Prospects for Genomic Selection in Cassava Breeding

Abstract

Cassava (Manihot esculenta Crantz) is a clonally propagated staple food crop in the tropics. Genomic selection (GS) has been implemented at three breeding institutions in Africa to reduce cycle times. Initial studies provided promising estimates of predictive abilities. Here, we expand on previous analyses by assessing the accuracy of seven prediction models for seven traits in three prediction scenarios: cross-validation within populations, cross-population prediction and cross-generation prediction. We also evaluated the impact of increasing the training population (TP) size by phenotyping progenies selected either at random or with a genetic algorithm. Cross-validation results were mostly consistent across programs, with nonadditive models predicting of 10% better on average. Cross-population accuracy was generally low (mean = 0.18) but prediction of cassava mosaic disease increased up to 57% in one Nigerian population when data from another related population were combined. Accuracy across generations was poorer than within-generation accuracy, as expected, but accuracy for dry matter content and mosaic disease severity should be sufficient for rapid-cycling GS. Selection of a prediction model made some difference across generations, but increasing TP size was more important. With a genetic algorithm, selection of one-third of progeny could achieve an accuracy equivalent to phenotyping all progeny. We are in the early stages of GS for this crop but the results are promising for some traits. General guidelines that are emerging are that TPs need to continue to grow but phenotyping can be done on a cleverly selected subset of individuals, reducing the overall phenotyping burden.

Genetic Variation and Trait Correlations in an East African Cassava Breeding Population for Genomic Selection

“…Clearly, our broad-sense heritability estimates for DMC were lower than the heritability estimate of 0.46 reported by Wolfe et al (2017). Clearly, our broad-sense heritability estimates for DMC were lower than the heritability estimate of 0.46 reported by Wolfe et al (2017).…”

“…In response to these challenges, the cassava breeding program based at NaCRRI initiated efforts to implement GS to accelerate the breeding cycle of cassava (Wolfe et al, 2016(Wolfe et al, , 2017. Notable production obstacles addressed include susceptibility to CMD and CBSD, and low yields of both fresh root and dry matter.…”

“…Genomic prediction accuracies from the initial training population (C 0 ) at NaCRRI have been estimated to be reasonably accurate for highly heritable traits, such as dry matter content (DMC) and CMD, but less for low heritability traits, such as fresh root yield (Wolfe et al, 2017). Genomic prediction accuracies from the initial training population (C 0 ) at NaCRRI have been estimated to be reasonably accurate for highly heritable traits, such as dry matter content (DMC) and CMD, but less for low heritability traits, such as fresh root yield (Wolfe et al, 2017).…”

“…Genomic prediction accuracies from the initial training population (C 0 ) at NaCRRI have been estimated to be reasonably accurate for highly heritable traits, such as dry matter content (DMC) and CMD, but less for low heritability traits, such as fresh root yield (Wolfe et al, 2017). Whereas Wolfe et al (2017) focused on predicting yield traits and CMD, which are common problems across all cassava breeding programs in Africa, Kayondo et al (2018) specifically focused on QTL mapping and genomic predictions for CBSD-related traits, a problem facing cassava production only in eastern, central, and southern parts of Africa. Whereas Wolfe et al (2017) focused on predicting yield traits and CMD, which are common problems across all cassava breeding programs in Africa, Kayondo et al (2018) specifically focused on QTL mapping and genomic predictions for CBSD-related traits, a problem facing cassava production only in eastern, central, and southern parts of Africa.…”

The role of genetics in mainstreaming the production of new and orphan crops to diversify food systems and support human nutrition

“…The efficacy of genomic selection is currently being tested on cassava (Manihot esculenta), a vegetatively propagated orphan annual root crop (Wolfe et al, 2017). A further orphan crop example in which the approach is beginning to be explored is finger millet (Eleusine coracana), a seed-propagated annual grain (discussed further below).…”