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The control of gene expression by transcriptional regulators and other types of functionally relevant DNA transactions such as chromatin remodeling and replication underlie a vast spectrum of biological processes in all organisms. DNA transactions require the controlled interaction of proteins with DNA sequence motifs which are often located in nucleosome-depleted regions (NDRs) of the chromatin. Formaldehyde-assisted isolation of regulatory elements (FAIRE) has been established as an easy-to-implement method for the isolation of NDRs from a number of eukaryotic organisms, and it has been successfully employed for the discovery of new regulatory segments in genomic DNA from, for example, yeast, Drosophila, and humans. Until today, however, FAIRE has only rarely been employed in plant research and currently no detailed FAIRE protocol for plants has been published. Here, we provide a step-by-step FAIRE protocol for NDR discovery in Arabidopsis thaliana. We demonstrate that NDRs isolated from plant chromatin are readily amenable to quantitative polymerase chain reaction and next-generation sequencing. Only minor modification of the FAIRE protocol will be needed to adapt it to other plants, thus facilitating the global inventory of regulatory regions across species.
Recent high-throughput technologies enable the acquisition of a variety of complementary data and imply regulatory networks on the systems biology level. A common approach to the reconstruction of such networks is the cluster analysis which is based on a similarity measure. We use the information theoretic concept of the mutual information, that has been originally defined for discrete data, as a measure of similarity and propose an extension to a commonly applied algorithm for its calculation from continuous biological data. We compare our approach to previously existing algorithms. We develop a performance optimised software package for the application of the mutual information to large-scale datasets. Furthermore, we design and implement a web-based service for the analysis of integrated data measured with different technologies. Application to biological data reveals biologically relevant groupings and reconstructed signalling networks show agreements with physiological findings.
Recent advances in high-throughput omics techniques render it possible to decode the function of genes by using the "guilt-by-association" principle on biologically meaningful clusters of gene expression data. However, the existing frameworks for biological evaluation of gene clusters are hindered by two bottleneck issues: (1) the choice for the number of clusters, and (2) the external measures which do not take in consideration the structure of the analyzed data and the ontology of the existing biological knowledge. Here, we address the identified bottlenecks by developing a novel framework that allows not only for biological evaluation of gene expression clusters based on existing structured knowledge, but also for prediction of putative gene functions. The proposed framework facilitates propagation of statistical significance at each of the following steps: (1) estimating the number of clusters, (2) evaluating the clusters in terms of novel external structural measures, (3) selecting an optimal clustering algorithm, and (4) predicting gene functions. The framework also includes a method for evaluation of gene clusters based on the structure of the employed ontology. Moreover, our method for obtaining a probabilistic range for the number of clusters is demonstrated valid on synthetic data and available gene expression profiles from Saccharomyces cerevisiae. Finally, we propose a network-based approach for gene function prediction which relies on the clustering of optimal score and the employed ontology. Our approach effectively predicts gene function on the Saccharomyces cerevisiae data set and is also employed to obtain putative gene functions for an Arabidopsis thaliana data set.
Polynucleobacter asymbioticus strain QLW-P1DMWA-1T represents a group of highly successful heterotrophic ultramicrobacteria that is frequently very abundant (up to 70% of total bacterioplankton) in freshwater habitats across all seven continents. This strain was originally isolated from a shallow Alpine pond characterized by rapid changes in water temperature and elevated UV radiation due to its location at an altitude of 1300 m. To elucidate the strain’s adjustment to fluctuating environmental conditions, we recorded changes occurring in its transcriptomic and proteomic profiles under contrasting experimental conditions by simulating thermal conditions in winter and summer as well as high UV irradiation. To analyze the potential connection between gene expression and regulation via methyl group modification of the genome, we also analyzed its methylome. The methylation pattern differed between the three treatments, pointing to its potential role in differential gene expression. An adaptive process due to evolutionary pressure in the genus was deduced by calculating the ratios of non-synonymous to synonymous substitution rates for 20 Polynucleobacter spp. genomes obtained from geographically diverse isolates. The results indicate purifying selection.
Polynucleobacter asymbioticus strain QLW-P1DMWA-1T represents a group of highly successful heterotrophic ultramicrobacteria that is frequently very abundant (up to 70% of total bacterioplankton) in freshwater habitats across all seven continents. This strain was originally isolated from a shallow Alpine pond characterized by rapid changes in water temperature and elevated UV radiation due to its location at an altitude of 1300 m. To elucidate the strain’s adjustment to fluctuating environmental conditions, we recorded changes occurring in its transcriptomic and proteomic profiles under contrasting experimental conditions by simulating thermal conditions in winter and summer as well as high UV irradiation. To analyze the potential connection between gene expression and regulation via methyl group modification of the genome, we also analyzed its methylome. The methylation pattern differed between the three treatments, pointing to its potential role in differential gene expression. An adaptive process due to evolutionary pressure in the genus was deduced by calculating the ratios of non-synonymous to synonymous substitution rates for 20 Polynucleobacter spp. genomes obtained from geographically diverse isolates. The results indicate purifying selection.
ORS1, an H2O2-Responsive NAC Transcription Factor, Controls Senescence in Arabidopsis thaliana
(2011)
We report here that ORS1, a previously uncharacterized member of the NAC transcription factor family, controls leaf senescence in Arabidopsis thaliana. Overexpression of ORS1 accelerates senescence in transgenic plants, whereas its inhibition delays it. Genes acting downstream of ORS1 were identified by global expression analysis using transgenic plants producing dexamethasone-inducible ORS1-GR fusion protein. Of the 42 up-regulated genes, 30 (similar to 70%) were previously shown to be up-regulated during age-dependent senescence. We also observed that 32 (similar to 76%) of the ORS1-dependent genes were induced by long-term (4 d), but not short-term (6 h) salinity stress (150 mM NaCl). Furthermore, expression of 16 and 24 genes, respectively, was induced after 1 and 5 h of treatment with hydrogen peroxide (H2O2), a reactive oxygen species known to accumulate during salinity stress. ORS1 itself was found to be rapidly and strongly induced by H2O2 treatment in both leaves and roots. Using in vitro binding site selection, we determined the preferred binding motif of ORS1 and found it to be present in half of the ORS1-dependent genes. ORS1 is a paralog of ORE1/ANAC092/AtNAC2, a previously reported regulator of leaf senescence. Phylogenetic footprinting revealed evolutionary conservation of the ORS1 and ORE1 promoter sequences in different Brassicaceae species, indicating strong positive selection acting on both genes. We conclude that ORS1, similarly to ORE1, triggers expression of senescence-associated genes through a regulatory network that may involve cross-talk with salt- and H2O2-dependent signaling pathways.
Reciprocal selection between aphids, their protective endosymbionts, and the parasitoid wasps that prey upon them offers an opportunity to study the basis of their coevolution. We investigated adaptation to symbiont‐conferred defense by rearing the parasitoid wasp Lysiphlebus fabarum on aphids (Aphis fabae) possessing different defensive symbiont strains (Hamiltonella defensa). After ten generations of experimental evolution, wasps showed increased abilities to parasitize aphids possessing the H. defensa strain they evolved with, but not aphids possessing the other strain. We show that the two symbiont strains encode different toxins, potentially creating different targets for counter‐adaptation. Phenotypic and behavioral comparisons suggest that neither life‐history traits nor oviposition behavior differed among evolved parasitoid lineages. In contrast, comparative transcriptomics of adult female wasps identified a suite of differentially expressed genes among lineages, even when reared in a common, symbiont‐free, aphid host. In concurrence with the specificity of each parasitoid lineages’ infectivity, most differentially expressed parasitoid transcripts were also lineage‐specific. These transcripts are enriched with putative venom toxins and contain highly expressed, potentially defensive viral particles. Together, these results suggest that wild populations of L. fabarum employ a complicated offensive arsenal with sufficient genetic variation for wasps to adapt rapidly and specifically to their hosts’ microbial defenses.
Background
The forelimb-specific gene tbx5 is highly conserved and essential for the development of forelimbs in zebrafish, mice, and humans. Amongst birds, a single order, Dinornithiformes, comprising the extinct wingless moa of New Zealand, are unique in having no skeletal evidence of forelimb-like structures.
Results
To determine the sequence of tbx5 in moa, we used a range of PCR-based techniques on ancient DNA to retrieve all nine tbx5 exons and splice sites from the giant moa, Dinornis. Moa Tbx5 is identical to chicken Tbx5 in being able to activate the downstream promotors of fgf10 and ANF. In addition we show that missexpression of moa tbx5 in the hindlimb of chicken embryos results in the formation of forelimb features, suggesting that Tbx5 was fully functional in wingless moa. An alternatively spliced exon 1 for tbx5 that is expressed specifically in the forelimb region was shown to be almost identical between moa and ostrich, suggesting that, as well as being fully functional, tbx5 is likely to have been expressed normally in moa since divergence from their flighted ancestors, approximately 60 mya.
Conclusions
The results suggests that, as in mice, moa tbx5 is necessary for the induction of forelimbs, but is not sufficient for their outgrowth. Moa Tbx5 may have played an important role in the development of moa’s remnant forelimb girdle, and may be required for the formation of this structure. Our results further show that genetic changes affecting genes other than tbx5 must be responsible for the complete loss of forelimbs in moa.
Leaf senescence is a developmentally controlled process, which is additionally modulated by a number of adverse environmental conditions. Nitrogen shortage is a well-known trigger of precocious senescence in many plant species including crops, generally limiting biomass and seed yield. However, leaf senescence induced by nitrogen starvation may be reversed when nitrogen is resupplied at the onset of senescence. Here, the transcriptomic, hormonal, and global metabolic rearrangements occurring during nitrogen resupply-induced reversal of senescence in Arabidopsis thaliana were analysed. The changes induced by senescence were essentially in keeping with those previously described; however, these could, by and large, be reversed. The data thus indicate that plants undergoing senescence retain the capacity to sense and respond to the availability of nitrogen nutrition. The combined data are discussed in the context of the reversibility of the senescence programme and the evolutionary benefit afforded thereby. Future prospects for understanding and manipulating this process in both Arabidopsis and crop plants are postulated.
SLocX predicting subcellular localization of Arabidopsis proteins leveraging gene expression data
(2011)
Despite the growing volume of experimentally validated knowledge about the subcellular localization of plant proteins, a well performing in silico prediction tool is still a necessity. Existing tools, which employ information derived from protein sequence alone, offer limited accuracy and/or rely on full sequence availability. We explored whether gene expression profiling data can be harnessed to enhance prediction performance. To achieve this, we trained several support vector machines to predict the subcellular localization of Arabidopsis thaliana proteins using sequence derived information, expression behavior, or a combination of these data and compared their predictive performance through a cross-validation test. We show that gene expression carries information about the subcellular localization not available in sequence information, yielding dramatic benefits for plastid localization prediction, and some notable improvements for other compartments such as the mito-chondrion, the Golgi, and the plasma membrane. Based on these results, we constructed a novel subcellular localization prediction engine, SLocX, combining gene expression profiling data with protein sequence-based information. We then validated the results of this engine using an independent test set of annotated proteins and a transient expression of GFP fusion proteins. Here, we present the prediction framework and a website of predicted localizations for Arabidopsis. The relatively good accuracy of our prediction engine, even in cases where only partial protein sequence is available (e.g., in sequences lacking the N-terminal region), offers a promising opportunity for similar application to non-sequenced or poorly annotated plant species. Although the prediction scope of our method is currently limited by the availability of expression information on the ATH1 array, we believe that the advances in measuring gene expression technology will make our method applicable for all Arabidopsis proteins.