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Nanopore sequencing provides signal data corresponding to the nucleotide motifs sequenced. Through machine learning-based methods, these signals are translated into long-read sequences that overcome the read size limit of short-read sequencing. However, analyzing the raw nanopore signal data provides many more opportunities beyond just sequencing genomes and transcriptomes: algorithms that use machine learning approaches to extract biological information from these signals allow the detection of DNA and RNA modifications, the estimation of poly(A) tail length, and the prediction of RNA secondary structures. In this review, we discuss how developments in machine learning methodologies contributed to more accurate basecalling and lower error rates, and how these methods enable new biological discoveries. We argue that direct nanopore sequencing of DNA and RNA provides a new dimensionality for genomics experiments and highlight challenges and future directions for computational approaches to extract the additional information provided by nanopore signal data.

An RNA global fold can be described at the level of helix orientations and relatively flexible loop conformations that connect the helices. The linkage between the helices plays an essential role in determining the structural topology, which restricts RNA local and global folds, especially for RNA tertiary structures involving cross-linked base pairs. We quantitatively analyze the topological constraints on RNA 3D conformational space, in particular, on the distribution of helix orientations, for pseudoknots and loop-loop kissing structures. The result shows that a viable conformational space is predominantly determined by the motif type, helix size, and loop size, indicating a strong topological coupling between helices and loops in RNA tertiary motifs. Moreover, the analysis indicates that (cross-linked) tertiary contacts can cause much stronger topological constraints on RNA global fold than non-cross-linked base pairs. Furthermore, based on the topological constraints encoded in the 2D structure and the 3D templates, we develop a 3D structure prediction approach. This approach can be further combined with structure probing methods to expand the capability of computational prediction for large RNA folds.

Simple sequence repeat (SSR) markers provide a reliable tool for the identification of accessions and the construction of genetic linkage maps because of their co-dominant inheritance. In the present study, we developed new SSR markers with next-generation sequencing using the Roche 454 GS FLX+ platform. Five hundred SSR primer sets were tested for the genetic identification of pineapple, including 100 each for the di-, tri-, tetra-, penta-, and hexa-nucleotide motif SSRs. In total, 160 SSR markers successfully amplified fragments and exhibited polymorphism among accessions. The SSR markers revealed the number of alleles per locus (ranging from 2 to 13), the expected heterozygosity (ranging from 0.041 to 0.823), and the observed heterozygosity (ranging from 0 to 0.875). A total of 117 SSR markers with tri- or greater nucleotide motifs were shown to be effective at facilitating accurate genotyping. Using the SSR markers, 25 accessions were distinguished genetically, with the exception of accessions 'MD-2' and 'Yonekura'. The developed SSR markers could facilitate the establishment of efficient and accurate genetic identification systems and the construction of genetic linkage maps in the future.

Microsatellites are short tandem repeats of 1–6 nucleotide motifs, studied for their utility as genome markers and in forensics. Recent evidence points to the role of microsatellites in important regulatory functions, and their length polymorphisms at coding regions are linked to various neurodegenerative disorders in humans. Microsatellites show a taxon-specific enrichment in eukaryotic genomes, and their evolution remains poorly understood. Though other databases of microsatellites exist, they fall short on several fronts. MSDB (MicroSatellite DataBase) is a collection of >4 billion microsatellites from 37 680 genomes presented in a user-friendly web portal for easy, interactive analysis and visualization. This is by far the most comprehensive, annotated, updated database to access and analyze microsatellite data of multiple species. The features of MSDB enable users to explore the data as tables that can be filtered and exported, and also as interactive charts to view and compare the data of multiple species simultaneously. Its modularity and architecture permit seamless updates with new data, making it a powerful tool and useful resource to researchers working on this important class of DNA elements, particularly in context of their evolution and emerging roles in genome organization and gene regulation.

The ever-expanding set of CRISPR technologies and their programmable RNA-guided nucleases exhibit remarkable flexibility in DNA targeting. However, this flexibility comes with an ever-present constraint: the requirement for a protospacer adjacent motif (PAM) flanking each target. While PAMs play an essential role in self/nonself discrimination by CRISPR-Cas immune systems, this constraint has launched a far-reaching expedition for nucleases with relaxed PAM requirements. Here, we review ongoing efforts toward realizing PAM-free nucleases through natural ortholog mining and protein engineering. We also address potential consequences of fully eliminating PAM recognition and instead propose an alternative nuclease repertoire covering all possible PAM sequences., One of the key limitations of CRISPR-Cas-based genome editing techniques is the PAM dependency. Here, the authors review ongoing efforts towards realizing PAM-free nucleases, address potential consequences of eliminating PAM recognition, and propose an alternative nuclease repertoire covering all possible PAM sequences.

The neurotrophin Brain-derived neurotrophic factor (BDNF) is encoded by multiple bipartite transcripts. Each BDNF transcript is composed by one out of eleven alternatively spliced exons containing the 5’untranslated region (UTR), and one common exon encompassing the coding sequence (CDS) and the 3’UTR with two variants (short and long). In neurons, BDNF mRNA variants have a distinct subcellular distribution, constituting a “spatial code”, with exon 1, 3, 5, 7 and 8 located in neuronal somata, exon 4 extending into proximal dendrites, and exon 2 and 6 reaching distal dendrites. We previously showed that the CDS encodes constitutive dendritic targeting signals (DTS) and that both the 3’UTR-short and the 3’UTR-long contain activity-dependent DTS. However, the role of individual 5’UTR exons in mRNA sorting remains unclear. Here, we tested the ability of each different BDNF 5'UTRs to affect the subcellular localization of the green fluorescent protein (GFP) reporter mRNA. We found that exon 2 splicing isoforms (2a, 2b, and 2c) induced a constitutive dendritic targeting of the GFP reporter mRNA towards distal dendritic segments. The other isoforms did not affect GFP-mRNA dendritic trafficking. Through a bioinformatic analysis, we identified five unique cis-elements in exon 2a, 2b, and 2c which might contribute to building a DTS. This study provides additional information on the mechanism regulating the cellular sorting of BDNF mRNA variants.

A decade ago, the role of the CRISPR-Cas (Clustered Regularly Interspaced Short Palindromic Repeats- CRISPR-associated) system as an adaptive immune system in prokaryotes was first demonstrated exp...

Single-stranded microRNAs (miRNAs) regulate gene expression by triggering mRNA degradation and/or inhibiting mRNA translation. miRNAs play important roles in various critical cellular processes and are associated with numerous human diseases, including cancer and neurodegenerative diseases. miRNA sequences are embedded in the primary miRNA transcripts (pri-miRNAs) that are initially processed by the Microprocessor complex in the nucleus. Microprocessor can orient itself on pri-miRNAs in two ways: one orientation results in subsequent miRNA production, and the other leads to cleavage of the miRNA sequence. Therefore, orienting Microprocessor on pri-miRNAs is a fundamental mechanism for determining the accuracy and efficiency of pri-miRNA processing and, in turn, miRNA production. Multiple mechanisms controlling Microprocessor orientation on pri-miRNAs, involving both cis-acting RNA elements and trans-acting factors, have recently been revealed. In this review, we discuss these exciting mechanisms and consider potential unknown mechanisms that might regulate Microprocessor orientation on pri-miRNAs.

In bacteria and archaea, short fragments of foreign DNA are integrated into Clustered Regularly Interspaced Short Palindromic Repeat (CRISPR) loci, providing a molecular memory of previous encounters with foreign genetic elements. In Escherichia coli, short CRISPR-derived RNAs are incorporated into a multi-subunit surveillance complex called Cascade (CRISPR-associated complex for antiviral defense). Recent structures of Cascade capture snapshots of this seahorse-shaped RNA-guided surveillance complex before and after binding to a DNA target. Here we determine a 3.2 Å x-ray crystal structure of Cascade in a new crystal form that provides insight into the mechanism of double-stranded DNA binding. Molecular dynamic simulations performed using available structures reveal functional roles for residues in the tail, backbone and belly subunits of Cascade that are critical for binding double-stranded DNA. Structural comparisons are used to make functional predictions and these predictions are tested in vivo and in vitro. Collectively, the results in this study reveal underlying mechanisms involved in target-induced conformational changes and highlight residues important in DNA binding and protospacer adjacent motif recognition.

The authors investigated the regulatory network motifs and corresponding motif positions of cancer‐related genes. First, they mapped disease‐related genes to a transcription factor regulatory network. Next, they calculated statistically significant motifs and subsequently identified positions within these motifs that were enriched in cancer‐related genes. Potential mechanisms of these motifs and positions are discussed. These results could be used to identify other disease‐ and cancer‐related genes and could also suggest mechanisms for how these genes relate to co‐occurring diseases.

Microsatellites or simple sequence repeats (SSRs) constitute a significant portion of genomes and play an important role in gene function and genome organization. The availability of a complete genome sequence for yak (Bos grunniens) has made it possible to carry out genome-wide analysis of microsatellites in this species. We analyzed the abundance and density of perfect SSRs in the yak genome. We found a total of 723,172 SSRs with 1-6 bp nucleotide motifs, indicating that about 0.47 % of the yak whole genome sequence (2.66 Gb) comprises perfect SSRs, the average length of which was 17.34 bp/Mb. The average frequency and density of perfect SSRs was 272.18 loci/Mb and 4719.25 bp/Mb, respectively. The proportion of the six classes of perfect SSRs was not evenly distributed in the yak genome. Mononucleotide repeats (44.04 %) with a total number of 318,435 and a average length of 14.71 bp appeared to be the most abundant SSRs class, while the percentages of dinucleotide, trinucleotide, pentanucleotide, tetranucleotide and hexanucleotide repeats was 24.11 %, 15.80 %, 9.50 %, 6.40 % and 0.15 %, respectively. Different repeat classes of SSRs varied in their repeat number with the highest being 1206. Our results suggest that 15 motifs comprised the predominant categories with a frequency above 1 loci/Mb: A, AC, AT, AG, AGC, AAC, AAT, ACC, ATTT, GTTT, AATG, CTTT, ATGG, AACTG and ATCTG.

Two second-generation quadruplex hammerhead ribozymes, whose activity enhances in response to K(+)via quadruplex formation of embedded r(GGA)3GG, were developed. Different strategies were applied to suppress basal activity when K(+) is absent. As a result, the activity enhancement upon the addition of K(+) has reached as high as 21-fold., Accepted 13 Feb 2015.

Identification of transcription factor binding sites or biological motifs is an important step in deciphering the mechanisms of gene regulation. It is a classic problem that has eluded a satisfactory and efficient solution. In this paper, we devise a three-phase algorithm to mine for biologically significant motifs. In the first phase, we generate all the possible string motifs, this phase is followed by a filtering process where we discard all motifs that do not meet the constraints. And in the final phase, motifs are scored and ranked using a combination of stochastic techniques and [Formula: see text]-value. We show that our method outperforms some very well-known motif discovery tools, e.g. MEME and Weeder on well-established benchmark data suites. We also apply the algorithm on the non-coding regions of M. tuberculosis and report significant motifs of size 10 with excellent [Formula: see text]-values in a fraction of the time MEME and MoSDi did. In fact, among the best 10 motifs ([Formula: see text]-value wise) in the non-coding regions of M. tuberculosis reported by the tools MEME, MoSDi and ours, five were discovered by our approach which included the third and the fourth best ones. All this in 1/17 and 1/6 the time which MEME and MoSDi (respectively) took.

Structured noncoding RNAs underlie fundamental cellular processes, but determining their three-dimensional structures remains challenging. We demonstrate that integrating 1H NMR chemical shift data with Rosetta de novo modeling can be used to consistently determine high-resolution RNA structures. On a benchmark set of 23 noncanonical RNA motifs, including 11 'blind' targets, chemical-shift Rosetta for RNA (CS-Rosetta-RNA) recovered experimental structures with high accuracy (0.6-2.0 Å all-heavy-atom r.m.s. deviation) in 18 cases. © 2014 Nature America, Inc. All rights reserved.

Aptamers are an interesting alternative to antibodies in pharmaceutics and biosensorics, because they are able to bind to a multitude of possible target molecules with high affinity. Therefore the process of finding such aptamers, which is commonly a SELEX screening process, becomes crucial. The standard SELEX procedure schedules the validation of certain found aptamers via binding experiments, which is not leading to any detailed specification of the aptamer enrichment during the screening. For the purpose of advanced analysis of the accrued enrichment within the SELEX library we used sequence information gathered by next generation sequencing techniques in addition to the standard SELEX procedure. As sequence motifs are one possibility of enrichment description, the need of finding those recurring sequence motifs corresponding to substructures within the aptamers, which are characteristically fitted to specific binding sites of the target, arises. In this paper a motif search algorithm is presented, which helps to describe the aptamers enrichment in more detail. The extensive characterization of target and binding aptamers may later reveal a functional connection between these molecules, which can be modeled and used to optimize future SELEX runs in case of the generation of target-specific starting libraries.

Global RNA structure and local functional motifs mediate interactions important in determining the rates and patterns of mRNA splicing. In this review, we overview approaches for the computational prediction of RNA secondary structure with a special emphasis on the discovery of motifs important to RNA splicing. The process of identifying and modeling potential splicing regulatory structures is illustrated using a recently-developed approach for RNA structural motif discovery, the ScanFold pipeline, which is applied to the identification of a known splicing regulatory structure in influenza virus.

N6-methyladenosine (m6A) is the most abundant modification on mRNA and is implicated in critical roles in development, physiology, and disease. A major limitation has been the inability to quantify m6A stoichiometry and the lack of antibody-independent methodologies for interrogating m6A. Here, we develop MAZTER-seq for systematic quantitative profiling of m6A at single-nucleotide resolution at 16%-25% of expressed sites, building on differential cleavage by an RNase. MAZTER-seq permits validation and de novo discovery of m6A sites, calibration of the performance of antibody-based approaches, and quantitative tracking of m6A dynamics in yeast gametogenesis and mammalian differentiation. We discover that m6A stoichiometry is "hard coded" in cis via a simple and predictable code, accounting for 33%-46% of the variability in methylation levels and allowing accurate prediction of m6A loss and acquisition events across evolution. MAZTER-seq allows quantitative investigation of m6A regulation in subcellular fractions, diverse cell types, and disease states.

Programmable and precise regulation of dCas9 functions in response to multiple molecular signals by using synthetic gene circuits will expand the application of the CRISPR-Cas technology. However, the application of CRISPR-Cas therapeutic circuits is still challenging due to the restrictive cargo size of existing viral delivery vehicles. Here, we construct logic AND circuits by integrating multiple split dCas9 domains, which is useful to reduce the size of synthetic circuits. In addition, we engineer sensory switches by exchanging split dCas9 domains, allowing differential regulations on one gene, or activating two different genes in response to cell-type specific microRNAs. Therefore, we provide a valuable split-dCas9 toolkit to engineer complex transcription controls, which may inspire new biomedical applications., Molecular engineering of Cas9 has the potential to expand the application of CRISPR-Cas technology. Here, Ma et al. show that dCas9 can be split and reconstituted in human cells and use a domain swapping strategy to engineer custom Cas9-based logic circuits and sensory switches.

Centromere protein B, which is involved in centromere formation, binds to centromeric repetitive DNA by recognizing a nucleotide motif called the CENP-B box. Humans have large numbers of CENP-B boxes in the centromeric repetitive DNA of their autosomes and X chromosome. The current understanding is that these CENP-B boxes are located at identical positions in the repeat units of centromeric DNA. Great apes also have CENP-B boxes in locations that are identical to humans. The purpose of the present study was to examine the location of CENP-B box in New World monkeys. We recently identified CENP-B box in one species of New World monkeys (marmosets). In this study, we found functional CENP-B boxes in CENP-A-assembled repeat units of centromeric DNA in 2 additional New World monkeys (squirrel monkeys and tamarins) by immunostaining and ChIP-qPCR analyses. The locations of the 3 CENP-B boxes in the repeat units differed from one another. The repeat unit size of centromeric DNA of New World monkeys (340–350 bp) is approximately twice that of humans and great apes (171 bp). This might be, associated with higher-order repeat structures of centromeric DNA, a factor for the observed variation in the CENP-B box location in New World monkeys.

The complexity of transcriptome-wide protein-RNA interaction networks is incompletely understood. While emerging studies are greatly expanding the known universe of RNA-binding proteins, methods for the discovery and characterization of protein-RNA interactions remain resource intensive and technically challenging. Here we introduce a UV-C crosslinking and immunoprecipitation platform, irCLIP, which provides an ultraefficient, fast, and nonisotopic method for the detection of protein-RNA interactions using far less material than standard protocols.

An Affymetrix GeneChip consists of an array of hundreds of thousands of probes (each a sequence of 25 bases) with the probe values being used to infer the extent to which genes are expressed in the biological material under investigation. In this article, we demonstrate that these probe values are also strongly influenced by their precise base sequence. We use data from >28 000 CEL files relating to 10 different Affymetrix GeneChip platforms and involving nearly 1000 experiments. Our results confirm known effects (those due to the T7-primer and the formation of G-quadruplexes) but reveal other effects. We show that there can be huge variations from one experiment to another, and that there may also be sizeable disparities between batches within an experiment and between CEL files within a batch.

Similarities in the 3D patterns of RNA base interactions or arrangements can provide insights into their functions and roles in stabilization of the RNA 3D structure. Nucleic Acids Search for Substructures and Motifs (NASSAM) is a graph theoretical program that can search for 3D patterns of base arrangements by representing the bases as pseudo-atoms. The geometric relationship of the pseudo-atoms to each other as a pattern can be represented as a labeled graph where the pseudo-atoms are the graph's nodes while the edges are the inter-pseudo-atomic distances. The input files for NASSAM are PDB formatted 3D coordinates. This web server can be used to identify matches of base arrangement patterns in a query structure to annotated patterns that have been reported in the literature or that have possible functional and structural stabilization implications. The NASSAM program is freely accessible without any login requirement at http://mfrlab.org/grafss/nassam/.

Motivation: How to find motifs from genome-scale functional sequences, such as all the promoters in a genome, is a challenging problem. Word-based methods count the occurrences of oligomers to detect excessively represented ones. This approach is known to be fast and accurate compared with other methods. However, two problems have hampered the application of such methods to large-scale data. One is the computational cost necessary for clustering similar oligomers, and the other is the bias in the frequency of fixed-length oligomers, which complicates the detection of significant words. Results: We introduce a method that uses a DNA Gray code and equiprobable oligomers, which solve the clustering problem and the oligomer bias, respectively. Our method can analyze 18 000 sequences of ~1 kbp long in 30 s. We also show that the accuracy of our method is superior to that of a leading method, especially for large-scale data and small fractions of motif-containing sequences. Availability: The online and stand-alone versions of the application, named Hegma, are available at our website: http://www.genome.ist.i.kyoto-u.ac.jp/~ichinose/hegma/ Contact:ichinose@i.kyoto-u.ac.jp; o.gotoh@i.kyoto-u.ac.jp

Motivation: Motif discovery is now routinely used in high-throughput studies including large-scale sequencing and proteomics. These datasets present new challenges. The first is speed. Many motif discovery methods do not scale well to large datasets. Another issue is identifying discriminative rather than generative motifs. Such discriminative motifs are important for identifying co-factors and for explaining changes in behavior between different conditions. Results: To address these issues we developed a method for DECOnvolved Discriminative motif discovery (DECOD). DECOD uses a k-mer count table and so its running time is independent of the size of the input set. By deconvolving the k-mers DECOD considers context information without using the sequences directly. DECOD outperforms previous methods both in speed and in accuracy when using simulated and real biological benchmark data. We performed new binding experiments for p53 mutants and used DECOD to identify p53 co-factors, suggesting new mechanisms for p53 activation. Availability: The source code and binaries for DECOD are available at http://www.sb.cs.cmu.edu/DECOD Contact: zivbj@cs.cmu.edu Supplementary information: Supplementary data are available at Bioinformatics online.

Molecular profiling for varietal differentiation assumes an important role in the light of UPOV initiatives and PVP act. Inter simple sequence repeats (ISSR), a PCR based genetic marker system circumvents the requirement for flanking sequence information, and thus has found wide applicability in a variety of plants. The potential of ISSR markers for molecular profiling was assessed in sugarcane using a panel of 42 varieties of subtropical India. ISSR amplification was achieved using di-, tri-and tetraoligonucleotide repeats. All the nucleotide motifs were amenable to amplification. The ISSR results suggested that the frequency and clustering of specific simple sequence repeats was variable and motif-specific, however, there was not much difference in the di-, tri-or tetra-nucleotide ISSR profiles. The ISSR amplification pattern was used to assess genetic similarity of these sugarcane genotypes by Dice similarity coefficients, which ranged from 0.68 to 0.97 with a mean similarity value of 0.878. The ISSR amplification proved to be a valuable method for determining genetic variability among sugarcane varieties and for identification of the cultivars.

Palindromic consensus nucleotide sequences are found at the genomic integration sites of retroviruses and other transposable elements. It has been suggested that the palindromic consensus arises as a consequence of structural symmetry in the integrase complex, but the precise mechanism has yet to be elucidated. Here we perform a statistical analysis of large datasets of HTLV-1 and HIV-1 integration sites. The results show that the palindromic consensus sequence is not present in individual integration sites, but appears to arise in the population average as a consequence of the existence of a non-palindromic nucleotide motif that occurs in approximately equal proportions on the plus-strand and the minus-strand of the host genome. We demonstrate that palindromic probability position matrices are characteristic of such situations. We develop a generally applicable algorithm to sort the individual integration site sequences into plus-strand and minus-strand subpopulations. We apply this algorithm to identify the respective integration site nucleotide motifs of five retroviruses of different genera: HTLV-1, HIV-1, MLV, ASLV, and PFV}. The results reveal a non-palindromic motif that is shared between these retroviruses.

There is an increasing demand for identifying the functional sites of noncoding RNAs (ncRNAs). Here we introduce a tertiary-structure based computational approach, Rsite, which first calculates the Euclidean distances between each nucleotide and all the other nucleotides in a RNA molecule and then determines the nucleotides that are the extreme points in the distance curve as the functional sites. By analyzing two ncRNAs, tRNA (Lys) and Diels-Alder ribozyme, we demonstrated the efficiency of Rsite. As a result, Rsite recognized all of the known functional sites of the two ncRNAs, suggesting that Rsite could be a potentially useful tool for discovering the functional sites of ncRNAs. The source codes and data sets of Rsite are available at http://www.cuilab.cn/rsite.

Massively parallel resequencing of mitochondrial DNA (mtDNA) has led to significant advances in the study of heteroplasmic mtDNA variants in health and disease, but confident resolution of very low-level variants ( C, from patient with MNGIE, mitochondrial neurogastrointestinal encephalomyopathy) and comparing mutational pattern distribution with healthy mtDNA by ligation-mediated deep resequencing (Applied Biosystems SOLiD). We empirically derived mtDNA-mutant heteroplasmy detection limits, demonstrating that the presence of stereotypical mutational motif could be statistically validated for heteroplasmy thresholds ≥ 0.22% (P = 0.034). We therefore provide empirical evidence from biological samples that very low-level mtDNA mutants can be meaningfully resolved by massively parallel resequencing, confirming the utility of the approach for studying somatic mtDNA mutation in health and disease. Our approach could also usefully be employed in other settings to derive platform-specific deep resequencing resolution limits.

Recent modifications and improvements to standard nucleic acid force fields have attempted to fix problems and issues that have been observed as longer timescale simulations have become routine. Although previous work has shown the ability to fold the UUCG stem–loop structure, until now no group has attempted to quantify the performance of current force fields using highly converged structural populations of the tetraloop conformational ensemble. In this study, we report the use of multiple independent sets of multidimensional replica exchange molecular dynamics (M-REMD) simulations with different initial conditions to generate well-converged conformational ensembles for the tetranucleotides r(GACC) and r(CCCC), as well as the larger UUCG tetraloop motif. By generating what is to our knowledge the most complete RNA structure ensembles reported to date for these systems, we remove the coupling between force field errors and errors due to incomplete sampling, providing a comprehensive comparison between current top-performing MD force fields for RNA. Of the RNA force fields tested in this study, none demonstrate the ability to correctly identify the most thermodynamically stable structure for all three systems. We discuss the deficiencies present in each potential function and suggest areas where improvements can be made. The results imply that although “short” (nsec-μsec timescale) simulations may stay close to their respective experimental structures and may well reproduce experimental observables, inevitably the current force fields will populate alternative incorrect structures that are more stable than those observed via experiment.

HRAS is regulated by two neighbouring quadruplex-forming GC-elements (hras-1 and hras-2), located upstream of the major transcription start sites (doi: 10.1093/nar/gku 5784). In this study we demonstrate that the C-rich strands of hras-1 and hras-2 fold into i-motif conformations (iMs) characterized under crowding conditions (PEG-300, 40% w/v) by semi-transitions at pH 6.3 and 6.7, respectively. Nondenaturing PAGE shows that the HRAS C-rich sequences migrate at both pH 5 and 7 as folded intramolecular structures. Chromatin immunoprecipitation shows that hnRNP A1 is associated under in vivo conditions to the GC-elements, while EMSA proves that hnRNP A1 binds tightly to the iMs. FRET and CD show that hnRNP A1 unfolds the iM structures upon binding. Furthermore, when hnRNP A1 is knocked out in T24 bladder cancer cells by a specific shRNA, the HRAS transcript level drops to 44 ± 5% of the control, suggesting that hnRNP A1 is necessary for gene activation. The sequestration by decoy oligonucleotides of the proteins (hnRNP A1 and others) binding to the HRAS iMs causes a significant inhibition of HRAS transcription. All these outcomes suggest that HRAS is regulated by a G-quadruplex/i-motif switch interacting with proteins that recognize non B-DNA conformations.

RNA sequence motifs are not sufficient for association with RBPs. In this issue of Molecular Cell, Taliaferro et al. (2016) demonstrate that, other than sequence motif, RNA secondary structure plays a repressive role on RBP binding, both in vitro and in vivo.

The versatility of RNA is achieved in part through its ability to adopt various shapes of structures. A new technology called X-ray scattering interferometry enables the detection of 'invisible' states by lighting up gold pairs tagged to RNA molecules.

Motivation: Identifying regulatory elements is a fundamental problem in the field of gene transcription. Motif discovery—the task of identifying the sequence preference of transcription factor proteins, which bind to these elements—is an important step in this challenge. MEME is a popular motif discovery algorithm. Unfortunately, MEME’s running time scales poorly with the size of the dataset. Experiments such as ChIP-Seq and DNase-Seq are providing a rich amount of information on the binding preference of transcription factors. MEME cannot discover motifs in data from these experiments in a practical amount of time without a compromising strategy such as discarding a majority of the sequences. Results: We present EXTREME, a motif discovery algorithm designed to find DNA-binding motifs in ChIP-Seq and DNase-Seq data. Unlike MEME, which uses the expectation-maximization algorithm for motif discovery, EXTREME uses the online expectation-maximization algorithm to discover motifs. EXTREME can discover motifs in large datasets in a practical amount of time without discarding any sequences. Using EXTREME on ChIP-Seq and DNase-Seq data, we discover many motifs, including some novel and infrequent motifs that can only be discovered by using the entire dataset. Conservation analysis of one of these novel infrequent motifs confirms that it is evolutionarily conserved and possibly functional. Availability and implementation: All source code is available at the Github repository http://github.com/uci-cbcl/EXTREME. Contact: xhx@ics.uci.edu Supplementary information: Supplementary data are available at Bioinformatics online.

Cys(2)-His(2) zinc finger proteins (ZFPs) are the largest family of transcription factors in higher metazoans. They also represent the most diverse family with regards to the composition of their recognition sequences. Although there are a number of ZFPs with characterized DNA-binding preferences, the specificity of the vast majority of ZFPs is unknown and cannot be directly inferred by homology due to the diversity of recognition residues present within individual fingers. Given the large number of unique zinc fingers and assemblies present across eukaryotes, a comprehensive predictive recognition model that could accurately estimate the DNA-binding specificity of any ZFP based on its amino acid sequence would have great utility. Toward this goal, we have used the DNA-binding specificities of 678 two-finger modules from both natural and artificial sources to construct a random forest-based predictive model for ZFP recognition. We find that our recognition model outperforms previously described determinant-based recognition models for ZFPs, and can successfully estimate the specificity of naturally occurring ZFPs with previously defined specificities.

International audience; The clinical importance of tumor suppressor p53 makes it one of the most studied transcription factors. A comparison of mammalian p53 transcriptional repertoires may help identify fundamental principles in genome evolution and better understand cancer processes. Here we summarize mechanisms underlying the divergence of mammalian p53 transcriptional repertoires, with an emphasis on the rapid evolution of fuzzy tandem repeats containing p53 response elements.

De novo discovery of "motifs" capturing the commonalities among related noncoding ncRNA structured RNAs is among the most difficult problems in computational biology. This chapter outlines the challenges presented by this problem, together with some approaches towards solving them, with an emphasis on an approach based on the CMfinder CMfinder program as a case study. Applications to genomic screens for novel de novo structured ncRNA ncRNA s, including structured RNA elements in untranslated portions of protein-coding genes, are presented.

The Nucleic Acid Database (NDB) (http://ndbserver.rutgers.edu) is a web portal providing access to information about 3D nucleic acid structures and their complexes. In addition to primary data, the NDB contains derived geometric data, classifications of structures and motifs, standards for describing nucleic acid features, as well as tools and software for the analysis of nucleic acids. A variety of search capabilities are available, as are many different types of reports. This article describes the recent redesign of the NDB Web site with special emphasis on new RNA-derived data and annotations and their implementation and integration into the search capabilities.

Summary: Genome-wide expression analysis can result in large numbers of clusters of co-expressed genes. Although there are tools for ab initio discovery of transcription factor-binding sites, most do not provide a quick and easy way to study large numbers of clusters. To address this, we introduce a web tool called MEME-LaB. The tool wraps MEME (an ab initio motif finder), providing an interface for users to input multiple gene clusters, retrieve promoter sequences, run motif finding and then easily browse and condense the results, facilitating better interpretation of the results from large-scale datasets. Availability: MEME-LaB is freely accessible at: http://wsbc.warwick.ac.uk/wsbcToolsWebpage/. Contact: ku.ca.kciwraw@nworb.e.p Supplementary information: Supplementary data are available at Bioinformatics online.

Scientists routinely scan DNA sequences for transcription factor (TF) bindingsites (TFBSs). Most of the available tools rely on position-specific scoringmatrices (PSSMs) constructed from aligned binding sites. Because of theresolutions of assays used to obtain TFBSs, databases such as TRANSFAC,ORegAnno and PAZAR store unaligned variable-length DNA segments containingbinding sites of a TF. These DNA segments need to be aligned to build aPSSM. While the TRANSFAC database provides scoring matrices for TFs, nearly78% of the TFs in the public release do not have matrices available. As workon TFBS alignment algorithms has been limited, it is highly desirable tohave an alignment algorithm tailored to TFBSs. We designed a novel algorithm named LASAGNA, which is aware of the lengths ofinput TFBSs and utilizes position dependence. Results on 189 TFs of 5species in the TRANSFAC database showed that our method significantlyoutperformed ClustalW2 and MEME. We further compared a PSSM method dependenton LASAGNA to an alignment-free TFBS search method. Results on 89 TFs whosebinding sites can be located in genomes showed that our method issignificantly more precise at fixed recall rates. Finally, we describedLASAGNA-ChIP, a more sophisticated version for ChIP (Chromatinimmunoprecipitation) experiments. Under the one-per-sequence model, itshowed comparable performance with MEME in discovering motifs in ChIP-seqpeak sequences. We conclude that the LASAGNA algorithm is simple and effective in aligningvariable-length binding sites. It has been integrated into a user-friendlywebtool for TFBS search and visualization called LASAGNA-Search. The toolcurrently stores precomputed PSSM models for 189 TFs and 133 TFs built fromTFBSs in the TRANSFAC Public database (release 7.0) and the ORegAnnodatabase (08Nov10 dump), respectively. The webtool is available at http://biogrid.engr.uconn.edu/lasagna_search/ .

International audience; The symmetry of i-motif tetramers gives to cytidine-rich oligonucleotides the capacity to associate into supramolecular structures (sms). In order to determine how the tetramers are linked together in such structures, we have measured by gel filtration chromatography and NMR the formation and dissociation kinetics of sms built by oligonucleotides containing two short C stretches separated by a non-cytidine-base. We show that a stretch of only two cytidines either at the 3'- or 5'-end is long enough to link the tetramers into sms. The analysis of the properties of sms formed by oligonucleotides differing by the length of the oligo-C stretches, the sequence orientation and the nature of the non-C base provides a model of the junction connecting the tetramers in sms.

The Pr promoter is the first verified member of a class of bacterial σ(70)-promoters that only possess a single match to consensus within its -10 element. In its native context, the activity of this promoter determines the ability of Pseudomonas putida CF600 to degrade phenolic compounds, which provides proof-of-principle for the significance of such promoters. Lack of identity within the -10 element leads to non-detection of Pr-like promoters by current search engines, because of their bias for detection of the -10 motif. Here, we report a mutagenesis analysis of Pr that reveals strict sequence requirements for its activity that includes an essential -15 element and preservation of non-consensus bases within its -35 and -10 elements. We found that highly similar promoters control plasmid- and chromosomally- encoded phenol degradative systems in various Pseudomonads. However, using a purpose-designed promoter-search algorithm and activity analysis of potential candidate promoters, no bona fide Pr-like promoter could be found in the entire genome of P. putida KT2440. Hence, Pr-like σ(70)-promoters, which have the potential to be a widely distributed class of previously unrecognized promoters, are in fact highly restricted and remain in a class of their own.

Base triples are recurrent clusters of three RNA nucleobases interacting edge-to-edge by hydrogen bonding. We find that the central base in almost all triples forms base pairs with the other two bases of the triple, providing a natural way to geometrically classify base triples. Given 12 geometric base pair families defined by the Leontis-Westhof nomenclature, combinatoric enumeration predicts 108 potential geometric base triple families. We searched representative atomic-resolution RNA 3D structures and found instances of 68 of the 108 predicted base triple families. Model building suggests that some of the remaining 40 families may be unlikely to form for steric reasons. We developed an on-line resource that provides exemplars of all base triples observed in the structure database and models for unobserved, predicted triples, grouped by triple family, as well as by three-base combination (http://rna.bgsu.edu/Triples). The classification helps to identify recurrent triple motifs that can substitute for each other while conserving RNA 3D structure, with applications in RNA 3D structure prediction and analysis of RNA sequence evolution.