Biopolym. Cell. 2009; 25(5):398-402.
http://dx.doi.org/10.7124/bc.0007F2
Bioinformatics
Identification of gene targets of ISGF-3 transcription factor
1Tokovenko B. T., 1Dragushchenko O. O., 1Kuklin A. V., 1Obolenskaya M. Yu.
  1. Institute of Molecular Biology and Genetics, NAS of Ukraine
    150, Akademika Zabolotnoho Str., Kyiv, Ukraine, 03680

Abstract

Aim. Transcription factor ISGF-3 is activated as a result of the signal transduction from IFNα via the dominating Jak-STAT pathway. The discovery of ISGF-3 binding sites will assist in identifying genes of primary response to IFNα. Methods. COTRASIF is a web-based tool for the genome-wide identification of the evolutionary-conservative regulatory sites in the promoters of eukaryotic genes. It offers 3 search methods: based on position-weight matrices (PWM), hybrid method based on hidden Markov models (PWM-HMM), and phylogenetic footprinting. Results. We have demonstrated that PWM-HMM method has higher search specificity, and used this method to identify the gene targets of ISGF-3 transcription factor. After applying phylogenetic foot-printing, we have obtained a list of 162 genes of putative primary response to IFNα. The reliability metrics to these gene targets has been developed and applied. Conclusions. Based on the search results, Gene Ontology over-representation analysis, and reliability metrics, we have identified 24 rat protein-coding genes as promising targets for further studies on the primary response to IFNα.
Keywords: interferon, ISGF-3, COTRASIF, IFNα
Full text: (PDF, in Ukrainian)

References

[1] Tokovenko B., Golda R., Protas O., Obolenskaya M., El'skaya A. COTRASIF: conservation-aided transcription-factorbinding site finder Nucl. Acids Res 2009 37, N 7 P. e49.
[2] Cartharius K., Frech K., Grote K., Klocke B., Haltmeier M., Klingenhoff A., Frisch M., Bayerlein M., Werner T. MatInspector and beyond: promoter analysis based on transcription factor binding sites Bioinformatics 2005 21, N 13 P. 2933–2942.
[3] Horvath C. M. The Jak-STAT pathway stimulated by interferon alpha or interferon beta Sigtrans 2004 2004 260 P. tr10.
[4] Kel A. E., Gossling E., Reuter I., Cheremushkin E., Kel-Margoulis O. V., Wingender E. MATCH: a tool for searching transcription factor binding sites in DNA sequences Nucl. Acids Res 2003 31, N 13:3576–3579.
[5] Al-Shahrour F., Minguez P., Tarraga J., Montaner D., Alloza E., Vaquerizas J. M., Conde L., Blaschke C., Vera J., Dopazo J. BABELOMICS: a systems biology perspective in the functional annotation of genome-scale experiments Nucl. Acids Res 2006 34, suppl. 2:W472–W476.
[6] Wheeler D. L., Church D. M., Federhen S., Lash A. E., Madden T. L., Pontius J. U., Schuler G. D., Schriml L. M., Sequeira E., Tatusova T. A., Wagner L. Database resources of the national center for biotechnology Nucl. Acids Res 2003 31, N 1:28–33.
[7] Hoffmann R., Valencia A. A gene network for navigating the literature Nat. Genet 2004 36, N 7:664.
[8] Li X., Leung S., Burns C., Stark G. R. Cooperative binding of Stat1-2 heterodimers and ISGF3 to tandem DNA elements Biochimie 1998 80, N 8–9:703–710.
[9] Hannenhalli S., Levy S. Predicting transcription factor synergism Nucl. Acids Res 2002 30, N 19:4278–4284.
[10] Bluyssen H. A., Vlietstra R. J., van der Mada A., Trapman J. The interferon-stimulated gene 54 K promoter contains two adjacent functional interferon-stimulated response elements of different strength, which act synergistically for maximal interferon-alpha inducibility Eur. J. Biochem 1994 220, N 2:395–402.