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.

The nutrient-rich tubers of the greater yam,Dioscorea alataL., provide food and income security for millions of people around the world. Despite its global importance, however, greater yam remains an orphan crop. Here, we address this resource gap by presenting a highly contiguous chromosome-scale genome assembly ofD. alatacombined with a dense genetic map derived from African breeding populations. The genome sequence reveals an ancient allotetraploidization in theDioscorealineage, followed by extensive genome-wide reorganization. Using the genomic tools, we find quantitative trait loci for resistance to anthracnose, a damaging fungal pathogen of yam, and several tuber quality traits. Genomic analysis of breeding lines reveals both extensive inbreeding as well as regions of extensive heterozygosity that may represent interspecific introgression during domestication. These tools and insights will enable yam breeders to unlock the potential of this staple crop and take full advantage of its adaptability to varied environments.

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.

Understanding the diversity and genetic relationships among and within crop germplasm is invaluable for genetic improvement. This study assessed genetic diversity in a panel of 173D. rotundataaccessions using joint analysis for 23 morphological traits and 136,429 SNP markers from the whole-genome resequencing platform. Various diversity matrices and clustering methods were evaluated for a comprehensive characterization of genetic diversity in white Guinea yam from West Africa at phenotypic and molecular levels. The translation of the different diversity matrices from the phenotypic and genomic information into distinct groups varied with the hierarchal clustering methods used. Gower distance matrix based on phenotypic data and identity by state (IBS) distance matrix based on SNP data with the UPGMA clustering method found the best fit to dissect the genetic relationship in current set materials. However, the grouping pattern was inconsistent (r = − 0.05) between the morphological and molecular distance matrices due to the non-overlapping information between the two data types. Joint analysis for the phenotypic and molecular information maximized a comprehensive estimate of the actual diversity in the evaluated materials. The results from our study provide valuable insights for measuring quantitative genetic variability for breeding and genetic studies in yam and other root and tuber crops.

Significance: Guinea yam is an important staple tuber crop in West Africa, where it contributes to the sustenance and sociocultural lives of millions of people. Understanding the genetic diversity of Guinea yam and its relationships with wild relatives is important for improving this important crop using genomic information. A recent genomics study proposed that Guinea yam originated from a wild relative, the rainforest species Dioscorea praehensilis . Our results based on sequencing of 336 Guinea yam accessions do not support this notion; rather, our results indicate a hybrid origin of Dioscorea rotundata from crosses between the savannah species Dioscorea abyssinica and D. praehensilis.