Applying FAIR Principles to Plant Phenotypic Data Management in GnpIS.

GnpIS is a data repository for plant phenomics that stores whole field and greenhouse experimental data including environment measures. It allows long-term access to datasets following the FAIR principles: Findable, Accessible, Interoperable, and Reusable, by using a flexible and original approach. It is based on a generic and ontology driven data model and an innovative software architecture that uncouples data integration, storage, and querying. It takes advantage of international standards including the Crop Ontology, MIAPPE, and the Breeding API. GnpIS allows handling data for a wide range of species and experiment types, including multiannual perennial plants experimental network or annual plant trials with either raw data, i.e., direct measures, or computed traits. It also ensures the integration and the interoperability among phenotyping datasets and with genotyping data. This is achieved through a careful curation and annotation of the key resources conducted in close collaboration with the communities providing data. Our repository follows the Open Science data publication principles by ensuring citability of each dataset. Finally, GnpIS compliance with international standards enables its interoperability with other data repositories hence allowing data links between phenotype and other data types. GnpIS can therefore contribute to emerging international federations of information systems.

Mining Plant Genomic and Genetic Data Using the GnpIS Information System.

GnpIS is an information system designed to help scientists working on plants and fungi to decipher the molecular and genetic architecture of trait variations by facilitating the navigation through genetic, genomic, and phenotypic information. The purpose of the present chapter is to illustrate how users can (1) explore datasets from phenotyping experiments in order to build new datasets for studying genotype × environment interactions in traits, (2) browse into the results of other genetic analysis data such as GWAS to generate or check working hypothesis about candidate genes or to identify important alleles and germplasms for breeding programs, and (3) explore the polymorphism in specific area of the genome using InterMine, JBrowse tools embedded in the GnpIS information system.

Towards an open grapevine information system.

Viticulture, like other fields of agriculture, is currently facing important challenges that will be addressed only through sustained, dedicated and coordinated research. Although the methods used in biology have evolved tremendously in recent years and now involve the routine production of large data sets of varied nature, in many domains of study, including grapevine research, there is a need to improve the findability, accessibility, interoperability and reusability (FAIR-ness) of these data. Considering the heterogeneous nature of the data produced, the transnational nature of the scientific community and the experience gained elsewhere, we have formed an open working group, in the framework of the International Grapevine Genome Program (www.vitaceae.org), to construct a coordinated federation of information systems holding grapevine data distributed around the world, providing an integrated set of interfaces supporting advanced data modeling, rich semantic integration and the next generation of data mining tools. To achieve this goal, it will be critical to develop, implement and adopt appropriate standards for data annotation and formatting. The development of this system, the GrapeIS, linking genotypes to phenotypes, and scientific research to agronomical and oeneological data, should provide new insights into grape biology, and allow the development of new varieties to meet the challenges of biotic and abiotic stress, environmental change, and consumer demand.

Mouse monoclonal antibodies to bovine blood group antigens: additional results.

Seven fusions of mouse myeloma cells with spleen cells from mice immunized with bovine red cells yielded 61 clones producing discriminant antibodies out of total of 651 secreting clones. Although antigenic factors of all known bovine blood group systems were present on the donors' cells, the antibodies identified reacted with antigenic factors from only five systems, A, B, F, S and Z. The antibody specificities produced by more than two clones were anti-A1 or -A2 (21 clones), -S (9),- Z(6),-G' (3) and -V1 (3). The absence of clones secreting antibodies to antigens of the other systems, especially the complex C system, remains unexplained. The properties of the antibodies reacting with antigens of the S system (anti-SU", anti-SUU') and of the B system (O-like antibodies) are in accordance with previous interpretations of polyclonal sera and with present knowledge of the genetic map of the B system.

The C system of cattle blood groups. 1. Additional factors in the system.

Four additional cattle blood group antigenic factors, provisionally termed F1, F6, F10 and F15, were shown to belong to the C system. Factor F1 appears to be a linear subtype of C" (initially designated F2, or P1B1). It is suggested that future international nomenclature should adopt C"1 and C"2 in place of F1 and C". No phenogroup was found to include C" together with C2 or C1, but a few phenogroups lack the three factors. Thus C1, C2 and C" do not form a closed system within the C system as concluded by Duniec et al. (1973). The effectiveness of the additional factors to uncover the genetic variability of the C system, and to translate phenotypes into genotypes is exemplified in the Charolais breed.