Rice histone deacetylase genes display specific expression patterns and developmental functions

Histone deacetylases (HDAC) are important in plant gene expression. Here we show that the expression of rice HDAC genes is both tissue/organ-specific, and most of them are responsive to drought or salt stresses. Over-expression of several rice HDACs did not produce any visible phenotype, whereas down-regulation of a few HDAC genes affected different developmental aspects. Specifically, down-regulation of HDA703 by amiRNA reduced rice peduncle elongation and fertility, while inactivation of a closely related homolog HDA710 by RNAi affected vegetative growth. HDA704 RNAi altered plant height and flag leaf morphology. Down-regulation of HDT702 led to the production of narrowed leaves and stems. These data suggest that rice HDAC genes may have divergent developmental functions compared with closely related homologs in Arabidopsis.     

Three sea urchin actin genes show different patterns of expression: muscle specific, embryo specific, and constitutive.

The expression of three different actin genes in the sea urchin, Strongylocentrotus purpuratus, was monitored in embryos and adult tissues by using untranslated mRNA sequences as specific hybridization probes. Three distinct patterns of expression were found: muscle specific, embryo specific, and constitutive (i.e., present in all tissues examined). The actin genes encoding the muscle-specific and constitutively expressed genes were each found to be present once in the haploid genome. The embryo-specific probe could derive from either a single gene or a small subset of actin genes. These data demonstrate that at least three members of the sea urchin actin gene family are expressed in distinct ways and thus are probably associated with different regulatory programs of gene expression necessary for development of this metazoan.     

Differential expression of specific sulphate transporters underlies seasonal and spatial patterns of sulphate allocation in trees

Sulphate uptake and its distribution within plants depend on the activity of different sulphate transporters (SULTR). In long‐living deciduous plants such as trees, seasonal changes of spatial patterns add another layer of complexity to the question of how the interplay of different transporters adjusts S distribution within the plant to environmental changes. Poplar is an excellent model to address this question because its S metabolism is already well characterized. In the present study, the importance of SULTRs for seasonal sulphate storage and mobilization was examined in the wood of poplar (Populus tremula × P. alba) by analysing their gene expression in relation to sulphate contents in wood and xylem sap. According to these results, possible functions of the respective SULTRs for seasonal sulphate storage and mobilization in the wood are suggested. Together, the present results complement the previously published model for seasonal sulphate circulation between leaves and bark and provide information for future mechanistic modelling of whole tree sulphate fluxes.     

Virulence genes of the phytopathogen Rhodococcus fascians show specific spatial and temporal expression patterns during plant infection

The phytopathogenic bacterium Rhodococcus fascians provokes shoot meristem formation and malformations on aerial plant parts, mainly at the axils. The interaction is accompanied by bacterial colonization of the plant surface and tissues. Upon infection, the two bacterial loci required for full virulence, fas and att, were expressed only at the sites of symptom development, although their expression profiles differed both spatially and temporally. The att locus was expressed principally in bacteria located on the plant surface at early stages of infection. Expression of the fas locus occurred throughout infection, mainly in bacteria that were penetrating, or had penetrated, the plant tissues and coincided with sites of meristem initiation and proliferation. The implications for the regulation of virulence genes of R. fascians during plant infection are discussed.     

Isoenzyme patterns of nodules from specific legume-Rhizobium combinations

Summary Plant genera and some bacterial-plant combinations are identifiable by the starch gel electrophoretic patterns of the enzymes studied, but no differences were obtained between plant species and variety.     

Overlapping and specific patterns of GDNF,c-ret and GFR alpha mRNA expression in the developing chicken retina

GDNF and the GDNF receptors, c-Ret, GFR alpha 1 and 2 mRNA is expressed in the developing chicken retina. GDNF labelling was mainly found in embryonic day 4-5 retina but weak labelling could also be found over scattered retinal cells at later stages. c-ret labelling was found over ganglion cells, amacrine and horizontal cells; the preferred GDNF receptor (GFR alpha 1) over amacrine and horizontal cells; and the less preferred GDNF receptor (GFR alpha 2) over ganglion cells, amacrine cells and photoreceptors.     

Clustering gene expression patterns.

Recent advances in biotechnology allow researchers to measure expression levels for thousands of genes simultaneously, across different conditions and over time. Analysis of data produced by such experiments offers potential insight into gene function and regulatory mechanisms. A key step in the analysis of gene expression data is the detection of groups of genes that manifest similar expression patterns. The corresponding algorithmic problem is to cluster multicondition gene expression patterns. In this paper we describe a novel clustering algorithm that was developed for analysis of gene expression data. We define an appropriate stochastic error model on the input, and prove that under the conditions of the model, the algorithm recovers the cluster structure with high probability. The running time of the algorithm on an n-gene dataset is O[n2[log(n)]c]. We also present a practical heuristic based on the same algorithmic ideas. The heuristic was implemented and its performance is demonstrated on simulated data and on real gene expression data, with very promising results.     

Tumor-specific gene expression patterns with gene expression profiles

Gene expression profiles of 14 common tumors and their counterpart normal tissues were analyzed with machine learning methods to address the problem of selection of tumor-specific genes and analysis of their differential expressions in tumor tissues. First, a variation of the Relief algorithm, "RFE_Relief algorithm" was proposed to learn the relations between genes and tissue types. Then, a support vector machine was employed to find the gene subset with the best classification performance for distinguishing cancerous tissues and their counterparts. After tissue-specific genes were removed, cross validation experiments were employed to demonstrate the common deregulated expressions of the selected gene in tumor tissues. The results indicate the existence of a specific expression fingerprint of these genes that is shared in different tumor tissues, and the hallmarks of the expression patterns of these genes in cancerous tissues are summarized at the end of this paper.     

Tumor-specific gene expression patterns with gene expression profiles

Gene expression profiles of 14 common tumors and their counterpart normal tissues were analyzed with machine learning methods to address the problem of selection of tumor-specific genes and analysis of their differential expressions in tumor tissues. First, a variation of the Relief algorithm, “RFE_Relief algorithm” was proposed to learn the relations between genes and tissue types. Then, a support vector machine was employed to find the gene subset with the best classification performance for distinguishing cancerous tissues and their counterparts. After tissue-specific genes were removed, cross validation experiments were employed to demonstrate the common deregulated expressions of the selected gene in tumor tissues. The results indicate the existence of a specific expression fingerprint of these genes that is shared in different tumor tissues, and the hallmarks of the expression patterns of these genes in cancerous tissues are summarized at the end of this paper.     

Differential transgene expression patterns in Alzheimer mouse models revealed by novel human amyloid precursor protein‐specific antibodies

Alzheimer's disease (AD) is histopathologically characterized by neurodegeneration, the formation of intracellular neurofibrillary tangles and extracellular Aβ deposits that derive from proteolytic processing of the amyloid precursor protein (APP). As rodents do not normally develop Aβ pathology, various transgenic animal models of AD were designed to overexpress human APP with mutations favouring its amyloidogenic processing. However, these mouse models display tremendous differences in the spatial and temporal appearance of Aβ deposits, synaptic dysfunction, neurodegeneration and the manifestation of learning deficits which may be caused by age‐related and brain region‐specific differences in APP transgene levels. Consequentially, a comparative temporal and regional analysis of the pathological effects of Aβ in mouse brains is difficult complicating the validation of therapeutic AD treatment strategies in different mouse models. To date, no antibodies are available that properly discriminate endogenous rodent and transgenic human APP in brains of APP‐transgenic animals. Here, we developed and characterized rat monoclonal antibodies by immunohistochemistry and Western blot that detect human but not murine APP in brains of three APP‐transgenic mouse and one APP‐transgenic rat model. We observed remarkable differences in expression levels and brain region‐specific expression of human APP among the investigated transgenic mouse lines. This may explain the differences between APP‐transgenic models mentioned above. Furthermore, we provide compelling evidence that our new antibodies specifically detect endogenous human APP in immunocytochemistry, FACS and immunoprecipitation. Hence, we propose these antibodies as standard tool for monitoring expression of endogenous or transfected APP in human cells and APP expression in transgenic animals.     

Gene expression patterns associated with caste and reproductive status in ants: worker‐specific genes are more derived than queen‐specific ones

Variation in gene expression leads to phenotypic diversity and plays a central role in caste differentiation of eusocial insect species. In social Hymenoptera, females with the same genetic background can develop into queens or workers, which are characterized by divergent morphologies, behaviours and lifespan. Moreover, many social insects exhibit behaviourally distinct worker castes, such as brood‐tenders and foragers. Researchers have just started to explore which genes are differentially expressed to achieve this remarkable phenotypic plasticity. Although the queen is normally the only reproductive individual in the nest, following her removal, young brood‐tending workers often develop ovaries and start to reproduce. Here, we make use of this ability in the ant Temnothorax longispinosus and compare gene expression patterns in the queens and three worker castes along a reproductive gradient. We found the largest expression differences between the queen and the worker castes (~2500 genes) and the smallest differences between infertile brood‐tenders and foragers (~300 genes). The expression profile of fertile workers is more worker‐like, but to a certain extent intermediate between the queen and the infertile worker castes. In contrast to the queen, a high number of differentially expressed genes in the worker castes are of unknown function, pointing to the derived status of hymenopteran workers within insects.