Generalization of DNA microarray dispersion properties: microarray equivalent of t-distribution

BACKGROUND: DNA microarrays are a powerful technology that can provide a wealth of gene expression data for disease studies, drug development, and a wide scope of other investigations. Because of the large volume and inherent variability of DNA microarray data, many new statistical methods have been developed for evaluating the significance of the observed differences in gene expression. However, until now little attention has been given to the characterization of dispersion of DNA microarray data. RESULTS: Here we examine the expression data obtained from 682 Affymetrix GeneChips(® )with 22 different types and we demonstrate that the Gaussian (normal) frequency distribution is characteristic for the variability of gene expression values. However, typically 5 to 15% of the samples deviate from normality. Furthermore, it is shown that the frequency distributions of the difference of expression in subsets of ordered, consecutive pairs of genes (consecutive samples) in pair-wise comparisons of replicate experiments are also normal. We describe a consecutive sampling method, which is employed to calculate the characteristic function approximating standard deviation and show that the standard deviation derived from the consecutive samples is equivalent to the standard deviation obtained from individual genes. Finally, we determine the boundaries of probability intervals and demonstrate that the coefficients defining the intervals are independent of sample characteristics, variability of data, laboratory conditions and type of chips. These coefficients are very closely correlated with Student's t-distribution. CONCLUSION: In this study we ascertained that the non-systematic variations possess Gaussian distribution, determined the probability intervals and demonstrated that the K(α )coefficients defining these intervals are invariant; these coefficients offer a convenient universal measure of dispersion of data. The fact that the K(α )distributions are so close to t-distribution and independent of conditions and type of arrays suggests that the quantitative data provided by Affymetrix technology give "true" representation of physical processes, involved in measurement of RNA abundance. REVIEWERS: This article was reviewed by Yoav Gilad (nominated by Doron Lancet), Sach Mukherjee (nominated by Sandrine Dudoit) and Amir Niknejad and Shmuel Friedland (nominated by Neil Smalheiser)

Impact of AtNHX1, a vacuolar Na+/H+ antiporter, upon gene expression during short- and long-term salt stress in Arabidopsis thaliana

BACKGROUND: AtNHX1, the most abundant vacuolar Na(+)/H(+ )antiporter in Arabidopsis thaliana, mediates the transport of Na(+ )and K(+ )into the vacuole, influencing plant development and contributing to salt tolerance. In this report, microarray expression profiles of wild type plants, a T-DNA insertion knockout mutant of AtNHX1 (nhx1), and a 'rescued' line (NHX1::nhx1) were exposed to both short (12 h and 48 h) and long (one and two weeks) durations of a non-lethal salt stress to identify key gene transcripts associated with the salt response that are influenced by AtNHX1. RESULTS: 147 transcripts showed both salt responsiveness and a significant influence of AtNHX1. Fifty-seven of these genes showed an influence of the antiporter across all salt treatments, while the remaining genes were influenced as a result of a particular duration of salt stress. Most (69%) of the genes were up-regulated in the absence of AtNHX1, with the exception of transcripts encoding proteins involved with metabolic and energy processes that were mostly down-regulated. CONCLUSION: While part of the AtNHX1-influenced transcripts were unclassified, other transcripts with known or putative roles showed the importance of AtNHX1 to key cellular processes that were not necessarily limited to the salt stress response; namely calcium signaling, sulfur metabolism, cell structure and cell growth, as well as vesicular trafficking and protein processing. Only a small number of other salt-responsive membrane transporter transcripts appeared significantly influenced by AtNHX1

Recommendations for Science-Based Safety Assessment of Genetically Modified (GM) Plants for Food and Feed Uses

Since the commercial introduction of genetically modified (GM) plants in agriculture over two decades ago, technology developers and regulatory authorities have gained significant experience in assessing their safety based on assessing potential impact to humans, animals and the environment.  Over 3500 independent regulatory agency reviews have positively concluded on the safety of GM plants for food and feed. Yet, divergent and increased regulatory requirements have led to delayed and asynchronous approvals, and have restricted access to innovative products for farmers and consumers. With accumulated knowledge from safety assessments conducted so far, an enhanced understanding of plant genomes, and a history of safe use, it is time to re-evaluate the current approaches to the regulation of GM plants used for food and feed.  A stepwise approach using weight-of-evidence should be sufficient for the safety assessment of newly expressed proteins in GM plants.  A set of core studies including molecular characterization, expression and characterization of the newly expressed proteins (or other expression product), and safety assessment of the introduced protein are appropriate to characterize the product and assess safety.  Using data from core studies, and employing a “problem formulation” approach, the need for supplementary hypothesis-driven or case-by-case studies can be determined.  Employing this approach for the evaluation of GM plants will remove regulatory data requirements that do not provide value to the safety assessment and provide a consistent framework for global regulation. doi: 10.21423/jrs-v09i1water