Association mapping for phenology and plant architecture in maize shows higher power for developmental traits compared with growth influenced traits

Abstract

Plant architecture, phenology and yield components of cultivated plants have repeatedly been shaped by selection to meet human needs and adaptation to different environments. Here we assessed the genetic architecture of 24 correlated maize traits that interact during plant cycle. Overall, 336 lines were phenotyped in a network of 9 trials and genotyped with 50K singlenucleotide polymorphisms. Phenology was the main factor of differentiation between genetic groups. Then yield components distinguished dents from lower yielding genetic groups. However, most of trait variation occurred within group and we observed similar overall and within group correlations, suggesting a major effect of pleiotropy and/or linkage. We found 34 quantitative trait loci (QTLs) for individual traits and six for trait combinations corresponding to PCA coordinates. Among them, only five were pleiotropic. We found a cluster of QTLs in a 5 Mb region around Tb1 associated with tiller number, ear row number and the first PCA axis, the latter being positively correlated to flowering time and negatively correlated to yield. Kn1 and ZmNIP1 were candidate genes for tillering, ZCN8 for leaf number and Rubisco Activase 1 for kernel weight. Experimental repeatabilities, numbers of QTLs and proportion of explained variation were higher for traits related to plant development such as tillering, leaf number and flowering time, than for traits affected by growth such as yield components. This suggests a simpler genetic determinism with larger individual QTL effects for the first category. Although technology to support this process has dramatically evolved, especially in recent decades, breeders' objectives have not fundamentally changed over the last 10 000 years. They still have to overcome the difficulty of conducting multiple trait selection in different and variable environments and their choices are often trade-offs between an ideal plant architecture, product quality, yield and adaptation to targeted environments. Low cost genotyping can accelerate the selection of large effect beneficial alleles and high throughput genotyping can improve the accuracy of breeding value predictions for multi-traits controlled by small effect quantitative trait loci (QTLs).In cereals, yield remains the main objective even though it may be negatively correlated with some quality traits. Yield is a complex trait to predict as it is the result of many trait interactions during plant development and growth. The objective is to combine plant architecture that maximizes light interception, phenology that synchronizes reproduction stage with optimal environmental conditions to minimize abortion, inflorescence architecture for optimal seed set, and numerous factors contributing to environmental adaptation and grain filling.

Exploring natural diversity of Medicago truncatula reveals physiotypes and loci associated with the response of seedling performance to nitrate supply

“…a PCA‐based integrative pTrait, revealed specific loci, different from those identified under each single treatment. Combined‐trait PC variables is an approach firstly used for QTL linkage mapping by Weller et al (1996) and then for GWAS in animals (Zhang et al 2018) and plants (Bonhomme et al 2014, Bouchet et al 2017). It allowed capturing the genetic variation for several traits simultaneously, that may be controlled by a single locus.…”

Interaction Between Induced and Natural Variation at oil yellow1 Delays Reproductive Maturity in Maize

“…zmmads1 is a functional homolog of the Arabidopsis flowering time and circadian rhythm regulator soc1 (Alter et al 2016). Several QTL studies have used the convenient phenotype of days to reproductive maturity as a proxy for flowering time and identified alleles controlling this trait in maize (Buckler et al 2009;Coles et al 2010;Steinhoff et al 2012;Bouchet et al 2017). While this trait is convenient it is determined by both the days to floral transition of the meristem and the growth rate of the stem and emergence and maturation of floral structures.…”

The Genetic Basis of Plant Architecture in 10 Maize Recombinant Inbred Line Populations

“…Most previous genetic studies focused on single or a few plant architecture traits and lacked power to dissect plant architecture traits as a whole. Bouchet et al (2017) assessed the genetic basis of 24 correlated maize traits and identified major pleioptropic effects and/or linkage for plant architecture traits in one population with 336 lines, which, however, only represents a small proportion of the genetic diversity in maize. Despite this progress, the genetics of plant architecture-related traits in maize have not been fully investigated in multiple diverse genetic backgrounds.…”