Natural accessions of Arabidopsis thaliana differ in their growth and development, but also vary dramatically in their nitrogen use efficiencies (NUE). The molecular basis for these differences has not been addressed yet. Experiments with five contrasting accessions grown in hydroponics at different levels of inorganic nitrogen confirmed low NUE of Col-0 and higher NUE in Tsu-0. At constant external nitrogen supply, higher NUE was based on nitrogen capture, rather than utilization of nitrogen for shoot biomass. This changed when a limited nitrogen amount was supplied. Nevertheless, the total NUE sequence remained similar. Interestingly, the two most contrasting accessions, Col-0 and Tsu-0, differed in the capture of single inorganic nitrogen sources, reflected by the differential consumption of 15N label from ammonium or nitrate, when supplied together. Tsu-0 acquired more nitrate than Col-0, both in roots and shoots. This preference was directly correlated with the expression of certain nitrogen uptake and assimilation systems in the root. However, early transcriptional responses of the root to nitrate deprivation were similar in both accessions, suggesting that the sensing of the external lack of nitrate was not different in the more nitrogen use efficient accession. Thus, a robust rapid nitrate-deprivation signaling exists in both genotypes.

The quantitatively inherited trait plant height is routinely evaluated in triticale breeding programs as it substantially influences lodging and disease susceptibility, is a main contributor to biomass yield, and is required to improve hybrid seed production by fine-tuning plant height in the female and male parental pools in hybrid breeding programs. In this study, we evaluated a panel of 846 diverse Central European triticale genotypes to dissect the genetic architecture underlying plant height by genome-wide association mapping. This revealed three medium- to large-effect QTL on chromosomes 5A, 4B, and 5R. Genetic and physical fine-mapping of the putative QTL revealed that the QTL on chromosome 5R most likely corresponds to Ddw1 and that the QTL on chromosome 5A is likely to be Rht12. Furthermore, we observed a temporal trend in registered cultivars with a decreasing plant height during the past decades, accompanied by an increasing use of the height-reducing alleles at the identified QTL. In summary, our results shed new light on the genetic control of plant height in triticale and open new avenues for future improvement by breeding.

Key message The comparably low genotype-by-nitrogen level interaction suggests that selection in early generations can be done under high-input conditions followed by selection under different nitrogen levels to identify genotypes ideally suited for the target environment. Abstract Breeding high-yielding, nitrogen-efficient crops is of utmost importance to achieve greater agricultural sustainability. The aim of this study was to evaluate nitrogen use efficiency (NUE) of triticale, investigate long-term genetic trends and the genetic architecture, and develop strategies for NUE improvement by breeding. For this, we evaluated 450 different triticale genotypes under four nitrogen fertilization levels in multi-environment field trials for grain yield, protein content, starch content and derived indices. Analysis of temporal trends revealed that modern cultivars are better in exploiting the available nitrogen. Genome-wide association mapping revealed a complex genetic architecture with many small-effect QTL and a high level of pleiotropy for NUE-related traits, in line with phenotypic correlations. Furthermore, the effect of some QTL was dependent on the nitrogen fertilization level. High correlations of each trait between N levels and the rather low genotype-by-N-level interaction variance showed that generally the same genotypes perform well over different N levels. Nevertheless, the best performing genotype was always a different one. Thus, selection in early generations can be done under high nitrogen fertilizer conditions as these provide a stronger differentiation, but the final selection in later generations should be conducted with a nitrogen fertilization as in the target environment.

Time‐ and resource‐efficient identification of promising lines is of utmost importance in hybrid breeding. Here, we present a novel approach to evaluate female candidate lines for single‐cross hybrids, which saves four to five generations by obtaining general (GCA) and specific combining ability (SCA) effect estimates prior to the introgression of the female lines into a male sterility‐inducing cytoplasm. The approach is based on three‐way crosses and we exemplarily demonstrate its power by predicting 57 single‐cross hybrids of triticale. Prediction accuracies based on GCA or GCA and SCA effects estimated in three‐way hybrids were generally superior to those based on mid‐parent values. Notably, a high proportion of SCA variance had only little influence on the prediction accuracies based on three‐way hybrids. Simulation studies support the empirical findings and illustrate approaches for further optimization. Thus, the presented approach appears highly valuable and has the potential to increase selection gain in hybrid breeding.

Accurate hybrid prediction and knowledge about the relative contribution of general (GCA) and specific combining ability (SCA) are of utmost importance for efficient hybrid breeding. We therefore evaluated 91 triticale single‐cross hybrids in field trials at seven environments for plant height, heading time, fresh biomass, dry matter content and dry biomass. Fresh and dry biomass showed the highest proportion (23%) of variance due to SCA. Prediction accuracies based on GCA were slightly higher than based on mid‐parent values. Utilizing parental kinship information yielded the highest prediction accuracies when both parental lines have been tested in other hybrid combinations, but still moderate‐to‐low prediction accuracies for two untested parents. Thus, hybrid prediction for biomass traits in triticale is currently promising based on mid‐parent values as emphasized by our simulation study, but can be expected to shift to GCA‐based prediction with an increasing importance of GCA due to selection in hybrid breeding. Moreover, the performance of potential hybrids between newly developed lines can be predicted with moderate accuracy using genomic relationship information.