Genomic prediction with haplotype blocks in wheat.

Haplotype blocks might carry additional information compared to single SNPs and have therefore been suggested for use as independent variables in genomic prediction. Studies in different species resulted in more accurate predictions than with single SNPs in some traits but not in others. In addition, it remains unclear how the blocks should be built to obtain the greatest prediction accuracies. Our objective was to compare the results of genomic prediction with different types of haplotype blocks to prediction with single SNPs in 11 traits in winter wheat. We built haplotype blocks from marker data from 361 winter wheat lines based on linkage disequilibrium, fixed SNP numbers, fixed lengths in cM and with the R package HaploBlocker. We used these blocks together with data from single-year field trials in a cross-validation study for predictions with RR-BLUP, an alternative method (RMLA) that allows for heterogeneous marker variances, and GBLUP performed with the software GVCHAP. The greatest prediction accuracies for resistance scores for B. graminis, P. triticina, and F. graminearum were obtained with LD-based haplotype blocks while blocks with fixed marker numbers and fixed lengths in cM resulted in the greatest prediction accuracies for plant height. Prediction accuracies of haplotype blocks built with HaploBlocker were greater than those of the other methods for protein concentration and resistances scores for S. tritici, B. graminis, and P. striiformis. We hypothesize that the trait-dependence is caused by properties of the haplotype blocks that have overlapping and contrasting effects on the prediction accuracy. While they might be able to capture local epistatic effects and to detect ancestral relationships better than single SNPs, prediction accuracy might be reduced by unfavorable characteristics of the design matrices in the models that are due to their multi-allelic nature.

Metabolite profiling of barley flag leaves under drought and combined heat and drought stress reveals metabolic QTLs for metabolites associated with antioxidant defense.

Barley (Hordeum vulgare L.) is among the most stress-tolerant crops; however, not much is known about the genetic and environmental control of metabolic adaptation of barley to abiotic stresses. We have subjected a genetically diverse set of 81 barley accessions, consisting of Mediterranean landrace genotypes and German elite breeding lines, to drought and combined heat and drought stress at anthesis. Our aim was to (i) investigate potential differences in morphological, physiological, and metabolic adaptation to the two stress scenarios between the Mediterranean and German barley genotypes and (ii) identify metabolic quantitative trait loci (mQTLs). To this end, we have genotyped the investigated barley lines with an Illumina iSelect 9K array and analyzed a set of 57 metabolites from the primary C and N as well as antioxidant metabolism in flag leaves under control and stress conditions. We found that drought-adapted genotypes attenuate leaf carbon metabolism much more strongly than elite lines during drought stress adaptation. Furthermore, we identified mQTLs for flag leaf γ-tocopherol, glutathione, and succinate content by association genetics that co-localize with genes encoding enzymes of the pathways producing these antioxidant metabolites. Our results provide the molecular basis for breeding barley cultivars with improved abiotic stress tolerance.

A saturated SNP linkage map for the orange wheat blossom midge resistance gene Sm1.

KEY MESSAGE: SNP markers were developed for the OWBM resistance gene Sm1 that will be useful for MAS. The wheat Sm1 region is collinear with an inverted syntenic interval in B. distachyon. Orange wheat blossom midge (OWBM, Sitodiplosis mosellana Géhin) is an important insect pest of wheat (Triticum aestivum) in many growing regions. Sm1 is the only described OWBM resistance gene and is the foundation of managing OWBM through host genetics. Sm1 was previously mapped to wheat chromosome arm 2BS relative to simple sequence repeat (SSR) markers and the dominant, sequence characterized amplified region (SCAR) marker WM1. The objectives of this research were to saturate the Sm1 region with markers, develop improved markers for marker-assisted selection (MAS), and examine the synteny between wheat, Brachypodium distachyon, and rice (Oryza sativa) in the Sm1 region. The present study mapped Sm1 in four populations relative to single nucleotide polymorphisms (SNPs), SSRs, Diversity Array Technology (DArT) markers, single strand conformation polymorphisms (SSCPs), and the SCAR WM1. Numerous high quality SNP assays were designed that mapped near Sm1. BLAST delineated the syntenic intervals in B. distachyon and rice using gene-based SNPs as query sequences. The Sm1 region in wheat was inverted relative to B. distachyon and rice, which suggests a chromosomal rearrangement within the Triticeae lineage. Seven SNPs were tested on a collection of wheat lines known to carry Sm1 and not to carry Sm1. Sm1-flanking SNPs were identified that were useful for predicting the presence or absence of Sm1 based upon haplotype. These SNPs will be a major improvement for MAS of Sm1 in wheat breeding programs.

Nitrogen-metabolism related genes in barley - haplotype diversity, linkage mapping and associations with malting and kernel quality parameters.

BACKGROUND: Several studies report about intra-specific trait variation of nitrogen-metabolism related traits, such as N(itrogen)-use efficiency, protein content, N-storage and remobilization in barley and related grass species. The goal of this study was to assess the intra-specific genetic diversity present in primary N-metabolism genes of barley and to investigate the associations of the detected haplotype diversity with malting and kernel quality related traits. RESULTS: Partial sequences of five genes related to N-metabolism in barley (Hordeum vulgare L.) were obtained, i.e. nitrate reductase 1, glutamine synthetase 2, ferredoxin-dependent glutamate synthase, aspartate aminotransferase and asparaginase. Two to five haplotypes in each gene were discovered in a set of 190 various varieties. The development of 33 SNP markers allowed the genotyping of all these barley varieties consisting of spring and winter types. Furthermore, these markers could be mapped in several doubled haploid populations. Cluster analysis based on haplotypes revealed a more uniform pattern of the spring barleys as compared to the winter barleys. Based on linear model approaches associations to several malting and kernel quality traits including soluble N and protein were identified. CONCLUSIONS: A study was conducted to investigate the presence of sequence variation of several genes related to the primary N-metabolism in barley. The detected diversity could be related to particular phenotypic traits. Specific differences between spring and winter barleys most likely reflect different breeding aims. The developed markers can be used as tool for further genetic studies and marker-assisted selection during breeding of barley.