A CPF-like phosphatase module links transcription termination to chromatin silencing.

The interconnections between co-transcriptional regulation, chromatin environment, and transcriptional output remain poorly understood. Here, we investigate the mechanism underlying RNA 3' processing-mediated Polycomb silencing of Arabidopsis FLOWERING LOCUS C (FLC). We show a requirement for ANTHESIS PROMOTING FACTOR 1 (APRF1), a homolog of yeast Swd2 and human WDR82, known to regulate RNA polymerase II (RNA Pol II) during transcription termination. APRF1 interacts with TYPE ONE SERINE/THREONINE PROTEIN PHOSPHATASE 4 (TOPP4) (yeast Glc7/human PP1) and LUMINIDEPENDENS (LD), the latter showing structural features found in Ref2/PNUTS, all components of the yeast and human phosphatase module of the CPF 3' end-processing machinery. LD has been shown to co-associate in vivo with the histone H3 K4 demethylase FLOWERING LOCUS D (FLD). This work shows how the APRF1/LD-mediated polyadenylation/termination process influences subsequent rounds of transcription by changing the local chromatin environment at FLC.

The nuclear cap-binding complex as choreographer of gene transcription and pre-mRNA processing.

The largely nuclear cap-binding complex (CBC) binds to the 5' caps of RNA polymerase II (RNAPII)-synthesized transcripts and serves as a dynamic interaction platform for a myriad of RNA processing factors that regulate gene expression. While influence of the CBC can extend into the cytoplasm, here we review the roles of the CBC in the nucleus, with a focus on protein-coding genes. We discuss differences between CBC function in yeast and mammals, covering the steps of transcription initiation, release of RNAPII from pausing, transcription elongation, cotranscriptional pre-mRNA splicing, transcription termination, and consequences of spurious transcription. We describe parameters known to control the binding of generic or gene-specific cofactors that regulate CBC activities depending on the process(es) targeted, illustrating how the CBC is an ever-changing choreographer of gene expression.

Post-transcriptional polyadenylation site cleavage maintains 3'-end processing upon DNA damage.

The recognition of polyadenylation signals (PAS) in eukaryotic pre-mRNAs is usually coupled to transcription termination, occurring while pre-mRNA is chromatin-bound. However, for some pre-mRNAs, this 3'-end processing occurs post-transcriptionally, i.e., through a co-transcriptional cleavage (CoTC) event downstream of the PAS, leading to chromatin release and subsequent PAS cleavage in the nucleoplasm. While DNA-damaging agents trigger the shutdown of co-transcriptional chromatin-associated 3'-end processing, specific compensatory mechanisms exist to ensure efficient 3'-end processing for certain pre-mRNAs, including those that encode proteins involved in the DNA damage response, such as the tumor suppressor p53. We show that cleavage at the p53 polyadenylation site occurs in part post-transcriptionally following a co-transcriptional cleavage event. Cells with an engineered deletion of the p53 CoTC site exhibit impaired p53 3'-end processing, decreased mRNA and protein levels of p53 and its transcriptional target p21, and altered cell cycle progression upon UV-induced DNA damage. Using a transcriptome-wide analysis of PAS cleavage, we identify additional pre-mRNAs whose PAS cleavage is maintained in response to UV irradiation and occurring post-transcriptionally. These findings indicate that CoTC-type cleavage of pre-mRNAs, followed by PAS cleavage in the nucleoplasm, allows certain pre-mRNAs to escape 3'-end processing inhibition in response to UV-induced DNA damage.

Selective Roles of Vertebrate PCF11 in Premature and Full-Length Transcript Termination.

The pervasive nature of RNA polymerase II (Pol II) transcription requires efficient termination. A key player in this process is the cleavage and polyadenylation (CPA) factor PCF11, which directly binds to the Pol II C-terminal domain and dismantles elongating Pol II from DNA in vitro. We demonstrate that PCF11-mediated termination is essential for vertebrate development. A range of genomic analyses, including mNET-seq, 3' mRNA-seq, chromatin RNA-seq, and ChIP-seq, reveals that PCF11 enhances transcription termination and stimulates early polyadenylation genome-wide. PCF11 binds preferentially between closely spaced genes, where it prevents transcriptional interference and consequent gene downregulation. Notably, PCF11 is sub-stoichiometric to the CPA complex. Low levels of PCF11 are maintained by an auto-regulatory mechanism involving premature termination of its own transcript and are important for normal development. Both in human cell culture and during zebrafish development, PCF11 selectively attenuates the expression of other transcriptional regulators by premature CPA and termination.

RNAdvisor: a comprehensive benchmarking tool for the measure and prediction of RNA structural model quality.

RNA is a complex macromolecule that plays central roles in the cell. While it is well known that its structure is directly related to its functions, understanding and predicting RNA structures is challenging. Assessing the real or predictive quality of a structure is also at stake with the complex 3D possible conformations of RNAs. Metrics have been developed to measure model quality while scoring functions aim at assigning quality to guide the discrimination of structures without a known and solved reference. Throughout the years, many metrics and scoring functions have been developed, and no unique assessment is used nowadays. Each developed assessment method has its specificity and might be complementary to understanding structure quality. Therefore, to evaluate RNA 3D structure predictions, it would be important to calculate different metrics and/or scoring functions. For this purpose, we developed RNAdvisor, a comprehensive automated software that integrates and enhances the accessibility of existing metrics and scoring functions. In this paper, we present our RNAdvisor tool, as well as state-of-the-art existing metrics, scoring functions and a set of benchmarks we conducted for evaluating them. Source code is freely available on the EvryRNA platform: https://evryrna.ibisc.univ-evry.fr.

Genetic screen for suppression of transcriptional interference identifies a gain-of-function mutation in Pol2 termination factor Seb1.

The system of long noncoding RNA (lncRNA)-mediated transcriptional interference that represses fission yeast phosphate homoeostasis gene pho1 provides a sensitive readout of genetic influences on cotranscriptional 3'-processing and termination and a tool for discovery of regulators of this phase of the Pol2 transcription cycle. Here, we conducted a genetic screen for relief of transcriptional interference that unveiled a mechanism by which Pol2 termination is enhanced via a gain-of-function mutation, G476S, in the RNA-binding domain of an essential termination factor, Seb1. The genetic and physical evidence for gain-of-function is compelling: 1) seb1-G476S de-represses pho1 and tgp1, both of which are subject to lncRNA-mediated transcriptional interference; 2) seb1-G476S elicits precocious lncRNA transcription termination in response to lncRNA 5'-proximal poly(A) signals; 3) seb1-G476S derepression of pho1 is effaced by loss-of-function mutations in cleavage and polyadenylation factor (CPF) subunits and termination factor Rhn1; 4) synthetic lethality of seb1-G476S with pho1 derepressive mutants rpb1-CTD-S7A and aps1∆ is rescued by CPF/Rhn1 loss-of-function alleles; and 5) seb1-G476S elicits an upstream shift in poly(A) site preference in several messenger RNA genes. A crystal structure of the Seb1-G476S RNA-binding domain indicates potential for gain of contacts from Ser476 to RNA nucleobases. To our knowledge, this is a unique instance of a gain-of-function phenotype in a eukaryal transcription termination protein.

ABC2A: A Straightforward and Fast Method for the Accurate Backmapping of RNA Coarse-Grained Models to All-Atom Structures.

RNAs play crucial roles in various essential biological functions, including catalysis and gene regulation. Despite the widespread use of coarse-grained (CG) models/simulations to study RNA 3D structures and dynamics, their direct application is challenging due to the lack of atomic detail. Therefore, the reconstruction of full atomic structures is desirable. In this study, we introduced a straightforward method called ABC2A for reconstructing all-atom structures from RNA CG models. ABC2A utilizes diverse nucleotide fragments from known structures to assemble full atomic structures based on the CG atoms. The diversification of assembly fragments beyond standard A-form ones, commonly used in other programs, combined with a highly simplified structure refinement process, ensures that ABC2A achieves both high accuracy and rapid speed. Tests on a recent large dataset of 361 RNA experimental structures (30-692 nt) indicate that ABC2A can reconstruct full atomic structures from three-bead CG models with a mean RMSD of ~0.34 Å from experimental structures and an average runtime of ~0.5 s (maximum runtime < 2.5 s). Compared to the state-of-the-art Arena, ABC2A achieves a ~25% improvement in accuracy and is five times faster in speed.

RNA tertiary structure prediction using RNAComposer in CASP15.

As CASP15 participants, in the new category of 3D RNA structure prediction, we applied expert modeling with the support of our proprietary system RNAComposer. Although RNAComposer is primarily known as an automated web server, its features allow it to be used interactively, for example, for homology-based modeling or assembling models from user-provided structural elements. In the paper, we present various scenarios of applying the system to predict the 3D RNA structures that we employed. Their combination with expert input, comparative analysis of models, and routines to select representative resultant structures form a ready-for-reuse workflow. With selected examples, we demonstrate its application for the in silico modeling of natural and synthetic RNA molecules targeted in CASP15.

Transcriptional profiling of fission yeast RNA polymerase II CTD mutants.

The carboxyl-terminal domain (CTD) of RNA polymerase II (Pol2) consists of tandem repeats of a consensus heptapeptide Y1 S2 P3 T4 S5 P6 S7 The CTD recruits numerous proteins that drive or regulate gene expression. The trafficking of CTD-interacting proteins is orchestrated by remodeling CTD primary structure via Ser/Thr/Tyr phosphorylation and proline cis-trans isomerization, which collectively inscribe a CTD code. The fission yeast CTD consists of 29 heptad repeats. To decipher the output of the fission yeast CTD code, we genetically manipulated CTD length and amino acid content and then gauged the effects of these changes on gene expression. Whereas deleting 11 consensus heptads has no obvious effect on fission yeast growth, RNA-seq revealed that 25% of the protein-coding transcripts were dysregulated by CTD truncation. We profiled the transcriptomes of full-length CTD mutants, in which: all Tyr1 residues were replaced by Phe; all Ser2, Thr4, or Ser7 positions were changed to Ala; and half of the essential CTD code "letters" Pro3, Ser5, and Pro6 were mutated to Ala. Overlapping RNA-seq profiles suggested that a quarter of the complement of up-regulated mRNAs and half of the down-regulated mRNAs seen in full-length CTD mutants might be attributable to a decrement in wild-type CTD heptad number. Concordant mutant-specific transcriptional profiles were observed for Y1F, S2A, and T4A cells, and for P6•P6A and S5•S5A cells, suggesting that Tyr1-Ser2-Thr4 and Ser5-Pro6 comprise distinct "words" in the fission yeast CTD code. The phosphate regulon, which is repressed by lncRNA-mediated transcription interference, is de-repressed by CTD mutations P6•P6A and S5•S5A. De-repression of pho1 in P6•P6A and S5•S5A cells depends on cleavage and polyadenylation factor subunits Swd22 and Ppn1 and transcription termination factor Rhn1, signifying that Pro6 and Ser5 mutations elicit precocious lncRNA 3'-processing/termination.

RNA 3D Structure Prediction: Progress and Perspective.

Ribonucleic acid (RNA) molecules play vital roles in numerous important biological functions such as catalysis and gene regulation. The functions of RNAs are strongly coupled to their structures or proper structure changes, and RNA structure prediction has been paid much attention in the last two decades. Some computational models have been developed to predict RNA three-dimensional (3D) structures in silico, and these models are generally composed of predicting RNA 3D structure ensemble, evaluating near-native RNAs from the structure ensemble, and refining the identified RNAs. In this review, we will make a comprehensive overview of the recent advances in RNA 3D structure modeling, including structure ensemble prediction, evaluation, and refinement. Finally, we will emphasize some insights and perspectives in modeling RNA 3D structures.

Advances in RNA 3D Structure Prediction.

RNA molecules carry out various cellular functions, and understanding the mechanisms behind their functions requires the knowledge of their 3D structures. Different types of computational methods have been developed to model RNA 3D structures over the past decade. These methods were widely used by researchers although their performance needs to be further improved. Recently, along with these traditional methods, machine-learning techniques have been increasingly applied to RNA 3D structure prediction and show significant improvement in performance. Here we shall give a brief review of the traditional methods and recent related advances in machine-learning approaches for RNA 3D structure prediction.

On the predictibility of A-minor motifs from their local contexts.

This study investigates the importance of the structural context in the formation of a type I/II A-minor motif. This very frequent structural motif has been shown to be important in the spatial folding of RNA molecules. We developed an automated method to classify A-minor motif occurrences according to their 3D context similarities, and we used a graph approach to represent both the structural A-minor motif occurrences and their classes at different scales. This approach leads us to uncover new subclasses of A-minor motif occurrences according to their local 3D similarities. The majority of classes are composed of homologous occurrences, but some of them are composed of non-homologous occurrences. The different classifications we obtain allow us to better understand the importance of the context in the formation of A-minor motifs. In a second step, we investigate how much knowledge of the context around an A-minor motif can help to infer its presence (and position). More specifically, we want to determine what kind of information, contained in the structural context, can be useful to characterize and predict A-minor motifs. We show that, for some A-minor motifs, the topology combined with a sequence signal is sufficient to predict the presence and the position of an A-minor motif occurrence. In most other cases, these signals are not sufficient for predicting the A-minor motif, however we show that they are good signals for this purpose. All the classification and prediction pipelines rely on automated processes, for which we describe the underlying algorithms and parameters.

Computational Pipeline for Reference-Free Comparative Analysis of RNA 3D Structures Applied to SARS-CoV-2 UTR Models.

RNA is a unique biomolecule that is involved in a variety of fundamental biological functions, all of which depend solely on its structure and dynamics. Since the experimental determination of crystal RNA structures is laborious, computational 3D structure prediction methods are experiencing an ongoing and thriving development. Such methods can lead to many models; thus, it is necessary to build comparisons and extract common structural motifs for further medical or biological studies. Here, we introduce a computational pipeline dedicated to reference-free high-throughput comparative analysis of 3D RNA structures. We show its application in the RNA-Puzzles challenge, in which five participating groups attempted to predict the three-dimensional structures of 5'- and 3'-untranslated regions (UTRs) of the SARS-CoV-2 genome. We report the results of this puzzle and discuss the structural motifs obtained from the analysis. All simulated models and tools incorporated into the pipeline are open to scientific and academic use.

Impact of PNPase on the transcriptome of Rhodobacter sphaeroides and its cooperation with RNase III and RNase E.

BACKGROUND: The polynucleotide phosphorylase (PNPase) is conserved among both Gram-positive and Gram-negative bacteria. As a core part of the Escherichia coli degradosome, PNPase is involved in maintaining proper RNA levels within the bacterial cell. It plays a major role in RNA homeostasis and decay by acting as a 3'-to-5' exoribonuclease. Furthermore, PNPase can catalyze the reverse reaction by elongating RNA molecules in 5'-to-3' end direction which has a destabilizing effect on the prolonged RNA molecule. RNA degradation is often initiated by an endonucleolytic cleavage, followed by exoribonucleolytic decay from the new 3' end. RESULTS: The PNPase mutant from the facultative phototrophic Rhodobacter sphaeroides exhibits several phenotypical characteristics, including diminished adaption to low temperature, reduced resistance to organic peroxide induced stress and altered growth behavior. The transcriptome composition differs in the pnp mutant strain, resulting in a decreased abundance of most tRNAs and rRNAs. In addition, PNPase has a major influence on the half-lives of several regulatory sRNAs and can have both a stabilizing or a destabilizing effect. Moreover, we globally identified and compared differential RNA 3' ends in RNA NGS sequencing data obtained from PNPase, RNase E and RNase III mutants for the first time in a Gram-negative organism. The genome wide RNA 3' end analysis revealed that 885 3' ends are degraded by PNPase. A fair percentage of these RNA 3' ends was also identified at the same genomic position in RNase E or RNase III mutant strains. CONCLUSION: The PNPase has a major influence on RNA processing and maturation and thus modulates the transcriptome of R. sphaeroides. This includes sRNAs, emphasizing the role of PNPase in cellular homeostasis and its importance in regulatory networks. The global 3' end analysis indicates a sequential RNA processing: 5.9% of all RNase E-dependent and 9.7% of all RNase III-dependent RNA 3' ends are subsequently degraded by PNPase. Moreover, we provide a modular pipeline which greatly facilitates the identification of RNA 5'/3' ends. It is publicly available on GitHub and is distributed under ICS license.

Barnaba: software for analysis of nucleic acid structures and trajectories.

RNA molecules are highly dynamic systems characterized by a complex interplay between sequence, structure, dynamics, and function. Molecular simulations can potentially provide powerful insights into the nature of these relationships. The analysis of structures and molecular trajectories of nucleic acids can be nontrivial because it requires processing very high-dimensional data that are not easy to visualize and interpret. Here we introduce Barnaba, a Python library aimed at facilitating the analysis of nucleic acid structures and molecular simulations. The software consists of a variety of analysis tools that allow the user to (i) calculate distances between three-dimensional structures using different metrics, (ii) back-calculate experimental data from three-dimensional structures, (iii) perform cluster analysis and dimensionality reductions, (iv) search three-dimensional motifs in PDB structures and trajectories, and (v) construct elastic network models for nucleic acids and nucleic acids-protein complexes. In addition, Barnaba makes it possible to calculate torsion angles, pucker conformations, and to detect base-pairing/base-stacking interactions. Barnaba produces graphics that conveniently visualize both extended secondary structure and dynamics for a set of molecular conformations. The software is available as a command-line tool as well as a library, and supports a variety of file formats such as PDB, dcd, and xtc files. Source code, documentation, and examples are freely available at https://github.com/srnas/barnaba under GNU GPLv3 license.

What is the best reference state for building statistical potentials in RNA 3D structure evaluation?

Knowledge-based statistical potentials have been shown to be efficient in protein structure evaluation/prediction, and the core difference between various statistical potentials is attributed to the choice of reference states. However, for RNA 3D structure evaluation, a comprehensive examination on reference states is still lacking. In this work, we built six statistical potentials based on six reference states widely used in protein structure evaluation, including averaging, quasi-chemical approximation, atom-shuffled, finite-ideal-gas, spherical-noninteracting, and random-walk-chain reference states, and we examined the six reference states against three RNA test sets including six subsets. Our extensive examinations show that, overall, for identifying native structures and ranking decoy structures, the finite-ideal-gas and random-walk-chain reference states are slightly superior to others, while for identifying near-native structures, there is only a slight difference between these reference states. Our further analyses show that the performance of a statistical potential is apparently dependent on the quality of the training set. Furthermore, we found that the performance of a statistical potential is closely related to the origin of test sets, and for the three realistic test subsets, the six statistical potentials have overall unsatisfactory performance. This work presents a comprehensive examination on the existing reference states and statistical potentials for RNA 3D structure evaluation.

LncRNA HOXA-AS3 Promotes the Progression of Pulmonary Arterial Hypertension through Mediation of miR-675-3p/PDE5A Axis.

Pulmonary arterial hypertension (PAH) seriously threatens the elder people. Long non-coding RNAs (lncRNAs) are involved in multiple diseases. However, the study of the lncRNAs in the occurrence of PAH is just beginning. For this, we sought to explore the biological function of lncRNA HOXA cluster antisense RNA 3 (HOXA-AS3) in PAH. Hypoxia (HYP) was used to mimic in vitro model of PAH. Gene and protein expressions in cells were detected by q-PCR and Western blotting, respectively. In addition, cell proliferation and viability were tested by CCK-8 and MTT assay. Cell apoptosis was measured by flow cytometry. Wound healing was used to detect cell migration. Furthermore, the connection of HOXA-AS3, miR-675-3p, and phosphodiesterase 5A (PDE5A) was verified by dual-luciferase report assay. HOXA-AS3 and PDE5A were upregulated in human pulmonary artery smooth muscle cells (HPASMCs) in the presence of HYP, while miR-675-3p was downregulated. Moreover, knockdown of HOXA-AS3 suppressed the growth and migration of HPASMCs, but induced the apoptosis. Overexpression of miR-675-3p achieved the same effect. MiR-675-3p inhibitor or overexpression of PDE5A notably reversed the inhibitory effect of HOXA-AS3 knockdown on PAH. Finally, HOXA-AS3 could sponge miR-675-3p, and PDE5A was directly targeted by miR-675-3p. HOXA-AS3 increased the development of PAH via regulation of miR-675-3p/PDE5 axis, which could be the potential biomarker for treatment of PAH.

Identification and Characterization of a Human Coronavirus 229E Nonstructural Protein 8-Associated RNA 3'-Terminal Adenylyltransferase Activity.

Coronavirus nonstructural protein 8 (nsp8) has been suggested to have diverse activities, including noncanonical template-dependent polymerase activities. Here, we characterized a recombinant form of the human coronavirus 229E (HCoV-229E) nsp8 and found that the protein has metal ion-dependent RNA 3'-terminal adenylyltransferase (TATase) activity, while other nucleotides were not (or very inefficiently) transferred to the 3' ends of single-stranded and (fully) double-stranded acceptor RNAs. Using partially double-stranded RNAs, very efficient TATase activity was observed if the opposite (template) strand contained a short 5' oligo(U) sequence, while very little (if any) activity was detected for substrates with other homopolymeric or heteropolymeric sequences in the 5' overhang. The oligo(U)-assisted/templated TATase activity on partial-duplex RNAs was confirmed for two other coronavirus nsp8 proteins, suggesting that the activity is conserved among coronaviruses. Replacement of a conserved Lys residue with Ala abolished the in vitro RNA-binding and TATase activities of nsp8 and caused a nonviable phenotype when the corresponding mutation was introduced into the HCoV-229E genome, confirming that these activities are mediated by nsp8 and critical for viral replication. In additional experiments, we obtained evidence that nsp8 has a pronounced specificity for adenylate and is unable to incorporate guanylate into RNA products, which strongly argues against the previously proposed template-dependent RNA polymerase activity of this protein. Given the presence of an oligo(U) stretch at the 5' end of coronavirus minus-strand RNAs, it is tempting to speculate (but remains to be confirmed) that the nsp8-mediated TATase activity is involved in the 3' polyadenylation of viral plus-strand RNAs.IMPORTANCE Previously, coronavirus nsp8 proteins were suggested to have template-dependent RNA polymerase activities resembling those of RNA primases or even canonical RNA-dependent RNA polymerases, while more recent studies have suggested an essential cofactor function of nsp8 (plus nsp7) for nsp12-mediated RNA-dependent RNA polymerase activity. In an effort to reconcile conflicting data from earlier studies, the study revisits coronavirus nsp8-associated activities using additional controls and proteins. The data obtained for three coronavirus nsp8 proteins provide evidence that the proteins share metal ion-dependent RNA 3' polyadenylation activities that are greatly stimulated by a short oligo(U) stretch in the template strand. In contrast, nsp8 was found to be unable to select and incorporate appropriate (matching) nucleotides to produce cRNA products from heteropolymeric and other homooligomeric templates. While confirming the critical role of nsp8 in coronavirus replication, the study amends the list of activities mediated by coronavirus nsp8 proteins in the absence of other proteins.

Identification of RNA 3´ ends and termination sites in Haloferax volcanii.

Archaeal genomes are densely packed; thus, correct transcription termination is an important factor for orchestrated gene expression. A systematic analysis of RNA 3´ termini, to identify transcription termination sites (TTS) using RNAseq data has hitherto only been performed in two archaea, Methanosarcina mazei and Sulfolobus acidocaldarius. In this study, only regions directly downstream of annotated genes were analysed, and thus, only part of the genome had been investigated. Here, we developed a novel algorithm (Internal Enrichment-Peak Calling) that allows an unbiased, genome-wide identification of RNA 3´ termini independent of annotation. In an RNA fraction enriched for primary transcripts by terminator exonuclease (TEX) treatment we identified 1,543 RNA 3´ termini. Approximately half of these were located in intergenic regions, and the remainder were found in coding regions. A strong sequence signature consistent with known termination events at intergenic loci indicates a clear enrichment for native TTS among them. Using these data we determined distinct putative termination motifs for intergenic (a T stretch) and coding regions (AGATC). In vivo reporter gene tests of selected TTS confirmed termination at these sites, which exemplify the different motifs. For several genes, more than one termination site was detected, resulting in transcripts with different lengths of the 3´ untranslated region (3´ UTR).

RNA 3D structure prediction guided by independent folding of homologous sequences.

BACKGROUND: The understanding of the importance of RNA has dramatically changed over recent years. As in the case of proteins, the function of an RNA molecule is encoded in its tertiary structure, which in turn is determined by the molecule's sequence. The prediction of tertiary structures of complex RNAs is still a challenging task. RESULTS: Using the observation that RNA sequences from the same RNA family fold into conserved structure, we test herein whether parallel modeling of RNA homologs can improve ab initio RNA structure prediction. EvoClustRNA is a multi-step modeling process, in which homologous sequences for the target sequence are selected using the Rfam database. Subsequently, independent folding simulations using Rosetta FARFAR and SimRNA are carried out. The model of the target sequence is selected based on the most common structural arrangement of the common helical fragments. As a test, on two blind RNA-Puzzles challenges, EvoClustRNA predictions ranked as the first of all submissions for the L-glutamine riboswitch and as the second for the ZMP riboswitch. Moreover, through a benchmark of known structures, we discovered several cases in which particular homologs were unusually amenable to structure recovery in folding simulations compared to the single original target sequence. CONCLUSION: This work, for the first time to our knowledge, demonstrates the importance of the selection of the target sequence from an alignment of an RNA family for the success of RNA 3D structure prediction. These observations prompt investigations into a new direction of research for checking 3D structure "foldability" or "predictability" of related RNA sequences to obtain accurate predictions. To support new research in this area, we provide all relevant scripts in a documented and ready-to-use form. By exploring new ideas and identifying limitations of the current RNA 3D structure prediction methods, this work is bringing us closer to the near-native computational RNA 3D models.