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Discovery of RNA structural elements using evolutionary computation.

ABSTRACT: RNA molecules fold into characteristic secondary and tertiary structures that account for their diverse functional activities. Many of these RNA structures, or certain structural motifs within them, are thought to recur in multiple genes within a single organism or across the same gene in several organisms and provide a common regulatory mechanism. Search algorithms, such as RNAMotif, can be used to mine nucleotide sequence databases for these repeating motifs. RNAMotif allows users to capture essential features of known structures in detailed descriptors and can be used to identify, with high specificity, other similar motifs within the nucleotide database. However, when the descriptor constraints are relaxed to provide more flexibility, or when there is very little a priori information about hypothesized RNA structures, the number of motif 'hits' may become very large. Exhaustive methods to search for similar RNA structures over these large search spaces are likely to be computationally intractable. Here we describe a powerful new algorithm based on evolutionary computation to solve this problem. A series of experiments using ferritin IRE and SRP RNA stem-loop motifs were used to verify the method. We demonstrate that even when searching extremely large search spaces, of the order of 10(23) potential solutions, we could find the correct solution in a fraction of the time it would have taken for exhaustive comparisons.

SUBMITTER: Fogel GB

PROVIDER: S-EPMC137967 | biostudies-literature | 2002 Dec

REPOSITORIES: biostudies-literature

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Discovery of RNA structural elements using evolutionary computation.

Fogel Gary B GB Porto V William VW Weekes Dana G DG Fogel David B DB Griffey Richard H RH McNeil John A JA Lesnik Elena E Ecker David J DJ Sampath Rangarajan R

Nucleic acids research 20021201 23

RNA molecules fold into characteristic secondary and tertiary structures that account for their diverse functional activities. Many of these RNA structures, or certain structural motifs within them, are thought to recur in multiple genes within a single organism or across the same gene in several organisms and provide a common regulatory mechanism. Search algorithms, such as RNAMotif, can be used to mine nucleotide sequence databases for these repeating motifs. RNAMotif allows users to capture e ...[more]

PMID: 12466557

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Project description:Decoding post-transcriptional regulatory programs underlying gene expression is a crucial step toward a predictive dynamical understanding of cellular state transitions. Despite recent systematic efforts, the sequence determinants of such mechanisms remain largely uncharacterized. An important obstacle in revealing these elements stems from the contribution of local secondary structures in defining interaction partners in a variety of regulatory contexts, including but not limited to transcript stability, alternative splicing and localization. There are many documented instances where the presence of a structural regulatory element dictates alternative splicing patterns (e.g. human cardiac troponin T) or affects other aspects of RNA biology. Thus, a full characterization of post-transcriptional regulatory programs requires capturing information provided by both local secondary structures and the underlying sequence. We have developed a computational framework based on context-free grammars and mutual information that systematically explores the immense space of structural elements and reveals motifs that are significantly informative of genome-wide measurements of RNA behavior. The application of this framework to genome-wide mammalian mRNA stability data revealed eight highly significant elements with substantial structural information, for the strongest of which we showed a major role in global mRNA regulation. Through biochemistry, mass-spectrometry, and in vivo binding studies, we identified HNRPA2B1 as the key regulator that binds this element and stabilizes a large number of its target genes. Ultimately, we created a global post-transcriptional regulatory map based on the identity of the discovered linear and structural cis-regulatory elements, their regulatory interactions and their target pathways. This approach can also be employed to reveal the structural elements that modulate other aspects of RNA behavior. This SuperSeries is composed of the following subset Series: GSE35749: sRSM1 synthetic decoy vs. scrambled transfections in MDA-MB-231 cells GSE35753: HNRPA2B1 RIP-chip GSE35756: Whole-genome decay rate measurements in MDA-MB-231 cells transfected with HNRPA2B1 siRNAs versus controls GSE35757: siRNA-mediated HNRPA2B1 knock-down in MDA-MB-231 cells GSE35799: HNRPA2B1 HITS-CLIP Refer to individual Series

Dataset Information

Discovery of RNA structural elements using evolutionary computation.

Publications

Discovery of RNA structural elements using evolutionary computation.

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