Abstract
In plant and animal breeding, genomic prediction models are established to select new lines based on genomic data, without the need for laborious phenotyping. Prediction models can be trained on recent or historic phenotypic data and increasingly available genotypic data. This enables the adoption of genomic selection also in under-used legume crops such as common bean. Beans are an important staple food in the tropics and mainly grown by smallholders under limiting environmental conditions such as drought or low soil fertility. Therefore, genotype-by-environment interactions (G × E) are an important consideration when developing new bean varieties. However, G × E are often not considered in genomic prediction models nor are these models implemented in current bean breeding programs. Here we show the prediction abilities of four agronomic traits in common bean under various environmental stresses based on twelve field trials. The dataset includes 481 elite breeding lines characterized by 5,820 SNP markers. Prediction abilities over all twelve trials ranged between 0.6 and 0.8 for yield and days to maturity, respectively, predicting new lines into new seasons. In all four evaluated traits, the prediction abilities reached about 50–80% of the maximum accuracies given by phenotypic correlations and heritability. Predictions under drought and low phosphorus stress were up to 10 and 20% improved when G × E were included in the model, respectively. Our results demonstrate the potential of genomic selection to increase the genetic gain in common bean breeding. Prediction abilities improved when more phenotypic data was available and G × E could be accounted for. Furthermore, the developed models allowed us to predict genotypic performance under different environmental stresses. This will be a key factor in the development of common bean varieties adapted to future challenging conditions.
Highlights
Common bean (Phaseolus vulgaris L.) is an important protein source for human nutrition contributing to food security in the tropics (Broughton et al, 2003)
This paper presents the results of applying genomic predictions (GPs) methods to common bean in the context of a breeding program
days to flowering (DF) and Days to physiological maturity (DPM) were delayed in the higher altitude location Darien compared to Palmira (Figure 1)
Summary
Common bean (Phaseolus vulgaris L.) is an important protein source for human nutrition contributing to food security in the tropics (Broughton et al, 2003). Bean breeding aims to sustainably increase grain production under challenging environmental conditions. An important breeding target is the resistance to biotic and abiotic stresses, such as diseases, drought and low phosphorus (P) (Mukankusi et al, 2018; Assefa et al, 2019). Low P and drought constrain bean production in up to 50 and 70% of the area under cultivation, respectively (Wortmann et al, 1998; Beebe et al, 2009). Improving common beans for drought and low soil fertility conditions is of special importance for current breeding programs (Buruchara et al, 2011; Beebe et al, 2013; Mukankusi et al, 2018)
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