Institut für Pflanzenzüchtung, Saatgutforschung und Populationsgenetik

Permanent URI for this collectionhttps://hohpublica.uni-hohenheim.de/handle/123456789/13

Browse

Now showing 1 - 3 of 3

Extensions of genomic prediction methods and approaches for plant breeding
(2013) Technow, Frank; Melchinger, Albrecht E.
Marker assisted selection (MAS) was a first attempt to exploit molecular marker information for selection purposes in plant breeding. The MAS approach rested on the identification of quantitative trait loci (QTL). Because of inherent shortcomings of this approach, MAS failed as a tool for improving polygenic traits, in most instances. By shifting focus from QTL identification to prediction of genetic values, a novel approach called 'genomic selection', originally suggested for breeding of dairy cattle, presents a solution to the shortcomings of MAS. In genomic selection, a training population of phenotyped and genotyped individuals is used for building the prediction model. This model uses the whole marker information simultaneously, without a preceding QTL identification step. Genetic values of selection candidates, which are only genotyped, are then predicted based on that model. Finally, the candidates are selected according their predicted genetic values. Because of its success, genomic selection completely revolutionized dairy cattle breeding. It is now on the verge of revolutionizing plant breeding, too. However, several features set apart plant breeding programs from dairy cattle breeding. Thus, the methodology has to be extended to cover typical scenarios in plant breeding. Providing such extensions to important aspects of plant breeding are the main objectives of this thesis. Single-cross hybrids are the predominant type of cultivar in maize and many other crops. Prediction of hybrid performance is of tremendous importance for identification of superior hybrids. Using genomic prediction approaches for this purpose is therefore of great interest to breeders. The conventional genomic prediction models estimate a single additive effect per marker. This was not appropriate for prediction of hybrid performance because of two reasons. (1) The parental inbred lines of single-cross hybrids are usually taken from genetically very distant germplasm groups. For example, in hybrid maize breeding in Central Europe, these are the Dent and Flint heterotic groups, separated for more than 500 years. Because of the strong divergence between the heterotic groups, it seemed necessary to estimate heterotic group specific marker effects. (2) Dominance effects are an important component of hybrid performance. They had to be included into the prediction models to capture the genetic variance between hybrids maximally. The use of different heterotic groups in hybrid breeding requires parallel breeding programs for inbred line development in each heterotic group. Increasing the training population size with lines from the opposite heterotic group was not attempted previously. Thus, a further objective of this thesis was to investigate whether an increase in the accuracy of genomic prediction can be achieved by using combined training sets. Important traits in plant breeding are characterized by binomially distributed phenotypes. Examples are germination rate, fertility rates, haploid induction rate and spontaneous chromosome doubling rate. No genomic prediction methods for such traits were available. Therefore, another objective was to provide methodological extensions for such traits. We found that incorporation of dominance effects for genomic prediction of maize hybrid performance led to considerable gains in prediction accuracy when the variance attributable to dominance effects was substantial compared to additive genetic variance. Estimation of marker effects specific to the Dent and Flint heterotic group was of less importance, at least not under the high marker densities available today. The main reason for this was the surprisingly high linkage phase consistency between Dent and Flint heterotic groups. Furthermore, combining individuals from different heterotic groups (Flint and Dent) into a single training population can result in considerable increases in prediction accuracy. Our extensions of the prediction methods to binomially distributed data yielded considerably higher prediction accuracies than approximate Gaussian methods. In conclusion, the developed extensions of prediction methods (to hybrid prediction and binomially distributed data) and approaches (training populations combining heterotic groups) can lead to considerable, cost free gains in prediction accuracy. They are therefore valuable tools for exploiting the full potential of genomic selection in plant breeding.
Identification and analysis of a transcriptome of Douglas-fir (Pseudotsuga menziesii) and population structure inference using different next-generation sequencing techniques
(2015) Müller, Thomas; Schmid, Karl J.
Predictions assume severe changes in the climatic conditions in Central Europe in the coming decades. Longer periods of drought and less precipitation during summer are expected. Plants cannot change their habitat and have to adapt to the new conditions or their offspring has to colonize new ecological niches. Due to the long generation times in trees it is important to know if and how trees can cope with the expected climatic conditions. Forest managers already give thought to the composition of future forests, because they have to choose species and populations which have no or only few problems with the changed climate. Douglas-fir (Pseudotsuga menziesii) is a promising tree species for this purpose, because it is adapted to different habitats and climate zones in its natural distribution range in North America. The two main varieties, coastal and interior Douglas-fir, differ genotypically and phenotypically, e.g. in drought tolerance. Douglas-fir trees, mainly of the coastal variety, showed good growth performances in field trials in Germany. Hence, a research project called "DougAdapt" was designed to analyze and to link genotypic and phenotypic differences in several coastal and interior Douglas-fir provenances. In this project, trees from field trials and from greenhouse experiments were sampled. To analyze the genetic diversity of the provenances we first generated reference sequences. Even with modern and cost-efficient next-generation sequencing technologies it would be very expensive to decipher the ~ 19 gigabases of the Douglas-fir genome completely. An alternative to whole genome sequencing is transcriptome sequencing, in which only the coding regions of a genome are sequenced. The transcriptome sequencing, which was performed for the first time in Douglas-fir, resulted in a large number of putative unique transcripts (PUTs). Comparisons with published transcriptomes of other plant species showed that the PUTs represented the transcriptome of Douglas-fir comprehensively. As the sampled seedlings were part of a drought stress experiment and grew under controlled conditions, we were able to identify drought related candidate PUTs, which may be part of the trees response to drought. Furthermore, more than 27,000 previously unknown single nucleotide polymorphisms (SNPs) in Douglas-fir could be identified. SNPs can influence the phenotype of individuals, and they can be used for instance as markers or to analyze genetic diversity. The analysis of genetic diversity of Douglas-fir provenances and the search for genes which may be part of local adaptation were performed with a sequence capture experiment. In sequence capture only predefined regions of a genome are sequenced. We showed that sequence capture based on PUTs as target regions is applicable in species with large and mostly unknown genomes. The polymorphic drought related candidate PUTs showed higher genetic differentiation than the remaining genes. Nevertheless, none of them was among the candidate PUTs for positive selection, which in turn are probably part of the local adaptation of the trees. Despite a high level of gene flow between coastal and interior provenances, the SNP data showed genetic differentiation between both varieties but only very low differentiation between the coastal provenances. We also investigated if genotyping-by-sequencing (GBS) is a suitable method to detect polymorphisms in Douglas-fir and compared the results of two GBS experiments with the sequence capture. The genome is digested with one or several restriction enzymes in GBS. Afterwards, only fragments with a specific length are sequenced, which considerably reduces the part of the genome that is sequenced as well as the costs. The advantage compared to sequence capture is the possibility to sample more individuals at the same time with less effort and costs. We showed that a digestion with two restriction enzymes results in more SNPs with less missing data, compared to using only one restriction enzyme. Both GBS methods returned considerably less SNPs than the sequence capture. Nevertheless, it was possible to distinguish between southern interior, northern interior, and coastal provenances using SNP data of the GBS experiments. GBS, especially with two restriction enzymes, seems to be a promising approach to genotype a large number of Douglas-fir trees and to obtain SNPs at low costs, which can be used in several tasks like genome-wide association studies. A large amount of sequence data and SNPs were analyzed in this thesis. Together with phenotypic information, these data will be crucial for the analysis of useful traits in Douglas-fir, like drought tolerance. Furthermore, the results concerning the Douglas-fir genome and the genetic diversity of different provenances will be beneficial in breeding programs and association studies, which in turn can be helpful to choose the optimal provenances for a given location.
Impacts of carbon dioxide enrichment on landrace and released Ethiopian barley (Hordeum vulgare L.) cultivars
(2021) Gardi, Mekides Woldegiorgis; Malik, Waqas Ahmed; Haussmann, Bettina I. G.
Barley (Hordeum vulgare L.) is an important food security crop due to its high-stress tolerance. This study explored the effects of CO2 enrichment (eCO2) on the growth, yield, and water-use efficiency of Ethiopian barley cultivars (15 landraces, 15 released). Cultivars were grown under two levels of CO2 concentration (400 and 550 ppm) in climate chambers, and each level was replicated three times. A significant positive effect of eCO2 enrichment was observed on plant height by 9.5 and 6.7%, vegetative biomass by 7.6 and 9.4%, and grain yield by 34.1 and 40.6% in landraces and released cultivars, respectively. The observed increment of grain yield mainly resulted from the significant positive effect of eCO2 on grain number per plant. The water-use efficiency of vegetative biomass and grain yield significantly increased by 7.9 and 33.3% in landraces, with 9.5 and 42.9% improvement in released cultivars, respectively. Pearson’s correlation analysis revealed positive relationships between grain yield and grain number (r = 0.95), harvest index (r = 0.86), and ear biomass (r = 0.85). The response of barley to eCO2 was cultivar dependent, i.e., the highest grain yield response to eCO2 was observed for Lan_15 (122.3%) and Rel_10 (140.2%). However, Lan_13, Land_14, and Rel_3 showed reduced grain yield by 16, 25, and 42%, respectively, in response to eCO2 enrichment. While the released cultivars benefited more from higher levels of CO2 in relative terms, some landraces displayed better actual values. Under future climate conditions, i.e., future CO2 concentrations, grain yield production could benefit from the promotion of landrace and released cultivars with higher grain numbers and higher levels of water-use efficiency of the grain. The superior cultivars that were identified in the present study represent valuable genetic resources for future barley breeding.

Browse

Browsing Institut für Pflanzenzüchtung, Saatgutforschung und Populationsgenetik by Classification "580"