Allegro

Allegro identifies cis-regulatory motifs and their associated expression profiles by integrating promoter and 3′ untranslated region (UTR) sequences with genome-wide expression data to define transcriptional modules.

Key Features:

• Joint Analysis: Performs joint analysis of genomic sequences (promoters and 3′ UTRs) and expression data to identify co-regulated genes and their regulatory elements.
• Log-Likelihood-Based Model: Employs a log-likelihood-based, non-parametric model to describe shared expression patterns among groups of co-regulated genes.
• Scalability and Efficiency: Analyzes thousands of gene expression profiles across numerous experimental conditions while processing regulatory sequences genome-wide.
• Multi-Dataset Capability: Simultaneously analyzes multiple expression datasets, including cases with more than 100 different conditions.

Scientific Applications:

• Characterization of Transcription Factors and miRNAs: Aids in understanding transcription factors and microRNAs (miRNAs) and the transcriptional programs they regulate.
• Species-Wide Analysis: Applied across several species to provide insights into species-specific regulatory mechanisms.
• Discovery of Novel Motifs: Has led to discovery of motifs over-represented in murine oocyte promoters and motifs related to fly development.
• Role in Human Embryogenesis: Identified three miRNA families with roles in human embryogenesis through analysis of stem-cell expression profiles.

Methodology:

Integrates genome-wide expression data with promoter or 3′ UTR sequences and applies a log-likelihood-based, non-parametric model to identify shared expression patterns among co-regulated genes and associated motifs.