High-throughput Comparison, Functional Annotation, and Metabolic Modeling of Plant Genomes using the PlantSEED Resource

There is a growing demand for genome-scale metabolic reconstructions for plants, fueled by the need to understand the metabolic basis of crop yield and by progress in genome and transcriptome sequencing. Methods are also required to enable the interpretation of plant transcriptome data to study how cellular metabolic activity varies under different growth conditions or even within different organs, tissues, and developmental stages. Such methods depend extensively on the accuracy with which genes have been mapped to the biochemical reactions in the plant metabolic pathways. Errors in these mappings lead to metabolic reconstructions with an inflated number of reactions and possible generation of unreliable metabolic phenotype predictions. Here we introduce a new evidence-based genome-scale metabolic reconstruction of maize, with significant improvements in the quality of the gene-reaction associations included within our model. We also present a new approach for applying our model to predict active metabolic genes based on transcriptome data. This method includes a minimal set of reactions associated with low expression genes to enable activity of a maximum number of reactions associated with high expression genes. We apply this method to construct an organ-specific model for the maize leaf, and tissue specific models for maize embryo and endosperm cells. We validate our models using fluxomics data for the endosperm and embryo, demonstrating an improved capacity of our models to fit the available fluxomics data. All models are publicly available via the DOE Systems Biology Knowledgebase and PlantSEED, and our new method is generally applicable for analysis transcript profiles from any plant, paving the way for further in silico studies with a wide variety of plant genomes

The RAST Server: Rapid Annotations using Subsystems Technology

<p>Abstract</p> <p>Background</p> <p>The number of prokaryotic genome sequences becoming available is growing steadily and is growing faster than our ability to accurately annotate them.</p> <p>Description</p> <p>We describe a fully automated service for annotating bacterial and archaeal genomes. The service identifies protein-encoding, rRNA and tRNA genes, assigns functions to the genes, predicts which subsystems are represented in the genome, uses this information to reconstruct the metabolic network and makes the output easily downloadable for the user. In addition, the annotated genome can be browsed in an environment that supports comparative analysis with the annotated genomes maintained in the SEED environment.</p> <p>The service normally makes the annotated genome available within 12–24 hours of submission, but ultimately the quality of such a service will be judged in terms of accuracy, consistency, and completeness of the produced annotations. We summarize our attempts to address these issues and discuss plans for incrementally enhancing the service.</p> <p>Conclusion</p> <p>By providing accurate, rapid annotation freely to the community we have created an important community resource. The service has now been utilized by over 120 external users annotating over 350 distinct genomes.</p

PATRIC, the bacterial bioinformatics database and analysis resource

The Pathosystems Resource Integration Center (PATRIC) is the all-bacterial Bioinformatics Resource Center (BRC) (http://www.patricbrc.org). A joint effort by two of the original National Institute of Allergy and Infectious Diseases-funded BRCs, PATRIC provides researchers with an online resource that stores and integrates a variety of data types [e.g. genomics, transcriptomics, protein-protein interactions (PPIs), three-dimensional protein structures and sequence typing data] and associated metadata. Datatypes are summarized for individual genomes and across taxonomic levels. All genomes in PATRIC, currently more than 10 000, are consistently annotated using RAST, the Rapid Annotations using Subsystems Technology. Summaries of different data types are also provided for individual genes, where comparisons of different annotations are available, and also include available transcriptomic data. PATRIC provides a variety of ways for researchers to find data of interest and a private workspace where they can store both genomic and gene associations, and their own private data. Both private and public data can be analyzed together using a suite of tools to perform comparative genomic or transcriptomic analysis. PATRIC also includes integrated information related to disease and PPIs. All the data and integrated analysis and visualization tools are freely available. This manuscript describes updates to the PATRIC since its initial report in the 2007 NAR Database Issu

The Subsystems Approach to Genome Annotation and its Use in the Project to Annotate 1000 Genomes

The release of the 1000(th) complete microbial genome will occur in the next two to three years. In anticipation of this milestone, the Fellowship for Interpretation of Genomes (FIG) launched the Project to Annotate 1000 Genomes. The project is built around the principle that the key to improved accuracy in high-throughput annotation technology is to have experts annotate single subsystems over the complete collection of genomes, rather than having an annotation expert attempt to annotate all of the genes in a single genome. Using the subsystems approach, all of the genes implementing the subsystem are analyzed by an expert in that subsystem. An annotation environment was created where populated subsystems are curated and projected to new genomes. A portable notion of a populated subsystem was defined, and tools developed for exchanging and curating these objects. Tools were also developed to resolve conflicts between populated subsystems. The SEED is the first annotation environment that supports this model of annotation. Here, we describe the subsystem approach, and offer the first release of our growing library of populated subsystems. The initial release of data includes 180 177 distinct proteins with 2133 distinct functional roles. This data comes from 173 subsystems and 383 different organisms

Towards an ethical ecology of international service learning

International Service-Learning (ISL) is a pedagogical activity that seeks to blend student learning with community engagement overseas and the development of a more just society. ISL programmes have grown as educational institutions and non-governmental organisations have sought to achieve the goal of developing ‘global citizens’. However, Service Learning (SL) in general and International Service-Learning (ISL) in particular remain deeply under theorised. These educational initiatives provide policy makers with a practical response to their quest for a ‘Big Society’and present alluring pedagogical approaches for Universities as they react to reforms in Higher Education and seek to enhance both the student learning experience and graduate employability. After outlining the development of ISL in policy and practice, this paper draws on the rich tradition of ISL at one British university to argue that ISL is a form of engagement that has the potential to be ethical in character although we identify a number of factors that militate against this. Our contention is that ISL which promotes rationaland instrumental learning represents a deficit model and we therefore conceptualise ISL here as a transformative learning experience that evinces distinctly aesthetic and even spiritual dimensions. Upon this theoretical groundwork we lay the foundations for conceptualizing ISL in ways that ensure its ethical integrity

Benthic and Hyporheic Macroinvertebrate Distribution Within the Heads and Tails of Riffles During Baseflow Conditions

The distribution of lotic fauna is widely acknowledged to be patchy reflecting the interaction between biotic and abiotic factors. In an in-situ field study, the distribution of benthic and hyporheic invertebrates in the heads (downwelling) and tails (upwelling) of riffles were examined during stable baseflow conditions. Riffle heads were found to contain a greater proportion of interstitial fine sediment than riffle tails. Significant differences in the composition of benthic communities were associated with the amount of fine sediment. Riffle tail habitats supported a greater abundance and diversity of invertebrates sensitive to fine sediment such as EPT taxa. Shredder feeding taxa were more abundant in riffle heads suggesting greater availability of organic matter. In contrast, no significant differences in the hyporheic community were recorded between riffle heads and tails. We hypothesise that clogging of hyporheic interstices with fine sediments may have resulted in the homogenization of the invertebrate community by limiting faunal movement into the hyporheic zone at both the riffle head and tail. The results suggest that vertical hydrological exchange significantly influences the distribution of fine sediment and macroinvertebrate communities at the riffle scale

On Automatic Differentiation of Codes with COMPLEX Arithmetic with Respect to Real Variables

We explore what it means to apply automatic differentiation with respect to a set of real variables to codes containing complex arithmetic. That is, both dependent and independent variables with respect to differentiation are real variables, but in order to exploit features of complex mathematics, part of the code is expressed by employing complex arithmetic. We investigate how one can apply automatic differentiation to complex variables if one exploits the homomorphism of the complex numbers C onto R 2 . It turns out that, by and large, the usual rules of differentiation apply, but subtle differences in special cases arise for sqrt(), abs(), and the power operator. 1 Introduction In physics and engineering applications, while the underlying independent variables and operations are intrinsically real-valued, it is nevertheless often convenient to employ complex-valued representations. Applications of complex function theory in applied mathematics, physics, and engineering (and hence..

Sensitivity Analysis of the MM5 Weather Model Using Automatic Differentiation

We present a general method for using automatic differentiation to facilitate model sensitivity analysis. Automatic differentiation techniques augment, in a completely mechanical fashion, an existing code such that it also simultaneously and efficiently computes derivatives. Our method allows the sensitivities of the code&apos;s outputs to its parameters and inputs to be determined with minimal human effort by exploiting the relationship between differentiation and formal perturbation theory. Employing this method, we performed a sensitivity study of the MM5 code, a mesoscale weather model jointly developed by Penn State University and the National Center for Atmospheric Research, comprising roughly 40,000 lines of Fortran 77 code. Our results show that AD-computed sensitivities exhibit superior accuracy compared with divided differences approximations computed from finite-amplitude perturbations, while consuming comparable or less CPU time and less human labor. We also comment on a numeric..

Supervised extraction of near-complete genomes from metagenomic samples: A new service in PATRIC

Large amounts of metagenomically-derived data are submitted to PATRIC for analysis. In the future, we expect even more jobs submitted to PATRIC will use metagenomic data. One in-demand use case is the extraction of near-complete draft genomes from assembled contigs of metagenomic origin. The PATRIC metagenome binning service utilizes the PATRIC database to furnish a large, diverse set of reference genomes. We provide a new service for supervised extraction and annotation of high-quality, near-complete genomes from metagenomically-derived contigs. Reference genomes are assigned to putative draft genome bins based on the presence of single-copy universal marker roles in the sample, and contigs are sorted into these bins by their similarity to reference genomes in PATRIC. Each set of binned contigs represents a draft genome that will be annotated by RASTtk in PATRIC. A structured-language binning report is provided containing quality measurements and taxonomic information about the contig bins. The PATRIC metagenome binning service emphasizes extraction of high-quality genomes for downstream analysis using other PATRIC tools and services. Due to its supervised nature, the binning service is not appropriate for mining novel or extremely low-coverage genomes from metagenomic samples.</p