 14:321-61

[6] Song C, Liu Y, Song A. et al. The Chrysanthemum nankingense genome provides insights into the evolution and diversification of chrysanthemum flowers and medicinal traits. Mol Plant. 2018; 11:1482-91

[7] Nakano M, Hirakawa H, Fukai E. et al. A chromosome-level genome sequence of Chrysanthemum seticuspe, a model species for hexaploid cultivated chrysanthemum. Commun Biol. 2021; 4:1167

[8] Wen X, Li J, Wang L. et al. The Chrysanthemum lavandulifolium genome and the molecular mechanism underlying diverse capitulum types. Hortic Res. 2022; 9:uhab022

[9] van Lieshout N, van Kaauwen M, Kodde L. et al. De novo whole-genome assembly of Chrysanthemum makinoi, a key wild chrysanthemum. G3 (Bethesda). 2022; 12:jkab358

[10] Deng Y, Yang P, Zhang Q. et al. Genomic insights into the evolution of flavonoid biosynthesis and O-methyltransferase and glucosyltransferase in Chrysanthemum indicum. Cell Rep. 2024; 43:113725

[11] Song A, Su J, Wang H. et al. Analyses of a chromosome-scale genome assembly reveal the origin and evolution of cultivated chrysanthemum. Nat Commun. 2023; 14:2021

[12] Lihavainen J, Šimura J, Bag P. et al. Salicylic acid metabolism and signalling coordinate senescence initiation in aspen in nature. Nat Commun. 2023; 14:4288

[13] Uhrig RG, Schläpfer P, Roschitzki B. et al. Diurnal changes in concerted plant protein phosphorylation and acetylation in Arabidopsis organs and seedlings. Plant J. 2019; 99:176-94

[14] Zhang X, Su J, Jia F. et al. Genetic architecture and genomic prediction of plant height-related traits in chrysanthemum. Hortic Res. 2023; 11:uhad236

[15] Wang S, Wang K, Li Z. et al. Architecture design of cucurbit crops for enhanced productivity by a natural allele. Nat Plants. 2022; 8:1394-407

[16] Ding L, Song A, Zhang X. et al. The core regulatory networks and hub genes regulating flower development in Chrysanthemum morifolium. Plant Mol Biol. 2020; 103:669-88

[17] Chen H, Wang T, He X. et al. BRAD V3. 0:an upgraded Brassicaceae database. Nucleic Acids Res. 2022; 50:D1432-41

[18] Yu J, Wu S, Sun H. et al. CuGenDBv2:an updated database for cucurbit genomics. Nucleic Acids Res. 2023; 51:D1457-64

[19] Gao Q, Tong W, Li F. et al. TPIA2: an updated tea plant information archive for camellia genomics. Nucleic Acids Res. 2023; 52:D1661-7

[20] Sakai H, Lee SS, Tanaka T. et al. Rice annotation project database (RAP-DB): an integrative and interactive database for rice genomics. Plant Cell Physiol. 2013; 54:e6-6

[21] Ma S, Wang M, Wu J. et al. WheatOmics: a platform combining multiple omics data to accelerate functional genomics studies in wheat. Mol Plant. 2021; 14:1965-8

[22] Gui S, Yang L, Li J. et al. ZEAMAP, a comprehensive database adapted to the maize multi-omics era. iScience. 2020; 23:101241

[23] Kudo T, Kobayashi M, Terashima S. et al. TOMATOMICS: a web database for integrated omics information in tomato. Plant Cell Physiol. 2017; 58:e8-8

[24] Yang Z, Wang S, Wei L. et al. BnIR: a multi-omics database with various tools for Brassica napus research and breeding. Mol Plant. 2023; 16:775-89

[25] Altschul SF, Gish W, Miller W. et al. Basic local alignment search tool. J Mol Biol. 1990; 215:403-10

[26] Wang Y, Tang H, DeBarry JD. et al. MCScanX: a toolkit for detection and evolutionary analysis of gene synteny and collinearity. Nucleic Acids Res. 2012; 40:e49-9

[27] Pruitt KD, Tatusova T, Maglott DR. NCBI reference sequence (RefSeq): a curated non-redundant sequence database of genomes, transcripts and proteins. Nucleic Acids Res. 2005; 33:D501-4

[28] UniProt Consortium. UniProt: the universal protein knowledgebase in 2021. Nucleic Acids Res. 2021; 49:D480-9

[29] Gene Ontology Consortium, Aleksander SA, Balhoff J. et al. The gene ontology knowledgebase in 2023. Genetics. 2023; 224:iyad031

[30] Kanehisa M, Furumichi M, Sato Y. et al. KEGG for taxonomy-based analysis of pathways and genomes. Nucleic Acids Res. 2023; 51:D587-92

[31] Blum M, Chang HY, Chuguransky S. et al. The InterPro protein families and domains database:20 years on. Nucleic Acids Res. 2021; 49:D344-54

[32] Shan Q, Wang Y, Li J. et al. Targeted genome modification of crop plants using a CRISPR-Cas system. Nat Biotechnol. 2013; 31:686-8

[33] Tang J, Ye J, Liu P. et al. Ornamental plant gene editing: past, present and future. Ornam Plant Res. 2023; 3:1-6

[34] Liu H, Ding Y, Zhou Y. et al. CRISPR-P 2.0: an improved CRISPR-Cas 9 tool for genome editing in plants. Mol Plant. 2017; 10:530-2

[35] Sun J, Liu H, Liu J. et al. CRISPR-local: a local single-guide RNA (sgRNA) design tool for non-reference plant genomes. Bioinformatics. 2019; 35:2501-3