There is an urgent need to improve the infrastructure supporting the reuse of scholarly data. A diverse set of stakeholders—representing academia, industry, funding agencies, and scholarly publishers—have come together to design and jointly endorse a concise and measureable set of principles that we refer to as the FAIR Data Principles. The intent is that these may act as a guideline for those wishing to enhance the reusability of their data holdings. Distinct from peer initiatives that focus on the human scholar, the FAIR Principles put specific emphasis on enhancing the ability of machines to automatically find and use the data, in addition to supporting its reuse by individuals. This Comment is the first formal publication of the FAIR Principles, and includes the rationale behind them, and some exemplar implementations in the community.

Steroidal glycoalkaloids (SGAs) such as α-solanine found in solanaceous food plants--as, for example, potato--are antinutritional factors for humans. Comparative coexpression analysis between tomato and potato coupled with chemical profiling revealed an array of 10 genes that partake in SGA biosynthesis. We discovered that six of them exist as a cluster on chromosome 7, whereas an additional two are adjacent in a duplicated genomic region on chromosome 12. Following systematic functional analysis, we suggest a revised SGA biosynthetic pathway starting from cholesterol up to the tetrasaccharide moiety linked to the tomato SGA aglycone. Silencing GLYCOALKALOID METABOLISM 4 prevented accumulation of SGAs in potato tubers and tomato fruit. This may provide a means for removal of unsafe, antinutritional substances present in these widely used food crops.

SUMMARYWe explored genetic variation by sequencing a selection of 84 tomato accessions and related wild species representative of the Lycopersicon, Arcanum, Eriopersicon and Neolycopersicon groups, which has yielded a huge amount of precious data on sequence diversity in the tomato clade. Three new reference genomes were reconstructed to support our comparative genome analyses. Comparative sequence alignment revealed group-, species-and accession-specific polymorphisms, explaining characteristic fruit traits and growth habits in the various cultivars. Using gene models from the annotated Heinz 1706 reference genome, we observed differences in the ratio between non-synonymous and synonymous SNPs (dN/dS) in fruit diversification and plant growth genes compared to a random set of genes, indicating positive selection and differences in selection pressure between crop accessions and wild species. In wild species, the number of single-nucleotide polymorphisms (SNPs) exceeds 10 million, i.e. 20-fold higher than found in most of the crop accessions, indicating dramatic genetic erosion of crop and heirloom tomatoes. In addition, the highest levels of heterozygosity were found for allogamous self-incompatible wild species, while facultative and autogamous self-compatible species display a lower heterozygosity level. Using whole-genome SNP information for maximum-likelihood analysis, we achieved complete tree resolution, whereas maximum-likelihood trees based on SNPs from ten fruit and growth genes show incomplete resolution for the crop accessions, partly due to the effect of heterozygous SNPs. Finally, results suggest that phylogenetic relationships are correlated with habitat, indicating the occurrence of geographical races within these groups, which is of practical importance for Solanum genome evolution studies.

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Tomato (Solanum lycopersicum) is susceptible to grey mold (Botrytis cinerea). Partial resistance to this fungus has been identiWed in accessions of wild relatives of tomato such as Solanum habrochaites LYC4. In a previous F 2 mapping study, three QTLs conferring resistance to B. cinerea (Rbcq1, Rbcq2 and Rbcq4a) were identiWed. As it was probable that this study had not identiWed all QTLs involved in resistance we developed an introgression line (IL) population (n = 30), each containing a S. habrochaites introgression in the S. lycopersicum cv. Moneymaker genetic background. On average each IL contained 5.2% of the S. habrochaites genome and together the lines provide an estimated coverage of 95%. The level of susceptibility to B. cinerea for each of the ILs was assessed in a greenhouse trial and compared to the susceptible parent S. lycopersicum cv. Moneymaker. The eVect of the three previously identiWed loci could be conWrmed and seven additional loci were detected. Some ILs contains multiple QTLs and the increased resistance to B. cinerea in these ILs is in line with a completely additive model. We conclude that this set of QTLs oVers good perspectives for breeding of B. cinerea resistant cultivars and that screening an IL population is more sensitive for detection of QTLs conferring resistance to B. cinerea than the analysis in an F 2 population.

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Apple (Malus×domestica Borkh) is among the main sources of phenolic compounds in the human diet. The genetic basis of the quantitative variations of these potentially beneficial phenolic compounds was investigated. A segregating F1 population was used to map metabolite quantitative trait loci (mQTLs). Untargeted metabolic profiling of peel and flesh tissues of ripe fruits was performed using liquid chromatography–mass spectrometry (LC-MS), resulting in the detection of 418 metabolites in peel and 254 in flesh. In mQTL mapping using MetaNetwork, 669 significant mQTLs were detected: 488 in the peel and 181 in the flesh. Four linkage groups (LGs), LG1, LG8, LG13, and LG16, were found to contain mQTL hotspots, mainly regulating metabolites that belong to the phenylpropanoid pathway. The genetics of annotated metabolites was studied in more detail using MapQTL®. A number of quercetin conjugates had mQTLs on LG1 or LG13. The most important mQTL hotspot with the largest number of metabolites was detected on LG16: mQTLs for 33 peel-related and 17 flesh-related phenolic compounds. Structural genes involved in the phenylpropanoid biosynthetic pathway were located, using the apple genome sequence. The structural gene leucoanthocyanidin reductase (LAR1) was in the mQTL hotspot on LG16, as were seven transcription factor genes. The authors believe that this is the first time that a QTL analysis was performed on such a high number of metabolites in an outbreeding plant species.

Motivation Modern genomic breeding methods rely heavily on very large amounts of phenotyping and genotyping data, presenting new challenges in effective data management and integration. Recently, the size and complexity of datasets have increased significantly, with the result that data are often stored on multiple systems. As analyses of interest increasingly require aggregation of datasets from diverse sources, data exchange between disparate systems becomes a challenge. Results To facilitate interoperability among breeding applications, we present the public plant Breeding Application Programming Interface (BrAPI). BrAPI is a standardized web service API specification. The development of BrAPI is a collaborative, community-based initiative involving a growing global community of over a hundred participants representing several dozen institutions and companies. Development of such a standard is recognized as critical to a number of important large breeding system initiatives as a foundational technology. The focus of the first version of the API is on providing services for connecting systems and retrieving basic breeding data including germplasm, study, observation, and marker data. A number of BrAPI-enabled applications, termed BrAPPs, have been written, that take advantage of the emerging support of BrAPI by many databases. Availability and implementation More information on BrAPI, including links to the specification, test suites, BrAPPs, and sample implementations is available at https://brapi.org/. The BrAPI specification and the developer tools are provided as free and open source.