Global rank-invariant set normalization (GRSN) to reduce systematic distortions in microarray data

<p>Abstract</p> <p>Background</p> <p>Microarray technology has become very popular for globally evaluating gene expression in biological samples. However, non-linear variation associated with the technology can make data interpretation unreliable. Therefore, methods to correct this kind of technical variation are critical. Here we consider a method to reduce this type of variation applied after three common procedures for processing microarray data: MAS 5.0, RMA, and dChip^®.</p> <p>Results</p> <p>We commonly observe intensity-dependent technical variation between samples in a single microarray experiment. This is most common when MAS 5.0 is used to process probe level data, but we also see this type of technical variation with RMA and dChip^®processed data. Datasets with unbalanced numbers of up and down regulated genes seem to be particularly susceptible to this type of intensity-dependent technical variation. Unbalanced gene regulation is common when studying cancer samples or genetically manipulated animal models and preservation of this biologically relevant information, while removing technical variation has not been well addressed in the literature. We propose a method based on using rank-invariant, endogenous transcripts as reference points for normalization (GRSN). While the use of rank-invariant transcripts has been described previously, we have added to this concept by the creation of a global rank-invariant set of transcripts used to generate a robust average reference that is used to normalize all samples within a dataset. The global rank-invariant set is selected in an iterative manner so as to preserve unbalanced gene expression. Moreover, our method works well as an overlay that can be applied to data already processed with other probe set summary methods. We demonstrate that this additional normalization step at the "probe set level" effectively corrects a specific type of technical variation that often distorts samples in datasets.</p> <p>Conclusion</p> <p>We have developed a simple post-processing tool to help detect and correct non-linear technical variation in microarray data and demonstrate how it can reduce technical variation and improve the results of downstream statistical gene selection and pathway identification methods.</p

The PI3K/Akt1 pathway enhances steady-state levels of FANCL

Fanconi anemia hematopoietic stem cells display poor self-renewal capacity when subjected to a variety of cellular stress. This phenotype raises the question of whether the Fanconi anemia proteins are stabilized or recruited as part of a stress response and protect against stem cell loss. Here we provide evidence that FANCL, the E3 ubiquitin ligase of the Fanconi anemia pathway, is constitutively targeted for degradation by the proteasome. We confirm biochemically that FANCL is polyubiquitinated with Lys-48-linked chains. Evaluation of a series of N-terminal-deletion mutants showed that FANCL's E2-like fold may direct ubiquitination. In addition, our studies showed that FANCL is stabilized in a complex with axin1 when glycogen synthase kinase-3β is overexpressed. This result leads us to investigate the potential regulation of FANCL by upstream signaling pathways known to regulate glycogen synthase kinase-3β. We report that constitutively active, myristoylated-Akt increases FANCL protein level by reducing polyubiquitination of FANCL. Two-dimensional PAGE analysis shows that acidic forms of FANCL, some of which are phospho-FANCL, are not subject to polyubiquitination. These results indicate that a signal transduction pathway involved in self-renewal and survival of hematopoietic stem cells also functions to stabilize FANCL and suggests that FANCL participates directly in support of stem cell function

Discovering early molecular determinants of leukemogenesis

Truncating mutations of the G-CSF receptor are found during disease course in nearly half of all patients with severe congenital neutropenia. In this issue of the JCI, Liu et al. demonstrate that these mutations confer a competitive clonal advantage upon HSCs in mice and that the advantage is conditional because it is observed only in the presence of the ligand G-CSF (see the related article beginning on page 946). Once activated, the mutant receptor requires the function of Stat5 in order to effect clonal expansion of this stem cell population. The results support the notion that early molecular steps in this and other neoplastic processes represent adaptations in which, through somatic mutations, “unfit” stem cells gain a measure of fitness by altering their relationships with their microenvironment