Prediction of condition-specific regulatory genes using machine learning.

Recent advances in genomic technologies have generated data on large-scale protein-DNA interactions and open chromatin regions for many eukaryotic species. How to identify condition-specific functions of transcription factors using these data has become a major challenge in genomic research. To solve this problem, we have developed a method called ConSReg, which provides a novel approach to integrate regulatory genomic data into predictive machine learning models of key regulatory genes.

Comparing time series transcriptome data between plants using a network module finding algorithm.

Background: Comparative transcriptome analysis is the comparison of expression patterns between homologous genes in different species. Since most molecular mechanistic studies in plants have been performed in model species, including Arabidopsis and rice, comparative transcriptome analysis is particularly important for functional annotation of genes in diverse plant species. Many biological processes, such as embryo development, are highly conserved between different plant species.

Proteome-wide, Structure-Based Prediction of Protein-Protein Interactions/New Molecular Interactions Viewer.

Determining the complete Arabidopsis () protein-protein interaction network is essential for understanding the functional organization of the proteome. Numerous small-scale studies and a couple of large-scale ones have elucidated a fraction of the estimated 300,000 binary protein-protein interactions in Arabidopsis. In this study, we provide evidence that a docking algorithm has the ability to identify real interactions using both experimentally determined and predicted protein structures.

Identification of regulatory modules in genome scale transcription regulatory networks.

Background: In gene regulatory networks, transcription factors often function as co-regulators to synergistically induce or inhibit expression of their target genes. However, most existing module-finding algorithms can only identify densely connected genes but not co-regulators in regulatory networks.

Methods: We have developed a new computational method, CoReg, to identify transcription co-regulators in large-scale regulatory networks.

Multilevel Regulation of Abiotic Stress Responses in Plants.

The sessile lifestyle of plants requires them to cope with stresses . Plants overcome abiotic stresses by altering structure/morphology, and in some extreme conditions, by compressing the life cycle to survive the stresses in the form of seeds. Genetic and molecular studies have uncovered complex regulatory processes that coordinate stress adaptation and tolerance in plants, which are integrated at various levels.

Beacon Editor: Capturing Signal Transduction Pathways Using the Systems Biology Graphical Notation Activity Flow Language.

The Beacon Editor is a cross-platform desktop application for the creation and modification of signal transduction pathways using the Systems Biology Graphical Notation Activity Flow (SBGN-AF) language. Prompted by biologists' requests for enhancements, the Beacon Editor includes numerous powerful features for the benefit of creation and presentation.

Expresso: A database and web server for exploring the interaction of transcription factors and their target genes in using ChIP-Seq peak data.

The increasing availability of chromatin immunoprecipitation sequencing (ChIP-Seq) data enables us to learn more about the action of transcription factors in the regulation of gene expression. Even though transcriptional regulation often involves the concerted action of more than one transcription factor, the format of each individual ChIP-Seq dataset usually represents the action of a single transcription factor. Therefore, a relational database in which available ChIP-Seq datasets are curated is essential.

A Machine Learning Approach to Predict Gene Regulatory Networks in Seed Development in Arabidopsis.

Gene regulatory networks (GRNs) provide a representation of relationships between regulators and their target genes. Several methods for GRN inference, both unsupervised and supervised, have been developed to date. Because regulatory relationships consistently reprogram in diverse tissues or under different conditions, GRNs inferred without specific biological contexts are of limited applicability.

CoSpliceNet: a framework for co-splicing network inference from transcriptomics data.

Background: Alternative splicing has been proposed to increase transcript diversity and protein plasticity in eukaryotic organisms, but the extent to which this is the case is currently unclear, especially with regard to the diversification of molecular function. Eukaryotic splicing involves complex interactions of splicing factors and their targets. Inference of co-splicing networks capturing these types of interactions is important for understanding this crucial, highly regulated post-transcriptional process at the systems level.

Potential targets of VIVIPAROUS1/ABI3-LIKE1 (VAL1) repression in developing Arabidopsis thaliana embryos.

Developing Arabidopsis seeds accumulate oils and seed storage proteins synthesized by the pathways of primary metabolism. Seed development and metabolism are positively regulated by transcription factors belonging to the LAFL (LEC1, AB13, FUSCA3 and LEC2) regulatory network. The VAL gene family encodes repressors of the seed maturation program in germinating seeds, although they are also expressed during seed maturation.

Transcriptome-wide functional characterization reveals novel relationships among differentially expressed transcripts in developing soybean embryos.

Background: Transcriptomics reveals the existence of transcripts of different coding potential and strand orientation. Alternative splicing (AS) can yield proteins with altered number and types of functional domains, suggesting the global occurrence of transcriptional and post-transcriptional events. Many biological processes, including seed maturation and desiccation, are regulated post-transcriptionally (e.

A rootstock provides water conservation for a grafted commercial tomato (Solanum lycopersicum L.) line in response to mild-drought conditions: a focus on vegetative growth and photosynthetic parameters.

The development of water stress resistant lines of commercial tomato by breeding or genetic engineering is possible, but will take considerable time before commercial varieties are available for production. However, grafting commercial tomato lines on drought resistant rootstock may produce drought tolerant commercial tomato lines much more rapidly. Due to changing climates and the need for commercial production of vegetables in low quality fields there is an urgent need for stress tolerant commercial lines of vegetables such as tomato.

Evidence for extensive heterotrophic metabolism, antioxidant action, and associated regulatory events during winter hardening in Sitka spruce.

Background: Cold acclimation in woody perennials is a metabolically intensive process, but coincides with environmental conditions that are not conducive to the generation of energy through photosynthesis. While the negative effects of low temperatures on the photosynthetic apparatus during winter have been well studied, less is known about how this is reflected at the level of gene and metabolite expression, nor how the plant generates primary metabolites needed for adaptive processes during autumn.

Results: The MapMan tool revealed enrichment of the expression of genes related to mitochondrial function, antioxidant and associated regulatory activity, while changes in metabolite levels over the time course were consistent with the gene expression patterns observed.

Metabolic and Transcriptional Reprogramming in Developing Soybean (Glycine max) Embryos.

Soybean (Glycine max) seeds are an important source of seed storage compounds, including protein, oil, and sugar used for food, feed, chemical, and biofuel production. We assessed detailed temporal transcriptional and metabolic changes in developing soybean embryos to gain a systems biology view of developmental and metabolic changes and to identify potential targets for metabolic engineering. Two major developmental and metabolic transitions were captured enabling identification of potential metabolic engineering targets specific to seed filling and to desiccation.

Changes in RNA Splicing in Developing Soybean (Glycine max) Embryos.

Developing soybean seeds accumulate oils, proteins, and carbohydrates that are used as oxidizable substrates providing metabolic precursors and energy during seed germination. The accumulation of these storage compounds in developing seeds is highly regulated at multiple levels, including at transcriptional and post-transcriptional regulation. RNA sequencing was used to provide comprehensive information about transcriptional and post-transcriptional events that take place in developing soybean embryos.

Mining and visualization of microarray and metabolomic data reveal extensive cell wall remodeling during winter hardening in Sitka spruce (Picea sitchensis).

Microarray gene expression profiling is a powerful technique to understand complex developmental processes, but making biologically meaningful inferences from such studies has always been challenging. We previously reported a microarray study of the freezing acclimation period in Sitka spruce (Picea sitchensis) in which a large number of candidate genes for climatic adaptation were identified. In the current paper, we apply additional systems biology tools to these data to further probe changes in the levels of genes and metabolites and activities of associated pathways that regulate this complex developmental transition.

Effects of drought on gene expression in maize reproductive and leaf meristem tissue revealed by RNA-Seq.

Drought stress affects cereals especially during the reproductive stage. The maize (Zea mays) drought transcriptome was studied using RNA-Seq analysis to compare drought-treated and well-watered fertilized ovary and basal leaf meristem tissue. More drought-responsive genes responded in the ovary compared with the leaf meristem.

Mining for meaning: visualization approaches to deciphering Arabidopsis stress responses in roots and shoots.

Massive amounts of transcriptomic data documenting plant responses to changes in environment continue to accumulate in online databases. Unfortunately, many of these data sets have not been analyzed in full detail, especially those that involve time course experiments. To gain more knowledge of the successive gene expression events that occur when stress is initiated in one organ and then relayed to another, we have chosen stress response data for Arabidopsis shoots and roots from the detailed time course study of Killian et al.

The iPlant Collaborative: Cyberinfrastructure for Plant Biology.

The iPlant Collaborative (iPlant) is a United States National Science Foundation (NSF) funded project that aims to create an innovative, comprehensive, and foundational cyberinfrastructure in support of plant biology research (PSCIC, 2006). iPlant is developing cyberinfrastructure that uniquely enables scientists throughout the diverse fields that comprise plant biology to address Grand Challenges in new ways, to stimulate and facilitate cross-disciplinary research, to promote biology and computer science research interactions, and to train the next generation of scientists on the use of cyberinfrastructure in research and education. Meeting humanity's projected demands for agricultural and forest products and the expectation that natural ecosystems be managed sustainably will require synergies from the application of information technologies.

Differential expression of heat shock protein genes in preconditioning for photosynthetic acclimation in water-stressed loblolly pine.

Heat shock proteins (HSPs) are induced not only under heat stress conditions but also under other environmental stresses such as water stress. In plants, HSPs families are larger than those of other eukaryotes. In order to elucidate a possible connection between HSP expression and photosynthetic acclimation or conditioning, we conducted a water stress experiment in loblolly pine (Pinus taeda L.

Molecular and physiological adaptation to prolonged drought stress in the leaves of two Andean potato genotypes.

Responses to prolonged drought and recovery from drought of two South American potato (Solanum tuberosum L. ssp. andigena (Juz & Buk) Hawkes) landraces, Sullu and Ccompis were compared under field conditions.

Studying the functional genomics of stress responses in loblolly pine with the Expresso microarray experiment management system.

Conception, design, and implementation of cDNA microarray experiments present a variety of bioinformatics challenges for biologists and computational scientists. The multiple stages of data acquisition and analysis have motivated the design of Expresso, a system for microarray experiment management. Salient aspects of Expresso include support for clone replication and randomized placement; automatic gridding, extraction of expression data from each spot, and quality monitoring; flexible methods of combining data from individual spots into information about clones and functional categories; and the use of inductive logic programming for higher-level data analysis and mining.

Physiological and molecular adaptations to drought in Andean potato genotypes.

The drought stress tolerance of two Solanum tuberosum subsp. andigena landraces, one hybrid (adgxtbr) and Atlantic (S. tuberosum subsp.

Tuber development phenotypes in adapted and acclimated, drought-stressed Solanum tuberosum ssp. andigena have distinct expression profiles of genes associated with carbon metabolism.

A drought screen identified accessions of Solanum tuberosum ssp. andigena that showed varying degrees of physiological acclimation or adaptation to repeated drought stress. The accessions also showed variable tuber phenotypes from small tubers that failed to develop in an accession that showed photosynthetic adaptation to normal tubers in an accession with a phenotype showing some degree of photosynthetic adaptation and acclimation.