Identificación y análisis de regiones genómicas que controlan la arquitectura radicular en Triticum aestivum

Resumen

Root system architecture is known to play a crucial role in plant development, tolerance against abiotic stresses and nutrient uptake, especially in cereals, where the phenological stage of grain filling is undoubtedly the most relevant one. Nonetheless, the knowledge of its genetic control has been hampered by the complex, repetitive and polyploid genome of wheat species and the inherent difficulties that imply phenotyping the root system architecture-related traits. All in all, the limited information gathered makes the root an ideal subject for future explorations, which could lead to the huge leap in the enhancement of wheat traits of interest like abiotic stress tolerance necessary to solve the current demographic escalation problems and climate change issues. When compared to other germplasm collections, the Spanish wheat landraces conserved at the National Plant Genetic Resources Center (CRF-INIA) showed a huge genetic diversity in prior studies. In the present work, a representative set from Spanish bread wheat landraces (85 accessions) has been analyzed. First and foremost, the phenotypic variability for several quantitative traits related to root architecture was studied, and then the population structure using genotype data from a set of 4713 molecular markers was investigated. The wide range of variation exhibited by the root traits and the existence of low genetic clustering supported the use of this collection to perform a GWAS study, where phenotype-genotype associations were pursued. After testing several methodologies to correct the analysis, no significative association was detected, so a quality trait with a well-known genetic control was added to the analysis as a positive control. The appearance of significant associations regarding this trait revealed the necessity of phenotyping more landraces to build a larger collection with which to repeat the analysis. Nevertheless, a molecular marker identified from previous studies was proven associated by SMA analysis. Together with markers from this work that were not associated but looked promising, we were able to detect QTLs (Quantitaive Trait Loci) – genomic regions potentially responsible for the studied traits. These regions were previously described in the literature, but we explored them in search of possible genes responsible for the association, which could undergo future studies to assess its potential as molecular markers for MAS (Marker Assisted Selection) in future plant breeding programs.