A composite transcriptional signature differentiates responses towards closely related herbicides in Arabidopsis thaliana and Brassica napus.

In this study, genome-wide expression profiling based on Affymetrix ATH1 arrays was used to identify discriminating responses of Arabidopsis thaliana to five herbicides, which contain active ingredients targeting two different branches of amino acid biosynthesis. One herbicide contained glyphosate, which targets 5-enolpyruvylshikimate-3-phosphate synthase (EPSPS), while the other four herbicides contain different acetolactate synthase (ALS) inhibiting compounds. In contrast to the herbicide containing glyphosate, which affected only a few transcripts, many effects of the ALS inhibiting herbicides were revealed based on transcriptional changes related to ribosome biogenesis and translation, secondary metabolism, cell wall modification and growth. The expression pattern of a set of 101 genes provided a specific, composite signature that was distinct from other major stress responses and differentiated among herbicides targeting the same enzyme (ALS) or containing the same chemical class of active ingredient (sulfonylurea). A set of homologous genes could be identified in Brassica napus that exhibited a similar expression pattern and correctly distinguished exposure to the five herbicides. Our results show the ability of a limited number of genes to classify and differentiate responses to closely related herbicides in A. thaliana and B. napus and the transferability of a complex transcriptional signature across species.

Transcriptional profiling of mature Arabidopsis trichomes reveals that NOECK encodes the MIXTA-like transcriptional regulator MYB106.

Leaf hairs (trichomes) of Arabidopsis (Arabidopsis thaliana) have been extensively used as a model to address general questions in cell and developmental biology. Here, we lay the foundation for a systems-level understanding of the biology of this model cell type by performing genome-wide gene expression analyses. We have identified 3,231 genes that are up-regulated in mature trichomes relative to leaves without trichomes, and we compared wild-type trichomes with two mutants, glabra3 and triptychon, that affect trichome morphology and physiology in contrasting ways. We found that cell wall-related transcripts were particularly overrepresented in trichomes, consistent with their highly elaborated structure. In addition, trichome expression maps revealed high activities of anthocyanin, flavonoid, and glucosinolate pathways, indicative of the roles of trichomes in the biosynthesis of secondary compounds and defense. Interspecies comparisons revealed that Arabidopsis trichomes share many expressed genes with cotton (Gossypium hirsutum) fibers, making them an attractive model to study industrially important fibers. In addition to identifying physiological processes involved in the development of a specific cell type, we also demonstrated the utility of transcript profiling for identifying and analyzing regulatory gene function. One of the genes that are differentially expressed in fibers is the MYB transcription factor GhMYB25. A combination of transcript profiling and map-based cloning revealed that the NOECK gene of Arabidopsis encodes AtMYB106, a MIXTA-like transcription factor and homolog of cotton GhMYB25. However, in contrast to Antirrhinum, in which MIXTA promotes epidermal cell outgrowth, AtMYB106 appears to function as a repressor of cell outgrowth in Arabidopsis.

Prospective isolation of functionally distinct radial glial subtypes--lineage and transcriptome analysis.

Since the discovery of radial glia as the source of neurons, their heterogeneity in regard to neurogenesis has been described by clonal and time-lapse analysis in vitro. However, the molecular determinants specifying neurogenic radial glia differently from radial glia that mostly self-renew remain ill-defined. Here, we isolated two radial glial subsets that co-exist at mid-neurogenesis in the developing cerebral cortex and their immediate progeny. While one subset generates neurons directly, the other is largely non-neurogenic but also gives rise to Tbr2-positive basal precursors, thereby contributing indirectly to neurogenesis. Isolation of these distinct radial glia subtypes allowed determining interesting differences in their transcriptome. These transcriptomes were also strikingly different from the transcriptome of radial glia isolated at the end of neurogenesis. This analysis therefore identifies, for the first time, the lineage origin of basal progenitors and the molecular differences of this lineage in comparison to directly neurogenic and gliogenic radial glia.

Transcriptome and proteome analysis of early embryonic mouse brain development.

Mouse embryonic brain development involves sequential differentiation of multipotent progenitors into neurons and glia cells. Using microarrays and large 2-DE, we investigated the mouse brain transcriptome and proteome of embryonic days 9.5, 11.5, and 13.5. During this developmental period, neural progenitor cells shift from proliferation to neuronal differentiation. As expected, we detected numerous expression changes between all time points investigated, but interestingly, the rate of alteration remained in a similar range within 2 days of development. Furthermore, up- and down-regulation of gene products was balanced at each time point which was also seen at embryonic days 16-18. We hypothesize that during embryonic development, the rate of gene expression alteration is rather constant due to limited cellular resources such as energy, space, and free water. A similar complexity in terms of expressed genes and proteins suggests that changes in relative concentrations rather than an increase in the number of gene products dominate cellular differentiation. In general, expression of metabolism and cell cycle related gene products was down-regulated when precursor cells switched from proliferation to neuronal differentiation (days 9.5-11.5), whereas neuron specific gene products were up-regulated. A detailed functional analysis revealed their implication in differentiation related processes such as rearrangement of the actin cytoskeleton as well as Notch- and Wnt-signaling pathways.

Loss- and gain-of-function analyses reveal targets of Pax6 in the developing mouse telencephalon.

Appropriate neurogenesis and patterning of the forebrain requires the transcription factor Pax6, yet it is largely unknown how Pax6 exerts its effects at the molecular level. To characterize Pax6-mediated regulation of gene expression during murine forebrain neurogenesis, we performed microarray analysis with tissue from the dorsal Pax6-dependent telencephalon and the ventral Pax6-negative telencephalon at the onset of neurogenesis (E12) and at mid-neurogenesis (E15) in wild-type and Pax6-deficient mutant littermates. In the Pax6-deficient cortex the expression levels of various transcription factors involved in neurogenesis (like Satb2, Nfia, AP-2gamma, NeuroD6, Ngn2, Tbr2, Bhlhb5) and the retinoic acid signalling molecule Rlbp1 were reduced. Regulation by Pax6 could be confirmed upon electroporation of a Pax6- and a dominant-negative Pax6-containing vector into embryonic cortex. Taken together, our data reveal novel insights into the molecular pathways regulated by Pax6 during cortical neurogenesis. Most intriguingly, this analysis revealed time- and region-specific differences in Pax6-mediated transcription, explaining the specific function of Pax6 at early and later stages of neurogenesis.

Large-scale cis-element detection by analysis of correlated expression and sequence conservation between Arabidopsis and Brassica oleracea.

The rapidly increasing amount of plant genomic sequences allows for the detection of cis-elements through comparative methods. In addition, large-scale gene expression data for Arabidopsis (Arabidopsis thaliana) have recently become available. Coexpression and evolutionarily conserved sequences are criteria widely used to identify shared cis-regulatory elements. In our study, we employ an integrated approach to combine two sources of information, coexpression and sequence conservation. Best-candidate orthologous promoter sequences were identified by a bidirectional best blast hit strategy in genome survey sequences from Brassica oleracea. The analysis of 779 microarrays from 81 different experiments provided detailed expression information for Arabidopsis genes coexpressed in multiple tissues and under various conditions and developmental stages. We discovered candidate transcription factor binding sites in 64% of the Arabidopsis genes analyzed. Among them, we detected experimentally verified binding sites and showed strong enrichment of shared cis-elements within functionally related genes. This study demonstrates the value of partially shotgun sequenced genomes and their combinatorial use with functional genomics data to address complex questions in comparative genomics.

Tumor-associated E-cadherin mutations do not induce Wnt target gene expression, but affect E-cadherin repressors.

E-cadherin is a cell-cell adhesion molecule and tumor invasion suppressor gene that is frequently altered in human cancers. It interacts through its cytoplasmic domain with beta-catenin which in turn interacts with the Wnt (wingless) signaling pathway. We have compared the effects of different tumor-derived E-cadherin variants with those of normal E-cadherin on Wnt signaling and on genes involved in epithelial mesenchymal transition. We established an in-house cDNA microarray composed of 1105 different, sequence verified cDNA probes corresponding to 899 unique genes that represent the majority of genes known to be involved in cadherin-dependent cell adhesion and signaling ('Adhesion/Signaling Array'). The expression signatures of E-cadherin-negative MDA-MB-435S cancer cells transfected with E-cadherin variants (in frame deletions of exon 8 or 9, D8 or D9, respectively, or a point mutation in exon 8 (D370A)) were compared to that of wild-type E-cadherin (WT) transfected cells. From the differentially expressed genes, we selected 38 that we subsequently analyzed by quantitative real-time RT-PCR and/or Northern Blot. A total of 92% of these were confirmed as differentially expressed. Most of these genes encode proteins of the cytoskeleton, cadherins/integrins, oncogenes and matrix metalloproteases. No significant expression differences of genes downstream of the Wnt-pathway were found, except in E-cadherin D8 transfected cells where upregulation of three Tcf/Lef-transcribed genes was seen. One possible reason for the lack of expression differences of the Tcf/Lef-regulated genes is upregulation of SFRP1 and SFRP3; both of which are competitive inhibitors of the Wnt proteins. Interestingly, known E-cadherin transcriptional repressors, such as SLUG (SNAI2), SIP1 (ZEB2), TWIST1, SNAIL (SNAI1) and ZEB1 (TCF8), but not E12/E47 (TCF3), had a lack of upregulation in cells expressing mutated E-cadherin compared to WT. In conclusion, E-cadherin mutations have no influence on expression of genes involved in Wnt-signaling, but they may promote their own expression by blocking upregulation of E-cadherin repressors.

Optimization models for cancer classification: extracting gene interaction information from microarray expression data.

MOTIVATION: Microarray data appear particularly useful to investigate mechanisms in cancer biology and represent one of the most powerful tools to uncover the genetic mechanisms causing loss of cell cycle control. Recently, several different methods to employ microarray data as a diagnostic tool in cancer classification have been proposed. These procedures take changes in the expression of particular genes into account but do not consider disruptions in certain gene interactions caused by the tumor. It is probable that some genes participating in tumor development do not change their expression level dramatically. Thus, they cannot be detected by simple classification approaches used previously. For these reasons, a classification procedure exploiting information related to changes in gene interactions is needed. RESULTS: We propose a MAximal MArgin Linear Programming (MAMA) method for the classification of tumor samples based on microarray data. This procedure detects groups of genes and constructs models (features) that strongly correlate with particular tumor types. The detected features include genes whose functional relations are changed for particular cancer types. The proposed method was tested on two publicly available datasets and demonstrated a prediction ability superior to previously employed classification schemes. AVAILABILITY: The MAMA system was developed using the linear programming system LINDO http://www.lindo.com. A Perl script that specifies the optimization problem for this software is available upon request from the authors.

The Drosophila standard brain.

Organisms and organs come in sizes and shapes. With size, science has no problems, but how to quantify shape? How similar are two birds or two brains? This problem is particularly pressing in cases like brains where structure reflects function. The problem is not new, but satisfying solutions have yet to be worked out. For brain anatomy, no general methodology for a statistically secured quantitative description is available. Using the small brain of the fly Drosophila melanogaster, we have explored a new approach combining immunohistochemistry, high-resolution 3D confocal microscopy, and advanced graphics computing. For a genetic model organism such as Drosophila, a quantitative assessment of brain structure is particularly rewarding, since it allows for the identification of genetic variants with subtle brain structure phenotypes and, even more importantly, the organization of the wealth of gene expression patterns in the brain into a genetic atlas linking molecular and organismic gene function. We now provide a representative standard for the brain of D. melanogaster wild-type with means and variances for several aspects of its shape. Its application to volumetry, mutants, and gene expression patterns is demonstrated.