Windows .NET Network Distributed Basic Local Alignment Search Toolkit (W.ND-BLAST)

BACKGROUND: BLAST is one of the most common and useful tools for Genetic Research. This paper describes a software application we have termed Windows .NET Distributed Basic Local Alignment Search Toolkit (W.ND-BLAST), which enhances the BLAST utility by improving usability, fault recovery, and scalability in a Windows desktop environment. Our goal was to develop an easy to use, fault tolerant, high-throughput BLAST solution that incorporates a comprehensive BLAST result viewer with curation and annotation functionality. RESULTS: W.ND-BLAST is a comprehensive Windows-based software toolkit that targets researchers, including those with minimal computer skills, and provides the ability increase the performance of BLAST by distributing BLAST queries to any number of Windows based machines across local area networks (LAN). W.ND-BLAST provides intuitive Graphic User Interfaces (GUI) for BLAST database creation, BLAST execution, BLAST output evaluation and BLAST result exportation. This software also provides several layers of fault tolerance and fault recovery to prevent loss of data if nodes or master machines fail. This paper lays out the functionality of W.ND-BLAST. W.ND-BLAST displays close to 100% performance efficiency when distributing tasks to 12 remote computers of the same performance class. A high throughput BLAST job which took 662.68 minutes (11 hours) on one average machine was completed in 44.97 minutes when distributed to 17 nodes, which included lower performance class machines. Finally, there is a comprehensive high-throughput BLAST Output Viewer (BOV) and Annotation Engine components, which provides comprehensive exportation of BLAST hits to text files, annotated fasta files, tables, or association files. CONCLUSION: W.ND-BLAST provides an interactive tool that allows scientists to easily utilizing their available computing resources for high throughput and comprehensive sequence analyses. The install package for W.ND-BLAST is freely downloadable from . With registration the software is free, installation, networking, and usage instructions are provided as well as a support forum

The rehydration transcriptome of the desiccation-tolerant bryophyte Tortula ruralis: transcript classification and analysis

BACKGROUND: The cellular response of plants to water-deficits has both economic and evolutionary importance directly affecting plant productivity in agriculture and plant survival in the natural environment. Genes induced by water-deficit stress have been successfully enumerated in plants that are relatively sensitive to cellular dehydration, however we have little knowledge as to the adaptive role of these genes in establishing tolerance to water loss at the cellular level. Our approach to address this problem has been to investigate the genetic responses of plants that are capable of tolerating extremes of dehydration, in particular the desiccation-tolerant bryophyte, Tortula ruralis. To establish a sound basis for characterizing the Tortula genome in regards to desiccation tolerance, we analyzed 10,368 expressed sequence tags (ESTs) from rehydrated rapid-dried Tortula gametophytes, a stage previously determined to exhibit the maximum stress induced change in gene expression. RESULTS: The 10, 368 ESTs formed 5,563 EST clusters (contig groups representing individual genes) of which 3,321 (59.7%) exhibited similarity to genes present in the public databases and 2,242 were categorized as unknowns based on protein homology scores. The 3,321 clusters were classified by function using the Gene Ontology (GO) hierarchy and the KEGG database. The results indicate that the transcriptome contains a diverse population of transcripts that reflects, as expected, a period of metabolic upheaval in the gametophyte cells. Much of the emphasis within the transcriptome is centered on the protein synthetic machinery, ion and metabolite transport, and membrane biosynthesis and repair. Rehydrating gametophytes also have an abundance of transcripts that code for enzymes involved in oxidative stress metabolism and phosphorylating activities. The functional classifications reflect a remarkable consistency with what we have previously established with regards to the metabolic activities that are important in the recovery of the gametophytes from desiccation. A comparison of the GO distribution of Tortula clusters with an identical analysis of 9,981 clusters from the desiccation sensitive bryophyte species Physcomitrella patens, revealed, and accentuated, the differences between stressed and unstressed transcriptomes. Cross species sequence comparisons indicated that on the whole the Tortula clusters were more closely related to those from Physcomitrella than Arabidopsis (complete genome BLASTx comparison) although because of the differences in the databases there were more high scoring matches to the Arabidopsis sequences. The most abundant transcripts contained within the Tortula ESTs encode Late Embryogenesis Abundant (LEA) proteins that are normally associated with drying plant tissues. This suggests that LEAs may also play a role in recovery from desiccation when water is reintroduced into a dried tissue. CONCLUSION: The establishment of a rehydration EST collection for Tortula ruralis, an important plant model for plant stress responses and vegetative desiccation tolerance, is an important step in understanding the genome level response to cellular dehydration. The type of transcript analysis performed here has laid the foundation for more detailed functional and genome level analyses of the genes involved in desiccation tolerance in plants

The role of war in deep transitions: exploring mechanisms, imprints and rules in sociotechnical systems

This paper explores in what ways the two world wars influenced the development of sociotechnical systems underpinning the culmination of the first deep transition. The role of war is an underexplored aspect in both the Techno-Economic Paradigms (TEP) approach and the Multi-level perspective (MLP) which form the two key conceptual building blocks of the Deep Transitions (DT) framework. Thus, we develop a conceptual approach tailored to this particular topic which integrates accounts of total war and mechanisms of war from historical studies and imprinting from organisational studies with the DT framework’s attention towards rules and meta-rules. We explore in what ways the three sociotechnical systems of energy, food, and transport were affected by the emergence of new demand pressures and logistical challenges during conditions of total war; how war impacted the directionality of sociotechnical systems; the extent to which new national and international policy capacities emerged during wartime in the energy, food, and transport systems; and the extent to which these systems were influenced by cooperation and shared sacrifice under wartime conditions. We then explore what lasting changes were influenced by the two wars in the energy, food, and transport systems across the transatlantic zone. This paper seeks to open up a hitherto neglected area in analysis on sociotechnical transitions and we discuss the importance of further research that is attentive towards entanglements of warfare and the military particularly in the field of sustainability transitions

A First Insight into Population Structure and Linkage Disequilibrium in the U.S. Peanut Minicore Collection

Knowledge of genetic diversity, population structure, and degree of linkage disequilibrium (LD) in target association mapping populations is of great importance and is a prerequisite for LD-based mapping. In the present study, 96 genotypes comprising 92 accessions of the US peanut minicore collection, a component line of the tetraploid variety Florunner, diploid progenitors A. duranensis (AA) and A. ipaënsis (BB), and synthetic amphidiploid accession TxAG-6 were investigated with 392 simple sequence repeat (SSR) marker bands amplified using 32 highly-polymorphic SSR primer pairs. Both distance- and model-based (Bayesian) cluster analysis revealed the presence of structured diversity. In general, the wild-species accessions and the synthetic amphidiploid grouped separately from most minicore accessions except for COC155, and were eliminated from most subsequent analyses. UPGMA analysis divided the population into four subgroups, two major subgroups representing subspecies fastigiata and hypogaea, a third group containing individuals from each subspecies or possibly of mixed ancestry, and a fourth group, either consisting of COC155 alone if wild species were excluded, or of COC155, the diploid species, and the synthetic amphidiploid. Modelbased clustering identified four subgroups- one each for fastigiata and hypogaea subspecies, a third consisting of individuals of both subspecies or of mixed ancestry predominantly from Africa or Asia, and a fourth group, consisting of individuals predominantly of var fastigiata, peruviana, and aequatoriana accessions from South America, including COC155. Analysis of molecular variance (AMOVA) revealed statistically-significant (P \u3c 0.0001) genetic variance of 16.87% among subgroups. A total of 4.85% of SSR marker pairs revealed significant LD (at r2 ≥ 0.1). Of the syntenic marker pairs separated by distances \u3c 10 cM, 11–20 cM, 21–50 cM, and \u3e 50 cM, 19.33, 5.19, 6.25 and 5.29% of marker pairs were found in strong LD (P ≤ 0.01), in accord with LD extending to great distances in self pollinated crops. A threshold value of r2 \u3e 0.035 was found to distinguish mean r2 values of linkage distance groups statistically from the mean r2 values of unlinked markers; LD was found to extend to 10 cM over the entire minicore collection by this criterion. However, there were large differences in r2 values among marker pairs even among tightly-linked markers. The implications of these findings with regard to the possibility of using association mapping for detection of genome-wide SSR marker-phenotype association are discussed

Windows .NET Network Distributed Basic Local Alignment Search Toolkit (W.ND-BLAST)-0

<p><b>Copyright information:</b></p><p>Taken from "Windows .NET Network Distributed Basic Local Alignment Search Toolkit (W.ND-BLAST)"</p><p>BMC Bioinformatics 2005;6():93-93.</p><p>Published online 8 Apr 2005</p><p>PMCID:PMC1087835.</p><p>Copyright © 2005 Dowd et al; licensee BioMed Central Ltd.</p>ample screenshot shows where the user is able to "Create New Project" by simply entering in a new project name. The "Create New Project" can also be changed to "Load Saved Project" where the user has the option to choose a previous project from the left text box

Windows .NET Network Distributed Basic Local Alignment Search Toolkit (W.ND-BLAST)-2

<p><b>Copyright information:</b></p><p>Taken from "Windows .NET Network Distributed Basic Local Alignment Search Toolkit (W.ND-BLAST)"</p><p>BMC Bioinformatics 2005;6():93-93.</p><p>Published online 8 Apr 2005</p><p>PMCID:PMC1087835.</p><p>Copyright © 2005 Dowd et al; licensee BioMed Central Ltd.</p>olumns information from an individual BLAST hit. This particular window is displaying the first five hits for a sequence named, "Contig_318." From here the user can move forward or backward through all BLAST output sequences. The user can also click on the "View Alignment" column to bring up the "Sequence Alignment Viewer" window

Utilizing intraspecific variation in phenotypic plasticity to bolster agricultural and forest productivity under climate change.

Climate change threatens the ability of agriculture and forestry to meet growing global demands for food, fibre and wood products. Information gathered from genotype-by-environment interactions (G × E), which demonstrate intraspecific variation in phenotypic plasticity (the ability of a genotype to alter its phenotype in response to environmental change), may prove important for bolstering agricultural and forest productivity under climate change. Nonetheless, very few studies have explicitly quantified genotype plasticity-productivity relationships in agriculture or forestry. Here, we conceptualize the importance of intraspecific variation in agricultural and forest species plasticity, and discuss the physiological and genetic factors contributing to intraspecific variation in phenotypic plasticity. Our discussion highlights the need for an integrated understanding of the mechanisms of G × E, more extensive assessments of genotypic responses to climate change under field conditions, and explicit testing of genotype plasticity-productivity relationships. Ultimately, further investigation of intraspecific variation in phenotypic plasticity in agriculture and forestry may prove important for identifying genotypes capable of increasing or sustaining productivity under more extreme climatic conditions