Low-lodging high-yielding wheat germplasm and SNP-tagged novel alleles for lodging were identified in a process that involved selecting donors through functional phenotyping for underlying traits with a designed phenotypic screen, and a crossing strategy involving multiple-donor × elite populations. Lodging is a barrier to achieving high yield in wheat. As part of a study investigating the potential to breed low-lodging high-yielding wheat, populations were developed crossing four low-lodging high-yielding donors selected based on lodging related traits, with three cultivars. Lodging was evaluated in single rows in an early generation and subsequently in plots in 2 years with contrasting lodging environment. A large number of lines lodged less than their recurrent parents, and some were also higher yielding. Heritability for lodging was high, but the genetic correlation between contrasting environments was intermediate-low. Lodging genotypic rankings in single rows did not correlate well with plots. Populations from the highest lodging background were genotyped (90 K iSelect BeadChip array). Fourteen markers on nine chromosomes were associated with lodging, differing under high- versus low-lodging conditions. Of the fourteen markers, ten were found to co-locate with previously identified QTL for lodging-related traits or at homoeologous locations for previously identified lodging-related QTL, while the remaining four markers (in chromosomes 2D, 4D, 7B and 7D) appear to map to novel QTL for lodging. Lines with more favourable markers lodged less, suggesting value in these markers as a selection tool. This study demonstrates that the combination of donor functional phenotyping, screen design and crossing strategy can help identify novel alleles in germplasm without requiring extensive bi-parental populations.

Key message A powerful QTL analysis method for nested association mapping populations is presented. Based on a one-stage multi-locus model, it provides accurate predictions of founder specific QTL effects. Abstract Nested association mapping (NAM) populations have been created to enable the identification of quantitative trait loci (QTL) in different genetic backgrounds. A whole-genome nested association mapping (WGNAM) method is presented to perform QTL analysis in NAM populations. The WGNAM method is an adaptation of the multi-parent whole genome average interval mapping approach where the crossing design is incorporated through the probability of inheriting founder alleles for every marker across the genome. Based on a linear mixed model, this method provides a one-stage analysis of raw phenotypic data, molecular markers, and crossing design. It simultaneously scans the whole-genome through an iterative process leading to a model with all the identified QTL while keeping the false positive rate low. The WGNAM approach was assessed through a simulation study, confirming to be a powerful and accurate method for QTL analysis for a NAM population. This novel method can also accommodate a multi-reference NAM (MR-NAM) population where donor parents are crossed with multiple reference parents to increase genetic diversity. Therefore, a demonstration is presented using a MR-NAM population for wheat ( Triticum aestivum L.) to perform a QTL analysis for plant height. The strength and size of the putative QTL were summarized enhancing the understanding of the QTL effects depending on the parental origin. Compared to other methods, the proposed methodology based on a one-stage analysis provides greater power to detect QTL and increased accuracy in the estimation of their effects. The WGNAM method establishes the basis for accurate QTL mapping studies for NAM and MR-NAM populations.

A stay-green phenotype is useful for adaptation of wheat to end-of-season drought conditions. We identified quantitative trait loci (QTL) for stay-green traits, as well as for height, days to anthesis and yield, in a multireference nested association mapping (MR-NAM) population of wheat (Triticum aestivum L.) in two environments differing in degree of drought stress experienced post-anthesis. The MR-NAM population consisted of three inter-related nested association mapping populations developed by nesting 11 diverse adaptation donors within three common reference parents, adapted to the northern, southern and western cropping regions of Australia, respectively. The construction of the MR-NAM population enables the assessment of the effect on a trait of multiple alleles at any particular locus, in different genetic backgrounds, and facilitates concurrent QTL mapping and germplasm development. This approach enabled identification of parent-specific alleles and context dependent expression. Using a new statistical method specifically developed to identify QTL in MR-NAM populations, we identified 65 QTL for stay-green traits. Co-location was observed between (i) trait by loci associations for some of the different stay-green traits, (ii) for QTL between the two environments, and (iii) between QTL for stay-green traits, plant height and grain yield. Some QTL co-located with those identified in other studies however, others are likely novel. Genetic markers associated with QTL for stay-green can be applied in breeding to enrich populations for stay-green traits in early generations of selection, prior to field testing in yield plots, in particular for the development of wheat cultivars targeted to end-of-season drought-stressed environments. This information is important for breeders, because it facilitates identification of the sources of the most promising alleles at particular loci for specific genetic backgrounds and growing environments.

Terminal drought stress is currently a major constraint in many wheat production regions. This is predicted to worsen with future climate change. The stay-green phenotype allows crops to remain green and photosynthesize for longer after anthesis, potentially improving yields in terminal drought environments. Root systems with greater root length density at depth can contribute by increasing access to deep soil moisture late in the season. To study the genetics of root and stay-green traits in wheat, a multi reference parent nested association mapping (NAM) population was developed. Using the “speed breeding” system of rapid generation advance, over 1500 recombinant inbred lines (RIL) were generated in approximately 18 months. Genome-wide association studies (GWAS) using a novel whole-genome NAM method (WG-NAM) identified genetic regions associated with the target traits. High-throughput techniques were developed and used for the NAM lines to (i) phenotype seedling roots in controlled conditions, and (ii) objectively characterize novel stay-green traits for hundreds of genotypes in standard yield plots in the field. NAM lines were phenotyped for yield and stay-green traits at multiple water-stressed and non-stressed environments during 4 seasons. Particular traits were associated with superior adaptation to certain environments. Many lines with adaptive root and stay-green traits exhibited superior yield to the reference parent in relevant target environments and 54 such lines have been provided to commercial Australian wheat breeders for cultivar development. This combination of technologies is increasing understanding of physiological adaptation to water-limited environments in wheat and helping accelerate genetic progress.

Take home messages New wheat germplasm has been identified that lodges less than Australian cultivars EGA Gregory , Suntop and LRPB Spitfire. From the favourable genetic markers identified in the new germplasm, only a proportion was present in a database of 502 Australian varieties, suggesting that there is room for improving lodging tolerance in high yielding wheats.