Odd-even disparity in the population of slipped hairpins in RNA repeat sequences with implications for phase separation

Molecular Drivers of RNA Phase Separation

RNA molecules are essential in orchestrating the assembly of biomolecular condensates and membraneless compartments in cells. Many condensates form via the association of RNA with proteins containing specific RNA binding motifs. However, recent reports indicate that low-complexity RNA sequences can self-assemble into condensate phases without protein assistance. Divalent cations significantly influence the thermodynamics and dynamics of RNA condensates, which exhibit base-specific lower-critical solution temperatures (LCST). The precise molecular origins of these temperatures remain elusive. In this study, we employ atomistic molecular simulations to elucidate the molecular driving forces governing the temperature-dependent phase behavior of RNA, providing new insights into the origins of LCST. Using RNA tetranucleotides and their chemically modified analogs, we map RNA condensates' equilibrium thermodynamic profiles and structural ensembles across various temperatures and ionic conditions. Our findings reveal that magnesium ions promote LCST behavior by inducing local order-disorder transitions within RNA structures. Consistent with experimental observations, we demonstrate that the thermal stability of RNA condensates follows the Poly(G) > Poly(A) > Poly(C) > Poly(U) order shaped by the interplay of base-stacking and hydrogen bonding interactions. Furthermore, our simulations show that ionic conditions and post-translational modifications can fine-tune RNA self-assembly and modulate condensate physical properties.

RPS 2.0: an updated database of RNAs involved in liquid-liquid phase separation

Liquid-liquid phase separation (LLPS) is a crucial process for the formation of biomolecular condensates such as coacervate droplets, P-bodies and stress granules, which play critical roles in many physiological and pathological processes. Increasing studies have shown that not only proteins but also RNAs play a critical role in LLPS. To host LLPS-associated RNAs, we previously developed a database named 'RPS' in 2021. In this study, we present an updated version RPS 2.0 (https://rps.renlab.cn/) to incorporate the newly generated data and to host new LLPS-associated RNAs driven by post-transcriptional regulatory mechanisms. Currently, RPS 2.0 hosts 171 301 entries of LLPS-associated RNAs in 24 different biomolecular condensates with four evidence types, including 'Reviewed', 'High-throughput (LLPS enrichment)', 'High-throughput (LLPS perturbation)' and 'Predicted', and five event types, including 'Expression', 'APA', 'AS', 'A-to-I' and 'Modification'. Additionally, extensive annotations of LLPS-associated RNAs are provided in RPS 2.0, including RNA sequence and structure features, RNA-protein/RNA-RNA interactions, RNA modifications, as well as diseases related annotations. We expect that RPS 2.0 will further promote research of LLPS-associated RNAs and deepen our understanding of the biological functions and regulatory mechanisms of LLPS.

Sequence complexity and monomer rigidity control the morphologies and aging dynamics of protein aggregates

Understanding the biophysical basis of protein aggregation is important in biology because of the potential link to several misfolding diseases. Although experiments have shown that protein aggregates adopt a variety of morphologies, the dynamics of their formation are less well characterized. Here, we introduce a minimal model to explore the dependence of the aggregation dynamics on the structural and sequence features of the monomers. Using simulations, we demonstrate that sequence complexity (codified in terms of word entropy) and monomer rigidity profoundly influence the dynamics and morphology of the aggregates. Flexible monomers with low sequence complexity (corresponding to repeat sequences) form liquid-like droplets that exhibit ergodic behavior. Strikingly, these aggregates abruptly transition to more ordered structures, reminiscent of amyloid fibrils, when the monomer rigidity is increased. In contrast, aggregates resulting from monomers with high sequence complexity are amorphous and display nonergodic glassy dynamics. The heterogeneous dynamics of the low and high-complexity sequences follow stretched exponential kinetics, which is one of the characteristics of glassy dynamics. Importantly, at nonzero values of the bending rigidities, the aggregates age with the relaxation times that increase with the waiting time. Informed by these findings, we provide insights into aging dynamics in protein condensates and contrast the behavior with the dynamics expected in RNA repeat sequences. Our findings underscore the influence of the monomer characteristics in shaping the morphology and dynamics of protein aggregates, thus providing a foundation for deciphering the general rules governing the behavior of protein condensates.

Accelerated Simulations Reveal Physicochemical Factors Governing Stability and Composition of RNA Clusters

Under certain conditions, RNA repeat sequences phase separate, yielding protein-free biomolecular condensates. Importantly, RNA repeat sequences have also been implicated in neurological disorders, such as Huntington's disease. Thus, mapping repeat sequences to their phase behavior, functions, and dysfunctions is an active area of research. However, despite several advances, it remains challenging to characterize the RNA phase behavior at a submolecular resolution. Here, we have implemented a residue-resolution coarse-grained model in LAMMPS─that incorporates both the RNA sequence and structure─to study the clustering propensities of protein-free RNA systems. Importantly, we achieve a multifold speedup in the simulation time compared to previous work. Leveraging this efficiency, we study the clustering propensity of all 20 nonredundant trinucleotide repeat sequences. Our results align with findings from experiments, emphasizing that canonical base-pairing and G-U wobble pairs play dominant roles in regulating cluster formation of RNA repeat sequences. Strikingly, we find strong entropic contributions to the stability and composition of RNA clusters, which is demonstrated for single-component RNA systems as well as binary mixtures of trinucleotide repeats. Additionally, we investigate the clustering behaviors of trinucleotide (odd) repeats and their quadranucleotide (even) counterparts. We observe that odd repeats exhibit stronger clustering tendencies, attributed to the presence of consecutive base pairs in their sequences that are disrupted in even repeat sequences. Altogether, our work extends the set of computational tools for probing RNA cluster formation at submolecular resolution and uncovers physicochemical principles that govern the stability and composition of the resulting clusters.

Stick-slip unfolding favors self-association of expanded HTT mRNA

In Huntington's Disease (HD) and related disorders, expansion of CAG trinucleotide repeats produces a toxic gain of function in affected neurons. Expanded huntingtin (expHTT) mRNA forms aggregates that sequester essential RNA binding proteins, dysregulating mRNA processing and translation. The physical basis of RNA aggregation has been difficult to disentangle owing to the heterogeneous structure of the CAG repeats. Here, we probe the folding and unfolding pathways of expHTT mRNA using single-molecule force spectroscopy. Whereas normal HTT mRNAs unfold reversibly and cooperatively, expHTT mRNAs with 20 or 40 CAG repeats slip and unravel non-cooperatively at low tension. Slippage of CAG base pairs is punctuated by concerted rearrangement of adjacent CCG trinucleotides, trapping partially folded structures that readily base pair with another RNA strand. We suggest that the conformational entropy of the CAG repeats, combined with stable CCG base pairs, creates a stick-slip behavior that explains the aggregation propensity of expHTT mRNA.

Stick-slip unfolding favors self-association of expanded HTT mRNA

In Huntington's Disease (HD) and related disorders, expansion of CAG trinucleotide repeats produces a toxic gain of function in affected neurons. Expanded huntingtin (expHTT) mRNA forms aggregates that sequester essential RNA binding proteins, dysregulating mRNA processing and translation. The physical basis of RNA aggregation has been difficult to disentangle owing to the heterogeneous structure of the CAG repeats. Here, we probe the folding and unfolding pathways of expHTT mRNA using single-molecule force spectroscopy. Whereas normal HTT mRNAs unfold reversibly and cooperatively, expHTT mRNAs with 20 or 40 CAG repeats slip and unravel non-cooperatively at low tension. Slippage of CAG base pairs is punctuated by concerted rearrangement of adjacent CCG trinucleotides, trapping partially folded structures that readily base pair with another RNA strand. We suggest that the conformational entropy of the CAG repeats, combined with stable CCG base pairs, creates a stick-slip behavior that explains the aggregation propensity of expHTT mRNA.

Energy landscapes of homopolymeric RNAs revealed by deep unsupervised learning

Conformational dynamics of RNA plays important roles in a variety of cellular functions such as transcriptional regulation, catalysis, scaffolding, and sensing. Recently, RNAs with low-complexity sequences have been shown to phase separate and form condensate phases similar to lowcomplexity protein domains. The affinity for phase separation and the material characteristics of RNA condensates are strongly dependent on sequence composition and patterning. We hypothesize that differences in the affinities for RNA phase separation can be uncovered by studying sequence-dependent conformational dynamics of single RNA chains. To this end, we have employed atomistic simulations and deep dimensionality reduction techniques to map temperature-dependent conformational free energy landscapes for 20 base-long homopolymeric RNA sequences: poly(U), poly(G), poly(C), and poly(A). The energy landscapes of homopolymeric RNAs reveal a plethora of metastable states with qualitatively different populations stemming from differences in base chemistry. Through detailed analysis of base, phosphate, and sugar interactions, we show that experimentally observed temperature-driven shifts in metastable state populations align with experiments on RNA phase transitions. Specifically, we find that the thermodynamics of unfolding of homopolymeric RNA follows the poly(G) > poly(A) > poly(C) > poly(U) order of stability, mirroring the propensity of RNA to form condensates. To conclude, this work shows that at least for homopolymeric RNA sequences the single-chain conformational dynamics contains sufficient information for predicting and quantifying condensate forming affinities of RNAs. Thus, we anticipate that atomically detailed studies of temeprature -dependent energy landscapes of RNAs will be a useful guide for understanding the propensity of various RNA molecules to form condensates.

Salt-Dependent Self-Association of Trinucleotide Repeat RNA Sequences

Repeat RNA sequences self-associate to form condensates. Simulations of a coarse-grained single-interaction site model for (CAG)n (n = 30 and 31) show that the salt-dependent free energy gap, ΔGS, between the ground (perfect hairpin) and the excited state (slipped hairpin (SH) with one CAG overhang) of the monomer for (n even) is the primary factor that determines the rates and yield of self-assembly. For odd n, the free energy (GS) of the ground state, which is an SH, is used to predict the self-association kinetics. As the monovalent salt concentration, CS, increases, ΔGS and GS increase, which decreases the rates of dimer formation. In contrast, ΔGS for shuffled sequences, with the same length and sequence composition as (CAG)31, is larger, which suppresses their propensities to aggregate. Although demonstrated explicitly for (CAG) polymers, the finding of inverse correlation between the free energy gap and RNA aggregation is general.