Abstract
Cassava improvement using traditional breeding strategies is slow due to the species’ long breeding cycle. However, the use of genomic selection can lead to a shorter breeding cycle. This study aimed to estimate genetic parameters for productive traits based on pedigree (pedigree and phenotypic information) and genomic (markers and phenotypic information) analyses using biparental crosses at different stages of selection. A total of 290 clones were genotyped and phenotyped for fresh root yield (FRY), dry matter content (DMC), dry yield (DY), fresh shoot yield (FSY) and harvest index (HI). The clones were evaluated in clonal evaluation trials (CET), preliminary yield trials (PYT), advanced yield trials (AYT) and uniform yield trials (UYT), from 2013 to 2018 in ten locations. The breeding stages were analyzed as follows: one stage (CET), two stages (CET and PYT), three stages (CET, PYT and AYT) and four stages (CET, PYT, AYT and UYT). The genomic predictions were analyzed via k-fold cross-validation based on the genomic best linear unbiased prediction (GBLUP) considering a model with genetic additive effects and genotype × location interactions. Genomic and pedigree accuracies were moderate to high (0.56–0.72 and 0.62–0.78, respectively) for important starch-related traits such as DY and FRY; when considering one breeding stage (CET) with the aim of early selection, the genomic accuracies ranged from 0.60 (DMC) to 0.71 (HI). Moreover, the correlations between the genomic estimation breeding values of one-stage genomic analysis and the estimated breeding values of the four-stage (full data set) pedigree analysis were high for all traits as well as for a selection index including all traits. The results indicate great possibilities for genomic selection in cassava, especially for selection early in the breeding cycle (saving time and effort).
Highlights
This study aims to (i) estimate genetic parameters from genomic and pedigree predictions for agronomic traits related to starch production, at different stages of a cassava breeding program; (ii) integrate clones’ breeding values into a selection index; (iii) obtain the clones’ genomic estimated breeding values through a genetic additive effect model with genotype × location interactions via Genomic Best Linear Unbiased Prediction (GBLUP); and (iv) compare the one-stage genomic analysis and the four-stage pedigree analysis to verify the feasibility of performing selection at the early stages of the breeding program using genomic selection (GS) predictions
In relation to the genotype × location interaction effect (GxL), when only one stage was evaluated, the clones presented different behaviors in relation to environmental changes for fresh root yield (FRY), dry yield (DY) and fresh shoot yield (FSY) (p 0.01); when four stages were included in the analysis, the additive GxL interaction effect was significant (p 0.01) for all of the traits (Table 3)
The results indicate excellent potential for breeding and genomic selection in these cassava populations aimed at increasing starch production for commercial use
Summary
The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript
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