Biomedical subjects

Russell D Wolfinger

Publications and source records attributed to Russell D Wolfinger.

12 recordsLinked to original sources

PubMed2006

Evaluation of external RNA controls for the assessment of microarray performance.

External RNA controls (ERCs), although important for microarray assay performance assessment, have yet to be fully implemented in the research community. As part of the MicroArray Quality Control (MAQC) study, two types of ERCs were implemented and evaluated; one was added to the total RNA in the samples before amplification and labeling; the other was added to the copyRNAs (cRNAs) before hybridization. ERC concentration-response curves were used across multiple commercial microarray platforms to identify problematic assays and potential sources of variation in the analytical process. In addition, the behavior of different ERC types was investigated, resulting in several important observations, such as the sample-dependent attributes of performance and the potential of using these control RNAs in a combinatorial fashion. This multiplatform investigation of the behavior and utility of ERCs provides a basis for articulating specific recommendations for their future use in evaluating assay performance across multiple platforms.

Algorithms↗

PubMed2006

Performance comparison of one-color and two-color platforms within the MicroArray Quality Control (MAQC) project.

Microarray-based expression profiling experiments typically use either a one-color or a two-color design to measure mRNA abundance. The validity of each approach has been amply demonstrated. Here we provide a simultaneous comparison of results from one- and two-color labeling designs, using two independent RNA samples from the Microarray Quality Control (MAQC) project, tested on each of three different microarray platforms. The data were evaluated in terms of reproducibility, specificity, sensitivity and accuracy to determine if the two approaches provide comparable results. For each of the three microarray platforms tested, the results show good agreement with high correlation coefficients and high concordance of differentially expressed gene lists within each platform. Cumulatively, these comparisons indicate that data quality is essentially equivalent between the one- and two-color approaches and strongly suggest that this variable need not be a primary factor in decisions regarding experimental microarray design.

Equipment Design↗

PubMed2005

Model selection in binary trait locus mapping.

Quantitative trait locus (QTL) mapping methodology for continuous normally distributed traits is the subject of much attention in the literature. Binary trait locus (BTL) mapping in experimental populations has received much less attention. A binary trait by definition has only two possible values, and the penetrance parameter is restricted to values between zero and one. Due to this restriction, the infinitesimal model appears to come into play even when only a few loci are involved, making selection of an appropriate genetic model in BTL mapping challenging. We present a probability model for an arbitrary number of BTL and demonstrate that, given adequate sample sizes, the power for detecting loci is high under a wide range of genetic models, including most epistatic models. A novel model selection strategy based upon the underlying genetic map is employed for choosing the genetic model. We propose selecting the "best" marker from each linkage group, regardless of significance. This reduces the model space so that an efficient search for epistatic loci can be conducted without invoking stepwise model selection. This procedure can identify unlinked epistatic BTL, demonstrated by our simulations and the reanalysis of Oncorhynchus mykiss experimental data.

Animals↗

PubMed2005

Genome-wide transcriptional variation within and between steady states for continuous growth of the hyperthermophile Thermotoga Maritima.

Maltose-limited, continuous growth of the hyperthermophile Thermotoga maritima at different temperatures and dilution rates (80 degrees C/0.25 h(-1), 80 degrees C/0.17 h(-1), and 85 degrees C/0.25 h(-1)) showed that transcriptome-wide variation in gene expression within mechanical steady states was minimal compared to that between steady states, supporting the efficacy of chemostat-based approaches for functional genomics studies.

Bacterial Proteins↗

PubMed2004

A mixed model approach to identify yeast transcriptional regulatory motifs via microarray experiments.

A genome-wide location analysis method has been introduced as a means to simultaneously study protein-DNA binding interactions for a large number of genes on a microarray platform. Identification of interactions between transcription factors (TF) and genes provide insight into the mechanisms that regulate a variety of cellular responses. Drawing proper inferences from the experimental data is key to finding statistically significant TF-gene binding interactions. We describe how the analysis and interpretation of genome-wide location data can be fit into a traditional statistical modeling framework that considers the data across all arrays and formulizes appropriate hypothesis tests. The approach is illustrated with data from a yeast transcription factor binding experiment that illustrates how identified TF-gene interactions can enhance initial exploration of transcriptional regulatory networks. Examples of five kinds of transcriptional regulatory structure are also demonstrated. Some stark differences with previously published results are explored.

Journal Article↗

PubMed2004

Comparison of Li-Wong and loglinear mixed models for the statistical analysis of oligonucleotide arrays.

MOTIVATION: Li and Wong have described some useful statistical models for probe-level, oligonucleotide array data based on a multiplicative parametrization. In earlier work, we proposed similar analysis-of-variance-style mixed models fit on a log scale. With only subtle differences in the specification of their mean and stochastic error components, a question arises as to whether these models could lead to varying conclusions in practical application. RESULTS: In this paper, we provide an empirical comparison of the two models using a real data set, and find the models perform quite similarly across most genes, but with some interesting and important distinctions. We also present results from a simulation study designed to assess inferential properties of the models, and propose a modified test statistic for the Li-Wong model that provides an improvement in Type 1 error control. Advantages of both methods include the ability to directly assess and account for key sources of variability in the chip data and a means to automate statistical quality control.

Algorithms↗

PubMed2004

Ordinary differential equation PK/PD models using the SAS macro NLINMIX.

We describe some theory and recent enhancements for the SAS macro NLINMIX (Wolfinger, R. D. (1993). Laplace's approximation for nonlinear mixed effects models. Biometrika 80:791-795) that enable model calculation to take place within the interaction matrix language SAS/IML (SAS Institute Inc. (1999a). SAS/IML User's Guide Version 7. Cary, NC: SAS Institute Inc.). They provide greater flexibility and scope for the specification and analysis of complex nonlinear mixed models. For example, using data from a frequently sampled intravenous glucose test, we fit a two-compartment kinetics model that has no closed-form representation. It is derived as the solution of a system of ordinary differential equations and specified as such in SAS/IML. Additional details and example NLINMIX code are available in Appendix A.

Humans↗

PubMed2003

Spatial prediction of counts and rates.

In this paper we provide both theoretical and empirical comparisons of marginal and conditional methods for analysing spatial count data. We focus on methods for spatial prediction developed from a generalized linear mixed model framework and compare them with the traditional linear (kriging) predictor. Prediction methods are illustrated and compared through a case study based on real data and through a detailed simulation study. The paper emphasizes a better understanding of the strengths and weaknesses of each approach.

Computer Simulation↗

PubMed2003

Consequences of reductive evolution for gene expression in an obligate endosymbiont.

The smallest cellular genomes are found in obligate symbiotic and pathogenic bacteria living within eukaryotic hosts. In comparison with large genomes of free-living relatives, these reduced genomes are rearranged and have lost most regulatory elements. To test whether reduced bacterial genomes incur reduced regulatory capacities, we used full-genome microarrays to evaluate transcriptional response to environmental stress in Buchnera aphidicola, the obligate endosymbiont of aphids. The 580 genes of the B. aphidicola genome represent a subset of the 4500 genes known from the related organism, Escherichia coli. Although over 20 orthologues of E. coli heat stress (HS) genes are retained by B. aphidicola, only five were differentially expressed after near-lethal heat stress treatments, and only modest shifts were observed. Analyses of upstream regulatory regions revealed loss or degradation of most HS (sigma32) promoters. Genomic rearrangements downstream of an intact HS promoter yielded upregulation of a functionally unrelated and an inactivated gene. Reanalyses of comparable experimental array data for E. coli and Bacillus subtilis revealed that genome-wide differential expression was significantly lower in B. aphidicola. Our demonstration of a diminished stress response validates reports of temperature sensitivity in B. aphidicola and suggests that this reduced bacterial genome exhibits transcriptional inflexibility.

Amino Acid Sequence↗

PubMed2003

Mixed-model reanalysis of primate data suggests tissue and species biases in oligonucleotide-based gene expression profiles.

An emerging issue in evolutionary genetics is whether it is possible to use gene expression profiling to identify genes that are associated with morphological, physiological, or behavioral divergence between species and whether these genes have undergone positive selection. Some of these questions were addressed in a recent study (Enard et al. 2002) of the difference in gene expression among human, chimp, and orangutan, which suggested an accelerated rate of divergence in gene expression in the human brain relative to liver. Reanalysis of the Affymetrix data set using analysis of variance methods to quantify the contributions of individuals and species to variation in expression of 12,600 genes indicates that as much as one-quarter of the genome shows divergent expression between primate species at the 5% level. The magnitude of fold change ranges from 1.2-fold up to 8-fold. Similar conclusions apply to reanalysis of Enard et al. 2002 parallel murine data set. However, biases inherent to short oligonucleotide microarray technology may account for some of the tissue and species effects. At high significance levels, more differences were observed in the liver than in the brain in each of the pairwise species comparisons, so it is not clear that expression divergence is accelerated in the human brain. Further, there is an apparent bias toward upregulation of gene expression in the brain in both primates and mice, whereas genes are equally likely to be up- or downregulated in the liver when these species diverge. A small subset of genes that are candidates for adaptive divergence may be identified on the basis of a high ratio of interspecific to intraspecific divergence.

Animals↗

PubMed2003

A prototype system for retrieval of gene functional information.

Microarrays allow researchers to gather data about the expression patterns of thousands of genes simultaneously. Statistical analysis can reveal which genes show statistically significant results. Making biological sense of those results requires the retrieval of functional information about the genes thus identified, typically a manual gene-by-gene retrieval of information from various on-line databases. For experiments generating thousands of genes of interest, retrieval of functional information can become a significant bottleneck. To address this issue, we are currently developing a prototype system to automate the process of retrieval of functional information from multiple on-line sources.

Animals↗

PubMed2002

Carbohydrate-induced differential gene expression patterns in the hyperthermophilic bacterium Thermotoga maritima.

The hyperthermophilic bacterium Thermotoga maritima MSB8 was grown on a variety of carbohydrates to determine the influence of carbon and energy source on differential gene expression. Despite the fact that T. maritima has been phylogenetically characterized as a primitive microorganism from an evolutionary perspective, results here suggest that it has versatile and discriminating mechanisms for regulating and effecting complex carbohydrate utilization. Growth of T. maritima on monosaccharides was found to be slower than growth on polysaccharides, although growth to cell densities of 10(8) to 10(9) cells/ml was observed on all carbohydrates tested. Differential expression of genes encoding carbohydrate-active proteins encoded in the T. maritima genome was followed using a targeted cDNA microarray in conjunction with mixed model statistical analysis. Coordinated regulation of genes responding to specific carbohydrates was noted. Although glucose generally repressed expression of all glycoside hydrolase genes, other sugars induced or repressed these genes to varying extents. Expression profiles of most endo-acting glycoside hydrolase genes correlated well with their reported biochemical properties, although exo-acting glycoside hydrolase genes displayed less specific expression patterns. Genes encoding selected putative ABC sugar transporters were found to respond to specific carbohydrates, and in some cases putative oligopeptide transporter genes were also found to respond to specific sugar substrates. Several genes encoding putative transcriptional regulators were expressed during growth on specific sugars, thus suggesting functional assignments. The transcriptional response of T. maritima to specific carbohydrate growth substrates indicated that sugar backbone- and linkage-specific regulatory networks are operational in this organism during the uptake and utilization of carbohydrate substrates. Furthermore, the wide ranging collection of such networks in T. maritima suggests that this organism is capable of adapting to a variety of growth environments containing carbohydrate growth substrates.

Carbohydrate Metabolism↗