TVIR 2.0: an enhanced database of the vegetables information resources

Tong Yu , Xiao Ma , Zhuo Liu , Tongbing Su , Chenhao Zhang , Lusheng Guo , Zipeng Meng , Di Guo , Nana Yao , Yingchao Zhang , Haibin Liu , Xiaoming Song

Horticulture Research ›› 2025, Vol. 12 ›› Issue (12) : 239

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Horticulture Research ›› 2025, Vol. 12 ›› Issue (12) :239 DOI: 10.1093/hr/uhaf239
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TVIR 2.0: an enhanced database of the vegetables information resources
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Abstract

Since its inaugural release in 2022, The Vegetables Information Resources (TVIR) has been a cornerstone for genomics and genetic breeding studies within the vegetable research community. With advancements in sequencing technologies leading to an influx of new genome sequences, TVIR has been upgraded to version 2.0 (http://tvir2.bio2db.com/), expanding from 59 to 84 vegetable species and introducing new functional modules to accelerate research. This upgrade incorporates a CRISPR/Cas9 resource module, which integrates four specialized tools: CasFinder, CasOT, Crisflash, and CRISPRCasFinder, to facilitate gene editing research. The database further features dynamic synteny analysis with an interactive interface, enabling users to visualize genomic relationships between species. Additionally, two novel bioinformatics tools Hmmsearch and CRISPRCasViewer are integrated to enhance comparative and functional genomic analyses. TVIR 2.0 retains all TVIR 1.0 features while updating resistance gene identification, expanding from 3 to 8 types, and transcription factor datasets, now including 237 431 TFs, an increase from 172 493.The database integrates comprehensive genomic, transcriptomic, and functional annotation data, providing freely accessible resources for vegetable breeding and gene editing.

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Tong Yu, Xiao Ma, Zhuo Liu, Tongbing Su, Chenhao Zhang, Lusheng Guo, Zipeng Meng, Di Guo, Nana Yao, Yingchao Zhang, Haibin Liu, Xiaoming Song. TVIR 2.0: an enhanced database of the vegetables information resources. Horticulture Research, 2025, 12(12): 239 DOI:10.1093/hr/uhaf239

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Acknowledgments

This work was supported by the National Key Research and Development Program of China (2023YFF1002000), the Tangshan Science and Technology Plan Project (24130219C), the Basic Research Program of Tangshan (22130231H), the Basic research expenses for provincial universities (JJC2024001), the National Natural Science Foundation of China (32172583), Basic Research Funds for Provincial Universities Basic Research Projects of North China University of Science and Technology (JQN2023036), Youth Scholars Promotion Plan of North China University of Science and Technology (QNTJ202308), the S&T Program of Hebei (23372505D), and the Hebei Natural Science Foundation (H2023209084).

Author contributions

X.S. conceived the project and was responsible for the initiation of the project. X.S., X.M., Y.Z., H.L., and T.Y. supervised and managed the project and research. Data generation and collection were performed by X.S., T.Y., X.M., T.S., C.Z., N.Y., and Z.M. Bioinformatics analysis and database construction was led by X.S., T.Y., Z.L., and L.G. The manuscript was organized, written, and revised by X.S., T.Y., X.M., Z.L., T.S., D.G., Y.Z., and H.L. All the authors read and revised the manuscript.

Data availability

TVIR 2.0 is freely available to the public without any registration or login requirements (http://tvir2.bio2db.com/). All the related datasets can be downloaded from the database.

Conflict of interest statement

The authors declare no conflicts of interest.

Supplementary data

Supplementary data is available at Horticulture Research online.

References

[1]

Yu T, Ma X, Liu Z. et al. TVIR: a comprehensive vegetable information resource database for comparative and functional genomic studies. Hortic Res. 2022;9:uhac213

[2]

Chen H, Wang T, He X. et al.BRAD V3.0:an upgraded Brassi-caceae database. Nucleic Acids Res.2022;50:D1432-d1441

[3]

LiuZ, LiN, YuT. et al. The Brassicaceae genome resource (TBGR): a comprehensive genome platform for Brassicaceae plants. Plant Physiol. 2022; 190:226-37

[4]

Gui S, Martinez-Rivas FJ, Wen W. et al. Going broad and deep: sequencing-driven insights into plant physiology, evolution, and crop domestication. Plant J. 2023; 113:446-59

[5]

Shen F, Xu S, Shen Q. et al. The allotetraploid horseradish genome provides insights into subgenome diversification and formation of critical traits. Nat Commun. 2023; 14:4102

[6]

Liao N, Hu Z, Miao J. et al. Chromosome-level genome assembly of bunching onion illuminates genome evolution and flavor formation in allium crops. Nat Commun. 2022; 13: 6690

[7]

Wang S, Wang A, Wang H. et al. Chromosome-level genome of a leaf vegetable Glebionis coronaria provides insights into the biosynthesis of monoterpenoids contributing to its special aroma. DNA Res. 2022;29:

[8]

Fan W, Wang S, Wang H. et al. The genomes of chicory, endive, great burdock and yacon provide insights into Asteraceae palaeo-polyploidization history and plant inulin production. Mol Ecol Resour. 2022; 22:3124-40

[9]

Bateman A, Martin MJ, Orchard S. et al. UniProt: the Univer-sal Protein Knowledgebase in 2023. Nucleic Acids Res.2023;51: D523-d531

[10]

Mistry J, Chuguransky S, Williams L. et al.Pfam:the protein families database in 2021. Nucleic Acids Res.2021;49:D412-d419

[11]

Aleksander SA, Balhoff J, Carbon S. et al. The gene ontology knowledgebase in 2023. Genetics. 2023;224:

[12]

Untergasser A, Cutcutache I, Koressaar T. et al. Primer3—new capabilities and interfaces. Nucleic Acids Res. 2012; 40:e115

[13]

Koressaar T, Remm M. Enhancements and modifications of primer design program Primer3. Bioinformatics. 2007; 23: 1289-91

[14]

Wang Y, Tang H, Debarry JD. et al. MCScanX: a toolkit for detec-tion and evolutionary analysis of gene synteny and collinearity. Nucleic Acids Res. 2012; 40:e49

[15]

Diesh C, Stevens GJ, Xie P. et al. JBrowse 2: a modular genome browser with views of synteny and structural variation. Genome Biol. 2023; 24:74

[16]

Potter SC, Luciani A, Eddy SR. et al. HMMER web server: 2018 update. Nucleic Acids Res. 2018;46:W200-4

[17]

Gong Z. Plant abiotic stress: new insights into the factors that activate and modulate plant responses. J Integr Plant Biol. 2021; 63:429-30

[18]

Tiwari JK, Singh AK, Behera TK. CRISPR/Cas genome editing in tomato improvement: advances and applications. Front Plant Sci. 2023; 14:1121209

[19]

Muto N, Matsumoto T. CRISPR/Cas9-mediated genome editing of RsGL1a and RsGL1b in radish (Raphanus sativus L.). Front Plant Sci. 2022; 13:951660

[20]

Ding X, Yu L, Chen L. et al. Recent progress and future prospect of CRISPR/Cas-Derived Transcription Activation (CRISPRa) system in plants. Cells. 2022;11:

[21]

Shelake RM, Kadam US, Kumar R. et al. Engineering drought and salinity tolerance traits in crops through CRISPR-mediated genome editing: targets, tools, challenges, and perspectives. Plant Commun. 2022; 3:100417

[22]

Barakate A, Stephens J. An overview of CRISPR-based tools and their improvements: new opportunities in understanding plant-pathogen interactions for better crop protection. Front Plant Sci. 2016; 7:765

[23]

Ren C, Lin Y, Liang Z. CRISPR/Cas genome editing in grapevine: recent advances, challenges and future prospects. Fruit Res. 2022; 2:1-9

[24]

Liu G, Lin Q, Jin S. et al. The CRISPR-Cas toolbox and gene editing technologies. Mol Cell. 2022; 82:333-47

[25]

Bradford J, Chappell T, Perrin D. Rapid whole-genome identi-fication of high quality CRISPR guide RNAs with the crackling method. Crispr J. 2022; 5:410-21

[26]

Gao C. Genome engineering for crop improvement and future agriculture. Cell. 2021; 184:1621-35

[27]

Zhu H, Li C, Gao C. Applications of CRISPR-Cas in agriculture and plant biotechnology. Nat Rev Mol Cell Biol. 2020; 21:661-77

[28]

Chen K, Wang Y, Zhang R. et al. CRISPR/Cas genome editing and precision plant breeding in agriculture. Annu Rev Plant Biol. 2019; 70:667-97

[29]

Prakash A, Jeffryes M, Bateman A. et al. The HMMER web server for protein sequence similarity search. Curr Protoc Bioinformatics. 2017; 60:3.15.1-3.15.23

[30]

Chen F, Song Y, Li X. et al. Genome sequences of horticultural plants: past, present, and future. Hortic Res. 2019; 6:112

[31]

Pei Q, Li N, Bai Y. et al. Comparative analysis of the TCP gene family in celery, coriander and carrot (family Apiaceae). Veg Res. 2021; 1:1-12

[32]

Pei Q, Yu T, Wu T. et al. Comprehensive identification and analyses of the Hsf gene family in the whole-genome of three Apiaceae species. Hortic Plant J. 2021; 7:12

[33]

Liu Z, Zhang C, He J. et al. plantGIR: a genomic database of plants. Hortic Res. 2024;11:uhae342

[34]

JinJ, TianF, YangDC. et al. PlantTFDB 4.0: toward a central hub for transcription factors and regulatory interactions in plants. Nucleic Acids Res. 2017;45:D1040-d1045

[35]

Feng S, Liu Z, Chen H. et al. PHGD: an integrative and user-friendly database for plant hormone-related genes. Imeta. 2024; 3:e164

[36]

Wu T,LiuZ,YuT. et al. Flowering genes identification, network analysis, and database construction for 837 plants. Hortic Res. 2024;11:

[37]

Liu Z, Shen S, Li C. et al. SoIR: a comprehensive Solanaceae information resource for comparative and functional genomic study. Nucleic Acids Res. 2025;53:D1623-32

[38]

Wang X, Wei Y, Liu Z. et al. TEGR: a comprehensive Ericaceae genome resource database. J Integr Agric. 2025; 24:1140-51

[39]

Liu J, Huang C, Xing D. et al. The genomic database of fruits: a comprehensive fruit information database for comparative and functional genomic studies. Agric Commun. 2024; 2:100041

[40]

Li P, Quan X, Jia G. et al. RGAugury: a pipeline for genome-wide prediction of resistance gene analogs (RGAs) in plants. BMC Genomics. 2016; 17:852

[41]

Cortaga CQ, Latina RA, Habunal RR. et al. Identification and char-acterization of genome-wide resistance gene analogs (RGAs) of durian (Durio zibethinus L.). J Genet Eng Biotechnol. 2022; 20:29

[42]

Ma Y, Meng Y, Wang Y. et al. Research progress on clubroot disease in Brassicaceae crops—advances and perspectives. Veg Res. 2024;4:

[43]

Langmead B, Salzberg SL. Fast gapped-read alignment with Bowtie 2. Nat Methods. 2012; 9:357-9

[44]

Aach J, Mali P, Church GM. CasFinder: flexible algorithm for identifying specific Cas9 targets in genomes. Biorxiv. 2014. https://doi.org/10.1101/005074

[45]

Xiao A, Cheng Z, Kong L. et al. CasOT: a genome-wide Cas9/gRNA off-target searching tool. Bioinformatics. 2014; 30:1180-2

[46]

Jacquin ALS, Odom DT, Lukk M. Crisflash: open-source software to generate CRISPR guide RNAs against genomes annotated with individual variation. Bioinformatics. 2019; 35:3146-7

[47]

Couvin D, Bernheim A, Toffano-Nioche C. et al. CRISPRCasFinder, an update of CRISRFinder, includes a portable version, enhanced performance and integrates search for Cas proteins. Nucleic Acids Res. 2018;46:W246-w251

[48]

Jiang F, Doudna JA. CRISPR-Cas 9 structures and mechanisms. Annu Rev Biophys. 2017; 46:505-29

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