Combined linkage and association mapping identifies a major QTL (qRtsc8-1), conferring tar spot complex resistance in maize.

KEY MESSAGE: A major QTL ( qRtsc8 - 1 ) conditioning resistance to tar spot complex of maize and occurring at a frequency of 3.5 % across 890 maize inbred lines. Tar spot complex (TSC) is a highly destructive disease of maize found in some countries in America. Identification of TSC resistant germplasm and elucidating the genetic mechanism of resistance is crucial for the use of host resistance to manage this disease. We evaluated 890 elite maize inbred lines in multiple environments and used genome wide association analysis (GWAS) with genotypic data from Illumina MaizeSNP50 BeadChip containing 56 K SNPs to dissect the genetics of TSC resistance. GWAS results were validated through linkage analysis in three bi-parental populations derived from different resistant and susceptible parents. Through GWAS, three TSC resistance loci were identified on chromosome 2, 7 and 8 (-log10 (p) > 5.99). A major quantitative resistance locus (QTL) designated qRtsc8-1, was detected on maize chromosome bin 8.03. qRtsc8-1, was confirmed in three independent bi-parental populations and it accounted for 18-43 % of the observed phenotypic variation for TSC. A rare haplotype within the qRtsc8-1 region, occurring at a frequency of 3.5 % increased TSC resistance by 14 %. Candidate gene analysis revealed that a leucine-rich repeat receptor-like protein (LRR-RLKs) gene family maybe the candidate gene for qRtsc8-1. Identification and localization of a major locus conditioning TSC resistance provides the foundation for fine mapping qRtsc8-1 and developing functional markers for improving TSC resistance in maize breeding programs. To the best of our knowledge, this is the first report of a major QTL for TSC resistance.

The plant ontology as a tool for comparative plant anatomy and genomic analyses.

The Plant Ontology (PO; http://www.plantontology.org/) is a publicly available, collaborative effort to develop and maintain a controlled, structured vocabulary ('ontology') of terms to describe plant anatomy, morphology and the stages of plant development. The goals of the PO are to link (annotate) gene expression and phenotype data to plant structures and stages of plant development, using the data model adopted by the Gene Ontology. From its original design covering only rice, maize and Arabidopsis, the scope of the PO has been expanded to include all green plants. The PO was the first multispecies anatomy ontology developed for the annotation of genes and phenotypes. Also, to our knowledge, it was one of the first biological ontologies that provides translations (via synonyms) in non-English languages such as Japanese and Spanish. As of Release #18 (July 2012), there are about 2.2 million annotations linking PO terms to >110,000 unique data objects representing genes or gene models, proteins, RNAs, germplasm and quantitative trait loci (QTLs) from 22 plant species. In this paper, we focus on the plant anatomical entity branch of the PO, describing the organizing principles, resources available to users and examples of how the PO is integrated into other plant genomics databases and web portals. We also provide two examples of comparative analyses, demonstrating how the ontology structure and PO-annotated data can be used to discover the patterns of expression of the LEAFY (LFY) and terpene synthase (TPS) gene homologs.

The Ontologies Community of Practice: A CGIAR Initiative for Big Data in Agrifood Systems.

Heterogeneous and multidisciplinary data generated by research on sustainable global agriculture and agrifood systems requires quality data labeling or annotation in order to be interoperable. As recommended by the FAIR principles, data, labels, and metadata must use controlled vocabularies and ontologies that are popular in the knowledge domain and commonly used by the community. Despite the existence of robust ontologies in the Life Sciences, there is currently no comprehensive full set of ontologies recommended for data annotation across agricultural research disciplines. In this paper, we discuss the added value of the Ontologies Community of Practice (CoP) of the CGIAR Platform for Big Data in Agriculture for harnessing relevant expertise in ontology development and identifying innovative solutions that support quality data annotation. The Ontologies CoP stimulates knowledge sharing among stakeholders, such as researchers, data managers, domain experts, experts in ontology design, and platform development teams.

Sensitive and specific detection of Xanthomonas campestris pv. vesicatoria by PCR using pathovar-specific primers based on rhs family gene sequences.

The present study describes PCR assay to detect bacterial spot caused by Xanthomonas campestris pv. vesicatoria in pepper and tomato. One set of PCR primer was developed to amplify gene required for an rhs family gene homologous to rhsA, cell envelope biogenesis, outer membrane. Only a PCR product of a 517bp was produced in PCR reaction with the Xanthomonas campestris pv. vesicatoria (XCVF/XCVR) primer set. A specific, and highly sensitive and rapid PCR assay for the detection of X. campestris pv. vesicatoria was achieved. The protocol can be used as a reliable diagnostic tool for specific detection of X. campestris pv. vesicatoria in pepper or tomato.

Genetic organization of the hrp genes cluster in Erwinia pyrifoliae and characterization of HR active domains in HrpNEp protein by mutational analysis.

The disease-specific (dsp) region and the hypersensitive response and pathogenicity (hrp) genes, including the hrpW, hrpNEp, and hrpC operons have previously been sequenced in Erwinia pyrifoliae WT3 [Shrestha et al. (2005a)]. In this study, the remaining hrp genes, including the hrpC, hrpA, hrpS, hrpXY, hrpL and hrpJ operons, were determined. The hrp genes cluster (ca. 38 kb) was comprised of eight transcriptional units and contained nine hrc (hrp conserved) genes. The genetic organization of the hrp/hrc genes and their orientation for the transcriptions were also similar to and collinear with those of E. amylovora, showing > or = 80% homologies. However, ORFU1 and ORFU2 of unknown functions, present between the hrpA and hrpS operons of E. amylovora, were absent in E. pyrifoliae. To determine the HR active domains, several proteins were prepared from truncated fragments of the N-terminal and the C-terminal regions of HrpN(Ep) protein of E. pyrifoliae. The proteins prepared from the N-terminal region elicited HR, but not from those of the C-terminal region indicating that HR active domains are located in only N-terminal region of the HrpN(Ep) protein. Two synthetic oligopeptides produced HR on tobacco confirming presence of two HR active domains in the HrpN(Ep). The HR positive N-terminal fragment (HN delta C187) was further narrowed down by deleting C-terminal amino acids and internal amino acids to investigate whether amino acid insertion region have role in faster and stronger HR activity in HrpN(Ep) than HrpN(Ea). The HrpN(Ep) mutant proteins HN delta C187 (D1AIR), HN delta C187 (D2AIR) and HN delta C187 (DM41) retained similar HR activation to that of wild-type HrpN(Ep). However, the HrpN(Ep) mutant protein HN delta C187 (D3AIR) lacking third amino acid insertion region (102 to 113 aa) reduced HR when compared to that of wild-type HrpN(Ep). Reduction in HR elicitation could not be observed when single amino acids at different positions were substituted at third amino acids insertion region. But, substitution of amino acids at L103R, L106K and L110R showed reduction in HR activity on tobacco suggesting their importance in activation of HR faster in the HrpN(Ep) although it requires further detailed analysis.

PCR-based specific detection of Ralstonia solanacearum by amplification of cytochrome c1 signal peptide sequences.

A polymerase chain reaction (PCR)-based method was developed to detect the DNA of Ralstonia solanacearum, the causal agent of bacterial wilt in various crop plants. One pair of primers (RALSF and RALSR), designed using cytochrome c1 signal peptide sequences specific to R. solanacearum, produced a PCR product of 932 bp from 13 isolates of R. solanacearum from several countries. The primer specificity was then tested using DNA from 21 isolates of Ralstonia, Pseudomonas, Burkholderia, Xanthomonas, and Fusarium oxysporum f. sp. dianthi. The specificity of the cytochrome c1 signal peptide sequences in R. solanacearum was further confirmed by a DNA-dot blot analysis. Moreover, the primer pair was able to detect the pathogen in artificially inoculated soil and tomato plants. Therefore, the present results indicate that the primer pair can be effectively used for the detection of R. solanacearum in soil and host plants.

Developing data interoperability using standards: A wheat community use case.

In this article, we present a joint effort of the wheat research community, along with data and ontology experts, to develop wheat data interoperability guidelines. Interoperability is the ability of two or more systems and devices to cooperate and exchange data, and interpret that shared information. Interoperability is a growing concern to the wheat scientific community, and agriculture in general, as the need to interpret the deluge of data obtained through high-throughput technologies grows. Agreeing on common data formats, metadata, and vocabulary standards is an important step to obtain the required data interoperability level in order to add value by encouraging data sharing, and subsequently facilitate the extraction of new information from existing and new datasets. During a period of more than 18 months, the RDA Wheat Data Interoperability Working Group (WDI-WG) surveyed the wheat research community about the use of data standards, then discussed and selected a set of recommendations based on consensual criteria. The recommendations promote standards for data types identified by the wheat research community as the most important for the coming years: nucleotide sequence variants, genome annotations, phenotypes, germplasm data, gene expression experiments, and physical maps. For each of these data types, the guidelines recommend best practices in terms of use of data formats, metadata standards and ontologies. In addition to the best practices, the guidelines provide examples of tools and implementations that are likely to facilitate the adoption of the recommendations. To maximize the adoption of the recommendations, the WDI-WG used a community-driven approach that involved the wheat research community from the start, took into account their needs and practices, and provided them with a framework to keep the recommendations up to date. We also report this approach's potential to be generalizable to other (agricultural) domains.

Genome-Wide Association Study and QTL Mapping Reveal Genomic Loci Associated with Fusarium Ear Rot Resistance in Tropical Maize Germplasm.

Fusarium ear rot (FER) incited by Fusarium verticillioides is a major disease of maize that reduces grain quality globally. Host resistance is the most suitable strategy for managing the disease. We report the results of genome-wide association study (GWAS) to detect alleles associated with increased resistance to FER in a set of 818 tropical maize inbred lines evaluated in three environments. Association tests performed using 43,424 single-nucleotide polymorphic (SNPs) markers identified 45 SNPs and 15 haplotypes that were significantly associated with FER resistance. Each associated SNP locus had relatively small additive effects on disease resistance and accounted for 1-4% of trait variation. These SNPs and haplotypes were located within or adjacent to 38 candidate genes, 21 of which were candidate genes associated with plant tolerance to stresses, including disease resistance. Linkage mapping in four biparental populations to validate GWAS results identified 15 quantitative trait loci (QTL) associated with F. verticillioides resistance. Integration of GWAS and QTL to the maize physical map showed eight colocated loci on chromosomes 2, 3, 4, 5, 9, and 10. QTL on chromosomes 2 and 9 are new. These results reveal that FER resistance is a complex trait that is conditioned by multiple genes with minor effects. The value of selection on identified markers for improving FER resistance is limited; rather, selection to combine small effect resistance alleles combined with genomic selection for polygenic background for both the target and general adaptation traits might be fruitful for increasing FER resistance in maize.

Bridging the phenotypic and genetic data useful for integrated breeding through a data annotation using the Crop Ontology developed by the crop communities of practice.

The Crop Ontology (CO) of the Generation Challenge Program (GCP) (http://cropontology.org/) is developed for the Integrated Breeding Platform (IBP) (http://www.integratedbreeding.net/) by several centers of The Consultative Group on International Agricultural Research (CGIAR): bioversity, CIMMYT, CIP, ICRISAT, IITA, and IRRI. Integrated breeding necessitates that breeders access genotypic and phenotypic data related to a given trait. The CO provides validated trait names used by the crop communities of practice (CoP) for harmonizing the annotation of phenotypic and genotypic data and thus supporting data accessibility and discovery through web queries. The trait information is completed by the description of the measurement methods and scales, and images. The trait dictionaries used to produce the Integrated Breeding (IB) fieldbooks are synchronized with the CO terms for an automatic annotation of the phenotypic data measured in the field. The IB fieldbook provides breeders with direct access to the CO to get additional descriptive information on the traits. Ontologies and trait dictionaries are online for cassava, chickpea, common bean, groundnut, maize, Musa, potato, rice, sorghum, and wheat. Online curation and annotation tools facilitate (http://cropontology.org) direct maintenance of the trait information and production of trait dictionaries by the crop communities. An important feature is the cross referencing of CO terms with the Crop database trait ID and with their synonyms in Plant Ontology (PO) and Trait Ontology (TO). Web links between cross referenced terms in CO provide online access to data annotated with similar ontological terms, particularly the genetic data in Gramene (University of Cornell) or the evaluation and climatic data in the Global Repository of evaluation trials of the Climate Change, Agriculture and Food Security programme (CCAFS). Cross-referencing and annotation will be further applied in the IBP.

Multifunctional crop trait ontology for breeders' data: field book, annotation, data discovery and semantic enrichment of the literature.

BACKGROUND AND AIMS: Agricultural crop databases maintained in gene banks of the Consultative Group on International Agricultural Research (CGIAR) are valuable sources of information for breeders. These databases provide comparative phenotypic and genotypic information that can help elucidate functional aspects of plant and agricultural biology. To facilitate data sharing within and between these databases and the retrieval of information, the crop ontology (CO) database was designed to provide controlled vocabulary sets for several economically important plant species. METHODOLOGY: Existing public ontologies and equivalent catalogues of concepts covering the range of crop science information and descriptors for crops and crop-related traits were collected from breeders, physiologists, agronomists, and researchers in the CGIAR consortium. For each crop, relationships between terms were identified and crop-specific trait ontologies were constructed following the Open Biomedical Ontologies (OBO) format standard using the OBO-Edit tool. All terms within an ontology were assigned a globally unique CO term identifier. PRINCIPAL RESULTS: The CO currently comprises crop-specific traits for chickpea (Cicer arietinum), maize (Zea mays), potato (Solanum tuberosum), rice (Oryza sativa), sorghum (Sorghum spp.) and wheat (Triticum spp.). Several plant-structure and anatomy-related terms for banana (Musa spp.), wheat and maize are also included. In addition, multi-crop passport terms are included as controlled vocabularies for sharing information on germplasm. Two web-based online resources were built to make these COs available to the scientific community: the 'CO Lookup Service' for browsing the CO; and the 'Crops Terminizer', an ontology text mark-up tool. CONCLUSIONS: The controlled vocabularies of the CO are being used to curate several CGIAR centres' agronomic databases. The use of ontology terms to describe agronomic phenotypes and the accurate mapping of these descriptions into databases will be important steps in comparative phenotypic and genotypic studies across species and gene-discovery experiments.