Genomic regions influencing seminal root traits in barley

Water availability is a major limiting factor for crop production, making drought adaptation and its many component traits a desirable attribute of plant cultivars. Previous studies in cereal crops indicate that root traits expressed at early plant developmental stages, such as seminal root angle and root number, are associated with water extraction at different depths. Here, we conducted the first study to map seminal root traits in barley (Hordeum vulgare L.). Using a recently developed high-throughput phenotyping method, a panel of 30 barley genotypes and a doubled-haploid (DH) population (ND24260 × 'Flagship') comprising 330 lines genotyped with diversity array technology (DArT) markers were evaluated for seminal root angle (deviation from vertical) and root number under controlled environmental conditions. A high degree of phenotypic variation was observed in the panel of 30 genotypes: 13.5 to 82.2 and 3.6 to 6.9° for root angle and root number, respectively. A similar range was observed in the DH population: 16.4 to 70.5 and 3.6 to 6.5° for root angle and number, respectively. Seven quantitative trait loci (QTL) for seminal root traits (root angle, two QTL; root number, five QTL) were detected in the DH population. A major QTL influencing both root angle and root number (RAQ2/RNQ4) was positioned on chromosome 5HL. Across-species analysis identified 10 common genes underlying root trait QTL in barley, wheat (Triticum aestivum L.), and sorghum [Sorghum bicolor (L.) Moench]. Here, we provide insight into seminal root phenotypes and provide a first look at the genetics controlling these traits in barley.

Molecular Breeding for Complex Adaptive Traits: How Integrating Crop Ecophysiology and Modelling Can Enhance Efficiency

Progress in crop improvement is limited by the ability to identify favourable combinations of genotypes (G) and management practices (M) in relevant target environments (E) given the resources available to search among the myriad of possible combinations. To underpin yield advance we require prediction of phenotype based on genotype. In plant breeding, traditional phenotypic selection methods have involved measuring phenotypic performance of large segregating populations in multi-environment trials and applying rigorous statistical procedures based on quantitative genetic theory to identify superior individuals. Recent developments in the ability to inexpensively and densely map/sequence genomes have facilitated a shift from the level of the individual (genotype) to the level of the genomic region. Molecular breeding strategies using genome wide prediction and genomic selection approaches have developed rapidly. However, their applicability to complex traits remains constrained by gene-gene and gene-environment interactions, which restrict the predictive power of associations of genomic regions with phenotypic responses. Here it is argued that crop ecophysiology and functional whole plant modelling can provide an effective link between molecular and organism scales and enhance molecular breeding by adding value to genetic prediction approaches. A physiological framework that facilitates dissection and modelling of complex traits can inform phenotyping methods for marker/gene detection and underpin prediction of likely phenotypic consequences of trait and genetic variation in target environments. This approach holds considerable promise for more effectively linking genotype to phenotype for complex adaptive traits. Specific examples focused on drought adaptation are presented to highlight the concepts.