NAR Top Articles - Computational Biology
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...
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...
What makes the lac-pathway switch: identifying the fluctuations that trigger phenotype switching in gene regulatory systems
Bhogale, PM; Sorg, RA; Veening, JW; Berg, J
Nucleic Acids Res. 2014, 42, 11321-11328
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Multistable gene regulatory systems sustain different levels of gene expression under identical external conditions. Such multistability is used to encode phenotypic states in processes including nutrient uptake and persistence in bacteria, fate selection in viral infection, cell-cycle control and development. Stochastic switching between different phenotypes can occur as the result of random fluctuations in molecular copy numbers of mRNA and proteins arising in transcription, translation, transport and binding. However, which component of a pathway triggers such a transition is generally not known. By linking single-cell experiments on the lactose-uptake pathway in E. coli to molecular simulations, we devise a general method to pinpoint the particular fluctuation driving phenotype switching and apply this method to the transition between the uninduced and induced states of the lac-genes. We find that the transition to the induced state is not caused only by the single event of lac-repressor unbinding, but depends crucially on the time period over which the repressor remains unbound from the lac-operon...
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...
A high-resolution network model for global gene regulation in Mycobacterium tuberculosis
Peterson, EJR; Reiss, DJ; Turkarslan, S; Minch, KJ; Rustad, T; Plaisier, CL; Longabaugh, WJR; Sherman, DR; Baliga, NS
Nucleic Acids Res. 2014, 42, 11291-11303
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The resilience of Mycobacterium tuberculosis (MTB) is largely due to its ability to effectively counteract and even take advantage of the hostile environments of a host. In order to accelerate the discovery and characterization of these adaptive mechanisms, we have mined a compendium of 2325 publicly available transcriptome profiles of MTB to decipher a predictive, systems-scale gene regulatory network model. The resulting modular organization of 98% of all MTB genes within this regulatory network was rigorously tested using two independently generated datasets: a genome-wide map of 7248 DNA-binding locations for 143 transcription factors (TFs) and global transcriptional consequences of over-expressing 206 TFs. This analysis has discovered specific TFs that mediate conditional co-regulation of genes within 240 modules across 14 distinct environmental contexts. In addition to recapitulating previously characterized regulons, we discovered 454 novel mechanisms for gene regulation during stress, cholesterol utilization and dormancy...
Profiling the transcription factor regulatory networks of human cell types
Zhang, SH; Tian, DC; Tran, NH; Choi, KP; Zhang, LX
Nucleic Acids Res. 2014, 42, 12380-12387
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Neph et al. (2012) (Circuitry and dynamics of human transcription factor regulatory networks. Cell, 150: 1274-1286) reported the transcription factor (TF) regulatory networks of 41 human cell types using the DNaseI footprinting technique. This provides a valuable resource for uncovering regulation principles in different human cells. In this paper, the architectures of the 41 regulatory networks and the distributions of housekeeping and specific regulatory interactions are investigated. The TF regulatory networks of different human cell types demonstrate similar global three-layer (top, core and bottom) hierarchical architectures, which are greatly different from the yeast TF regulatory network. However, they have distinguishable local organizations, as suggested by the fact that wiring patterns of only a few TFs are enough to distinguish cell identities. The TF regulatory network of human embryonic stem cells (hESCs) is dense and enriched with interactions that are unseen in the networks of other cell types. The examination of specific regulatory interactions suggests that specific interactions play important roles in hESCs.
Predicting DNA methylation level across human tissues
Ma, BS; Wilker, EH; Willis-Owen, SAG; Byun, HM; Wong, KCC; Motta, V; Baccarelli, AA; Schwartz, J; Cookson, WOCM; Khabbaz, K; Mittleman, MA; Moffatt, MF; Liang, LM
Nucleic Acids Res. 2014, 42, 3515-3528
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Differences in methylation across tissues are critical to cell differentiation and are key to understanding the role of epigenetics in complex diseases. In this investigation, we found that locus-specific methylation differences between tissues are highly consistent across individuals. We developed a novel statistical model to predict locus-specific methylation in target tissue based on methylation in surrogate tissue. The method was evaluated in publicly available data and in two studies using the latest IlluminaBeadChips: a childhood asthma study with methylation measured in both peripheral blood leukocytes (PBL) and lymphoblastoid cell lines; and a study of postoperative atrial fibrillation with methylation in PBL, atrium and artery. We found that our method can greatly improve accuracy of cross-tissue prediction at CpG sites that are variable in the target tissue...
Modeling epigenome folding: formation and dynamics of topologically associated chromatin domains
Jost, D; Carrivain, P; Cavalli, G; Vaillant, C
Nucleic Acids Res. 2014, 42, 9553-9561
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Genomes of eukaryotes are partitioned into domains of functionally distinct chromatin states. These domains are stably inherited across many cell generations and can be remodeled in response to developmental and external cues, hence contributing to the robustness and plasticity of expression patterns and cell phenotypes. Remarkably, recent studies indicate that these 1D epigenomic domains tend to fold into 3D topologically associated domains forming specialized nuclear chromatin compartments. However, the general mechanisms behind such compartmentalization including the contribution of epigenetic regulation remain unclear. Here, we address the question of the coupling between chromatin folding and epigenome. Using polymer physics, we analyze the properties of a block copolymer model that accounts for local epigenomic information. Considering copolymers build from the epigenomic landscape of Drosophila, we observe a very good agreement with the folding patterns observed in chromosome conformation capture experiments. Moreover, this model provides a physical basis for the existence of multistability in epigenome folding at sub-chromosomal scale...
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...
Cooperative gene regulation by microRNA pairs and their identification using a computational workflow
Schmitz, U; Lai, X; Winter, F; Wolkenhauer, O; Vera, J; Gupta, SK
Nucleic Acids Res. 2014, 42, 7539-7552
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MicroRNAs (miRNAs) are an integral part of gene regulation at the post-transcriptional level. Recently, it has been shown that pairs of miRNAs can repress the translation of a target mRNA in a cooperative manner, which leads to an enhanced effectiveness and specificity in target repression. However, it remains unclear which miRNA pairs can synergize and which genes are target of cooperative miRNA regulation. In this paper, we present a computational workflow for the prediction and analysis of cooperating miRNAs and their mutual target genes, which we refer to as RNA triplexes. The workflow integrates methods of miRNA target prediction; triplex structure analysis; molecular dynamics simulations and mathematical modeling for a reliable prediction of functional RNA triplexes and target repression efficiency. In a case study we analyzed the human genome and identified several thousand targets of cooperative gene regulation. Our results suggest that miRNA cooperativity is a frequent mechanism for an enhanced target repression by pairs of miRNAs facilitating distinctive and fine-tuned target gene expression patterns...
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