Functional pathway mapping analysis for hypoxia-inducible factors

• Published in: BMC systems biology 2011-06, Vol.5 Suppl 1 (S1), p.S3-S3, Article S3
• Main Authors: Chuang, Chia-Sheng, Pai, Tun-Wen, Hu, Chin-Hua, Tzou, Wen-Shyong, Dah-Tsyr Chang, Margaret, Chang, Hao-Teng, Chen, Chih-Chia
• Format: Article
• Language: English
• Subjects: Animals; Base Sequence; Basic Helix-Loop-Helix Transcription Factors - metabolism; Binding Sites; Computational Biology - methods; Conserved Sequence - genetics; Databases, Genetic; Humans; Mice; Response Elements - genetics; Sequence Homology, Nucleic Acid; Species Specificity
• ISSN: 1752-0509; 1752-0509
• DOI: 10.1186/1752-0509-5-S1-S3

Hypoxia-inducible factors (HIFs) are transcription factors that play a crucial role in response to hypoxic stress in living organisms. The HIF pathway is activated by changes in cellular oxygen levels and has significant impacts on the regulation of gene expression patterns in cancer cells. Identifying functional conservation across species and discovering conserved regulatory motifs can facilitate the selection of reference species for empirical tests. This paper describes a cross-species functional pathway mapping strategy based on evidence of homologous relationships that employs matrix-based searching techniques for identifying transcription factor-binding sites on all retrieved HIF target genes. HIF-related orthologous and paralogous genes were mapped onto the conserved pathways to indicate functional conservation across species. Quantitatively measured HIF pathways are depicted in order to illustrate the extent of functional conservation. The results show that in spite of the evolutionary process of speciation, distantly related species may exhibit functional conservation owing to conservative pathways. The novel terms OrthRate and ParaRate are proposed to quantitatively indicate the flexibility of a homologous pathway and reveal the alternative regulation of functional genes. The developed functional pathway mapping strategy provides a bioinformatics approach for constructing biological pathways by highlighting the homologous relationships between various model species. The mapped HIF pathways were quantitatively illustrated and evaluated by statistically analyzing their conserved transcription factor-binding elements. hypoxia-inducible factor (HIF), hypoxia-response element (HRE), transcription factor (TF), transcription factor binding site (TFBS), KEGG (Kyoto Encyclopedia of Genes and Genomes), cross-species comparison, orthology, paralogy, functional pathway.