Search

Non-coding RNA regulatory elements are important for viral replication, making them promising targets for therapeutic intervention. However, regulatory RNA is challenging to detect and characterise using classical structure-function assays. Here, we present in cell Mutational Interference Mapping Experiment (in cell MIME) as a way to define RNA regulatory landscapes at single nucleotide resolution under native conditions. In cell MIME is based on (i) random mutation of an RNA target, (ii) expression of mutated RNA in cells, (iii) physical separation of RNA into functional and non-functional populations, and (iv) high-throughput sequencing to identify mutations affecting function. We used in cell MIME to define RNA elements within the 5' region of the HIV-1 genomic RNA (gRNA) that are important for viral replication in cells. We identified three distinct RNA motifs controlling intracellular gRNA production, and two distinct motifs required for gRNA packaging into virions. Our analysis reveals the 73AAUAAA78 polyadenylation motif within the 5' PolyA domain as a dual regulator of gRNA production and gRNA packaging, and demonstrates that a functional polyadenylation signal is required for viral packaging even though it negatively affects gRNA production.

The structure and function of conserved motifs constituting the apex of Stem I in T-box mRNA leaders are investigated. We point out that this apex shares striking similarities with the L1 stalk (helices 76-78) of the ribosome. A sequence and structure analysis of both elements shows that, similarly to the head of the L1 stalk, the function of the apex of Stem I lies in the docking of tRNA through a stacking interaction with the conserved G19:C56 base pair platform. The inferred structure in the apex of Stem I consists of a module of two T-loops bound together head to tail, a module that is also present in the head of the L1 stalk, but went unnoticed. Supporting the analysis, we show that a highly conserved structure in RNAse P formerly described as the J11/12-J12/11 module, which is precisely known to bind the elbow of tRNA, constitutes a third instance of this T-loop module. A structural analysis explains why six nucleotides constituting the core of this module are highly invariant among all three types of RNA. Our finding that major RNA partners of tRNA bind the elbow with a same RNA structure suggests an explanation for the origin of the tRNA L-shape.

Summary: Assemble is an intuitive graphical interface to analyze, manipulate and build complex 3D RNA architectures. It provides several advanced and unique features within the framework of a semi-automated modeling process that can be performed by homology and ab initio with or without electron density maps. Those include the interactive editing of a secondary structure and a searchable, embedded library of annotated tertiary structures. Assemble helps users with performing recurrent and otherwise tedious tasks in structural RNA research., Availability and Implementation: Assemble is released under an open-source license (MIT license) and is freely available at http://bioinformatics.org/assemble. It is implemented in the Java language and runs on MacOSX, Linux and Windows operating systems.

It has long been accepted that the structural constraints stemming from the 3D structure of ribosomal RNA (rRNA) lead to coevolution through compensating mutations between interacting sites. State-of-the-art methods for detecting coevolving sites, however, while reaching high levels of specificity and sensitivity for Watson-Crick (WC) pairs of the helices defining the secondary structure, only scarcely reveal tertiary interactions occurring at the level of the 3D structure. In order to understand the relative failure of coevolutionary methods to detect such interactions, we analyze 2,682 interacting sites derived from high-resolution structures, which include a comprehensive data set of rRNA sequences from Archaea and Bacteria. We report a striking difference in the amount of coevolution between WC and non-WC pairs. In order to understand this pattern, we derive fitness landscapes from the geometry of base pairing interactions and construct neutral networks of substitutions for each type of interaction. These networks show that coevolution is a property of WC pairs because, unlike non-WC pairs, their landscapes exhibit fitness valleys, a single mutation in a WC pair resulting in a fitness drop. Second, we used the inferred neutral networks to estimate the level of constraint acting on each type of base pair and show that it correlates negatively with the observed rate of substitutions for all non-WC pairs. WC pairs appear as outliers, fixing more substitutions than expected according to their level of constraint. We here propose that the rate of substitution in WC pairs is due to coevolution resulting from constraints acting at intermediate levels of organization, namely the one of the helical stem with its forming WC pairs. In agreement with this hypothesis, we report a significant excess of intrahelical, inter-WC pairs coevolution compared with interhelices pairs. Altogether, these results show that detailed biochemical knowledge is required and has to be incorporated into evolutionary reasoning in order to understand the fine patterns of variation at the molecular level. They also demonstrate that coevolutionary analysis provides almost exclusively 2D information and only little 3D signal.

Summary: Efficient RNA sequence manipulations (such as multiple alignments) need to be constrained by rules of RNA structure folding. The structural knowledge has increased dramatically in the last years with the accumulation of several large RNA structures similar to those of the bacterial ribosome subunits. However, no tool in the RNA community provides an easy way to link and integrate progress made at the sequence level using the available three-dimensional information. Sequence to Structure (S2S) proposes a framework in which an user can easily display, manipulate and interconnect heterogeneous RNA data, such as multiple sequence alignments, secondary and tertiary structures. S2S has been implemented using the Java language and has been developed and tested under UNIX systems, such as Linux and MacOSX., Availability: S2S is available at http://bioinformatics.org/S2S/.

Three programs have been developed to aid in the classification and visualization of RNA structure. BPViewer provides a web interface for displaying three-dimensional (3D) coordinates of individual base pairs or base pair collections. A web server, RNAview, automatically identifies and classifies the types of base pairs that are formed in nucleic acid structures by various combinations of the three edges, Watson-Crick, Hoogsteen and the Sugar edge. RNAView produces two-dimensional (2D) diagrams of secondary and tertiary structure in either Postscript, VRML or RNAML formats. The application RNAMLview can be used to rearrange various parts of the RNAView 2D diagram to generate a standard representation (like the cloverleaf structure of tRNAs) or any layout desired by the user. A 2D diagram can be rapidly reformatted using RNAMLview since all the parts of RNA (like helices and single strands) are dynamically linked while moving the selected parts. With the base pair annotation and the 2D graphic display, RNA motifs are rapidly identified and classified. A survey has been carried out for 41 unique structures selected from the NDB database. The statistics for the occurrence of each edge and of each of the 12 bp families are given for the combinations of the four bases: A, G, U and C. The program also allows for visualization of the base pair interactions by using a symbolic convention previously proposed for base pairs. The web servers for BPViewer and RNAview are available at http://ndbserver.rutgers.edu/services/. The application RNAMLview can also be downloaded from this site. The 2D diagrams produced by RNAview are available for RNA structures in the Nucleic Acid Database (NDB) at http://ndbserver.rutgers.edu/atlas/.