There are surprisingly few RNA intramolecular triple helices known in the human transcriptome. The structure has been most well-studied as a stability-element at the 3 ` end of lncRNAs such as MALAT1 and NEAT1, but the intrigue remains whether it is indeed as rare as it is understood to be or just waiting for a closer look from a new vantage point. TRIPinRNA, our Python-based in silico platform, allows for a comprehensive sequence-pattern search for potential triplex formation in the human transcriptome-noncoding as well as coding. Using this tool, we report the putative occurrence of homopyrimidine type (canonical) triple helices as well as heteropurine-pyrimidine strand type (noncanonical) triple helices in the human transcriptome and validate the formation of both types of triplexes using biophysical approaches. We find that the occurrence of triplex structures has a strong correlation with local GC content, which might be influencing their formation. By employing a search that encompasses both canonical and noncanonical triplex structures across the human transcriptome, this study enriches the understanding of RNA biology. Lastly, TRIPinRNA can be utilized in finding triplex structures for any organism with an annotated transcriptome.

Foreign