Microarrays Commons^™

Gene Expression Profiling In Salmonella Choleraesuis-Infected Porcine Lung Using A Long Oligonucleotide Microarray, Shu-Hong Zhao, Daniel Kuhar, Joan K. Lunney, Harry Dawson, Catherine Guidry, Jolita J. Uthe, Shawn M. D. Bearson, Justin Recknor, Dan Nettleton, Christopher K. Tuggle

Dan Nettleton

Understanding the transcriptional response to pathogenic bacterial infection within food animals is of fundamental and applied interest. To determine the transcriptional response to Salmonella enterica serovar Choleraesuis (SC) infection, a 13,297-oligonucleotide swine array was used to analyze RNA from control, 24-h postinoculation (hpi), and 48-hpi porcine lung tissue from pigs infected with SC. In total, 57 genes showed differential expression (p < 0.001; false discovery rate = 12%). Quantitative real-time PCR (qRT-PCR) of 61 genes was used to confirm the microarray results and to identify pathways responding to infection. Of the 33 genes identified by microarray analysis as differentially expressed, 23 were confirmed by qRT-PCR results. A novel finding was that two transglutaminase family genes (TGM1 and TGM3) showed dramatic increases in expression postinoculation; combined with several other apoptotic genes, they indicated the induction of apoptotic pathways during SC infection. A predominant T helper 1-type immune response occurred during infection, with interferon …

Laser Microdissection Of Narrow Sheath Mutant Maize Uncovers Novel Gene Expression In The Shoot Apical Meristem, Xiaolan Zhang, Shahinez Madi, Lisa Borsuk, Dan Nettleton, Robert J. Elshire, Brent Buckner, Diane Janick-Buckner, Jon Beck, Marja Timmermans, Patrick S. Schnable, Michael J. Scanlon

Dan Nettleton

Microarrays enable comparative analyses of gene expression on a genomic scale, however these experiments frequently identify an abundance of differentially expressed genes such that it may be difficult to identify discrete functional networks that are hidden within large microarray datasets. Microarray analyses in which mutant organisms are compared to nonmutant siblings can be especially problematic when the gene of interest is expressed in relatively few cells. Here, we describe the use of laser microdissection microarray to perform transcriptional profiling of the maize shoot apical meristem (SAM), a ~100-μm pillar of organogenic cells that is required for leaf initiation. Microarray analyses …

Scanning Microarrays At Multiple Intensities Enhances Discovery Of Differentially Expressed Genes, David S. Skibbe, Xiujuan Wang, Xuefeng Zhao, Lisa A. Borsuk, Dan Nettleton, Patrick S. Schnable

Dan Nettleton

Motivation: Scanning parameters are often overlooked when optimizing microarray experiments. A scanning approach that extends the dynamic data range by acquiring multiple scans of different intensities has been developed.

Results: Data from each of three scan intensities (low, medium, high) were analyzed separately using multiple scan and linear regression approaches to identify and compare the sets of genes that exhibit statistically significant differential expression. In the multiple scan approach only one-third of the differentially expressed genes were shared among the three intensities, and each scan intensity identified unique sets of differentially expressed genes. The set of differentially expressed genes from …

Microarray Gene Expression Profiles Of Fasting Induced Changes In Liver And Adipose Tissues Of Pigs Expressing The Melanocortin-4 Receptor D298n Variant, Sender Lkhagvadorj, Long Qu, Weiguo Cai, Oliver P. Coutoure, C. Richard Barb, Gary J. Hausman, Dan Nettleton, Lloyd L. Anderson, Jack C. M. Dekkers, Christopher K. Tuggle

Dan Nettleton

Transcriptional profiling coupled with blood metabolite analyses were used to identify porcine genes and pathways that respond to a fasting treatment or to a D298N missense mutation in the melanocortin-4 receptor (MC4R) gene. Gilts (12 homozygous for D298 and 12 homozygous for N298) were either fed ad libitum or fasted for 3 days. Fasting decreased body weight, backfat, and serum urea concentration and increased serum nonesterified fatty acid. In response to fasting, 7,029 genes in fat and 1,831 genes in liver were differentially expressed (DE). MC4R genotype did not significantly affect gene expression, body weight, backfat depth, or any measured …

Analysis Of Porcine Transcriptional Response To Salmonella Enterica Serovar Choleraesuis Suggests Novel Targets Of Nfkappab Are Activated In The Mesenteric Lymph Node, Yanfang Wang, Olivre P. Couture, Long Qu, Jolita J. Uthe, Shawn M. D. Bearson, Daniel Kuhar, Joan K. Lunney, Dan Nettleton, Jack C. M. Dekkers, Christopher K. Tuggle

Dan Nettleton

Background: Specific knowledge of the molecular pathways controlling host-pathogen interactions can increase our understanding of immune response biology as well as provide targets for drug development and genetic improvement of disease resistance. Toward this end, we have characterized the porcine transcriptional response to Salmonella enterica serovar Choleraesuis (S. Choleraesuis), a Salmonella serovar that predominately colonizes swine, yet can cause serious infections in human patients. Affymetrix technology was used to screen for differentially expressed genes in pig mesenteric lymph nodes (MLN) responding to infection with S. Choleraesuis at acute (8 hours (h), 24 h and 48 h post-inoculation (pi)) and chronic …

Comparative Gene Expression Profiles Between Heterotic And Non-Heterotic Hybrids Of Tetraploid Medicago Sativa, Xuehui Li, Yanling Wei, Dan Nettleton, E. Charles Brummer

Dan Nettleton

Background: Heterosis, the superior performance of hybrids relative to parents, has clear agricultural value, but its genetic control is unknown. Our objective was to test the hypotheses that hybrids expressing heterosis for biomass yield would show more gene expression levels that were different from midparental values and outside the range of parental values than hybrids that do not exhibit heterosis.

Results: We tested these hypotheses in three Medicago sativa (alfalfa) genotypes and their three hybrids, two of which expressed heterosis for biomass yield and a third that did not, using Affymetrix M. truncatula GeneChip arrays. Alfalfa hybridized to approximately 47% …

Distinct Peripheral Blood Rna Responses To Salmonella In Pigs Differing In Salmonella Shedding Levels: Intersection Of Ifng, Tlr And Mirna Pathways, Ting-Hua Huang, Jolita J. Uthe, Shawn M. D. Bearson, Cumhur Yusuf Demirkale, Dan Nettleton, Susan Knetter, Curtis Christian, Amanda E. Ramer-Tait, Michael J. Wannemeuhler, Christopher K. Tuggle

Dan Nettleton

Transcriptomic analysis of the response to bacterial pathogens has been reported for several species, yet few studies have investigated the transcriptional differences in whole blood in subjects that differ in their disease response phenotypes. Salmonella species infect many vertebrate species, and pigs colonized with Salmonella enterica serovar Typhimurium (ST) are usually asymptomatic, making detection of these Salmonella-carrier pigs difficult. The variable fecal shedding of Salmonella is an important cause of foodborne illness and zoonotic disease. To investigate gene pathways and biomarkers associated with the variance in Salmonellashedding following experimental inoculation, we initiated the first analysis of the whole …

Unique Genome-Wide Transcriptome Profiles Of Chicken Macrophages Exposed To Salmonella-Derived Endotoxin, Ceren Ciraci, Christopher K. Tuggle, Michael J. Wannemeuhler, Dan Nettleton, Susan J. Lamont

Dan Nettleton

Background: Macrophages play essential roles in both innate and adaptive immune responses. Bacteria require endotoxin, a complex lipopolysaccharide, for outer membrane permeability and the host interprets endotoxin as a signal to initiate an innate immune response. The focus of this study is kinetic and global transcriptional analysis of the chicken macrophage response to in vitro stimulation with endotoxin from Salmonella typhimurium-798.

Results: The 38535-probeset Affymetrix GeneChip Chicken Genome array was used to profile transcriptional response to endotoxin 1, 2, 4, and 8 hours post stimulation (hps). Using a maximum FDR (False Discovery Rate) of 0.05 to declare genes as differentially …

Bayesian Joint Selection Of Genes And Pathways: Applications In Multiple Myeloma Genomics, Lin Zhang, Jeffrey S. Morris, Jiexin Zhang, Robert Orlowski, Veerabhadran Baladandayuthapani

Jeffrey S. Morris

It is well-established that the development of a disease, especially cancer, is a complex process that results from the joint effects of multiple genes involved in various molecular signaling pathways. In this article, we propose methods to discover genes and molecular pathways significantly associ- ated with clinical outcomes in cancer samples. We exploit the natural hierarchal structure of genes related to a given pathway as a group of interacting genes to conduct selection of both pathways and genes. We posit the problem in a hierarchical structured variable selection (HSVS) framework to analyze the corresponding gene expression data. HSVS methods conduct …

Global Quantitative Assessment Of The Colorectal Polyp Burden In Familial Adenomatous Polyposis Using A Web-Based Tool, Patrick M. Lynch, Jeffrey S. Morris, William A. Ross, Miguel A. Rodriguez-Bigas, Juan Posadas, Rossa Khalaf, Diane M. Weber, Valerie O. Sepeda, Bernard Levin, Imad Shureiqi

Jeffrey S. Morris

Background: Accurate measures of the total polyp burden in familial adenomatous polyposis (FAP) are lacking. Current assessment tools include polyp quantitation in limited-field photographs and qualitative total colorectal polyp burden by video.

Objective: To develop global quantitative tools of the FAP colorectal adenoma burden.

Design: A single-arm, phase II trial.

Patients: Twenty-seven patients with FAP.

Intervention: Treatment with celecoxib for 6 months, with before-treatment and after-treatment videos posted to an intranet with an interactive site for scoring.

Main Outcome Measurements: Global adenoma counts and sizes (grouped into categories: less than 2 mm, 2-4 mm, and greater than 4 mm) were …

Bayesian Methods For Expression-Based Integration, Elizabeth M. Jennings, Jeffrey S. Morris, Raymond J. Carroll, Ganiraju C. Manyam, Veera Baladandayuthapani

Jeffrey S. Morris

We propose methods to integrate data across several genomic platforms using a hierarchical Bayesian analysis framework that incorporates the biological relationships among the platforms to identify genes whose expression is related to clinical outcomes in cancer. This integrated approach combines information across all platforms, leading to increased statistical power in finding these predictive genes, and further provides mechanistic information about the manner in which the gene affects the outcome. We demonstrate the advantages of the shrinkage estimation used by this approach through a simulation, and finally, we apply our method to a Glioblastoma Multiforme dataset and identify several genes potentially …

A Bayesian Model For Pooling Gene Expression Studies That Incorporates Co-Regulation Information, Erin M. Conlon, Bradley L. L. Postier, Barbara A. Methé, Kelly P. Nevin, Derek R. Lovley

Erin M. Conlon

Current Bayesian microarray models that pool multiple studies assume gene expression is independent of other genes. However, in prokaryotic organisms, genes are arranged in units that are co-regulated (called operons). Here, we introduce a new Bayesian model for pooling gene expression studies that incorporates operon information into the model. Our Bayesian model borrows information from other genes within the same operon to improve estimation of gene expression. The model produces the gene-specific posterior probability of differential expression, which is the basis for inference. We found in simulations and in biological studies that incorporating co-regulation information improves upon the independence model. …

Statistical Methods For Proteomic Biomarker Discovery Based On Feature Extraction Or Functional Modeling Approaches, Jeffrey S. Morris

Jeffrey S. Morris

In recent years, developments in molecular biotechnology have led to the increased promise of detecting and validating biomarkers, or molecular markers that relate to various biological or medical outcomes. Proteomics, the direct study of proteins in biological samples, plays an important role in the biomarker discovery process. These technologies produce complex, high dimensional functional and image data that present many analytical challenges that must be addressed properly for effective comparative proteomics studies that can yield potential biomarkers. Specific challenges include experimental design, preprocessing, feature extraction, and statistical analysis accounting for the inherent multiple testing issues. This paper reviews various computational …

Integrative Bayesian Analysis Of High-Dimensional Multi-Platform Genomics Data, Wenting Wang, Veerabhadran Baladandayuthapani, Jeffrey S. Morris, Bradley M. Broom, Ganiraju C. Manyam, Kim-Anh Do

Jeffrey S. Morris

Motivation: Analyzing data from multi-platform genomics experiments combined with patients’ clinical outcomes helps us understand the complex biological processes that characterize a disease, as well as how these processes relate to the development of the disease. Current integration approaches that treat the data are limited in that they do not consider the fundamental biological relationships that exist among the data from platforms.

Statistical Model: We propose an integrative Bayesian analysis of genomics data (iBAG) framework for identifying important genes/biomarkers that are associated with clinical outcome. This framework uses a hierarchical modeling technique to combine the data obtained from multiple platforms …

Wavelet-Based Functional Linear Mixed Models: An Application To Measurement Error–Corrected Distributed Lag Models, Elizabeth J. Malloy, Jeffrey S. Morris, Sara D. Adar, Helen Suh, Diane R. Gold, Brent A. Coull

Jeffrey S. Morris

Frequently, exposure data are measured over time on a grid of discrete values that collectively define a functional observation. In many applications, researchers are interested in using these measurements as covariates to predict a scalar response in a regression setting, with interest focusing on the most biologically relevant time window of exposure. One example is in panel studies of the health effects of particulate matter (PM), where particle levels are measured over time. In such studies, there are many more values of the functional data than observations in the data set so that regularization of the corresponding functional regression coefficient …

Members’ Discoveries: Fatal Flaws In Cancer Research, Jeffrey S. Morris

Jeffrey S. Morris

A recent article published in The Annals of Applied Statistics (AOAS) by two MD Anderson researchers—Keith Baggerly and Kevin Coombes—dissects results from a highly-influential series of medical papers involving genomics-driven personalized cancer therapy, and outlines a series of simple yet fatal flaws that raises serious questions about the veracity of the original results. Having immediate and strong impact, this paper, along with related work, is providing the impetus for new standards of reproducibility in scientific research.

Statistical Contributions To Proteomic Research, Jeffrey S. Morris, Keith A. Baggerly, Howard B. Gutstein, Kevin R. Coombes

Jeffrey S. Morris

Proteomic profiling has the potential to impact the diagnosis, prognosis, and treatment of various diseases. A number of different proteomic technologies are available that allow us to look at many proteins at once, and all of them yield complex data that raise significant quantitative challenges. Inadequate attention to these quantitative issues can prevent these studies from achieving their desired goals, and can even lead to invalid results. In this chapter, we describe various ways the involvement of statisticians or other quantitative scientists in the study team can contribute to the success of proteomic research, and we outline some of the …

Informatics And Statistics For Analyzing 2-D Gel Electrophoresis Images, Andrew W. Dowsey, Jeffrey S. Morris, Howard G. Gutstein, Guang Z. Yang

Jeffrey S. Morris

Whilst recent progress in ‘shotgun’ peptide separation by integrated liquid chromatography and mass spectrometry (LC/MS) has enabled its use as a sensitive analytical technique, proteome coverage and reproducibility is still limited and obtaining enough replicate runs for biomarker discovery is a challenge. For these reasons, recent research demonstrates the continuing need for protein separation by two-dimensional gel electrophoresis (2-DE). However, with traditional 2-DE informatics, the digitized images are reduced to symbolic data though spot detection and quantification before proteins are compared for differential expression by spot matching. Recently, a more robust and automated paradigm has emerged where gels are directly …

Bayesian Random Segmentationmodels To Identify Shared Copy Number Aberrations For Array Cgh Data, Veerabhadran Baladandayuthapani, Yuan Ji, Rajesh Talluri, Luis E. Nieto-Barajas, Jeffrey S. Morris

Jeffrey S. Morris

Array-based comparative genomic hybridization (aCGH) is a high-resolution high-throughput technique for studying the genetic basis of cancer. The resulting data consists of log fluorescence ratios as a function of the genomic DNA location and provides a cytogenetic representation of the relative DNA copy number variation. Analysis of such data typically involves estimation of the underlying copy number state at each location and segmenting regions of DNA with similar copy number states. Most current methods proceed by modeling a single sample/array at a time, and thus fail to borrow strength across multiple samples to infer shared regions of copy number aberrations. …

A Statistical Framework For The Analysis Of Chip-Seq Data, Pei Fen Kuan, Dongjun Chung, Guangjin Pan, James A. Thomson, Ron Stewart, Sunduz Keles

Sunduz Keles

Chromatin immunoprecipitation followed by sequencing (ChIP-Seq) has revolutionalized experiments for genome-wide profiling of DNA-binding proteins, histone modifications, and nucleosome occupancy. As the cost of sequencing is decreasing, many researchers are switching from microarray-based technologies (ChIP-chip) to ChIP-Seq for genome-wide study of transcriptional regulation. Despite its increasing and well-deserved popularity, there is little work that investigates and accounts for sources of biases in the ChIP-Seq technology. These biases typically arise from both the standard pre-processing protocol and the underlying DNA sequence of the generated data.

We study data from a naked DNA sequencing experiment, which sequences non-cross-linked DNA after deproteinizing and …

Rapid Changes In Gene Expression Dynamics In Response To Superoxide Reveal Soxrs-Dependent And Independent Transcriptional Networks, Jeffrey L. Blanchard, Wei-Yun Wholey, Erin M. Conlon, Pablo J. Pomposiello

Erin M. Conlon

Background

SoxR and SoxS constitute an intracellular signal response system that rapidly detects changes in superoxide levels and modulates gene expression in E. coli. A time series microarray design was used to identify co-regulated SoxRS-dependent and independent genes modulated by superoxide minutes after exposure to stress.

Methodology/Principal Findings

soxS mRNA levels surged to near maximal levels within the first few minutes of exposure to paraquat, a superoxide-producing compound, followed by a rise in mRNA levels of known SoxS-regulated genes. Based on a new method for determining the biological significance of clustering results, a total of 138 genic regions, including several …

Bayesian Meta-Analysis Models For Microarray Data: A Comparative Study, Erin M. Conlon, Joon J. Song, Anna Liu

Erin M. Conlon

Background With the growing abundance of microarray data, statistical methods are increasingly needed to integrate results across studies. Two common approaches for meta-analysis of microarrays include either combining gene expression measures across studies or combining summaries such as p-values, probabilities or ranks. Here, we compare two Bayesian meta-analysis models that are analogous to these methods. Results Two Bayesian meta-analysis models for microarray data have recently been introduced. The first model combines standardized gene expression measures across studies into an overall mean, accounting for inter-study variability, while the second combines probabilities of differential expression without combining expression values. Both models produce …

Bayesian Models For Pooling Microarray Studies With Multiple Sources Of Replications, Erin M. Conlon, Joon J. Song, Jun S. Liu

Erin M. Conlon

Background Biologists often conduct multiple but different cDNA microarray studies that all target the same biological system or pathway. Within each study, replicate slides within repeated identical experiments are often produced. Pooling information across studies can help more accurately identify true target genes. Here, we introduce a method to integrate multiple independent studies efficiently. Results We introduce a Bayesian hierarchical model to pool cDNA microarray data across multiple independent studies to identify highly expressed genes. Each study has multiple sources of variation, i.e. replicate slides within repeated identical experiments. Our model produces the gene-specific posterior probability of differential expression, which …

Program Of Gene Transcription For A Single Differentiating Cell Type During Sporulation In Bacillus Subtilis, Patrick Eichenberger, Masaya Fujita, Shane T. Jensen, Erin M. Conlon, David Z. Rudner, Stephanie T. Want, Caitlin Ferguson, Koki Haga, Txutomu Sato, Jun S. Liu, Richard Losick

Erin M. Conlon

Asymmetric division during sporulation by Bacillus subtilis generates a mother cell that undergoes a 5-h program of differentiation. The program is governed by a hierarchical cascade consisting of the transcription factors: σE, σK, GerE, GerR, and SpoIIID. The program consists of the activation and repression of 383 genes. The σE factor turns on 262 genes, including those for GerR and SpoIIID. These DNA-binding proteins downregulate almost half of the genes in the σE regulon. In addition, SpoIIID turns on ten genes, including genes involved in the appearance of σK. Next, σK activates 75 additional genes, including that for GerE. This …

The Program Of Gene Transcription For A Single Differentiating Cell Type During Sporulation In Bacillus Subtilis, Patrick Eichenberger, Masaya Fujita, Shane T. Jensen, Erin M. Conlon, David Z. Rudner, Stephanie T. Wang, Caitlin Ferguson, Koki Haga, Tsutomu Sato, Jun S. Liu, Richard Losick

Erin M. Conlon

Asymmetric division during sporulation by Bacillus subtilis generates a mother cell that undergoes a 5-h program of differentiation. The program is governed by a hierarchical cascade consisting of the transcription factors: σE, σK, GerE, GerR, and SpoIIID. The program consists of the activation and repression of 383 genes. The σE factor turns on 262 genes, including those for GerR and SpoIIID. These DNA-binding proteins downregulate almost half of the genes in the σE regulon. In addition, SpoIIID turns on ten genes, including genes involved in the appearance of σK. Next, σK activates 75 additional genes, including that for GerE. This …

Statistical Issues In The Clustering Of Gene Expression Data, Darlene R. Goldstein, Debashis Ghosh, Erin M. Conlon

Erin M. Conlon

This paper illustrates some of the problems which can occur in any data set when clustering samples of gene expression profiles. These include a possible high degree of dependence of results on choice of clustering algorithm, further dependence of results on the choices of genes and samples to be included in the clustering (for example, whether or not to include control samples), and difficulty in assessing the validity of the grouping. We also demonstrate the use of Cox regression as a tool to identify genes influencing survival.