Joshua S. Martin

Disease-associated mutations that alter the RNA structural ensemble.

Genome-wide association studies (GWAS) often identify disease-associated mutations in intergenic and non-coding regions of the genome. Given the high percentage of the human genome that is transcribed, we postulate that for some observed associations the disease phenotype is caused by a structural rearrangement in a regulatory region of the RNA transcript. To identify such mutations, we have performed a genome-wide analysis of all known disease-associated Single Nucleotide Polymorphisms (SNPs) from the Human Gene Mutation Database (HGMD) that map to the untranslated regions (UTRs) of a gene. Rather than using minimum free energy approaches (e.g. mFold), we use a partition function calculation that takes into consideration the ensemble of possible RNA conformations for a given sequence. We identified in the human genome disease-associated SNPs that significantly alter the global conformation of the UTR to which they map. For six disease-states (Hyperferritinemia Cataract Syndrome, β-Thalassemia, Cartilage-Hair Hypoplasia, Retinoblastoma, Chronic Obstructive Pulmonary Disease (COPD), and Hypertension), we identified multiple SNPs in UTRs that alter the mRNA structural ensemble of the associated genes. Using a Boltzmann sampling procedure for sub-optimal RNA structures, we are able to characterize and visualize the nature of the conformational changes induced by the disease-associated mutations in the structural ensemble. We observe in several cases (specifically the 5′ UTRs of FTL and RB1) SNP–induced conformational changes analogous to those observed in bacterial regulatory Riboswitches when specific ligands bind. We propose that the UTR and SNP combinations we identify constitute a “RiboSNitch,” that is a regulatory RNA in which a specific SNP has a structural consequence that results in a disease phenotype. Our SNPfold algorithm can help identify RiboSNitches by leveraging GWAS data and an analysis of the mRNA structural ensemble.

Evolutionary Evidence for Alternative Structure in RNA Sequence Co-variation

Sequence conservation and co-variation of base pairs are hallmarks of structured RNAs. For certain RNAs (e.g. riboswitches), a single sequence must adopt at least two alternative secondary structures to effectively regulate the message. If alternative secondary structures are important to the function of an RNA, we expect to observe evolutionary co-variation supporting multiple conformations. We set out to characterize the evolutionary co-variation supporting alternative conformations in riboswitches to determine the extent to which alternative secondary structures are conserved. We found strong co-variation support for the terminator, P1, and anti-terminator stems in the purine riboswitch by extending alignments to include terminator sequences. When we performed Boltzmann suboptimal sampling on purine riboswitch sequences with terminators we found that these sequences appear to have evolved to favor specific alternative conformations. We extended our analysis of co-variation to classic alignments of group I/II introns, tRNA, and other classes of riboswitches. In a majority of these RNAs, we found evolutionary evidence for alternative conformations that are compatible with the Boltzmann suboptimal ensemble. Our analyses suggest that alternative conformations are selected for and thus likely play functional roles in even the most structured of RNAs.

Differentially expressed miRNAs in retinoblastoma

MicroRNAs (miRNAs) are short non-coding RNA transcripts that have the ability to regulate the expression of target genes, and have been shown to influence the development of various tumors. The purpose of our study is to identify aberrantly expressed miRNAs in retinoblastoma for the discovery of potential therapeutic targets for this disease, and to gain a greater understanding of the mechanisms driving retinoblastoma progression. We report 41 differentially expressed miRNAs (p<0.05) in 12 retinoblastomas as compared to three normal human retinae. Of these miRNAs, many are newly identified as being differentially expressed in retinoblastoma. Further, we report the validations of five of the most downregulated miRNAs in primary human retinoblastomas (p<0.05), human retinoblastoma cell lines, and mouse retinoblastoma cell lines. This serves as the largest and most comprehensive retinoblastoma miRNA analysis to date with corresponding clinical and pathological characteristics. This is an essential step in the discovery of miRNAs associated with retinoblastoma progression, and in the identification of potential therapeutic targets for this disease.

Single Molecule Cluster Analysis dissects splicing pathway conformational dynamics

We report Single Molecule Cluster Analysis (SiMCAn), which utilizes hierarchical clustering of hidden Markov modeling–fitted single-molecule fluorescence resonance energy transfer (smFRET) trajectories to dissect the complex conformational dynamics of biomolecular machines. We used this method to study the conformational dynamics of a precursor mRNA during the splicing cycle as carried out by the spliceosome. By clustering common dynamic behaviors derived from selectively blocked splicing reactions, SiMCAn was able to identify the signature conformations and dynamic behaviors of multiple ATP-dependent intermediates. In addition, it identified an open conformation adopted late in splicing by a 3′ splice-site mutant, invoking a mechanism for substrate proofreading. SiMCAn enables rapid interpretation of complex single-molecule behaviors and should prove useful for the comprehensive analysis of a plethora of dynamic cellular machines.

HUGIn: Hi-C Unifying Genomic Interrogator

Motivation High throughput chromatin conformation capture (3C) technologies, such as Hi-C and ChIA-PET, have the potential to elucidate the functional roles of non-coding variants. However, most of published genome-wide unbiased chromatin organization studies have used cultured cell lines, limiting their generalizability. Results We developed a web browser, HUGIn, to visualize Hi-C data generated from 21 human primary tissues and cell lines. HUGIn enables assessment of chromatin contacts both constitutive across and specific to tissue(s) and/or cell line(s) at any genomic loci, including GWAS SNPs, eQTLs and cis-regulatory elements, facilitating the understanding of both GWAS and eQTL results and functional genomics data. Availability and implementation HUGIn is available at http://yunliweb.its.unc.edu/HUGIn. Contact yunli@med.unc.edu or hum@ccf.org. Supplementary information Supplementary data are available at Bioinformatics online.

Exhaustive Enumeration of Kinetic Model Topologies for the Analysis of Time-Resolved RNA Folding

Unlike protein folding, the process by which a large RNA molecule adopts a functionally active conformation remains poorly understood. Chemical mapping techniques, such as Hydroxyl Radical (·OH) footprinting report on local structural changes in an RNA as it folds with single nucleotide resolution. The analysis and interpretation of this kinetic data requires the identification and subsequent optimization of a kinetic model and its parameters. We detail our approach to this problem, specifically focusing on a novel strategy to overcome a factorial explosion in the number of possible models that need to be tested to identify the best fitting model. Previously, smaller systems (less than three intermediates) were computationally tractable using a distributed computing approach. However, for larger systems with three or more intermediates, the problem became computationally intractable. With our new enumeration strategy, we are able to significantly reduce the number of models that need to be tested using non-linear least squares optimization, allowing us to study systems with up to five intermediates. Furthermore, two intermediate systems can now be analyzed on a desktop computer, which eliminates the need for a distributed computing solution for most medium-sized data sets. Our new approach also allows us to study potential degeneracy in kinetic model selection, elucidating the limits of the method when working with large systems. This work establishes clear criteria for determining if experimental ·OH data is sufficient to determine the underlying kinetic model, or if other experimental modalities are required to resolve any degeneracy.

Novel miRNA-31 and miRNA-200a-Mediated Regulation of Retinoblastoma Proliferation.

Retinoblastoma is the most common intraocular tumor in children. Current management includes broad-based treatments such as chemotherapy, enucleation, laser therapy, or cryotherapy. However, therapies that target specific pathways important for retinoblastoma progression could provide valuable alternatives for treatment. MicroRNAs are short, noncoding RNA transcripts that can regulate the expression of target genes, and their aberrant expression often facilitates disease. The identification of post-transcriptional events that occur after the initiating genetic lesions could further define the rapidly aggressive growth displayed by retinoblastoma tumors. In this study, we used two phenotypically different retinoblastoma cell lines to elucidate the roles of miRNA-31 and miRNA-200a in tumor proliferation. Our approach confirmed that miRNAs-31 and -200a expression is significantly reduced in human retinoblastomas. Moreover, overexpression of these two miRNAs restricts the expansion of a highly proliferative cell line (Y79), but does not restrict the growth rate of a less aggressive cell line (Weri1). Gene expression profiling of miRNA-31 and/or miRNA-200a-overexpressing cells identified differentially expressed mRNAs associated with the divergent response of the two cell lines. This work has the potential to enhance the development of targeted therapeutic approaches for retinoblastoma and improve the efficacy of treatment.

Understanding the role of three-dimensional topology in determining the folding intermediates of group i introns

Many RNA molecules exert their biological function only after folding to unique three-dimensional structures. For long, noncoding RNA molecules, the complexity of finding the native topology can be a major impediment to correct folding to the biologically active structure. An RNA molecule may fold to a near-native structure but not be able to continue to the correct structure due to a topological barrier such as crossed strands or incorrectly stacked helices. Achieving the native conformation thus requires unfolding and refolding, resulting in a long-lived intermediate. We investigate the role of topology in the folding of two phylogenetically related catalytic group I introns, the Twort and Azoarcus group I ribozymes. The kinetic models describing the Mg(2+)-mediated folding of these ribozymes were previously determined by time-resolved hydroxyl (∙OH) radical footprinting. Two intermediates formed by parallel intermediates were resolved for each RNA. These data and analytical ultracentrifugation compaction analyses are used herein to constrain coarse-grained models of these folding intermediates as we investigate the role of nonnative topology in dictating the lifetime of the intermediates. Starting from an ensemble of unfolded conformations, we folded the RNA molecules by progressively adding native constraints to subdomains of the RNA defined by the ∙OH time-progress curves to simulate folding through the different kinetic pathways. We find that nonnative topologies (arrangement of helices) occur frequently in the folding simulations despite using only native constraints to drive the reaction, and that the initial conformation, rather than the folding pathway, is the major determinant of whether the RNA adopts nonnative topology during folding. From these analyses we conclude that biases in the initial conformation likely determine the relative flux through parallel RNA folding pathways.

Mapping the Kinetic Barriers of a Large RNA Molecule's Folding Landscape

The folding of linear polymers into discrete three-dimensional structures is often required for biological function. The formation of long-lived intermediates is a hallmark of the folding of large RNA molecules due to the ruggedness of their energy landscapes. The precise thermodynamic nature of the barriers (whether enthalpic or entropic) that leads to intermediate formation is still poorly characterized in large structured RNA molecules. A classic approach to analyzing kinetic barriers are temperature dependent studies analyzed with Eyrings transition state theory. We applied Eyrings theory to time-resolved hydroxyl radical (•OH) footprinting kinetics progress curves collected at eight temperature from 21.5°C to 51°C to characterize the thermodynamic nature of folding intermediate formation for the Mg2+-mediated folding of the Tetrahymena thermophila group I ribozyme. A common kinetic model configuration describes this RNA folding reaction over the entire temperature range studied consisting of primary (fast) transitions to misfolded intermediates followed by much slower secondary transitions, consistent with previous studies. Eyring analysis reveals that the primary transitions are moderate in magnitude and primarily enthalpic in nature. In contrast, the secondary transitions are daunting in magnitude and entropic in nature. The entropic character of the secondary transitions is consistent with structural rearrangement of the intermediate species to the final folded form. This segregation of kinetic control reveals distinctly different molecular mechanisms during the two stages of RNA folding and documents the importance of entropic barriers to defining rugged RNA folding landscapes.

Rapid quantification and analysis of kinetic • OH radical footprinting data using SAFA

The use of highly reactive chemical species to probe the structure and dynamics of nucleic acids is greatly simplified by software that enables rapid quantification of the gel images that result from these experiments. Semiautomated footprinting analysis (SAFA) allows a user to quickly and reproducibly quantify a chemical footprinting gel image through a series of steps that rectify, assign, and integrate the relative band intensities. The output of this procedure is raw band intensities that report on the relative reactivity of each nucleotide with the chemical probe. We describe here how to obtain these raw band intensities using SAFA and the subsequent normalization and analysis procedures required to process these data. In particular, we focus on analyzing time-resolved hydroxyl radical ((•)OH) data, which we use to monitor the kinetics of folding of a large RNA (the L-21 T. thermophila group I intron). Exposing the RNA to bursts of (•)OH radicals at specific time points during the folding process monitors the time progress of the reaction. Specifically, we identify protected (nucleotides that become inaccessible to the (•)OH radical probe when folded) and invariant (nucleotides with constant accessibility to the (•)OH probe) residues that we use for monitoring and normalization of the data. With this analysis, we obtain time-progress curves from which we determine kinetic rates of folding. We also report on a data visualization tool implemented in SAFA that allows users to map data onto a secondary structure diagram.