QTL Mapping of Stem Rust Resistance in Populations of Durum Wheat

Stem rinfectionust, caused by the fungus Puccinia graminis f. sp. tritici (Pgt), is one of the most devastating fungal diseases of durum and common wheat worldwide. The identification of sources of resistance and the validation of QTLs identified through genome-wide association studies is of paramount importance for reducing the losses caused by this disease to wheat grain yield and quality. Four segregating populations whose parents showed contrasting reactions to some Pgt races were assessed in the present study, and 14 QTLs were identified on chromosomes 3A, 4A, 6A, and 6B, with some regions in common between different segregating populations. Several QTLs were mapped to chromosomal regions coincident with previously mapped stem rust resistance loci; however, their reaction to different Pgt races suggest that novel genes or alleles could be present on chromosomes 3A and 6B. Putative candidate genes with a disease-related functional annotation have been identified in the QTL regions based on information available from the reference genome of durum cv. 'Svevo'

Genetic mapping of loci for resistance to stem rust in a tetraploid wheat collection

Stem rust, caused by Puccinia graminis f. sp. tritici (Pgt), is a major biotic constraint to wheat production worldwide. Disease resistant cultivars are a sustainable means for the efficient control of this disease. To identify quantitative trait loci (QTLs) conferring resistance to stem rust at the seedling stage, an association mapping panel consisting of 230 tetraploid wheat accessions were evaluated for reaction to five Pgt races under greenhouse conditions. A high level of phenotypic variation was observed in the panel in response to all of the races, allowing for genome-wide association mapping of resistance QTLs in wild, landrace, and cultivated tetraploid wheats. Twenty-two resistance QTLs were identified, which were characterized by at least two marker-trait associations. Most of the identified resistance loci were coincident with previously identified rust resistance genes/QTLs; however, six regions detected on chromosomes 1B, 5A, 5B, 6B, and 7B may be novel. Availability of the reference genome sequence of wild emmer wheat accession Zavitan facilitated the search for candidate resistance genes in the regions where QTLs were identified, and many of them were annotated as NOD (nucleotide binding oligomerization domain)-like receptor (NLR) genes or genes related to broad spectrum resistance

A major root architecture QTL responding to water limitation in durum wheat

The optimal root system architecture (RSA) of a crop is context dependent and critical for efficient resource capture in the soil. Narrow root growth angle promoting deeper root growth is often associated with improved access to water and nutrients in deep soils during terminal drought. RSA, therefore is a drought-adaptive trait that could minimize yield losses in regions with limited rainfall. Here, GWAS for seminal root angle (SRA) identified seven marker-trait associations clustered on chromosome 6A, representing a major quantitative trait locus (qSRA-6A) which also displayed high levels of pairwise LD (r2 = 0.67). Subsequent haplotype analysis revealed significant differences between major groups. Candidate gene analysis revealed loci related to gravitropism, polar growth and hormonal signaling. No differences were observed for root biomass between lines carrying hap1 and hap2 for qSRA-6A, highlighting the opportunity to perform marker-assisted selection for the qSRA-6A locus and directly select for wide or narrow RSA, without influencing root biomass. Our study revealed that the genetic predisposition for deep rooting was best expressed under water-limitation, yet the root system displayed plasticity producing root growth in response to water availability in upper soil layers. We discuss the potential to deploy root architectural traits in cultivars to enhance yield stability in environments that experience limited rainfall

A major root architecture QTL responding to water limitation in durum wheat

The optimal root system architecture (RSA) of a crop is context dependent and critical for efficient resource capture in the soil. Narrow root growth angle promoting deeper root growth is often associated with improved access to water and nutrients in deep soils during terminal drought. RSA, therefore is a drought-adaptive trait that could minimize yield losses in regions with limited rainfall. Here, GWAS for seminal root angle (SRA) identified seven marker-trait associations clustered on chromosome 6A, representing a major quantitative trait locus (qSRA-6A) which also displayed high levels of pairwise LD (r 2 = 0.67). Subsequent haplotype analysis revealed significant differences between major groups. Candidate gene analysis revealed loci related to gravitropism, polar growth and hormonal signaling. No differences were observed for root biomass between lines carrying hap1 and hap2 for qSRA-6A, highlighting the opportunity to perform marker-assisted selection for the qSRA-6A locus and directly select for wide or narrow RSA, without influencing root biomass. Our study revealed that the genetic predisposition for deep rooting was best expressed under water-limitation, yet the root system displayed plasticity producing root growth in response to water availability in upper soil layers. We discuss the potential to deploy root architectural traits in cultivars to enhance yield stability in environments that experience limited rainfall.Samir Alahmad, Khaoula El Hassouni, Filippo M. Bassi, Eric Dinglasan, Chvan Youssef, Georgia Quarry, Alpaslan Aksoy, Elisabetta Mazzucotelli, Angéla Juhász, Jason A. Able, Jack Christopher, Kai P. Voss-Fels and Lee T. Hicke

The Global Durum Wheat Panel (GDP): An International Platform to Identify and Exchange Beneficial Alleles

Representative, broad and diverse collections are a primary resource to dissect genetic diversity and meet pre-breeding and breeding goals through the identification of beneficial alleles for target traits. From 2,500 tetraploid wheat accessions obtained through an international collaborative effort, a Global Durum wheat Panel (GDP) of 1,011 genotypes was assembled that captured 94-97% of the original diversity. The GDP consists of a wide representation of Triticum turgidum ssp. durum modern germplasm and landraces, along with a selection of emmer and primitive tetraploid wheats to maximize diversity. GDP accessions were genotyped using the wheat iSelect 90K SNP array. Among modern durum accessions, breeding programs from Italy, France and Central Asia provided the highest level of genetic diversity, with only a moderate decrease in genetic diversity observed across nearly 50 years of breeding (1970-2018). Further, the breeding programs from Europe had the largest sets of unique alleles. LD was lower in the landraces (0.4 Mbp) than in modern germplasm (1.8 Mbp) at r 2 = 0.5. ADMIXTURE analysis of modern germplasm defined a minimum of 13 distinct genetic clusters (k), which could be traced to the breeding program of origin. Chromosome regions putatively subjected to strong selection pressure were identified from fixation index (F st ) and diversity reduction index (DRI) metrics in pairwise comparisons among decades of release and breeding programs. Clusters of putative selection sweeps (PSW) were identified as co-localized with major loci controlling phenology (Ppd and Vrn), plant height (Rht) and quality (gliadins and glutenins), underlining the role of the corresponding genes as driving elements in modern breeding. Public seed availability and deep genetic characterization of the GDP make this collection a unique and ideal resource to identify and map useful genetic diversity at loci of interest to any breeding program

Differential regulation of alanine aminotransferase homologues by abiotic stresses in wheat (Triticum aestivum L.) seedlings

Wheat (Triticum aestivum L.) seedlings contain four alanine aminotransferase (AlaAT) homologues. Two of them encode AlaAT enzymes, whereas two homologues act as glumate:glyoxylate aminotransferase (GGAT). To address the function of the distinct AlaAT homologues a comparative examination of the changes in transcript level together with the enzyme activity and alanine and glutamate content in wheat seedlings subjected to low oxygen availability, nitrogen and light deficiency has been studied. Shoots of wheat seedlings were more tolerant to hypoxia than the roots as judging on the basis of enzyme activity and transcript level. Hypoxia induced AlaAT1 earlier in roots than in shoots, while AlaAT2 and GGAT were unaffected. The increase in AlaAT activity lagged behind the increase in alanine content. Nitrogen deficiency has little effect on the activity of GGAT. In contrast, lower activity of AlaAT and the level of mRNA for AlaAT1 and AlaAT2 in wheat seedlings growing on a nitrogen-free medium seems to indicate that AlaAT is regulated by the availability of nitrogen. Both AlaAT and GGAT activities were present in etiolated wheat seedlings but their activity was half of that observed in light-grown seedlings. Exposure of etiolated seedlings to light caused an increase in enzyme activities and up-regulated GGAT1. It is proposed that hypoxia-induced AlaAT1 and light-induced peroxisomal GGAT1 appears to be crucial for the regulation of energy availability in plants grown under unfavourable environmental conditions

Integrative Identification of Arabidopsis Mitochondrial Proteome and Its Function Exploitation through Protein Interaction Network

Mitochondria are major players on the production of energy, and host several key reactions involved in basic metabolism and biosynthesis of essential molecules. Currently, the majority of nucleus-encoded mitochondrial proteins are unknown even for model plant Arabidopsis. We reported a computational framework for predicting Arabidopsis mitochondrial proteins based on a probabilistic model, called Naive Bayesian Network, which integrates disparate genomic data generated from eight bioinformatics tools, multiple orthologous mappings, protein domain properties and co-expression patterns using 1,027 microarray profiles. Through this approach, we predicted 2,311 candidate mitochondrial proteins with 84.67% accuracy and 2.53% FPR performances. Together with those experimental confirmed proteins, 2,585 mitochondria proteins (named CoreMitoP) were identified, we explored those proteins with unknown functions based on protein-protein interaction network (PIN) and annotated novel functions for 26.65% CoreMitoP proteins. Moreover, we found newly predicted mitochondrial proteins embedded in particular subnetworks of the PIN, mainly functioning in response to diverse environmental stresses, like salt, draught, cold, and wound etc. Candidate mitochondrial proteins involved in those physiological acitivites provide useful targets for further investigation. Assigned functions also provide comprehensive information for Arabidopsis mitochondrial proteome