Gene Regulation and Systems Biology
Synopsis: An open access, peer reviewed electronic journal that covers regulation of genes and proteins they encode and the broader field of systems biology.
Indexing: 8 major databases. Pubmed indexing for NIH-funded research.
Processing time: Decision in 2 weeks for 90% of papers.
Latest news:
Variability of DNA Microarray Gene Expression Profiles in Cultured Rat Primary Hepatocytes
Jun Xu1, Xutao Deng1,2, Victor Chan3, Nancy Kelley-Loughnane4, Brent W Harker5, Leming Shi6, Saber M. Hussain7, John M. Frazier7 and Charles Wang1,2
1Department of Medicine and Burns and Allen Research Institute, Cedars-Sinai Medical Center, Los Angeles, CA 90048; 2David Geffen School of Medicine at UCLA, Los Angeles, CA 90048; 3Alion Science and Technology, Inc., Dayton, OH, 45433; 4Geo-Centers, Inc., WPAFB, OH 45433; 5Center for Tropical Disease Research and Training, University of Notre Dame, Notre Dame, IN 46556; 6National Center for Toxicological Research, U.S. FDA, Jefferson, AR 72079; 7U.S. Air Force Research Laboratory, WPAFB, OH 45433.
Abstract: DNA microarray is a powerful tool in biomedical research. However, transcriptomic profiling using DNA microarray is subject to many variations including biological variability. To evaluate the different sources of variation in mRNA gene expression profiles, gene expression profiles were monitored using the Affymetrix RatTox U34 arrays in cultured primary hepatocytes derived from six rats over a 26 hour period at 6 time points (0h, 2h, 5h, 8h, 14h and 26h) with two replicate arrays at each time point for each animal. In addition, the impact of sample size on the variability of differentially expressed gene lists and the consistency of biological responses were also investigated. Excellent intra-animal reproducibility was obtained at all time points with 0 out of 370 present probe sets across all time points showing significant difference between the 2 replicate arrays (3-way ANOVA, p 0.0001). However, large inter-animal biological variation in mRNA expression profi les was observed with 337 out of 370 present probe sets showing significant differences among 6 animals (3-way ANOVA, p 0.05). Principal Component Analysis (PCA) revealed that time effect (PC1) in this data set accounted for 47.4% of total variance indicating the dynamics of transcriptomics. The second and third largest effects came from animal difference, which accounted for 16.9% (PC2 and PC3) of the total variance. The reproducibility of gene lists and their functional classification was declined considerably when the sample size was decreased. Overall, our results strongly support that there is significant inter-animal variability in the time-course gene expression profi les, which is a confounding factor that must be carefully evaluated to correctly interpret microarray gene expression studies. The consistency of the gene lists and their biological functional classification are also sensitive to sample size with the reproducibility decreasing considerably under small sample size.
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Gene Regulation and Systems Biology
James Willey, Editor in Chief
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