Publications by authors named "Dmitri D Pervouchine"

20 Publications

  • Page 1 of 1

An extended catalogue of tandem alternative splice sites in human tissue transcriptomes.

PLoS Comput Biol 2021 Apr 7;17(4):e1008329. Epub 2021 Apr 7.

Skolkovo Institute for Science and Technology, Moscow, Russia.

Tandem alternative splice sites (TASS) is a special class of alternative splicing events that are characterized by a close tandem arrangement of splice sites. Most TASS lack functional characterization and are believed to arise from splicing noise. Based on the RNA-seq data from the Genotype Tissue Expression project, we present an extended catalogue of TASS in healthy human tissues and analyze their tissue-specific expression. The expression of TASS is usually dominated by one major splice site (maSS), while the expression of minor splice sites (miSS) is at least an order of magnitude lower. Among 46k miSS with sufficient read support, 9k (20%) are significantly expressed above the expected noise level, and among them 2.5k are expressed tissue-specifically. We found significant correlations between tissue-specific expression of RNA-binding proteins (RBP), tissue-specific expression of miSS, and miSS response to RBP inactivation by shRNA. In combination with RBP profiling by eCLIP, this allowed prediction of novel cases of tissue-specific splicing regulation including a miSS in QKI mRNA that is likely regulated by PTBP1. The analysis of human primary cell transcriptomes suggested that both tissue-specific and cell-type-specific factors contribute to the regulation of miSS expression. More than 20% of tissue-specific miSS affect structured protein regions and may adjust protein-protein interactions or modify the stability of the protein core. The significantly expressed miSS evolve under the same selection pressure as maSS, while other miSS lack signatures of evolutionary selection and conservation. Using mixture models, we estimated that not more than 15% of maSS and not more than 54% of tissue-specific miSS are noisy, while the proportion of noisy splice sites among non-significantly expressed miSS is above 63%.
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http://dx.doi.org/10.1371/journal.pcbi.1008329DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8055015PMC
April 2021

Multiple competing RNA structures dynamically control alternative splicing in the human ATE1 gene.

Nucleic Acids Res 2021 01;49(1):479-490

Skolkovo Institute of Science and Technology, Center of Life Sciences, Moscow 143026, Russia.

The mammalian Ate1 gene encodes an arginyl transferase enzyme with tumor suppressor function that depends on the inclusion of one of the two mutually exclusive exons (MXE), exons 7a and 7b. We report that the molecular mechanism underlying MXE splicing in Ate1 involves five conserved regulatory intronic elements R1-R5, of which R1 and R4 compete for base pairing with R3, while R2 and R5 form an ultra-long-range RNA structure spanning 30 Kb. In minigenes, single and double mutations that disrupt base pairings in R1R3 and R3R4 lead to the loss of MXE splicing, while compensatory triple mutations that restore RNA structure revert splicing to that of the wild type. In the endogenous Ate1 pre-mRNA, blocking the competing base pairings by LNA/DNA mixmers complementary to R3 leads to the loss of MXE splicing, while the disruption of R2R5 interaction changes the ratio of MXE. That is, Ate1 splicing is controlled by two independent, dynamically interacting, and functionally distinct RNA structure modules. Exon 7a becomes more included in response to RNA Pol II slowdown, however it fails to do so when the ultra-long-range R2R5 interaction is disrupted, indicating that exon 7a/7b ratio depends on co-transcriptional RNA folding. In sum, these results demonstrate that splicing is coordinated both in time and in space over very long distances, and that the interaction of these components is mediated by RNA structure.
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http://dx.doi.org/10.1093/nar/gkaa1208DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7797038PMC
January 2021

A limited set of transcriptional programs define major cell types.

Genome Res 2020 07 29;30(7):1047-1059. Epub 2020 Jul 29.

Centre for Genomic Regulation (CRG), The Barcelona Institute of Science and Technology, E-08003 Barcelona, Catalonia, Spain.

We have produced RNA sequencing data for 53 primary cells from different locations in the human body. The clustering of these primary cells reveals that most cells in the human body share a few broad transcriptional programs, which define five major cell types: epithelial, endothelial, mesenchymal, neural, and blood cells. These act as basic components of many tissues and organs. Based on gene expression, these cell types redefine the basic histological types by which tissues have been traditionally classified. We identified genes whose expression is specific to these cell types, and from these genes, we estimated the contribution of the major cell types to the composition of human tissues. We found this cellular composition to be a characteristic signature of tissues and to reflect tissue morphological heterogeneity and histology. We identified changes in cellular composition in different tissues associated with age and sex, and found that departures from the normal cellular composition correlate with histological phenotypes associated with disease.
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http://dx.doi.org/10.1101/gr.263186.120DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7397875PMC
July 2020

Circular exonic RNAs: When RNA structure meets topology.

Biochim Biophys Acta Gene Regul Mech 2019 Nov - Dec;1862(11-12):194384. Epub 2019 May 15.

Skolkovo Institute of Science and Technology, 3 Nobel St, Moscow 143026, Russia; Faculty of Bioengineering and Bioinformatics, Moscow State University, Leninskiye Gory 1-73, Moscow 119234, Russia. Electronic address:

Although RNA circularization was first documented in the 1990s, the extent to which it occurs was not known until recent advances in high-throughput sequencing enabled the widespread identification of circular RNAs (circRNAs). Despite this, many aspects of circRNA biogenesis, structure, and function yet remain obscure. This review focuses on circular exonic RNAs, a subclass of circRNAs that are generated through backsplicing. Here, I hypothesize that RNA secondary structure can be the common factor that promotes both exon skipping and spliceosomal RNA circularization, and that backsplicing of double-stranded regions could generate topologically linked circRNA molecules. CircRNAs manifest themselves by the presence of tail-to-head exon junctions, which were previously attributed to post-transcriptional exon permutation and repetition. I revisit these observations and argue that backsplicing does not automatically imply RNA circularization because tail-to-head exon junctions give only local information about transcript architecture and, therefore, they are in principle insufficient to determine globally circular topology. This article is part of a Special Issue entitled: RNA structure and splicing regulation edited by Francisco Baralle, Ravindra Singh and Stefan Stamm.
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http://dx.doi.org/10.1016/j.bbagrm.2019.05.002DOI Listing
February 2020

An Evolutionary Mechanism for the Generation of Competing RNA Structures Associated with Mutually Exclusive Exons.

Genes (Basel) 2018 Jul 17;9(7). Epub 2018 Jul 17.

Skolkovo Institute for Science and Technology, Ulitsa Nobelya 3, Moscow 121205, Russia.

Alternative splicing is a commonly-used mechanism of diversifying gene products. Mutually exclusive exons (MXE) represent a particular type of alternative splicing, in which one and only one exon from an array is included in the mature RNA. A number of genes with MXE do so by using a mechanism that depends on RNA structure. Transcripts of these genes contain multiple sites called selector sequences that are all complementary to a regulatory element called the docking site; only one of the competing base pairings can form at a time, which exposes one exon from the cluster to the spliceosome. MXE tend to have similar lengths and sequence content and are believed to originate through tandem genomic duplications. Here, we report that pre-mRNAs of this class of exons have an increased capacity to fold into competing secondary structures. We propose an evolutionary mechanism for the generation of such structures via duplications that affect not only exons, but also their adjacent introns with stem-loop structures. If one of the two arms of a stem-loop is duplicated, it will generate two selector sequences that compete for the same docking site, a pattern that is associated with MXE splicing. A similar partial duplication of two independent stem-loops produces a pattern that is consistent with the so-called bidirectional pairing model. These models explain why tandem exon duplications frequently result in mutually exclusive splicing.
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http://dx.doi.org/10.3390/genes9070356DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6071210PMC
July 2018

Towards Long-Range RNA Structure Prediction in Eukaryotic Genes.

Genes (Basel) 2018 Jun 15;9(6). Epub 2018 Jun 15.

Skolkovo Institute for Science and Technology, Ulitsa Nobelya 3, Moscow 121205, Russia.

The ability to form an intramolecular structure plays a fundamental role in eukaryotic RNA biogenesis. Proximate regions in the primary transcripts fold into a local secondary structure, which is then hierarchically assembled into a tertiary structure that is stabilized by RNA-binding proteins and long-range intramolecular base pairings. While the local RNA structure can be predicted reasonably well for short sequences, long-range structure at the scale of eukaryotic genes remains problematic from the computational standpoint. The aim of this review is to list functional examples of long-range RNA structures, to summarize current comparative methods of structure prediction, and to highlight their advances and limitations in the context of long-range RNA structures. Most comparative methods implement the “first-align-then-fold” principle, i.e., they operate on multiple sequence alignments, while functional RNA structures often reside in non-conserved parts of the primary transcripts. The opposite “first-fold-then-align” approach is currently explored to a much lesser extent. Developing novel methods in both directions will improve the performance of comparative RNA structure analysis and help discover novel long-range structures, their higher-order organization, and RNA⁻RNA interactions across the transcriptome.
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http://dx.doi.org/10.3390/genes9060302DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6027157PMC
June 2018

Gene-specific patterns of expression variation across organs and species.

Genome Biol 2016 07 8;17(1):151. Epub 2016 Jul 8.

Centre for Genomic Regulation (CRG), The Barcelona Institute of Science and Technology, Dr. Aiguader 88, Barcelona, 08003, Spain.

Background: A comparison of transcriptional profiles derived from different tissues in a given species or among different species assumes that commonalities reflect evolutionarily conserved programs and that differences reflect species or tissue responses to environmental conditions or developmental program staging. Apparently conflicting results have been published regarding whether organ-specific transcriptional patterns dominate over species-specific patterns, or vice versa, making it unclear to what extent the biology of a given organism can be extrapolated to another. These studies have in common that they treat the transcriptomes monolithically, implicitly ignoring that each gene is likely to have a specific pattern of transcriptional variation across organs and species.

Results: We use linear models to quantify this pattern. We find a continuum in the spectrum of expression variation: the expression of some genes varies considerably across species and little across organs, and simply reflects evolutionary distance. At the other extreme are genes whose expression varies considerably across organs and little across species; these genes are much more likely to be associated with diseases than are genes whose expression varies predominantly across species.

Conclusions: Whether transcriptomes, when considered globally, cluster preferentially according to one component or the other may not be a property of the transcriptomes, but rather a consequence of the dominant behavior of a subset of genes. Therefore, the values of the components of the variance of expression for each gene could become a useful resource when planning, interpreting, and extrapolating experimental data from mouse to humans.
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http://dx.doi.org/10.1186/s13059-016-1008-yDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4937605PMC
July 2016

Human genomics. The human transcriptome across tissues and individuals.

Science 2015 May;348(6235):660-5

Center for Genomic Regulation (CRG), Barcelona, Catalonia, Spain. Universitat Pompeu Fabra (UPF), Barcelona, Catalonia, Spain. Institut Hospital del Mar d'Investigacions Mèdiques (IMIM), Barcelona, Catalonia, Spain. Joint CRG-Barcelona Super Computing Center (BSC)-Institut de Recerca Biomedica (IRB) Program in Computational Biology, Barcelona, Catalonia, Spain.

Transcriptional regulation and posttranscriptional processing underlie many cellular and organismal phenotypes. We used RNA sequence data generated by Genotype-Tissue Expression (GTEx) project to investigate the patterns of transcriptome variation across individuals and tissues. Tissues exhibit characteristic transcriptional signatures that show stability in postmortem samples. These signatures are dominated by a relatively small number of genes—which is most clearly seen in blood—though few are exclusive to a particular tissue and vary more across tissues than individuals. Genes exhibiting high interindividual expression variation include disease candidates associated with sex, ethnicity, and age. Primary transcription is the major driver of cellular specificity, with splicing playing mostly a complementary role; except for the brain, which exhibits a more divergent splicing program. Variation in splicing, despite its stochasticity, may play in contrast a comparatively greater role in defining individual phenotypes.
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http://dx.doi.org/10.1126/science.aaa0355DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4547472PMC
May 2015

Enhanced transcriptome maps from multiple mouse tissues reveal evolutionary constraint in gene expression.

Nat Commun 2015 Jan 13;6:5903. Epub 2015 Jan 13.

Functional Genomics Group, Cold Spring Harbor Laboratory, 1 Bungtown Road, Cold Spring Harbor, New York 11724, USA.

Mice have been a long-standing model for human biology and disease. Here we characterize, by RNA sequencing, the transcriptional profiles of a large and heterogeneous collection of mouse tissues, augmenting the mouse transcriptome with thousands of novel transcript candidates. Comparison with transcriptome profiles in human cell lines reveals substantial conservation of transcriptional programmes, and uncovers a distinct class of genes with levels of expression that have been constrained early in vertebrate evolution. This core set of genes captures a substantial fraction of the transcriptional output of mammalian cells, and participates in basic functional and structural housekeeping processes common to all cell types. Perturbation of these constrained genes is associated with significant phenotypes including embryonic lethality and cancer. Evolutionary constraint in gene expression levels is not reflected in the conservation of the genomic sequences, but is associated with conserved epigenetic marking, as well as with characteristic post-transcriptional regulatory programme, in which sub-cellular localization and alternative splicing play comparatively large roles.
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http://dx.doi.org/10.1038/ncomms6903DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4308717PMC
January 2015

A comparative encyclopedia of DNA elements in the mouse genome.

Nature 2014 Nov;515(7527):355-64

Bioinformatics and Genomics, Centre for Genomic Regulation (CRG) and UPF, Doctor Aiguader, 88, 08003 Barcelona, Catalonia, Spain.

The laboratory mouse shares the majority of its protein-coding genes with humans, making it the premier model organism in biomedical research, yet the two mammals differ in significant ways. To gain greater insights into both shared and species-specific transcriptional and cellular regulatory programs in the mouse, the Mouse ENCODE Consortium has mapped transcription, DNase I hypersensitivity, transcription factor binding, chromatin modifications and replication domains throughout the mouse genome in diverse cell and tissue types. By comparing with the human genome, we not only confirm substantial conservation in the newly annotated potential functional sequences, but also find a large degree of divergence of sequences involved in transcriptional regulation, chromatin state and higher order chromatin organization. Our results illuminate the wide range of evolutionary forces acting on genes and their regulatory regions, and provide a general resource for research into mammalian biology and mechanisms of human diseases.
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http://dx.doi.org/10.1038/nature13992DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4266106PMC
November 2014

IRBIS: a systematic search for conserved complementarity.

RNA 2014 Oct 20;20(10):1519-31. Epub 2014 Aug 20.

Centre for Genomic Regulation and UPF, Barcelona 08003, Spain Faculty of Bioengineering and Bioinformatics, Moscow State University, 119992 Moscow, Russia

IRBIS is a computational pipeline for detecting conserved complementary regions in unaligned orthologous sequences. Unlike other methods, it follows the "first-fold-then-align" principle in which all possible combinations of complementary k-mers are searched for simultaneous conservation. The novel trimming procedure reduces the size of the search space and improves the performance to the point where large-scale analyses of intra- and intermolecular RNA-RNA interactions become possible. In this article, I provide a rigorous description of the method, benchmarking on simulated and real data, and a set of stringent predictions of intramolecular RNA structure in placental mammals, drosophilids, and nematodes. I discuss two particular cases of long-range RNA structures that are likely to have a causal effect on single- and multiple-exon skipping, one in the mammalian gene Dystonin and the other in the insect gene Ca-α1D. In Dystonin, one of the two complementary boxes contains a binding site of Rbfox protein similar to one recently described in Enah gene. I also report that snoRNAs and long noncoding RNAs (lncRNAs) have a high capacity of base-pairing to introns of protein-coding genes, suggesting possible involvement of these transcripts in splicing regulation. I also find that conserved sequences that occur equally likely on both strands of DNA (e.g., transcription factor binding sites) contribute strongly to the false-discovery rate and, therefore, would confound every such analysis. IRBIS is an open-source software that is available at http://genome.crg.es/~dmitri/irbis/.
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http://dx.doi.org/10.1261/rna.045088.114DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4174434PMC
October 2014

Intron-centric estimation of alternative splicing from RNA-seq data.

Bioinformatics 2013 Jan 21;29(2):273-4. Epub 2012 Nov 21.

Centre de Regulació Genòmica, 08003 Barcelona, Spain.

Motivation: Novel technologies brought in unprecedented amounts of high-throughput sequencing data along with great challenges in their analysis and interpretation. The percent-spliced-in (PSI, ) metric estimates the incidence of single-exon-skipping events and can be computed directly by counting reads that align to known or predicted splice junctions. However, the majority of human splicing events are more complex than single-exon skipping.

Results: In this short report, we present a framework that generalizes the metric to arbitrary classes of splicing events. We change the view from exon centric to intron centric and split the value of into two indices, and , measuring the rate of splicing at the 5' and 3' end of the intron, respectively. The advantage of having two separate indices is that they deconvolute two distinct elementary acts of the splicing reaction. The completeness of splicing index is decomposed in a similar way. This framework is implemented as bam2ssj, a BAM-file-processing pipeline for strand-specific counting of reads that align to splice junctions or overlap with splice sites. It can be used as a consistent protocol for quantifying splice junctions from RNA-seq data because no such standard procedure currently exists.

Availability: The C code of bam2ssj is open source and is available at https://github.com/pervouchine/bam2ssj

Contact: dp@crg.eu
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http://dx.doi.org/10.1093/bioinformatics/bts678DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3546801PMC
January 2013

Evidence for widespread association of mammalian splicing and conserved long-range RNA structures.

RNA 2012 Jan 29;18(1):1-15. Epub 2011 Nov 29.

Department of Bioengineering and Bioinformatics, Moscow State University, Moscow, 119992, GSP-2 Russia.

Pre-mRNA structure impacts many cellular processes, including splicing in genes associated with disease. The contemporary paradigm of RNA structure prediction is biased toward secondary structures that occur within short ranges of pre-mRNA, although long-range base-pairings are known to be at least as important. Recently, we developed an efficient method for detecting conserved RNA structures on the genome-wide scale, one that does not require multiple sequence alignments and works equally well for the detection of local and long-range base-pairings. Using an enhanced method that detects base-pairings at all possible combinations of splice sites within each gene, we now report RNA structures that could be involved in the regulation of splicing in mammals. Statistically, we demonstrate strong association between the occurrence of conserved RNA structures and alternative splicing, where local RNA structures are generally more frequent at alternative donor splice sites, while long-range structures are more associated with weak alternative acceptor splice sites. As an example, we validated the RNA structure in the human SF1 gene using minigenes in the HEK293 cell line. Point mutations that disrupted the base-pairing of two complementary boxes between exons 9 and 10 of this gene altered the splicing pattern, while the compensatory mutations that reestablished the base-pairing reverted splicing to that of the wild-type. There is statistical evidence for a Dscam-like class of mammalian genes, in which mutually exclusive RNA structures control mutually exclusive alternative splicing. In sum, we propose that long-range base-pairings carry an important, yet unconsidered part of the splicing code, and that, even by modest estimates, there must be thousands of such potentially regulatory structures conserved throughout the evolutionary history of mammals.
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http://dx.doi.org/10.1261/rna.029249.111DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3261731PMC
January 2012

Modulation of alternative splicing by long-range RNA structures in Drosophila.

Nucleic Acids Res 2009 Aug 22;37(14):4533-44. Epub 2009 May 22.

Center for Genomic Regulation (CRG), Dr. Aiguader, 88, 08003 Barcelona, Spain.

Accurate and efficient recognition of splice sites during pre-mRNA splicing is essential for proper transcriptome expression. Splice site usage can be modulated by secondary structures, but it is unclear if this type of modulation is commonly used or occurs to a significant degree with secondary structures forming over long distances. Using phlyogenetic comparisons of intronic sequences among 12 Drosophila genomes, we elucidated a group of 202 highly conserved pairs of sequences, each at least nine nucleotides long, capable of forming stable stem structures. This set was highly enriched in alternatively spliced introns and introns with weak acceptor sites and long introns, and most occurred over long distances (>150 nucleotides). Experimentally, we analyzed the splicing of several of these introns using mini-genes in Drosophila S2 cells. Wild-type splicing patterns were changed by mutations that opened the stem structure, and restored by compensatory mutations that re-established the base-pairing potential, demonstrating that these secondary structures were indeed implicated in the splice site choice. Mechanistically, the RNA structures masked splice sites, brought together distant splice sites and/or looped out introns. Thus, base-pairing interactions within introns, even those occurring over long distances, are more frequent modulators of alternative splicing than is currently assumed.
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http://dx.doi.org/10.1093/nar/gkp407DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2724269PMC
August 2009

Low-dimensional maps encoding dynamics in entorhinal cortex and hippocampus.

Neural Comput 2006 Nov;18(11):2617-50

Department of Mathematics and Statistics and Center for BioDynamics, Boston University, Boston, MA 02215, USA.

Cells that produce intrinsic theta oscillations often contain the hyperpolarization-activated current I(h). In this article, we use models and dynamic clamp experiments to investigate the synchronization properties of two such cells (stellate cells of the entorhinal cortex and O-LM cells of the hippocampus) in networks with fast-spiking (FS) interneurons. The model we use for stellate cells and O-LM cells is the same, but the stellate cells are excitatory and the O-LM cells are inhibitory, with inhibitory postsynaptic potential considerably longer than those from FS interneurons. We use spike time response curve methods (STRC), expanding that technique to three-cell networks and giving two different ways in which the analysis of the three-cell network reduces to that of a two-cell network. We show that adding FS cells to a network of stellate cells can desynchronize the stellate cells, while adding them to a network of O-LM cells can synchronize the O-LM cells. These synchronization and desynchronization properties critically depend on I(h). The analysis of the deterministic system allows us to understand some effects of noise on the phase relationships in the stellate networks. The dynamic clamp experiments use biophysical stellate cells and in silico FS cells, with connections that mimic excitation or inhibition, the latter with decay times associated with FS cells or O-LM cells. The results obtained in the dynamic clamp experiments are in a good agreement with the analytical framework.
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http://dx.doi.org/10.1162/neco.2006.18.11.2617DOI Listing
November 2006

RNAKinetics: a web server that models secondary structure kinetics of an elongating RNA.

J Bioinform Comput Biol 2006 Apr;4(2):589-96

Institute for Problems of Information Transition RAS, Bolshoi Karetnyi per. 19, Moscow, 127994, Russia.

The RNAKinetics server (http://www.ig-msk.ru/RNA/kinetics) is a web interface for the newly developed RNAKinetics software. The software models the dynamics of RNA secondary structure by the means of kinetic analysis of folding transitions of a growing RNA molecule. The result of the modeling is a kinetic ensemble, i.e. a collection of RNA structures that are endowed with probabilities, which depend on time. This approach gives comprehensive probabilistic description of RNA folding pathways, revealing important kinetic details that are not captured by the traditional structure prediction methods. The access to the RNAKinetics server is free.
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http://dx.doi.org/10.1142/s0219720006001904DOI Listing
April 2006

Slow and fast inhibition and an H-current interact to create a theta rhythm in a model of CA1 interneuron network.

J Neurophysiol 2005 Aug 27;94(2):1509-18. Epub 2005 Apr 27.

Department of Mathematics and Statistics and Center for Biodynamics, Boston University, Boston, MA 02215, USA.

The oriens-lacunosum moleculare (O-LM) subtype of interneuron is a key component in the formation of the theta rhythm (8-12 Hz) in the hippocampus. It is known that the CA1 region of the hippocampus can produce theta rhythms in vitro with all ionotropic excitation blocked, but the mechanisms by which this rhythmicity happens were previously unknown. Here we present a model suggesting that individual O-LM cells, by themselves, are capable of producing a single-cell theta-frequency firing, but coupled O-LM cells are not capable of producing a coherent population theta. By including in the model fast-spiking (FS) interneurons, which give rise to IPSPs that decay faster than those of the O-LM cells, coherent theta rhythms are produced. The inhibition to O-LM cells from the FS cells synchronizes the O-LM cells, but only when the FS cells themselves fire at a theta frequency. Reciprocal connections from the O-LM cells to the FS cells serve to parse the FS cell firing into theta bursts, which can then synchronize the O-LM cells. A component of the model O-LM cell critical to the synchronization mechanism is the hyperpolarization-activated h-current. The model can robustly reproduce relative phases of theta frequency activity in O-LM and FS cells.
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http://dx.doi.org/10.1152/jn.00957.2004DOI Listing
August 2005

IRIS: intermolecular RNA interaction search.

Genome Inform 2004 ;15(2):92-101

Center for BioDynamics, Boston University, Boston, MA 02215, USA.

Here we present IRIS, a method for prediction of RNA-RNA interactions that is based on dynamic programming and extends current RNA secondary structure prediction approaches. Using this method we have found a number of interesting refinements to the structures of RNA-RNA complexes that have been studied previously and predicted novel targets for several known regulatory RNAs in E. coli. The computational time and memory usage of IRIS are O(n(3)m(3)) and O(n(2)m(2)), respectively, where n and m are the lengths of the input sequences. IRIS can be used for analysis of antisense regulatory systems in sequenced organisms and for the design of artificial riboregulators such as antisense drugs.
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January 2006

Engineered riboregulators enable post-transcriptional control of gene expression.

Nat Biotechnol 2004 Jul 20;22(7):841-7. Epub 2004 Jun 20.

Center for BioDynamics and Department of Biomedical Engineering, Boston University, 44 Cummington Street, Boston, Massachusetts 02215, USA.

Recent studies have demonstrated the important enzymatic, structural and regulatory roles of RNA in the cell. Here we present a post-transcriptional regulation system in Escherichia coli that uses RNA to both silence and activate gene expression. We inserted a complementary cis sequence directly upstream of the ribosome binding site in a target gene. Upon transcription, this cis-repressive sequence causes a stem-loop structure to form at the 5'-untranslated region of the mRNA. The stem-loop structure interferes with ribosome binding, silencing gene expression. A small noncoding RNA that is expressed in trans targets the cis-repressed RNA with high specificity, causing an alteration in the stem-loop structure that activates expression. Such engineered riboregulators may lend insight into mechanistic actions of endogenous RNA-based processes and could serve as scalable components of biological networks, able to function with any promoter or gene to directly control gene expression.
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http://dx.doi.org/10.1038/nbt986DOI Listing
July 2004

On the normalization of RNA equilibrium free energy to the length of the sequence.

Nucleic Acids Res 2003 May;31(9):e49

Bioinformatics Program, Boston University, Boston, MA 02215, USA.

There is no universal definition of stability for RNA secondary structures. Here we present an approach that is based on normalization of the equilibrium free energy to the length of the sequence: a segment of RNA is said to be stable if the ratio of the equilibrium free energy to the length of the segment is greater than a certain threshold value. Discarding the segments whose normalized equilibrium free energies are smaller than the threshold allows us to view the secondary structure at different levels of stability. Confined to only highly stable structures, the algorithm for secondary structure prediction admits a number of simplifications that make it computationally tractable for large sequences and advantageous over most other methods on a genome-wide scale. This method was applied to the Caenorhabditis elegans genome to localize the regions that encode stable secondary structures. In particular, 36 of 56 previously reported micro-RNAs were localized to 4% of the genome. A fraction of long (>or=400 nt) stable inverted repeats in the genomic sequence of C.elegans was found. Their distribution is very uneven, and skewed towards the ends of chromosomes. This method can be used for genome-wide detection of transcription termination signals, putative micro-RNAs, and other regulatory elements that involve stable RNA secondary structures.
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC154237PMC
http://dx.doi.org/10.1093/nar/gng049DOI Listing
May 2003