Browsing by Subject "Molecular marker"

Now showing 1 - 7 of 7

Development and fine mapping of markers closely linked to the SCMV resistance loci Scmv1 and Scmv2 in European maize (Zea mays L.)
(2002) Dußle, Christina M.; Melchinger, Albrecht E.
Sugarcane mosaic virus (SCMV) is an important disease in European maize cultivars (Zea mays L.). Because of its non-persistent transmission by aphid vectors, it is not possible to control SCMV directly. Therefore, cultivation of resistant maize varieties is an efficient way to control SCMV infections. The overall objectives of this study were the genetic analysis of SCMV resistance in cross F7 x FAP1360A and the identification of closely linked markers to the SCMV resistance genes Scmv1 on chromosome 6 and Scmv2 on chromosome 3 for map-based cloning and marker-assisted selection (MAS). The technical objectives were to (1) identify in particular the location of Scmv1 and Scmv2 on chromosomes 3 and 6 in cross F7 x FAP1360A, (2) estimate the gene action of the alleles present at these loci, (3) enrich the SCMV resistance regions surrounding Scmv1 and Scmv2 with amplified fragment length polymorphism (AFLP) and simple sequence repeat (SSR) markers by applying a modified targeted bulked segregant analysis, tBSA, (4) convert AFLP markers into codominant, simple PCR-based markers as a tool for MAS and map-based cloning of Scmv1 and Scmv2 and, (5) assess resistance gene analogues (RGAs) as potential candidate genes for Scmv1 and Scmv2. Quantitative trait loci (QTL) mapping SSR markers revealed the presence of two QTL on chromosome 6 (Scmv1a and Scmv1b) and one QTL on chromosome 3 (Scmv2). tBSA identified 24 AFLP and 25 SSR markers adjacent to either Scmv1 or Scmv2. AFLP marker E35M62-1, closely linked to Scmv1 on chromosome 6, was successfully converted into an indel marker. For chromosome 3, AFLP marker E33M61-2 was converted into a CAPS marker. Both converted AFLP markers mapped to the same chromosome region as their original AFLP markers. Development of CAPS of the RGAs and mapping in relation to SCMV resistance genes Scmv1 and Scmv2 identified pic19 and pic13 as potential candidates for these resistance genes. In this study, useful markers were developed for applications in MAS. Because inheritance of SCMV resistance is strongly affected by the environment, MAS enables the selection of resistant individuals independently of field experiments. Furthermore, MAS can assist breeders to identify resistant individuals before flowering and to pyramid resistance genes in elite inbred lines. Another benefit of these closely linked markers is their application for map-based cloning. Final evidence, whether there are one or more genes clustered on chromosomes 3 and 6, conferring resistance against SCMV, can only be solved after cloning these genes.
Evaluation of alternative statistical methods for genomic selection for quantitative traits in hybrid maize
(2012) Schulz-Streeck, Torben; Piepho, Hans-Peter
The efficacy of several contending approaches for Genomic selection (GS) were tested using different simulation and empirical maize breeding datasets. Here, GS is viewed as a general approach, incorporating all the different stages from the phenotypic analysis of the raw data to the marker-based prediction of the breeding values. The overall goal of this study was to develop and comparatively evaluate different approaches for accurately predicting genomic breeding values in GS. In particular, the specific objectives were to: (1) Develop different approaches for using information from analyses preceding the marker-based prediction of breeding values for GS. (2) Extend and/or suggest efficient implementations of statistical methods used at the marker-based prediction stage of GS, with a special focus on improving the predictive accuracy of GS in maize breeding. (3) Compare different approaches to reliably evaluate and compare methods for GS. An important step in the analyses preceding the marker-based prediction is the phenotypic analysis stage. One way of combining phenotypic analysis and marker-based prediction into a single stage analysis is presented. However, a stagewise analysis is typically computationally more efficient than a single stage analysis. Several different weighting schemes for minimizing information loss in stagewise analyses are therefore proposed and explored. It is demonstrated that orthogonalizing the adjusted means before submitting them to the next stage is the most efficient way within the set of weighting schemes considered. Furthermore, when using stagewise approaches, it may suffice to omit the marker information until the very last stage, if the marker-by-environment interaction has only a minor influence, as was found to be the case for the datasets considered in this thesis. It is also important to ensure that genotypic and phenotypic data for GS are of sufficiently high-quality. This can be achieved by using appropriate field trial designs and carrying out adequate quality controls to detect and eliminate observations deemed to be outlying based on various diagnostic tools. Moreover, it is shown that pre-selection of markers is less likely to be of high practical relevance to GS in most cases. Furthermore, the use of semivariograms to select models with the greatest strength of support in the data for GS is proposed and explored. It is shown that several different theoretical semivariogram models were all well supported by an example dataset and no single model was selected as being clearly the best. Several methods and extensions of GS methods have been proposed for marker-based prediction in GS. Their predictive accuracies were similar to that of the widely used ridge regression best linear unbiased prediction method (RR-BLUP). It is thus concluded that RR-BLUP, spatial methods, machine learning methods, such as componentwise boosting, and regularized regression methods, such as elastic net and ridge regression, have comparable performance and can therefore all be routinely used for GS for quantitative traits in maize breeding. Accounting for environment-specific or population-specific marker effects had only minor influence on predictive accuracy contrary to findings of several other studies. However, accuracy varied markedly among populations, with some populations showing surprisingly very low levels of accuracy. Combining different populations prior to marker-based prediction improved prediction accuracy compared to doing separate population-specific analyses. Moreover, polygenetic effects can be added to the RR-BLUP model to capture genetic variance not captured by the markers. However, doing so yielded minor improvements, especially for high marker densities. To relax the assumption of homogenous variance of markers, the RR-BLUP method was extended to accommodate heterogeneous marker variances but this had negligible influence on the predictive accuracy of GS for a simulated dataset. The widely used information-theoretic model selection criterion, namely the Akaike information criterion (AIC), ranked models in terms of their predictive accuracies similar to cross-validation in the majority of cases. But further tests would be required to definitively determine whether the computationally more demanding cross-validation may be substituted with the more efficient model selection criteria, such as AIC, without much loss of accuracy. Overall, a stagewise analysis, in which the markers are omitted until at the very last stage, is recommended for GS for the tested datasets. The particular method used for marker-based prediction from the set of those currently in use is of minor importance. Hence, the widely used and thoroughly tested RR-BLUP method would seem adequate for GS for most practical purposes, because it is easy to implement using widely available software packages for mixed models and it is computationally efficient.
Genetic diversity in elite lines and landraces of CIMMYT spring bread wheat and hybrid performance of crosses among elite germplasm
(2005) Dreisigacker, Susanne; Melchinger, Albrecht E.
Wheat (Triticum aestivum) is one of the major cereals in the world. During the past years, the world consumption of wheat increased up to nearly 600 million tones, whereas wheat production continuously decreased. Due to land limitations, new production gains must be achieved from improved plant management systems as well as from the development of high yielding varieties. The International Maize and Wheat Improvement Center (CIMMYT) employs different strategies to enhance yield potential in wheat especially for developing countries. For instance, the wheat breeding program focuses on defined mega-environments (MEs), assuming similar growing conditions in certain countries. In the search for useful alleles, breeders often turn back to wild relatives of wheat stored in the CIMMYT gene bank. With the production of synthetic hexaploid bread wheat (SHWs), characteristics from T. durum and T. tauschii can be combined and via backcrossing incorporated into modern breeding materials. Wheat landraces (LCs) are an additional reservoir of resistances to pests and diseases as well as for environmental adaptation. The production of wheat hybrids is seen as a further option to improve yield potential. A considerable amount of genetic diversity among the materials is a prerequisite for all strategies. Due to the worldwide importance of CIMMYT wheat varieties, they represent a suitable source to examine different breeding strategies in wheat. The main objective of our research was to determine the genetic diversity in modern wheat breeding materials and genetic resources at CIMMYT. Specific research questions were: (i) Is the systematic breeding targeted for different MEs reflected in the genetic diversity among breeding lines (Experiment 1)? (ii) Does the production of SHWs (Experiment 2) and the use of LCs (Experiment 3) enhance the genetic variation in modern breeding materials? (iii) Does the development of hybrids represent an option to improve yield potential in wheat? (iv) Is it possible to predict levels of heterosis with the determination of genetic distance (GD) among hybrid parents? (v) Do genomic and EST- derived SSRs differ in the measurement of genetic diversity (Experiments 1 and 3)? (vi) Are GD values based on SSRs correlated with the coefficient of parentage (COP) (Experiments 1 to 4)? In Experiment 1, a total of 68 CIMMYT advanced breeding lines was analyzed with 99 SSRs, of which 51 were EST- and 46 genomic derived SSRs. A high level of genetic diversity (GD = 0.41) was observed among the breeding lines. The majority of variation (91%) was detected among lines targeted to one specific ME, which indicates a broad genetic base of the current CIMMYT breeding materials. Principal coordinate analysis (PCoA) could clearly separate the lines, but they clustered independently from their target MEs. Main explanations are: (i) alleles were selected that provide fitness to several MEs, (ii) adaptation depends only on a small number of genes that were not detected with the SSRs applied, or (iii) too few cycles of selection were considered to separate the germplasm. In Experiment 2, a total of 11 SHWs, 7 recurrent parent lines, and 13 families of backcross-derived lines (SBLs) were analyzed with 90 SSRs. The SHWs clustered far from the SBLs and the recurrent parents in the cluster analyses and PCoA, and formed a distinct germplasm pool with high allelic variation. Two families of SBLs were tested for a selective advantage of the SHW alleles. Six SSRs revealed non-Mendelian inheritance, indicating that the genomic region of SHWs was actively selected for. Thus, the production of SHWs provides a promising approach for the enhancement of genetic variation in modern breeding materials. In Experiment 3, gene bank accessions of 36 LCs from different countries and a total of 119 accessions from nine LCs populations collected in Turkey and Mexico were analysed with 44 and 76 SSRs, respectively. Both LC materials revealed high allelic variation (GD = 0.69 and 0.54). The 36 LC accessions could not be separated according to their continent of origin. An unexpected relationship was observed between the Chilean LC ?Trigo africano? and the Nigerian LCs ?Dikwa?. All of the nine LC populations could be discriminated except for two Turkish LCs collected from the same location. In accordance with previous studies, considerable genetic variation was observed within the LC populations. Our results contributed a lot to the characterisation of the LCs and generated important knowledge for the management of seed bank accessions. In Experiment 4, a total of 112 wheat hybrids and their 22 parental lines were evaluated at two locations in Mexico for grain yield, plant height, days to flowering and maturity. The level of heterosis varied between -15.3% and 14.1%, but was generally too low to compensate for the high costs of hybrid seed production. The correlations between mid-parent values and hybrid performance, as well as between parental line per se performance and general combining ability were significant (P < 0.01) for all traits, and particularly high for grain yield (r = 0.86 and 0.91). PCoA based on 113 SSR markers revealed three groups of parents. However, the correlations of GDs and COPs with the values of heterosis were negative and not significant. Thus, the prospects of large-scale cultivation of hybrid wheat in developing countries are low. The correlations between GDs and COP in Experiments 1 and 3 were generally significant but low. This can be explained by unrealistic assumptions in the calculation of COPs, which ignore the effects of selection and genetic drift. Similarly to genomic SSRs, EST-SSRs did not reflect functional diversity. The latter revealed lower degrees of polymorphism than genomic SSRs in all experiments, but the allele designation was simpler and more reliable. Across all experiments, our study demonstrates that plant breeding does not inevitably lead to a loss of genetic diversity. We confirmed that CIMMYT?s breeding strategies contributed to a successful increase in genetic variation. These results provide useful information to wheat breeders in CIMMYT and other national programs, regarding the use of wild relatives and landraces for the enhancement of the genetic base of wheat germplasm. In addition, our research provides a base of knowledge for future association studies, identification of useful alleles, and their use in marker-assisted selection.
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.
Molecular and agronomic assessment of genetic diversity and hybrid breeding in triticale
(2006) Tams, Swenja H.; Melchinger, Albrecht E.
Knowledge of the genetic diversity of a species is of paramount importance for the choice of crossing parents in line and hybrid breeding. Genetic distance (GD) estimates based on molecular markers proved to be well suited for direct exploration of the relationship within a germplasm pool. Triticale hybrid breeding and heterosis have received increasing attention in recent years. Hybrid seed production is highly attractive for autogamous species because of the built-in variety protection of hybrids in comparison to line varieties. The main objective was to appraise the prospect of hybrid breeding in European winter triticale and develop time- and cost-reducing strategies. In particular, the main objectives were to (i) assess and compare genetic diversity estimates in European winter triticale elite germplasm based on molecular markers and pedigree data, (ii) determine hybrid performance and heterosis in multiple environments, and (iii) evaluate prediction methods for hybrid performance and heterosis to support future hybrid breeding programs. Average coancestry coefficient between all pairs of the 128 European elite genotypes was low (f = 0.059) due to scanty information available for the majority of the varieties and breeding lines. Better estimates of genetic distance of triticale genotypes were obtained by molecular marker assessment with 93 simple sequence repeat (SSR) markers and 10 PstI/TaqI primer combinations of amplified fragment length polymorphism (AFLP) markers. While SSR markers have been developed in wheat and rye and are mapped in the genome, the location and distribution of AFLP markers is unknown. Both marker systems resulted in reliable genetic diversity estimates. The moderate correlation between genetic distance estimate (GD) of SSR and AFLP marker analyses (GDSSR; GDAFLP) corresponded with other studies. Cluster analysis and principle coordinate analysis revealed no clear separation of germplasm groups. Supported by a bootstrap analysis, it was concluded that both marker systems provide consistent information for germplasm identification. The lack of grouping is in concordance with the breeding history of triticale as a self-pollinator, the wide adaptation of the inter-generic species and the single end-use purpose. Simultaneously to the marker assessment, 209 F1 hybrids were produced by a chemical hybridizing agent. The hybrids and their parents (57 females and five testers) were evaluated in field trials in six environments in Germany during the season 2001-2002. A combined analysis revealed significant heterosis for all eight traits. The level of mid-parent heterosis was positive for grain yield, 1000-kernel weight, number of kernels per spike, test weight and plant height and negative for number of spikes per m², falling number and protein concentration. Forty-six of the hybrids outyielded modern varieties, which were included as checks, by 10% and more. This aspect is important for the success of hybrids on the market for commercial production. Results regarding hybrid performance, heterosis, GCA/SCA relationship, trait correlation in hybrids and parents and aspects regarding cost-effective high quality F1 seed production appear to be sufficiently positive to encourage further work on hybrid breeding. Approaches to reduce time and costs for the identification of superior parental combinations and the prediction of hybrid performance revealed no reliable method yet. Correlations between SCA and GD of parents based on the different marker systems were low for all traits, which hampers prediction. Grouping of germplasm based on GD estimates or on heterotic response of the hybrids could not be discovered in triticale. As a consequence, a first step for an optimum allocation of resources in commercial hybrid breeding programs is the development of heterotic groups. In the present study, several females have been sub-grouped according to their heterotic response and SCA for grain yield with two tester pairs. Following the early history of hybrid breeding in maize, a multi-stage procedure was suggested for triticale to evaluate and expand the sub-grouping and enhance heterosis among groups.
Molecular and genetic analyses of aggressiveness in Fusarium graminearum populations and variation for Fusarium head blight resistance in durum wheat
(2011) Talas, Firas; Miedaner, Thomas
Fusarium head blight (FHB) is a devastating disease of wheat, barley and other cereals, which affects all wheat-growing areas of the world. The most prevalent species are Fusarium graminearum Schwabe (teleomorph: Gibberella zeae (Schweinitz) Petch) and Fusarium culmorum (W. G. Smith) Saccardo. Wheat breeding for FHB resistance has become the most effective and cost efficient strategy to combat this disease. Assisting long term stable breeding programs need a better understanding of the biology and dynamic changes of the population structure. Deoxyninalenol (DON) has the most economical impact among the other mycotoxin secreted by this fungus. Several chemotypes characterizes F. graminearum isolates. All chemotypes (3-ADON, 15-ADON, and NIV) were detected in Europe. The prevalent chemotype in Germany and UK is 15-ADON. Population structure is the result of evolutionary forces acting on the population in time and space together with mutation, recombination, and migration enhancing the genetic variance of a population, random drift and the selection reducing it. Aggressiveness in F. graminearum denotes the quantity of disease induced by a pathogenic isolate on a susceptible host in a non-race specific pathosystem, and is measured quantitatively. The quantitative traits such as aggressiveness and DON production mirror both the environmental changes and the genetic variation. Several genes are responsible for DON production; majority of these genes are grouped in TRI5 cluster. Few genes are known to be associated with F. graminearum aggressiveness such as MAP kinase genes, RAS2, and TRI14. Association between single nucleotide polymorphism and genetic variation of aggressiveness and DON production traits provide a clear identification of quantitative participation of different SNPs in expressing the trait. Also, this approach provides a good method to test the association between candidate genes and the traits. The objectives of this research were to (1) screen some durum wheat landraces for FHB resistance; (2) determine the genetic and chemotypic structure of natural population of F. graminearum in Germany; (3) determine the phenotypic variation in Aggressiveness and DON production, which come out one farmer wheat field; (4) compare the phenotypic variation and genetic variation occurring in one wheat field; and (5) associate the phenotypic traits with SNPs in candidate genes. Screening for FHB resistance was performed on sixty-eight entries form the Syrian landraces. The main characters of selection for resisting FHB disease are low mean value of infection and stability in different environments. Four genotypes (ICDW95842, ICDW92330, ICDW96165, Chahba) had small mean FHB value, small value of deviation form regression, and regression coefficient close to zero. These genotypes were considered as candidate resistant sources of FHB for further agronomic performance analysis through backcrossing generation. The causal agent of FHB in Germany is F. graminearum s.s. with a dominating rate of 64.9 % (out of 521 Fusarium spp. isolates). Nonetheless, the three chemotypes were detected in Germany and some times within one wheat field. The 15-ADON chemotype dominated the populations of F. graminearum s.s. in Germany followed by 3-ADON then NIV chemotype (92, 6.8, and 1.2%, respectively). High genetic diversity (Nei?s gene diversity ranged form 0.30 to 0.58) was detected on a single wheat field scale. Analysis of molecular variance (AMOVA) revealed a higher variance within populations (71.2%) than among populations (28.8%). Populations of F. graminearum s.s. in Germany display a tremendous genetic variation on a local scale with a restricted diversity among populations. Surprisingly the phenotypic variation of aggressiveness and DON production revealed a similar partitioning scale as the genetic variation. In other words, analyses of variance (ANOVA) revealed a higher variance within populations (72%) than between (28%) populations. The wide spectrum of aggressiveness (i.e., from 18 to 39%) and DON production (from 0.3 to 23 mg kg-1) within single wheat field simulate the global variation in both traits. Consequently, associating the observed variation of aggressiveness and DON production with detected single nucleotide polymorphism (SNPs) in some candidate genes revealed few but significant associations. According to Bonferroni-Holm adjustment, three SNPs were associated significantly with the aggressiveness, two in MetAP1 and one in Erf2 with explained proportions of genotypic variance (pG) of 25.6%, 0.5%, and 13.1%, respectively. One SNP in TRI1 was significantly associated with DON content on TRI1 (pG=4.4). The rapid decay of the LD facilitate a better high resolution of the association approach and is in turn suggest the need of higher number of SNP marker to facilitate a genome wide association study. The linkage disequilibrium between unlinked genes suggests the involvement of these genes in the same biosynthesis network. In conclusion, building wheat breeding program for FHB resistance depend initially on identifying sources of resistance among wheat varieties or wild relatives. Moreover, understanding the population structure of the pathogen and the selection forces causing genetic alteration of the population structure enable us employ a sufficient increase of the host resistance. Keeping such a balanced equilibrium between increasing host resistance and changes occur in genetic structure of F. graminearum population would insure no application of additional selection pressure. Further association of candidate genes with aggressiveness can provide effective information of the population development. Continuous observation of Fusarium population?s development is needed to insure a stable management of Fusarium head blight disease.
Prediction of hybrid performance in maize using molecular markers
(2008) Schrag, Tobias; Melchinger, Albrecht E.
Maize breeders develop a large number of inbred lines in each breeding cycle, but, owing to resource constraints, evaluate only a small proportion of all possible crosses among these lines in field trials. Therefore, predicting the performance of hybrids by utilising the data available from related crosses to identify untested but promising hybrids is extremely important. The objectives of this thesis research were to develop and evaluate methods for marker-based prediction of hybrid performance (HP) in unbalanced data as typically generated in commercial maize hybrid breeding programs. For HP prediction, a promising approach uses the sum of effects across quantitative trait loci (QTL) as predictor. However, comparison of this approach with established prediction methods based on general combining ability (GCA) was lacking. In addition, prediction of specific combining ability (SCA) is also possible with this approach, but was so far not used for HP prediction. The objectives of the first study in this thesis were to identify QTL for grain yield and grain dry matter content, combine GCA with marker-based SCA estimates for HP prediction, and compare marker-based prediction with established methods. Hybrids from four Dent × Flint factorial mating experiments were evaluated in field trials and their parental inbreds were genotyped with amplified fragment length polymorphism (AFLP) markers. Efficiency for prediction of hybrids, of which both parents were testcross evaluated (Type 2), was assessed by leave-one-out cross-validation. The established GCA-based method predicted HP better than the approach exclusively based on markers. However, with greater relevance of SCA, combining GCA with marker-based SCA estimates was superior compared with HP prediction based on GCA only. Linkage disequilibrium between markers was expected to reduce the prediction efficiency due to inflated QTL effects and reduced power. Thus, in the second study, multiple linear regression (MLR) with forward selection was employed for HP prediction. In addition, adjacent markers in strong linkage disequilibrium were combined into haplotype blocks. An approach based on total effects of associated markers (TEAM) was developed for multi-allelic haplotype blocks. Genome scans to search for significant QTL involve multiple testing of many markers, which increases the rate of false-positive associations. Thus, the TEAM approach was enhanced by controlling the false discovery rate. Considerable loss of marker information can be caused by few missing observations, if the prediction method depends on complete marker data. Therefore, the TEAM approach was improved to cope with missing marker observations. Modification of the cross-validation procedure reflected, that often only a subset of parental lines is crossed with all lines from the opposite heterotic group in a factorial mating design. The prediction approaches were evaluated with the same field data as in the previous study. The results suggested that with haplotype blocks instead of original marker data, similar or higher efficiencies for HP prediction can be achieved. Marker-based HP prediction of inter-group crosses between lines, which were marker genotyped but not testcross evaluated, was not investigated hitherto. Heterosis, which considerably contributes to maize grain yield, was so far not incorporated into marker-based HP prediction. Combined analyses of field trials from multiple experiments of a breeding program provide valuable data for HP prediction. With a mixed linear model analysis of such unbalanced data from nine factorial mating experiments, best linear unbiased prediction (BLUP) values for HP, GCA, SCA, line per se performance, and heterosis of 400 hybrids were obtained in the third study. The prediction efficiency was assessed in cross-validation for prediction of hybrids, of which none (Type 0) or one (Type 1) parental inbred was testcross evaluated. An extension of the established HP prediction method based on BLUP of GCA and SCA, but not using marker data, resulted in prediction efficiency intermediate for Type 1 and very low for Type 0 hybrids. Combining line per se with marker-based heterosis estimates (TEAM-LM) mostly resulted in the highest prediction efficiencies of grain yield and grain dry matter content for both Type 0 and Type 1 hybrids. For the heterotic trait grain yield, the highest prediction efficiencies were generally obtained with marker-based TEAM approaches. In conclusion, this thesis research provided methods for the marker-based prediction of HP. The experimental results suggested that marker-based HP prediction is an efficient tool which supports the selection of superior hybrids and has great potential to accelerate commercial hybrid breeding programs in a very cost-effective manner. The significance of marker-based HP prediction is further enhanced by recent advances in production of doubled haploid lines and high-throughput technologies for rapid and inexpensive marker assays.