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NAR Top Articles - Computational Biology

Computational Biology

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October 2015

Predicting enhancer transcription and activity from chromatin modifications
Zhu, Y; Sun, L; Chen, Z; Whitaker, JW; Wang, T; Wang, W
Nucleic Acids Res. 2013, 41, 10032-10043
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Enhancers play a pivotal role in regulating the transcription of distal genes. Although certain chromatin features, such as the histone acetyltransferase P300 and the histone modification H3K4me1, indicate the presence of enhancers, only a fraction of enhancers are functionally active. Individual chromatin marks, such as H3K27ac and H3K27me3, have been identified to distinguish active from inactive enhancers. However, the systematic identification of the most informative single modification, or combination thereof, is still lacking. Furthermore, the discovery of enhancer RNAs (eRNAs) provides an alternative approach to directly predicting enhancer activity. However, it remains challenging to link chromatin modifications to eRNA transcription. Herein, we develop a logistic regression model to unravel the relationship between chromatin modifications and eRNA synthesis. We perform a systematic assessment of 24 chromatin modifications in fetal lung fibroblast and demonstrate that a combination of four modifications is sufficient to accurately predict eRNA transcription. Furthermore, we compare the ability of eRNAs and H3K27ac to discriminate enhancer activity...

miRDeep*: an integrated application tool for miRNA identification from RNA sequencing data
An, JY; Lai, J; Lehman, ML; Nelson, CC
Nucleic Acids Res. 2013, 41, 727-737
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miRDeep and its varieties are widely used to quantify known and novel micro RNA (miRNA) from small RNA sequencing (RNAseq). This article describes miRDeep*, our integrated miRNA identification tool, which is modeled off miRDeep, but the precision of detecting novel miRNAs is improved by introducing new strategies to identify precursor miRNAs. miRDeep* has a user-friendly graphic interface and accepts raw data in FastQ and Sequence Alignment Map (SAM) or the binary equivalent (BAM) format. Known and novel miRNA expression levels, as measured by the number of reads, are displayed in an interface, which shows each RNAseq read relative to the pre-miRNA hairpin. The secondary pre-miRNA structure and read locations for each predicted miRNA are shown and kept in a separate figure file. Moreover, the target genes of known and novel miRNAs are predicted using the TargetScan algorithm, and the targets are ranked according to the confidence score. miRDeep* is an integrated standalone application where sequence alignment, pre-miRNA secondary structure calculation and graphical display are purely Java coded. This application tool can be executed using a normal personal computer with 1.5 GB of memory...

Interplay of microRNAs, transcription factors and target genes: linking dynamic expression changes to function
Nazarov, PV; Reinsbach, SE; Muller, A; Nicot, N; Philippidou, D; Vallar, L; Kreis, S
Nucleic Acids Res. 2013, 41, 2817-2831
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MicroRNAs (miRNAs) are ubiquitously expressed small non-coding RNAs that, in most cases, negatively regulate gene expression at the post-transcriptional level. miRNAs are involved in fine-tuning fundamental cellular processes such as proliferation, cell death and cell cycle control and are believed to confer robustness to biological responses. Here, we investigated simultaneously the transcriptional changes of miRNA and mRNA expression levels over time after activation of the Janus kinase/Signal transducer and activator of transcription (Jak/STAT) pathway by interferon-gamma stimulation of melanoma cells. To examine global miRNA and mRNA expression patterns, time-series microarray data were analysed. We observed delayed responses of miRNAs (after 24-48 h) with respect to mRNAs (12-24 h) and identified biological functions involved at each step of the cellular response. Inference of the upstream regulators allowed for identification of transcriptional regulators involved in cellular reactions to interferon-gamma stimulation...

DNA hybridization kinetics: zippering, internal displacement and sequence dependence
Ouldridge, TE; Sulc, P; Romano, F; Doye, JPK; Louis, AA
Nucleic Acids Res. 2013, 41, 8886-8895
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Although the thermodynamics of DNA hybridization is generally well established, the kinetics of this classic transition is less well understood. Providing such understanding has new urgency because DNA nanotechnology often depends critically on binding rates. Here, we explore DNA oligomer hybridization kinetics using a coarse-grained model. Strand association proceeds through a complex set of intermediate states, with successful binding events initiated by a few metastable base-pairing interactions, followed by zippering of the remaining bonds. But despite reasonably strong interstrand interactions, initial contacts frequently dissociate because typical configurations in which they form differ from typical states of similar enthalpy in the double-stranded equilibrium ensemble. Initial contacts must be stabilized by two or three base pairs before full zippering is likely, resulting in negative effective activation enthalpies. Non-Arrhenius behavior arises because the number of base pairs required for nucleation increases with temperature. In addition, we observe two alternative pathways-pseudoknot and inchworm internal displacement-through which misaligned duplexes can rearrange to form duplexes.

The elusive evidence for chromothripsis
Kinsella, M; Patel, A; Bafna, V
Nucleic Acids Res. 2014, 42, 8231-8242
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The chromothripsis hypothesis suggests an extraordinary one-step catastrophic genomic event allowing a chromosome to 'shatter into many pieces' and reassemble into a functioning chromosome. Recent efforts have aimed to detect chromothripsis by looking for a genomic signature, characterized by a large number of breakpoints (50-250), but a limited number of oscillating copy number states (2-3) confined to a few chromosomes. The chromothripsis phenomenon has become widely reported in different cancers, but using inconsistent and sometimes relaxed criteria for determining rearrangements occur simultaneously rather than progressively. We revisit the original simulation approach and show that the signature is not clearly exceptional, and can be explained using only progressive rearrangements. For example, 3.9% of progressively simulated chromosomes with 50-55 breakpoints were dominated by two or three copy number states. In addition, by adjusting the parameters of the simulation, the proposed footprint appears more frequently. Lastly, we provide an algorithm to find a sequence of progressive rearrangements that explains all observed breakpoints from a proposed chromothripsis chromosome...

Molecular evolutionary and structural analysis of the cytosolic DNA sensor cGAS and STING
Wu, XM; Wu, FH; Wang, XQ; Wang, LL; Siedow, JN; Zhang, WG; Pei, ZM
Nucleic Acids Res. 2014, 42, 8243-8257
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Cyclic GMP-AMP (cGAMP) synthase (cGAS) is recently identified as a cytosolic DNA sensor and generates a non-canonical cGAMP that contains G(2',5')pA and A(3',5')pG phosphodiester linkages. cGAMP activates STING which triggers innate immune responses in mammals. However, the evolutionary functions and origins of cGAS and STING remain largely elusive. Here, we carried out comprehensive evolutionary analyses of the cGAS-STING pathway. Phylogenetic analysis of cGAS and STING families showed that their origins could be traced back to a choanoflagellate Monosiga brevicollis. Modern cGAS and STING may have acquired structural features, including zinc-ribbon domain and critical amino acid residues for DNA binding in cGAS as well as carboxy terminal tail domain for transducing signals in STING, only recently in vertebrates. In invertebrates, cGAS homologs may not act as DNA sensors. Both proteins cooperate extensively, have similar evolutionary characteristics, and thus may have co-evolved during metazoan evolution. cGAS homologs and a prokaryotic dinucleotide cyclase for canonical cGAMP share conserved secondary structures and catalytic residues...

Enriching the gene set analysis of genome-wide data by incorporating directionality of gene expression and combining statistical hypotheses and methods
Varemo, L; Nielsen, J; Nookaew, I
Nucleic Acids Res. 2013, 41, 4378-4391
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Gene set analysis (GSA) is used to elucidate genome-wide data, in particular transcriptome data. A multitude of methods have been proposed for this step of the analysis, and many of them have been compared and evaluated. Unfortunately, there is no consolidated opinion regarding what methods should be preferred, and the variety of available GSA software and implementations pose a difficulty for the end-user who wants to try out different methods. To address this, we have developed the R package Piano that collects a range of GSA methods into the same system, for the benefit of the end-user. Further on we refine the GSA workflow by using modifications of the gene-level statistics. This enables us to divide the resulting gene set P-values into three classes, describing different aspects of gene expression directionality at gene set level. We use our fully implemented workflow to investigate the impact of the individual components of GSA by using microarray and RNA-seq data. The results show that the evaluated methods are globally similar and the major separation correlates well with our defined directionality classes...

Surprisingly extensive mixed phylogenetic and ecological signals among bacterial Operational Taxonomic Units
Koeppel, AF; Wu, M
Nucleic Acids Res. 2013, 41, 5175-5188
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The lack of a consensus bacterial species concept greatly hampers our ability to understand and organize bacterial diversity. Operational taxonomic units (OTUs), which are clustered on the basis of DNA sequence identity alone, are the most commonly used microbial diversity unit. Although it is understood that OTUs can be phylogenetically incoherent, the degree and the extent of the phylogenetic inconsistency have not been explicitly studied. Here, we tested the phylogenetic signal of OTUs in a broad range of bacterial genera from various phyla. Strikingly, we found that very few OTUs were monophyletic, and many showed evidence of multiple independent origins. Using previously established bacterial habitats as benchmarks, we showed that OTUs frequently spanned multiple ecological habitats. We demonstrated that ecological heterogeneity within OTUs is caused by their phylogenetic inconsistency, and not merely due to 'lumping' of taxa resulting from using relaxed identity cut-offs. We argue that ecotypes, as described by the Stable Ecotype Model, are phylogenetically and ecologically more consistent than OTUs and therefore could serve as an alternative unit for bacterial diversity studies...

Accurate detection of differential RNA processing
Drewe, P; Stegle, O; Hartmann, L; Kahles, A; Bohnert, R; Wachter, A; Borgwardt, K; Ratsch, G
Nucleic Acids Res. 2013, 41, 5189-5198
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Deep transcriptome sequencing (RNA-Seq) has become a vital tool for studying the state of cells in the context of varying environments, genotypes and other factors. RNA-Seq profiling data enable identification of novel isoforms, quantification of known isoforms and detection of changes in transcriptional or RNA-processing activity. Existing approaches to detect differential isoform abundance between samples either require a complete isoform annotation or fall short in providing statistically robust and calibrated significance estimates. Here, we propose a suite of statistical tests to address these open needs: a parametric test that uses known isoform annotations to detect changes in relative isoform abundance and a non-parametric test that detects differential read coverages and can be applied when isoform annotations are not available. Both methods account for the discrete nature of read counts and the inherent biological variability. We demonstrate that these tests compare favorably to previous methods, both in terms of accuracy and statistical calibrations. We use these techniques to analyze RNA-Seq libraries from Arabidopsis thaliana and Drosophila melanogaster...

A modular framework for gene set analysis integrating multilevel omics data
Sass, S; Buettner, F; Mueller, NS; Theis, FJ
Nucleic Acids Res. 2013, 41, 9622-9633
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Modern high-throughput methods allow the investigation of biological functions across multiple 'omics' levels. Levels include mRNA and protein expression profiling as well as additional knowledge on, for example, DNA methylation and microRNA regulation. The reason for this interest in multi-omics is that actual cellular responses to different conditions are best explained mechanistically when taking all omics levels into account. To map gene products to their biological functions, public ontologies like Gene Ontology are commonly used. Many methods have been developed to identify terms in an ontology, overrepresented within a set of genes. However, these methods are not able to appropriately deal with any combination of several data types. Here, we propose a new method to analyse integrated data across multiple omics-levels to simultaneously assess their biological meaning. We developed a model-based Bayesian method for inferring interpretable term probabilities in a modular framework. Our Multi-level ONtology Analysis (MONA) algorithm performed significantly better than conventional analyses of individual levels and yields best results even for sophisticated models including mRNA fine-tuning by microRNAs...

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