The eDAL Suite: Tools and Concepts for Primary Data Citation

Retrieval and citation of primary data is the important factor in the approaching age of “data science”. Digital data are easily shared, and just as easily wiped or lost. The problem of keeping on-line data accessible and
retrievable is especially difficult for SME like plant breeders plant biotech companies as well as research projects in this domain.
Intension of eDAL is the provisioning of an information retrieval and data citation infrastructure that meets the requirements of the “data science” age and implements a re-usable platform for data retrieval, data
citation, and data publication. Like a shopping cart, the idea is to combine a search engine and a data cart, which retrieves, rank and collect query relevant data from crop plant data centers

The LAILAPS Search Engine: A Feature Model for Relevance Ranking in Life Science Databases

Efficient and effective information retrieval in life sciences is one of the most pressing challenge in bioinformatics. The incredible growth of life science databases to a vast network of interconnected information systems is to the same extent a big challenge and a great chance for life science research. The knowledge found in the Web, in particular in life-science databases, are a valuable major resource. In order to bring it to the scientist desktop, it is essential to have well performing search engines. Thereby, not the response time nor the number of results is important. The most crucial factor for millions of query results is the relevance ranking. In this paper, we present a feature model for relevance ranking in life science databases and its implementation in the LAILAPS search engine. Motivated by the observation of user behavior during their inspection of search engine result, we condensed a set of 9 relevance discriminating features. These features are intuitively used by scientists, who briefly screen database entries for potential relevance. The features are both sufficient to estimate the potential relevance, and efficiently quantifiable. The derivation of a relevance prediction function that computes the relevance from this features constitutes a regression problem. To solve this problem, we used artificial neural networks that have been trained with a reference set of relevant database entries for 19 protein queries. Supporting a flexible text index and a simple data import format, this concepts are implemented in the LAILAPS search engine. It can easily be used both as search engine for comprehensive integrated life science databases and for small in-house project databases. LAILAPS is publicly available for SWISSPROT data at http://lailaps.ipk-gatersleben.d

BARLEX – the Barley Draft Genome Explorer

Colmsee C, Beier S, Himmelbach A, et al. BARLEX – the Barley Draft Genome Explorer. Molecular Plant. 2015;8(6):964-966

Maize Source Leaf Adaptation to Nitrogen Deficiency Affects Not Only Nitrogen and Carbon Metabolism But Also Control of Phosphate Homeostasis

Schlueter U, Mascher M, Colmsee C, et al. Maize Source Leaf Adaptation to Nitrogen Deficiency Affects Not Only Nitrogen and Carbon Metabolism But Also Control of Phosphate Homeostasis. Plant Physiology. 2012;160(3):1384-1406.Crop plant development is strongly dependent on the availability of nitrogen (N) in the soil and the efficiency of N utilization for biomass production and yield. However, knowledge about molecular responses to N deprivation derives mainly from the study of model species. In this article, the metabolic adaptation of source leaves to low N was analyzed in maize (Zea mays) seedlings by parallel measurements of transcriptome and metabolome profiling. Inbred lines A188 and B73 were cultivated under sufficient (15 mM) or limiting (0.15 mM) nitrate supply for up to 30 d. Limited availability of N caused strong shifts in the metabolite profile of leaves. The transcriptome was less affected by the N stress but showed strong genotype-and age-dependent patterns. N starvation initiated the selective down-regulation of processes involved in nitrate reduction and amino acid assimilation; ammonium assimilation-related transcripts, on the other hand, were not influenced. Carbon assimilation-related transcripts were characterized by high transcriptional coordination and general down-regulation under low-N conditions. N deprivation caused a slight accumulation of starch but also directed increased amounts of carbohydrates into the cell wall and secondary metabolites. The decrease in N availability also resulted in accumulation of phosphate and strong down-regulation of genes usually involved in phosphate starvation response, underlining the great importance of phosphate homeostasis control under stress conditions

Adaptation of maize source leaf metabolism to stress related disturbances in carbon, nitrogen and phosphorus balance

Schlueter U, Colmsee C, Scholz U, et al. Adaptation of maize source leaf metabolism to stress related disturbances in carbon, nitrogen and phosphorus balance. BMC Genomics. 2013;14(1): 442.Background: Abiotic stress causes disturbances in the cellular homeostasis. Re-adjustment of balance in carbon, nitrogen and phosphorus metabolism therefore plays a central role in stress adaptation. However, it is currently unknown which parts of the primary cell metabolism follow common patterns under different stress conditions and which represent specific responses. Results: To address these questions, changes in transcriptome, metabolome and ionome were analyzed in maize source leaves from plants suffering low temperature, low nitrogen (N) and low phosphorus (P) stress. The selection of maize as study object provided data directly from an important crop species and the so far underexplored C-4 metabolism. Growth retardation was comparable under all tested stress conditions. The only primary metabolic pathway responding similar to all stresses was nitrate assimilation, which was down-regulated. The largest group of commonly regulated transcripts followed the expression pattern: down under low temperature and low N, but up under low P. Several members of this transcript cluster could be connected to P metabolism and correlated negatively to different phosphate concentration in the leaf tissue. Accumulation of starch under low temperature and low N stress, but decrease in starch levels under low P conditions indicated that only low P treated leaves suffered carbon starvation. Conclusions: Maize employs very different strategies to manage N and P metabolism under stress. While nitrate assimilation was regulated depending on demand by growth processes, phosphate concentrations changed depending on availability, thus building up reserves under excess conditions. Carbon and energy metabolism of the C-4 maize leaves were particularly sensitive to P starvation

Construction of a map-based reference genome sequence for barley, Hordeum vulgare L.

Barley (Hordeum vulgare L.) is a cereal grass mainly used as animal fodder and raw material for the malting industry. The map-based reference genome sequence of barley cv. `Morex' was constructed by the International Barley Genome Sequencing Consortium (IBSC) using hierarchical shotgun sequencing. Here, we report the experimental and computational procedures to (i) sequence and assemble more than 80,000 bacterial artificial chromosome (BAC) clones along the minimum tiling path of a genome-wide physical map, (ii) find and validate overlaps between adjacent BACs, (iii) construct 4,265 non-redundant sequence scaffolds representing clusters of overlapping BACs, and (iv) order and orient these BAC clusters along the seven barley chromosomes using positional information provided by dense genetic maps, an optical map and chromosome conformation capture sequencing (Hi-C). Integrative access to these sequence and mapping resources is provided by the barley genome explorer (BARLEX).Peer reviewe

A chromosome conformation capture ordered sequence of the barley genome

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