Abstract
Leaf orientation traits of maize (Zea mays) are complex traits controlling by multiple loci with additive, dominance, epistasis, and environmental interaction effects. In this study, an attempt was made for identifying the causal loci, and estimating the additive, non-additive, environmental specific genetic effects underpinning leaf traits (leaf length, leaf width, and upper leaf angle) of maize NAM population. Leaf traits were analyzed by using full genetic model and additive model of multiple loci. Analysis with full genetic model identified 38∼47 highly significant loci (-log10PEW > 5), while estimated total heritability were 64.32∼79.06% with large contributions due to dominance and dominance related epistasis effects (16.00∼56.91%). Analysis with additive model obtained smaller total heritability ( ≙ 18.68∼29.56%) and detected fewer loci (30∼36) as compared to the full genetic model. There were 12 pleiotropic loci identified for the three leaf traits: eight loci for leaf length and leaf width, and four loci for leaf length and leaf angle. Optimal genotype combinations of superior line (SL) and superior hybrid (SH) were predicted for each of the traits under four different environments based on estimated genotypic effects to facilitate maker-assisted selection for the leaf traits.
Highlights
Maize is one of the most economically important crops, source of around 24% of the total cereal production and of food, fuel, feed, or fiber in the world (Gore et al, 2009)
Large portion of the estimated total heritability was due to dominance and dominance related epistasis interaction for leaf length
We identified 46 quantitative trait SNPs (QTSs) with highly experimental-wise significant (−log10PEW > 5) effects underpinning to the leaf length using full model approach (Figure 1 and Supplementary Table S3)
Summary
Maize is one of the most economically important crops, source of around 24% of the total cereal production and of food, fuel, feed, or fiber in the world (Gore et al, 2009). Due to the economical importance, several studies have been conducted to dissect the genetic architectures of maize traits to assist in breeding programs for crop improvement (Burton et al, 2014; Lemmon and Doebley, 2014; Foerster et al, 2015). Leaf orientation traits including upper leaf angle, leaf length, and leaf width are important plant traits related with the grains of maize (Tian et al, 2011), genetic dissection of these traits could assist maize breeding programs. Tian et al (2011) identified several significant quantitative trait loci (QTLs) and SNPs for the leaf traits using QTL mapping and genome-wide association studies (GWAS). GWAS has advantages as compared to conventional linkage mapping for dissecting genetic architecture of plant complex traits (Shi et al, 2017)
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