Marker-Based Estimates Reveal Significant Nonadditive Effects in Clonally Propagated Cassava (Manihot esculenta): Implications for the Prediction of Total Genetic Value and the Selection of Varieties

Abstract

In clonally propagated crops, nonadditive genetic effects can be effectively exploited by the identification of superior genetic individuals as varieties. Cassava (Manihot esculenta Crantz) is a clonally propagated staple food crop that feeds hundreds of millions. We quantified the amount and nature of nonadditive genetic variation for three key traits in a breeding population of cassava from sub-Saharan Africa using additive and nonadditive genome-wide marker-based relationship matrices. We then assessed the accuracy of genomic prediction for total (additive plus nonadditive) genetic value. We confirmed previous findings based on diallel crosses that nonadditive genetic variation is significant for key cassava traits. Specifically, we found that dominance is particularly important for root yield and epistasis contributes strongly to variation in cassava mosaic disease (CMD) resistance. Further, we showed that total genetic value predicted observed phenotypes more accurately than additive only models for root yield but not for dry matter content, which is mostly additive or for CMD resistance, which has high narrow-sense heritability. We address the implication of these results for cassava breeding and put our work in the context of previous results in cassava, and other plant and animal species.

Metabolite database for root, tuber, and banana crops to facilitate modern breeding in understudied crops

“…In recent years many large‐scale efforts have sought to further understand these crops using genome sequences (Xu et al , ; D'Hont et al , ; Wang et al , ; Tamiru et al , ; Yang et al , ; Li et al , ) and genome diversity studies (Bredeson et al , ; Hardigan et al , ; Nyine et al , ; Christelová et al , ; Muñoz‐Rodríguez et al , ; Němečková et al , ), genetic selection (Wolfe et al , ), molecular markers (QTLs) (Monden and Tahara, ; Kim et al , ; Sharma and Bryan, ), and comparative transcriptome resources (Kundapura Venkataramana et al , ; Sarah et al , ; van Wesemael et al , ; Cenci et al , ) widely developed alongside morphologic, agronomic and phenotypic classifications (Oliveira et al , ; Rahajeng and Rahayuningsih, ; Dépigny et al , ; Girma et al , ; van Wesemael et al , ). The progress of the CGIAR Research Program on Roots, Tubers and Bananas (http://www.rtb.cgiar.org), applying genomics‐assisted breeding to RTBs, has recently been reviewed (Friedmann et al , ).…”

Genomics-Assisted Breeding in the CGIAR Research Program on Roots, Tubers and Bananas (RTB)

“…The correlation between predicted and observed phenotypes ranged from 0.15 to 0.47 for 19 traits, suggesting that GS has potential to accelerate gains in cassava, and the existing training population should give a reasonable estimate of future prediction accuracies. Further assessment of the prospects of GS in cassava was reported by Wolfe et al [101,102], using a larger population consisting of breeding populations from IITA, NRCRI, and NaCRRI. Factors tested included seven prediction models that considered different genetic architectures (additive and total genetic value), cross-validation within populations, cross-population prediction, and cross-generation prediction.…”

Recent Biotechnological Advances in the Improvement of Cassava

“…Using a combination of genotype-by-sequencing (GBS)-based SNPs and physical mapping of scaffolds from cassava whole genome sequencing (WGS), 1061 cassava immunity-related genes were mapped [114]. Notably, from 105 putative CMD2 genes identified from the CMD2 locus on chromosome 8 [115], 35 were identical to those identified in a RNA-seq study of SACMV-infected cassava genotype TME3 [109]. These genes could be strong candidates contributing to resistance in cassava.…”