Browsing by Subject "GWAS"
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Publication Assessment of phenotypic, genomic and novel approaches for soybean breeding in Central Europe(2022) Zhu, Xintian; Würschum, TobiasSoybean is the economically most important leguminous crop worldwide and serves as a main source of plant protein for human nutrition and animal feed. Europe is dependent on plant protein imports and the EU protein self-sufficiency, which is an issue that has been on the political agenda for several decades, has recently received renewed interest. The protein imports are mainly in the form of soybean meal, and soybean therefore appears well-suited to mitigate the protein deficit in Europe. This, however, requires an improvement of soybean production as well as an expansion of soybean cultivation and thus breeding of new cultivars that combine agronomic performance with adaptation to the climatic conditions in Central Europe. The objective of this thesis was to characterize, evaluate and devise approaches that can improve the efficiency of soybean breeding. Breeding is essentially the generation of new genetic variation and the subsequent selection of superior genotypes as candidates for new cultivars. The process of selection can be supported by marker-assisted or genomic selection, which are both based on molecular markers. A first step towards the utilization of these approaches in breeding is the characterization of the genetic architecture underlying the target traits. In this study, we therefore performed QTL mapping for six target traits in a large population of 944 recombinant inbred lines from eight biparental families. The results showed that some major-effect QTL are present that could be utilized in marker-assisted selection, but in general the target traits are quantitatively inherited. For such traits controlled by numerous small-effect QTL, genomic selection has proven as a powerful tool to assist selection in breeding programs. We therefore also evaluated the genomic prediction accuracy and found this to be high and promising for the six traits of interest. In conclusion, these results illustrated the potential of genomic selection for soybean breeding programs, but a potential limitation of this approach are the costs required for genotyping with molecular markers. Phenomic selection is an alternative approach that uses near-infrared or other spectral data for prediction instead of the marker data used for its genomic counterpart. Here, we evaluated the phenomic predictive ability in soybean as well as in triticale and maize. Phenomic prediction based on near-infrared spectroscopy (NIRS) of seeds showed a comparable or even slightly higher predictive ability than genomic prediction. Collectively, our results illustrate the potential of phenomic selection for breeding of complex traits in soybean and other crops. The advantage of this approach is that NIRS data are often available anyhow and can be generated with much lower costs than the molecular marker data, also in high-throughput required to screen the large numbers of selection candidates in breeding programs. Soybean is a short-day plant originating from temperate China, and thus adaptation to the climatic conditions of Central Europe is a major breeding goal. In this study, we established a large diversity panel of 1,503 early-maturing soybeans, comprising of European breeding material and accessions from genebanks. This panel was evaluated in six environments, which revealed valuable genetic variation that can be introgressed into our breeding programs. In addition, we deciphered the genetic architecture of the adaptation traits flowering time and maturity. Taken together, the findings of this study show the potential of several phenotypic, genomic and novel approaches that can be integrated to improve the efficiency of soybean breeding and thus hold great promise to assist the expansion of soybean cultivation in Central Europe through breeding of adapted and agronomically improved cultivars.Publication Genome-wide association mapping of molecular and physiological component traits in maize(2013) Riedelsheimer, Christian; Melchinger, Albrecht E.Genome-wide association (GWA) mapping emerged as a powerful tool to dissect complex traits in maize. Yet, most agronomic traits were found to be highly polygenic and the detected associations explained together only a small portion of the total genetic variance. Hence, the majority of genetic factors underlying many agronomically important traits are still unknown. New approaches are needed for unravelling the chain from the genes to the phenotype which is still largely unresolved for most quantitative traits in maize. Instead of further enlarging the mapping population to increase the power to detect even smaller QTL, this thesis research aims to present an alternative route by mapping not the polygenic trait of primary interest itself, but genetically correlated molecular and physiological component traits. As such components represent biological sub-processes underlying the trait of interest, they are supposed to be genetically less complex and thus, more suitable for genetic mapping. Using large diversity panels of maize inbred lines, this approach is demonstrated with (i) biomass yield by using metabolites and lipids as molecular component traits and with (ii) chilling sensitivity by using physiological component traits such as photosynthesis parameters derived from chlorophyll fluorescence measurements. In a first step, we developed a sampling and randomization scheme which allowed us to obtain metabolic and lipid profiles from large-scale field trials. Both profiles were found to be inten- sively structured reflecting their functional grouping. They also showed repeatabilities higher than in comparable profiles obtained in previous studies with the model plant Arabidopsis under controlled conditions. By applying GWAS with 56,110 SNPs to metabolites and lipids, large-scale genetic associations explaining more than 30 % of the genetic variance were detected. Confounding with structure was found to be a problem of less extent for molecular components than for agronomic traits like flowering time. The lipidome was also found to show a multilevel control architecture similar as employed in controlling complex mechanical systems. In several instances, direct links between candidate genes underlying the detected associations and agronomic traits could be established. An example is cinnamoyl-CoA reductase, a key enzyme in the lingin biosynthesis pathway. It was found to be a candidate gene underlying a major QTL found for several intermediates in the lignin biosynthesis pathways. These intemediates were in turn found to be correlated with plant height, lignin content, and dry matter yield at the end of the vegetation period. The different signs of these correlations indicated that the relationships between pathway intermediates and the final product is not simple. Directly modeling complex traits with individual component traits may therefore require consideration of feedback loops and other interdependencies. Such connections were however found difficult to be established with physiological components underlying chilling sensitivity. The main reasons for this were the weak correlations between physiological components under controlled conditions and chilling sensitivity in the field as well as high levels of genotype × environment interactions caused by the complex and environment- dependent responses of maize after perception of chilling temperatures. The approach explored in this thesis research uses component traits to gain biological insights about the genetic control of biomass yield and chilling sensitivity evaluated in diverse populations of still manageable sizes. We showed that GWAS with 56k SNPs can identify large additive effects for component traits correlated with these traits. For mapping epistatic interactions and rare variants, classical linkage mapping with biparental populations will be a reasonable complementary approach. However, controlling and modeling genotype × environment interactions remains an important issue for understanding the genetic basis of especially chilling sensitivity. If the goal is merely to predict the phenotypic value in a given set of en- vironments, black-box genomic selection methods with either SNPs, molecular profiles, or a combination of both, are very promising strategies to achieve this goal.Publication Phenotypic and genotypic evaluation of yield components and nitrogen use efficiency of triticale (× Triticosecale Wittmack)(2024) Neuweiler, Jan Eric; Würschum, TobiasModern agricultural systems require the use of mineral or organic fertilization to keep up with the growing demand for food, feed and recently also to replace fossil energy sources. One of the most important macronutrients to increase yields is nitrogen, mostly applied in its mineral form nitrate and ammonium. However, the biggest disadvantage of mineral fertilization is the good water solubility of these ions, leading to a high rate of fertilizers being leached out by strong rain falls. This results in the eutrophication of aquatic ecosystems and thus the destruction of these habitats. Further critical points are the entry of nitrates into the groundwater, evaporation of gaseous nitrogen compounds from agricultural soils and canopies as well as high energy consumption for the production of mineral nitrogen fertilizers and in result an increased emission of greenhouse gases. This has led to an increasingly restrictive legislation regulating nitrogen fertilization. The solution to resolve this contradiction, where yields should be as high as possible and fertilizer inputs as low as possible is not trivial. A big part of the solution will be the breeding of new, resource efficient cultivars producing high yields under limited nitrogen availability as well as special purpose cultivars, having a chemical grain composition and grain shape characteristics as demanded by the market. Triticale (× Triticosecale Wittmack), is a man-made small-grain cereal created by the hybridization of wheat (Triticum spp.) as female parent and rye (Secale spp.) as male parent. Triticale can be considered as a multi-purpose crop as its grain is used as animal feed and for the production of bioethanol as well as the whole plant is used as substrate for the production of biogas. Therefore, triticale can be regarded as an ideal crop to develop breeding strategies to tackle future challenges and to study the genetic basis of traits related to resource efficiency, as these results might also be transferred to other crops. In order to contribute to the solution of these challenges, the objectives of this thesis were to: (i) evaluate the genetic architecture of grain yield and grain quality related traits as well as of traits related to nitrogen use efficiency (NUE), (ii) evaluate long-term genetic trends resulting from breeding progress for traits of agronomic importance, (iii) assess the potential of index-selection to simultaneously improve negatively correlated grain yield and grain protein content, (iv) develop strategies for the identification of nitrogen efficient triticale genotypes and (v) assess the usefulness of marker-based selection techniques to improve grain yield and grain quality related traits as well as traits related to NUE in triticale by breeding. For this purpose, we used two panels of diverse genotypes representing the variation present in the European winter triticale germplasm pool. The PredBreed panel, comprising 1,218 genotypes tested in 2014 and 2015 at five locations and the SENSELGO panel, comprising 450 genotypes tested in 2018 and 2019 at four locations. Grain yield and protein content were evaluated in all field trials. In addition, grain shape characteristics were evaluated in the PredBreed panel. The SENSELGO panel was tested under four different nitrogen fertilization levels representing 40%, 70% 100% and 130% of the legal, site-specific maximum amount of nitrogen to be applied according to the latest fertilizer regulation of Germany to test their reaction on different nitrogen fertilization rates and to assess their NUE. Additionally starch content was measured. Our results show, that there is a continuous annual increase of 0.5 dt/ha for grain yield over the last decades. Moreover, we found that modern cultivars were able to make better use of the available nitrogen. This indicates, that modern cultivars have a better NUE compared to old cultivars due to their higher overall grain yield potential. Besides grain yield, quality and grain shape related traits are of great importance for the subsequent use of the harvested grain. For these traits it was found that modern cultivars tend to have bigger and more spherical grains with the potential to produce higher protein contents from the available nitrogen. To simultaneously select for negatively correlated grain yield and the most important quality related trait protein content, we evaluated different indices accounting for both traits, revealing that the sum of the standardized grain yield and protein content (IndexEW) led to the most balanced selection, whereas the index grain protein deviation (GPD) led to the selection of mostly low-yielding genotypes with a high protein content. The genetic architecture of all traits under investigation was found to be complex with many small- and medium-effect quantitative trait loci (QTL) and a high level of pleiotropy. Moreover, the analysis of the SENSELGO panel revealed a nitrogen dependent effect for some quantitative trait loci and the use of indices does not lead to a reduction in the complexity of the genetic architecture. These findings suggest that marker-assisted selection (MAS) methods only have a limited potential for the improvement of traits related to resource efficiency and grain characteristics and we therefore suggest phenotypic selection as the method of choice. By calculating the genotype-by-nitrogen interaction variance of every single genotype, it is possible to identify genotypes deviating from normal behavior. These genotypes can be selected and used as parental components to start a new breeding cycle with the aim of breeding more nitrogen-efficient cultivars. However, our results show that the overall genotype-by-nitrogen interaction variance is rather low, with highest estimates under conventional nitrogen conditions, whereas the highest yielding genotype was always different for every nitrogen fertilization level. From these results we concluded that the selection under conventional nitrogen conditions in early generations followed by trials under the nitrogen condition of the target environment is the best approach to select the highest yielding and nitrogen efficient cultivars for all environments and markets. In conclusion, the breeding of resource efficient and special purpose triticale cultivars is of utmost importance to maintain our yields on a high level and take responsibility for the environment and future generations at the same time. It is a challenging but feasible task. The genetic architecture of these traits is too complex to make successful use of MAS but phenotypic selection methods offer sufficient tools as index selection and multi-stage selection under varying nitrogen fertilization levels, to improve these traits in order to fulfill the task of using the available resources responsibly and at the same time ensuring the supply for a growing world population under more and more extreme climatic conditions.