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Abstract
Grain yield and stay-green drought adaptation trait are important targets of selection in grain sorghum breeding for broad adaptation to a range of environments. Genomic prediction for these traits may be enhanced by joint multi-trait analysis. The objectives of this study were to assess the capacity of multi-trait models to improve genomic prediction of parental breeding values for grain yield and stay-green in sorghum by using information from correlated auxiliary traits, and to determine the combinations of traits that optimize predictive results in specific scenarios. The dataset included phenotypic performance of 2645 testcross hybrids across 26 environments as well as genomic and pedigree information on their female parental lines. The traits considered were grain yield (GY), stay-green (SG), plant height (PH), and flowering time (FT). We evaluated the improvement in predictive performance of multi-trait G-BLUP models relative to single-trait G-BLUP. The use of a blended kinship matrix exploiting pedigree and genomic information was also explored to optimize multi-trait predictions. Predictive ability for GY increased up to 16% when PH information on the training population was exploited through multi-trait genomic analysis. For SG prediction, full advantage from multi-trait G-BLUP was obtained only when GY information was also available on the predicted lines per se, with predictive ability improvements of up to 19%. Predictive ability, unbiasedness and accuracy of predictions from conventional multi-trait G-BLUP were further optimized by using a combined pedigree-genomic relationship matrix. Results of this study suggest that multi-trait genomic evaluation combining routinely measured traits may be used to improve prediction of crop productivity and drought adaptability in grain sorghum.
Highlights
Water scarcity in rain-fed cropping systems is a major challenge to a world of increasing food demand (UNCTAD, 2011)
The narrow-sense heritability estimates using ST G-BLUP are given in Table 1 along with the additive genetic and residual correlations between traits estimated by multiple traits (MT) G-BLUP
Additive genetic correlations were significant only for grain yield (GY) with SG and plant height (PH), while flowering time (FT) was statistically uncorrelated with the other traits
Summary
Water scarcity in rain-fed cropping systems is a major challenge to a world of increasing food demand (UNCTAD, 2011). Moench) is a cereal crop that can play an important role for sustainable farming, as it is resilient to stress conditions caused by drought and erratic rainfall (Paterson et al, 2009). This crop is a staple food in semi-arid regions of the world and is used for feed globally (Acquaah, 2012). Grain yield is the primary trait in sorghum, as it is a key measure of crop productivity and profitability of farmers Another important trait is stay-green; a complex drought-adaptation mechanism associated with increased yield in environments where postflowering drought occurs frequently (Borrell et al, 2000; Jordan et al, 2003). Further improvement in productivity and drought adaptability requires knowledge-based selection strategies that efficiently exploit available phenotypic and genotypic information in sorghum breeding programs
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