Williams Esuma

The paper presents a population-based transcriptomics atlas of cassava, identifying differentially expressed genes and gene modules related to disease resistance and physiological traits.

This study evaluates genomic selection accuracy in cassava breeding across different prediction models and scenarios, finding that training population size significantly impacts accuracy.

The paper constructs a cassava haplotype map to evaluate deleterious mutations, finding increased fixed deleterious variants, limited purging due to low recombination, and masking of harmful mutations in breeding.