Roberto Tuberosa

Characterization of polyploid wheat genomic diversity using a high-density 90 000 single nucleotide polymorphism array

High-density single nucleotide polymorphism (SNP) genotyping arrays are a powerful tool for studying genomic patterns of diversity, inferring ancestral relationships between individuals in populations and studying marker–trait associations in mapping experiments. We developed a genotyping array including about 90 000 gene-associated SNPs and used it to characterize genetic variation in allohexaploid and allotetraploid wheat populations. The array includes a significant fraction of common genome-wide distributed SNPs that are represented in populations of diverse geographical origin. We used density-based spatial clustering algorithms to enable high-throughput genotype calling in complex data sets obtained for polyploid wheat. We show that these model-free clustering algorithms provide accurate genotype calling in the presence of multiple clusters including clusters with low signal intensity resulting from significant sequence divergence at the target SNP site or gene deletions. Assays that detect low-intensity clusters can provide insight into the distribution of presence–absence variation (PAV) in wheat populations. A total of 46 977 SNPs from the wheat 90K array were genetically mapped using a combination of eight mapping populations. The developed array and cluster identification algorithms provide an opportunity to infer detailed haplotype structure in polyploid wheat and will serve as an invaluable resource for diversity studies and investigating the genetic basis of trait variation in wheat.

Quantitative Trait Loci and Crop Performance under Abiotic Stress: Where Do We Stand?

The improvement of crop yield has been possible through the indirect manipulation of quantitative trait loci (QTLs) that control heritable variability of the traits and physiological mechanisms that determine biomass production and its partitioning. This article surveys how QTL-based approaches

Conserved noncoding genomic sequences associated with a flowering-time quantitative trait locus in maize

Flowering time is a fundamental trait of maize adaptation to different agricultural environments. Although a large body of information is available on the map position of quantitative trait loci for flowering time, little is known about the molecular basis of quantitative trait loci. Through positional cloning and association mapping, we resolved the major flowering-time quantitative trait locus, Vegetative to generative transition 1 (Vgt1), to an ≈2-kb noncoding region positioned 70 kb upstream of an Ap2-like transcription factor that we have shown to be involved in flowering-time control. Vgt1 functions as a cis-acting regulatory element as indicated by the correlation of the Vgt1 alleles with the transcript expression levels of the downstream gene. Additionally, within Vgt1, we identified evolutionarily conserved noncoding sequences across the maize–sorghum–rice lineages. Our results support the notion that changes in distant cis-acting regulatory regions are a key component of plant genetic adaptation throughout breeding and evolution.

Quantitative Trait Loci for Grain Yield and Adaptation of Durum Wheat (Triticum durum Desf.) Across a Wide Range of Water Availability

Grain yield is a major goal for the improvement of durum wheat, particularly in drought-prone areas. In this study, the genetic basis of grain yield (GY), heading date (HD), and plant height (PH) was investigated in a durum wheat population of 249 recombinant inbred lines evaluated in 16 environments (10 rainfed and 6 irrigated) characterized by a broad range of water availability and GY (from 5.6 to 58.8 q ha−1). Among the 16 quantitative trait loci (QTL) that affected GY, two major QTL on chromosomes 2BL and 3BS showed significant effects in 8 and 7 environments, with R2 values of 21.5 and 13.8% (mean data of all 16 environments), respectively. In both cases, extensive overlap was observed between the LOD profiles of GY and PH, but not with those for HD. QTL specific for PH were identified on chromosomes 1BS, 3AL, and 7AS. Additionally, three major QTL for HD on chromosomes 2AS, 2BL, and 7BS showed limited or no effects on GY. For both PH and GY, notable epistasis between the chromosome 2BL and 3BS QTL was detected across several environments.

Translational research impacting on crop productivity in drought-prone environments

Conventional breeding for drought-prone environments (DPE) has been complemented by using exotic germplasm to extend crop gene pools and physiological approaches that consider water uptake (WU), water-use efficiency (WUE), and harvest index (HI) as drivers of yield. Drivers are associated with proxy genetic markers, such as carbon-isotope discrimination for WUE, canopy temperature for WU, and anthesis-silking interval for HI in maize. Molecular markers associated with relevant quantitative trait loci are being developed. WUE has also been increased through combining understanding of root-to-shoot signaling with deficit irrigation. Impacts in DPE will be accelerated by combining proven technologies with promising new strategies such as marker-assisted selection, and genetic transformation, as well as conservation agriculture that can increase WU while averting soil degradation.

Phenotyping for drought tolerance of crops in the genomics era

Improving crops yield under water-limited conditions is the most daunting challenge faced by breeders. To this end, accurate, relevant phenotyping plays an increasingly pivotal role for the selection of drought-resilient genotypes and, more in general, for a meaningful dissection of the quantitative genetic landscape that underscores the adaptive response of crops to drought. A major and universally recognized obstacle to a more effective translation of the results produced by drought-related studies into improved cultivars is the difficulty in properly phenotyping in a high-throughput fashion in order to identify the quantitative trait loci that govern yield and related traits across different water regimes. This review provides basic principles and a broad set of references useful for the management of phenotyping practices for the study and genetic dissection of drought tolerance and, ultimately, for the release of drought-tolerant cultivars.

Dissection and modelling of abiotic stress tolerance in plants

Plants have acquired a variety of whole-plant protection mechanisms in response to abiotic stresses, often at the expenses of performance. Hence, a given trait can have positive, negative or no effect depending on the stress scenario. A new approach has emerged that dissects yield and integrative traits that influence stress tolerance into heritable traits (e.g. sensitivity parameters or architectural traits) by using phenotyping platforms with model-assisted methods. The genetic and physiological mechanisms accounting for the variability of these traits and their effects on yield are considered in a second step. Effects of traits on yield are analysed via a combination of modelling and field experiments, which allows identification of the stress scenarios where a given allele has favourable effects.

Genetic and genomic dissection of maize root development and architecture

The complex architecture and plasticity of the maize root system is controlled by a plethora of genes. Mutant analyses have identified genes regulating shoot-borne root initiation (RTCS) and root hair elongation (RTH1 and RTH3). Quantitative trait locus (QTL) studies have highlighted the importance of seminal roots, lateral roots, and root hairs in phosphorus acquisition. Additionally, QTLs that influence root features were shown to affect yield under different water regimes and under flooding conditions. Finally, proteome and transcriptome analyses provided insights into maize root development and identified candidate genes associated with cell specification, and lateral root initiation in pericycle cells. The targeted application of forward-genetics and reverse-genetics approaches will accelerate the unraveling of the functional basis of root development and architecture.

Association mapping in durum wheat grown across a broad range of water regimes

Association mapping was used to dissect the genetic basis of drought-adaptive traits and grain yield (GY) in a collection of 189 elite durum wheat accessions evaluated in 15 environments highly different for water availability during the crop cycle (from 146 to 711 mm) and GY (from 9.9 to 67.3 q ha(-1)). For highly heritable traits (e.g. heading date, kernel weight, etc.) several significant experiment-wise marker-trait associations were detected across five or more (up to 13 for kernel weight) environments, with R(2) values ranging from ca. 5 to 10%. As to GY, significant associations (R(2) from 2.5 to 4.2%) were mostly detected in one environment only (56 markers), while decreasing rapidly from two to five environments (from 20 to three markers, respectively) and with only one marker (Xbarc197 on chr. 5A) found significant in six environments (ranging from low- to high-yielding). These results are probably due to the complex genetic basis of GY and its interaction with environmental conditions. The number of markers significantly affecting GY decreased considerably under drought conditions, suggesting a limited effectiveness of association mapping to identify loci for GY under low-moisture conditions, most likely because different genotypes can attain similar phenotypes via different morpho-physiological traits and corresponding gene networks. Our study confirmed the role of major loci for phenology previously described in biparental mapping populations, highlighted a novel set of loci for drought-adaptive traits, and provided information on the agronomic value of the alleles at such loci across a broad range of soil moisture conditions.

RFLP mapping of quantitative trait loci controlling abscisic acid concentration in leaves of drought-stressed maize (Zea mays L.)

Abstract Abscisic acid (ABA) concentration in leaves of drought-stressed plants is a quantitatively inherited trait. In order to identify quantitative trait loci (QTLs) controlling leaf ABA concentration (L-ABA) in maize, leaf samples were collected from 80 F3:4 families of the cross Os420 (high L-ABA)×IABO78 (low L-ABA) tested under drought conditions in field trials conducted over 2 years. In each year, leaf samples were collected at stem elongation and near anthesis. The genetic map obtained with 106 restriction fragment length polymorphism (RFLP) loci covered 1370 cM, which represented approximately 85% of the UMC maize map. Sixteen different QTLs with a LOD>2.0 were revealed in at least one sampling. Across samplings, only four QTLs significantly influenced L-ABA, accounting for 66% of the phenotypic variation and 76% of the genetic variation among families. At these QTLs, the alleles which increased L-ABA were contributed by Os420. The two most important QTLs were mapped on chromosome 2 near csu133 and csu109a. The effects associated with the QTL near csu133 were more pronounced near anthesis. The support intervals of the four primary QTLs for L-ABA did not overlap the presumed map position of mutants impaired in ABA biosynthesis.