iTAR: A Web Server for Identifying Target Genes of Transcription Factors using ChIP-Seq or ChIP-Chip Data

Chromatin immunoprecipitation followed by massively parallel DNA sequencing (ChIP-seq) or microarray hybridization (ChIP-chip) has been widely used to determine the genomic occupation of transcription factors (TFs). We have previously developed a probabilistic method, called TIP (Target Identification from Profiles), to identify TF target genes using ChIP-seq/ChIP-chip data. To achieve high specificity, TIP applies a conservative method to estimate significance of target genes, with the trade-off being a relatively low sensitivity of target gene identification compared to other methods. Additionally, TIP’s output does not render binding-peak locations or intensity, information highly useful for visualization and general experimental biological use, while the variability of ChIP-seq/ChIP-chip file formats has made input into TIP more difficult than desired. To improve upon these facets, here we present are fined TIP with key extensions. First, it implements a Gaussian mixture model for p-value estimation, increasing target gene identification sensitivity and more accurately capturing the shape of TF binding profile distributions. Second, it enables the incorporation of TF binding-peak data by identifying their locations in significant target gene promoter regions and quantifies their strengths. Finally, for full ease of implementation we have incorporated it into a web server (http://syslab3.nchu.edu.tw/iTAR/) that enables flexibility of input file format, can be used across multiple species and genome assembly versions, and is freely available for public use. The web server additionally performs GO enrichment analysis for the identified target genes to reveal the potential function of the corresponding TF

RANKL Deletion in Periodontal Ligament and Bone Lining Cells Blocks Orthodontic Tooth Movement

The bone remodeling process in response to orthodontic forces requires the activity of osteoclasts to allow teeth to move in the direction of the force applied. Receptor activator of nuclear factor-κB ligand (RANKL) is essential for this process although its cellular source in response to orthodontic forces has not been determined. Orthodontic tooth movement is considered to be an aseptic inflammatory process that is stimulated by leukocytes inclduing T and B lymphocytes which are presumed to stimulate bone resorption. We determined whether periodontal ligament and bone lining cells were an essential source of RANKL by tamoxifen induced deletion of RANKL in which Cre recombinase was driven by a 3.2 kb reporter element of the Col1α1 gene in experimental mice (Col1α1.CreERTM+.RANKLf/f) and compared results with littermate controls (Col1α1.CreERTM-.RANKLf/f). By examination of Col1α1.CreERTM+.ROSA26 reporter mice we showed tissue specificity of tamoxifen induced Cre recombinase predominantly in the periodontal ligament and bone lining cells. Surprisingly we found that most of the orthodontic tooth movement and formation of osteoclasts was blocked in the experimental mice, which also had a reduced periodontal ligament space. Thus, we demonstrate for the first time that RANKL produced by periodontal ligament and bone lining cells provide the major driving force for tooth movement and osteoclastogenesis in response to orthodontic forces

Egy hazai matematikai felmérés eredményei nemzetközi összehasonlításban

<p><b>Comparisons of the effect of different dipeptidyl peptidase-4 inhibitor treatment for 1 year on adjusted mean changes in fasting plasma glucose (FPG) (A) and glycated hemoglobin (HbA</b>_<b>1</b><b>c) (B) in the patients with a low and high hemoglobin glycation index (HGI).</b> Factors included in the analysis of variance statistical model were baseline oral anti-diabetes drugs, age, sex and renal function. VI = vildagliptin (n = 24 in the low HGI and n = 36 in the high HGI groups), LI = linagliptin (n = 33 in the low HGI and n = 31 in the high HGI groups), SA = saxagliptin (n = 45 in low HGI and n = 64 in the high HGI groups), SI = sitagliptin (n = 97 in the low HGI and n = 138 in the high HGI group). Error bars represent 95% confidence interval (CI). p-value for between-group difference. (To convert glucose to millimoles per liter, multiply by 0.0555)</p

UNIT project: Universe NN-body simulations for the Investigation of Theoretical models from galaxy surveys

We present the UNIT $N$-body cosmological simulations project, designed to provide precise predictions for nonlinear statistics of the galaxy distribution. We focus on characterizing statistics relevant to emission line and luminous red galaxies in the current and upcoming generation of galaxy surveys. We use a suite of precise particle mesh simulations (FastPM) as well as with full $N$-body calculations with a mass resolution of $\sim 1.2\times10^9\,h^{-1}$M$_{\odot}$ to investigate the recently suggested technique of Angulo & Pontzen 2016 to suppress the variance of cosmological simulations We study redshift space distortions, cosmic voids, higher order statistics from $z=2$ down to $z=0$. We find that both two- and three-point statistics are unbiased. Over the scales of interest for baryon acoustic oscillations and redshift-space distortions, we find that the variance is greatly reduced in the two-point statistics and in the cross correlation between halos and cosmic voids, but is not reduced significantly for the three-point statistics. We demonstrate that the accuracy of the two-point correlation function for a galaxy survey with effective volume of 20 ($h^{-1}$Gpc)$^3$ is improved by about a factor of 40, indicating that two pairs of simulations with a volume of 1 ($h^{-1}$Gpc)$^3$ lead to the equivalent variance of $\sim$150 such simulations. The $N$-body simulations presented here thus provide an effective survey volume of about seven times the effective survey volume of DESI or Euclid. The data from this project, including dark matter fields, halo catalogues, and their clustering statistics, are publicly available at http://www.unitsims.org.Comment: 12 pages, 9 figures. This version matches the one accepted by MNRAS. The data from this project are publicly available at: http://www.unitsims.or

Probing the DNA kink structure induced by the hyperthermophilic chromosomal protein Sac7d

Sac7d, a small, abundant, sequence-general DNA-binding protein from the hyperthermophilic archaeon Sulfolobus acidocaldarius, causes a single-step sharp kink in DNA (∼60°) via the intercalation of both Val26 and Met29. These two amino acids were systematically changed in size to probe their effects on DNA kinking. Eight crystal structures of five Sac7d mutant–DNA complexes have been analyzed. The DNA-binding pattern of the V26A and M29A single mutants is similar to that of the wild-type, whereas the V26A/M29A protein binds DNA without side chain intercalation, resulting in a smaller overall bending (∼50°). The M29F mutant inserts the Phe29 side chain orthogonally to the C2pG3 step without stacking with base pairs, inducing a sharp kink (∼80°). In the V26F/M29F-GCGATCGC complex, Phe26 intercalates deeply into DNA bases by stacking with the G3 base, whereas Phe29 is stacked on the G15 deoxyribose, in a way similar to those used by the TATA box-binding proteins. All mutants have reduced DNA-stabilizing ability, as indicated by their lower T(m) values. The DNA kink patterns caused by different combinations of hydrophobic side chains may be relevant in understanding the manner by which other minor groove-binding proteins interact with DNA

Extended Smoothed Boundary Method for Solving Partial Differential Equations with General Boundary Conditions on Complex Boundaries

In this article, we describe an approach for solving partial differential equations with general boundary conditions imposed on arbitrarily shaped boundaries. A continuous function, the domain parameter, is used to modify the original differential equations such that the equations are solved in the region where a domain parameter takes a specified value while boundary conditions are imposed on the region where the value of the domain parameter varies smoothly across a short distance. The mathematical derivations are straightforward and generically applicable to a wide variety of partial differential equations. To demonstrate the general applicability of the approach, we provide four examples herein: (1) the diffusion equation with both Neumann and Dirichlet boundary conditions; (2) the diffusion equation with both surface diffusion and reaction; (3) the mechanical equilibrium equation; and (4) the equation for phase transformation with the presence of additional boundaries. The solutions for several of these cases are validated against corresponding analytical and semi-analytical solutions. The potential of the approach is demonstrated with five applications: surface-reaction-diffusion kinetics with a complex geometry, Kirkendall-effect-induced deformation, thermal stress in a complex geometry, phase transformations affected by substrate surfaces, and a self-propelled droplet.Comment: This document is the revised version of arXiv:0912.1288v