Sequence and functional analyses of the aldehyde dehydrogenase 7B4 gene promoter in Arabidopsis thaliana and selected Brassicaceae: regulation patterns in response to wounding and osmotic stress

Key message

The core promoter of the antiquitin ALDH7B4 gene was compared between selected Brassicaceae. Conserved cis elements controlling osmotic stress and wound-induced expression were identified and analysed in Arabidopsis thaliana leaves and seeds.

Abstract

Aldehyde dehydrogenases metabolise a wide range of aliphatic and aromatic aldehydes, which become cytotoxic at high levels. Family 7 aldehyde dehydrogenase genes, often described as antiquitins or turgor-responsive genes in plants, are broadly conserved across all domains. Despite the high conservation of the plant ALDH7 proteins and their importance in stress responses, their regulation has not been investigated. Here, we compared ALDH7 genes of different Brassicaceae and found that, in contrast to the gene organisation and protein coding sequences, similarities in the promoter sequences were limited to the first few hundred nucleotides upstream of the translation start codon. The function of this region was studied by isolating the core promoter of the Arabidopsis thaliana ALDH7B4 gene, taken as model. The promoter was found to be responsive to wounding in addition to salt and dehydration stress. Cis-acting elements involved in stress responsiveness were analysed and two conserved ACGT-containing motifs proximal to the translation start codon were found to be essential for the responsiveness to osmotic stress in leaves and in seeds. The integrity of an upstream ACGT motif and a dehydration-responsive element/C-repeat—low temperature-responsive element was found to be necessary for ALDH7B4 expression in seeds and induction by salt, dehydration and ABA in leaves. The comparison of the gene expression in selected Arabidopsis mutants demonstrated that osmotic stress-induced ALDH7B4 expression in leaves and seeds involves both ABA- and lipid-signalling components.     

Computable visually observed phenotype ontological framework for plants

Background

Gene regulatory networks have an essential role in every process of life. In this regard, the amount of genome-wide time series data is becoming increasingly available, providing the opportunity to discover the time-delayed gene regulatory networks that govern the majority of these molecular processes.

Results

This paper aims at reconstructing gene regulatory networks from multiple genome-wide microarray time series datasets. In this sense, a new model-free algorithm called GRNCOP2 (Gene Regulatory Network inference by Combinatorial OPtimization 2), which is a significant evolution of the GRNCOP algorithm, was developed using combinatorial optimization of gene profile classifiers. The method is capable of inferring potential time-delay relationships with any span of time between genes from various time series datasets given as input. The proposed algorithm was applied to time series data composed of twenty yeast genes that are highly relevant for the cell-cycle study, and the results were compared against several related approaches. The outcomes have shown that GRNCOP2 outperforms the contrasted methods in terms of the proposed metrics, and that the results are consistent with previous biological knowledge. Additionally, a genome-wide study on multiple publicly available time series data was performed. In this case, the experimentation has exhibited the soundness and scalability of the new method which inferred highly-related statistically-significant gene associations.

Conclusions

A novel method for inferring time-delayed gene regulatory networks from genome-wide time series datasets is proposed in this paper. The method was carefully validated with several publicly available data sets. The results have demonstrated that the algorithm constitutes a usable model-free approach capable of predicting meaningful relationships between genes, revealing the time-trends of gene regulation.     

Gene Expression Browser: large-scale and cross-experiment microarray data integration, management, search & visualization

Background

In the last decade, a large amount of microarray gene expression data has been accumulated in public repositories. Integrating and analyzing high-throughput gene expression data have become key activities for exploring gene functions, gene networks and biological pathways. Effectively utilizing these invaluable microarray data remains challenging due to a lack of powerful tools to integrate large-scale gene-expression information across diverse experiments and to search and visualize a large number of gene-expression data points.

Results

Gene Expression Browser is a microarray data integration, management and processing system with web-based search and visualization functions. An innovative method has been developed to define a treatment over a control for every microarray experiment to standardize and make microarray data from different experiments homogeneous. In the browser, data are pre-processed offline and the resulting data points are visualized online with a 2-layer dynamic web display. Users can view all treatments over control that affect the expression of a selected gene via Gene View, and view all genes that change in a selected treatment over control via treatment over control View. Users can also check the changes of expression profiles of a set of either the treatments over control or genes via Slide View. In addition, the relationships between genes and treatments over control are computed according to gene expression ratio and are shown as co-responsive genes and co-regulation treatments over control.

Conclusion

Gene Expression Browser is composed of a set of software tools, including a data extraction tool, a microarray data-management system, a data-annotation tool, a microarray data-processing pipeline, and a data search & visualization tool. The browser is deployed as a free public web service (http://www.ExpressionBrowser.com) that integrates 301 ATH1 gene microarray experiments from public data repositories (viz. the Gene Expression Omnibus repository at the National Center for Biotechnology Information and Nottingham Arabidopsis Stock Center). The set of Gene Expression Browser software tools can be easily applied to the large-scale expression data generated by other platforms and in other species.     

Genome-wide identification and expression profiling of DNA methyltransferase gene family in maize

Key message

In this study, we identified eight DNA MTase genes in maize and the diversity of expression patterns of them was presented by EST mining, microarray and semi-quantitative expression profile analyses.

Abstract

DNA methylation plays a pivotal role in promoting genomic stability through diverse biological processes including regulation of gene expression during development and chromatin organization. Although this important biological process is mainly regulated by several conserved Cytosine-5 DNA methyltransferases encoded by a smaller multigene family in plants, investigation of the plant C5-MTase-encoding gene family will serve to elucidate the epigenetic mechanism diversity in plants. Recently, genome-wide identification and evolutionary analyses of the C5-MTase-encoding gene family have been characterized in multiple plant species including Arabidopsis, rice, carrot and wheat. However, little is known regarding the C5-MTase-encoding genes in the entire maize genome. Here, genome-wide identification and expression profile analyses of maize C5-MTase-encoding genes (ZmMETs) were performed from the latest version of the maize (B73) genome. Phylogenetic analysis indicated that the orthologs from the three species (maize, Arabidopsis and rice) were categorized into four classes. Chromosomal location of these genes revealed that they are unevenly distributed on 6 of all 10 chromosomes with three chromosomal/segmental duplication events, suggesting that gene duplication played a key role in expansion of the maize C5-MTase-encoding gene family. Furthermore, EST expression data mining, microarray data and semi-quantitative expression profile analyses detected in the leaves by two different abiotic stress treatments have demonstrated that these genes had temporal and spatial expression pattern and exhibited different expression levels in stress treatments, suggesting that functional diversification of ZmMET genes family. Overall, our study will serve to present signification insights to explore the plant C5-MTase-encoding gene expression and function and also be beneficial for future experimental research to further unravel the mechanisms of epigenetic regulation in plants.