A Computational Pipeline for High- Throughput Discovery of cis-Regulatory Noncoding RNA in Prokaryotes

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Abstract
Noncoding RNAs (ncRNAs) are important functional RNAs that do not code for proteins. We present a highly efficient computational pipeline for discovering cis-regulatory ncRNA motifs de novo. The pipeline differs from previous methods in that it is structure-oriented, does not require a multiple-sequence alignment as input, and is capable of detecting RNA motifs with low sequence conservation. We also integrate RNA motif prediction with RNA homolog search, which improves the quality of the RNA motifs significantly. Here, we report the results of applying this pipeline to Firmicute bacteria. Our top-ranking motifs include most known Firmicute elements found in the RNA family database (Rfam). Comparing our motif models with Rfam's hand-curated motif models, we achieve high accuracy in both membership prediction and base-pair–level secondary structure prediction (at least 75% average sensitivity and specificity on both tasks). Of the ncRNA candidates not in Rfam, we find compelling evidence that some of them are functional, and analyze several potential ribosomal protein leaders in depth. For decades, scientists believed that, with a few key exceptions, RNA played a secondary role in the cell. Recent discoveries have sharply revised this simple picture, revealing widespread, diverse, and surprisingly sophisticated roles for RNA. For example, many bacteria use RNA elements called “riboswitches” to switch various gene activities on or off in response to extremely sensitive detection of specific molecules. Discovery of new functional RNA elements remains a very challenging task, both computationally and experimentally. It is computationally difficult largely because of the importance of an RNA molecule's 3-D structure, and the fact that molecules with very different nucleotide sequences can fold into the same shape. In this paper, we propose a computational procedure, based on comparing the genomes of multiple bacteria, for discovery of novel RNAs. Unlike most previous approaches, ours does not require a letter-by-letter alignment of these diverse genomes, making it more applicable to RNA elements whose structure, but not nucleotide sequence, has been preserved through evolution. In an extensive test on the Firmicutes, a bacterial phylum containing well-studied organisms such as Bacillus subtilis and important pathogens such as anthrax, we recover most known noncoding RNA elements, as well as making many novel predictions.