TRANSFAC® release 2021.3
The TRANSFAC® database on transcription factors, their genomic binding sites and DNA-binding motifs (PWMs), contains these new data features:
- Tissue-specific gene lists in MATCH Suite
MATCH Suite now supports new input gene list selection option: construct the input gene list from scratch based on the genes that are highly and specifically expressed in the selected tissue. Just pick the tissue of your interest and make the selection of genes that will be submitted to the gene regulation analysis using a nice graphical expression & specificity-based gene selection tool. This feature requires an active HumanPSD™ subscription.
31,933 human and mouse silencer sequences have been imported from the SilencerDB database and lifted over to the GRCh38 and GRCm39 genome assemblies. Silencer reports display genes with which promoters the silencer interacts, tissues and cell types/lines the silencer is active in, and genomic regions such as histone modification sequences, DNase I hypersensitivity sites, and transcription factor binding sites that overlap with the silencer.
- Integration of new human ChIP-Seq experiments from ENCODE
83 new human transcription factor binding site ChIP-Seq experiments released by the ENCODE phase 4 project have been integrated.
- Enhanced human SNP content
The 2021 dbSNP release 155 data for human has been integrated and increases the number of SNPs mapped to promoter, enhancer, and silencer sequences by more than 72,000,000 new single nucleotide variations compared to the previously used version 154.
- Mouse genome assembly update
TRANSFAC® now uses the latest mouse genome assembly GRCm39 (mm39).
Genomic information for genes, promoters, and ChIP fragments for the species human, mouse, rat, pig, macaque, Drosophila, and Arabidopsis is now based on Ensembl release 104.
Most transcription factors (TFs) possess a DNA-binding domain (DBD), which mediates the recognition of specific, short DNA sequence elements in promoter, enhancer, etc. In order to approach the problem of deciphering the underlying DNA-protein recognition code, we have completely revised an earlier TF classification scheme (1,2) by adapting it to the wealth of data that were reported during the last ten years (TFClass; 3-5). TFClass has been implemented at the Dept. of Bioinformatics at the University Medical Center Göttingen (3,6).
Part of this work was done in the context of the Syscol
project, where our partner at the Karolinska institute (Prof. J. Taipale and his team) have characterized the DNA-binding profiles of more than 400 mammalian TFs (7). It will be tempting to compare the similarities of their matrices with the DBD classification reported here, and with our own approaches to classify DNA-binding profiles (8).
- Wingender, E., Schoeps, T., Haubrock, M., Krull, M. and Dönitz, J. (2018) TFClass: expanding the classification of human transcription factors to their mammalian orthologs. Nucleic Acids Res. 46, D343-D347. Link
- Wingender, E., Schoeps, T., Haubrock, M., Dönitz, J. (2015) TFClass: a classification of human transcription factors and their rodent orthologs. Nucleic Acids Res. 43, D97-D102. Link
- Stegmaier, P., Kel, A., Wingender, E., Borlak, J. (2013) A discriminative approach for unsupervised clustering of DNA sequence motifs. PLoS Comput. Biol. 9, e1002958.
- Jolma, A., et al. (2013) DNA-Binding Specificities of Human Transcription Factors. Cell 152, 327–339. Link
- Wingender, E. (2013) Criteria for an updated classification of human transcription factor DNA-binding domains. J. Bioinform. Comput. Biol. 11, 1340007. Link
- Wingender, E., Schoeps, T., Dönitz, J. (2013) TFClass: An expandable hierarchical classification of human transcription factors. Nucleic Acids Res. 41, D165-D170. Link
- Heinemeyer, T., Chen, X., Karas, H., Kel, A.E., Kel, O.V., Liebich, I., Meinhardt, T., Reuter, I., Schacherer, F., Wingender, E. (1999) Expanding the TRANSFAC database towards an expert system of regulatory molecular mechanisms. Nucleic Acids Res. 27, 318–322. Link
- Wingender, E. (1997) Classification scheme of eukaryotic transcription factors. Mol. Biol. Engl. Tr. 31, 498-512. Link
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Kaplun, A., Krull, M., Lakshman, K., Matys, V., Lewicki, B., Hogan, J.D. (2016) Establishing and validating regulatory regions for variant annotation and expression analysis. BMC Genomics 17 (Suppl. 2), 393. PubMed
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