Gene co-expression analyses: an overview from microarray collections in Arabidopsis thaliana

Gene Co-expression Network Analysis and Linking Modules to Phenotyping Response in Plants

Environmental factors, including different stresses, can have an impact on the expression of genes and subsequently the phenotype and development of plants. Since a large number of genes are involved in response to the perturbation of the environment, identifying groups of co-expressed genes is meaningful. The gene co-expression network models can be used for the exploration, interpretation, and identification of genes responding to environmental changes. Once a gene co-expression network is constructed, one can determine gene modules and the association of gene modules to the phenotypic response. To link modules to phenotype, one approach is to find the correlated eigengenes of given modules or to integrate all eigengenes in regularized linear model. This manuscript describes the method from construction of co-expression network, module discovery, association between modules and phenotypic data, and finally to annotation/visualization.

Bioinformatics Resources for Plant Abiotic Stress Responses: State of the Art and Opportunities in the Fast Evolving -Omics Era

Abiotic stresses are among the principal limiting factors for productivity in agriculture. In the current era of continuous climate changes, the understanding of the molecular aspects involved in abiotic stress response in plants is a priority. The rise of -omics approaches provides key strategies to promote effective research in the field, facilitating the investigations from reference models to an increasing number of species, tolerant and sensitive genotypes. Integrated multilevel approaches, based on molecular investigations at genomics, transcriptomics, proteomics and metabolomics levels, are now feasible, expanding the opportunities to clarify key molecular aspects involved in responses to abiotic stresses. To this aim, bioinformatics has become fundamental for data production, mining and integration, and necessary for extracting valuable information and for comparative efforts, paving the way to the modeling of the involved processes. We provide here an overview of bioinformatics resources for research on plant abiotic stresses, describing collections from -omics efforts in the field, ranging from raw data to complete databases or platforms, highlighting opportunities and still open challenges in abiotic stress research based on -omics technologies.

Plant mechanosensitive ion channels: an ocean of possibilities

Mechanosensitive ion channels, transmembrane proteins that directly couple mechanical stimuli to ion flux, serve to sense and respond to changes in membrane tension in all branches of life. In plants, mechanosensitive channels have been implicated in the perception of important mechanical stimuli such as osmotic pressure, touch, gravity, and pathogenic invasion. Indeed, three established families of plant mechanosensitive ion channels play roles in cell and organelle osmoregulation and root mechanosensing - and it is likely that many other channels and functions await discovery. Inspired by recent discoveries in bacterial and animal systems, we are beginning to establish the conserved and the unique ways in which mechanosensitive channels function in plants.

Global gene expression analysis of the response of physic nut (Jatropha curcas L.) to medium- and long-term nitrogen deficiency

Jatropha curcas L. is an important biofuel plant with excellent tolerance of barren environments. However, studies on the regulatory mechanisms that operate in this plant in response to nitrogen (N) shortage are scarce. In this study, genome-wide transcriptional profiles of the roots and leaves of 8-week old physic nut seedlings were analyzed after 2 and 16 days of N starvation. Enrichment results showed that genes associated with N metabolism, processing and regulation of RNA, and transport predominated among those showing alterations in expression. Genes encoding transporter families underwent major changes in expression in both roots and leaves; in particular, those with roles in ammonia, amino acid and peptide transport were generally up-regulated after long-term starvation, while AQUAPORIN genes, whose products function in osmoregulation, were down-regulated. We also found that ASPARA−GINASE B1 and SARCOSINE OXIDASE genes were up-regulated in roots and leaves after 2 and 16 d N starvation. Genes associated with ubiquitination-mediated protein degradation were significantly up-regulated. In addition, genes in the JA biosynthesis pathway were strongly activated while expression of those in GA signaling was inhibited in leaves. We showed that four major classes of genes, those with roles in N uptake, N reutilization, C/N ratio balance, and cell structure and synthesis, were particularly influenced by long-term N limitation. Our discoveries may offer clues to the molecular mechanisms that regulate N reallocation and reutilization so as to maintain or increase plant performance even under adverse environmental conditions.

RapaNet: A Web Tool for the Co-Expression Analysis of Brassica rapa Genes

Accumulated microarray data are used for assessing gene function by providing statistical values for co-expressed genes; however, only a limited number of Web tools are available for analyzing the co-expression of genes of Brassica rapa. We have developed a Web tool called RapaNet (http://bioinfo.mju.ac.kr/arraynet/brassica300k/query/), which is based on a data set of 143 B rapa microarrays compiled from various organs and at different developmental stages during exposure to biotic or abiotic stress. RapaNet visualizes correlated gene expression information via correlational networks and phylogenetic trees using Pearson correlation coefficient (r). In addition, RapaNet provides hierarchical clustering diagrams, scatterplots of log ratio intensities, related pathway maps, and cis-element lists of promoter regions. To ascertain the functionality of RapaNet, the correlated genes encoding ribosomal protein (L7Ae), photosystem II protein D1 (psbA), and cytochrome P450 monooxygenase in glucosinolate biosynthesis (CYP79F1) were retrieved from RapaNet and compared with their Arabidopsis homologues. An analysis of the co-expressed genes revealed their shared and unique features.

Bioinformatics resources for pollen

Bioinformatics for Pollen. Pollen plays a key role in crop production, and its development is the most delicate phase in reproduction. Different metabolic pathways are involved in pollen development, and changes in the level of some metabolites, as well as responses to stress, are correlated with the reduction in pollen viability, leading consequently to a decrease in the fruit production. However, studies on pollen may be hard because gamete development and fertilization are complex processes that occur during a short window of time. The rise of the so-called -omics sciences provided key strategies to promote molecular research in pollen tissues, starting from model organisms and moving to increasing number of species. An integrated multi-level approach based on investigations from genomics, transcriptomics, proteomics and metabolomics appears now feasible to clarify key molecular processes in pollen development and viability. To this aim, bioinformatics has a fundamental role for data production and analysis, contributing varied and ad hoc methodologies, endowed with different sensitivity and specificity, necessary for extracting added-value information from the large amount of molecular data achievable. Bioinformatics is also essential for data management, organization, distribution and integration in suitable resources. This is necessary to catch the biological features of the pollen tissues and to design effective approaches to identifying structural or functional properties, enabling the modeling of the major involved processes in normal or in stress conditions. In this review, we provide an overview of the available bioinformatics resources for pollen, ranging from raw data collections to complete databases or platforms, when available, which include data and/or results from -omics efforts on the male gametophyte. Perspectives in the fields will also be described.