ART: a next-generation sequencing read simulatorUNLABELLED: ART is a set of simulation tools that generate synthetic next-generation sequencing reads. This functionality is essential for testing and benchmarking tools for next-generation sequencing data analysis including read alignment, de novo assembly and genetic variation discovery. ART generates simulated sequencing reads by emulating the sequencing process with built-in, technology-specific read error models and base quality value profiles parameterized empirically in large sequencing datasets. We currently support all three major commercial next-generation sequencing platforms: Roche's 454, Illumina's Solexa and Applied Biosystems' SOLiD. ART also allows the flexibility to use customized read error model parameters and quality profiles. AVAILABILITY: Both source and binary software packages are available at http://www.niehs.nih.gov/research/resources/software/art.
Role of LXRs in control of lipogenesisJoshua R. Schultz, Hua Tu, Alvin Luk et al.|Genes & Development|2000 The discovery of oxysterols as the endogenous liver X receptor (LXR) ligands and subsequent gene targeting studies in mice provided strong evidence that LXR plays a central role in cholesterol metabolism. The identification here of a synthetic, nonsteroidal LXR-selective agonist series represented by T0314407 and T0901317 revealed a novel physiological role of LXR. Oral administration of T0901317 to mice and hamsters showed that LXR activated the coordinate expression of major fatty acid biosynthetic genes (lipogenesis) and increased plasma triglyceride and phospholipid levels in both species. Complementary studies in cell culture and animals suggested that the increase in plasma lipids occurs via LXR-mediated induction of the sterol regulatory element-binding protein 1 (SREBP-1) lipogenic program.
New tricks for modelers from the crystallography toolkit: the particle mesh Ewald algorithm and its use in nucleic acid simulationsGene selection for sample classification based on gene expression data: study of sensitivity to choice of parameters of the GA/KNN methodMOTIVATION: We recently introduced a multivariate approach that selects a subset of predictive genes jointly for sample classification based on expression data. We tested the algorithm on colon and leukemia data sets. As an extension to our earlier work, we systematically examine the sensitivity, reproducibility and stability of gene selection/sample classification to the choice of parameters of the algorithm. METHODS: Our approach combines a Genetic Algorithm (GA) and the k-Nearest Neighbor (KNN) method to identify genes that can jointly discriminate between different classes of samples (e.g. normal versus tumor). The GA/KNN method is a stochastic supervised pattern recognition method. The genes identified are subsequently used to classify independent test set samples. RESULTS: The GA/KNN method is capable of selecting a subset of predictive genes from a large noisy data set for sample classification. It is a multivariate approach that can capture the correlated structure in the data. We find that for a given data set gene selection is highly repeatable in independent runs using the GA/KNN method. In general, however, gene selection may be less robust than classification. AVAILABILITY: The method is available at http://dir.niehs.nih.gov/microarray/datamining CONTACT: LI3@niehs.nih.gov
Oct4/Sox2-Regulated miR-302 Targets Cyclin D1 in Human Embryonic Stem CellsOct4 and Sox2 are transcription factors required for pluripotency during early embryogenesis and for the maintenance of embryonic stem cell (ESC) identity. Functional mechanisms contributing to pluripotency are expected to be associated with genes transcriptionally activated by these factors. Here, we show that Oct4 and Sox2 bind to a conserved promoter region of miR-302, a cluster of eight microRNAs expressed specifically in ESCs and pluripotent cells. The expression of miR-302a is dependent on Oct4/Sox2 in human ESCs (hESCs), and miR-302a is expressed at the same developmental stages and in the same tissues as Oct4 during embryogenesis. miR-302a is predicted to target many cell cycle regulators, and the expression of miR-302a in primary and transformed cell lines promotes an increase in S-phase and a decrease in G(1)-phase cells, reminiscent of an ESC-like cell cycle profile. Correspondingly, the inhibition of miR-302 causes hESCs to accumulate in G(1) phase. Moreover, we show that miR-302a represses the productive translation of an important G(1) regulator, cyclin D1, in hESCs. The transcriptional activation of miR-302 and the translational repression of its targets, such as cyclin D1, may provide a link between Oct4/Sox2 and cell cycle regulation in pluripotent cells.