Browsing by Subject "Populationsgenetik"

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Development and applications of Plabsoft : a computer program for population genetic data analyses and simulations in plant breeding
(2008) Maurer, Hans Peter; Melchinger, Albrecht E.
Marker-assisted breeding approaches are promising tools for enhancement of the conventional plant breeding process. They have been successfully applied in many areas such as plant variety protection, classification of germplasm, assessment of genetic diversity, mapping of genes underlying important agronomic traits, and using the mapping information for selection decisions. Powerful and flexible bioinformatic tools are urgently required for a better integration of molecular marker applications and classical plant breeding methods. The objective of my thesis work was to develop and apply Plabsoft, a computer program for population genetic data analyses and simulations in plant breeding. The assumption of Hardy-Weinberg equilibrium is a cornerstone of many concepts in population and quantitative genetics. Therefore, tests for Hardy-Weinberg equilibrium are of crucial importance, but the assumptions underlying asymptotic chi-square tests are often not met in datasets from plant breeding programs. I developed and implemented in Plabsoft a new algorithm for exact tests of Hardy-Weinberg equilibrium with multiple alleles. The newly derived algorithm has considerable computational advantages over previously described algorithms and extends substantially the range of problems that can be tested. Knowledge about the amount and distribution of linkage disequilibrium (LD) in breeding populations is of fundamental importance to assess the prospects for gene mapping with whole-genome association studies. To analyze LD in breeding populations, I implemented various LD measures in Plabsoft and developed a new significance test for these LD measures. The routines were employed to analyze LD in 497 elite maize lines from a commercial hybrid breeding program, which were fingerprinted by 81 simple sequence repeat (SSR) markers covering the entire genome. Strong LD was detected and, therefore, whole-genome association studies were recommended as promising. However, LD between unlinked loci will most likely result in a high rate of false positives. The prediction of hybrid performance with DNA markers facilitates the identification of superior hybrids. The single marker models used so far do not take into account the correlation between allele frequencies at linked markers. To overcome this problem, the concept of haplotype blocks was proposed. I developed and implemented in Plabsoft three alternative algorithms for haplotype block detection suitable for plant breeding. The algorithms were applied for the haplotype-based prediction of the hybrid performance of 270 hybrids, the parents of which were fingerprinted with 20 amplified fragment length polymorphism (AFLP) primer combinations. Employing haplotypes resulted in an improved prediction of hybrid performance compared with single marker models. Consequently, haplotype-based prediction methods have a high potential to improve substantially the efficiency of hybrid breeding programs. Computer simulations can be employed to solve population genetic problems in plant breeding, for which the simplifying assumptions underlying the classical population genetic theory do not hold true. However, before the start of my thesis no flexible simulation software was available. I developed algorithms for simulation of single breeding steps and entire plant breeding programs and implemented these in Plabsoft. The routines allow the simulation of plant breeding programs as they are conducted in practice. The simulation routines of Plabsoft were validated by simulating two marker-assisted backcross programs in rice conducted by the International Rice Research Institute (IRRI). In the simulations, the frequency distributions of the proportion of recurrent parent genome in the backcross populations were assessed. The simulation results were in good agreement with the experimental data. Therefore, computer simulations are a useful tool for pre-test estimation of selection response in marker-assisted backcrossing. The application of Plabsoft was exemplified by two studies in maize. In the first study, the expected LD decay in the intermating generations of two recurrent selections programs was determined with simulations. This application demonstrates the use of Plabsoft to solve problems for which analytical results are not available. In the second study, the forces generating and maintaining LD in a hybrid maize breeding program were investigated with computer simulations. This application demonstrates the capability of modeling complex long-term breeding programs as performed in practice. The studies of my thesis provide an example for the broad range of possible applications of Plabsoft. In addition to the presented studies, Plabsoft has so far been employed in about 40 further studies, which corroborates the usefulness of Plabsoft for integrating new genomic tools in applied plant breeding programs.
European population genomic differentiation and dispersal pattern of the invasive beetle Anoplophora glabripennis
(2023) Häussermann, Iris Hanna; Hasselmann, Martin
Anthropogenic activities (e.g. homogenized habitats, trade) are the main factors to facilitate the increasing rates of invasive alien species. In this study, the invasion of the Asian long-horned beetle (Anoplophora glabripennis) was examined. Its native distribution is eastern Asia (China, Korean peninsula), but by extensive trade, this beetle was introduced via wood packing materials to North-America (1996) and Europe (2001). ALB attacks healthy broadleaved trees (e.g. Acer spp., Salix spp., Populus spp.), which can become lethal due to larval feeding. This study aims to detect genetic differences and kinship between the European infestation sites in Germany, Switzerland and Italy, from which the introduction and dispersal patterns can be deviated. Therefore, mitochondrial (mt) DNA-markers of the Cytochrome oxidase subunits I and II genes (COI and II) were used (ch. A and B, Sanger sequencing), as well as genome wide single nucleotide polymorphisms (SNPs), which were obtained by a Genotype-by-sequencing (GBS) approach (ch. C, Illumina sequencing). The results of this population genomic study of invasive European ALB populations showed very complex introduction patterns into Europe including multiple independent introductions characterized by the high population structure between the European infestation sites and some cases of human mediated secondary dispersal.
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.
Optimizing the prediction of genotypic values accounting for spatial trend andpopulation structure
(2010) Müller, Bettina Ulrike; Piepho, Hans-Peter
Different effects, like the design of the field trial, agricultural practice, competition between neighboured plots, climate as well as the spatial trend, have an influence on the non-genotypic variation of the genotype. This effects influence the prediction of the genotypic value by the non-genotypic variation. The error, which results from the influence of the non-genotypic variation, can be separated from the phenotypic value by field design and statistical models. The integration of different information, like spatial trend or marker, can lead to an improved prediction of genotypic values. The present work consists of four studies from the area of plant breeding and crop science, in which the prediction of the genotypic values was optimized with inclusion of the above mentioned aspects. Goals of the work were: (1) to compare the different spatial models and to find one model, which is applicable as routine in plant breeding analysis, (2) to optimize the analysis of unreplicated trials of plant breeding experiments by improving the allocation of replicated check genotypes, (3) to improve the analysis of intercropping experiments by using spatial models and to detect the neighbour effect between the different cultivars, and (4) to optimize the calculation of the genome-wide error rate in association mapping experiments by using an approach which regards the population structure. Different spatial models and a baseline model, which reflects the randomization of the field trial, were compared in three of the four studies. In one study the models were compared on basis of different efficiency criteria with the goal to find a model, which is applicable as routine in plant breeding experiments. In the second study the different spatial models and the baseline model were compared on unreplicated trials, which are used in the early generation of the plant breeding process. Adjacent to the comparison of the models in this study different designs were compared with the goal to see if a non-systematic allocation of check genotypes is more preferable than a systematic allocation of check genotypes. In the third study these different models were tested for intercropping experiments. In this study it should be tested, if an improvement is expectable for these non randomized or restricted randomized trials by using a spatial analysis. The results of the three studies are that no spatial model could be found, which is preferable over all other spatial models. In a lot of cases the baseline model, which regards only the randomization, but no spatial trend, was better than the spatial models, also for the restricted or non-randomized intercropping trials. In all three studies the basic principle was followed to start first with the baseline model, which is based on the randomization theory, and then to extend it by spatial trend, if the model fit can be improved. In the second study the systematic and non-systematic allocation of check plots in unreplicated trials were compared to solve the question if a non-systematic allocation leads to more efficient estimates of genotypes as the systematic allocation. The non-systematic allocation of check plots led to an unbiased estimation in three of four uniformity trials. As well as in the third study an analysis was done, if the border plots of the different cultivars are influenced by the neighboured cultivar and if there are significant differences to the inner plot. The position of the cultivars, border plot or inner plot, had a significant influence of the yield. If maize was cultivated adjacent to pea, the yield of the border plot of maize was much higher than the inner plot of maize. When wheat was cultivated behind maize, there were no significant differences in the yield, if the plot was a border plot or inner plot. In addition to optimizing the field design for unreplicated trials and the extension of the models by spatial trend the marker information was integrated in a fourth study. An approach was proposed in this study, which calculates the genome wide error for association mapping experiments and accounts for the population structure. Advantages of this approach in contrast to previously published approaches are that the approach on the one hand is not too conservative and on the other hand accounts the population structure. The adherence of the genome wide error rate was tested on three datasets, which were provided by different plant breeding companies. The results of these studies, which were obtained in this thesis, show that by the different extensions, like integration of spatial trend and marker information, and modifications of the field design, an improved prediction of the genotypic values can be achieved.
Pedigreeanalysen zur Beschreibung der populations- und quantitativgenetischen Situation von baden-württembergischen Lokalrinderrassen
(2014) Hartwig, Sonja; Bennewitz, Jörn
The challenge of a conservation breeding program is to solve a conflict of goals: genetic variability and genetic autonomy should be maintained, and on time a certain amount of breeding progress has to be realized to ensure the ability to compete. The aim of the present study was to analyse the situation concerning the targets mentioned above for traditional cattle breeds of Baden-Württemberg. Furthermore, methods for the consolidation and development of these breeds should be reconsidered. In chapter 1 the organisation of a breeding program for small cattle breeds is discussed. The challenge of such a program is the conservation of agrobiodiversity, culture and traditions and the progress of traditional local breeds. Number and extend of these breeds declined due to the increasing popularity of high-yielding breeds. Additionally, some of the local breeds are used in different branches of production compared to their original usage. Breeding programs have to be fitted. The establishment of individual adapted breeding methods is required for a sophisticated solution of the conflict mentioned above. Federal support is requested. Nowadays the implementation of genomic selection is not yet practicable for small breeds. But future opportunities should be analysed. The establishment of performance tests concerning breed specific product and efforts is demanded to improve these characteristics. In the following genetic variability of Vorderwald, Hinterwald and Limpurg cattle was examined. In chapter 2 for each breed two reference populations were defined that enable to observe the development over the years. Animals within the reference population comply with restrictions concerning racial origin and completeness of pedigree. Effective population size and the effective number of founders, and ancestors were estimated. The interpretation of the results was done with regard to the history of the breeds. The absolute population size of Vorderwald cattle is the biggest one. The number of Hinterwald cattle is intermediate; Limpurg cattle have the smallest population size. Whereas the management of Hinterwald cattle seemed to maintain genetic variability, the management of Vorderwald cattle was not that target-orientated. With an effective population size greater than 100 there is enough genetic variability within Vorderwald and Hinterwald. In contrast the values of Limpurg cattle are too low. Besides genetic variability, genetic autonomy and breeding progress are the targets of a conservation breeding program. Cross-breeding was carried out to mitigate the risk of inbreeding depression and to improve the performance of local breeds. However, breeding activities for local breeds were not as intensive and target oriented as for popular high yielding breeds. While the gap between the performance of high-yielding and local breeds increase, genetic autonomy of local breeds declined due to migrant influences. Chapter 3 examined the importance of migrant breed influences for the realization of breeding progress of beef traits of Vorderwald and Hinterwald cattle. The results show that there is a high amount of migrant contributions and their effects on performance are substantial for most traits. Breeding values adjusted for the effects of the migrant breeds showed little genetic trend for beef traits. The subject of chapter 4 is the development of milk yield and the associated migrant influences. Yield deviations for milk, fat, and protein content were analysed. Migrant contributions to Vorderwald cattle were high and even rose in the latest past. All the effects of foreign breeds were positive and in most cases highly significant. Most influential breed was Montbéliard. The influences of migrant breeds were substantial for the development of milk performance. However, the trend of milk yield traits for both breeds was positive even without foreign breeds’ influences. In comparison the number of analysed Hinterwald cows was small due to the reason that just a few Hinterwald husbandries take part at the official milk performance recording. Migrant breed contributions were moderate and nearly constant over the time. The most influential migrant breed was the Vorderwald cattle. The development of milk yield shows a flat trend. Influences of migrant breeds were low. The thesis ends with a general discussion.
Population genomics of herbicide resistance in Alopecurus myosuroides
(2022) Kersten, Sonja; Schmid, Karl J.
Over the past 50 years, herbicides have often replaced mechanical and manual human weed control, thus representing a major factor in yield productivity in modern agriculture. Herbicide applications, however, exert strong selection pressures on weeds. As a consequence, these species have developed herbicide resistance through adaptive, beneficial alleles that increase in number to ensure the persistence of the populations, a phenomenon known as evolutionary rescue. A major research question is whether herbicide resistance adaptation is more likely to arise from standing genetic variation that was present before the onset of herbicide selection or from de novo mutations that arose after herbicide selection began. To address this question, I focused on target-site resistance (TSR) point mutations, which cause a lower binding affinity to the target protein of the respective herbicides. I first investigated the diversity of TSR haplotypes in populations of the grass species Alopecurus myosuroides (common name: blackgrass), and compared it with the TSR diversity outcome of simulated populations under both evolutionary scenarios. I first conducted a population genetics study of A. myosuroides, which is the most problematic weed in winter cereals across the European continent due to rapid resistance evolution. To obtain genome-wide polymorphic markers, I adapted a restriction site-associated DNA sequencing protocol to this species. I began by analyzing the diversity and population structure in a smaller local South German collection. The fact that I could differentiate populations on a local scale motivated me to extend the study to a European-wide collection, in which I found clear population structure, albeit with low differentiation and some evidence for admixture across Europe. In addition, I generated highly accurate long-read amplicons from single individuals of two loci, ACETYL-COA CARBOXYLASE (ACCase) and ACETOLACTATE SYNTHASE (ALS), which are the targets of the two main herbicide modes of action used in European cereal crops. I obtained completely phased haplotype information, supporting the analysis of haplotype diversity on a population level. I found a remarkable diversity of beneficial TSR mutations at the field level arising from multiple haplotypes of independent origin, so called soft sweeps. I used this information to perform forward simulations to investigate the evolutionary origin of these mutations. I found evidence that a majority of resistance mutations originated from standing genetic variation. While this at first may appear surprising, it is consistent with very large census and effective population sizes in blackgrass. Since long-read amplicon sequencing of single individuals could be costly and time consuming, I extended the analysis to pools of 150 to 200 individuals from Germany, Belgium, France, the Netherlands and the United Kingdom. By combining the power of a more stringent accuracy criterion in our long-reads and a novel clustering software (PacBio amplicon analysis), I was able to preserve individual haplotype information in pooled samples. Furthermore, in a proof of concept experiment, I was able to recover in our pools most haplotypes previously sequenced in individuals. The amplicon study provides a versatile workflow that can be easily adapted to any gene of interest in different species. In conclusion, I found that many A. myosuroides populations likely already have the genetic prerequisites not only for rapid evolution of resistance to currently used herbicides, but also to herbicides that have not yet been brought to market.
Quantitativ-genetische Untersuchungen zur Vererbung der Resistenz gegen Ährenfusarium bei Triticale (x Triticosecale Wittmack)
(2004) Heinrich, Nicole; Miedaner, Thomas
Fusarium head blight (FHB), caused by Fusarium culmorum (W.G. Smith) Sacc. and F. graminearum Schwabe, is recognized as one of the most destructive diseases of small-grain cereals. Fusarium infection can cause substantial yield losses. Infected grain may also be contaminated by mycotoxins that are harmful to humans and livestock. Agronomical measures and fungicides are only partly effective in controlling FHB. The development of disease-resistant cultivars together with appropriate crop management practices are effective strategies to control FHB. In this study, seven triticale cultivars and three breeding strains, representing a range of FHB resistances, their 45 diallel F1 crosses, progenies of 15 F2s from a six-parent diallel and their 30 backcrosses (BC, 15 to each parent), and five F2:3 bulks were investigated. Parents and their progenies were grown in several environments (years, locations) and tested for FHB resistance after artificial inoculation with Fusarium culmorum. Within the scope of this study, three experiments were conducted to estimate various quantitative-genetic parameters of several traits. In Experiment 1, the influence of FHB on yield-related traits of the ten parents was assessed. Compared to a non-inoculated variant, Fusarium reduced 1000-grain weight by 10.0%, spike weight by 9.3%, the number of kernels per spike by 4.3%, and test weight by 7.4%. Inoculation also increased deoxynivalenol (DON, 26.4 mg kg-1) and exoantigen (1.34 OD). content of the kernels. Genotypic variation and genotype-environment interaction were significant for all traits. The correlation between symptom ratings (spikes, kernels) and yield traits and between spike weight and kernels per spike were negative and high. The aim of Experiment 2 was to estimate combining ability, hybrid performance and heterosis for FHB ratings, DON and exoantigen content. Heterosis of FHB for spike and kernel rating was small. Across environments, the DON content in F1 crosses, however, was 15.5% higher than their mid-parent value. A high and significant (P = 0.01) correlation of r = 0.8 was found for both spike and kernel FHB symptom ratings between mid-parent and F1 performance. Except for exoantigen content, the general combining ability (GCA) was the main source of variation, suggesting additive gene effects for FHB resistance. Significant specific combining ability variance implies non-additive types of allelic interaction also. Therefore, in some crosses dominant effects can play an important role. The relationship between the GCA effect of a parent and its per se performance was close. In Experiment 3, genetic variation and effects for FHB resistance were estimated in segregating generations. The resistance level of the parents and their F2 progenies were similar. In contrast, the resistance of the BC progenies to the resistant parent was considerably higher than that of the backcrosses to the susceptible parent. Significant differences between the means of the 15 crosses and a high genetic variation within crosses were observed. Transgression could not be detected. F2:3 bulks and their parents had a comparable resistance level. For F2 and BC progenies, the additive effect was more important than the dominant effect. In contrast, the F1 crosses had a higher dominant effect, but with a large error. The study revealed considerable genetic variation in all generations for FHB resistance that can be exploited in a breeding programme. The mainly additive genetic effect makes it possible to select crossing parents on the basis of their per se performance. Due to the importance of genotype-environment interaction, resistance tests in various environments are strongly recommended. Screening for FHB resistance can best be accomplished by assessing symptom ratings of spikes and/or the spike weight relative to a non-inoculated variant. The high cross-environment interaction variance in the F2 generation points to the problem of selecting in unreplicated segregating material. Selection should be postponed to the F3 or later generations. The large genetic variation of FHB resistance and the preponderance of additive gene effects are encouraging to further increase resistance in triticale by recurrent selection.