Integrating suboptimal secondary structures, AI-assisted genomic synteny, and evolutionary conservation to identify bacterial ncRNA homologs beyond sequence similarity

A bioinformatic approach for genome-wide identification of homologs of bacterial non-coding RNAs (ncRNAs) integrating structural similarity, genomic synteny, and evolutionary conservation is presented. The structural similarity is detected using an algorithm for genome-wide identification of loci in genomic intergenic regions (IGRs) containing sequences capable of adopting secondary structures similar to that of the query ncRNA. The algorithm scans IGR sequences using a sliding window with a predefined step. For each window, suboptimal secondary structures are predicted and compared with the template structure to compute structural similarity scores. These scores are evaluated statistically on a genome-wide scale to infer homology of the RNAs represented by the predicted structures. Loci encoding statistically significant structures are further filtered using genomic synteny of the query ncRNAs inferred from genomic annotations. ChatGPT was used to assist in identifying literature-supported biological relationships between genes with distinct functional annotations. Syntenic loci with the structures are then examined for homologs in related species, as evolutionary conservation among related species is a common feature of ncRNAs Using this approach, we predicted novel homologs of the spot42 RNA-encoding spf gene in Glaciecola and Pseudoalteromonas genomes, and ms1 RNA genes in Frankia and Bifidobacterium genomes, where previous homology searches had failed. GRAPHICAL ABSTRACT O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=44 SRC="FIGDIR/small/737749v1_ufig1.gif" ALT="Figure 1"> View larger version (13K): org.highwire.dtl.DTLVardef@dd18baorg.highwire.dtl.DTLVardef@18261eforg.highwire.dtl.DTLVardef@eb95c3org.highwire.dtl.DTLVardef@b535ad_HPS_FORMAT_FIGEXP M_FIG C_FIG