Natural variation in Arabidopsis thaliana: Molecular genetic architecture of stress tolerance under water deficit

Abstract only availableThe functional genomics tools available for studying Arabidopsis thaliana are a great resource for researchers trying to characterize and understand the genetic basis of natural variation. Genome wide transcript profiling can simultaneously monitor the gene expression programs regulated by growth and development and signal transduction pathways in response to environmental stress conditions. The responses of plants to water deficit depend on the extent and rate of water loss and its timing and duration. As a physical stress, water deficit triggers biochemical responses through a cascade that includes stress perception, signal transduction and regulation of gene expression. Arabidopsis accessions differ largely in their adaptation to stress tolerance. To understand the genetic basis of this intra-specific variation we analyzed five accessions under gradual water deficit leading to severe stress conditions. The changes in the gene expression profiles under water deficit conditions were studied using functional genomics tools, microarray and quantitative real time PCR and the regulatory roles of stress induced and developmental related transcripts will be discussed.Plant Genomics Internships @ M

Constructing proteome and metabolome maps for genetic improvement of energy-related traits in soybean [abstract]

Only abstract of poster available.Track V: BiomassAlthough the genetic blueprint of soybean is represented by the genome, its phenotype is a product of that blueprint manifested as the production of proteins and metabolites influencing growth characteristics, stress responses, seed composition, and yield. We are using various tools of genomics and molecular breeding with an aim towards development of value-added soybeans that will help United States farmers to maintain their competitiveness and expand utilization of soybean crops (e.g. functional foods, industrial uses, biodiesel, etc). Profiling soybean gene products will lay the foundation for a systems biology approach to key processes such as seed development, which will lead to the genetic improvement of yield and seed composition. Being one of the major bio-energy crops, building a comprehensive map of proteins and metabolites for soybean will help make connections between regulatory or metabolic pathways not previously characterized. Another major benefit from these studies is the discovery of energy related traits including plant productivity and seed compositional traits for the genetic improvement of soybean. It is well known that environmental cues influence developmental phenotypes in plants. Different biotic stresses such as fungal diseases and abiotic stresses, such as drought and flooding, also elicit phenotypic responses from the genome. Thus, by studying the gene products, a direct correlation between response and specific peptides/metabolites can be made. This will lead to crop improvement either through breeding or transgenic efforts. Major objectives of this study are: a) to identify key soybean seed, leaf, and root proteins involved in development and biotic and abiotic stress responses; b) to establish a comprehensive set of chemical standards for soybean metabolites moving toward construction of a metabolome map with a focus on seed and drought effects on seed development and, c) to compile a database linking proteomic and metabolite information and associate this information to value-added soybean traits and markers for assisted breeding. We are utilizing GC/MS, LC/MS, and NMR approaches to identify key molecules for further characterization

Soybean transcription factor ORFeome associated with drought resistance: a valuable resource to accelerate research on abiotic stress resistance

Tissue/organ expression pattern of TF genes. The expression of soybean TF-ORFeome candidates in seven soybean organs including root, root tip, leaf, shoot apical meristem (SAM), nodule, flower and green pod were based on published RNA-Seq data [26]. The color scale indicates the degree of gene expression levels (yellow, low expression level; red, high expression level)

SoyDB: a knowledge database of soybean transcription factors

<p>Abstract</p> <p>Background</p> <p>Transcription factors play the crucial rule of regulating gene expression and influence almost all biological processes. Systematically identifying and annotating transcription factors can greatly aid further understanding their functions and mechanisms. In this article, we present SoyDB, a user friendly database containing comprehensive knowledge of soybean transcription factors.</p> <p>Description</p> <p>The soybean genome was recently sequenced by the Department of Energy-Joint Genome Institute (DOE-JGI) and is publicly available. Mining of this sequence identified 5,671 soybean genes as putative transcription factors. These genes were comprehensively annotated as an aid to the soybean research community. We developed SoyDB - a knowledge database for all the transcription factors in the soybean genome. The database contains protein sequences, predicted tertiary structures, putative DNA binding sites, domains, homologous templates in the Protein Data Bank (PDB), protein family classifications, multiple sequence alignments, consensus protein sequence motifs, web logo of each family, and web links to the soybean transcription factor database PlantTFDB, known EST sequences, and other general protein databases including Swiss-Prot, Gene Ontology, KEGG, EMBL, TAIR, InterPro, SMART, PROSITE, NCBI, and Pfam. The database can be accessed via an interactive and convenient web server, which supports full-text search, PSI-BLAST sequence search, database browsing by protein family, and automatic classification of a new protein sequence into one of 64 annotated transcription factor families by hidden Markov models.</p> <p>Conclusions</p> <p>A comprehensive soybean transcription factor database was constructed and made publicly accessible at <url>http://casp.rnet.missouri.edu/soydb/</url>.</p

Spatial distribution of transcript changes in the maize primary root elongation zone at low water potential

Background: Previous work showed that the maize primary root adapts to low Ψw (-1.6 MPa) by maintaining longitudinal expansion in the apical 3 mm (region 1), whereas in the adjacent 4 mm (region 2) longitudinal expansion reaches a maximum in well-watered roots but is progressively inhibited at low Ψw. To identify mechanisms that determine these responses to low Ψw, transcript expression was profiled in these regions of water-stressed and well-watered roots. In addition, comparison between region 2 of water-stressed roots and the zone of growth deceleration in well-watered roots (region 3) distinguished stress-responsive genes in region 2 from those involved in cell maturation. Results: Responses of gene expression to water stress in regions 1 and 2 were largely distinct. The largest functional categories of differentially expressed transcripts were reactive oxygen species and carbon metabolism in region 1, and membrane transport in region 2. Transcripts controlling sucrose hydrolysis distinguished well-watered and water-stressed states (invertase vs. sucrose synthase), and changes in expression of transcripts for starch synthesis indicated further alteration in carbon metabolism under water deficit. A role for inositols in the stress response was suggested, as was control of proline metabolism. Increased expression of transcripts for wall-loosening proteins in region 1, and for elements of ABA and ethylene signaling were also indicated in the response to water deficit. Conclusion: The analysis indicates that fundamentally different signaling and metabolic response mechanisms are involved in the response to water stress in different regions of the maize primary root elongation zone