Sprague, D. A. | Search bioRxiv

bioRxiv2026

Scanning transcriptomes for nonlinear, domain-level similarities using hmSEEKR

Long noncoding RNAs (lncRNAs) play roles in gene regulation across kingdoms of life. However, lncRNAs with related functions often lack linear sequence similarity, making it difficult to leverage studies of one lncRNA to inform the understanding of others. We describe a k-mer-based hidden Markov model, hmSEEKR, that enables the scanning of transcriptomes for regions of non-linear sequence similarity to a query domain, without prior knowledge of where within the transcriptome the similarities may be located. When individual lncRNA domains were used as search features, hmSEEKR successfully identified regions in other RNAs that harbor non-linear sequence similarity and bind similar sets of proteins. Applying hmSEEKR to transcriptome-wide searches, we found that certain domains within the lncRNAs XIST, NEAT1, and MALAT1 exhibited widespread regional similarity to both lncRNA and protein-coding genes, while others were more unique, exhibiting similarity to [~]100 genes or fewer. Combinatorial searches uncovered RNAs containing sequential matches to core functional domains of XIST and NEAT1, and eCLIP-inferred protein-interaction networks within these RNAs more closely resembled those of XIST and NEAT1, respectively, than would be expected by chance, suggesting the searches recovered RNAs with similar biological properties. Finally, within annotated sets of cis-activating and cis-repressive lncRNAs, we observed opposing enrichments for similarity to domains associated with transcription-promoting complexes and heterogeneous nuclear ribonucleoprotein (hnRNP) binding, respectively, suggesting the enriched sequences may contribute to regulatory functions. hmSEEKR can be applied with minimal training data and enables the a priori discovery of RNA domains that share nonlinear similarity, offering a sequence-informed approach to discover functional elements within noncoding transcriptomes.

bioinformatics↗

bioRxiv2026

Phenotypic screening for small molecules that lower PrP in cultured cells

PrP lowering is a validated therapeutic hypothesis in prion disease. To identify small molecules that reduce PrP levels, we performed phenotypic screening in cultured cells. To prioritize PrP specificity in our primary screen, we generated mouse N2a cells stably expressing GFP and used high content imaging analysis to select compounds that lowered PrP without affecting GFP signal or cell viability. Screening a curated library of 3,492 compounds with annotated mechanisms of action identified two small molecules, EYH (PubChem CID: 71678945) and LCZ (PubChem CID: 24970350), that selectively and dose-dependently lowered PrP. Proteomics on whole cell lysates identified PrP as the #1 or #2 most potently downregulated out of 8,722 proteins detected. Both compounds minimally affected Prnp mRNA, reduced expression of exogenously transfected PrP, and remained potent in non-dividing primary cells, consistent with a post-translational mechanism. Co-treatment with the proteasome inhibitor MG132 yielded accumulation of unglycosylated PrP, demonstrating proteasome clearance of PrP. However, both compounds showed limited or no activity in human cell lines, and failed to reduce PrP in vivo after 14 days of treatment. These findings highlight the challenges associated with mechanism-agnostic phenotypic screening for PrP-lowering compounds and support prioritizing compounds with known mechanisms of action.

neuroscience↗