Impact of Tandem Repeats on the Scaling of Nucleotide Sequences

Techniques such as detrended fluctuation analysis (DFA) and its extensions have been widely used to determine the nature of scaling in nucleotide sequences. In this brief communication we show that tandem repeats which are ubiquitous in nucleotide sequences can prevent reliable estimation of possible long-range correlations. Therefore, it is important to investigate the presence of tandem repeats prior to scaling exponent estimation.Comment: 14 Pages, 3 Figure

Strategies for analyzing highly enriched IP-chip datasets

BACKGROUND: Chromatin immunoprecipitation on tiling arrays (ChIP-chip) has been employed to examine features such as protein binding and histone modifications on a genome-wide scale in a variety of cell types. Array data from the latter studies typically have a high proportion of enriched probes whose signals vary considerably (due to heterogeneity in the cell population), and this makes their normalization and downstream analysis difficult. RESULTS: Here we present strategies for analyzing such experiments, focusing our discussion on the analysis of Bromodeoxyruridine (BrdU) immunoprecipitation on tiling array (BrdU-IP-chip) datasets. BrdU-IP-chip experiments map large, recently replicated genomic regions and have similar characteristics to histone modification/location data. To prepare such data for downstream analysis we employ a dynamic programming algorithm that identifies a set of putative unenriched probes, which we use for both within-array and between-array normalization. We also introduce a second dynamic programming algorithm that incorporates a priori knowledge to identify and quantify positive signals in these datasets. CONCLUSION: Highly enriched IP-chip datasets are often difficult to analyze with traditional array normalization and analysis strategies. Here we present and test a set of analytical tools for their normalization and quantification that allows for accurate identification and analysis of enriched regions

Fkh1 and Fkh2 bind multiple chromosomal elements in the S. cerevisiae genome with distinct specificities and cell cycle dynamics

Forkhead box (FOX) transcription factors regulate a wide variety of cellular functions in higher eukaryotes, including cell cycle control and developmental regulation. In Saccharomyces cerevisiae, Forkhead proteins Fkh1 and Fkh2 perform analogous functions, regulating genes involved in cell cycle control, while also regulating mating-type silencing and switching involved in gamete development. Recently, we revealed a novel role for Fkh1 and Fkh2 in the regulation of replication origin initiation timing, which, like donor preference in mating-type switching, appears to involve long-range chromosomal interactions, suggesting roles for Fkh1 and Fkh2 in chromatin architecture and organization. To elucidate how Fkh1 and Fkh2 regulate their target DNA elements and potentially regulate the spatial organization of the genome, we undertook a genome-wide analysis of Fkh1 and Fkh2 chromatin binding by ChIP-chip using tiling DNA microarrays. Our results confirm and extend previous findings showing that Fkh1 and Fkh2 control the expression of cell cycle-regulated genes. In addition, the data reveal hundreds of novel loci that bind Fkh1 only and exhibit a distinct chromatin structure from loci that bind both Fkh1 and Fkh2. The findings also show that Fkh1 plays the predominant role in the regulation of a subset of replication origins that initiate replication early, and that Fkh1/2 binding to these loci is cell cycle-regulated. Finally, we demonstrate that Fkh1 and Fkh2 bind proximally to a variety of genetic elements, including centromeres and Pol III-transcribed snoRNAs and tRNAs, greatly expanding their potential repertoire of functional targets, consistent with their recently suggested role in mediating the spatial organization of the genome

Inferring pandemic growth rates from sequence data

Using sequence data to infer population dynamics is playing an increasing role in the analysis of outbreaks. The most common methods in use, based on coalescent inference, have been widely used but not extensively tested against simulated epidemics. Here, we use simulated data to test the ability of both parametric and non-parametric methods for inference of effective population size (coded in the popular BEAST package) to reconstruct epidemic dynamics. We consider a range of simulations centred on scenarios considered plausible for pandemic influenza, but our conclusions are generic for any exponentially growing epidemic. We highlight systematic biases in non-parametric effective population size estimation. The most prominent such bias leads to the false inference of slowing of epidemic spread in the recent past even when the real epidemic is growing exponentially. We suggest some sampling strategies that could reduce (but not eliminate) some of the biases. Parametric methods can correct for these biases if the infected population size is large. We also explore how some poor sampling strategies (e.g. that over-represent epidemiologically linked clusters of cases) could dramatically exacerbate bias in an uncontrolled manner. Finally, we present a simple diagnostic indicator, based on coalescent density and which can easily be applied to reconstructed phylogenies, that identifies time-periods for which effective population size estimates are less likely to be biased. We illustrate this with an application to the 2009 H1N1 pandemic

R/Bioconductor software for Illumina's Infinium whole-genome genotyping BeadChips

Summary: Illumina produces a number of microarray-based technologies for human genotyping. An Infinium BeadChip is a two-color platform that types between 105 and 106 single nucleotide polymorphisms (SNPs) per sample. Despite being widely used, there is a shortage of open source software to process the raw intensities from this platform into genotype calls. To this end, we have developed the R/Bioconductor package crlmm for analyzing BeadChip data. After careful preprocessing, our software applies the CRLMM algorithm to produce genotype calls, confidence scores and other quality metrics at both the SNP and sample levels. We provide access to the raw summary-level intensity data, allowing users to develop their own methods for genotype calling or copy number analysis if they wish

Computational system identification of continuous-time nonlinear systems using approximate Bayesian computation

In this paper, we derive a system identification framework for continuous-time nonlinear systems, for the first time using a simulation-focused computational Bayesian approach. Simulation approaches to nonlinear system identification have been shown to outperform regression methods under certain conditions, such as non-persistently exciting inputs and fast-sampling. We use the approximate Bayesian computation (ABC) algorithm to perform simulation-based inference of model parameters. The framework has the following main advantages: (1) parameter distributions are intrinsically generated, giving the user a clear description of uncertainty, (2) the simulation approach avoids the difficult problem of estimating signal derivatives as is common with other continuous-time methods, and (3) as noted above, the simulation approach improves identification under conditions of non-persistently exciting inputs and fast-sampling. Term selection is performed by judging parameter significance using parameter distributions that are intrinsically generated as part of the ABC procedure. The results from a numerical example demonstrate that the method performs well in noisy scenarios, especially in comparison to competing techniques that rely on signal derivative estimation

Differential signaling to glycogen synthesis by the intracellular domain of the insulin versus the insulin-like growth factor-1 receptor

Insulin and insulin-like growth factor-1 (IGF-1) have similar cell-surface receptors yet subserve different physiological functions, To examine whether these differences relate to intrinsic signaling properties of the intracellular domains of their respective receptors, chimeric receptors were constructed using the extracellular domain of the neurotrophin-3 (NT-3) receptor, TrkC, and the intracellular domain of either the insulin receptor or the IGF-1 receptor, TrkC-IR (TIR) and TrkC-IGF-1R (TIGR) were stably expressed in 3T3-L1 cells, While TIR and TIGR cell lines expressing similar numbers of chimeric receptors showed a similar dose-response relationship in NT-3 stimulated DNA synthesis, NT-3 stimulated glycogen synthesis was greater in TIR than in TIGR cells (maximum TIGR response was 35% of maximum TIR response), Additionally, the concentration of NT-3 at which significant stimulation of glycogen synthesis was seen was 0.1 ng/ml in TIR and 1 ng/ml in TIGR cells, Basal levels of thymidine incorporation but not glycogen synthesis were consistently higher in TIR than in TIGR expressing cells, No detectable basal autophosphorylation of chimeric receptors was seen in any of the cell lines, However, exposure of cell lines to the phosphatase inhibitor bisperoxovanadate resulted in greater basal autophosphorylation of the TIR and endogenous murine IR than the TIGR and endogenous murine IGF-1R. Thus, in this system, the intracellular domain of the IR appears to couple more effectively to glycogen synthesis than that of the IGF-1R, whereas the intracellular domains of both receptors have a similar capacity to stimulate DNA synthesis

The level of origin firing inversely affects the rate of replication fork progression

DNA damage slows DNA synthesis at replication forks; however, the mechanisms remain unclear. Cdc7 kinase is required for replication origin activation, is a target of the intra-S checkpoint, and is implicated in the response to replication fork stress. Remarkably, we found that replication forks proceed more rapidly in cells lacking Cdc7 function than in wild-type cells. We traced this effect to reduced origin firing, which results in fewer replication forks and a consequent decrease in Rad53 checkpoint signaling. Depletion of Orc1, which acts in origin firing differently than Cdc7, had similar effects as Cdc7 depletion, consistent with decreased origin firing being the source of these defects. In contrast, mec1-100 cells, which initiate excess origins and also are deficient in checkpoint activation, showed slower fork progression, suggesting the number of active forks influences their rate, perhaps as a result of competition for limiting factors

Quantitative plane-resolved crystal growth and dissolution kinetics by coupling in situ optical microscopy and diffusion models : the case of salicylic acid in aqueous solution

The growth and dissolution kinetics of salicylic acid crystals are investigated in situ by focusing on individual microscale crystals. From a combination of optical microscopy and finite element method (FEM) modeling, it was possible to obtain a detailed quantitative picture of dissolution and growth dynamics for individual crystal faces. The approach uses real-time in situ growth and dissolution data (crystal size and shape as a function of time) to parametrize a FEM model incorporating surface kinetics and bulk to surface diffusion, from which concentration distributions and fluxes are obtained directly. It was found that the (001) face showed strong mass transport (diffusion) controlled behavior with an average surface concentration close to the solubility value during growth and dissolution over a wide range of bulk saturation levels. The (1̅10) and (110) faces exhibited mixed mass transport/surface controlled behavior, but with a strong diffusive component. As crystals became relatively large, they tended to exhibit peculiar hollow structures in the end (001) face, observed by interferometry and optical microscopy. Such features have been reported in a number of crystals, but there has not been a satisfactory explanation for their origin. The mass transport simulations indicate that there is a large difference in flux across the crystal surface, with high values at the edge of the (001) face compared to the center, and this flux has to be redistributed across the (001) surface. As the crystal grows, the redistribution process evidently can not be maintained so that the edges grow at the expense of the center, ultimately creating high index internal structures. At later times, we postulate that these high energy faces, starved of material from solution, dissolve and the extra flux of salicylic acid causes the voids to close