Identifying pairwise RNA-RNA interactions is key to understanding how RNAs fold and interact with other RNAs inside the cell. We present a high-throughput approach, sequencing of psoralen crosslinked, ligated, and selected hybrids (SPLASH), that maps pairwise RNA interactions in vivo with high sensitivity and specificity, genome-wide. Applying SPLASH to human and yeast transcriptomes revealed the diversity and dynamics of thousands of long-range intra- and intermolecular RNA-RNA interactions. Our analysis highlighted key structural features of RNA classes, including the modular organization of mRNAs, its impact on translation and decay, and the enrichment of long-range interactions in noncoding RNAs. Additionally, intermolecular mRNA interactions were organized into network clusters and were remodeled during cellular differentiation. We also identified hundreds of known and new snoRNA-rRNA binding sites, expanding our knowledge of rRNA biogenesis. These results highlight the underexplored complexity of RNA interactomes and pave the way to better understanding how RNA organization impacts biology.

Short single-stranded nucleic acids are ubiquitous in biological processes; understanding their physical properties provides insights to nucleic acid folding and dynamics. We used small-angle x-ray scattering to study 8-100 residue homopolymeric single-stranded DNAs in solution, without external forces or labeling probes. Poly-T's structural ensemble changes with increasing ionic strength in a manner consistent with a polyelectrolyte persistence length theory that accounts for molecular flexibility. For any number of residues, poly-A is consistently more elongated than poly-T, likely due to the tendency of A residues to form stronger base-stacking interactions than T residues.

Dengue (DENV) and Zika (ZIKV) viruses are clinically important members of the Flaviviridae family with an 11 kb positive strand RNA genome that folds to enable virus function. Here, we perform structure and interaction mapping on four DENV and ZIKV strains inside virions and in infected cells. Comparative analysis of SHAPE reactivities across serotypes nominates potentially functional regions that are highly structured, conserved, and contain low synonymous mutation rates. Interaction mapping by SPLASH identifies many pair-wise interactions, 40% of which form alternative structures, suggesting extensive structural heterogeneity. Analysis of shared interactions between serotypes reveals a conserved macro-organization whereby interactions can be preserved at physical locations beyond sequence identities. We further observe that longer-range interactions are preferentially disrupted inside cells, and show the importance of new interactions in virus fitness. These findings deepen our understanding of Flavivirus genome organization and serve as a resource for designing therapeutics in targeting RNA viruses.

Protein ␣-helices are ubiquitous secondary structural elements, seldom considered to be stable without tertiary contacts. However, amino acid sequences in proteins that are based on alternating repeats of four glutamic acid (E) residues and four positively charged residues, a combination of arginine (R) and lysine (K), have been shown to form stable ␣-helices in a few proteins, in the absence of tertiary interactions. Here, we find that this ER/K motif is more prevalent than previously reported, being represented in proteins of diverse function from archaea to humans. By using molecular dynamics (MD) simulations, we characterize a dynamic pattern of side-chain interactions that extends along the backbone of ER/K ␣-helices. A simplified model predicts that side-chain interactions alone contribute substantial bending rigidity (0.5 pN/ nm) to ER/K ␣-helices. Results of small-angle x-ray scattering (SAXS) and single-molecule optical-trap analyses are consistent with the high bending rigidity predicted by our model. Thus, the ER/K ␣-helix is an isolated secondary structural element that can efficiently span long distances in proteins, making it a promising tool in designing synthetic proteins. We propose that the significant rigidity of the ER/K ␣-helix can help regulate protein function, as a force transducer between protein subdomains.MD simulations ͉ protein structure ͉ single-molecule analysis ͉ small-angle x-ray scattering

RNA molecules play integral roles in gene regulation, and understanding their structures gives us important insights into their biological functions. Despite recent developments in template-based and parameterized energy functions, the structure of RNA-in particular the nonhelical regions-is still difficult to predict. Knowledge-based potentials have proven efficient in protein structure prediction. In this work, we describe two differentiable knowledge-based potentials derived from a curated data set of RNA structures, with all-atom or coarse-grained representation, respectively. We focus on one aspect of the prediction problem: the identification of native-like RNA conformations from a set of near-native models. Using a variety of near-native RNA models generated from three independent methods, we show that our potential is able to distinguish the native structure and identify native-like conformations, even at the coarse-grained level. The all-atom version of our knowledge-based potential performs better and appears to be more effective at discriminating near-native RNA conformations than one of the most highly regarded parameterized potential. The fully differentiable form of our potentials will additionally likely be useful for structure refinement and/or molecular dynamics simulations.

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We develop a unique algorithm implemented in the program MOSAICS (Methodologies for Optimization and Sampling in Computational Studies) that is capable of nanoscale modeling without compromising the resolution of interest. This is achieved by modeling with customizable hierarchical degrees of freedom, thereby circumventing major limitations of conventional molecular modeling. With the emergence of RNA-based nanotechnology, large RNAs in all-atom representation are used here to benchmark our algorithm. Our method locates all favorable structural states of a model RNA of significant complexity while improving sampling accuracy and increasing speed many fold over existing all-atom RNA modeling methods. We also modeled the effects of sequence mutations on the structural building blocks of tRNA-based nanotechnology. With its flexibility in choosing arbitrary degrees of freedom as well as in allowing different all-atom energy functions, MOSAICS is an ideal tool to model and design biomolecules of the nanoscale.hierarchical sampling | junctions | molecular simulation | Monte Carlo | nanostructure C omputational modeling is an important aspect of biology and nanotechnology. In silico design and manipulation of nanostructures often precedes experimental validation (1, 2), while effective computational structure prediction of biomolecules paves the way for biomolecular design (3). Most molecular modeling packages are either general but inefficient in modeling large molecular systems or designed to be effective for modeling only specific types of systems (e.g., coarse-grained modeling of DNA as an elastic rod) and are therefore not general purpose. These limitations are mainly a consequence of two major obstacles to computational modeling: (i) the high dimensionality of the systems studied and (ii) the complexity of the potential energy surface guiding the simulation. When attempting to model nanoscale systems at all-atom resolution, the combination of these two factors often leads to intractable complexity.A wide range of methods has been proposed to remove obstacles presented by high dimensionality (4-6) and complex energy surfaces (7-12), but none of these studies has considered both limitations in the same context. The difficulty of such a unified approach is that limitations arising from both obstacles are related in that reducing dimensionality often results in a more complex energy surface. For example, conformational sampling using dihedral angles, which is a common solution to the high dimensionality problem of macromolecular assemblies, often results in a more complex energy surface with energy barriers that could have been easily avoided in Cartesian space. The algorithm [implemented in MOSAICS (13)] proposed here overcomes the problem of high dimensionality without increasing the complexity of the underlying energy surface. This is achieved by sampling with hierarchical variables: Degrees of freedom that introduce large conformational changes are combined with degrees of freedom that allow for local rearrangeme...

Riboswitches are gene-regulating RNAs that are usually found in the 59-untranslated regions of messenger RNA. As the sugarphosphate backbone of RNA is highly negatively charged, the folding and ligand-binding interactions of riboswitches are strongly dependent on the presence of cations. Using small angle X-ray scattering (SAXS) and hydroxyl radical footprinting, we examined the cation dependence of the different folding stages of the glycine-binding riboswitch from Vibrio cholerae. We found that the partial folding of the tandem aptamer of this riboswitch in the absence of glycine is supported by all tested monoand divalent ions, suggesting that this transition is mediated by nonspecific electrostatic screening. Poisson-Boltzmann calculations using SAXS-derived low-resolution structural models allowed us to perform an energetic dissection of this process. The results showed that a model with a constant favorable contribution to folding that is opposed by an unfavorable electrostatic term that varies with ion concentration and valency provides a reasonable quantitative description of the observed folding behavior. Glycine binding, on the other hand, requires specific divalent ions binding based on the observation that Mg 2+ , Ca 2+ , and Mn 2+ facilitated glycine binding, whereas other divalent cations did not. The results provide a case study of how iondependent electrostatic relaxation, specific ion binding, and ligand binding can be coupled to shape the energetic landscape of a riboswitch and can begin to be quantitatively dissected.