The Experts below are selected from a list of 360 Experts worldwide ranked by ideXlab platform
Kevin M Weeks - One of the best experts on this subject based on the ideXlab platform.
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direct duplex detection an emerging tool in the RNA Structure analysis toolbox
Trends in Biochemical Sciences, 2016Co-Authors: Chase A Weidmann, Anthony M Mustoe, Kevin M WeeksAbstract:While a variety of powerful tools exists for analyzing RNA Structure, identifying long-range and intermolecular base-pairing interactions has remained challenging. Recently, three groups introduced a high-throughput strategy that uses psoralen-mediated crosslinking to directly identify RNA-RNA duplexes in cells. Initial application of these methods highlights the preponderance of long-range Structures within and between RNA molecules and their widespread structural dynamics.
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detection of RNA protein interactions in living cells with shape
Biochemistry, 2015Co-Authors: Matthew J Smola, Mauro J Calabrese, Kevin M WeeksAbstract:SHAPE-MaP is unique among RNA Structure probing strategies in that it both measures flexibility at single-nucleotide resolution and quantifies the uncertainties in these measurements. We report a s...
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selective 2 hydroxyl acylation analyzed by primer extension and mutational profiling shape map for direct versatile and accurate RNA Structure analysis
Nature Protocols, 2015Co-Authors: Matthew J Smola, Greggory M Rice, Steven Busan, Nathan A Siegfried, Kevin M WeeksAbstract:Selective 2'-hydroxyl acylation analyzed by primer extension (SHAPE) chemistries exploit small electrophilic reagents that react with 2'-hydroxyl groups to interrogate RNA Structure at single-nucleotide resolution. Mutational profiling (MaP) identifies modified residues by using reverse transcriptase to misread a SHAPE-modified nucleotide and then counting the resulting mutations by massively parallel sequencing. The SHAPE-MaP approach measures the Structure of large and transcriptome-wide systems as accurately as can be done for simple model RNAs. This protocol describes the experimental steps, implemented over 3 d, that are required to perform SHAPE probing and to construct multiplexed SHAPE-MaP libraries suitable for deep sequencing. Automated processing of MaP sequencing data is accomplished using two software packages. ShapeMapper converts raw sequencing files into mutational profiles, creates SHAPE reactivity plots and provides useful troubleshooting information. SuperFold uses these data to model RNA secondary Structures, identify regions with well-defined Structures and visualize probable and alteRNAtive helices, often in under 1 d. SHAPE-MaP can be used to make nucleotide-resolution biophysical measurements of individual RNA motifs, rare components of complex RNA ensembles and entire transcriptomes.
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challenge of mimicking the influences of the cellular environment on RNA Structure by peg induced macromolecular crowding
Biochemistry, 2015Co-Authors: Jillian Tyrrell, Kevin M Weeks, Gary J PielakAbstract:There are large differences between the cellular environment and the conditions widely used to study RNA in vitro. SHAPE RNA Structure probing in Escherichia coli cells has shown that the cellular environment stabilizes both long-range and local tertiary interactions in the adenine riboswitch aptamer domain. Synthetic crowding agents are widely used to understand the forces that stabilize RNA Structure and in efforts to recapitulate the cellular environment under simplified experimental conditions. Here, we studied the Structure and ligand binding ability of the adenine riboswitch in the presence of the macromolecular crowding agent, polyethylene glycol (PEG). Ethylene glycol and low-molecular mass PEGs destabilized RNA Structure and caused the riboswitch to sample secondary Structures different from those observed in simple buffered solutions or in cells. In the presence of larger PEGs, longer-range loop–loop interactions were more similar to those in cells than in buffer alone, consistent with prior wor...
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the cellular environment stabilizes adenine riboswitch RNA Structure
Biochemistry, 2013Co-Authors: Jillian Tyrrell, Kevin M Weeks, Jennifer L Mcginnis, Gary J PielakAbstract:There are large differences between the intracellular environment and the conditions widely used to study RNA Structure and function in vitro. To assess the effects of the crowded cellular environment on RNA, we examined the Structure and ligand binding function of the adenine riboswitch aptamer domain in healthy, growing Escherichia coli cells at single-nucleotide resolution on the minute time scale using SHAPE (selective 2′-hydroxyl acylation analyzed by primer extension). The ligand-bound aptamer Structure is essentially the same in cells and in buffer at 1 mM Mg2+, the approximate Mg2+ concentration we measured in cells. In contrast, the in-cell conformation of the ligand-free aptamer is much more similar to the fully folded ligand-bound state. Even adding high Mg2+ concentrations to the buffer used for in vitro analyses did not yield the conformation observed for the free aptamer in cells. The cellular environment thus stabilizes the aptamer significantly more than does Mg2+ alone. Our results show t...
David Haussler - One of the best experts on this subject based on the ideXlab platform.
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fragseq transcriptome wide RNA Structure probing using high throughput sequencing
Nature Methods, 2010Co-Authors: Jason G. Underwood, Andrew V. Uzilov, Jacob E. Mainzer, David H. Mathews, Sofie R. Salama, Sol Katzman, Todd M Lowe, Courtney Onodera, David HausslerAbstract:High-throughput sequencing of RNA fragments generated from a single-strand RNA-specific nuclease followed by novel computational analysis yields structural insights into noncoding RNA at the transcriptome level.
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FragSeq: Transcriptome-wide RNA Structure probing using high-throughput sequencing
Nature Methods, 2010Co-Authors: Jason G. Underwood, Andrew V. Uzilov, Courtney S. Onodera, Jacob E. Mainzer, David H. Mathews, Sofie R. Salama, Sol Katzman, Todd M Lowe, David HausslerAbstract:Classical approaches to determine Structures of noncoding RNA (ncRNA) probed only one RNA at a time with enzymes and chemicals, using gel electrophoresis to identify reactive positions. To accelerate RNA Structure inference, we developed fragmentation sequencing (FragSeq), a high-throughput RNA Structure probing method that uses high-throughput RNA sequencing of fragments generated by digestion with nuclease P1, which specifically cleaves single-stranded nucleic acids. In experiments probing the entire mouse nuclear transcriptome, we accurately and simultaneously mapped single-stranded RNA regions in multiple ncRNAs with known Structure. We probed in two cell types to verify reproducibility. We also identified and experimentally validated Structured regions in ncRNAs with, to our knowledge, no previously reported probing data.
Howard Y Chang - One of the best experts on this subject based on the ideXlab platform.
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RNA Structure maps across mammalian cellular compartments
Nature Structural & Molecular Biology, 2019Co-Authors: Lei Sun, Howard Y Chang, Furqan M Fazal, James P Broughton, Byron Lee, Lei Tang, Wenze Huang, Eric T Kool, Qiangfeng Cliff ZhangAbstract:RNA Structure is intimately connected to each step of gene expression. Recent advances have enabled transcriptome-wide maps of RNA secondary Structure, called 'RNA structuromes'. However, previous whole-cell analyses lacked the resolution to unravel the landscape and also the regulatory mechanisms of RNA structural changes across subcellular compartments. Here we reveal the RNA structuromes in three compartments, chromatin, nucleoplasm and cytoplasm, in human and mouse cells. The cytotopic structuromes substantially expand RNA structural information and enable detailed investigation of the central role of RNA Structure in linking transcription, translation and RNA decay. We develop a resource with which to visualize the interplay of RNA-protein interactions, RNA modifications and RNA Structure and predict both direct and indirect reader proteins of RNA modifications. We also validate a novel role for the RNA-binding protein LIN28A as an N6-methyladenosine modification 'anti-reader'. Our results highlight the dynamic nature of RNA Structures and its functional importance in gene regulation.
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dynamic regulation of RNA Structure in mammalian cells
bioRxiv, 2018Co-Authors: Lei Sun, Howard Y Chang, Furqan M Fazal, James P Broughton, Byron Lee, Lei Tang, Wenze Huang, Qiangfeng Cliff ZhangAbstract:RNA Structure is intimately connected to each step of gene expression. Recent advances have enabled transcriptome-wide maps of RNA secondary Structure, termed RNA structuromes. However, previous whole-cell analyses lacked the resolution to unravel the dynamic regulation of RNA Structure across subcellular states. Here we reveal the RNA structuromes in three compartments-chromatin, nucleoplasm and cytoplasm. The cytotopic structuromes substantially expand RNA structural information, and enable detailed investigation of the central role of RNA Structure in linking transcription, translation, and RNA decay. Through comparative Structure analysis, we develop a resource to visualize the interplay of RNA-protein interactions, RNA chemical modifications, and RNA Structure, and predict both direct and indirect reader proteins of RNA modifications. We validate the novel role of the RNA binding protein LIN28A as an N6-methyladenosine (m6A) modification 'anti-reader'. Our results highlight the dynamic nature of RNA Structures and its functional significance in gene regulation.
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landscape and variation of RNA secondary Structure across the human transcriptome
Nature, 2014Co-Authors: Yue Wan, Robert C Spitale, Eran Segal, Qiangfeng Cliff Zhang, Ryan A Flynn, Ohad Manor, Zhengqing Ouyang, Jiajing Zhang, Michael Snyder, Howard Y ChangAbstract:In parallel to the genetic code for protein synthesis, a second layer of information is embedded in all RNA transcripts in the form of RNA Structure. RNA Structure influences practically every step in the gene expression program. However, the nature of most RNA Structures or effects of sequence variation on Structure are not known. Here we report the initial landscape and variation of RNA secondary Structures (RSSs) in a human family trio (mother, father and their child). This provides a comprehensive RSS map of human coding and non-coding RNAs. We identify unique RSS signatures that demarcate open reading frames and splicing junctions, and define authentic microRNA-binding sites. Comparison of native deproteinized RNA isolated from cells versus refolded purified RNA suggests that the majority of the RSS information is encoded within RNA sequence. Over 1,900 transcribed single nucleotide variants (approximately 15% of all transcribed single nucleotide variants) alter local RNA Structure. We discover simple sequence and spacing rules that determine the ability of point mutations to impact RSSs. Selective depletion of 'riboSNitches' versus structurally synonymous variants at precise locations suggests selection for specific RNA shapes at thousands of sites, including 3' untranslated regions, binding sites of microRNAs and RNA-binding proteins genome-wide. These results highlight the potentially broad contribution of RNA Structure and its variation to gene regulation.
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understanding the transcriptome through RNA Structure
Nature Reviews Genetics, 2011Co-Authors: Yue Wan, Robert C Spitale, Michael Kertesz, Eran Segal, Howard Y ChangAbstract:RNA Structure is crucial for gene regulation and function. In the past, transcriptomes have largely been parsed by primary sequences and expression levels, but it is now becoming feasible to annotate and compare transcriptomes based on RNA Structure. In addition to computational prediction methods, the recent advent of experimental techniques to probe RNA Structure by high-throughput sequencing has enabled genome-wide measurements of RNA Structure and has provided the first picture of the structural organization of a eukaryotic transcriptome - the 'RNA structurome'. With additional advances in method refinement and interpretation, structural views of the transcriptome should help to identify and validate regulatory RNA motifs that are involved in diverse cellular processes and thereby increase understanding of RNA function.
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genome wide measurement of RNA secondary Structure in yeast
Nature, 2010Co-Authors: Michael Kertesz, Yue Wan, Howard Y Chang, Elad Mazor, John L Rinn, Robert C Nutter, Eran SegalAbstract:The Structures of RNA molecules are often important for their function and regulation, yet there are no experimental techniques for genome-scale measurement of RNA Structure. Here we describe a novel strategy termed parallel analysis of RNA Structure (PARS), which is based on deep sequencing fragments of RNAs that were treated with Structure-specific enzymes, thus providing simultaneous in vitro profiling of the secondary Structure of thousands of RNA species at single nucleotide resolution. We apply PARS to profile the secondary Structure of the messenger RNAs (mRNAs) of the budding yeast Saccharomyces cerevisiae and obtain structural profiles for over 3,000 distinct transcripts. Analysis of these profiles reveals several RNA structural properties of yeast transcripts, including the existence of more secondary Structure over coding regions compared with untranslated regions, a three-nucleotide periodicity of secondary Structure across coding regions and an anti-correlation between the efficiency with which an mRNA is translated and the Structure over its translation start site. PARS is readily applicable to other organisms and to profiling RNA Structure in diverse conditions, thus enabling studies of the dynamics of secondary Structure at a genomic scale.
David H. Mathews - One of the best experts on this subject based on the ideXlab platform.
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fragseq transcriptome wide RNA Structure probing using high throughput sequencing
Nature Methods, 2010Co-Authors: Jason G. Underwood, Andrew V. Uzilov, Jacob E. Mainzer, David H. Mathews, Sofie R. Salama, Sol Katzman, Todd M Lowe, Courtney Onodera, David HausslerAbstract:High-throughput sequencing of RNA fragments generated from a single-strand RNA-specific nuclease followed by novel computational analysis yields structural insights into noncoding RNA at the transcriptome level.
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FragSeq: Transcriptome-wide RNA Structure probing using high-throughput sequencing
Nature Methods, 2010Co-Authors: Jason G. Underwood, Andrew V. Uzilov, Courtney S. Onodera, Jacob E. Mainzer, David H. Mathews, Sofie R. Salama, Sol Katzman, Todd M Lowe, David HausslerAbstract:Classical approaches to determine Structures of noncoding RNA (ncRNA) probed only one RNA at a time with enzymes and chemicals, using gel electrophoresis to identify reactive positions. To accelerate RNA Structure inference, we developed fragmentation sequencing (FragSeq), a high-throughput RNA Structure probing method that uses high-throughput RNA sequencing of fragments generated by digestion with nuclease P1, which specifically cleaves single-stranded nucleic acids. In experiments probing the entire mouse nuclear transcriptome, we accurately and simultaneously mapped single-stranded RNA regions in multiple ncRNAs with known Structure. We probed in two cell types to verify reproducibility. We also identified and experimentally validated Structured regions in ncRNAs with, to our knowledge, no previously reported probing data.
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accurate shape directed RNA Structure determination
Proceedings of the National Academy of Sciences of the United States of America, 2009Co-Authors: Katherine E Deigan, David H. Mathews, Kevin M WeeksAbstract:Almost all RNAs can fold to form extensive base-paired secondary Structures. Many of these Structures then modulate numerous fundamental elements of gene expression. Deducing these Structure–function relationships requires that it be possible to predict RNA secondary Structures accurately. However, RNA secondary Structure prediction for large RNAs, such that a single predicted Structure for a single sequence reliably represents the correct Structure, has remained an unsolved problem. Here, we demonstrate that quantitative, nucleotide-resolution information from a SHAPE experiment can be interpreted as a pseudo-free energy change term and used to determine RNA secondary Structure with high accuracy. Free energy minimization, by using SHAPE pseudo-free energies, in conjunction with nearest neighbor parameters, predicts the secondary Structure of deproteinized Escherichia coli 16S rRNA (>1,300 nt) and a set of smaller RNAs (75–155 nt) with accuracies of up to 96–100%, which are comparable to the best accuracies achievable by comparative sequence analysis.
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efficient pairwise RNA Structure prediction using probabilistic alignment constraints in dynalign
BMC Bioinformatics, 2007Co-Authors: Arif Harmanci, Gaurav Sharma, David H. MathewsAbstract:Background Joint alignment and secondary Structure prediction of two RNA sequences can significantly improve the accuracy of the structural predictions. Methods addressing this problem, however, are forced to employ constraints that reduce computation by restricting the alignments and/or Structures (i.e. folds) that are permissible. In this paper, a new methodology is presented for the purpose of establishing alignment constraints based on nucleotide alignment and insertion posterior probabilities. Using a hidden Markov model, posterior probabilities of alignment and insertion are computed for all possible pairings of nucleotide positions from the two sequences. These alignment and insertion posterior probabilities are additively combined to obtain probabilities of co-incidence for nucleotide position pairs. A suitable alignment constraint is obtained by thresholding the co-incidence probabilities. The constraint is integrated with Dynalign, a free energy minimization algorithm for joint alignment and secondary Structure prediction. The resulting method is benchmarked against the previous version of Dynalign and against other programs for pairwise RNA Structure prediction.
Jeffrey S. Kieft - One of the best experts on this subject based on the ideXlab platform.
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a folded viral noncoding RNA blocks host cell exoribonucleases through a conformationally dynamic RNA Structure
Proceedings of the National Academy of Sciences of the United States of America, 2018Co-Authors: Anna-lena Steckelberg, Benjamin M Akiyama, David A. Costantino, Jeffrey S. KieftAbstract:Folded RNA elements that block processive 5′ → 3′ cellular exoribonucleases (xrRNAs) to produce biologically active viral noncoding RNAs have been discovered in flaviviruses, potentially revealing a new mode of RNA maturation. However, whether this RNA Structure-dependent mechanism exists elsewhere and, if so, whether a singular RNA fold is required, have been unclear. Here we demonstrate the existence of authentic RNA Structure-dependent xrRNAs in dianthoviruses, plant-infecting viruses unrelated to animal-infecting flaviviruses. These xrRNAs have no sequence similarity to known xrRNAs; thus, we used a combination of biochemistry and virology to characterize their sequence requirements and mechanism of stopping exoribonucleases. By solving the Structure of a dianthovirus xrRNA by X-ray crystallography, we reveal a complex fold that is very different from that of the flavivirus xrRNAs. However, both versions of xrRNAs contain a unique topological feature, a pseudoknot that creates a protective ring around the 5′ end of the RNA Structure; this may be a defining structural feature of xrRNAs. Single-molecule FRET experiments reveal that the dianthovirus xrRNAs undergo conformational changes and can use “codegradational remodeling,” exploiting the exoribonucleases’ degradation-linked helicase activity to help form their resistant Structure; such a mechanism has not previously been reported. Convergent evolution has created RNA Structure-dependent exoribonuclease resistance in different contexts, which establishes it as a general RNA maturation mechanism and defines xrRNAs as an authentic functional class of RNAs.
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a folded viral noncoding RNA blocks host cell exoribonucleases through programmed remodeling of RNA Structure
bioRxiv, 2018Co-Authors: Anna-lena Steckelberg, Benjamin M Akiyama, David A. Costantino, Jeffrey S. KieftAbstract:Folded RNA elements that block processive 5'-->3' cellular exoribonucleases (xrRNAs) to produce biologically active viral non-coding RNAs were discovered in flaviviruses, potentially revealing a new mode of RNA maturation. However, it was unknown if this RNA Structure-dependent mechanism exists elsewhere and if so, whether a singular RNA fold is required. Here, we demonstrate the existence of authentic RNA Structure-dependent xrRNAs in dianthoviruses, plant-infecting viruses unrelated to animal-infecting flaviviruses. These novel xrRNAs have no sequence similarity to known xrRNAs, thus we used a combination of biochemistry and virology to characterize their sequence requirements and mechanism of stopping exoribonucleases. By solving the Structure of a dianthovirus xrRNAs by x-ray crystallography, we reveal a complex fold that is very different from the flavivirus xrRNAs. However, both versions of xrRNAs contain a unique topological feature that is created by a different set of intramolecular contacts; this may be a defining structural feature of xrRNAs. Remarkably, the dianthovirus xrRNA can use 'co-degradational remodeling,' exploiting the exoribonuclease's degradation-linked helicase activity to help form their resistant Structure; such a mechanism has not previously been reported. Convergent evolution has created RNA Structure-dependent exoribonuclease resistance in different contexts, which establishes it as a general RNA maturation mechanism and defines xrRNAs as an authentic functional class of RNAs.
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viral ires RNA Structures and ribosome interactions
Trends in Biochemical Sciences, 2008Co-Authors: Jeffrey S. KieftAbstract:In eukaryotes, protein synthesis initiates primarily by a mechanism that requires a modified nucleotide ‘cap’ on the mRNA and also proteins that recruit and position the ribosome. Many pathogenic viruses use an alteRNAtive, cap-independent mechanism that substitutes RNA Structure for the cap and many proteins. The RNAs driving this process are called inteRNAl ribosome-entry sites (IRESs) and some are able to bind the ribosome directly using a specific 3D RNA Structure. Recent Structures of IRES RNAs and IRES–ribosome complexes are revealing the structural basis of viral IRES’ ‘hijacking’ of the protein-making machinery. It now seems that there are fundamental differences in the 3D Structures used by different IRESs, although there are some common features in how they interact with ribosomes.
