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.

Modern breeding methods integrate next-generation sequencing and phenomics to identify plants with the best characteristics and greatest genetic merit for use as parents in subsequent breeding cycles to ultimately create improved cultivars able to sustain high adoption rates by farmers. This data-driven approach hinges on strong foundations in data management, quality control, and analytics. Of crucial importance is a central database able to (1) track breeding materials, (2) store experimental evaluations, (3) record phenotypic measurements using consistent ontologies, (4) store genotypic information, and (5) implement algorithms for analysis, prediction, and selection decisions. Because of the complexity of the breeding process, breeding databases also tend to be complex, difficult, and expensive to implement and maintain. Here, we present a breeding database system, Breedbase (https://breedbase.org/, last accessed 4/18/2022). Originally initiated as Cassavabase (https://cassavabase.org/, last accessed 4/18/2022) with the NextGen Cassava project (https://www.nextgencassava.org/, last accessed 4/18/2022), and later developed into a crop-agnostic system, it is presently used by dozens of different crops and projects. The system is web based and is available as open source software. It is available on GitHub (https://github.com/solgenomics/, last accessed 4/18/2022) and packaged in a Docker image for deployment (https://hub.docker.com/u/breedbase, last accessed 4/18/2022). The Breedbase system enables breeding programs to better manage and leverage their data for decision making within a fully integrated digital ecosystem.

Summary: Manihot esculenta (cassava) is a root crop originating from South America that is a major staple in the tropics, including in marginal environments. This study focused on South American and African germplasm and investigated the genetic architecture of hydrogen cyanide (HCN), a major component of root quality. HCN, representing total cyanogenic glucosides, is a plant defense component against herbivory but is also toxic for human consumption. We genotyped 3354 landraces and modern breeding lines originating from 26 Brazilian states and 1389 individuals were phenotypically characterized across multi‐year trials for HCN. All plant material was subjected to high‐density genotyping using genotyping by sequencing. We performed genome‐wide association mapping to characterize the genetic architecture and gene mapping of HCN. Field experiments revealed strong broad‐ and narrow‐sense trait heritability (0.82 and 0.41, respectively). Two major loci were identified, encoding for an ATPase and a MATE protein, and contributing up to 7 and 30% of the HCN concentration in roots, respectively. We developed diagnostic markers for breeding applications, validated trait architecture consistency in African germplasm and investigated further evidence for the domestication of sweet and bitter cassava. Fine genomic characterization revealed: (i) the major role played by vacuolar transporters in regulating HCN content; (ii) the co‐domestication of sweet and bitter cassava major alleles are dependent upon geographical zone; and (iii) the major loci allele for high HCN in M. esculenta Crantz seems to originate from its ancestor, M. esculenta subsp. flabellifolia. Taken together, these findings expand our insights into cyanogenic glucosides in cassava roots and its glycosylated derivatives in plants.

Introgression of alleles from wild relatives has often been adaptive in plant breeding. However, the significance of historical hybridization events in modern breeding is often not clear. Cassava (Manihot esculenta) is among the most important staple foods in the world, sustaining hundreds of millions of people in the tropics, especially in sub-Saharan Africa. Widespread genotyping makes cassava a model for clonally propagated root and tuber crops in the developing world, and provides an opportunity to study the modern benefits and consequences of historical introgression. We detected large introgressed Manihot glaziovii genome-segments in a collection of 2742 modern cassava landraces and elite germplasm, the legacy of a 1930s era breeding to combat disease epidemics. African landraces and improved varieties were, on average, 3.8% (max 13.6%) introgressed. Introgressions accounted for a significant (mean 20%, max 56%) portion of the heritability of tested traits. M. glaziovii alleles on the distal 10 Mb of chr. 1 increased dry matter and root number. On chr. 4, introgressions in a 20 Mb region improved harvest index and brown streak disease tolerance. We observed the introgression frequency on chr. 1 double over three cycles of selection, and that later stage trials selectively excluded homozygotes from consideration as varieties. This indicates a heterozygous advantage of introgressions. However, we also found that maintaining large recombination-suppressed introgressions in the heterozygous state allowed the accumulation of deleterious mutations. We conclude that targeted recombination of introgressions would increase the efficiency of cassava breeding by allowing simultaneous fixation of beneficial alleles and purging of genetic load.

White yam (Dioscorearotundata Poir.) is one of the most important tuber crops in West Africa, where it is indigenous and represents the largest repository of biodiversity through several years of domestication, production, consumption, and trade. In this study, the genotyping-by-sequencing (GBS) approach was used to sequence 814 genotypes consisting of genebank landraces, breeding lines, and market varieties to understand the level of genetic diversity and pattern of the population structure among them. The genetic diversity among different genotypes was assessed using three complementary clustering methods, the model-based admixture, discriminant analysis of principal components (DAPC), and phylogenetic tree. ADMIXTURE analysis revealed an optimum number of four groups that matched with the number of clusters obtained through phylogenetic tree. Clustering results obtained from ADMIXTURE analysis were further validated using DAPC-based clustering. Analysis of molecular variance (AMOVA) revealed high genetic diversity (96%) within each genetic group. A network analysis was further carried out to depict the genetic relationships among the three genetic groups (breeding lines, genebank landraces, and market varieties) used in the study. This study showed that the use of advanced sequencing techniques such as GBS coupled with statistical analysis is a robust method for assessing genetic diversity and population structure in a complex crop such as white yam.