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.

From Nasty to Tasty: Some of our favorite food crops derive from wild relatives that were distasteful or even toxic. Domestication over many years selected for variants with reduced levels of antinutritional compounds. The wild relatives remain valuable, however, for other traits such as resistance to pathogens, but their use in crop development is complicated by the continued presence of unpalatable compounds. Itkin et al. (p. 175 , published online 20 June) elucidate the metabolic pathways and genes directing synthesis of some of these antinutritionals in potato and tomato.

Summary: We 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.

Summary: Enabling data reuse and knowledge discovery is increasingly critical in modern science, and requires an effort towards standardising data publication practices. This is particularly challenging in the plant phenotyping domain, due to its complexity and heterogeneity. We have produced the MIAPPE 1.1 release, which enhances the existing MIAPPE standard in coverage, to support perennial plants, in structure, through an explicit data model, and in clarity, through definitions and examples. We evaluated MIAPPE 1.1 by using it to express several heterogeneous phenotyping experiments in a range of different formats, to demonstrate its applicability and the interoperability between the various implementations. Furthermore, the extended coverage is demonstrated by the fact that one of the datasets could not have been described under MIAPPE 1.0. MIAPPE 1.1 marks a major step towards enabling plant phenotyping data reusability, thanks to its extended coverage, and especially the formalisation of its data model, which facilitates its implementation in different formats. Community feedback has been critical to this development, and will be a key part of ensuring adoption of the standard.

Cultivated potato is a clonally propagated autotetraploid species with a highly heterogeneous genome. Phased assemblies of six cultivars including two chromosome-scale phased genome assemblies revealed extensive allelic diversity, including altered coding and transcript sequences, preferential allele expression, and structural variation that collectively result in a highly complex transcriptome and predicted proteome, which are distributed across the homologous chromosomes. Wild species contribute to the extensive allelic diversity in tetraploid cultivars, demonstrating ancestral introgressions predating modern breeding efforts. As a clonally propagated autotetraploid that undergoes limited meiosis, dysfunctional and deleterious alleles are not purged in tetraploid potato. Nearly a quarter of the loci bore mutations are predicted to have a high negative impact on protein function, complicating breeder's efforts to reduce genetic load. The StCDF1 locus controls maturity, and analysis of six tetraploid genomes revealed that 12 allelic variants of StCDF1 are correlated with maturity in a dosage-dependent manner. Knowledge of the complexity of the tetraploid potato genome with its rampant structural variation and embedded deleterious and dysfunctional alleles will be key not only to implementing precision breeding of tetraploid cultivars but also to the construction of homozygous, diploid potato germplasm containing favorable alleles to capitalize on heterosis in F1 hybrids.