meta

meta aligns predicted transcription factor binding site maps from promoter regions to compare regulatory architectures and identify conserved regulatory elements among co-expressed or orthologous genes.

Key Features:

• Transcription Factor Maps (TF-maps): Predicts transcription factor binding sites within promoter regions and annotates them with factor-specific labels to produce TF-maps representing promoter regulatory landscapes.
• Alignment Algorithm: Employs an adapted global pairwise alignment algorithm originally developed for restriction enzyme map alignment, optimized for TF-map alignment to detect conserved regulatory elements.
• Parameter Optimization: Parameters were fine-tuned using a curated dataset of human-mouse orthologous gene pairs to improve detection accuracy of functional sites.

Scientific Applications:

• Comparative promoter analysis: Characterizes promoter regions from orthologous genes across species to identify conserved regulatory motifs.
• Co-regulated gene analysis: Analyzes promoters of co-regulated genes identified through microarray analyses to reveal shared regulatory elements.
• Detection of non-sequence-conserved elements: Enhances detection of functional regulatory elements that are not apparent from direct nucleotide sequence alignments, reducing signal-to-noise in regulatory element discovery.

Methodology:

Predicts transcription factor binding sites in promoter regions; annotates predicted sites with corresponding transcription factors to create TF-maps; aligns TF-maps using an adapted global pairwise alignment algorithm derived from restriction enzyme map alignment; optimizes parameters using a curated human-mouse ortholog dataset and evaluates performance on the curated dataset and the CISRED database.