Skim exome capture genotyping in wheat

Next-generation sequencing (NGS) technology advancements continue to reduce the cost of high-throughput genome-wide genotyping for breeding and genetics research. Skim sequencing, which surveys the entire genome at low coverage, has become feasible for quantitative trait locus (QTL) mapping and genomic selection in various crops. However, the genome complexity of allopolyploid crops such as wheat (Triticum aestivum L.) still poses a significant challenge for genome-wide genotyping. Targeted sequencing of the protein-coding regions (i.e., exome) reduces sequencing costs compared to whole genome re-sequencing and can be used for marker discovery and genotyping. We developed a method called skim exome capture (SEC) that combines the strengths of these existing technologies and produces targeted genotyping data while decreasing the cost on a per-sample basis compared to traditional exome capture. Specifically, we fragmented genomic DNA using a tagmentation approach, then enriched those fragments for the low-copy genic portion of the genome using commercial wheat exome baits and multiplexed the sequencing at different levels to achieve desired coverage. We demonstrated that for a library of 48 samples, ∼7-8× target coverage was sufficient for high-quality variant detection. For higher multiplexing levels of 528 and 1056 samples per library, we achieved an average coverage of 0.76× and 0.32×, respectively. Combining these lower coverage SEC sequencing data with genotype imputation using a customized wheat practical haplotype graph database that we developed, we identified hundreds of thousands of high-quality genic variants across the genome. The SEC method can be used for high-resolution QTL mapping, genome-wide association studies, genomic selection, and other downstream applications.

Cloning of the broadly effective wheat leaf rust resistance gene Lr42 transferred from Aegilops tauschii

The wheat wild relative Aegilops tauschii was previously used to transfer the Lr42 leaf rust resistance gene into bread wheat. Lr42 confers resistance at both seedling and adult stages, and it is broadly effective against all leaf rust races tested to date. Lr42 has been used extensively in the CIMMYT international wheat breeding program with resulting cultivars deployed in several countries. Here, using a bulked segregant RNA-Seq (BSR-Seq) mapping strategy, we identify three candidate genes for Lr42. Overexpression of a nucleotide-binding site leucine-rich repeat (NLR) gene AET1Gv20040300 induces strong resistance to leaf rust in wheat and a mutation of the gene disrupted the resistance. The Lr42 resistance allele is rare in Ae. tauschii and likely arose from ectopic recombination. Cloning of Lr42 provides diagnostic markers and over 1000 CIMMYT wheat lines carrying Lr42 have been developed documenting its widespread use and impact in crop improvement.

Genomic Selection in Preliminary Yield Trials in a Winter Wheat Breeding Program

Genomic prediction (GP) is now routinely performed in crop plants to predict unobserved phenotypes. The use of predicted phenotypes to make selections is an active area of research. Here, we evaluate GP for predicting grain yield and compare genomic and phenotypic selection by tracking lines advanced. We examined four independent nurseries of F3:6 and F3:7 lines trialed at 6 to 10 locations each year. Yield was analyzed using mixed models that accounted for experimental design and spatial variations. Genotype-by-sequencing provided nearly 27,000 high-quality SNPs. Average genomic predictive ability, estimated for each year by randomly masking lines as missing in steps of 10% from 10 to 90%, and using the remaining lines from the same year as well as lines from other years in a training set, ranged from 0.23 to 0.55. The predictive ability estimated for a new year using the other years ranged from 0.17 to 0.28. Further, we tracked lines advanced based on phenotype from each of the four F3:6 nurseries. Lines with both above average genomic estimated breeding value (GEBV) and phenotypic value (BLUP) were retained for more years compared to lines with either above average GEBV or BLUP alone. The number of lines selected for advancement was substantially greater when predictions were made with 50% of the lines from the testing year added to the training set. Hence, evaluation of only 50% of the lines yearly seems possible. This study provides insights to assess and integrate genomic selection in breeding programs of autogamous crops.

Genotyping-by-Sequencing Derived High-Density Linkage Map and its Application to QTL Mapping of Flag Leaf Traits in Bread Wheat

Winter wheat parents ‘Harry’ (drought tolerant) and ‘Wesley’ (drought susceptible) were used to develop a recombinant inbred population with future goals of identifying genomic regions associated with drought tolerance. To precisely map genomic regions, high-density linkage maps are a prerequisite. In this study genotyping-by- sequencing (GBS) was used to construct the high-density linkage map. The map contained 3,641 markers distributed on 21 chromosomes and spanned 1,959 cM with an average distance of 1.8 cM between markers. The constructed linkage map revealed strong collinearity in marker order across 21 chromosomes with POPSEQ-v2.0, which was based on a high-density linkage map. The reliability of the linkage map for QTL mapping was demonstrated by co-localizing the genes to previously mapped genomic regions for two highly heritable traits, chaff color, and leaf cuticular wax. Applicability of linkage map for QTL mapping of three quantitative traits, flag leaf length, width, and area, identified 21 QTLs in four environments, and QTL expression varied across the environments. Two major stable QTLs, one each for flag leaf length (Qfll.hww-7A) and flag leaf width (Qflw.hww-5A) were identified. The map constructed will facilitate QTL and fine mapping of quantitative traits, map-based cloning, comparative mapping, and in marker-assisted wheat breeding endeavors.

A novel QTL associated with dwarf bunt resistance in Idaho 444 winter wheat

KEY MESSAGE

A novel QTL, Q.DB.ui-7DS, and the PCR-based markers identified in the current study will accelerate variety development for resistance to dwarf and common bunt of wheat. Dwarf bunt [Tilletia controversa J.G. Kühn [as 'contraversa'], in Rabenhorst, Hedwigia 13: 188 (1874)] is a destructive disease of wheat (Triticum aestivum L.) that reduces grain yield and quality. A number of distinct genes conferring resistance to dwarf bunt have been used by breeding programs for nearly 100 years. However, few markers were identified that can be used in selection of dwarf bunt resistance. A recombinant inbred line (RIL) population derived from the bunt-resistant germplasm, Idaho 444 (IDO444), and the susceptible cultivar, Rio Blanco, was evaluated for phenotypic reaction to dwarf bunt inoculation in four trials in two locations (USU and USDA) over 3 years. The population was genotyped with the Diversity Arrays Technology (DArT) and the Illumina Infinium 9K iSelect marker platforms. A total of three QTL were detected, and resistant alleles were from IDO444. QTL Q.DB.ui-7DS on 7DS was determined based on the location of a DArT marker wPt-2565 (X116197), which was consistently detected and explained 32 to 56 % of phenotypic variation among the four trials. QTL Q.DB.ui-1A on 1A was detected in three Utah State University (USU) trials and explained 11-15 % of phenotypic variation. QTL Q.DB.ui-2B on 2B was detected in two USU and one United States Department of Agriculture (USDA) trials and explained up to 6 % of phenotypic variation. Two PCR-based markers were developed based on the sequence of wPt-2565 and validated in the RIL population and used in genotyping of dwarf bunt differential lines, known resistance sources, and resistant cultivars.

Distribution of Cadmium, Iron, and Zinc in Millstreams of Hard Winter Wheat (Triticum aestivum L.)

Hard winter wheat (Triticum aestivum L.) is a major crop in the Great Plains of the United States, and our previous work demonstrated that wheat genotypes vary for grain cadmium accumulation with some exceeding the CODEX standard (0.2 mg kg(-1)). Previous reports of cadmium distribution in flour milling fractions have not included high cadmium grain. This study measured the distribution of cadmium, zinc, and iron in flour and bran streams from high cadmium (0.352 mg kg(-1)) grain on a pilot mill that produced 12 flour and four bran streams. Recovery in flour was substantially greater for cadmium (50%) than for zinc (31%) or iron (22%). Cadmium, zinc, and iron in the lowest mineral concentration flour stream, representing the purest endosperm fraction, were 52, 22, and 11%, respectively, of initial grain concentration. Our results indicate that, relative to zinc and iron, a greater proportion of cadmium is stored in the endosperm, the source of white flour.

Nonstarch polysaccharides in wheat flour wire-cut cookie making

Nonstarch polysaccharides in wheat flour have significant capacity to affect the processing quality of wheat flour dough and the finished quality of wheat flour products. Most research has focused on the effects of arabinoxylans (AX) in bread making. This study found that water-extractable AX and arabinogalactan peptides can predict variation in pastry wheat quality as captured by the wire-cut cookie model system. The sum of water-extractable AX plus arabinogalactan was highly predictive of cookie spread factor. The combination of cookie spread factor and the ratio of water-extractable arabinose to xylose predicted peak force of the three-point bend test of cookie texture.

Microcomputer programs for prediction and comparative evaluation of protein secondary structure from nucleotide sequence data: application to ribulose-1,5-bisphosphate carboxylase sequences

Apple II PASCAL computer programs are described for routine evaluation of protein secondary structures predicted from DNA or amino acid sequence data. The programs predict protein secondary structure using the directional information algorithm of Garnier et al. (1978), and calculate hydrophobicity (Kyte and Doolittle, 1982), hydrophilicity (Hopp and Woods, 1981), hydrophobic moment (Eisenberg et al., 1984b), and secondary structure propensity profiles. The novel feature of these programs is the application of numeric and graphic methods, designed to facilitate detection and characterization of structural similarities/divergences using the aforementioned structural parameters. The use of the programs is demonstrated on a set of sequences from the large and small subunits of ribulose-1,5-bisphosphate carboxylase.