Cassava is an important crop in Africa, Asia, Latin America, and the Caribbean. Cassava can be produced adequately in drought conditions making it the ideal food security crop in marginal environments. Although cassava can tolerate drought stress, it can be genetically improved to enhance productivity in such environments. Drought adaptation studies in over three decades in cassava have identified relevant mechanisms which have been explored in conventional breeding. Drought is a quantitative trait and its multigenic nature makes it very challenging to effectively manipulate and combine genes in breeding for rapid genetic gain and selection process. Cassava has a long growth cycle of 12–18 months which invariably contributes to a long breeding scheme for the crop. Modern breeding using advances in genomics and improved genotyping, is facilitating the dissection and genetic analysis of complex traits including drought tolerance, thus helping to better elucidate and understand the genetic basis of such traits. A beneficial goal of new innovative breeding strategies is to shorten the breeding cycle using minimized, efficient or fast phenotyping protocols. While high throughput genotyping have been achieved, this is rarely the case for phenotyping for drought adaptation. Some of the storage root phenotyping in cassava are often done very late in the evaluation cycle making selection process very slow. This paper highlights some modified traits suitable for early-growth phase phenotyping that may be used to reduce drought phenotyping cycle in cassava. Such modified traits can significantly complement the high throughput genotyping procedures to fast track breeding of improved drought tolerant varieties. The need for metabolite profiling, improved phenomics to take advantage of next generation sequencing technologies and high throughput phenotyping are basic steps for future direction to improve genetic gain and maximize speed for drought tolerance breeding.

Yam (Dioscorea spp.) is an important tuber crop with tremendous potential as a functional food in the tropics and subtropics. However, the crop has not shown progressive productivity gain over decades due to various production constraints. This paper reviews the progress achieved in empirical breeding endeavours and the development, status and application of emerging breeding tools and technologies to translate genetic gains in yam improvement. Significant progress has been made in yam genetic improvement over the years which has led to the identification and development of several improved clones and sources of variability for various economically important traits. Substantial efforts have also been made to develop diverse molecular markers, transcriptome and metabolome profiles of crucial traits, trait mapping and generate reference genome sequences of the key species. However, there seems to be a slow translation of research improvements into widespread applications. These advances and the integration of empirical and emerging methods and technologies into the breeding process will enhance yam breeding efforts and ensure the quick delivery of improved varieties that possess superior agronomic and quality traits.

Cassava mosaic disease (CMD) is a serious threat to cassava production in sub-Saharan Africa. The use of genomic-assisted selection at the seedling trial stage would help to reduce the time for release, breeding cost, and resources used, hence increase selection efficiency in cassava breeding programs. Five cassava populations were screened for resistance to CMD during the seedling evaluation trial at 1, 3, and 5 months after planting using a scale of 1–5. The genotypes in the five populations were also screened using six molecular markers linked to the CMD2 gene. The correlation between the phenotypic and marker data was estimated. Based on Cassava Mosaic Disease Severity Score (CMDSS), between 53 and 82% of the progenies were resistant across the populations with an average of 70.5%. About 70% of the progenies were identified to be resistant to the disease across the populations with a range of 62–80% using the marker data. With both marker data and CMDSS combined, 40–60% of the progenies in each population, with an average of 52%, were identified to be resistant to CMD. There was a fairly significant correlation between the marker data and CMDSS in each cassava population with correlation coefficients ranging from 0.2024 to 0.3460 suggesting that novel genes not associated to the markers used might be involved in the resistance to CMD. The resistant genotypes identified in this study with potential for other desirable traits were selected for evaluation at the advanced trial stage thereby shortening the period required for the breeding program.

Cassava mosaic disease (CMD) is a major viral disease adversely affecting cassava production in Africa and Asia. Genomic regions conferring resistance to the disease have been mapped in African cassava germplasm through biparental quantitative trait loci (QTL) mapping and genome-wide association studies. To facilitate the utilization of these markers in breeding pipelines to support selections, proof-of-concept technical and biological validation research was carried out using independent pre-breeding and breeding populations. Kompetitive Allele-Specific Polymerase Chain Reaction (KASP) assays were designed from three single nucleotide polymorphism (SNP) markers linked to a major resistance locus on chromosome 12 (S12_7926132, S12_7926163) and a minor locus on chromosome 14 (S14_4626854). The designed assays were robust and easy to score with >99% genotype call rate. The overall predictive accuracy (proportion of true positives and true negatives) of the markers (S12_7926132 and S14_4626854) was 0.80 and 0.78 in the pre-breeding and breeding population, respectively. On average, genotypes that carried at least one copy of the resistant allele at the major CMD2 locus had a significantly higher yield advantage. Nevertheless, variation was observed in prediction accuracies for the major locus (S12_7926132) among sub-families from the two populations, suggesting the need for context-specific utilization, for example, by screening for co-segregation of favorable SNP alleles with resistance in the parents being used for crosses. Availability of these validated SNP markers on the uniplex KASP genotyping platform represents an important step in translational genetics toward marker-assisted selection to accelerate introgression of favorable resistant alleles in breeding populations.

Background/Objectives: Understanding the genetic diversity of soybean genotypes can provide valuable information that guides parental selection and the design of an effective hybridization strategy in a soybean breeding program. In order to identify genetically diverse, complementary, and prospective parental lines for breeding, this study set out to ascertain the genetic diversity, relationships, and population structure among 35 soybean genotypes based on agro-morphological traits and Single Nucleotide Polymorphic (SNP) marker data. Methods/Results: Cluster analysis, based on agro-morphological traits, grouped the studied genotypes into four clusters. The first two principal components accounted for 62.8% of the total phenotypic variation, where days to 50% flowering, days to 95% maturity, grain yield, shattering score, and lodging score had high and positive contributions to the total variation. Using the SNP marker information, mean values of 0.16, 0.19, 0.067, and 0.227 were obtained for minor allele frequency (MAF), polymorphic information content (PIC), observed heterozygosity (Ho), and expected heterozygosity (He), respectively. Using different clustering approaches (admixture population structure, principal component scatter plot, and hierarchical clustering), the studied genotypes were grouped into four major clusters. Conclusions:The agro-morphological and molecular analysis results indicated the existence of moderate genetic diversity among the studied genotypes. The traits identified to be significantly related to yield provide valuable information for the genetic improvement of soybeans for yield.