Folding and Finding RNA Secondary Structure

Mathews, David H.; Moss, William C.; Turner, Douglas H.

doi:10.1101/cshperspect.a003665

Cited by 145 publications

(129 citation statements)

References 122 publications

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“…3, Left; Spearman's ρ = 0.4 ± 0.08, median ± MAD; P < 10 −4 for all tested regions). Although it was previously shown that the MFE can predict ∼70% of secondary structure (47), some RNAs can give rise to several structures (48,49), and the MFE may not always represent the native conformation (50). Therefore, we additionally calculated the ensemble free energy (EFE; using RNAfold, ref.…”

Section: Construction and Measurement Of Thousands Of 5′-utr Sequencementioning

confidence: 99%

Deciphering the rules by which 5′-UTR sequences affect protein expression in yeast

Dvir

Velten

Sharon

et al. 2013

Proc. Natl. Acad. Sci. U.S.A.

241

287

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The 5′-untranslated region (5′-UTR) of mRNAs contains elements that affect expression, yet the rules by which these regions exert their effect are poorly understood. Here, we studied the impact of 5′-UTR sequences on protein levels in yeast, by constructing a large-scale library of mutants that differ only in the 10 bp preceding the translational start site of a fluorescent reporter. Using a high-throughput sequencing strategy, we obtained highly accurate measurements of protein abundance for over 2,000 unique sequence variants. The resulting pool spanned an approximately sevenfold range of protein levels, demonstrating the powerful consequences of sequence manipulations of even 1-10 nucleotides immediately upstream of the start codon. We devised computational models that predicted over 70% of the measured expression variability in held-out sequence variants. Notably, a combined model of the most prominent features successfully explained protein abundance in an additional, independently constructed library, whose nucleotide composition differed greatly from the library used to parameterize the model. Our analysis reveals the dominant contribution of the start codon context at positions −3 to −1, mRNA secondary structure, and out-of-frame upstream AUGs (uAUGs) to phenotypic diversity, thereby advancing our understanding of how protein levels are modulated by 5′-UTR sequences, and paving the way toward predictably tuning protein expression through manipulations of 5′-UTRs.post-transcriptional regulation | computational prediction | AUG sequence context | mRNA folding | upstream start codons T he control of protein expression is a fundamental process of living cells. Much progress has recently been made in understanding how information encoded within DNA regulatory sequences is converted to yield a precise expression output (1-4). However, functional elements are also embedded within RNA sequences, such as 5′-untranslated regions (5′-UTRs). Accumulating evidence has revealed the importance of 5′-UTRs in shaping eukaryotic protein expression (5-12). Such 5′-UTR sequences encode a variety of cis-regulatory elements, including a 5′-cap structure (13), a translation initiation motif (14-16), upstream AUGs (uAUGs) and upstream ORFs (17, 18), internal ribosome entry sites (19), terminal oligo-pyrimidine tracts (20), secondary structures (21), and G-quadruplexes (22). Many of these elements were shown to control protein levels by altering the efficiency of translation (7-9, 11), whereas some elements affect translation and in addition, transcription (15) or mRNA degradation (23). Despite much progress, significant challenges remain in deciphering the rules by which multiple elements combine to fine-tune protein expression, as well as in quantifying the degree of expression variation that may be jointly explained by known and novel regulatory elements.Traditionally, the impact of 5′-UTR elements on protein abundance is determined experimentally by comparing a perturbed 5′-UTR sequence with an appropriate control (16,(23)(2...

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Section: Construction and Measurement Of Thousands Of 5′-utr Sequencementioning

confidence: 99%

Deciphering the rules by which 5′-UTR sequences affect protein expression in yeast

Dvir

Velten

Sharon

et al. 2013

Proc. Natl. Acad. Sci. U.S.A.

241

287

View full text Add to dashboard Cite

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“…RNA function depends on its structure-it is the seemingly limitless variety of structures that allows so many diverse functions. We can now predict RNA secondary structure quite well (Mathews et al 2010) and see much progress on predicting 3D structure (Westhof et al 2010). Remarkably, we can now watch molecules of RNA fold and unfold and switch from one state to another in "singlemolecule experiments" (Tinoco et al 2010).…”

Section: The World Of Rna Technology and Medical Applicationsmentioning

confidence: 99%

The RNA Worlds in Context

Cech

2011

Cold Spring Harbor Perspectives in Biology

188

136

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SUMMARYThere are two RNAworlds. The first is the primordial RNAworld, a hypothetical era when RNA served as both information and function, both genotype and phenotype. The second RNA world is that of today's biological systems, where RNA plays active roles in catalyzing biochemical reactions, in translating mRNA into proteins, in regulating gene expression, and in the constant battle between infectious agents trying to subvert host defense systems and host cells protecting themselves from infection. This second RNA world is not at all hypothetical, and although we do not have all the answers about how it works, we have the tools to continue our interrogation of this world and refine our understanding. The fun comes when we try to use our secure knowledge of the modern RNAworld to infer what the primordial RNAworld might have looked like.

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“…The de novo discovery of structured regions in long RNA strands, such as viral RNAs, has been approached with a variety of techniques (Washietl et al 2005a;Schroeder 2009;Mathews et al 2010). One method is based on searching for regions predicted to be unusually stable thermodynamically (Washietl et al 2005b;Uzilov et al 2006).…”

Section: Introductionmentioning

confidence: 99%

Identification of potential conserved RNA secondary structure throughout influenza A coding regions

Moss¹,

Priore²,

Turner³

2011

RNA

163

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Influenza A is a negative sense RNA virus of significant public health concern. While much is understood about the life cycle of the virus, knowledge of RNA secondary structure in influenza A virus is sparse. Predictions of RNA secondary structure can focus experimental efforts. The present study analyzes coding regions of the eight viral genome segments in both the (+) and (-) sense RNA for conserved secondary structure. The predictions are based on identifying regions of unusual thermodynamic stabilities and are correlated with studies of suppression of synonymous codon usage (SSCU). The results indicate that secondary structure is favored in the (+) sense influenza RNA. Twenty regions with putative conserved RNA structure have been identified, including two previously described structured regions. Of these predictions, eight have high thermodynamic stability and SSCU, with five of these corresponding to current annotations (e.g., splice sites), while the remaining 12 are predicted by the thermodynamics alone. Secondary structures with high conservation of base-pairing are proposed within the five regions having known function. A combination of thermodynamics, amino acid and nucleotide sequence comparisons along with SSCU was essential for revealing potential secondary structures.

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Folding and Finding RNA Secondary Structure

Cited by 145 publications

References 122 publications

Deciphering the rules by which 5′-UTR sequences affect protein expression in yeast

Deciphering the rules by which 5′-UTR sequences affect protein expression in yeast

The RNA Worlds in Context

Identification of potential conserved RNA secondary structure throughout influenza A coding regions

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