Biomedical subjects

Martin Neeb

Publications and source records attributed to Martin Neeb.

3 recordsLinked to original sources

PubMed2003

Analysis of the eye developmental pathway in Drosophila using DNA microarrays.

Pax-6 genes encode evolutionarily conserved transcription factors capable of activating the gene-expression program required to build an eye. When ectopically expressed in Drosophila imaginal discs, Pax-6 genes induce the eye formation on the corresponding appendages of the adult fly. We used two different Drosophila full-genome DNA microarrays to compare gene expression in wild-type leg discs versus leg discs where eyeless, one of the two Drosophila Pax-6 genes, was ectopically expressed. We validated these data by analyzing the endogenous expression of selected genes in eye discs and identified 371 genes that are expressed in the eye imaginal discs and up-regulated when an eye morphogenetic field is ectopically induced in the leg discs. These genes mainly encode transcription factors involved in photoreceptor specification, signal transducers, cell adhesion molecules, and proteins involved in cell division. As expected, genes already known to act downstream of eyeless during eye development were identified, together with a group of genes that were not yet associated with eye formation.

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PubMed2003

Statistical methods for analyzing microarray feature data with replications.

Expression levels in oligonucleotide microarray experiments depend on a potentially large number of factors, for example, treatment conditions, different probes, different arrays, and so on. To dissect the effects of these factors on expression levels, fixed-effects ANOVA methods have previously been proposed. Because we are not necessarily interested in estimating the specific effects of different probes and arrays, we propose to treat these as random effects. Then we only need to estimate their means and variances but not the effect of each of their levels; that is, we can work with a much reduced number of parameters and, consequently, higher precision for estimating expression levels. Thus, we developed a mixed-effects ANOVA model with some random and some fixed effects. It automatically accounts for local normalization between different arrays and for background correction. The method was applied to each of the 6,584 genes investigated in a microarray experiment on two mouse cell lines, PA6/S and PA6/8, where PA6/S enhances proliferation of Pre B cells in vitro but PA6/8 does not. To detect a set of differentially expressed genes (multiple testing problem), we applied the method of controlling the false discovery rate (FDR), which successfully identified 207 genes with significantly different expression levels.

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PubMed2002

Changes in gene expression profiles in developing B cells of murine bone marrow.

Gene expression profiles of five consecutive stages of mouse B cell development were generated with high-density oligonucleotide arrays from as few as 2 x 10(4) ex vivo isolated and flow-cytometrically purified cells. Between 2.8% and 6.8% of all genes change on differentiation from one cellular stage to the next by at least twofold. The entire pathway involves differential expression of 10.7% of all genes. Previously known expression patterns of 15 genes (like surrogate light chain, RAG-1/2, MHC class II, mel-14 antigen) are confirmed. The gene expression patterns of the proliferating pre-BI and large pre-BII cells on the one hand, and the resting immature and mature B cells on the other hand, are most similar to each other. Small pre-BII cells display a pattern that is transitional between these two groups. Most of the genes expressed in early precursors are involved in general processes, like protein folding or cell cycle regulation, whereas more mature precursors express genes involved in more specific molecular programs (cell surface receptors, secreted factors, and adhesion molecules, among others). Between 19 and 139 genes share a given expression pattern. Combining knowledge about gene function and expression pattern allows identification of novel candidate genes potentially involved in self-maintenance of pre-BI cells, allelic exclusion and pre-B cell receptor signaling in large pre BII cells, cell-cycle arrest of small pre-BII cells, propensity toward apoptosis or anergization in immature B cells, propensity toward cell division and activation in mature B cells, and stage-specific interactions with stromal cells in the bone marrow.

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