Stephan Weise

Towards recommendations for metadata and data handling in plant phenotyping

Recent methodological developments in plant phenotyping, as well as the growing importance of its applications in plant science and breeding, are resulting in a fast accumulation of multidimensional data. There is great potential for expediting both discovery and application if these data are made publicly available for analysis. However, collection and storage of phenotypic observations is not yet sufficiently governed by standards that would ensure interoperability among data providers and precisely link specific phenotypes and associated genomic sequence information. This lack of standards is mainly a result of a large variability of phenotyping protocols, the multitude of phenotypic traits that are measured, and the dependence of these traits on the environment. This paper discusses the current situation of standardization in the area of phenomics, points out the problems and shortages, and presents the areas that would benefit from improvement in this field. In addition, the foundations of the work that could revise the situation are proposed, and practical solutions developed by the authors are introduced.

MetaCrop: a detailed database of crop plant metabolism

MetaCrop is a manually curated repository of high quality information concerning the metabolism of crop plants. This includes pathway diagrams, reactions, locations, transport processes, reaction kinetics, taxonomy and literature. MetaCrop provides detailed information on six major crop plants with high agronomical importance and initial information about several other plants. The web interface supports an easy exploration of the information from overview pathways to single reactions and therefore helps users to understand the metabolism of crop plants. It also allows model creation and automatic data export for detailed models of metabolic pathways therefore supporting systems biology approaches. The MetaCrop database is accessible at http://metacrop.ipk-gatersleben.de.

MetaCrop 2.0: managing and exploring information about crop plant metabolism

MetaCrop is a manually curated repository of high-quality data about plant metabolism, providing different levels of detail from overview maps of primary metabolism to kinetic data of enzymes. It contains information about seven major crop plants with high agronomical importance and two model plants. MetaCrop is intended to support research aimed at the improvement of crops for both nutrition and industrial use. It can be accessed via web, web services and an add-on to the Vanted software. Here, we present several novel developments of the MetaCrop system and the extended database content. MetaCrop is now available in version 2.0 at http://metacrop.ipk-gatersleben.de.

Species-wide genome sequence and nucleotide polymorphisms from the model allopolyploid plant Brassica napus

Brassica napus (oilseed rape, canola) is one of the world’s most important sources of vegetable oil for human nutrition and biofuel, and also a model species for studies investigating the evolutionary consequences of polyploidisation. Strong bottlenecks during its recent origin from interspecific hybridisation, and subsequently through intensive artificial selection, have severely depleted the genetic diversity available for breeding. On the other hand, high-throughput genome profiling technologies today provide unprecedented scope to identify, characterise and utilise genetic diversity in primary and secondary crop gene pools. Such methods also enable implementation of genomic selection strategies to accelerate breeding progress. The key prerequisite is availability of high-quality sequence data and identification of high-quality, genome-wide sequence polymorphisms representing relevant gene pools. We present comprehensive genome resequencing data from a panel of 52 highly diverse natural and synthetic B. napus accessions, along with a stringently selected panel of 4.3 million high-confidence, genome-wide SNPs. The data is of great interest for genomics-assisted breeding and for evolutionary studies on the origins and consequences in allopolyploidisation in plants.

Association of haplotype diversity in the α-amylase gene amy1 with malting quality parameters in barley.

Amylases play an essential role in the germination and malting process. Therefore, these genes are interesting candidates for marker development in order to improve malting quality as an important breeding aim. The intervarietal diversity of the α-amylase gene amy1 mapping to chromosome 6H was investigated. A total of six single nucleotide polymorphisms (SNPs) were detected which defined four haplotypes. Associations between SNP-markers and important malting parameters were discovered in a collection of 117 European spring and winter barley cultivars, representing the current commercial germplasm. Haplotype amy1_H2 was significantly associated with a number of malting related traits and explained 19% of the phenotypic variation of the malting quality index (MQI) for all varieties and 35% in a subset of 72 winter barleys. The diagnostic SNP3 was associated with a 45% difference in the MQI. Within the spring barleys, the average value of haplotype amy1_H1 for friability was significantly higher than that of amy1_H4. All discovered SNPs were converted into high-throughput markers for pyrosequencing and can be used for marker assisted selection.

Population structure revealed by different marker types (SSR or DArT) has an impact on the results of genome-wide association mapping in European barley cultivars

Diversity arrays technology (DArT) and simple sequence repeat (SSR) markers were applied to investigate population structure, extent of linkage disequilibrium and genetic diversity (kinship) on a genome-wide level in European barley (Hordeum vulgare L.) cultivars. A set of 183 varieties could be clearly distinguished into spring and winter types and was classified into five subgroups based on 253 DArT or 22 SSR markers. Despite the fact, that the same number of groups was revealed by both marker types, it could be shown that this grouping was more distinct for the SSRs than the DArTs, when assigned to a Q-matrix by STRUCTURE. This was supported by the findings from principal coordinate analysis, where the SSRs showed a better resolution according to seasonal habit and row number than the DArTs. A considerable influence on the rate of significant associations with malting and kernel quality parameters was revealed by different marker types in this genome-wide association study using general and mixed linear models considering population structure. Fewer spurious associations were observed when population structure was based on SSR rather than on DArT markers. We therefore conclude that it is advisable to use independent marker datasets for calculating population structure and for performing the association analysis.

Measures for interoperability of phenotypic data: minimum information requirements and formatting

BackgroundPlant phenotypic data shrouds a wealth of information which, when accurately analysed and linked to other data types, brings to light the knowledge about the mechanisms of life. As phenotyping is a field of research comprising manifold, diverse and time-consuming experiments, the findings can be fostered by reusing and combining existing datasets. Their correct interpretation, and thus replicability, comparability and interoperability, is possible provided that the collected observations are equipped with an adequate set of metadata. So far there have been no common standards governing phenotypic data description, which hampered data exchange and reuse.ResultsIn this paper we propose the guidelines for proper handling of the information about plant phenotyping experiments, in terms of both the recommended content of the description and its formatting. We provide a document called “Minimum Information About a Plant Phenotyping Experiment”, which specifies what information about each experiment should be given, and a Phenotyping Configuration for the ISA-Tab format, which allows to practically organise this information within a dataset. We provide examples of ISA-Tab-formatted phenotypic data, and a general description of a few systems where the recommendations have been implemented.ConclusionsAcceptance of the rules described in this paper by the plant phenotyping community will help to achieve findable, accessible, interoperable and reusable data.

Meta-All: a system for managing metabolic pathway information

BackgroundMany attempts are being made to understand biological subjects at a systems level. A major resource for these approaches are biological databases, storing manifold information about DNA, RNA and protein sequences including their functional and structural motifs, molecular markers, mRNA expression levels, metabolite concentrations, protein-protein interactions, phenotypic traits or taxonomic relationships. The use of these databases is often hampered by the fact that they are designed for special application areas and thus lack universality. Databases on metabolic pathways, which provide an increasingly important foundation for many analyses of biochemical processes at a systems level, are no exception from the rule. Data stored in central databases such as KEGG, BRENDA or SABIO-RK is often limited to read-only access. If experimentalists want to store their own data, possibly still under investigation, there are two possibilities. They can either develop their own information system for managing that own data, which is very time-consuming and costly, or they can try to store their data in existing systems, which is often restricted. Hence, an out-of-the-box information system for managing metabolic pathway data is needed.ResultsWe have designed META-ALL, an information system that allows the management of metabolic pathways, including reaction kinetics, detailed locations, environmental factors and taxonomic information. Data can be stored together with quality tags and in different parallel versions. META-ALL uses Oracle DBMS and Oracle Application Express. We provide the META-ALL information system for download and use. In this paper, we describe the database structure and give information about the tools for submitting and accessing the data. As a first application of META-ALL, we show how the information contained in a detailed kinetic model can be stored and accessed.ConclusionMETA-ALL is a system for managing information about metabolic pathways. It facilitates the handling of pathway-related data and is designed to help biochemists and molecular biologists in their daily research. It is available on the Web at http://bic-gh.de/meta-all and can be downloaded free of charge and installed locally.

Development of SNP markers for genes of the phenylpropanoid pathway and their association to kernel and malting traits in barley

BackgroundFlavonoids are an important class of secondary compounds in angiosperms. Next to certain biological functions in plants, they play a role in the brewing process and have an effect on taste, color and aroma of beer. The aim of this study was to reveal the haplotype diversity of candidate genes involved in the phenylpropanoid biosynthesis pathway in cultivated barley varieties (Hordeum vulgare L.) and to determine associations to kernel and malting quality parameters.ResultsFive genes encoding phenylalanine ammonia-lyase (PAL), cinnamate 4-hydroxylase (C4H), chalcone synthase (CHS), flavanone 3-hydroxylase (F3H) and dihydroflavonol reductase (DFR) of the phenylpropanoid biosynthesis pathway were partially resequenced in 16 diverse barley reference genotypes. Their localization in the barley genome, their genetic structure, and their genetic variation e.g. single nucleotide polymorphism (SNP) and Insertion/Deletion (InDel) patterns were revealed. In total, 130 SNPs and seven InDels were detected. Of these, 21 polymorphisms were converted into high-throughput pyrosequencing markers. The resulting SNP and haplotype patterns were used to calculate associations with kernel and malting quality parameters.ConclusionsSNP patterns were found to be highly variable for the investigated genes. The developed high-throughput markers are applicable for assessing the genetic variability and for the determination of haplotype patterns in a set of barley accessions. The candidate genes PAL, C4H and F3H were shown to be associated to several malting properties like glassiness (PAL), viscosity (C4H) or to final attenuation (F3H).

Information Retrieval in Life Sciences: A Programmatic Survey

Biomedical databases are a major resource of knowledge for research in the life sciences. The biomedical knowledge is stored in a network of thousands of databases, repositories and ontologies. These data repositories differ substantially in granularity of data, storage formats, database systems, supported data models and interfaces. In order to make full use of available data resources, the high number of heterogeneous query methods and frontends requires high bioinformatic skills. Consequently, the manual inspection of database entries and citations is a time-consuming task for which methods from computer science should be applied.Concepts and algorithms from information retrieval (IR) play a central role in facing those challenges. While originally developed to manage and query less structured data, information retrieval techniques become increasingly important for the integration of life science data repositories and associated information. This chapter provides an overview of IR concepts and their current applications in life sciences. Enriched by a high number of selected references to pursuing literature, the following sections will successively build a practical guide for biologists and bioinformaticians.