Comparative Genomics Unveils Parallel Recognition of DNA Regulatory Motifs: Insights from Langya Virus

Motivation: The intricate tango between transcription factors and their target genes orchestrates the symphony of cellular life. The functional roles of TFs are intricately tied to the genes under their regulation. Unraveling these roles not only elucidates the genomic and transcriptional landscape of the specific genes and TFs under investigation but also situates them within the comprehensive context of the entire regulatory network. Results: In this study, we present a novel alignment-free and threshold-independent comparative genomics approach for assigning functional roles to DNA regulatory motifs specifically geared towards prokaryotic gene prediction. This approach, integrated into the Gomo and GeneMarkS algorithms, leverages cross-species information to identify Gene Ontology (GO) terms associated with the target genes of transcription factors (TFs). Incorporating two comparative species for Langya virus (LayV) and Paramyxovirus analysis significantly enhances Gomo's ability to predict GO terms, providing deeper biological insights into TF function. To mitigate false positives, we adjust motif affinity scores based on individual sequence composition through a novel sequence-scoring algorithm that refines thermodynamic binding predictions. Notably, Gomo's accuracy remains robust to promoter definition and requires no parameter tuning due to its threshold-free gene set analysis. This empowers biologists to explore the potential roles of specific DNA regulatory motifs and predicted genes through Gomo (http://meme.nbcr.net) and GeneMark web software (http://opal.biology.gatech.edu/GeneMark/).