Browsing by Subject "Breeding"

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Assessing the genetic variation of phosphate efficiency in European maize (Zea mays L.)
(2022) Weiß, Thea Mi; Würschum, Tobias
Why should plant breeders in Central Europe care about phosphate efficiency? Soil phosphorus levels have mostly reached high to very high levels over the last decades in intensively farmed, livestock-rich regions. However, the European Union demands a restructuring of the agricultural production systems through setting ambitious goals envisaged in the Farm to Fork Strategy. By 2030, fertilizer use should be reduced by 20 %, nutrient losses by at least 50 %. As a consequence, farmers have to be even more efficient with crop inputs, among them the globally limited resource of phosphorus fertilizers, while maintaining high yields. Plant breeding means thinking ahead. Therefore, phosphate-efficient varieties should be developed to help farmers meet this challenge and reduce the need for additional fertilizers. One prerequisite to reach this target is that genotypic variation for the relevant traits is available. Moreover, approaches that assist selection by accurate but also time- and resource-efficient prediction of genotypes are highly valuable in breeding. Finally, the choice of the selection environment and suitable trait assessment for the improvement of phosphate efficiency under well-supplied conditions, need to be elaborated. In this dissertation, a diverse set of maize genotypes from ancient landraces to modern hybrids was investigated for phosphate efficiency-related traits under well-supplied P soil conditions. Multi-environmental field trials were conducted in 2019 and 2020. The reaction to different starter fertilizer treatments of the 20 commercially most important maize hybrids grown in Germany was studied. In the hybrid trial, the factor environment had a significant effect on the impact of starter fertilizers. Especially in early developmental stages genotypes showed a different response to the application of starter fertilizers. On the overall very well-supplied soils, we observed no significant genotype-by-starter fertilizer interaction. Nonetheless, we identified hybrids, which maintained high yields also if no starter fertilizer was provided. Thus, it seems that sufficient variation is available to select and breed for phosphate efficiency under reduced fertilizer conditions. Furthermore, the concept of phenomic prediction, based on near-infrared spectra instead of marker data to predict the performance of genotypes, was applied to 400 diverse lines of maize and compared to genomic prediction. For this, we used seed-based near-infrared spectroscopy data to perform phenomic selection in our line material, which comprised doubled haploid lines from landraces and elite lines. We observed that phenomic prediction generally performed comparable to genomic prediction or even better. In particular, the phenomic selection approach holds great potential for predictions among different groups of breeding material as it is less prone to artifacts resulting from population structure. Phenomic selection is therefore deemed a useful and cost-efficient tool to predict complex traits, including phosphorus concentration and grain yield, which together form the basis to determine phosphate efficiency. Lastly, 20 different indicators for phosphate efficiency were calculated, the genetic variation of the different measures present in this unique set of lines was quantified, and recommendations for breeding were derived. Of the different measures for phosphate efficiency reported in literature, Flint landraces demonstrated valuable allelic diversity with regard to phosphate efficiency during the seedling stage. Due to the highly complex genetic architecture of phosphate efficiency-related traits, a combination of genomic and phenotypic selection appears best suited for their improvement in breeding. Taken together, phosphate efficiency, including its definition and meaning, is largely dependent on the available phosphorus in the target environment as well as the farm type, which specifies the harvested produce and thereby the entire phosphorus removal from the field. In conclusion, future maize breeding should work in environments that are similar to the future target environments, meaning reduced fertilizer inputs and eventually lower soil P levels. Our results demonstrate that breeding of varieties, which perform well without starter fertilizers is feasible and meaningful under the well-supplied conditions prevalent in Central Europe. For the improvement of the highly complex trait phosphate efficiency through breeding we recommend to apply genomic and phenomic prediction along with classical phenotypic screening of genotypes and by this making our food systems more resilient towards upcoming challenges in agriculture.
Breeding for resistance to Fusarium ear diseases in maize and small-grain cereals using genomic tools
(2021) Gaikpa, David Sewordor; Miedaner, Thomas
The world’s human and livestock population is increasing and there is the need to increase quality food production to achieve the global sustainable development goal 3, zero hunger by year 2030 (United Nations, 2015). However, biotic stresses such as Fusarium ear infections pose serious threat to cereal crop production. Breeding for host plant resistance against toxigenic Fusarium spp. is a sustainable way to produce more and safer cereal crops such as maize and small-grain winter cereals. Many efforts have been made to improve maize and small-grain cereals for ear rot (ER) and Fusarium head blight (FHB) resistances, using conventional and genomic techniques. Among small-grain cereals, rye had the shortest maturity period followed by the descendant, hexaploid triticale while both wheat species had the longest maturity period. In addition, rye and triticale were more robust to Fusarium infection and deoxynivalenol accumulation, making them safer grain sources for human and animal consumption. However, a few resistant cultivars have been produced by prolonged conventional breeding efforts in durum wheat and bread wheat. High genetic variation was present within each crop species and can be exploited for resistance breeding. In this thesis, the genetic architecture of FHB resistance in rye was investigated for the first time, by means of genome-wide association study (GWAS) and genomic prediction (GP). GWAS detected 15 QTLs for Fusarium culmorum head blight severity, of which two had major effects. Both weighted and unweighted GP approaches yielded higher prediction abilities than marker-assisted selection (MAS) for FHB severity, heading stage and plant height. Genomics-assisted breeding can shorten the duration of breeding rye for FHB resistance. In the past decade, genetic mapping and omics were used to identify a multitude of QTLs and candidate genes for ear rot resistances and mycotoxin accumulation in maize. The polygenic nature of resistance traits, high genotype x environment interaction, and large-scale phenotyping remain major bottlenecks to increasing genetic gains for ear rots resistance in maize. Phenotypic and molecular analyses of DH lines originating from two European flint landraces (“Kemater Landmais Gelb”, KE, and “Petkuser Ferdinand Rot”, PE) revealed high variation for Gibberella ear rot (GER) severity and three agronomic traits viz. number of days to female flowering, plant height and proportion of kernels per cob. By employing multi-SNP GWAS method, we found four medium-effect QTLs and many small-effect (10) QTLs for GER severity in combined DH libraries (when PCs used as fixed effects), none co-localized with the QTLs detected for the three agronomic traits analyzed. However, one major QTL was detected within KE DH library for GER severity. Two prioritized SNPs detected for GER resistance were associated with 25 protein-coding genes placed in various functional categories, which further enhances scientific knowledge on the molecular mechanisms of GER resistance. Genome-based approaches seems promising for tapping GER resistance alleles from European maize landraces for applied breeding. After several cycles of backcrossing and sufficient selection for agronomic adaptation traits, the resistant lines identified in this thesis can be incorporated into existing maize breeding programs to improve immunity against F. graminearum ear infection. Breeding progress can be faster using KE landrace than PE. A successful validation of QTLs identified in this thesis can pave way for MAS in rye and marker-assisted backcrossing in maize. Effective implementation of genomic selection requires proper design of the training and validation sets, which should include part of the current breeding population.
Deciphering the potential of large-scale proteomics to improve product quality and nutritional value in different wheat species
(2022) Afzal, Muhammad; Longin, Friedrich
Wheat (Triticum aestivum) is one of the most important staple crops globally, which provides on average ~20% of the dietary intake of protein, starch and further important ingredients like fiber, minerals, vitamins, and essential amino acids for humans. Besides common wheat, there exist further wheat species with global to only local importance, i.e., durum, spelt, emmer and einkorn. Common wheat and durum are relatively widely cultivated whereas the other three species are cultivated only in specific regions. Apart from other functions, wheat proteins largely influence the end-use quality of products such as bread and pasta quality. Furthermore, wheat proteins can induce inflammatory reactions in humans such as celiac disease, wheat allergy and non-celiac wheat sensitivity. Thus, proteome profiles of different wheat species and cultivars within these species are of high relevance for stakeholders along the wheat supply chain. Proteomic technology has made breakthrough advancements in the recent times capable of quantifying thousands of proteins in 1.5–2 hours. Also, the wheat reference genome has been published and extended recently. These developments are extremely helpful in studying the wheat proteome at a high resolution. However, the modern large-scale proteomics has yet neither been applied to perform comparative investigation of the proteomes of different wheat species nor to study the proteomes of different types of breads and flours nor to study its application in the context of plant breeding. Therefore, we utilized modern large-scale proteomics to fill these gaps within the framework of this PhD work. First of all, an optimized data analysis pipeline was designed to deal with big proteomics data. This was necessary to estimate a multitude of quantitative genetics parameters for each protein and perform a comparative investigation of the proteomes. Optimization included implementation of data filtering based on the quantification of a protein in a given proportion of the samples, cultivars and environments. Different tests such as test for normal distribution of each protein in the context of statistical modelling and test to check the equality of variance between groups to apply the appropriate t-test were incorporated into a semi-automated workflow. In parallel, we adjusted and improved the lab methodology to deal with hundreds of samples within a short time period. We introduced a novel hybrid liquid chromatography-mass spectrometry (LC-MS) approach that combines quantification concatamer (QconCAT) technology with short microflow LC gradients and data-independent acquisition (DIA). The proposed approach measures the proteome by label-free quantification (LFQ) while concurrently providing accurate QconCAT-based absolute quantification of the key amylase/trypsin inhibitors (ATIs). These methods were then applied to compare different wheat species based on dozens of cultivars grown at multiple locations. First, we compared common wheat and spelt and identified 3,050 proteins overall. Of total proteins, 1,555 proteins in spelt and 1,166 in common wheat were only detected in a subset of the field locations. There were 1,495 and 1,604 proteins in spelt and common wheat, respectively, which were consistently expressed across all test locations in at least one cultivar. Finally, there were 84 and 193 unique proteins for spelt and common wheat, respectively, as well as 396 joint proteins, which were significantly differentially expressed between the two species. Using potentially allergenic proteins – annotated as amylase/trypsin inhibitors, serpins, and wheat germ agglutinin – we calculated an equally weighted “allergen index” that largely varied across cultivars ranging from –13.32 to 10.88 indicating the potential to select for cultivars with favorable proteome profiles. Next, we examined the proteomes of six different flours (wholegrain and superfine flours) and 14 different bread types (yeast and sourdough fermented breads and common wheat breads plus/minus bread improver) from common wheat, spelt and rye. Proteins that could cause allergies were functionally classified and comparatively measured by LFQ in flours and breads. Our findings showed that allergenic proteins were more prevalent in common wheat and spelt than rye and were not specifically degraded during bread manufacturing. In terms of abundance of the allergenic proteins, there was almost no difference between spelt and common wheat and the type of grain is likely more important for allergenicity than milling or traditional fermentation techniques. In a further study, we generated the flour reference proteomes for five wheat species, identifying at least 2,540 proteins in each species. More than 50% of the proteins significantly differed between species. Particularly, einkorn expressed 5.4 and 7.2 times less allergens and amylase/trypsin inhibitors than common wheat, respectively, emerging as a potential alternative cereal crop for people with sensitivities to cereal allergens. Lastly, we studied the application of large-scale proteomics for plant breeding. We found a significant impact of the environmental factors on protein expression. Only a fraction of proteins was stably expressed in all environments in at least one cultivar. Environmental influence was observed not only in the form of absolute expression or suppression of a certain protein at one or more environments but also in the form of low heritability (H2). High coefficients of variation across wheat cultivars indicate that the protein profiles of different cultivars vary considerably. Although, heritability was low for many proteins, we were able to identify hundreds of proteins with H²>0.5 – including key proteins for baking quality and human health. It should be possible to specifically manipulate the expression of functionally important proteins with high heritability by selecting and breeding for superior wheat cultivars along the wheat supply chain. Nevertheless, a successful implementation in plant breeding programs needs an improvement in the speed of protein quantification methods and in the validation of protein functions and annotations. In a nutshell, high number of proteins can be quantified in cereal grains utilizing cutting-edge proteomics techniques, opening new avenues for their use in the wheat supply chain. We generated lists of intriguing candidate proteins for further investigations on wheat sensitivity, and proteins with high heritability and important biological functions. Current research work has significant implications for the scientific and business communities across multiple disciplines including breeding, agriculture, cereal technology, nutritional science, health, and medicine. Political decision-makers and stakeholders in the food supply chain can benefit from the findings of this PhD project.
Design of breeding strategies for energy maize in Central Europe
(2012) Grieder, Christoph; Melchinger, Albrecht E.
The area of maize (Zea mays L.) grown for production of biogas has tremendously increased in Germany during the past decade. Thus, breeding companies have a keen interest to develop special varieties for this new market segment. A high methane yield per area (MY), which depends multiplicatively on dry matter yield (DMY) and methane fermentation yield (MFY), is required to ensure the efficiency of biogas maize cultivation. However, information on the targeted biogas maize ideotype is still missing and estimates of relevant quantitative genetic parameters for representative material are required to design optimum breeding strategies. We conducted a large field experiment to assess the relevant traits in biogas maize, their variation, and associations among them. In detail, our objectives were to (1) determine MFY and its production kinetics as well as the chemical composition, (2) examine the relationship of MFY and traits related to its kinetics with plant chemical composition and silage quality traits like in vitro digestible organic matter (IVDOM) and metabolizable energy concentration (MEC); (3) examine the potential of near infrared spectroscopy (NIRS) for prediction of traits related to methane production; (4) evaluate a large population of inbred lines and their testcrosses under field conditions for agronomic and quality traits; (5) estimate variance components and heritabilities (h2) of traits relevant to biogas production; (6) study correlations among traits as well as between inbred line per se (LP) and testcross performance (TP); and (7) draw conclusions for breeding maize as a substrate for biogas production. For this purpose, a representative set of 285 dent inbred lines from diverse origins and their 570 testcross progenies with two adapted flint testers was produced. Both material groups were evaluated in field experiments conducted in six environments (three locations, two years) in Germany. For analysis of MFY, samples of a diverse core set of 16 inbred lines and their 32 testcrosses were analyzed using the Hohenheim Biogas Yield Test, a discontinuous, laboratory fermentation assay. The kinetics of methane production was assessed by non-linear regression. Estimates of h2 for MFY measured after short fermentation time (3 days) were high, but genotypic variance and, therefore, also h2 decreased towards the end of the fermentation period (35 days). This was presumably the consequence of a nearly complete degradation of all chemical components during the long fermentation period. This interpretation was supported by strong correlations of MFY with chemical components, IVDOM and MEC for the early, but not the late fermentation stages. Based on the samples in the core set, NIRS calibrations were developed for MFY, parameters related to the kinetics of methane production, and chemical composition. With a coefficient of determination from validation (R2V) of 0.82, accuracy of prediction was sufficiently high for the maximum methane production rate, which is related to the early fermentation phase, but not satisfactory for the time needed to reach 95% of a sample?s final MFY (R2V = 0.51). In agreement with the trend of h2, performance of NIRS to predict MFY on day 35 (R2V = 0.77) was lower than for MFY on day 3 (R2V = 0.85), but still at a satisfactory level, as was the case for concentrations of different chemical components. Hence, NIRS proved to be a powerful tool for prediction of MFY and chemical composition in the main experiment. For TP, estimates of variance components from the main experiments revealed that general combining ability (GCA) was the major source of variation. The very tight correlation of MY with DMY but not with MFY indicated that variation in MY was primarily attributable to differences in DMY. Compared to MEC, MFY showed a weaker association with chemical composition. Genotypic correlation (rg) of MFY was strongest with non-degradable lignin (-0.58). Correlation of MFY with starch was not significant and indicated a lower importance of high cob proportions for biogas maize than for forage maize. Hence, to improve MY, selection should primarily focus on increasing DMY. Results for LP in the main experiment largely confirmed results from testcrosses and favor selection for high dry matter yielding genotypes with less emphasis on ear proportion. Estimates of rg between LP and GCA were highest (> 0.94) for maturity traits (days to silking, dry matter concentration) and moderate (> 0.65) for DMY and MY. Indirect selection for GCA on basis of LP looks promising for maturity traits, plant height, and to some extent also for DMY.
Differences in mucilage properties and stomatal sensitivity of locally adapted Zea mays in relation with precipitation seasonality and vapour pressure deficit regime of their native environment
(2023) Berauer, Bernd J.; Akale, Asegidew; Schweiger, Andreas H.; Knott, Mathilde; Diehl, Dörte; Wolf, Marc‐Philip; Sawers, Ruairidh J. H.; Ahmed, Mutez A.
With ongoing climate change and the increase in extreme weather events, especially droughts, the challenge of maintaining food security is becoming ever greater. Locally adapted landraces of crops represent a valuable source of adaptation to stressful environments. In the light of future droughts—both by altered soil water supply and increasing atmospheric water demand (vapor pressure deficit [VPD])—plants need to improve their water efficiency. To do so, plants can enhance their access to soil water by improving rhizosphere hydraulic conductivity via the exudation of mucilage. Furthermore, plants can reduce transpirational water loss via stomatal regulation. Although the role of mucilage and stomata regulation on plant water management have been extensively studied, little is known about a possible coordination between root mucilage properties and stomatal sensitivity as well as abiotic drivers shaping the development of drought resistant trait suits within landraces. Mucilage properties and stomatal sensitivity of eight Mexican landraces of Zea mays in contrast with one inbred line were first quantified under controlled conditions and second related to water demand and supply at their respective site of origin. Mucilage physical properties—namely, viscosity, contact angle, and surface tension—differed between the investigated maize varieties. We found strong influences of precipitation seasonality, thus plant water availability, on mucilage production (R2 = .88, p < .01) and mucilage viscosity (R2 = .93, p < .01). Further, stomatal sensitivity to increased atmospheric water demand was related to mucilage viscosity and contact angle, both of which are crucial in determining mucilage's water repellent, thus maladaptive, behavior upon soil drying. The identification of landraces with pre‐adapted suitable trait sets with regard to drought resistance is of utmost importance, for example, trait combinations such as exhibited in one of the here investigated landraces. Our results suggest a strong environmental selective force of seasonality in plant water availability on mucilage properties as well as regulatory stomatal effects to avoid mucilage's maladaptive potential upon drying and likely delay critical levels of hydraulic dysfunction. By this, landraces from highly seasonal climates may exhibit beneficial mucilage and stomatal traits to prolong plant functioning under edaphic drought. These findings may help breeders to efficiently screen for local landraces with pre‐adaptations to drought to ultimately increase crop yield resistance under future climatic variability.
Gibberella ear rot resistance in European maize : genetic analysis by complementary mapping approaches and improvement with genomic selection
(2022) Han, Sen; Melchinger, Albrecht E.
During the last decades, implementation of molecular markers such as single nucleotide polymorphisms (SNPs) has transformed plant breeding practices from conventional phenotypic selection to marker-assisted selection (MAS) and genomic selection (GS) that are more precise, faster and less resource-consuming. In this dissertation, we investigated these three selection approaches for improving the polygenic trait Gibberella ear rot (GER) resistance in maize (Zea mays L.), which is an important fungal disease in Europe and North America leading to reduced grain yield and grain contaminated with mycotoxins such as deoxynivalenol (DON) and zearalenone (ZON). Three different sets of materials were evaluated in multiple environments and analyzed for different objectives. In the first study, five flint doubled-haploid (DH) families (with size 43 to 204) inter-connected at various levels through common parents, were generated in an incomplete half-diallel design with four parental lines developed by the University of Hohenheim. Significant genotypic variances and generally high heritabilities were observed for all three traits (i.e., GER, DON and days to silking (DS)) in all families, implying good prospects for resistance breeding and phenotypic selection against GER across different environments in European maize germplasm. Genetic correlations were extremely tight between DON and GER and moderately negative for DS with DON or GER, suggesting that indirect selection against GER would be efficient to reduce DON, but maturity should be considered in GER resistance breeding. Using a high-density consensus map with 2,472 marker loci, we compared classical bi-parental mapping of QTL (quantitative trait locus/loci) with multi-parental QTL mapping conducted with joint families and using four different biometric models. Multi-parental QTL mapping models identified all and even further QTL than the bi-parental QTL mapping model conducted within each family. Interestingly, QTL for DON and GER were mostly family-specific, yet multiple families had several common QTL for DS. Many QTL displayed large additive effects and most favorable alleles originated from the highly resistant parent. Interactions between detected QTL and genetic background (family) were rare and had comparatively small effects. Multi-parental QTL mapping models generally did not yield higher prediction accuracy than the bi-parental QTL mapping model for all traits. In the second study, two diversity panels consisting of 130 elite European dent and 114 flint lines, respectively, from the University of Hohenheim were evaluated and subject to a genome-wide association study within each pool. Similar to the first study, highly significant genotypic and genotype × environment interaction variances were observed for GER, DON and DS. Heritabilities were moderately high for GER and DON and high for DS in both pools. Estimated genomic correlations between pools were close to zero for DON and DS, and slightly higher for GER. The detected QTL for DON were all specific to each heterotic pool and none of them was in common with previously detected QTL. Furthermore, no QTL was detected for GER and DS in both pools. Genomic prediction (GP) across pools yielded low or even negative prediction accuracy for all traits. When the training set (TS) size was increased by combining lines from both heterotic pools, the combined-pool GP approaches had no higher prediction accuracy than the within-pool GP approach. Different from expectation, method BayesB did not outperform genomic best linear unbiased prediction (GBLUP). In the third study, we analyzed two backcross (BC) families derived from a resistant and a susceptible recurrent parent. Both BC populations differed substantially in their means for all traits, suggesting that the two recurrent parents have different QTL alleles for GER resistance. Relatively high correlations were observed between DON and ZON concentrations measured by immunoassays and GER visual severity scoring and NIRS (near-infrared spectroscopy) within each BC population. Thus, the mycotoxin content in grain can reliably be reduced by directional selection for GER severity and NIRS measurements that are less expensive and less laborious. In conclusion, GER resistance in European maize germplasm can be effectively improved through breeding with resistant donor lines. GER visual severity scoring and NIRS measurements were found to be reliable predictors for DON and ZON concentrations in grain. We observed that QTL for GER and DON are mostly specific to a few families or a limited number of materials, whereas QTL for DS are more commonly shared between families. The multi-parental QTL mapping approach is complementary to the classical bi-parental QTL mapping in that the latter has generally higher power to identify rare but large-effect QTL for traits such as GER and DON, whereas the former is superior in detecting common but small-effect QTL for traits such as DS. Composing the TS with materials more closely related to the prediction set and increasing the TS size generally resulted in higher prediction accuracy for MAS and GS, irrespective of the trait and statistical model.
Improvement of breeding strategies for the trait vase life in cut carnations (Dianthus caryophyllus L.)
(2018) Boxriker, Maike; Piepho, Hans-Peter
Carnation (Dianthus caryophyllus L.) is one of the ten most famous cut flowers worldwide. A single big flower characterizes standard carnations, while mini car-nations possess multiple flowers per stem. Vase life (VL) is one of the most im-portant breeding objectives in carnations due to the need of long transportation times and direct influence on the costumers. But VL is a complex trait with several effects influencing it. Two-phase traits like VL are traits where the assessment is done in a second phase, in the laboratory and the plants are cultivated in the greenhouse, the first phase. Many experiments have a two-phase character, but little research has been conducted to develop experimental designs in the second phase. To improve breeding efficiency, molecular markers and genomic selection is used in agriculture science but it is so far not common in ornamental breeding. The goal of this thesis was the implementation of SNP-based molecular markers for the trait VL to improve selection of long-lasting, transportable cut carnations. For marker association, 1,500 carnation genotypes were screened for VL behav-ior in an experimental design in both phases. Response to selection was used to assess efficiency. The second-phase experimental design was more important for precise data analyses. This highlights the research need on this topic. Fur-thermore, it was possible to suggest row-column designs for VL trials. Row-column designs are more flexible in the case of positional effects compared with one-dimensional blocking and can be easily analyzed like an α-design. The easiest way to design the following phases are to apply the design one-to-one. The carnation types, mini and standard, showed an influence on VL. The mini carnations last 0.5 d longer than the standard carnations. The same conclusion was drawn based on the molecular data. Transcriptome data was generated with two different sequencing methods. By independent analysis of both carnation types, different results than via the analysis of the whole data set were found. This indicates that the analysis of carnations should be done separately for each carnation type. Association of the phenotypic and genotypic data was so far not possible. As an alternative to molecular markers, genetic correlations for the use as indirect selection for the trait VL and others for breeding relevant traits was calculated. For the first time, bivariate analysis was conducted in two-phase ex-periments. The genotypic correlation between VL and FD was high, but indirect selection would be less effective than direct selection. However, the information can provide an indication of the performance and the effort to measure FD is small. The calculated high heritability of VL and found differences in VL of up to 15 d between the best and worst genotypes showed the potential of improving the population mean by using improved selection strategies like marker-assisted selection or auxiliary traits and the use of statistical methods like experimental designs in all phases of the experiment. The influence of carnation type was shown with this thesis and indicates that the implementation of molecular markers must be done independently for each car-nation type. The importance of experimental designs in multi-phase experiments was highlighted and statistical analysis by mixed models and a bivariate analysis of different traits was performed. Until now, no molecular marker for VL was identified but in a further research project, this will be solved by generating more genotypic data and the construction of a genetic map.
Multiomics based association mapping in wheat reveals genetic architecture of quality and allergenic related proteins
(2023) El Hassouni, Khaoula; Afzal, Muhammad; Steige, Kim A.; Sielaff, Malte; Curella, Valentina; Neerukonda, Manjusha; Tenzer, Stefan; Schuppan, Detlef; Longin, Carl Friedrich Horst; Thorwarth, Patrick
Wheat is an important staple crop since its proteins contribute to human and animal nutrition and are important for its end-use quality. However, wheat proteins can also cause adverse human reactions for a large number of people. We performed a genome wide association study (GWAS) on 114 proteins quantified by LC-MS-based proteomics and expressed in an environmentally stable manner in 148 wheat cultivars with a heritability > 0.6. For 54 proteins, we detected quantitative trait loci (QTL) that exceeded the Bonferroni-corrected significance threshold and explained 17.3–84.5% of the genotypic variance. Proteins in the same family often clustered at a very close chromosomal position or the potential homeolog. Major QTLs were found for four well-known glutenin and gliadin subunits, and the QTL segregation pattern in the protein encoding the high molecular weight glutenin subunit Dx5 could be confirmed by SDS gel-electrophoresis. For nine potential allergenic proteins, large QTLs could be identified, and their measured allele frequencies open the possibility to select for low protein abundance by markers as long as their relevance for human health has been conclusively demonstrated. A potential allergen was introduced in the beginning of 1980s that may be linked to the cluster of resistance genes introgressed on chromosome 2AS from Triticum ventricosum. The reported sequence information for the 54 major QTLs can be used to design efficient markers for future wheat breeding.
Optimum schemes for hybrid maize breeding with doubled haploids
(2011) Wegenast, Thilo; Melchinger, Albrecht E.
In hybrid maize breeding, the doubled haploid technique is increasingly replacing conventional recurrent selfing for the development of new lines. In addition, novel statistical methods have become available as a result of enhanced computing facilities. This has opened up many avenues to develop more efficient breeding schemes and selection strategies for maximizing progress from selection. The overall aim of the present study was to compare the selection progress by employing different breeding schemes and selection strategies. Two breeding schemes were considered, each involving selection in two stages: (i) developing DH lines from S0 plants and evaluating their testcrosses in stage one and testcrosses of the promising DH lines in stage two (DHTC) and (ii) early testing for testcross performance of S1 families before production of DH lines from superior S1 families and then evaluating their testcrosses in the second stage (S1TC-DHTC). For both breeding schemes, we examined different selection strategies, in which variance components and budgets varied, the cross and family structure was considered or ignored, and best linear unbiased prediction (BLUP) of testcross performance was employed. The specific objectives were to (1) maximize through optimum allocation of test resources the progress from selection, using the selection gain (ΔG) or the probability to select superior genotypes (P(q)) as well as their standard deviations as criteria, (2) investigate the effect of parental selection, varying variance components and budgets on the optimum allocation of test resources for maximizing the progress from selection, (3) assess the optimum filial generation (S0 or S1) for DH production, (4) compare various selection strategies - sequential selection considering or ignoring the cross and family structure - for maximizing progress from selection, (5) examine the effect of producing a larger number of candidates within promising crosses and S1 families on the progress from selection, and (6) determine the effect of BLUP, where information from genetically related candidates is integrated in the selection criteria, on the progress from selection. For both breeding schemes, the best strategy was to select among all S1 families and/or DH lines ignoring the cross structure. Further, in breeding scheme S1TC-DHTC, the progress from selection increased with variable sizes of crosses and S1 families, i.e., larger numbers of DH lines devoted to superior crosses and S1 families. Parental cross selection strongly influenced the optimum allocation of test resources and, consequently, the selection gain ΔG in both breeding schemes. With an increasing correlation between the mean testcross performance of the parental lines and the mean testcross performance of their progenies, the superiority in progress from selection compared to randomly chosen parents increased markedly, whereas the optimum number of parental crosses decreased in favor of an increased number of test candidates within crosses. With BLUP, information from genetically related test candidates resulted in more precise estimates of their genotypic values and the progress from selection slightly increased for both optimization criteria ΔG and P(q), compared with conventional phenotypic selection. Analytical solutions to enable fast calculations of the optimum allocation of test resources were developed. This analytical approach superseded matrix inversions required for the solution of the mixed model equations. In breeding scheme S1TC-DHTC, the optimum allocation of test resources involved (1) 10 or more test locations at both stages, (2) 10 or fewer parental crosses each with 100 to 300 S1 families at the first stage, and (3) 500 or more DH lines within a low number of parental crosses and S1 families at the second stage. In breeding scheme DHTC, the optimum number of test candidates at the first stage was 5 to 10 times larger, whereas the number of test locations at the first stage and the number of DH lines at the second stage was strongly reduced compared with S1TC-DHTC. The possibility to reduce the number of parental crosses by selection among parental lines is of utmost importance for the optimization of the allocation of test resources and maximization of the progress from selection. Further, the optimum allocation of test resources is crucial to maximize the progress from selection under given economic and quantitative-genetic parameters. By using marker information and BLUP-based genomic selection, more efficient selection strategies could be developed for hybrid maize breeding.
Phenotypic and genomics-assisted breeding of soybean for Central Europe : from environmental adaptation to tofu traits
(2022) Kurasch, Alena; Würschum, Tobias
Soybean (Glycine max Merr.) is one of the major crops in the world providing an important source of protein and oil for food and feed; however it is still a minor crop in Central Europe. Soybean cultivation can play an important role in a more sustainable agricultural system by increasing local and regional protein production in Europe. The demand for locally produced soybean products is still growing in Europe. The key for a successful establishment of soybean cultivation in Europe is adaptation of soybean varieties to the Central European growing conditions. For the latitudinal adaptation to long-day conditions in Central to Northern Europe, an adapted early flowering and maturity time is of crucial importance for a profitable cultivation. The key traits flowering and maturity are quantitatively inherited and mainly affected by photoperiod responsiveness and temperature sensitivity. The most important loci for an early flowering and maturity are E1-E4 and the various allelic combinations condition soybean flowering and maturity time and therefore strongly contribute to the wide adaptability (Jiang et al., 2014; Tsubokura et al., 2014; M. Xu et al., 2013). Besides the main usage as protein source for animal feeding, soybean is also a very valuable source for human consumption. Tofu is enjoying ever greater popularity in Europe, as it is one of the best sources of plant protein with additional health benefits, rich in essential amino acids, beneficial lipids, vitamins, and minerals, as well as other bioactive compounds, such as isoflavones, soyasaponin, and others, (Lima et al., 2017; Zhang et al., 2018). Thus, plant breeding has to provide not only well-adapted varieties with good agronomic and quality properties, but also provide varieties well-suited to the further processing into soymilk and tofu. Therefore, a good knowledge about the breeding target, how to assess it and how it is inherited is crucial. The conducted studies covered a broad range of aspects relevant to improve a soybean breeding program. By combining environmental analysis, E-gene analysis, genomic approaches (QTL mapping and genomic prediction), and tofu phenotyping, breeder decisions become more accurate and targeted in the way of selection thereby increasing the genetic gain. In addition, combining the results of the different aspects helps to optimize the resources of a breeding program. Increasing the knowledge about the different aspects from environment to tofu QTL enables a breeder to be more precise and focused. But the more targeted and specific, the more complex a breeding program gets, which requires adequate tools to handle all the different information in a meaningful and efficient way to enable a quick and precise breeding decision.
Quantitative-trait loci (QTL) mapping of important agronomical traits of the grain and biomass production in winter rye (Secale cereale L.)
(2015) Haffke, Stefan; Miedaner, Thomas
Rye is an important crop in Northern and Eastern Europe and mainly used for food and feed and became most recently important for biogas production. Hybrid rye varieties dominate the cultivated area, which is mainly on light and sandy soils, because rye has a relatively high tolerance to biotic and abiotic stress factors. Climate change will also affect Central Europe, causing higher temperatures and less precipitation in spring and summer. Rye will be influenced more by these effects than other cereals because it is mainly grown on marginal environments. Rye has a high potential for being used as a biogas substrate, but detailed information on improving this trait in hybrid rye is missing. Until now, no study that analyzed phenotypic and genotypic agronomic traits for using rye for biogas production exists. Further, there is only one study, which dealt with the influence of periodic drought stress in rye cultivated areas. Beside this, we analyzed yield stability over a wide range of environments in consideration of drought stress in Central Europe. We analyzed an interpool hybrid population (Pop-D) in 2011 and 2012 at seven environments in Germany for the biomass yield and grain yield (Publication I). This study showed low correlations between grain yield and dry matter yield (r = 0.33). Higher correlations were obtained with two plant height measurements (at heading time, r = 0.64; before harvest, r = 0.52) and dry matter yield. The indirect selection via plant height was superior in contrast to the direct selection of dry matter yield by factor 1.24. Genotypic results confirmed phenotypic results as no overlapping QTL for grain yield and dry matter yield were detected (Publication II). However, we identified common gene regions for plant height and dry matter yield due to the high correlation between both. Plant height is a promising trait for indirectly selecting high biomass yielding varieties. The paradigm shift from shorter plants with high grain yield to taller hybrids as a resource for biogas substrate needs additional breeding efforts for lodging resistance. In Publication III we analyzed two intrapool populations (Pop-A and -B) and one interpool population (Pop-C) at 16 – 18 environments (location x year combinations) under irrigated and rainfed conditions in Germany and Poland. Yield stability was high over a wide range of environments, even when drought stress environments were included. This illustrates the adaption of rye to marginal and drought stress environments. The analyzed populations showed no differences within yield stability, but yield differences between inter- (Pop-C) and intra-pool (Pop-A and -B) crosses were visible. Selection for yield stability is possible due to the genetic variance for this trait within all three populations. Therefore, it is important to select genotypes with low genotype x environment interaction. All three populations showed high yield stability on a high yield level and were already well adapted to extreme weather events caused by climate change. It is recommended to use highly diverse environments with irrigated and rainfed conditions to select on yield stability and high yielding varieties under optimum and drought conditions
Sorghum breeding strategies for phosphorus-limited environments in Western Africa : from field to genome level
(2014) Leiser, Willmar Lukas; Haussmann, Bettina
A growing world population juxtaposed with dwindling phosphorus (P) resources present new challenges to current and future global agricultural production. The burden of depleting phosphorus resources is particularly felt in sub-Saharan Africa (SSA). The expected doubling of its population by 2050 and the widespread poor soil fertility will pose an enormous task to future food security in SSA. Plant breeding can be considered as one major factor to improve agricultural production under these harsh low-input conditions. Nevertheless, until recently there have been no thorough breeding efforts to enhance crop production for low-P soil conditions in SSA. Sorghum (Sorghum bicolor L. Moench) is the world’s fifth and Africa’s second most grown cereal crop. Sorghum is a staple crop of SSA and is mostly grown in resource poor regions under low-input cropping conditions, with the largest share in West Africa (WA). Its good adaptation to harsh environmental conditions makes it an important crop for the arid and semi-arid regions, hence a crop vital for food security and increasingly farm income in WA. Breeding sorghum specifically targeting P-limited soils is considered as one of the major challenges for future food production and can serve millions of smallholder farmers in WA. Nevertheless, plant breeders are mostly reluctant to conduct breeding experiments under low-input conditions due to a higher spatial variability of soil properties leading to a lower response to selection. In an unprecedented large scale multi-environment experiment from 2006-2012 in three WA countries, namely Mali, Senegal and Niger, 187 WA sorghum genotypes were evaluated for their performance under P-sufficient and P-deficient conditions. The main goal of this study was to establish a breeding strategy for sorghum targeting P-limited environments. In order to establish such a strategy, the following objectives were defined: (I) to evaluate the impact of spatial models on genotypic selection in low-input field trials, (II) to develop a selection strategy for sorghum targeting P-limited environments, based on quantitative genetic parameters and (III) to identify genomic regions influencing sorghum performance in P-limited environments using modern genomic tools. The major findings of this study can be summarized as follows: Spatial models can increase the precision and efficiency especially of low-input field trials and may lead to different genotype rankings. Hence spatial models and/or adequate field designs are necessary tools for efficient genotype selection under low-input conditions and must be considered in a breeding program targeting P-limited conditions. Sorghum performance is severely impeded by low-P soil conditions and shows large grain yield and plant height reductions and delayed flowering. Nevertheless, WA sorghum is generally well adapted to low-P soil conditions and shows a large exploitable genetic variation for P efficiency. Direct selection under low-P conditions is feasible, necessary and more efficient than indirect selection under high-P conditions and should be pursued in a breeding program targeting P-limited environments. Landrace genotypes are more specifically adapted to low-P conditions and show a higher P acquisition capacity, Durra and Guinea race sorghums show a similar specific low-P adaptation, hence these genotype groups are very promising source germplasm for further breeding efforts. Photoperiod sensitive genotypes show less delay in heading, a higher P acquisition rate and a specific low-P adaptation, hence should be considered for climate and low-P resilience breeding. Selection for low P concentration of grain can be used to enhance internal P use efficiency, therefore decreasing further soil P mining. WA sorghum shows a large genetic diversity, hence providing a valuable source for genetic studies examining the underlying genetics of low-P adaptation. There are many genomic regions involved in sorghum adaptation to low-P soil conditions. Nevertheless, some regions could be identified as major contributors, showing large effects on and strong associations to genotypic performance. Molecular markers in sorghum homologs of the major P efficiency gene PSTOL1 from rice stably enhanced P uptake and crop performance through an increased root growth of sorghum under low-P soil conditions and can be used in marker assisted selection for grain yield production under P-limited conditions. Furthermore, it was observed that grain yield production under P-limited conditions and Al-tolerance are pleiotropically regulated by the same genomic region and most probably the same gene SbMATE. Molecular markers of this region and within the gene SbMATE should be used for marker assisted selection to simultaneously enhance the tolerance to two of the most serious abiotic stresses for sorghum in WA, Al toxicity and P deficiency. WA Guinea race sorghums are an excellent source not only for low-P specific alleles, but also for Al-tolerance and represent therefore an excellent source germplasm for allele mining and marker assisted selection. Genomic selection appears to be a very promising approach to further increase the response to selection. But methods giving more weight to single molecular markers linked to Al-tolerance should be considered. The laid out results show that breeding sorghum specifically targeting P-limited conditions is necessary and feasible using advanced statistical models and modern genetic tools, and should be pursued as a major selection criterion in WA sorghum breeding programs. Nevertheless, only by combining agronomic and socio-economic measures with plant breeding efforts, millions of WA smallholder farmers can be reached and major yield increases can be expected in the near future.
Status-Quo und Perspektiven von Zweinutzungshühnern in Baden-Württemberg : Ergebnisse eines World-Cafés im Rahmen des 1. Dialogforums des Projektes „ZweiWert“ am 2.3.2023.
(2023) Bermejo, Gabriela; Imort-Just, Annik; Gebhardt, Beate; Hess, Sebastian; Kiefer, Lukas; Zikeli, Sabine
The motivation behind the growing interest in dual-purpose chicken is diverse. Among other things, it is driven by the prohibition of killing male chicks from laying lines, by the desire to improve animal welfare in general, and by the preservation of genetic biodiversity and a more sustainable poultry production system. The project "ZweiWert" aims to create a regional network of actors in order to build up a value chain for dual-purpose chickens in Baden-Württemberg. Following a status quo and potential analysis of the agricultural production of dual-purpose chicken, a network will be established along the entire value chain, so that a sustainable production as well as a regular supply of the resulting products can be ensured. In order to promote the exchange between actors and to be able to develop policy options and recommendations, dialogue forums will be organized during the course of the project. The first forum took place in March 2023 and brought together representatives from different sectors. After various expert contributions, participants were able to exchange views on different areas of the value chain in the format of a World Café. In particular, the topics of networking and economic efficiency, cooperation, aspects of the legal/political framework and the need for more transparency and communication were mentioned during these discussions.
Strategies for selecting high-yielding and broadly adapted maize hybrids for the target environment in Eastern and Southern Africa
(2012) Windhausen, Sandra Vanessa; Melchinger, Albrecht E.
Maize is a major food crop in Africa and primarily grown by small-holder farmers under rain-fed conditions with low fertilizer input. Projections of decreasing precipitation and increasing fertilizer prices accentuate the need to provide farmers with maize varieties tolerant to random abiotic stress, especially drought and N deficiency. Genetic improvement for the target environment in Eastern and Southern Africa can be achieved by: (i) direct selection of grain yield in random abiotic stress environments, (ii) indirect selection for a secondary trait or grain yield in optimal, low-N and/or managed stress environments, or (iii) index selection using information from all test environments. At present, the maize hybrid testing programs of the International Maize and Wheat Improvement Center (CIMMYT) select primarily for grain yield under managed stress and optimal environments and subdivide the target environment according to geographic and climatic differences. It is not known to what extend the current strategy contributes to selection gains. The same holds true for genomic prediction, a strategy that is not yet implemented into the CIMMYT maize breeding program but that may accelerate breeding progress and reduce cycle length by predicting genotype performance based on molecular markers. Regarding the different strategies mentioned for selecting high-yielding and broadly adapted maize hybrids, the breeder needs to decide which of them are most promising to increase genetic gains. Consequently, the objectives of my thesis were to (1) evaluate the potential of leaf and canopy spectral reflectance as novel secondary traits to predict grain yield across different environments, (2) estimate to what extent indirect selection in managed drought and low-N stress environments is predictive of grain yield in random abiotic stress environments, (3) investigate whether subdividing the target environment into climate, altitude, geographic, yield level or country subregions is likely to increase rates of genetic gain, and (4) evaluate the prospects of genomic prediction in the presence of population structure. The measurement of spectral reflectance (495 ? 1853 nm) of both leaves and canopy at anthesis and milk grain stage explained less than 40% of the genetic variation in grain yield after validation. Consequently, selection based on predicted grain yield is only suitable for pre-screening, while final yield evaluation will still be necessary. Nevertheless, the prospect of developing inexpensive and easy to handle devices that can provide, at anthesis, precise estimates of final grain yield warrants further research. Based on a retrospective analysis across 9 years, more than 600 trials and 448 maize hybrids, it was shown that maize hybrids were broadly adapted to climate, altitude, geographic and country subregions in Eastern and Southern Africa. Consequently, I recommend that the maize breeding programs of CIMMYT in the region should be consolidated. Within the consolidated breeding programs, genotypes should be selected for performance in low- and high yielding environments as the genotype-by-yield level interaction variance was high relative to the genetic variance and genetic correlations between low- and high-yielding environments were moderate. Genetic gains were maximized by index selection, considering the yield-level effect as fixed and appropriately weighting information from all trials. To allow better allocation of resources, locations with high occurrence of random abiotic stress need to be identified. Heritability in trials conducted at these locations may be increased by the use of row- and column designs and/or spatial adjustment. Furthermore, resources invested into managed drought trials should be maintained during early breeding stages but shifted to the conduct of low-N trials at later breeding stages. Investments in a larger number of low-N trials may increase selection gain, because performance under low-N and random abiotic stress was highly correlated and genotypes can be easily selected under different levels of soil N. Prospects are promising to accelerate breeding cycles by the use of genomic prediction. Based on two large data sets on the performance of eight breeding populations, it was shown that prediction accuracy resulted primarily from differences in mean performance of these populations. Genomic prediction may be implemented into the CIMMYT maize breeding program to predict the performance of lines from a diversity panel, segregating lines from the same or related crosses, and progenies from closed populations within a recurrent selection program. The breeding scenarios in which genomic prediction is most promising still need to be defined. Generally, the construction of larger training sets with strong relationship to the validation set and a detailed analysis of the population structure within the training and validation sets are required. In conclusion, combining index and genomic selection is the most promising strategy for providing high-yielding and broadly adapted maize genotypes for the target environments in Eastern and Southern Africa.
Untersuchungen zur Vererbung von Qualitätseigenschaften bei Silomais (Zea mays L.)
(2004) Krützfeldt, Birte A. E.; Geiger, Hartwig H.
In central Europe silage maize (Zea mays L.) is a major source of cattle feed. The quality or the feeding value of a silage maize variety mainly depends on its digestibility and energy content. The establishing of the near-infrared-reflectance-spectroscopy- (NIRS) technique allows the analysis of more than one quality determining trait simultaneously in an easy and short way. In this study one objective was the influence of stover quality on whole plant quality. In hybrid breeding indirect selection on the basis of inbred line performance has a great advantage because the number of testcrosses can be reduced. Therefore it was tested, if the stover quality of the testcrosses could be predicted on the line per se value. Besides the correlation between agronomic and quality traits was analysed. In the years 1999 and 2000 the evaluation of the stover of the lines and testcrosses and the whole plant of the testcrosses was conducted at four climatically diverse sites in Germany. Three data sets with flint-lines and dent-lines, each proved with one tester-line, were evaluated for the correlation between inbred line and testcross performance. The test for combining ability was performed with three smaller data sets also consisting of flint-lines and dent-lines with two tester-lines per data set. The coefficients of heritability were high for the agronomic and quality traits in the data sets of the inbred lines. In the data sets of the testcrosses the variation attributed to the genotypic variance was smaller, genotype × location-interactions were of lower importance. In the data sets, each with two tester-lines it was obvious that for quality traits of stover and whole plant the interaction between line and tester was mostly not significant. The genotypic correlation between inbred line and testcross performance was highly significant for almost all quality traits of the stover, but the correlation coefficients were mostly only moderate. Only the expected success of an indirect selection on line per se- value for cell-wall digestibility of the stover exceeded that of the direct selection on testcross performance in all data sets. However, a selection of extremes on line per se value should be possible for stover digestibility. The genotypic correlations between comparable traits in stover and whole plant were mainly low. The cell-wall digestibility was the only trait which was independent of dry matter content. For evaluation of the further quality traits attention has to be paid to the maturity stage, to prevent a maturity-based bias of the results. In the testcrosses stover digestibility increased and whole plant digestibility was reduced with an increase in whole plant dry matter yield. But the genotypic correlations were only moderate and a simultaneous selection to improve quality and yield seems to be possible.