RNA secondary structure prediction from multi-aligned sequences

It has been well accepted that the RNA secondary structures of most functional non-coding RNAs (ncRNAs) are closely related to their functions and are conserved during evolution. Hence, prediction of conserved secondary structures from evolutionarily related sequences is one important task in RNA bioinformatics; the methods are useful not only to further functional analyses of ncRNAs but also to improve the accuracy of secondary structure predictions and to find novel functional RNAs from the genome. In this review, I focus on common secondary structure prediction from a given aligned RNA sequence, in which one secondary structure whose length is equal to that of the input alignment is predicted. I systematically review and classify existing tools and algorithms for the problem, by utilizing the information employed in the tools and by adopting a unified viewpoint based on maximum expected gain (MEG) estimators. I believe that this classification will allow a deeper understanding of each tool and provide users with useful information for selecting tools for common secondary structure predictions.Comment: A preprint of an invited review manuscript that will be published in a chapter of the book `Methods in Molecular Biology'. Note that this version of the manuscript may differ from the published versio

Facilitated Variation: How Evolution Learns from Past Environments To Generalize to New Environments

One of the striking features of evolution is the appearance of novel structures in organisms. Recently, Kirschner and Gerhart have integrated discoveries in evolution, genetics, and developmental biology to form a theory of facilitated variation (FV). The key observation is that organisms are designed such that random genetic changes are channeled in phenotypic directions that are potentially useful. An open question is how FV spontaneously emerges during evolution. Here, we address this by means of computer simulations of two well-studied model systems, logic circuits and RNA secondary structure. We find that evolution of FV is enhanced in environments that change from time to time in a systematic way: the varying environments are made of the same set of subgoals but in different combinations. We find that organisms that evolve under such varying goals not only remember their history but also generalize to future environments, exhibiting high adaptability to novel goals. Rapid adaptation is seen to goals composed of the same subgoals in novel combinations, and to goals where one of the subgoals was never seen in the history of the organism. The mechanisms for such enhanced generation of novelty (generalization) are analyzed, as is the way that organisms store information in their genomes about their past environments. Elements of facilitated variation theory, such as weak regulatory linkage, modularity, and reduced pleiotropy of mutations, evolve spontaneously under these conditions. Thus, environments that change in a systematic, modular fashion seem to promote facilitated variation and allow evolution to generalize to novel conditions

Local Absence of Secondary Structure Permits Translation of mRNAs that Lack Ribosome-Binding Sites

The initiation of translation is a fundamental and highly regulated process in gene expression. Translation initiation in prokaryotic systems usually requires interaction between the ribosome and an mRNA sequence upstream of the initiation codon, the so-called ribosome-binding site (Shine-Dalgarno sequence). However, a large number of genes do not possess Shine-Dalgarno sequences, and it is unknown how start codon recognition occurs in these mRNAs. We have performed genome-wide searches in various groups of prokaryotes in order to identify sequence elements and/or RNA secondary structural motifs that could mediate translation initiation in mRNAs lacking Shine-Dalgarno sequences. We find that mRNAs without a Shine-Dalgarno sequence are generally less structured in their translation initiation region and show a minimum of mRNA folding at the start codon. Using reporter gene constructs in bacteria, we also provide experimental support for local RNA unfoldedness determining start codon recognition in Shine-Dalgarno–independent translation. Consistent with this, we show that AUG start codons reside in single-stranded regions, whereas internal AUG codons are usually in structured regions of the mRNA. Taken together, our bioinformatics analyses and experimental data suggest that local absence of RNA secondary structure is necessary and sufficient to initiate Shine-Dalgarno–independent translation. Thus, our results provide a plausible mechanism for how the correct translation initiation site is recognized in the absence of a ribosome-binding site

The Effect of Central Loops in miRNA:MRE Duplexes on the Efficiency of miRNA-Mediated Gene Regulation

MicroRNAs (miRNAs) guide posttranscriptional repression of mRNAs. Hundreds of miRNAs have been identified but the target identification of mammalian mRNAs is still a difficult task due to a poor understanding of the interaction between miRNAs and the miRNA recognizing element (MRE). In recent research, the importance of the 5′ end of the miRNA:MRE duplex has been emphasized and the effect of the tail region addressed, but the role of the central loop has largely remained unexplored. Here we examined the effect of the loop region in miRNA:MRE duplexes and found that the location of the central loop is one of the important factors affecting the efficiency of gene regulation mediated by miRNAs. It was further determined that the addition of a loop score combining both location and size as a new criterion for predicting MREs and their cognate miRNAs significantly decreased the false positive rates and increased the specificity of MRE prediction

Accurate classification of RNA structures using topological fingerprints

While RNAs are well known to possess complex structures, functionally similar RNAs often have little sequence similarity. While the exact size and spacing of base-paired regions vary, functionally similar RNAs have pronounced similarity in the arrangement, or topology, of base-paired stems. Furthermore, predicted RNA structures often lack pseudoknots (a crucial aspect of biological activity), and are only partially correct, or incomplete. A topological approach addresses all of these difficulties. In this work we describe each RNA structure as a graph that can be converted to a topological spectrum (RNA fingerprint). The set of subgraphs in an RNA structure, its RNA fingerprint, can be compared with the fingerprints of other RNA structures to identify and correctly classify functionally related RNAs. Topologically similar RNAs can be identified even when a large fraction, up to 30%, of the stems are omitted, indicating that highly accurate structures are not necessary. We investigate the performance of the RNA fingerprint approach on a set of eight highly curated RNA families, with diverse sizes and functions, containing pseudoknots, and with little sequence similarity–an especially difficult test set. In spite of the difficult test set, the RNA fingerprint approach is very successful (ROC AUC \u3e 0.95). Due to the inclusion of pseudoknots, the RNA fingerprint approach both covers a wider range of possible structures than methods based only on secondary structure, and its tolerance for incomplete structures suggests that it can be applied even to predicted structures. Source code is freely available at https://github.rcac.purdue.edu/mgribsko/XIOS_RNA_fingerprint

Secondary structure impacts patterns of selection in human IncRNAs

Background: Metazoans transcribe many long non-coding RNAs (lncRNAs) that are poorly conserved and whose function remains unknown. This has raised the questions of what fraction of the predicted lncRNAs is actually functional, and whether selection can effectively constrain lncRNAs in species with small effective population sizes such as human populations. Results: Here we evaluate signatures of selection in human lncRNAs using inter-specific data and intra-specific comparisons from five major populations, as well as by assessing relationships between sequence variation and predictions of secondary structure. In all analyses we included a reference of functionally characterized lncRNAs. Altogether, our results show compelling evidence of recent purifying selection acting on both characterized and predicted lncRNAs. We found that RNA secondary structure constrains sequence variation in lncRNAs, so that polymorphisms are depleted in paired regions with low accessibility and tend to be neutral with respect to structural stability. Conclusions: Important implications of our results are that secondary structure plays a role in the functionality of lncRNAs, and that the set of predicted lncRNAs contains a large fraction of functional ones that may play key roles that remain to be discovered.Toni Gabaldon's (TG’s) group acknowledges support from the Spanish Ministry of Economy and Competitiveness grants “Centro de Excelencia Severo Ochoa 2013-2017” SEV-2012-0208 and BFU2015-67107, cofounded by the European Regional Development Fund (ERDF); from the European Union and ERC Seventh Framework Programme (FP7/2007-2013) under grant agreements FP7-PEOPLE-2013-ITN-606786 and ERC-2012-StG-310325; and a grant from the European Union’s Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement number H2020-MSCA-ITN-2014-642095