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Olen E Domon

Publications and source records attributed to Olen E Domon.

2 recordsLinked to original sources

Dye bias correction in dual-labeled cDNA microarray gene expression measurements.

A significant limitation to the analytical accuracy and precision of dual-labeled spotted cDNA microarrays is the signal error due to dye bias. Transcript-dependent dye bias may be due to gene-specific differences of incorporation of two distinctly different chemical dyes and the resultant differential hybridization efficiencies of these two chemically different targets for the same probe. Several approaches were used to assess and minimize the effects of dye bias on fluorescent hybridization signals and maximize the experimental design efficiency of a cell culture experiment. Dye bias was measured at the individual transcript level within each batch of simultaneously processed arrays by replicate dual-labeled split-control sample hybridizations and accounted for a significant component of fluorescent signal differences. This transcript-dependent dye bias alone could introduce unacceptably high numbers of both false-positive and false-negative signals. We found that within a given set of concurrently processed hybridizations, the bias is remarkably consistent and therefore measurable and correctable. The additional microarrays and reagents required for paired technical replicate dye-swap corrections commonly performed to control for dye bias could be costly to end users. Incorporating split-control microarrays within a set of concurrently processed hybridizations to specifically measure dye bias can eliminate the need for technical dye swap replicates and reduce microarray and reagent costs while maintaining experimental accuracy and technical precision. These data support a practical and more efficient experimental design to measure and mathematically correct for dye bias.

Cell Culture Techniques↗

Alterations in gene expression profiles and the DNA-damage response in ionizing radiation-exposed TK6 cells.

Identifying genes that are differentially expressed in response to DNA damage may help elucidate markers for genetic damage and provide insight into the cellular responses to specific genotoxic agents. We utilized cDNA microarrays to develop gene expression profiles for ionizing radiation-exposed human lymphoblastoid TK6 cells. In order to relate changes in the expression profiles to biological responses, the effects of ionizing radiation on cell viability, cloning efficiency, and micronucleus formation were measured. TK6 cells were exposed to 0.5, 1, 5, 10, and 20 Gy ionizing radiation and cultured for 4 or 24 hr. A significant (P < 0.0001) decrease in cloning efficiency was observed at all doses at 4 and 24 hr after exposure. Flow cytometry revealed significant decreases in cell viability at 24 hr in cells exposed to 5 (P < 0.001), 10 (P < 0.0001), and 20 Gy (P < 0.0001). An increase in micronucleus frequency occurred at both 4 and 24 hr at 0.5 and 1 Gy; however, insufficient binucleated cells were present for analysis at the higher doses. Gene expression profiles were developed from mRNA isolated from cells exposed to 5, 10, and 20 Gy using a 350 gene human cDNA array platform. Overall, more genes were differentially expressed at 24-hr than at the 4-hr time point. The genes upregulated (> 1.5-fold) or downregulated (< 0.67-fold) at 4 hr were those primarily involved in the cessation of the cell cycle, cellular detoxification pathways, DNA repair, and apoptosis. At 24 hr, glutathione-associated genes were induced in addition to genes involved in apoptosis. Genes involved in cell cycle progression and mitosis were downregulated at 24 hr. Real-time quantitative PCR was used to confirm the microarray results and to evaluate expression levels of selected genes at the low doses (0.5 and 1.0 Gy). The expression profiles reflect the cellular and molecular responses to ionizing radiation related to the recognition of DNA damage, a halt in progression through the cell cycle, activation of DNA-repair pathways, and the promotion of apoptosis.

Analysis of Variance↗