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Summary: The DynaSig-ML (Dynamical Signatures - Machine Learning) Python package allows the efficient, user-friendly exploration of 3D dynamics-function relationships in biomolecules, using datasets of experimental measures from large numbers of sequence variants. The DynaSig-ML package is built around the Elastic Network Contact Model (ENCoM), the first and only sequence-sensitive coarse-grained NMA model, which is used to generate the input Dynamical Signatures. Starting from in silico mutated structures, the whole pipeline can be run with just a few lines of Python and modest computational resources. The compute-intensive steps can also easily be parallelized in the case of either large biomolecules or vast amounts of sequence variants. As an example application, we use the DynaSig-ML package to predict the evolutionary fitness of the bacterial enzyme VIM-2 lactamase from deep mutational scan data. Availability and implementation: DynaSig-ML is open source software available at https: //github.com/gregorpatof/dynasigml package Contact: rafael.najmanovich@umontreal.ca, 10 pages

International audience; RNA-Puzzles is a collective endeavor dedicated to the advancement and improvement of RNA 3D structure prediction. With agreement from crystallographers, the RNA structures are predicted by various groups before the publication of the crystal structures. We now report the prediction of 3D structures for six RNA sequences: four nucleolytic ribozymes and two riboswitches. Systematic protocols for comparing models and crystal structures are described and analyzed. In these six puzzles, we discuss (i) the comparison between the automated web servers and human experts; (ii) the prediction of coaxial stacking; (iii) the prediction of structural details and ligand binding; (iv) the development of novel prediction methods; and (v) the potential improvements to be made. We show that correct prediction of coaxial stacking and tertiary contacts is essential for the prediction of RNA architecture, while ligand binding modes can only be predicted with low resolution and simultaneous prediction of RNA structure with accurate ligand binding still remains out of reach. All the predicted models are available for the future development of force field parameters and the improvement of comparison and assessment tools.

MicroRNAs (miRNAs) are ribonucleic acids (RNAs) of ∼21 nucleotides that interfere with the translation of messenger RNAs (mRNAs) and play significant roles in development and diseases. In bilaterian animals, the specificity of miRNA targeting is determined by sequence complementarity involving the seed. However, the role of the remaining nucleotides (non-seed) is only vaguely defined, impacting negatively on our ability to efficiently use miRNAs exogenously to control gene expression. Here, using reporter assays, we deciphered the role of the base pairs formed between the non-seed region and target mRNA. We used molecular modeling to reveal that this mechanism corresponds to the formation of base pairs mediated by ordered motions of the miRNA-induced silencing complex. Subsequently, we developed an algorithm based on this distinctive recognition to predict from sequence the levels of mRNA downregulation with high accuracy (r2 > 0.5, P-value < 10-12). Overall, our discovery improves the design of miRNA-guide sequences used to simultaneously downregulate the expression of multiple predetermined target genes.

RNA structures are hierarchically organized. The secondary structure is articulated around sophisticated local three-dimensional (3D) motifs shaping the full 3D architecture of the molecule. Recent contributions have identified and organized recurrent local 3D motifs, but applications of this knowledge for predictive purposes is still in its infancy. We recently developed a computational framework, named RNA-MoIP, to reconcile RNA secondary structure and local 3D motif information available in databases. In this paper, we introduce a web service using our software for predicting RNA hybrid 2D–3D structures from sequence data only. Optionally, it can be used for (i) local 3D motif prediction or (ii) the refinement of user-defined secondary structures. Importantly, our web server automatically generates a script for the MC-Sym software, which can be immediately used to quickly predict all-atom RNA 3D models. The web server is available at http://rnamoip.cs.mcgill.ca.

Cellular protein levels are finely tuned through microRNA-mediated gene regulation, triggered by RNA-induced silencing complexes (RISCs) that recognize, bind and silence mRNA targets. A recent study shows that, while mRNA target recognition is achieved with only about a third of the guide RNA sequence, formation of an efficient RISC conformation required for target silencing involves the coordination of transient structural states of the entire guide RNA–mRNA duplex.

Genome-wide transcriptomic analyses have provided valuable insight into fundamental biology and disease pathophysiology. Many studies have taken advantage of the correlation in the expression patterns of the transcriptome to infer potential biologic function of uncharacterized genes and multiple groups have examined the relationship between co-expression, co-regulation, and gene function on a broader scale. Given the unique characteristics of immune cells circulating in blood, we were interested in determining whether it was possible to identify functional co-expression modules in human immune cells. Specifically, we sequenced the transcriptome of nine immune cell types from peripheral blood cells of healthy donors and, using a combination of global and targeted analyses of genes within co-expression modules, we were able to determine functions for these modules that were cell lineage specific or shared among multiple cell lineages. In addition, our analyses identified transcription factors likely important for immune cell lineage commitment and/or maintenance.

Endothelial cells have multifaceted interactions with the immune system, both as initiators and targets of immune responses. In vivo, apoptotic endothelial cells release two types of extracellular vesicles upon caspase-3 activation: apoptotic bodies and exosome-like nanovesicles (ApoExos). Only ApoExos are immunogenic: their injection causes inflammation and autoimmunity in mice. Based on deep sequencing of total RNA, we report that apoptotic bodies and ApoExos are loaded with divergent RNA cargos that are not released by healthy endothelial cells. Apoptotic bodies, like endothelial cells, contain mainly ribosomal RNA whereas ApoExos essentially contain non-ribosomal non-coding RNAs. Endogenous retroelements, bearing viral-like features, represented half of total ApoExos RNA content. ApoExos also contained several copies of unedited Alu repeats and large amounts of non-coding RNAs with a demonstrated role in autoimmunity such as U1 RNA and Y RNA. Moreover, ApoExos RNAs had a unique nucleotide composition and secondary structure characterized by strong enrichment in U-rich motifs and unstably folded RNAs. Globally, ApoExos were therefore loaded with RNAs that can stimulate a variety of RIG-I-like receptors and endosomal TLRs. Hence, apoptotic endothelial cells selectively sort in ApoExos a diversified repertoire of immunostimulatory “self RNAs” that are tailor-made for initiation of innate immune responses and autoimmunity.

In eucaryotes, gene expression is regulated by microRNAs (miRNAs) which bind to messenger RNAs (mRNAs) and interfere with their translation into proteins, either by promoting their degradation or inducing their repression. We study the effect of miRNA interference on each gene using experimental methods, such as microarrays and RNA-seq at the mRNA level, or luciferase reporter assays and variations of SILAC at the protein level. Alternatively, computational predictions would provide clear benefits. However, no algorithm toward this task has ever been proposed. Here, we introduce a new algorithm to predict genome-wide expression data from initial transcriptome abundance. The algorithm simulates the miRNA and mRNA hybridization competition that occurs in given cellular conditions, and derives the whole set of miRNA::mRNA interactions at equilibrium (microtargetome). Interestingly, solving the competition improves the accuracy of miRNA target predictions. Furthermore, this model implements a previously reported and fundamental property of the microtargetome: the binding between a miRNA and a mRNA depends on their sequence complementarity, but also on the abundance of all RNAs expressed in the cell, i.e. the stoichiometry of all the miRNA sites and all the miRNAs given their respective abundance. This model generalizes the miRNA-induced synchronistic silencing previously observed, and described as sponges and competitive endogenous RNAs.

ADARs (Adenosine deaminases that act on RNA) “edit” RNA by converting adenosines to inosines within double-stranded regions. The primary targets of ADARs are long duplexes present within noncoding regions of mRNAs, such as introns and 3′ untranslated regions (UTRs). Because adenosine and inosine have different base-pairing properties, editing within these regions can alter splicing and recognition by small RNAs. However, despite numerous studies identifying multiple editing sites in these genomic regions, little is known about the extent to which editing sites co-occur on individual transcripts or the functional output of these combinatorial editing events. To begin to address these questions, we performed an ultra-deep sequencing analysis of 4 Caenorhabditis elegans 3′ UTRs that are known ADAR targets. Synchronous editing events were determined for the long duplexes in vivo. Furthermore, the validity of each editing event was confirmed by sequencing the same regions of mRNA from worms that lack A-to-I editing. This analysis identified a large number of editing sites that can occur within each 3′ UTR, but interestingly, each individual transcript contained only a small fraction of these A-to-I editing events. In addition, editing patterns were not random, indicating that an editing event can affect the efficiency of editing at subsequent adenosines. Furthermore, we identified specific sites that can be both positively and negatively correlated with additional sites leading to mutually exclusive editing patterns. These results suggest that editing in noncoding regions is selective and hyper-editing of cellular RNAs is rare.

MotivationThe use of Normal Mode Analysis (NMA) methods to study both protein and nucleic acid dynamics is well established. However, the most widely used coarse-grained methods are based on backbone geometry alone and do not take into account the chemical nature of the residues. Elastic Network Contact Model (ENCoM) is a coarse-grained NMA method that includes a pairwise atom-type non-bonded interaction term, which makes it sensitive to the sequence of the studied molecule. We adapted ENCoM to simulate the dynamics of ribonucleic acid (RNA) molecules.ResultsENCoM outperforms the most commonly used coarse-grained model on RNA, Anisotropic Network Model (ANM), in the prediction of b-factors, in the prediction of conformational change as measured by overlap (a measure of effective prediction of structural transitions) and in the prediction of structural variance from NMR ensembles. These benchmarks were derived from the set of all RNA structures available from the Protein Data Bank (PDB) and contain more total cases than previous studies applying NMA to RNA. We thus established ENCoM as an attractive tool for fast and accurate exploration of the conformational space of RNA molecules.AvailabilityENCoM is open source software available at https://github.com/NRGlab/ENCoM

RNA-Puzzles is a collective experiment in blind 3D RNA structure prediction. We report here a third round of RNA-Puzzles. Five puzzles, 4, 8, 12, 13, 14, all structures of riboswitch aptamers and puzzle 7, a ribozyme structure, are included in this round of the experiment. The riboswitch structures include biological binding sites for small molecules (S-adenosyl methionine, cyclic diadenosine monophosphate, 5-amino 4-imidazole carboxamide riboside 5′-triphosphate, glutamine) and proteins (YbxF), and one set describes large conformational changes between ligand-free and ligand-bound states. The Varkud satellite ribozyme is the most recently solved structure of a known large ribozyme. All puzzles have established biological functions and require structural understanding to appreciate their molecular mechanisms. Through the use of fast-track experimental data, including multidimensional chemical mapping, and accurate prediction of RNA secondary structure, a large portion of the contacts in 3D have been predicted correctly leading to similar topologies for the top ranking predictions. Template-based and homology-derived predictions could predict structures to particularly high accuracies. However, achieving biological insights from de novo prediction of RNA 3D structures still depends on the size and complexity of the RNA. Blind computational predictions of RNA structures already appear to provide useful structural information in many cases. Similar to the previous RNA-Puzzles Round II experiment, the prediction of non-Watson–Crick interactions and the observed high atomic clash scores reveal a notable need for an algorithm of improvement. All prediction models and assessment results are available at http://ahsoka.u-strasbg.fr/rnapuzzles/.

Anti-infection drugs target vital functions of infectious agents, including their ribosome and other essential non-coding RNAs. One of the reasons infectious agents become resistant to drugs is due to mutations that eliminate drug-binding affinity while maintaining vital elements. Identifying these elements is based on the determination of viable and lethal mutants and associated structures. However, determining the structure of enough mutants at high resolution is not always possible. Here, we introduce a new computational method, MC-3DQSAR, to determine the vital elements of target RNA structure from mutagenesis and available high-resolution data. We applied the method to further characterize the structural determinants of the bacterial 23S ribosomal RNA sarcin–ricin loop (SRL), as well as those of the lead-activated and hammerhead ribozymes. The method was accurate in confirming experimentally determined essential structural elements and predicting the viability of new SRL variants, which were either observed in bacteria or validated in bacterial growth assays. Our results indicate that MC-3DQSAR could be used systematically to evaluate the drug-target potentials of any RNA sites using current high-resolution structural data.

We created an accelerated version of MC-Fold called MC-Flashfold that allows us to compute large numbers of competing secondary structures including noncanonical base pairs. We visualize the base pairs in these sets using high quality intuitive dot plots and arc plots. Our new tools allow us to explore RNA dynamics by visualizing the competing structures in free energy bands. Here we describe how to use these tools to generate dot plots that reveal the postulated anti-terminator stem in the E. coli trp operon leader sequence. These plots show the anti-terminator hairpin loop during transcription and as a minor population of the full-length leader sequence. This is a case of switching RNA structure that had been originally postulated based on short dyad inverted repeats. Other switching RNA sequences can be analyzed by using our method.

Hyperconnectivity of neuronal circuits due to increased synaptic protein synthesis is thought to cause autism spectrum disorders (ASDs). The mammalian target of rapamycin (mTOR) is strongly implicated in ASDs by means of upstream signalling; however, downstream regulatory mechanisms are ill-defined. Here we show that knockout of the eukaryotic translation initiation factor 4E-binding protein 2 (4E-BP2)-an eIF4E repressor downstream of mTOR-or eIF4E overexpression leads to increased translation of neuroligins, which are postsynaptic proteins that are causally linked to ASDs. Mice that have the gene encoding 4E-BP2 (Eif4ebp2) knocked out exhibit an increased ratio of excitatory to inhibitory synaptic inputs and autistic-like behaviours (that is, social interaction deficits, altered communication and repetitive/stereotyped behaviours). Pharmacological inhibition of eIF4E activity or normalization of neuroligin 1, but not neuroligin 2, protein levels restores the normal excitation/inhibition ratio and rectifies the social behaviour deficits. Thus, translational control by eIF4E regulates the synthesis of neuroligins, maintaining the excitation-to-inhibition balance, and its dysregulation engenders ASD-like phenotypes.

We report the results of a first, collective, blind experiment in RNA three-dimensional (3D) structure prediction, encompassing three prediction puzzles. The goals are to assess the leading edge of RNA structure prediction techniques; compare existing methods and tools; and evaluate their relative strengths, weaknesses, and limitations in terms of sequence length and structural complexity. The results should give potential users insight into the suitability of available methods for different applications and facilitate efforts in the RNA structure prediction community in ongoing efforts to improve prediction tools. We also report the creation of an automated evaluation pipeline to facilitate the analysis of future RNA structure prediction exercises.

The NMR solution structure is reported of a duplex, 5′GUGAAGCCCGU/3′UCACAGGAGGC, containing a 4 × 4 nucleotide internal loop from an R2 retrotransposon RNA. The loop contains three sheared purine–purine pairs and reveals a structural element found in other RNAs, which we refer to as the 3RRs motif. Optical melting measurements of the thermodynamics of the duplex indicate that the internal loop is 1.6 kcal/mol more stable at 37°C than predicted. The results identify the 3RRs motif as a common structural element that can facilitate prediction of 3D structure. Known examples include internal loops having the pairings: 5′GAA/3′AGG, 5′GAG/3′AGG, 5′GAA/3′AAG, and 5′AAG/3′AGG. The structural information is compared with predictions made with the MC-Sym program.

Tandem stretches of guanines can associate in hydrogen-bonded arrays to form G-quadruplexes, which are stabilized by K(+) ions. Using computational methods, we searched for G-Quadruplex Sequence (GQS) patterns in the model plant species Arabidopsis thaliana. We found ∼ 1200 GQS with a G(3) repeat sequence motif, most of which are located in the intergenic region. Using a Markov modeled genome, we determined that GQS are significantly underrepresented in the genome. Additionally, we found ∼ 43,000 GQS with a G(2) repeat sequence motif; notably, 80% of these were located in genic regions, suggesting that these sequences may fold at the RNA level. Gene Ontology functional analysis revealed that GQS are overrepresented in genes encoding proteins of certain functional categories, including enzyme activity. Conversely, GQS are underrepresented in other categories of genes, notably those for non-coding RNAs such as tRNAs and rRNAs. We also find that genes that are differentially regulated by drought are significantly more likely to contain a GQS. CD-detected K(+) titrations performed on representative RNAs verified formation of quadruplexes at physiological K(+) concentrations. Overall, this study indicates that GQS are present at unique locations in Arabidopsis and that folding of RNA GQS may play important roles in regulating gene expression.

The classical RNA secondary structure model considers A.U and G.C Watson-Crick as well as G.U wobble base pairs. Here we substitute it for a new one, in which sets of nucleotide cyclic motifs define RNA structures. This model allows us to unify all base pairing energetic contributions in an effective scoring function to tackle the problem of RNA folding. We show how pipelining two computer algorithms based on nucleotide cyclic motifs, MC-Fold and MC-Sym, reproduces a series of experimentally determined RNA three-dimensional structures from the sequence. This demonstrates how crucial the consideration of all base-pairing interactions is in filling the gap between sequence and structure. We use the pipeline to define rules of precursor microRNA folding in double helices, despite the presence of a number of presumed mismatches and bulges, and to propose a new model of the human immunodeficiency virus-1 -1 frame-shifting element.

We created an accelerated version of MC-Fold called MC-Flashfold that allows us to compute large numbers of competing secondary structures including noncanonical base pairs. We visualize the base pairs in these sets using high quality intuitive dot plots and arc plots. Our new tools allow us to explore RNA dynamics by visualizing the competing structures in free energy bands. Here we describe how to use these tools to generate dot plots that reveal the postulated anti-terminator stem in the E. coli trp operon leader sequence. These plots show the anti-terminator hairpin loop during transcription and as a minor population of the full-length leader sequence. This is a case of switching RNA structure that had been originally postulated based on short dyad inverted repeats. Other switching RNA sequences can be analyzed by using our method.

Despite an increasing number of experimentally determined RNA structures, the gap between the number of structures and that of RNA families is still growing. To overcome this limitation, efficient and reliable RNA modeling methodologies must be developed. In order to reach this goal, here, we show how triloop sequence–structure relationships have been inferred through a systematic analysis of all triloops found in available high-resolution structures. The structural annotation of all triloops allowed us to define discrete states of the triloop's conformational space, and therefore an explicit sequence-to-structure relation. The sequence–structure relationships inferred from this explicit relation are presented in a convenient modeling table that provides a limited set of possible three-dimensional structures given any triloop sequence. The table is indexed by the two nucleotides that form the triloop's flanking base pair, since they are shown to provide the most information about the triloop three-dimensional structures. We also report the observations in the X-ray crystallographic structures of important conformational variations, which we believe might be the result of RNA dynamic.

The formation of beta-sheet domains in proteins involves five energetically important factors: the formation of networks of hydrogen bonds and hydrophobic faces, and the residue propensities, or preferences, to be found at the edges of the beta-sheet, to adopt the extended conformation, and to make contact with other residues. These relative energy contributions define a potential energy function. Here, we show how optimizing this potential energy function reveals the formation of hydrophobic faces as the utmost factor. The potential energy function was optimized to minimize the Z-scores of the native topologies among the exhaustive sets of over 400 different beta-sheets. These results corroborate with experimental data that showed the environment of a protein is an important modulator of beta-sheet folding. The contact propensities were found to be the least important, which could explain the poor predictive power of beta-strand alignment methods based on pair-wise contact matrices.

A new approach, graph-grammars, to encode RNA tertiary structure patterns is introduced and exemplified with the classical sarcin-ricin motif. The sarcin-ricin motif is found in the stem of the crucial ribosomal loop E (also referred to as the sarcin-ricin loop), which is sensitive to the alpha-sarcin and ricin toxins. Here, we generate a graph-grammar for the sarcin-ricin motif and apply it to derive putative sequences that would fold in this motif. The biological relevance of the derived sequences is confirmed by a comparison with those found in known sarcin-ricin sites in an alignment of over 800 bacterial 23S ribosomal RNAs. The comparison raised alternative alignments in few sarcin-ricin sites, which were assessed using tertiary structure predictions and 3D modeling. The sarcin-ricin motif graph-grammar was built with indivisible nucleotide interaction cycles that were recently observed in structured RNAs. A comparison of the sequences and 3D structures of each cycle that constitute the sarcin-ricin motif gave us additional insights about RNA sequence-structure relationships. In particular, this analysis revealed the sequence space of an RNA motif depends on a structural context that goes beyond the single base pairing and base-stacking interactions.

The E2F family of transcription factors is essential in the regulation of the cell cycle and apoptosis. While the activity of E2F1-3 is tightly controlled by the retinoblastoma family of proteins, the expression of these factors is also regulated at the level of transcription, post-translational modifications and protein stability. Recently, a new level of regulation of E2Fs has been identified, where micro-RNAs (miRNAs) from the mir-17-92 cluster influence the translation of the E2F1 mRNA. We now report that miR-20a, a member of the mir-17-92 cluster, modulates the translation of the E2F2 and E2F3 mRNAs via binding sites in their 3'-untranslated region. We also found that the endogenous E2F1, E2F2, and E2F3 directly bind the promoter of the mir-17-92 cluster activating its transcription, suggesting an autoregulatory feedback loop between E2F factors and miRNAs from the mir-17-92 cluster. Our data also point toward an anti-apoptotic role for miR-20a, since overexpression of this miRNA decreased apoptosis in a prostate cancer cell line, while inhibition of miR-20a by an antisense oligonucleotide resulted in increased cell death after doxorubicin treatment. This anti-apoptotic role of miR-20a may explain some of the oncogenic capacities of the mir-17-92 cluster. Altogether, these results suggest that the autoregulation between E2F1-3 and miR-20a is important for preventing an abnormal accumulation of E2F1-3 and may play a role in the regulation of cellular proliferation and apoptosis.

A minimum cycle basis of the tertiary structure of a large ribosomal subunit (LSU) X-ray crystal structure was analyzed. Most cycles are small, as they are composed of 3- to 5 nt, and repeated across the LSU tertiary structure. We used hierarchical clustering to quantify and classify the 4 nt cycles. One class is defined by the GNRA tetraloop motif. The inspection of the GNRA class revealed peculiar instances in sequence. First is the presence of UA, CA, UC and CC base pairs that substitute the usual sheared GA base pair. Second is the revelation of GNR(X(n))A tetraloops, where X(n) is bulged out of the classical GNRA structure, and of GN/RA formed by the two strands of interior-loops. We were able to unambiguously characterize the cycle classes using base stacking and base pairing annotations. The cycles identified correspond to small and cyclic motifs that compose most of the LSU RNA tertiary structure and contribute to its thermodynamic stability. Consequently, the RNA minimum cycles could well be used as the basic elements of RNA tertiary structure prediction methods.

The aim of the RNA Ontology Consortium (ROC) is to create an integrated conceptual framework—an RNA Ontology (RO)—with a common, dynamic, controlled, and structured vocabulary to describe and characterize RNA sequences, secondary structures, three-dimensional structures, and dynamics pertaining to RNA function. The RO should produce tools for clear communication about RNA structure and function for multiple uses, including the integration of RNA electronic resources into the Semantic Web. These tools should allow the accurate description in computer-interpretable form of the coupling between RNA architecture, function, and evolution. The purposes for creating the RO are, therefore, (1) to integrate sequence and structural databases; (2) to allow different computational tools to interoperate; (3) to create powerful software tools that bring advanced computational methods to the bench scientist; and (4) to facilitate precise searches for all relevant information pertaining to RNA. For example, one initial objective of the ROC is to define, identify, and classify RNA structural motifs described in the literature or appearing in databases and to agree on a computer-interpretable definition for each of these motifs. To achieve these aims, the ROC will foster communication and promote collaboration among RNA scientists by coordinating frequent face-to-face workshops to discuss, debate, and resolve difficult conceptual issues. These meeting opportunities will create new directions at various levels of RNA research. The ROC will work closely with the PDB/NDB structural databases and the Gene, Sequence, and Open Biomedical Ontology Consortia to integrate the RO with existing biological ontologies to extend existing content while maintaining interoperability.

The STT3 subunit of the oligosaccharyltransferase complex plays a critical role in the N-glycosylation process. From Arabidopsis thaliana to Homo sapiens, two functional STT3 isoforms have been identified, STT3-A and STT3-B. We report that the last transmembrane (TM) segment of STT3-B corresponds to a topogenic determinant that is sufficient for proper integration and orientation of STT3-B C-terminal domain. Notably, the last TM segment of STT3-A and -B isoforms present major differences in amino acid sequence and predicted 3D structure. We also identified a bipartite nuclear targeting sequence in the C-terminal tail of STT3-B that is absent in STT3-A. The latter sequence is sufficient to induce nucleolar localization of a reporter protein. Our results show that STT3-A and -B display two structural differences that may have a drastic influence on their function and might account for the remarkable evolutionary conservation of the two STT3 paralogs.

In order to characterize regulatory genes that are expressed in ovule tissues after fertilization we have undertaken an EST sequencing project in Solanum chacoense, a self-incompatible wild potato species. Two cDNA libraries made from ovule tissues covering embryo development from zygote to late torpedo-stage were constructed and plated at high density on nylon membranes. To decrease EST redundancy and enrich for transcripts corresponding to weakly expressed genes a self-probe subtraction method was used to select the colonies harboring the genes to be sequenced. 7741 good sequences were obtained and, from these, 6374 unigenes were isolated. Thus, the self-probe subtraction resulted in a strong enrichment in singletons, a decrease in the number of clones per contigs, and concomitantly, an enrichment in the total number of unigenes obtained (82%). To gain insights into signal transduction events occurring during embryo development all the receptor-like kinases (or protein receptor kinases) were analyzed by quantitative real-time RT-PCR. Interestingly, 28 out of the 30 RLK isolated were predominantly expressed in ovary tissues or young developing fruits, and 23 were transcriptionaly induced following fertilization. Thus, the self-probe subtraction did not select for genes weakly expressed in the target tissue while being highly expressed elsewhere in the plant. Of the receptor-like kinases (RLK) genes isolated, the leucine-rich repeat (LRR) family of RLK was by far the most represented with 25 members covering 11 LRR classes.

Systematic protein folding studies depend on protein three-dimensional structure annotation, the assignment of amino acid structural types from atomic coordinates. Significant stabilizing factors between adjacent β-sheet peptide chains have recently been characterized and were not considered during the development of previously published annotation methods. To produce an accurate β-sheet domain catalog and to encompass the full β-sheet spectacle, we developed a method, β-Spider, which evaluates a packing energy between adjacent peptide chains in accordance with the newly discovered stabilizing factors. While considering important energetic factors, our approach also minimizes the use of subjective criteria, such as (ϕ,ψ) boundaries and sets of H-bonding motifs that are used in other existing methods. As a result of the application of β-Spider to a set of available high-resolution X-ray crystal structures, we present here a new β-sheet catalog that differs considerably from the one produced by the most acclaimed DSSP method. The catalog includes new H-bonding motifs that were never reported. Proteins 2005. © 2005 Wiley-Liss, Inc.

The PrP-like Doppel (Dpl) protein causes apoptotic death of cerebellar neurons in transgenic mice, a process prevented by expression of the wild type (wt) cellular prion protein, PrP(C). Internally deleted forms of PrP(C) resembling Dpl such as PrPDelta32-121 produce a similar PrP(C)-sensitive pro-apoptotic phenotype in transgenic mice. Here we demonstrate that these phenotypic attributes of wt Dpl, wt PrP(C), and PrPDelta132-121 can be accurately recapitulated by transfected mouse cerebellar granule cell cultures. This system was then explored by mutagenesis of the co-expressed prion proteins to reveal functional determinants. By this means, neuroprotective activity of wt PrP(C) was shown to be nullified by a deletion of the N-terminal charged region implicated in endocytosis and retrograde axonal transport (PrPDelta23-28), by deletion of all five octarepeats (PrPDelta51-90), or by glycine replacement of four octarepeat histidine residues required for selective binding of copper ions (Prnp"H/G"). In the case of Dpl, overlapping deletions defined a requirement for the gene interval encoding helices B and B' (DplDelta101-125). These data suggest contributions of copper binding and neuronal trafficking to wt PrP(C) function in vivo and place constraints upon current hypotheses to explain Dpl/PrP(C) antagonism by competitive ligand binding. Further implementation of this assay should provide a fuller understanding of the attributes and subcellular localizations required for activity of these enigmatic proteins.

Substrate cleavage by the Neurospora Varkud satellite (VS) ribozyme involves a structural change in the stem-loop I substrate from an inactive to an active conformation. We have determined the NMR solution structure of a mutant stem-loop I that mimics the active conformation of the cleavage site internal loop. This structure shares many similarities, but also significant differences, with the previously determined structures of the inactive internal loop. The active internal loop displays different base-pairing interactions and forms a novel RNA fold composed exclusively of sheared G-A base pairs. From chemical-shift mapping we identified two Mg 2 + binding sites in the active internal loop. One of the Mg 2 + binding sites forms in the active but not the inactive conformation of the internal loop and is likely important for catalysis. Using the structure comparison program mc - search , we identified the active internal loop fold in other RNA structures. In Thermus thermophilus 16S rRNA, this RNA fold is directly involved in a long-range tertiary interaction. An analogous tertiary interaction may form between the active internal loop of the substrate and the catalytic domain of the VS ribozyme. The combination of NMR and bioinformatic approaches presented here has identified a novel RNA fold and provides insights into the structural basis of catalytic function in the Neurospora VS ribozyme.