C. Friedrich H. Longin

Flowering time control in European winter wheat

Flowering time is an important trait in wheat breeding as it affects adaptation and yield potential. The aim of this study was to investigate the genetic architecture of flowering time in European winter bread wheat cultivars. To this end a population of 410 winter wheat varieties was evaluated in multi-location field trials and genotyped by a genotyping-by-sequencing approach and candidate gene markers. Our analyses revealed that the photoperiod regulator Ppd-D1 is the major factor affecting flowering time in this germplasm set, explaining 58% of the genotypic variance. Copy number variation at the Ppd-B1 locus was present but explains only 3.2% and thus a comparably small proportion of genotypic variance. By contrast, the plant height loci Rht-B1 and Rht-D1 had no effect on flowering time. The genome-wide scan identified six QTL which each explain only a small proportion of genotypic variance and in addition we identified a number of epistatic QTL, also with small effects. Taken together, our results show that flowering time in European winter bread wheat cultivars is mainly controlled by Ppd-D1 while the fine tuning to local climatic conditions is achieved through Ppd-B1 copy number variation and a larger number of QTL with small effects.

Genome-based establishment of a high-yielding heterotic pattern for hybrid wheat breeding

Significance Selfing species wheat are bred as pure-line varieties with stagnating yield growths. In contrast, selection gain in maize is high, owing to massive investment sustained by hybrid seed sales, coupled with an efficient exploitation of hybrid vigor. We have developed a three-step strategy for establishing a heterotic pattern, which was one of the central unsolved challenges for initiating hybrid breeding programs. The benefits of our approach are demonstrated using data for wheat, but the strategy is relevant for several autogamous crops. Our three-step approach facilitates identification of a heterotic pattern, and thus may contribute to meeting the global challenge of increasing demand for food, feed, and fuel. Hybrid breeding promises to boost yield and stability. The single most important element in implementing hybrid breeding is the recognition of a high-yielding heterotic pattern. We have developed a three-step strategy for identifying heterotic patterns for hybrid breeding comprising the following elements. First, the full hybrid performance matrix is compiled using genomic prediction. Second, a high-yielding heterotic pattern is searched based on a developed simulated annealing algorithm. Third, the long-term success of the identified heterotic pattern is assessed by estimating the usefulness, selection limit, and representativeness of the heterotic pattern with respect to a defined base population. This three-step approach was successfully implemented and evaluated using a phenotypic and genomic wheat dataset comprising 1,604 hybrids and their 135 parents. Integration of metabolomic-based prediction was not as powerful as genomic prediction. We show that hybrid wheat breeding based on the identified heterotic pattern can boost grain yield through the exploitation of heterosis and enhance recurrent selection gain. Our strategy represents a key step forward in hybrid breeding and is relevant for self-pollinating crops, which are currently shifting from pure-line to high-yielding and resilient hybrid varieties.

Dissecting the genetic architecture of frost tolerance in Central European winter wheat.

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.

Hybrid maize breeding with doubled haploids: I. One-stage versus two-stage selection for testcross performance

Optimum allocation of resources is of fundamental importance for the efficiency of breeding programs. The objectives of our study were to (1) determine the optimum allocation for the number of lines and test locations in hybrid maize breeding with doubled haploids (DHs) regarding two optimization criteria, the selection gain ΔGk and the probability Pk of identifying superior genotypes, (2) compare both optimization criteria including their standard deviations (SDs), and (3) investigate the influence of production costs of DHs on the optimum allocation. For different budgets, number of finally selected lines, ratios of variance components, and production costs of DHs, the optimum allocation of test resources under one- and two-stage selection for testcross performance with a given tester was determined by using Monte Carlo simulations. In one-stage selection, lines are tested in field trials in a single year. In two-stage selection, optimum allocation of resources involves evaluation of (1) a large number of lines in a small number of test locations in the first year and (2) a small number of the selected superior lines in a large number of test locations in the second year, thereby maximizing both optimization criteria. Furthermore, to have a realistic chance of identifying a superior genotype, the probability Pk of identifying superior genotypes should be greater than 75%. For budgets between 200 and 5,000 field plot equivalents, Pk > 75% was reached only for genotypes belonging to the best 5% of the population. As the optimum allocation for Pk(5%) was similar to that for ΔGk, the choice of the optimization criterion was not crucial. The production costs of DHs had only a minor effect on the optimum number of locations and on values of the optimization criteria.

Redesigning the exploitation of wheat genetic resources

More than half a million wheat genetic resources are resting in gene banks worldwide. Unlocking their hidden favorable genetic diversity for breeding is pivotal for enhancing grain yield potential, and averting future food shortages. Here, we propose exploiting recent advances in hybrid wheat technology to uncover the masked breeding values of wheat genetic resources. The gathered phenotypic information will enable a targeted choice of accessions with high value for pre-breeding among this plethora of genetic resources. We intend to provoke a paradigm shift in pre-breeding strategies for grain yield, moving away from allele mining toward genome-wide selection to bridge the yield gap between genetic resources and elite breeding pools.

Genomic selection in wheat: optimum allocation of test resources and comparison of breeding strategies for line and hybrid breeding

Key message The implementation of genomic selection in breeding programs can be recommended for hybrid and line breeding in wheat.AbstractHigh prediction accuracies from genomic selection (GS) were reported for grain yield in wheat asking for the elaboration of efficient breeding strategies applying GS. Our objectives were therefore, (1) to optimize the number of lines, locations and testers in different multi-stage breeding strategies with and without GS, (2) to elaborate the most efficient breeding strategy based on the selection gain and its standard deviation, and (3) to investigate the potential of GS to improve the relative efficiency of hybrid versus line breeding in wheat. We used the open source software package “selectiongain” to optimize the allocation of resources in different breeding strategies by predicting the expected selection gain for a fixed budget. Classical two-stage phenotypic selection was compared with three GS breeding strategies for line and hybrid breeding in wheat. The ranking of the alternative breeding strategies varied largely in dependence of the GS prediction accuracy. Fast-track breeding strategies based solely on GS were only advantageous for high GS prediction accuracies that is >0.50 and >0.65 for hybrid and line breeding, respectively. However, a GS prediction accuracy across breeding cycles of 0.3 or even less must be assumed as realistic for grain yield in wheat. For this low GS prediction accuracy, the use of GS is advantageous for line but especially for hybrid breeding in wheat. Furthermore, the use of GS in hybrid wheat breeding increased the relative efficiency of hybrid versus line breeding and, thus, might be an important pillar for the establishment of hybrid wheat.

Multiply to conquer: Copy number variations at Ppd-B1 and Vrn-A1 facilitate global adaptation in wheat

BackgroundCopy number variation was found to be a frequent type of DNA polymorphism in the human genome often associated with diseases but its importance in crops and the effects on agronomic traits are still largely unknown.ResultsHere, we employed a large worldwide panel of 1110 winter wheat varieties to assess the frequency and the geographic distribution of copy number variants at the Photoperiod-B1 (Ppd-B1) and the Vernalization-A1 (Vrn-A1) loci as well as their effects on flowering time under field conditions. We identified a novel four copy variant of Vrn-A1 and based on the phylogenetic relationships among the lines show that the higher copy variants at both loci are likely to have arisen independently multiple times. In addition, we found that the frequency of the different copy number variants at both loci reflects the environmental conditions in the varieties’ region of origin and based on multi-location field trials show that Ppd-B1 copy number has a substantial effect on the fine-tuning of flowering time.ConclusionsIn conclusion, our results show the importance of copy number variation at Ppd-B1 and Vrn-A1 for the global adaptation of wheat making it a key factor for wheat success in a broad range of environments and in a wider context substantiate the significant role of copy number variation in crops.

Lutein and Lutein Esters in Whole Grain Flours Made from 75 Genotypes of 5 Triticum Species Grown at Multiple Sites

Concentrations of lutein and lutein esters were determined in an ample collection of 75 wheat genotypes comprising bread wheat (Triticum aestivum L.), durum (Triticum durum Desf.), spelt (Triticum spelta L.), emmer (Triticum dicoccum Schrank), and einkorn (Triticum monococcum L.) grown in five different environments. Einkorn genotypes showed the highest total amounts of lutein (4.5-7.8 μg/g dry matter), followed by durum (2.0-4.6 μg/g), spelt (0.9-2.0 μg/g), emmer (0.8-1.9 μg/g), and bread wheat (0.7-2.0 μg/g). Due to the observed highly significant genetic variance and high heritability, lutein contents of wheat genotypes may be increased by future plant breeding. Detailed HPLC-DAD-APCI(±)-MS(n) data allowing the identification of six lutein monoesters and nine diesters are presented. Linoleic, palmitic, and oleic acids were the most abundant fatty acids in both the lutein esters and total free lipid fractions. Lutein esters were virtually absent in the tetraploid durum and emmer species, whereas their concentrations considerably differed among the genotypes belonging to the other species.

Hybrid maize breeding with doubled haploids: III. Efficiency of early testing prior to doubled haploid production in two-stage selection for testcross performance

Early testing prior to doubled haploid (DH) production is a promising approach in hybrid maize breeding. We (1) determined the optimum allocation of the number of S1 families, DH lines, and test locations for two different breeding schemes, (2) compared the maximum selection gain achievable under both breeding schemes, and (3) investigated limitations in the current method of DH production. Selection gain was calculated by numerical integration in two-stage breeding schemes with evaluation of testcross progenies of (1) DH lines in both stages (DHTC), or (2) S1 families in the first and DH lines within S1 families in the second stage (S1TC-DHTC). Different assumptions were made regarding the budget, variance components, and time of DH production within S1 families. Maximum selection gain in S1TC-DHTC was about 10% larger than in DHTC, indicating the large potential of early testing prior to DH production. The optimum allocation of test resources in S1TC-DHTC involved similar numbers of test locations and test candidates in both stages resulting in a large optimum number of S1 families in the first stage and DH lines within the best two S1 families in the second stage. The longer cycle length of S1TC-DHTC can be compensated by haploid induction of individual S1 plants instead of S1 families. However, this reduces selection gain largely due to the current limitations in the DH technique. Substantial increases in haploid induction and chromosome doubling rates as well as reduction in costs of DH production would allow early testing of S1 lines and subsequent production and testing of DH lines in a breeding scheme that combines high selection gain with a short cycle length.

Hybrid maize breeding with doubled haploids: II. Optimum type and number of testers in two-stage selection for general combining ability.

Optimum allocation of test resources is of crucial importance for the efficiency of breeding programs. Our objectives were to (1) determine the optimum allocation of the number of lines, test locations, as well as number and type of testers in hybrid maize breeding using doubled haploids with two breeding strategies for improvement of general combining ability (GCA), (2) compare the maximum selection gain (ΔG) achievable under both strategies, and (3) give recommendations for the optimum implementation of doubled haploids in commercial hybrid maize breeding. We calculated ΔG by numerical integration for two two-stage selection strategies with evaluation of (1) testcross performance in both stages (BS1) or (2) line per se performance in the first stage followed by testcross performance in the second stage (BS2). Different assumptions were made regarding the budget, variance components (VCs), and the correlation between line per se performance and GCA. Selection gain for GCA increased with a broader genetic base of the tester. Hence, testers combining a large number of divergent lines are advantageous. However, in applied breeding programs, the use of single- or double-cross testers in the first and inbred testers in the second selection stage may be a good compromise between theoretical and practical requirements. With a correlation between line per se performance and GCA of 0.50, ΔG for BS1 is about 5% higher than for BS2, if an economic weight of line per se performance is neglected. With increasing economic weight of line per se performance, relative efficiency of BS2 increased rapidly resulting in a superiority of BS2 over BS1 already for an economic weight for line per se performance larger than 0.1. Considering the importance of an economic seed production, an economic weight larger than 0.1 seems realistic indicating the necessity of separate breeding strategies for seed and pollen parent heterotic groups.