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Sharron G Penn

Publications and source records attributed to Sharron G Penn.

5 recordsLinked to original sources

Gene expression analysis in response to lung toxicants: I. Sequencing and microarray development.

A key challenge in measuring gene expression changes in the lung in response to site-selective toxicants is differentiating between target and nontarget areas. The toxicity for the cytotoxicant 1-nitronaphthalene is highly localized in the airway epithelium. Target cells comprise but a fraction of the total lung cell mass; measurements from whole lung homogenates are not likely to reflect what occurs at the target site. Additionally, the use of generic microarrays to measure expression in airway epithelium may not provide a good representation of transcripts present at the site of toxic action. cDNA libraries from airway and alveolar subcompartments of rat lung were sequenced for the development of a custom microarray representative of these lung regions. We identified 7,460 nonredundant rat lung sequences. Nearly 30% of the sequences on this array are not present on the Affymetrix Rat GeneChip 230. A 20,000-element microarray was developed that delineates differences in gene expression between subcompartments. This is the first in a series of articles employing this microarray for detecting gene expression changes during acute injury produced by 1-nitronaphthalene and subsequent repair.

Animals↗

A conditional density error model for the statistical analysis of microarray data.

MOTIVATION: In many microarray experiments, relatively few intra- and inter-array replicate measurements are made due to significant cost limitations and sample availability. Compounding this problem is a lack of robust statistical methods for analyzing gene expression data with limited experimental replicates. As a result, the interpretation of the results of these experiments are difficult with little understanding of the probability of type I and type II errors. RESULTS: The variability in a series of replicate microarray measurements was modelled using a combination of parametric and non-parametric methods. A 3-dimensional surface was created for the conditional distribution of the variability given the mean signal intensity in both the Cy3 and Cy5 channels. The results were used as the basis for developing statistical methods for analyzing gene expression data with limited experimental replicates. AVAILABILITY: The statistical analysis scripts are available upon request.

Computer Simulation↗

Sequence variation and phylogenetic history of the mouse Ahr gene.

The Ahr locus encodes for the aryl hydrocarbon receptor (AHR), which plays an important toxicological and developmental role. Sequence variation in this gene was studied in 13 different mouse lines that included eight laboratory strains, two Mus musculus subspecies and three additional Mus species. The data presented represent the largest study of sequence variation across multiple mouse lines in a single gene (approximately equal to 15.9 kb/mouse line). Among all mice, the average frequency of all polymorphisms in the intronic regions was 20.3 variants/kb and the average exonic frequency was 14.1 variants/kb. For substitutions alone, the average frequencies in the intronic and exonic regions for all mice were 13.3 and 8.9 substitutions/kb, respectively. Between laboratory strains, the average intronic and exonic frequencies for all polymorphisms dropped to 5.4 and 2.9 variants/kb, respectively. There were 111 non-synonymous polymorphisms that resulted in 42 different amino acid changes, of which only 10 amino acid changes had been previously identified. Based on the nucleotide sequence, the phylogenetic history of the gene showed mice from the Ahr(b2) and Ahr(d) alleles in separate branches while mice from the Ahr(b1) and Ahr(b3) alleles exhibited a more complex history. Evolutionarily, the AHR protein as a whole appears to be under purifying selective pressure (K(a) : K(s) ratio = 0.237). Despite significant functional constraint in the basic helix-loop-helix and PAS domains, ligand binding is not constrained to the high-affinity allele, which supports further the role of the AHR in development and its importance beyond the adaptive response to environmental toxicants.

Amino Acid Sequence↗

Application of genomics to toxicology research.

Traditional models of toxicity have relied on dissecting chemical action into pharmacokinetic and pharmacodynamic processes. However, the integration of genomic information with toxicology will enhance our basic understanding of these processes and significantly change the way we apply toxicological information to risk assessment and regulatory problems. In this article, we summarize the application of gene expression information and polymorphism discovery to four areas in toxicology: toxicity testing, cross-species extrapolation, understanding mechanism of action, and susceptibility.

Animals↗