Generalization of DNA microarray dispersion properties: microarray equivalent of t-distribution

BACKGROUND: DNA microarrays are a powerful technology that can provide a wealth of gene expression data for disease studies, drug development, and a wide scope of other investigations. Because of the large volume and inherent variability of DNA microarray data, many new statistical methods have been developed for evaluating the significance of the observed differences in gene expression. However, until now little attention has been given to the characterization of dispersion of DNA microarray data. RESULTS: Here we examine the expression data obtained from 682 Affymetrix GeneChips(® )with 22 different types and we demonstrate that the Gaussian (normal) frequency distribution is characteristic for the variability of gene expression values. However, typically 5 to 15% of the samples deviate from normality. Furthermore, it is shown that the frequency distributions of the difference of expression in subsets of ordered, consecutive pairs of genes (consecutive samples) in pair-wise comparisons of replicate experiments are also normal. We describe a consecutive sampling method, which is employed to calculate the characteristic function approximating standard deviation and show that the standard deviation derived from the consecutive samples is equivalent to the standard deviation obtained from individual genes. Finally, we determine the boundaries of probability intervals and demonstrate that the coefficients defining the intervals are independent of sample characteristics, variability of data, laboratory conditions and type of chips. These coefficients are very closely correlated with Student's t-distribution. CONCLUSION: In this study we ascertained that the non-systematic variations possess Gaussian distribution, determined the probability intervals and demonstrated that the K(α )coefficients defining these intervals are invariant; these coefficients offer a convenient universal measure of dispersion of data. The fact that the K(α )distributions are so close to t-distribution and independent of conditions and type of arrays suggests that the quantitative data provided by Affymetrix technology give "true" representation of physical processes, involved in measurement of RNA abundance. REVIEWERS: This article was reviewed by Yoav Gilad (nominated by Doron Lancet), Sach Mukherjee (nominated by Sandrine Dudoit) and Amir Niknejad and Shmuel Friedland (nominated by Neil Smalheiser)

Identification and Characterization of lpfABCC′DE, a Fimbrial Operon of Enterohemorrhagic Escherichia coli O157:H7

The mechanisms underlying the adherence of Escherichia coli O157:H7 and other enterohemorrhagic E. coli (EHEC) strains to intestinal epithelial cells are poorly understood. We have identified a chromosomal region (designated lpfABCC′DE) in EHEC O157:H7 containing six putative open reading frames that was found to be closely related to the long polar (LP) fimbria operon (lpf) of Salmonella enterica serovar Typhimurium, both in gene order and in conservation of the deduced amino acid sequences. We show that lpfABCC′DE is organized as an operon and that its expression is induced during the exponential growth phase. The lpf genes from EHEC strain EDL933 were introduced into a nonfimbriated (Fim(−)) E. coli K-12 strain, and the transformed strain produced fimbriae as visualized by electron microscopy and adhered to tissue culture cells. Anti-LpfA antiserum recognized a ca. 16-kDa LpfA protein when expressed under regulation of the T7 promoter system. The antiserum also cross-reacted with the LP fimbriae in immunogold electron microscopy and Western blot experiments. Isogenic E. coli O157:H7 lpf mutants derived from strains 86-24 and AGT300 showed slight reductions in adherence to tissue culture cells and formed fewer microcolonies compared with their wild-type parent strains. The adherence and microcolony formation phenotypes were restored when the lpf operon was introduced on a plasmid. We propose that LP fimbriae participate in the interaction of E. coli O157:H7 with eukaryotic cells by assisting in microcolony formation

Regulatory Network of Escherichia coli: Consistency Between Literature Knowledge and Microarray Profiles

The transcriptional network of Escherichia coli may well be the most complete experimentally characterized network of a single cell. A rule-based approach was built to assess the degree of consistency between whole-genome microarray experiments in different experimental conditions and the accumulated knowledge in the literature compiled in RegulonDB, a data base of transcriptional regulation and operon organization in E. coli. We observed a high and statistical significant level of consistency, ranging from 70%-87%. When effector metabolites of regulatory proteins are not considered in the prediction of the active or inactive state of the regulators, consistency falls by up to 40%. Similarly, consistency decreases when rules for multiple regulatory interactions are altered or when “on” and “off” entries were assigned randomly. We modified the initial state of regulators and evaluated the propagation of errors in the network that do not correlate linearly with the connectivity of regulators. We interpret this deviation mainly as a result of the existence of redundant regulatory interactions. Consistency evaluation opens a new space of dialogue between theory and experiment, as the consequences of different assumptions can be evaluated and compared

Gene Expression Analysis Using Oligonucleotide Arrays Produced by Maskless Photolithography

Microarrays containing 195,000 in situ synthesized oligonucleotide features have been created using a benchtop, maskless photolithographic instrument. This instrument, the Maskless Array Synthesizer (MAS), uses a digital light processor (DLP) developed by Texas Instruments. The DLP creates the patterns of UV light used in the light-directed synthesis of oligonucleotides. This digital mask eliminates the need for expensive and time-consuming chromium masks. In this report, we describe experiments in which we tested this maskless technology for DNA synthesis on glass surfaces. Parameters examined included deprotection rates, repetitive yields, and oligonucleotide length. Custom gene expression arrays were manufactured and hybridized to Drosophila melanogaster and mouse samples. Quantitative PCR was used to validate the gene expression data from the mouse arrays. [The sequence data from this study have been submitted to GEO under accession nos. GPL208, GSM2409, GSM2410, GSM2411, GSM2412, GSM2413, GSM2414, GSE81, GSE82.

The Molecular Taxonomy of Primary Prostate Cancer

There is substantial heterogeneity among primary prostate cancers, evident in the spectrum of molecular abnormalities and its variable clinical course. As part of The Cancer Genome Atlas (TCGA), we present a comprehensive molecular analysis of 333 primary prostate carcinomas. Our results revealed a molecular taxonomy in which 74% of these tumors fell into one of seven subtypes defined by specific gene fusions (ERG, ETV1/4, and FLI1) or mutations (SPOP, FOXA1, and IDH1). Epigenetic profiles showed substantial heterogeneity, including an IDH1 mutant subset with a methylator phenotype. Androgen receptor (AR) activity varied widely and in a subtype-specific manner, with SPOP and FOXA1 mutant tumors having the highest levels of AR-induced transcripts. 25% of the prostate cancers had a presumed actionable lesion in the PI3K or MAPK signaling pathways, and DNA repair genes were inactivated in 19%. Our analysis reveals molecular heterogeneity among primary prostate cancers, as well as potentially actionable molecular defectsclose