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Search Results: 1 - 10 of 202968 matches for " Eric D. Siggia "
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Sequence context affects the rate of short insertions and deletions in flies and primates
Amos Tanay, Eric D Siggia
Genome Biology , 2008, DOI: 10.1186/gb-2008-9-2-r37
Abstract: Here we analyze a large collection of high confidence short insertions and deletions in primates and flies, revealing extensive correlations between sequence context and indel rates and building principled models for predicting these rates from sequence. According to our results, the rate of insertion or deletion of specific lengths can vary by more than 100-fold, depending on the surrounding sequence. These mutational biases can strongly influence the composition of the genome and the rate at which particular sequences appear. We exemplify this by showing how degenerate loci in human exons are selected to reduce their frame shifting indel propensity.Insertions and deletions are strongly affected by sequence context. Consequentially, genomes must adapt to significant variation in the mutational input at indel-prone and indel-immune loci.The evolution of genomes is driven by an influx of mutations that are subject to a stochastic process of neutral fixation and to multiple selective pressures that can change the neutral fixation dynamics. Good understanding of the evolutionary process requires characterization of both the mutational and fixation processes. This is particularly important in applications that try to reveal genomic loci that are evolving under selection by looking for slowly or rapidly evolving sequences. In such studies one has to make sure the mutational input at the genomic regions under study is not abnormally high or low [1-4], or else the inferred selection may be an artifact of the mutational dynamics and not a true indication for a functional constraint on the sequence. Changes are introduced into genomes through point mutations, insertions and deletions. The dynamics of each of these mechanisms may vary according to genomic context and the presence of various factors acting in trans.Before the availability of numerous fully sequenced genomes, evolutionary studies focused on two extremes: replacements of entire genes and chromosome domains or po
Conservation of regulatory elements between two species of Drosophila
Eldon Emberly, Nikolaus Rajewsky, Eric D Siggia
BMC Bioinformatics , 2003, DOI: 10.1186/1471-2105-4-57
Abstract: We find that 50%–70% of known binding sites reside in conserved sequence blocks, but these percentages are not greatly enriched over what is expected by chance. Finally, a computational genome-wide search in both species for regulatory modules based on clusters of binding sites suggests that genes central to the regulatory network are consistently recovered.Our results indicate that binding sites remain clustered for these "core modules" while not necessarily residing in conserved blocks. This is an important clue as to how regulatory information is encoded in the genome and how modules evolve.Changes in the body plans of metazoans are thought to be largely a consequence of changes in the spatiotemporal pattern of the expression of developmental genes and thus a consequence of changes in their transcriptional regulation ([1,2] and references therein). Hence, genomic cis-regulatory sequences that control developmental gene expression can be thought of as the genomic "source code" for development [3]. Multiple transcription factors recognize and bind regulatory sites in these genomic regulatory sequences ("modules") and together define the rate of transcription of the target gene. This combinatorial mode of gene regulation is thought to be prevalent in all multicellular organisms. Modules are often separable and define space and time specific aspects of gene expression. They integrate inputs from several genes and regulate another gene to form regulatory networks. Modules are typically a few hundred nucleotides long and receive multiple inputs from roughly 4–5 different transcription factors. Recently, it has been demonstrated in D. melanogaster that modules may be identified by searching the genome for regions which are dense in binding sites [4-8]. These computational methods are important practically, since the experimental detection of modules is very time consuming. Computational techniques applied to whole genomes may also prove informative about how modules evo
Genome wide identification of regulatory motifs in Bacillus subtilis
Michael M Mwangi, Eric D Siggia
BMC Bioinformatics , 2003, DOI: 10.1186/1471-2105-4-18
Abstract: To identify motifs involved in the control of transcription, an algorithm was developed that searches upstream of operons for improbably frequent dimers. The algorithm was applied to the B. subtilis genome, which is predicted to encode for approximately 200 DNA binding proteins. The dimers found to be over-represented could be clustered into 317 distinct groups, each thought to represent a class of motifs uniquely recognized by some transcription factor. For each cluster of dimers, a representative weight matrix was derived and scored over the regions upstream of the operons to predict the sites recognized by the cluster's factor, and a putative regulon of the operons immediately downstream of the sites was inferred. The distribution in number of operons per predicted regulon is comparable to that for well characterized transcription factors. The most highly over-represented dimers matched σA, the T-box, and σW sites. We have evidence to suggest that at least 52 of our clusters of dimers represent actual regulatory motifs, based on the groups' weight matrix matches to experimentally characterized sites, the functional similarity of the component operons of the groups' regulons, and the positional biases of the weight matrix matches. All predictions are assigned a significance value, and thresholds are set to avoid false positives. Where possible, we examine our false negatives, drawing examples from known regulatory motifs and regulons inferred from RNA expression data.We have demonstrated that in the case of B. subtilis our algorithm allows for the genome wide identification of regulatory sites. As well as recovering known sites, we predict new sites of yet uncharacterized factors. Results can be viewed at http://www.physics.rockefeller.edu/~mwangi/ webcite.Bacterial genome annotation has generally been confined to the prediction of sequences encoding proteins and prominent families of RNA genes. The predicted ORF's are grouped into categories by comparing them (e.
Symmetry and Scaling of Turbulent Mixing
Boris I Shraiman,Eric D Siggia
Physics , 1996, DOI: 10.1103/PhysRevLett.77.2463
Abstract: The stationary condition (Hopf equation) for the ($n$+1) point correlation function of a passive scalar advected by turbulent flow is argued to have an approximate $SL(n, R)$ symmetry which provides a starting point for the perturbative treatment of less symmetric terms. The large scale anisotropy is found to be a relevant field, in contradiction with Kolmogorov phenomenology, but in agreement with the large scalar skewness observed in shear flows. Exponents are not universal, yet quantitative predictions for experiments to test the $SL(n, R)$ symmetry can be formulated in terms of the correlation functions.
Adaptive Temperature Compensation in Circadian Oscillations
Paul Fran?ois ,Nicolas Despierre,Eric D. Siggia
PLOS Computational Biology , 2012, DOI: 10.1371/journal.pcbi.1002585
Abstract: A temperature independent period and temperature entrainment are two defining features of circadian oscillators. A default model of distributed temperature compensation satisfies these basic facts yet is not easily reconciled with other properties of circadian clocks, such as many mutants with altered but temperature compensated periods. The default model also suggests that the shape of the circadian limit cycle and the associated phase response curves (PRC) will vary since the average concentrations of clock proteins change with temperature. We propose an alternative class of models where the twin properties of a fixed period and entrainment are structural and arise from an underlying adaptive system that buffers temperature changes. These models are distinguished by a PRC whose shape is temperature independent and orbits whose extrema are temperature independent. They are readily evolved by local, hill climbing, optimization of gene networks for a common quality measure of biological clocks, phase anticipation. Interestingly a standard realization of the Goodwin model for temperature compensation displays properties of adaptive rather than distributed temperature compensation.
PhyloGibbs: A Gibbs Sampling Motif Finder That Incorporates Phylogeny
Rahul Siddharthan,Eric D Siggia,Erik van Nimwegen
PLOS Computational Biology , 2005, DOI: 10.1371/journal.pcbi.0010067
Abstract: A central problem in the bioinformatics of gene regulation is to find the binding sites for regulatory proteins. One of the most promising approaches toward identifying these short and fuzzy sequence patterns is the comparative analysis of orthologous intergenic regions of related species. This analysis is complicated by various factors. First, one needs to take the phylogenetic relationship between the species into account in order to distinguish conservation that is due to the occurrence of functional sites from spurious conservation that is due to evolutionary proximity. Second, one has to deal with the complexities of multiple alignments of orthologous intergenic regions, and one has to consider the possibility that functional sites may occur outside of conserved segments. Here we present a new motif sampling algorithm, PhyloGibbs, that runs on arbitrary collections of multiple local sequence alignments of orthologous sequences. The algorithm searches over all ways in which an arbitrary number of binding sites for an arbitrary number of transcription factors (TFs) can be assigned to the multiple sequence alignments. These binding site configurations are scored by a Bayesian probabilistic model that treats aligned sequences by a model for the evolution of binding sites and “background” intergenic DNA. This model takes the phylogenetic relationship between the species in the alignment explicitly into account. The algorithm uses simulated annealing and Monte Carlo Markov-chain sampling to rigorously assign posterior probabilities to all the binding sites that it reports. In tests on synthetic data and real data from five Saccharomyces species our algorithm performs significantly better than four other motif-finding algorithms, including algorithms that also take phylogeny into account. Our results also show that, in contrast to the other algorithms, PhyloGibbs can make realistic estimates of the reliability of its predictions. Our tests suggest that, running on the five-species multiple alignment of a single gene's upstream region, PhyloGibbs on average recovers over 50% of all binding sites in S. cerevisiae at a specificity of about 50%, and 33% of all binding sites at a specificity of about 85%. We also tested PhyloGibbs on collections of multiple alignments of intergenic regions that were recently annotated, based on ChIP-on-chip data, to contain binding sites for the same TF. We compared PhyloGibbs's results with the previous analysis of these data using six other motif-finding algorithms. For 16 of 21 TFs for which all other motif-finding methods
A Microfluidic Device for Temporally Controlled Gene Expression and Long-Term Fluorescent Imaging in Unperturbed Dividing Yeast Cells
Gilles Charvin, Frederick R. Cross, Eric D. Siggia
PLOS ONE , 2008, DOI: 10.1371/journal.pone.0001468
Abstract: Background Imaging single cells with fluorescent markers over multiple cell cycles is a powerful tool for unraveling the mechanism and dynamics of the cell cycle. Over the past ten years, microfluidic techniques in cell biology have emerged that allow for good control of growth environment. Yet the control and quantification of transient gene expression in unperturbed dividing cells has received less attention. Methodology/Principal Findings Here, we describe a microfluidic flow cell to grow Saccharomyces Cerevisiae for more than 8 generations (≈12 hrs) starting with single cells, with controlled flow of the growth medium. This setup provides two important features: first, cells are tightly confined and grow in a remarkably planar array. The pedigree can thus be determined and single-cell fluorescence measured with 3 minutes resolution for all cells, as a founder cell grows to a micro-colony of more than 200 cells. Second, we can trigger and calibrate rapid and transient gene expression using reversible administration of inducers that control the GAL1 or MET3 promoters. We then show that periodic 10–20 minutes gene induction pulses can drive many cell division cycles with complete coherence across the cell cluster, with either a G1/S trigger (cln1 cln2 cln3 MET3-CLN2) or a mitotic trigger (cdc20 GALL-CDC20). Conclusions/Significance In addition to evident cell cycle applications, this device can be used to directly measure the amount and duration of any fluorescently scorable signal-transduction or gene-induction response over a long time period. The system allows direct correlation of cell history (e.g., hysteresis or epigenetics) or cell cycle position with the measured response.
Origin of Irreversibility of Cell Cycle Start in Budding Yeast
Gilles Charvin,Catherine Oikonomou,Eric D. Siggia,Frederick R. Cross
PLOS Biology , 2012, DOI: 10.1371/journal.pbio.1000284
Abstract: Budding yeast cells irreversibly commit to a new division cycle at a regulatory transition called Start. This essential decision-making step involves the activation of the SBF/MBF transcription factors. SBF/MBF promote expression of the G1 cyclins encoded by CLN1 and CLN2. Cln1,2 can activate their own expression by inactivating the Whi5 repressor of SBF/MBF. The resulting transcriptional positive feedback provides an appealing, but as yet unproven, candidate for generating irreversibility of Start. Here, we investigate the logic of the Start regulatory module by quantitative single-cell time-lapse microscopy, using strains in which expression of key regulators is efficiently controlled by changes of inducers in a microfluidic chamber. We show that Start activation is ultrasensitive to G1 cyclin. In the absence of CLN1,2-dependent positive feedback, we observe that Start transit is reversible, due to reactivation of the Whi5 transcriptional repressor. Introduction of the positive feedback loop makes Whi5 inactivation and Start activation irreversible, which therefore guarantees unidirectional entry into S phase. A simple mathematical model to describe G1 cyclin turn on at Start, entirely constrained by empirically measured parameters, shows that the experimentally measured ultrasensitivity and transcriptional positive feedback are necessary and sufficient dynamical characteristics to make the Start transition a bistable and irreversible switch. Our study thus demonstrates that Start irreversibility is a property that arises from the architecture of the system (Whi5/SBF/Cln2 loop), rather than the consequence of the regulation of a single component (e.g., irreversible protein degradation).
Computational detection of genomic cis-regulatory modules applied to body patterning in the early Drosophila embryo
Nikolaus Rajewsky, Massimo Vergassola, Ulrike Gaul, Eric D Siggia
BMC Bioinformatics , 2002, DOI: 10.1186/1471-2105-3-30
Abstract: Here we present novel algorithms to detect cis-regulatory modules through genome wide scans for clusters of transcription factor binding sites using three levels of prior information. When binding sites for the factors are known, our statistical segmentation algorithm, Ahab, yields about 150 putative gap gene regulated modules, with no adjustable parameters other than a window size. If one or more related modules are known, but no binding sites, repeated motifs can be found by a customized Gibbs sampler and input to Ahab, to predict genes with similar regulation. Finally using only the genome, we developed a third algorithm, Argos, that counts and scores clusters of overrepresented motifs in a window of sequence. Argos recovers many of the known modules, upstream of the segmentation genes, with no training data.We have demonstrated, in the case of body patterning in the Drosophila embryo, that our algorithms allow the genome-wide identification of regulatory modules. We believe that Ahab overcomes many problems of recent approaches and we estimated the false positive rate to be about 50%. Argos is the first successful attempt to predict regulatory modules using only the genome without training data. Complete results and module predictions across the Drosophila genome are available at http://uqbar.rockefeller.edu/~siggia/ webcite.In higher eukaryotes, many genes feature differential spatial-temporal expression during development and throughout the life cycle of the organism. Their complex transcription regulation is thought to be achieved by the combinatorial action of multiple transcription factors which bind to cis-regulatory DNA sequences. Here, transcription factors are defined as proteins which recognize and bind regulatory sites and have a potential to modulate directly or indirectly through the recruitment of cofactors the activity of the basal transcriptional apparatus of proximal genes. The number of transcription factors is a substantial part of the total n
Origin of Irreversibility of Cell Cycle Start in Budding Yeast
Gilles Charvin ,Catherine Oikonomou,Eric D. Siggia,Frederick R. Cross
PLOS Biology , 2010, DOI: 10.1371/journal.pbio.1000284
Abstract: Budding yeast cells irreversibly commit to a new division cycle at a regulatory transition called Start. This essential decision-making step involves the activation of the SBF/MBF transcription factors. SBF/MBF promote expression of the G1 cyclins encoded by CLN1 and CLN2. Cln1,2 can activate their own expression by inactivating the Whi5 repressor of SBF/MBF. The resulting transcriptional positive feedback provides an appealing, but as yet unproven, candidate for generating irreversibility of Start. Here, we investigate the logic of the Start regulatory module by quantitative single-cell time-lapse microscopy, using strains in which expression of key regulators is efficiently controlled by changes of inducers in a microfluidic chamber. We show that Start activation is ultrasensitive to G1 cyclin. In the absence of CLN1,2-dependent positive feedback, we observe that Start transit is reversible, due to reactivation of the Whi5 transcriptional repressor. Introduction of the positive feedback loop makes Whi5 inactivation and Start activation irreversible, which therefore guarantees unidirectional entry into S phase. A simple mathematical model to describe G1 cyclin turn on at Start, entirely constrained by empirically measured parameters, shows that the experimentally measured ultrasensitivity and transcriptional positive feedback are necessary and sufficient dynamical characteristics to make the Start transition a bistable and irreversible switch. Our study thus demonstrates that Start irreversibility is a property that arises from the architecture of the system (Whi5/SBF/Cln2 loop), rather than the consequence of the regulation of a single component (e.g., irreversible protein degradation).
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