bioRxivBioinformaticsPreprint
Conservation and discovery of regulatory motifs across oomycetes through comparative genomic analysis
Abstract
Promoter sequences contain specific transcription factor (TFs) binding sites that regulate gene expression. While the conservation of TFs in pathogen development and infection among oomycetes is known, little is understood about TFs bind to conserved promoter regions across species. This study employs a robust comparative computational genomics approach to identify the TFs binding to orthologous DNA motifs in oomycetes. By integrating high-confidence TF binding site (TFBS) profiles, in-silico motif discovery, sequence conservation analysis and protein sequence similarity searches, the study revealed conserved regulatory mechanisms in oomycetes. The multi-layered computational framework identified two major TF classes in oomycetes: Cys2-His2 (C2H2) zinc finger proteins and winged helix repressor proteins, binding to orthologous motifs regulating gene clusters involved in epigenetic regulation, effectors, intracellular trafficking, host cell wall degrading enzymes, RNA processing and cytoskeletal organization. Structural comparisons indicate high sequence similarity between oomycete TFs and well-characterized eukaryotic TFs, supporting the predictive power of the computational approach. Moreover, motif plasticity analysis across developmental phases revealed conserved and phase-specific motifs emphasizing dynamic transcriptional regulation during infection and colonization. The presence of highly conserved motifs across multiple oomycete species suggests strong evolutionary selection pressure on key regulatory elements. The results provide a computational foundation for future experimental validation, guiding functional characterization of transcriptional regulation in oomycetes. This study highlights the potential of in-silico TFBS discovery for understanding gene regulation, paving the way for targeted experimental approaches such as ChIP-seq or electrophoretic mobility shift assays (EMSA).
- assay: DNA methylation
- research focus: gene regulatory network inference
- approach: statistical model
- approach: matrix factorization
- Citations
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