CBGG

Cassava (Manihot esculenta Crantz) is a critical tropical root crop that underpins food security, industrial applications, and rural livelihoods, particularly across sub-Saharan Africa. Traditional cassava breeding has faced significant challenges due to the crop’s long growth cycle, clonal propagation, high heterozygosity, polygenic inheritance of key traits, and strong genotype × environment (G × E) interactions. These factors have historically limited the rate of genetic improvement, despite cassava’s socio-economic importance. Recent developments in genomics-assisted breeding (GAB) are transforming cassava improvement by combining high-density molecular markers, genome-wide association studies (GWAS), genomic selection (GS), and multi-omics approaches such as transcriptomics, metabolomics, and high-throughput phenotyping. The sequencing of the cassava reference genome has enabled single nucleotide polymorphism (SNP) discovery, quantitative trait loci (QTL) mapping, and the development of genomic prediction models, allowing early selection for complex traits including root yield, dry matter content, starch quality, carotenoid accumulation, disease resistance, and early storage root bulking. Functional genomics, together with non-invasive root imaging technologies such as ground-penetrating radar, provides insight into the genetic and physiological mechanisms underlying root development and stress responses. Multi-environment GWAS and genomic selection models now account for G × E interactions, improving prediction accuracy and supporting rapid-cycle breeding. Furthermore, integrating metabolomic and transcriptomic datasets enhances trait prediction, accelerates candidate gene discovery, and advances precision breeding strategies. This review provides recent progress, tools, and future prospects in genomics-assisted cassava breeding, illustrating how modern genomic and phenomic technologies are reshaping breeding pipelines, shortening breeding cycles, and facilitating the development of climate-resilient, high-yielding, and farmer-preferred cassava varieties.

genomics-assisted breeding; cassava (Manihot esculenta); genomic selection; multi-omics integration; trait prediction and precision breeding