Treffer: InsectTFDB: A Comprehensive Database and Analysis Platform for Insect Transcription Factors.
Title:
InsectTFDB: A Comprehensive Database and Analysis Platform for Insect Transcription Factors.
Authors:
Zhou H; College of Plant Protection, Jilin Agricultural University, Changchun, China.; Zhejiang Key Laboratory of Biology and Ecological Regulation of Crop Pathogens and Insects, Institute of Insect Sciences, Zhejiang University, Hangzhou, Zhejiang, China., Tang J; Zhejiang Key Laboratory of Biology and Ecological Regulation of Crop Pathogens and Insects, Institute of Insect Sciences, Zhejiang University, Hangzhou, Zhejiang, China., Cheng Z; College of Plant Protection, Jilin Agricultural University, Changchun, China., Mei Y; College of Plant Protection, Jilin Agricultural University, Changchun, China.
Source:
Molecular ecology resources [Mol Ecol Resour] 2025 Oct; Vol. 25 (7), pp. e70006. Date of Electronic Publication: 2025 Jun 30.
Publication Type:
Journal Article
Language:
English
Journal Info:
Publisher: Blackwell Country of Publication: England NLM ID: 101465604 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1755-0998 (Electronic) Linking ISSN: 1755098X NLM ISO Abbreviation: Mol Ecol Resour Subsets: MEDLINE
Imprint Name(s):
Original Publication: Oxford, England : Blackwell
MeSH Terms:
Insecta*/genetics , Transcription Factors*/genetics , Transcription Factors*/metabolism , Databases, Genetic*, Databases as Topic ; Gene Expression Regulation ; Animals ; Gene Regulatory Networks ; Classification ; Insect Proteins/genetics ; Insect Proteins/metabolism ; Genes, Insect/genetics ; Genome, Insect/physiology
References:
Ardakani, F. B., K. Kattler, T. Heinen, et al. 2020. “Prediction of Single‐Cell Gene Expression for Transcription Factor Analysis.” GigaScience 9: giaa113. https://doi.org/10.1093/gigascience/giaa113.
Avramov, M., É. Schád, Á. Révész, et al. 2022. “Identification of Intrinsically Disordered Proteins and Regions in a Non‐Model Insect Species Ostrinia nubilalis (Hbn.).” Biomolecules 12: 592. https://doi.org/10.3390/biom12040592.
Aydin, B., A. Kakumanu, M. Rossillo, et al. 2019. “Proneural Factors Ascl1 and Neurog2 Contribute to Neuronal Subtype Identities by Establishing Distinct Chromatin Landscapes.” Nature Neuroscience 22: 897–908. https://doi.org/10.1038/s41593‐019‐0399‐y.
Beck, Y., F. Pecasse, and G. Richards. 2004. “Krüppel‐Homolog Is Essential for the Coordination of Regulatory Gene Hierarchies in Early Drosophila Development.” Developmental Biology 268: 64–75. https://doi.org/10.1016/J.YDBIO.2003.12.017.
Blum, M., H.‐Y. Chang, S. Chuguransky, et al. 2021. “The Interpro Protein Families and Domains Database: 20 Years on.” Nucleic Acids Research 49: D344–D354. https://doi.org/10.1093/nar/gkaa977.
Bono, H., T. Sakamoto, T. Kasukawa, and H. Tabunoki. 2022. “Systematic Functional Annotation Workflow for Insects.” Insects 13, no. 7: 586. https://doi.org/10.3390/insects13070586.
Buchfink, B., K. Reuter, and H.‐G. Drost. 2021. “Sensitive Protein Alignments at Tree‐Of‐Life Scale Using DIAMOND.” Nature Methods 18: 366–368. https://doi.org/10.1038/s41592‐021‐01101‐x.
Cantalapiedra, C. P., A. Hernández‐Plaza, I. Letunic, P. Bork, and J. Huerta‐Cepas. 2021. “eggNOG‐Mapper v2: Functional Annotation, Orthology Assignments, and Domain Prediction at the Metagenomic Scale.” Molecular Biology and Evolution 38: 5825–5829. https://doi.org/10.1093/molbev/msab293.
Cao, X., and H. Jiang. 2018. “Building a Platform for Predicting Functions of Serine Protease‐Related Proteins in Drosophila melanogaster and Other Insects.” Insect Biochemistry and Molecular Biology 103: 53–69. https://doi.org/10.1016/j.ibmb.2018.10.006.
Chang, V., and M. Meuti. 2020. “Circadian Transcription Factors Differentially Regulate Features of the Adult Overwintering Diapause in the Northern House Mosquito, Culex pipiens.” Insect Biochemistry and Molecular Biology 121: 103365. https://doi.org/10.1016/j.ibmb.2020.103365.
Domsch, K., J. Schröder, M. Janeschik, C. Schaub, and I. Lohmann. 2021. “The Hox Transcription Factor Ubx Ensures Somatic Myogenesis by Suppressing the Mesodermal Master Regulator Twist.” Cell Reports 34: 108577. https://doi.org/10.1016/j.celrep.2020.108577.
Dönitz, J., L. Gerischer, S. Hahnke, S. Pfeiffer, and G. Bucher. 2018. “Expanded and Updated Data and a Query Pipeline for iBeetle‐Base.” Nucleic Acids Research 46: D831–D835. https://doi.org/10.1093/nar/gkx984.
Dubowy, C., and A. Sehgal. 2017. “Circadian Rhythms and Sleep in Drosophila melanogaster.” Genetics 205: 1373–1397. https://doi.org/10.1534/genetics.115.185157.
Eddy, S. R. 2011. “Accelerated Profile HMM Searches.” PLoS Computational Biology 7: e1002195. https://doi.org/10.1371/journal.pcbi.1002195.
Giebultowicz, J. M. 2000. “Molecular Mechanism and Cellular Distribution of Insect Circadian Clocks.” Annual Review of Entomology 45: 769–793. https://doi.org/10.1146/ANNUREV.ENTO.45.1.769.
Guo, Z., J. Qin, X. Zhou, and Y. Zhang. 2018. “Insect Transcription Factors: A Landscape of Their Structures and Biological Functions in Drosophila and Beyond.” International Journal of Molecular Sciences 19: 3691. https://doi.org/10.3390/ijms19113691.
Jaramillo, M. L., D. Ammar, R. L. Quispe, et al. 2022. “Identification of Hox Genes and Their Expression Profiles During Embryonic Development of the Emerging Model Organism, Macrobrachium olfersii.” Journal of Experimental Zoology Part B: Molecular and Developmental Evolution 338: 292–300. https://doi.org/10.1002/jez.b.23118.
Kanehisa, M., M. Furumichi, Y. Sato, M. Ishiguro‐Watanabe, and M. Tanabe. 2021. “KEGG: Integrating Viruses and Cellular Organisms.” Nucleic Acids Research 49: D545–D551. https://doi.org/10.1093/nar/gkaa970.
Lambert, S. A., A. Jolma, L. F. Campitelli, et al. 2018. “The Human Transcription Factors.” Cell 172: 650–665. https://doi.org/10.1016/j.cell.2018.01.029.
Larkin, A., S. J. Marygold, G. Antonazzo, et al. 2021. “FlyBase: Updates to the Drosophila melanogaster Knowledge Base.” Nucleic Acids Research 49: D899–D907. https://doi.org/10.1093/nar/gkaa1026.
Li, F., X. Zhao, M. Li, et al. 2019. “Insect Genomes: Progress and Challenges.” Insect Molecular Biology 28: 739–758. https://doi.org/10.1111/imb.12599.
Li, K.‐L., S.‐Y. Yuan, S. Nanda, et al. 2018. “The Roles of E93 and Kr‐h1 in Metamorphosis of Nilaparvata lugens.” Frontiers in Physiology 9: 1677. https://doi.org/10.3389/fphys.2018.01677.
Mei, Y., D. Jing, S. Tang, et al. 2022. “InsectBase 2.0: A Comprehensive Gene Resource for Insects.” Nucleic Acids Research 50: D1040–D1045. https://doi.org/10.1093/nar/gkab1090.
Pecasse, F., Y. Beck, C. Ruiz, and G. Richards. 2000. “Krüppel‐Homolog, a Stage‐Specific Modulator of the Prepupal Ecdysone Response, Is Essential for Drosophila Metamorphosis.” Developmental Biology 221: 53–67. https://doi.org/10.1006/DBIO.2000.9687.
Poelchau, M., C. Childers, G. Moore, et al. 2015. “The i5k Workspace@ NAL—Enabling Genomic Data Access, Visualization and Curation of Arthropod Genomes.” Nucleic Acids Research 43: D714–D719. https://doi.org/10.1093/nar/gku983.
Pucker, B. 2021. “Automatic Identification and Annotation of MYB Gene Family Members in Plants.” BMC Genomics 23: 220. https://doi.org/10.1186/s12864‐022‐08452‐5.
Rauluseviciute, I., R. Riudavets‐Puig, R. Blanc‐Mathieu, et al. 2024. “JASPAR 2024: 20th Anniversary of the Open‐Access Database of Transcription Factor Binding Profiles.” Nucleic Acids Research 52: D174–D182. https://doi.org/10.1093/nar/gkad1059.
Sayers, E. W., J. Beck, E. E. Bolton, et al. 2025. “Database Resources of the National Center for Biotechnology Information in 2025.” Nucleic Acids Research 53: D20–D29. https://doi.org/10.1093/nar/gkae979.
Shen, W.‐K., S.‐Y. Chen, Z.‐Q. Gan, et al. 2023. “AnimalTFDB 4.0: A Comprehensive Animal Transcription Factor Database Updated With Variation and Expression Annotations.” Nucleic Acids Research 51: D39–D45. https://doi.org/10.1093/nar/gkac907.
Simão, F. A., R. M. Waterhouse, P. Ioannidis, E. V. Kriventseva, and E. M. Zdobnov. 2015. “BUSCO: Assessing Genome Assembly and Annotation Completeness With Single‐Copy Orthologs.” Bioinformatics 31: 3210–3212. https://doi.org/10.1093/bioinformatics/btv351.
Simicevic, J., and B. Deplancke. 2017. “Transcription Factor Proteomics—Tools, Applications, and Challenges.” Proteomics 17: 1600317. https://doi.org/10.1002/pmic.201600317.
Spitz, F., and E. E. M. Furlong. 2012. “Transcription Factors: From Enhancer Binding to Developmental Control.” Nature Reviews Genetics 13: 613–626. https://doi.org/10.1038/nrg3207.
Steinegger, M., and J. Söding. 2017. “MMseqs2 Enables Sensitive Protein Sequence Searching for the Analysis of Massive Data Sets.” Nature Biotechnology 35: 1026–1028. https://doi.org/10.1038/nbt.3988.
Taylor, M., and S. Hughes. 2017. “Mef2 and the Skeletal Muscle Differentiation Program.” Seminars in Cell & Developmental Biology 72: 33–44. https://doi.org/10.1016/j.semcdb.2017.11.020.
The Gene Ontology Consortium. 2021. “The Gene Ontology Resource: Enriching a GOld Mine.” Nucleic Acids Research 49: D325–D334. https://doi.org/10.1093/nar/gkaa1113.
The UniProt Consortium. 2025. “UniProt: The Universal Protein Knowledgebase in 2025.” Nucleic Acids Research 53: D609–D617. https://doi.org/10.1093/nar/gkae1010.
Tian, F., D.‐C. Yang, Y.‐Q. Meng, J. Jin, and G. Gao. 2020. “PlantRegMap: Charting Functional Regulatory Maps in Plants.” Nucleic Acids Research 48: D1104–D1113. https://doi.org/10.1093/nar/gkz1020.
Truman, J. 2019. “The Evolution of Insect Metamorphosis.” Current Biology 29: R1252–R1268. https://doi.org/10.1016/j.cub.2019.10.009.
Weidemüller, P., M. Kholmatov, E. Petsalaki, and J. B. Zaugg. 2021. “Transcription Factors: Bridge Between Cell Signaling and Gene Regulation.” Proteomics 21: 2000034. https://doi.org/10.1002/pmic.202000034.
Wilhelmsson, P., C. Mühlich, K. Ullrich, and S. Rensing. 2017. “Comprehensive Genome‐Wide Classification Reveals That Many Plant‐Specific Transcription Factors Evolved in Streptophyte algae.” Genome Biology and Evolution 9: 3384–3397. https://doi.org/10.1093/gbe/evx258.
Yan, J., Y. Qiu, A. R. D. Santos, et al. 2021. “Systematic Analysis of Binding of Transcription Factors to Noncoding Variants.” Nature 591: 147–151. https://doi.org/10.1038/s41586‐021‐03211‐0.
Avramov, M., É. Schád, Á. Révész, et al. 2022. “Identification of Intrinsically Disordered Proteins and Regions in a Non‐Model Insect Species Ostrinia nubilalis (Hbn.).” Biomolecules 12: 592. https://doi.org/10.3390/biom12040592.
Aydin, B., A. Kakumanu, M. Rossillo, et al. 2019. “Proneural Factors Ascl1 and Neurog2 Contribute to Neuronal Subtype Identities by Establishing Distinct Chromatin Landscapes.” Nature Neuroscience 22: 897–908. https://doi.org/10.1038/s41593‐019‐0399‐y.
Beck, Y., F. Pecasse, and G. Richards. 2004. “Krüppel‐Homolog Is Essential for the Coordination of Regulatory Gene Hierarchies in Early Drosophila Development.” Developmental Biology 268: 64–75. https://doi.org/10.1016/J.YDBIO.2003.12.017.
Blum, M., H.‐Y. Chang, S. Chuguransky, et al. 2021. “The Interpro Protein Families and Domains Database: 20 Years on.” Nucleic Acids Research 49: D344–D354. https://doi.org/10.1093/nar/gkaa977.
Bono, H., T. Sakamoto, T. Kasukawa, and H. Tabunoki. 2022. “Systematic Functional Annotation Workflow for Insects.” Insects 13, no. 7: 586. https://doi.org/10.3390/insects13070586.
Buchfink, B., K. Reuter, and H.‐G. Drost. 2021. “Sensitive Protein Alignments at Tree‐Of‐Life Scale Using DIAMOND.” Nature Methods 18: 366–368. https://doi.org/10.1038/s41592‐021‐01101‐x.
Cantalapiedra, C. P., A. Hernández‐Plaza, I. Letunic, P. Bork, and J. Huerta‐Cepas. 2021. “eggNOG‐Mapper v2: Functional Annotation, Orthology Assignments, and Domain Prediction at the Metagenomic Scale.” Molecular Biology and Evolution 38: 5825–5829. https://doi.org/10.1093/molbev/msab293.
Cao, X., and H. Jiang. 2018. “Building a Platform for Predicting Functions of Serine Protease‐Related Proteins in Drosophila melanogaster and Other Insects.” Insect Biochemistry and Molecular Biology 103: 53–69. https://doi.org/10.1016/j.ibmb.2018.10.006.
Chang, V., and M. Meuti. 2020. “Circadian Transcription Factors Differentially Regulate Features of the Adult Overwintering Diapause in the Northern House Mosquito, Culex pipiens.” Insect Biochemistry and Molecular Biology 121: 103365. https://doi.org/10.1016/j.ibmb.2020.103365.
Domsch, K., J. Schröder, M. Janeschik, C. Schaub, and I. Lohmann. 2021. “The Hox Transcription Factor Ubx Ensures Somatic Myogenesis by Suppressing the Mesodermal Master Regulator Twist.” Cell Reports 34: 108577. https://doi.org/10.1016/j.celrep.2020.108577.
Dönitz, J., L. Gerischer, S. Hahnke, S. Pfeiffer, and G. Bucher. 2018. “Expanded and Updated Data and a Query Pipeline for iBeetle‐Base.” Nucleic Acids Research 46: D831–D835. https://doi.org/10.1093/nar/gkx984.
Dubowy, C., and A. Sehgal. 2017. “Circadian Rhythms and Sleep in Drosophila melanogaster.” Genetics 205: 1373–1397. https://doi.org/10.1534/genetics.115.185157.
Eddy, S. R. 2011. “Accelerated Profile HMM Searches.” PLoS Computational Biology 7: e1002195. https://doi.org/10.1371/journal.pcbi.1002195.
Giebultowicz, J. M. 2000. “Molecular Mechanism and Cellular Distribution of Insect Circadian Clocks.” Annual Review of Entomology 45: 769–793. https://doi.org/10.1146/ANNUREV.ENTO.45.1.769.
Guo, Z., J. Qin, X. Zhou, and Y. Zhang. 2018. “Insect Transcription Factors: A Landscape of Their Structures and Biological Functions in Drosophila and Beyond.” International Journal of Molecular Sciences 19: 3691. https://doi.org/10.3390/ijms19113691.
Jaramillo, M. L., D. Ammar, R. L. Quispe, et al. 2022. “Identification of Hox Genes and Their Expression Profiles During Embryonic Development of the Emerging Model Organism, Macrobrachium olfersii.” Journal of Experimental Zoology Part B: Molecular and Developmental Evolution 338: 292–300. https://doi.org/10.1002/jez.b.23118.
Kanehisa, M., M. Furumichi, Y. Sato, M. Ishiguro‐Watanabe, and M. Tanabe. 2021. “KEGG: Integrating Viruses and Cellular Organisms.” Nucleic Acids Research 49: D545–D551. https://doi.org/10.1093/nar/gkaa970.
Lambert, S. A., A. Jolma, L. F. Campitelli, et al. 2018. “The Human Transcription Factors.” Cell 172: 650–665. https://doi.org/10.1016/j.cell.2018.01.029.
Larkin, A., S. J. Marygold, G. Antonazzo, et al. 2021. “FlyBase: Updates to the Drosophila melanogaster Knowledge Base.” Nucleic Acids Research 49: D899–D907. https://doi.org/10.1093/nar/gkaa1026.
Li, F., X. Zhao, M. Li, et al. 2019. “Insect Genomes: Progress and Challenges.” Insect Molecular Biology 28: 739–758. https://doi.org/10.1111/imb.12599.
Li, K.‐L., S.‐Y. Yuan, S. Nanda, et al. 2018. “The Roles of E93 and Kr‐h1 in Metamorphosis of Nilaparvata lugens.” Frontiers in Physiology 9: 1677. https://doi.org/10.3389/fphys.2018.01677.
Mei, Y., D. Jing, S. Tang, et al. 2022. “InsectBase 2.0: A Comprehensive Gene Resource for Insects.” Nucleic Acids Research 50: D1040–D1045. https://doi.org/10.1093/nar/gkab1090.
Pecasse, F., Y. Beck, C. Ruiz, and G. Richards. 2000. “Krüppel‐Homolog, a Stage‐Specific Modulator of the Prepupal Ecdysone Response, Is Essential for Drosophila Metamorphosis.” Developmental Biology 221: 53–67. https://doi.org/10.1006/DBIO.2000.9687.
Poelchau, M., C. Childers, G. Moore, et al. 2015. “The i5k Workspace@ NAL—Enabling Genomic Data Access, Visualization and Curation of Arthropod Genomes.” Nucleic Acids Research 43: D714–D719. https://doi.org/10.1093/nar/gku983.
Pucker, B. 2021. “Automatic Identification and Annotation of MYB Gene Family Members in Plants.” BMC Genomics 23: 220. https://doi.org/10.1186/s12864‐022‐08452‐5.
Rauluseviciute, I., R. Riudavets‐Puig, R. Blanc‐Mathieu, et al. 2024. “JASPAR 2024: 20th Anniversary of the Open‐Access Database of Transcription Factor Binding Profiles.” Nucleic Acids Research 52: D174–D182. https://doi.org/10.1093/nar/gkad1059.
Sayers, E. W., J. Beck, E. E. Bolton, et al. 2025. “Database Resources of the National Center for Biotechnology Information in 2025.” Nucleic Acids Research 53: D20–D29. https://doi.org/10.1093/nar/gkae979.
Shen, W.‐K., S.‐Y. Chen, Z.‐Q. Gan, et al. 2023. “AnimalTFDB 4.0: A Comprehensive Animal Transcription Factor Database Updated With Variation and Expression Annotations.” Nucleic Acids Research 51: D39–D45. https://doi.org/10.1093/nar/gkac907.
Simão, F. A., R. M. Waterhouse, P. Ioannidis, E. V. Kriventseva, and E. M. Zdobnov. 2015. “BUSCO: Assessing Genome Assembly and Annotation Completeness With Single‐Copy Orthologs.” Bioinformatics 31: 3210–3212. https://doi.org/10.1093/bioinformatics/btv351.
Simicevic, J., and B. Deplancke. 2017. “Transcription Factor Proteomics—Tools, Applications, and Challenges.” Proteomics 17: 1600317. https://doi.org/10.1002/pmic.201600317.
Spitz, F., and E. E. M. Furlong. 2012. “Transcription Factors: From Enhancer Binding to Developmental Control.” Nature Reviews Genetics 13: 613–626. https://doi.org/10.1038/nrg3207.
Steinegger, M., and J. Söding. 2017. “MMseqs2 Enables Sensitive Protein Sequence Searching for the Analysis of Massive Data Sets.” Nature Biotechnology 35: 1026–1028. https://doi.org/10.1038/nbt.3988.
Taylor, M., and S. Hughes. 2017. “Mef2 and the Skeletal Muscle Differentiation Program.” Seminars in Cell & Developmental Biology 72: 33–44. https://doi.org/10.1016/j.semcdb.2017.11.020.
The Gene Ontology Consortium. 2021. “The Gene Ontology Resource: Enriching a GOld Mine.” Nucleic Acids Research 49: D325–D334. https://doi.org/10.1093/nar/gkaa1113.
The UniProt Consortium. 2025. “UniProt: The Universal Protein Knowledgebase in 2025.” Nucleic Acids Research 53: D609–D617. https://doi.org/10.1093/nar/gkae1010.
Tian, F., D.‐C. Yang, Y.‐Q. Meng, J. Jin, and G. Gao. 2020. “PlantRegMap: Charting Functional Regulatory Maps in Plants.” Nucleic Acids Research 48: D1104–D1113. https://doi.org/10.1093/nar/gkz1020.
Truman, J. 2019. “The Evolution of Insect Metamorphosis.” Current Biology 29: R1252–R1268. https://doi.org/10.1016/j.cub.2019.10.009.
Weidemüller, P., M. Kholmatov, E. Petsalaki, and J. B. Zaugg. 2021. “Transcription Factors: Bridge Between Cell Signaling and Gene Regulation.” Proteomics 21: 2000034. https://doi.org/10.1002/pmic.202000034.
Wilhelmsson, P., C. Mühlich, K. Ullrich, and S. Rensing. 2017. “Comprehensive Genome‐Wide Classification Reveals That Many Plant‐Specific Transcription Factors Evolved in Streptophyte algae.” Genome Biology and Evolution 9: 3384–3397. https://doi.org/10.1093/gbe/evx258.
Yan, J., Y. Qiu, A. R. D. Santos, et al. 2021. “Systematic Analysis of Binding of Transcription Factors to Noncoding Variants.” Nature 591: 147–151. https://doi.org/10.1038/s41586‐021‐03211‐0.
Grant Information:
2021YFD1400100 National Key Research and Development Program of China; 2021YFD1400101 National Key Research and Development Program of China; 32102271 National Natural Science Foundation of China; 2022T150579 China Postdoctoral Science Foundation
Contributed Indexing:
Keywords: BLAST; database; insects; prediction; transcription factors
Substance Nomenclature:
0 (Transcription Factors)
0 (Insect Proteins)
0 (Insect Proteins)
Entry Date(s):
Date Created: 20250630 Date Completed: 20250910 Latest Revision: 20250910
Update Code:
20250910
DOI:
10.1111/1755-0998.70006
PMID:
40583840
Database:
MEDLINE
Weitere Informationen
Transcription factors (TFs) are key regulators of gene expression, driving diverse biological processes in insects. Despite their importance, a dedicated and comprehensive database for insect TFs has been lacking. To address this gap, we developed InsectTFDB (http://www.insecttfdb.com/), a specialised resource encompassing 1796 insect species across 21 orders, 258 families and 1034 genera. From 59,491,033 predicted proteins, we identified 1,570,627 TFs, systematically classified into six structural groups and annotated using multiple approaches. Approximately 87% of these TFs were successfully annotated to known proteins, enhancing their functional interpretability. InsectTFDB offers a user-friendly interface with four functional modules, including tools for species retrieval, TF exploration, sequence alignment and predictive analysis of novel sequences. These features make it a versatile platform for diverse research applications, from evolutionary studies to functional genomics and pest management. By providing unprecedented taxonomic coverage and reliable annotations, InsectTFDB serves as a critical resource for advancing our understanding of transcriptional regulation and gene regulatory networks across the insects.
(© 2025 John Wiley & Sons Ltd.)