Computationally Characterizing Protein-Bound Long Noncoding RNAs and Their Secondary Structure Using Protein Interaction Profile Sequencing (PIP-Seq) in Plants.

Two major components of posttranscriptional regulation are RNA-protein interactions and RNA secondary structure. While noncoding RNAs are far more abundant than messenger RNAs in eukaryotic systems, their functions remain largely unstudied. Evidence suggests that RNA-protein interactions and RNA secondary structure also regulate the function of long noncoding RNAs (lncRNAs), which are noncoding RNAs over 200 nucleotides (nt) in length. Protein interaction profile sequencing (PIP-seq) allows researchers to perform an unbiased screen of protein-bound regions and secondary structure of RNAs throughout a transcriptome of interest. Using a peak calling approach, our pipeline is able to identify protein-protected sites (PPSs), which are putative RNA-protein interaction sites. Additionally, by taking the ratio of read coverages in double-stranded RNA (dsRNA)-seq compared to single-stranded RNA (ssRNA)-seq libraries, our analysis can also calculate an RNA secondary structure score that reflects the likelihood of a region being comprised of double- or single-stranded ribonucleotides. Researchers can also use this pipeline to look at specific regions of interest, such as known lncRNAs, and determine their protein-bound status as well as elucidate their secondary structure.

Citation

Mengge Shan, Zachary D Anderson, Brian D Gregory. Computationally Characterizing Protein-Bound Long Noncoding RNAs and Their Secondary Structure Using Protein Interaction Profile Sequencing (PIP-Seq) in Plants. Methods in molecular biology (Clifton, N.J.). 2019;1933:363-380

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PMID: 30945197

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