Genotypic variability of maize growth and developmental traits under semi-controlled conditions

SANTIAGO ALVAREZ PRADO; ANTONIN GRAU; LLORENÇ CABRERA-BOSQUET; CLAUDE WELCKER; FRANÇOIS TARDIEU

Montpellier

Congreso; Recent progress in drought tolerance: from genetics to modelling; 2015

DROPS develop strategies for yield improvementunder dry environments and for enhanced plant water-use efficiency. Anassociation panel of 255 maize hybrids was genotyped with 50K and 600K chips ofSingle Nucleotide Polymorphism (SNPs) and phenotyped in a network of fields, inplatforms and via omic data. In particular, three experiments with two watertreatments were carried out in the phenotyping platform PhenoArch to assistthose in the field in view of possible confusions of effects in the field. Hybridswere characterized via the progression of phenological stages (phyllochron),those of leaf area, plant height and plant volume dynamics, and finally metabolitesconcentrations and aquaporin activity at key developmental stages. Phyllochronranged from 0.19 to 0.26 leaves per day at 20°C, plant height ranged from 705to 1756 cm, leaf area from 0.13 to 0.54 m2 and plant fresh weight from117 to 577 g. All traits showed high heritability values along the vegetativephase (H²= 0.60-0.91). Variations in plant volume were closely and positivelyrelated to changes in plant evapo-transpiration in all situations. Genotypicvariability for water use efficiency ranged from 34.6 to 73.4 g FW/l and from40.3 to 64.9 g FW/l for well-watered and water deficit scenarios, respectively.Plant growth traits were linked to alleles of genes through Genome WideAssociation Studies (GWAS). Significant SNP were detected for all traits in allsituations showing several SNP co-location for phenotypically correlated traits.The results will be useful to (i) assist field experiments, in particular forthe timing of plant development, (ii) compare QTLs in the field and in theplatform and (iii) modelling for selecting specific genotypes for droughtscenarios : several variables measured in the platform can serve as parametersof a crop model.