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.

A better understanding of the structure and extent of genetic variability in a breeding population of a crop is essential for translating genetic diversity to genetic gain. We assessed the nature and pattern of genetic variability and differentiation in a panel of 100 winged-yam (Dioscorea alata) accessions using 24 phenotypic traits and 6,918 single nucleotide polymorphism (SNP) markers. Multivariate analysis for phenotypic variability indicated that all phenotypic traits assessed were useful in discriminating the yam clones and cultivars. Cluster analysis based on phenotypic data distinguished two significant groups, while a corresponding analysis with SNP markers indicated three genetic groups. However, joint analysis for the phenotypic and genotypic data provided three clusters that could be useful for the identification of heterotic groups in the D. alata breeding program. Our analysis for phenotypic and molecular level diversity provided valuable information about overall diversity and variation in economically important traits useful for establishing crossing panels with contrasting traits of interest. The selection and hybridization of parental lines from the different heterotic groups identified would facilitate maximizing diversity and exploiting population heterosis in the D. alata breeding program.

Yam (Dioscorea spp.) is a nutritional and medicinal staple tuber crop grown in the tropics and sub-tropics. Among the food yam species, water yam (Dioscorea alata L.) is the most widely distributed and cultivated species worldwide. Tuber dry matter content (DMC) and oxidative browning (OxB) are important quality attributes that determine cultivar acceptability in water yam. This study used a single nucleotide polymorphism (SNP) assay from a diversity arrays technology (DArT) platform for a genome-wide association study (GWAS) of the two quality traits in a panel of 100 water yam clones grown in three environments. The marker–trait association analysis identified significant SNPs associated with tuber DMC on chromosomes 6 and 19 and with OxB on chromosome 5. The significant SNPs cumulatively explained 45.87 and 12.74% of the total phenotypic variation for the tuber DMC and OxB, respectively. Gene annotation for the significant SNP loci identified important genes associated in the process of the proteolytic modification of carbohydrates in the dry matter accumulation pathway as well as fatty acid β-oxidation in peroxisome for enzymatic oxidation. Additional putative genes were also identified in the peak SNP sites for both tuber dry matter and enzymatic oxidation with unknown functions. The results of this study provide valuable insight for further dissection of the genetic architecture of tuber dry matter and enzymatic oxidation in water yam. They also highlight SNP variants and genes useful for genomics-informed selection decisions in the breeding process for improving food quality traits in water yam.

Background: Improvement of tuber yield and tolerance to viruses are priority objectives in white Guinea yam breeding programs. However, phenotypic selection for these traits is quite challenging due to phenotypic plasticity and cumbersome screening of phenotypic-induced variations. This study assessed quantitative trait nucleotides (QTNs) and the underlying candidate genes related to tuber yield per plant (TYP) and yam mosaic virus (YMV) tolerance in a panel of 406 white Guinea yam (Dioscorea rotundata) breeding lines using a genome-wide association study (GWAS).Results: Population structure analysis using 5,581 SNPs differentiated the 406 genotypes into seven distinct sub-groups based delta K. Marker-trait association (MTA) analysis using the multi-locus linear model (mrMLM) identified seventeen QTN regions significant for TYP and five for YMV with various effects. The seveteen QTNs were detected on nine chromosomes, while the five QTNs were identified on five chromosomes. We identified variants responsible for predicting higher yield and low virus severity scores in the breeding panel through the marker-effect prediction. Gene annotation for the significant SNP loci identified several essential putative genes associated with the growth and development of tuber yield and those that code for tolerance to mosaic virus.Conclusion: Application of different multi-locus models of GWAS identified 22 QTNs. Our results provide valuable insight for marker validation and deployment for tuber yield and mosaic virus tolerance in white yam breeding. The information on SNP variants and genes from the present study would fast-track the application of genomics-informed selection decisions in breeding white Guinea yam for rapid introgression of the targeted traits through markers validation.

Yam (Dioscorea spp.) is a monocotyledonous herbaceous vine cultivated for its starchy underground or aerial tubers in the tropics and subtropics. It is an allogamous and polyploid species that reproduces by both sexual and asexual mechanisms. However, many of the landrace cultivars, including most of the popular varieties, reproduce exclusively by vegetative propagation (planting the tubers). These varieties are either sterile or produce sparse and irregular flowering with high flower abortion rate, low fruit and seed set. Production of crossbreed seeds for genetic improvement and for maintaining genetic diversity in yams is, therefore, mainly achieved through natural or managed pollination. Flowering in yam is mostly dioecious and, in some instances, monoecious. Flowering asynchrony, sticky nature of the pollen grains, and cross incompatibility are among the challenges in making genetic progress in yam breeding. There are many limitations in basic and applied knowledge of yam flower biology and pollination. This paper, therefore, reviews the flowering biology, pollination, and methods of improving pollination efficiency in yam breeding programs.

Background: Striga hermonthica (Benth.) parasitism militates against increased maize production and productivity in savannas of sub-Saharan Africa (SSA). Identification of Striga resistance genes is important in developing genotypes with durable resistance. So far, there is only one report on the existence of QTL for Striga resistance on chromosome 6 of maize. The objective of this study was to identify genomic regions significantly associated with grain yield and other agronomic traits under artificial Striga field infestation. A panel of 132 early-maturing maize inbreds were phenotyped for key agronomic traits under Striga-infested and Striga-free conditions. The inbred lines were also genotyped using 47,440 DArTseq markers from which 7224 markers were retained for population structure analysis and genome-wide association study (GWAS). Results: The inbred lines were grouped into two major clusters based on structure analysis as well as the neighbor-joining hierarchical clustering. A total of 24 SNPs significantly associated with grain yield, Striga damage at 8 and 10 weeks after planting (WAP), ears per plant and ear aspect under Striga infestation were detected. Under Striga-free conditions, 11 SNPs significantly associated with grain yield, number of ears per plant and ear aspect were identified. Three markers physically located close to the putative genes GRMZM2G164743 (bin 10.05), GRMZM2G060216 (bin 3.06) and GRMZM2G103085 (bin 5.07) were detected, linked to grain yield, Striga damage at 8 and 10 WAP and number of ears per plant under Striga infestation, explaining 9 to 42% of the phenotypic variance. Furthermore, the S9_154,978,426 locus on chromosome 9 was found at 2.61 Mb close to the ZmCCD1 gene known to be associated with the reduction of strigolactone production in the maize roots. Conclusions: Presented in this study is the first report of the identification of significant loci on chromosomes 9 and 10 of maize that are closely linked to ZmCCD1 and amt5 genes, respectively and may be related to plant defense mechanisms against Striga parasitism. After validation, the identified loci could be targets for breeders for marker-assisted selection (MAS) to accelerate genetic enhancement of maize for Striga resistance in the tropics, particularly in SSA, where the parasitic weed is endemic.