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.

Global efforts are underway to biofortify cassava (Manihot esculenta Crantz) with provitamin A carotenoids to help combat dietary vitamin A deficiency afflicting the health of more than 500 million resource-poor people in Sub-Saharan Africa. To further the biofortification initiative in Uganda, a 6×6 diallel analysis was conducted to estimate combining ability of six provitamin A clones and gene actions controlling total carotenoid content (TCC), dry matter content (DMC) in cassava roots and other relevant traits. Fifteen F1 families generated from the diallel crosses were evaluated in two environments using a randomized complete block design. General combining ability (GCA) effects were significant for TCC and DMC, suggesting the relative importance of additive gene effects in controlling these traits in cassava. On the other hand, non-additive effects were predominant for root and shoot weight. MH02-073HS, with the highest level of TCC, was the best general combiner for TCC while NASE 3, a popular white-fleshed variety grown by farmers in Uganda, was the best general combiner for DMC. Such progenitors with superior GCA effects could form the genetic source for future programs targeting cassava breeding for TCC and DMC. A negative correlation was observed between TCC and DMC, which will require breeding strategies to combine both traits for increased adoption of provitamin A cassava varieties.

Global efforts are underway to develop cassava with enhanced levels of provitamin A carotenoids to sustainably meet increasing demands for food and nutrition where the crop is a major staple. Herein, we tested the effectiveness of genomic selection (GS) for rapid improvement of cassava for total carotenoids content and associated traits. We evaluated 632 clones from Uganda’s provitamin A cassava breeding pipeline and 648 West African introductions. At harvest, each clone was assessed for level of total carotenoids, dry matter content, and resistance to cassava brown streak disease (CBSD). All clones were genotyped with diversity array technology and imputed to a set of 23,431 single nucleotide polymorphic markers. We assessed predictive ability of four genomic prediction methods in scenarios of cross-validation, across population prediction, and inclusion of quantitative trait loci markers. Cross-validations produced the highest mean prediction ability for total carotenoids content (0.52) and the lowest for CBSD resistance (0.20), with G-BLUP outperforming other models tested. Across population, predictions showed low ability of Ugandan population to predict the performance of West African clones, with the highest predictive ability recorded for total carotenoids content (0.34) and the lowest for CBSD resistance (0.12) using G-BLUP. By incorporating chromosome 1 markers associated with carotenoids content as independent kernel in the G-BLUP model of a cross-validation scenario, prediction ability slightly improved from 0.52 to 0.58. These results reinforce ongoing efforts aimed at integrating GS into cassava breeding and demonstrate the utility of this tool for rapid genetic improvement.

Efforts are underway to develop staple crops with improved levels of provitamin A carotenoids to help combat dietary vitamin A deficiency (VAD), which has afflicted the health of resource-poor people in the developing world. As a staple crop for more than 500 million people in sub-Saharan Africa, cassava enriched with provitamin A carotenoids could have a widespread nutritional impact. To this effect, 13 provitamin A clones were evaluated in a randomized complete block design in six environments to assess genotype by environment interaction (GEI) effects for total carotenoid (TCC) and dry matter content (DMC) in roots. Additive main effect and multiplicative interaction analysis showed significant variation among genotypes for TCC, DMC, fresh root weight and harvest index. Environmental effects were non-significant for TCC, but GEI effects were significantly large for all traits measured. There were significant temporal increments for all traits measured within 12 months after planting. TCC correlated negatively with DMC, illustrating an important challenge to overcome when developing provitamin A cassava varieties without compromising DMC, which is a major farmer-preference trait. Nonetheless, best performing genotypes were identified for TCC, DMC and FRW, and these could constitute genetic resources for advancement or developing breeding populations through hybridization.

Introduction: The intrinsic high heterozygosity of cassava makes conventional breeding ineffective for rapid genetic improvement. However, recent advances in next generation sequencing technologies have enabled the use of high-density markers for genome-wide association studies, aimed at identifying single nucleotide polymorphisms (SNPs) linked to major traits such as cassava mosaic disease (CMD) resistance, dry matter content (DMC) and total carotenoids content (TCC). A number of these trait-linked SNPs have been converted to Kompetitive allele-specific polymerase chain reaction (KASP) markers for downstream application of marker assisted selection.Methods: We assayed 13 KASP markers to evaluate their effectiveness in selecting for CMD, DMC and TCC in 1,677 diverse cassava genotypes representing two independent breeding populations in Uganda.Results: Five KASP markers had significant co-segregation with phenotypes; CMD resistance (2), DMC (1) and TCC (2), with each marker accounting for at least 30% of the phenotypic variation. Markers located within the chromosomal regions for which strong marker-trait association loci have been characterised (chromosome 12 markers for CMD, chromosome 1 markers for DMC and TCC) had consistently superior ability to discriminate the respective phenotypes.Discussion: The results indicate varying discriminatory abilities of the KASP markers assayed and the need for their context-based use for MAS, with PSY2_572 particularly effective in selecting for high TCC. Availing the effective KASP markers on cost-effective genotyping platforms could facilitate practical implementation of marker-assisted cassava breeding for accelerated genetic gains for CMD, DMC and provitamin A carotenoids.