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Abiotic stress tolerance in plants is pivotal to increase yield stability, but its genetic basis is still poorly understood. To gain insight into the genetic architecture of frost tolerance, this work evaluated a large mapping population of 1739 wheat (Triticum aestivum L.) lines and hybrids adapted to Central Europe in field trials in Germany and fingerprinted the lines with a 9000 single-nucleotide polymorphism array. Additive effects prevailed over dominance effects. A two-dimensional genome scan revealed the presence of epistatic effects. Genome-wide association mapping in combination with a robust cross-validation strategy identified one frost tolerance locus with a major effect located on chromosome 5B. This locus was not in linkage disequilibrium with the known frost loci Fr-B1 and Fr-B2. The use of the detected diagnostic markers on chromosome 5B, however, does not allow prediction of frost tolerance with high accuracy. Application of genome-wide selection approaches that take into account also loci with small effect sizes considerably improved prediction of the genetic variation of frost tolerance in wheat. The developed prediction model is valuable for improving frost tolerance because this trait displays a wide variation in occurrence across years and is therefore a difficult target for conventional phenotypic selection.

To achieve the food and energy security of an increasing World population likely to exceed nine billion by 2050 represents a major challenge for plant breeding. Our ability to measure traits under field conditions has improved little over the last decades and currently constitutes a major bottleneck in crop improvement. This work describes the development of a tractor-pulled multi-sensor phenotyping platform for small grain cereals with a focus on the technological development of the system. Various optical sensors like light curtain imaging, 3D Time-of-Flight cameras, laser distance sensors, hyperspectral imaging as well as color imaging are integrated into the system to collect spectral and morphological information of the plants. The study specifies: the mechanical design, the system architecture for data collection and data processing, the phenotyping procedure of the integrated system, results from field trials for data quality evaluation, as well as calibration results for plant height determination as a quantified example for a platform application. Repeated measurements were taken at three developmental stages of the plants in the years 2011 and 2012 employing triticale (×Triticosecale Wittmack L.) as a model species. The technical repeatability of measurement results was high for nearly all different types of sensors which confirmed the high suitability of the platform under field conditions. The developed platform constitutes a robust basis for the development and calibration of further sensor and multi-sensor fusion models to measure various agronomic traits like plant moisture content, lodging, tiller density or biomass yield, and thus, represents a major step towards widening the bottleneck of non-destructive phenotyping for crop improvement and plant genetic studies.

Drought is one of the major abiotic stresses with a severe negative impact on maize production globally. Understanding the genetic architecture of drought tolerance in maize is a crucial step towards the breeding of drought-tolerant varieties and a targeted exploitation of genetic resources. In this study, 511 quantitative trait loci (QTL) related to grain yield components, flowering time, and plant morphology under drought conditions, as well as drought tolerance index were collected from 27 published studies and then projected on the IBM2 2008 Neighbors reference map for meta-analysis. In total, 83 meta-QTL (MQTL) associated with drought tolerance in maize were identified, of which 20 were determined as core MQTL. The average confidence interval of MQTL was strongly reduced compared to that of the previously published QTL. Nearly half of the MQTL were confirmed by co-localized marker-trait associations from genome-wide association studies. Based on the alignment of rice proteins related to drought tolerance, 63 orthologous genes were identified near the maize MQTL. Furthermore, 583 candidate genes were identified within the 20 core MQTL regions and maize–rice homologous genes. Based on KEGG analysis of candidate genes, plant hormone signaling pathways were found to be significantly enriched. The signaling pathways can have direct or indirect effects on drought tolerance and also interact with other pathways. In conclusion, this study provides novel insights into the genetic and molecular mechanisms of drought tolerance in maize towards a more targeted improvement of this important trait in breeding. [ABSTRACT FROM AUTHOR]

Abstract Background Doubled haploid production is a key technology in triticale research and breeding. A critical component of this method depends on chromosome doubling, which is traditionally achieved by in vivo treatment of seedlings with colchicine. Results In this study we investigated the applicability of an in vitro approach for chromosome doubling based on microspore culture. Our results show a pronounced increase in the proportion of doubled haploid triticale plants compared to the spontaneous doubling rate, but also compared to the doubling obtained by the standard in vivo approach. In addition, the frequency of plants surviving from culture medium to maturity is also much higher for the in vitro approach. Colchicine concentrations of 1 mM for 24 h or 0.3 mM applied for 48 or 72 h during the first hours of microspore culture performed best. Conclusions Our results suggest that for triticale, in vitro chromosome doubling is a promising alternative to the in vivo approach.

Abstract Background Recent advances in genotyping with high-density markers nowadays enable genome-wide genomic analyses in crops. A detailed characterisation of the population structure and linkage disequilibrium (LD) is essential for the application of genomic approaches and consequently for knowledge-based breeding. In this study we used the triticale-specific DArT array to analyze population structure, genetic diversity, and LD in a worldwide set of 161 winter and spring triticale lines. Results The principal coordinate analysis revealed that the first principal coordinate divides the triticale population into two clusters according to their growth habit. The density distributions of the first ten principal coordinates revealed that several show a distribution indicative of population structure. In addition, we observed relatedness within growth habits which was higher among the spring types than among the winter types. The genome-wide analysis of polymorphic information content (PIC) showed that the PIC is variable among and along chromosomes and that especially the R genome of spring types possesses a reduced genetic diversity. We also found that several chromosomes showed regions of high genetic distance between the two growth habits, indicative of divergent selection. Regarding linkage disequilibrium, the A and B genomes showed a similar LD of 0.24 for closely linked markers and a decay within approximately 12 cM. LD in the R genome was lower with 0.19 and decayed within a shorter map distance of approximately 5 cM. The extent of LD was generally higher for the spring types compared to the winter types. In addition, we observed strong variability of LD along the chromosomes. Conclusions Our results confirm winter and spring growth habit are the major contributors to population structure in triticale, and a family structure exists in both growth types. The specific patterns of genetic diversity observed within these types, such as the low diversity on some rye chromosomes of spring habits, provide a basis for targeted broadening of the available breeding germplasm. In addition, the genome-wide analysis of the extent and the pattern of LD will assist scientists and breeders alike in the implementation and the interpretation of association mapping in triticale.

Abstract Background Fusarium graminearum sensu stricto (s.s.) is an ubiquitous pathogen of cereals. The economic impact of Fusarium head blight (FHB) is characterized by crop losses and mycotoxin contamination. Our objective was to associate SNP diversity within candidate genes with phenotypic traits. A total of 77 F. graminearum s.s. isolates was tested for severity of fungal infection (= aggressiveness) and deoxynivalenol (DON) production in an inoculated field experiment at two locations in each of two years. For seven genes known to control fungal growth (MetAP1, Erf2) or DON production (TRI1, TRI5, TRI6 TRI10 and TRI14) single nucleotides polymorphic sites (SNPs) were determined and evaluated for the extent of linkage disequilibrium (LD). Associations of SNPs with both phenotypic traits were tested using linear mixed models. Results Decay of LD was in most instances fast. Two neighboring SNPs in MetAP1 and one SNP in Erf2 were significantly (P < 0.05) associated with aggressiveness explaining proportions of genotypic variance (pG) of 25.6%, 0.5%, and 13.1%, respectively. One SNP in TRI1 was significantly associated with DON production (pG = 4.4). Conclusions We argue that using the published sequence information of Fusarium graminearum as a template to amplify comparative sequence parts of candidate genes is an effective method to detect quantitative trait loci. Our findings underline the potential of candidate gene association mapping approaches to identify functional SNPs underlying aggressiveness and DON production for F. graminearum s.s populations.

Abstract Background Triticale is adapted to a wide range of abiotic stress conditions, is an important high-quality feed stock and produces similar grain yield but more biomass compared to other crops. Modern genomic approaches aimed at enhancing breeding progress in cereals require high-quality genetic linkage maps. Consensus maps are genetic maps that are created by a joint analysis of the data from several segregating populations and different approaches are available for their construction. The phenomenon that alleles at a locus deviate from the Mendelian expectation has been defined as segregation distortion. The study of segregation distortion is of particular interest in doubled haploid (DH) populations due to the selection pressure exerted on the plants during the process of their establishment. Results The final consensus map, constructed out of six segregating populations derived from nine parental lines, incorporated 2555 DArT markers mapped to 2602 loci (1929 unique). The map spanned 2309.9 cM with an average number of 123.9 loci per chromosome and an average marker density of one unique locus every 1.2 cM. The R genome showed the highest marker coverage followed by the B genome and the A genome. In general, locus order was well maintained between the consensus linkage map and the component maps. However, we observed several groups of loci for which the colinearity was slightly uneven. Among the 2602 loci mapped on the consensus map, 886 showed distorted segregation in at least one of the individual mapping populations. In several DH populations derived by androgenesis, we found chromosomes (2B, 3B, 1R, 2R, 4R and 7R) containing regions where markers exhibited a distorted segregation pattern. In addition, we observed evidence for segregation distortion between pairs of loci caused either by a predominance of parental or recombinant genotypes. Conclusions We have constructed a reliable, high-density DArT marker consensus genetic linkage map as a basis for genomic approaches in triticale research and breeding, for example for multiple-line cross QTL mapping experiments. The results of our study exemplify the tremendous impact of different DH production techniques on allele frequencies and segregation distortion covering whole chromosomes.

Large-scale application of the doubled haploid (DH) technology by in vivo haploid induction has greatly improved the efficiency of maize breeding. While the haploid induction rate and the efficiency of identifying haploid plants have greatly improved in recent years, the low efficiency of doubling of haploid plants has remained and currently presents the main limitation to maize DH line production. In this study, we aimed to assess the available genetic variation for haploid male fertility (HMF), i.e., the production of fertile pollen on haploid plants, and to investigate the underlying genetic architecture. To this end, a diversity panel of 481 maize inbred lines was crossed with “Mo17” and “Zheng58,” the F1 hybrids subjected to haploid induction, and resulting haploid plants assessed for male fertility in two environments. Across both genetic backgrounds, we observed a large variation of HMF ranging from zero to ~60%, with a mean of 18%, and a heritability of 0.65. HMF was higher in the “Mo17” than in the “Zheng58” background and the correlation between both genetic backgrounds was 0.68. Genome-wide association mapping identified only few putative QTL that jointly explained 22.5% of the phenotypic variance. With the exception of one association explaining 11.77% of the phenotypic variance, all other putative QTL were of minor importance. A genome-wide prediction approach further corroborated the quantitative nature of HMF in maize. Analysis of the 14 significantly associated SNPs revealed several candidate genes. Collectively, our results illustrate the large variation of HMF that can be exploited for maize DH breeding. Owing to the apparent genetic complexity of this trait, this might best be achieved by rapid recurrent phenotypic selection coupled with marker-assisted selection for individual QTL. [ABSTRACT FROM AUTHOR]