Maria Corinna Sanguineti, Elisabetta Frascaroli, Pierangelo Landi, Silvia Giuliani, Sergio Conti, Roberto Tuberosa, Silvio Salvi, COSTA DE OLIVEIRA A., VARSHNEY R.K., TUBEROSA R., SALVI S., GIULIANI S., SANGUINETI M.C., FRASCAROLI E., CONTI S., and LANDI P.
Genomics approaches and platforms offer novel opportunities to identify and clone the loci that control root architecture in maize. Mutants for root features have been described and in some cases the relevant genes have been cloned. A number of studies have also described quantitative trait loci (QTLs) that provide access to valuable genetic diversity for the morpho-physiological features that characterize root functionality. Nonetheless, although a number of major QTLs have been identified, none of these QTLs has been cloned so far, mainly due to the difficulty to accurately phenotype the target traits in a sufficiently large number of plants. It is foreseeable that QTL cloning will be facilitated by the adoption of high-throughput phenomics platforms as well as by the information made available through the sequencing of the maize genome and the profiling of the transcriptome, proteome, and metabolome, all of which will contribute to the identification of plausible candidate genes. Allele mining in germplasm and mutant collections through forward- and reverse-genetics approaches, coupled with marker-assisted backcrossing and/or genetic engineering, will further facilitate the introgression of novel genetic variation in elite materials. New QTL-based modeling approaches will improve our capacity to understand genotype × environment interaction at varying water and nutrient regimes, thus contributing to define the most promising “molecular” ideotypes. This notwithstanding, a sizeable impact of marker-assisted selection and other genomics approaches in tailoring the ideal root architecture in maize will only be possible through a deeper knowledge of root functions under a broad range of growing conditions and an integration with conventional breeding methodologies.