APPLICATIONS OF MULTITRAIT AND MULTI-KERNEL MODELS FOR GENOMIC SELECTION IN AFRICAN CASSAVA.

Genomic selection (GS) could help accelerate African cassava breeding towards the development of high yielding, high dry matter (DM), disease resistant and provitamin A varieties. This work addresses some issues for implementing GS in cassava. First, we evaluated multivariate and univariate GS models via prediction accuracies. Second, the genetic basis for DM content was investigated using the Regional Heritability Mapping (RHM) procedure. Lastly, the genetic basis for co-inheritance of DM, root color and fresh yield (FYLD) were investigated using the Regional co-heritability Mapping (RHM) procedure. Key lessons were: (1) Multitrait (MT) models for single location data offered 40% higher average prediction accuracies for genomic breeding values (GEBVs) of six target traits across 3 locations compared to single-trait (uT) models. (2) Multivariate multi-environment (ME) models also offered 12% higher average prediction accuracies compared to a compound symmetric multi-environment model (uE) parameterized as a univariate multi-kernel model for multi-year multi-environment data. (3) The RHM analysis identified segments associated with DM in white cassava on chromosomes 1, 4, 5, 10, 17,18 and on yellow cassava chromosome 1. Candidates extracted from genes adjacent to the RHM significant segments include: glycosyltransferases, serine-threonine kinases (SnRKs), invertases and fructose bisphosphate aldolase. Prediction accuracies from these candidates and all genes in the RHM significant regions suggest that they may be tagging regions associated with DM. (4) Genome-wide segment correlations from the RcHM analysis in yellow cassava showed a limited prospect for high DM yellow cassava development but good prospects for high DM, high yielding white cassava development

Regional Heritability Mapping Provides Insights into Dry Matter Content in African White and Yellow Cassava Populations

The HarvestPlus program for cassava ( Crantz) fortifies cassava with β-carotene by breeding for carotene-rich tubers (yellow cassava). However, a negative correlation between yellowness and dry matter (DM) content has been identified. We investigated the genetic control of DM in white and yellow cassava. We used regional heritability mapping (RHM) to associate DM with genomic segments in both subpopulations. Significant segments were subjected to candidate gene analysis and candidates were validated with prediction accuracies. The RHM procedure was validated via a simulation approach and revealed significant hits for white cassava on chromosomes 1, 4, 5, 10, 17, and 18, whereas hits for the yellow were on chromosome 1. Candidate gene analysis revealed genes in the carbohydrate biosynthesis pathway including plant serine–threonine protein kinases (SnRKs), UDP (uridine diphosphate)-glycosyltransferases, UDP-sugar transporters, invertases, pectinases, and regulons. Validation using 1252 unique identifiers from the SnRK gene family genome-wide recovered 50% of the predictive accuracy of whole-genome single nucleotide polymorphisms for DM, whereas validation using 53 likely genes (extracted from the literature) from significant segments recovered 32%. Genes including an acid invertase, a neutral or alkaline invertase, and a glucose-6-phosphate isomerase were validated on the basis of an a priori list for the cassava starch pathway, and also a fructose-biphosphate aldolase from the Calvin cycle pathway. The power of the RHM procedure was estimated as 47% when the causal quantitative trait loci generated 10% of the phenotypic variance (sample size = 451). Cassava DM genetics are complex and RHM may be useful for complex traits