Institut für Pflanzenzüchtung, Saatgutforschung und Populationsgenetik

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Application of Near-Infrared Spectroscopy in Plant Breeding Programs
(2006) Montes, Juan Manuel; Melchinger, Albrecht E.
The success of plant breeding programs depends on the availability of genetic variation and efficient data collection processes that allow large-scale screenings of genotypes. When genetic variation is present, the goal is to identify those genotypes that are closest to the breeding objectives. In this context, the evaluation of a large number of genotypes requires optimization of the data collection process in order to provide reliable information for making selection decisions. The process of data collection must yield an accurate and precise assessment of genotypes timely because the information is needed to plan the next generation for breeding and cultivar development. Laboratory NIRS is routinely used in the data collection process of many breeding programs, but it requires the withdrawal of field plot samples and involves manual work. Applications of the near-infrared spectroscopy on choppers (NOC) and near-infrared spectroscopy on combine harvester (NOCH) are a step forward to the automation of data collection processes, by which sampling, labor, and sources of error in the data can be reduced. The objective of this thesis research was to assess the potential of NOC and NOCH for application in breeding programs of grain maize, rapeseed, and silage maize. Plot combine harvesters and choppers were equipped with diode-array spectrometers for collection of near-infrared plot spectra, and used to harvest experimental varieties of breeding programs in Central Europe. Two alternative sample presentation designs (conveyor belt and spout) were used for the NOC systems. The NOCH systems used the conveyor belt as sample presentation design. NOCH showed a high potential for determination of dry matter (DM), crude protein (CP), and starch (ST) contents of maize grain. NOCH calibration models yielded standard errors of prediction (SEP) and coefficients of determination of validation (R2V) of 1.2% and 0.95 for DM, 0.3% and 0.88 for CP, and 1.0% and 0.79 for ST, respectively. The potential of NOCH for determination of DM, CP, oil and glucosinolate contents of rapeseed was also high. NOCH calibration models yielded standard errors of cross validation (SECV) and coefficients of determination of cross validation (R2CV) of 0.3% and 0.96 for DM, 0.6% and 0.69 for CP, 0.9% and 0.71 for oil, and 2.2 μmol/g and 0.40 for glucosinolate, respectively. The NOC systems showed high potential for the determination of DM, ST, and soluble sugars (SS) content of silage maize hybrids. The NOC system equipped with a conveyor belt design yielded calibration models with SEP and R2V of 0.9% and 0.93 for DM, and 2.1% and 0.78 for ST, respectively. For the NOC system equipped with the spout design, the SEP and R2V amounted to 1.4% and 0.84 for DM, 2.3% and 0.75 for ST, and 0.9% and 0.81 for SS. The potential of both NOC systems for determination of fiber contents (CF, ADF, and NDF), digestibility and energy-related traits was lower than for DM, ST, and SS. The precision of NOCH for the determination of DM content in maize grain was higher than by traditional drying-oven method. A higher precision of NOCH is also expected for other traits and may also be extended to the NOC systems because the sampling error associated with traditional processes of data collection is reduced drastically by NOC and NOCH. The investigation of the effects caused by the calibration technique, mathematical transformation of the near-infrared spectra, and scatter correction on the development of NOCH calibration models for the prediction of DM, CP, and ST content in maize grain revealed that calibration technique was the most important factor affecting the prediction ability, whereas the importance of mathematical transformation and scatter correction depended on the particular constituent considered. Presently, there exists high uncertainty about the optimal NOC and NOCH sample presentation designs for agricultural harvesters. The dynamic signal range, i.e., the range of spectral values on which predictions are based, and the amount of plot material measured were identified as guide parameters for optimization of sample presentation designs. In addition, calibration transferability between NOC systems with different sample presentation designs proved to be feasible after merging spectra from both NOC systems in the calibration set. In conclusion, NOC and NOCH show high potential for replacing laboratory NIRS analysis of several traits in a plant breeding context and yield a more accurate and precise evaluation of field plot characteristics. Therefore, technological applications of the electromagnetic radiation is predicted to have a high impact in plant breeding, precision farming, and agriculture.
Assessing the Genetic Diversity in Crops with Molecular Markers: Theory and Experimental Results with CIMMYT Wheat and Maize Elite Germplasm and Genetic Resources
(2004) Reif, Jochen Christoph; Melchinger, Albrecht E.
Genetic diversity is a valuable natural resource and plays a key role in future breeding progress. Germplasm collections as a source of genetic diversity must be well-characterized for an efficient management and effective exploitation. The advent of PCR-based molecular markers such as sim-ple sequence repeats (SSRs) has created an opportunity for fine-scale genetic characterization of germplasm collections. The objective of this research was to optimize the utilization of genetic re-sources conserved at the International Wheat and Maize Improvement Center (CIMMYT), with the aid of DNA markers. Choice of suitable dissimilarity measures is important to facilitate the interpretation of findings from DNA marker studies on a theoretically sound basis. The objective of a theoretical study was to examine 10 dissimilarity coefficients widely used in germplasm surveys, with special focus on applications in plant breeding and seed banks. The distance and Euclidean properties of the dissimi-larity coefficients were investigated as well as the underlying genetic models. Application areas for different coefficients were suggested on the basis of the theoretical findings. It has been claimed that plant breeding reduces genetic diversity in elite germplasm, which could seriously jeopardize the continued ability to improve crops. The objectives of the presented ex-perimental study with wheat were to examine the loss of genetic diversity during (i) domestication of the species, (ii) change from traditional landrace cultivars (LC) to modern breeding varieties, and (iii) intensive selection over 50 years of international breeding. A sample of 253 CIMMYT or CIMMYT-related modern wheat cultivars, LC, and Triticum tauschii accessions were characterized with up to 90 SSR markers covering the entire wheat genome. A loss of genetic diversity was ob-served from T. tauschii to LC and from LC to the elite breeding germplasm. Wheat genetic diver-sity was narrowed from 1950 to 1989, but was enhanced from 1990 to 1997. The results indicate that breeders averted the narrowing of the wheat germplasm base and subsequently increased the genetic diversity through the introgression of novel materials. The LC and T. tauschii contain nu-merous unique alleles that were absent in modern wheat cultivars. Consequently, both LC and T. tauschii represent useful sources for broadening the genetic base of elite wheat breeding germ-plasm. In the 1980's, CIMMYT generated more than 100 maize populations and pools but little is known about the genetic diversity of this germplasm. The objective of the study with 23 CIMMYT maize populations was to characterize their population genetic structure with SSRs. The populations adapted to tropical, subtropical intermediate-maturity, subtropical early-maturity, and temperate mega-environments (ME) were fingerprinted with 83 SSR markers. Estimates of genetic differen-tiation between populations revealed that most of the molecular variation was found within the populations. Principal coordinate analysis based on allele frequencies of the populations revealed that populations adapted to the same ME clustered together and, thus, supported clearly the ME structure. Novel strategies were suggested to optimize the conservation of the genetic diversity within and among the populations. Heterotic groups and patterns are of fundamental importance in hybrid breeding. The objective of the presented study with a subset of 20 out of the 23 maize populations was to investigate the rela-tionship between heterosis and genetic distance determined with SSR markers. The published data of three diallels and one factorial trial evaluated for grain yield were re-analyzed to calculate het-erosis in population hybrids. Correlations of squared modified Rogers distance and heterosis were mostly positive and significant, but adaption problems caused deviations in some cases. For popu-lations adapted to the target regions, genetic distance can be used as a further criterion in the search for promising heterotic patterns and groups. For intermediate- and early-maturity subtropical germ-plasm, two heterotic groups were suggested, consisting of a flint and dent composite. For the tropi-cal germplasm, it was possible to assign population (Pop29) to the established heterotic group A and propose new heterotic groups (Pop25, Pop43). Our experimental results corroborate that SSRs are a powerful tool to (i) detect relationships among different germplasm, (ii) assess the level of genetic diversity present in germplasm pools and its flux over time, and (iii) search for promising heterotic groups for hybrid breeding in complementa-tion to field trials.
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.
Assessment of phenotypic, genomic and novel approaches for soybean breeding in Central Europe
(2022) Zhu, Xintian; Würschum, Tobias
Soybean 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.
Association analysis of genes controlling variation of flowering time in West and Central African sorghum
(2012) Bhosale, Sankalp; Melchinger, Albrecht E.
Sorghum is extremely important for the food security in the arid to semi-arid regions of West and Central Africa (WCA). A serious constraint to the sorghum production in WCA is the scattered beginning but relatively fixed end of the rainy season among years, forcing farmers to adjust their individual sowing dates according to the start of the rains. Owing to the delayed sowing and fixed end of the rainy season, farmers require varieties that flower at the end of the rainy season, regardless of the sowing date. Photoperiod sensitivity of sorghum accessions is an important adaptation trait that allows flowering or synchronized flowering of the accessions at the end of the rainy season. This is also particularly important in avoiding grain mold, insect and bird damages for early maturing varieties, and incomplete grain filling due to soil water shortage occurring at the end of the season in late maturing varieties. Cultivars with photoperiod sensitivity may have the potential to increase yield and yield stability. Unfortunately, in WCA most of the present day cultivars are photoperiod insensitive. Furthermore, unavailability of simple screening methods in selecting photoperiod sensitive cultivars complicates the situation. Breeding techniques such as marker assisted selection (MAS) by employment of molecular markers would greatly enhance the selection efficiency for this major adaptation trait. Candidate-gene (CG) based association studies can assist in investigating the effect of polymorphisms in flowering time genes on phenotypic variation. Allele-specific molecular markers can be developed after a significant marker-phenotype association is identified. These markers can effectively be used in MAS of photoperiod sensitive sorghum cultivars. In this study we carried out a CG based association analysis to investigate the association between variation for photoperiodic sensitivity of flowering time in sorghum and polymorphisms in six partially amplified genes putatively related to variation in flowering time. Five out of six CGs were known to be involved in photoperiod pathway of flowering time [CRYPTOCHROME 1 (CRY1-b1), CRYPTOCHROME 2 (CRY2), LATE ELONGATED HYPOCOTYL (LHY), GIGANTEA (GI), HEADING DATE 6 (HD6)], and the gene SbD8 was involved in the gibberellic acid (GA) pathway of flowering time. In the first part of the study we determined the presence, the expression and the molecular diversity of genes homologous to the important flowering time gene D8 in maize on a set of 26 sorghum and 20 pearl millet accessions. Homologs of D8 were successfully amplified and tested for their expression in sorghum (SbD8) and pearl millet (PgD8). Pearl millet, because of its autogamous nature, showed higher nucleotide diversity than sorghum, which is an allogamous species. In maize, a 6 bp deletion flanking the SH2-like domain of D8 was found to be significantly associated with flowering by Thornsberry et al. (2001). We found in the PgD8 gene a 3 bp insertion or deletion (Indel) flanking the SH2 domain in the region, which was only conserved between D8 and PgD8. Cluster analysis performed for the D8, SbD8, and PgD8 indicated that maize is more closely related to pearl millet than sorghum. These findings suggest that, similar to maize, the indel in PgD8 flanking the SH2 domain might play an important role in determination of flowering. It is advisable to carry out an association study to reveal the potential role of PgD8 in flowering time control in pearl millet. After successfully amplifying and confirming the expression of SbD8 and PgD8, we carried out the association analysis on the selected CGs. A panel of 219 mostly inbred accessions of sorghum from major sorghum growing areas in WCA was complied. In the second part of the study the association analysis panel of accessions was phenotyped for their flowering response in the field in 2007 in Mali. The entire panel was sown twice (June and July), photoperiod response index (PRI) was estimated as the difference between DFL50% of the two sowing dates of the accessions. The PRI of the accessions showed a wide range from close to zero (photoperiod-insensitive) up to values close to 30 or above (highly-photoperiod sensitive). This result confirmed that the range of response based on the choice of the accessions was appropriate for an association analysis. The plant height reduction observed in accessions sown in July compared to the once sown in June was in accordance with previous studies performed in West African sorghum varieties. The sorghum accessions were genotyped using 27 simple sequence repeat markers. Population structure analysis using software STRUCTURE was carried out to control the false positives in the association analysis. The results showed existence of two subgroups in our sorghum accessions. The first subgroup included mainly race guinea (83%) originating from western West African countries such as Mali and Bukina Faso and the second subgroup included accessions mainly from Nigeria and Niger and also accessions originating from other countries and other major races. The race guinea could clearly be distinguished from the other races. Fisher's exact test for the presence of earliness among subgroups showed that there are significantly (p = 0.06) more early maturing accessions in subgroup one than subgroup two. But there was an absence of a clear structuring pattern. The study suggests that the race, the geographical origin, and maturity of the accessions are the most likely forces behind the observed structuring pattern of the accessions. We found a high level of genetic diversity among the sorghum accessions. Race guinea was found to be the most diverse and race kaura was the least diverse. In general, the estimates of the gene diversity were comparable to previous studies. The results showed that clustering of early-intermediate maturing guinea varieties may have increased the linkage disequilibrium (LD) in subgroup one compared to subgroup two. The differences in the extent of LD between our study and those in the previous studies can be due to the differences in the molecular markers used as well as differences in the racial composition of the accessions studied. In the final part of the study the association analysis was carried out using a mixed-model method. This method takes both population structure and kinship information into account. The candidate genes polymorphism data were obtained by amplifying and sequencing of the chosen genes. The association analysis for the polymorphism found within the CGs was carried out using values of PRI for each accession. From the six genes studied, genes CRY1-b1 and GI had several polymorphic sites which were significantly (p < 0.005) associated with PRI variation in the sorghum panel. The most important polymorphism in the gene CRY1-b1 showed an effect on PRI value of up to -4.2 days. This single nucleotide polymorphism (SNP) at position 722 in CRY1-b1 was located in the flavin adenine dinucleotide binding domain (N-terminal domain) of SbCRY1; hence, this domain appears to be important in photomorphogenesis in sorghum. In the case of the GI gene homolog, SNP888 had the largest effect on PRI of about +8 days. Similar to the studies in rice, the GI gene delayed flowering under June sowing (long-day conditons) and shortened the time to flower in sorghum under July sowing (short-day conditons). Therefore, the action of the GI gene homolog in sorghum might be revealed by a detailed investigation of GI by comparison of sorghum accessions grown under short-day and long-day conditions. In the case of gene SbD8, no significant association with PRI could be found; hence, the potential involvement of this gene in flowering time control of sorghum was not confirmed. Negative Tajima?s D values, of CGs indicated that the genes may have been subjected to adaptive selection as variation in flowering time may confer adaptive advantages in sorghum. The results showed that CG-based association analysis using a mixed model approach can be successfully applied to unravel the genetic variation related to phenotypic variation in flowering time. The polymorphisms significantly associated with PRI can be used to develop cleaved amplified polymorphic sequence markers. Functional markers could also be created directly from the significant SNPs. These molecular markers can serve as powerful tools in MAS for sorghum to identify cultivars sensitive to photoperiod.
Biometrical Analyses of Epistasis and the Relationship between Line per se and Testcross Performance of Agronomic Traits in Elite Populations of European Maize (Zea mays L.)
(2005) Mihaljevic, Renata; Melchinger, Albrecht E.
Relations of yield and other important agronomic traits of inbred lines to the same traits in hybrids have been studied from the time of initiation of hybrid breeding to the present. Because crossing lines to a tester and conducting yield trials are expensive and time-consuming, reliable information on inbred lines that is indicative of their testcross performance is crucial for optimum testing schemes in hybrid breeding as well as simultaneous improvement of commercial hybrids and their inbred parents. It has therefore been of great importance to determine the magnitude of correlation between line per se performance (LP) and testcross performance (TP) and investigate if epistasis influences this correlation. The comprehensive study on hand was performed with five populations (F3 to F6 lines) differing in size (ranging from 71 to 344), level of inbreeding, and the number of common parents. The populations employed were derived from three biparental crosses within the heterotic pool of European elite flint maize (Zea mays L.). All five populations were evaluated for TP (using an unrelated dent tester inbred) of five agronomically important quantitative traits: grain yield, grain moisture, kernel weight, protein concentration, and plant height. Four of these populations were also evaluated for LP of the same five traits. The objectives were to (i) estimate phenotypic and genotypic correlations between LP and TP within four populations for all five traits, (ii) map quantitative trait loci (QTL) for LP and TP in four and five populations, respectively, for all five traits, (iii) validate estimated QTL effects and positions for TP by assessing QTL congruency among testcross populations differing in size and genetic background, (iv) determine the value of LP-QTL for the prediction of TP, (v) estimate the importance of epistatic effects for LP and TP of grain yield and grain moisture by generation means analysis as well as genome-wide testing for epistatic marker pairs, and (vi) draw conclusions regarding the prospects of marker-assisted selection (MAS). Genotypic correlations between LP and TP, rg(LP, TP), estimated herein were comparable with those obtained for European flint or U.S. dent material. The magnitude of rg(LP, TP) was trait-specific: for traits of high heritability, i.e. grain moisture, kernel weight, protein concentration, and plant height, estimates were generally larger than 0.7 across all four populations, whereas for grain yield, estimates were consistently lower and did not exceed the intermediate level of 0.5. For grain yield, lowest rg(LP, TP) were estimated with lowest precision (largest confidence intervals). This requires testing for both LP and TP and/or combining the data in a selection index to ensure sufficient inbred performance (seed production) and yield improvement. However, combined selection for LP and TP proved less efficient than sole selection for TP unless unadapted material was employed. For kernel weight, protein concentration, and plant height, we detected "large" congruent QTL across testcross populations derived from the same cross, which individually explained up to 46% of the validated genotypic variance p. However, as the p values estimated from validation were still below the corresponding heritability estimates, MAS will be superior to phenotypic selection only if it is more cost-efficient. For the above traits, similar numbers of QTL for LP and TP were detected across populations. More than half of the QTL regions detected for LP were in common for LP and TP in the largest population (N = 280). To assess the value of QTL identified for LP in predicting TP, we calculated the genotypic correlation rg(MLP, YTP). This parameter assesses QTL congruency for LP and TP quantitatively and is thus the key parameter for assessing the prospects of MAS. The number of common QTL for LP and TP (qualitative QTL congruency) was generally not indicative of the magnitude of rg(MLP, YTP) due to the differences in the effect size of the respective QTL detected for LP and used for the prediction of TP. For all traits, rg(MLP, YTP) were smaller than rg(LP, TP). This is because rg(MLP, YTP) is only predictive for the validated proportion of genotypic variance explained by the QTL for LP, which was generally below 50% because of the limited power of QTL detection, in particular with small sample sizes below 100. Only if QTL detected for LP explain a substantial proportion of the genotypic variance, MAS based on these QTL can be applied, provided it is more cost-efficient than an indirect phenotypic selection for TP based on LP. QTL detection power was drastically reduced for the complex trait grain yield with a presumably large number of small QTL underlying its genetic architecture. Thus, the number of common QTL for LP and TP as well as the QTL congruency across testcross populations was much lower for grain yield than the other four traits. Estimated gene action of QTL detected for LP was primarily additive for grain yield. Evidence for dominance and/or epistasis, which may be a reason for the low rg(LP, TP) and the low number of common QTL for LP and TP was generally weak. Both generation means analysis for LP and TP and genome-wide search for epistatic marker pairs yielded no evidence for epistasis. This is not only because the detected epistatic effects could not be validated, but also because there is low chance to find epistasis unless the generation examined displays the full epistatic variance such as expected from doubled haploids produced from an F1 cross. Thus, it is anticipated that the relative importance of epistatic effects in hybrid maize breeding may strongly increase with the currently happening shift in line development from recurrent selfing towards the production of doubled haploids.
Bridging genomics and genetic diversity
association between sequence polymorphism and trait variation in a spring barley collection
(2009) Haseneyer, Grit; Geiger, Hartwig H.
Association analysis has become common praxis in plant genetics for high-resolution mapping of quantitative trait loci (QTL), validating candidate genes, and identifying important alleles for crop improvement. In the present study the feasibility of association mapping in barley is investigated by associating DNA polymorphisms in selected candidate genes with variation in grain quality traits, plant height, and flowering time to gain further understanding of gene functions involved in the control of these traits. (1) As a starting point a worldwide collection of spring barley (Hordeum vulgare L.) accessions has been established to serve as an association platform for the present and possible further studies. This collection of 224 accessions, sampled from the IPK genebank, consists of 109 European, 45 West Asian and North African, 40 East Asian and 30 American entries. Forty-five EST derived polymorphic SSRs were used to determine the genetic structure. The markers were equally distributed over all seven chromosomes. Phenotypic data were assessed in field experiments performed at three locations in 2004 and 2005 in Germany. (2) Seven candidate genes were considered. Fragments of these genes were amplified and sequenced in the established collection. Single nucleotide polymorphisms (SNPs), haplotype variants, and linkage disequilibrium (LD) were investigated. (3) One gene was additionally analysed in 42 bread wheat (Triticum aestivum L.) accessions in order to compare barley and wheat for nucleotide diversity and LD. (4) Association analysis between SNPs and haplotype variants of the selected candidate genes and the phenotypic variation in thousand-grain weight, crude protein content, starch content, plant height, and flowering time was used to identify candidate genes influencing the variation of these traits in spring barley. A mixed model association-mapping method was employed for this purpose. In the established collection, significant genotypic variation was observed for all traits under study. Genotype×environment interaction variances were much smaller than the genotypic variances and heritability coefficients exceeded 0.9. Statistical analyses of population stratification revealed two major subgroups, mainly comprising two-rowed and six-rowed accessions, respectively. Within the sequenced fragments (13kb) of the seven candidate genes, 216 polymorphic sites and 93 haplotypes were detected demonstrating a moderate to high level of nucleotide and haplotype diversity in the germplasm collection. Most haplotypes (74.2%) occurred at a low frequency (<0.05) and therefore were rejected in the candidate gene-based association analysis. Pair-wise LD estimates between the detected SNPs revealed different intra-gene linkage patterns. The 45 SSR markers used for analysing the population structure revealed low intra- and interchromosomal LD (r²<0.2). Significant marker-trait associations between the candidate genes and the respective target traits were identified. The barley and wheat genes showed a high level of nucleotide identity (>95%) in the coding sequences, the distribution of polymorphisms was also similar in the two species, and both map to a syntenic position on chromosome 3. However, the genes were different in both collections with respect to LD and Tajima?s D statistic. In the barley collection only a moderate level of LD was observed whereas in wheat, LD was absolute between polymorphic sites located in the first intron while it decayed by distance between the former sites and those located downstream the first intron. Differences in Tajima?s D values indicate a lower selection pressure on the gene in barley than in wheat. In conclusion, the established association platform represents an excellent resource for marker-trait association studies. The germplasm collection displays a wide range of genotypic and phenotypic diversity providing phenotypic data for economically important traits and comprehensive information about the nucleotide and haplotype polymorphism of seven candidate genes. Association results demonstrate that the candidate gene-based approach of association mapping is an appropriate tool for characterising gene loci that have a significant impact on plant development and grain quality in spring barley.
Characterization and management of Jatropha curcas L. germplasm
(2018) Senger, Elisa; Melchinger, Albrecht E.
Jatropha curcas L. (jatropha) is a perennial plant of the Euphorbiaceae family that grows in the tropics and subtropics worldwide. Jatropha is targeted to be grown in marginal environments. The seeds are used mainly for production of food products and bioenergy, amongst others. Jatropha breeding is at an early stage. The first obstacle is to generate competitive cultivars for economically feasible cultivation. Mayor breeding objectives are to increase seed yield and yield stability, to decrease production costs, and to improve product quality adapted to specific markets. Jatropha breeding needs to be optimized in several research areas, such as methods and tools for germplasm characterization and breeding techniques, while considering requirements of the agronomic management and product processing. The germplasm can be separated into two naturally occurring germplasm pools that differ in the presence of phorbol esters (PE). These chemical compounds have antinutritional effects on humans and animals and cannot be inactivated or eliminated from the plant material on an industrial scale yet. Therefore, food production is based on cultivars lacking PE, while bioenergy production is less affected from PE presence. The germplasm needs to be characterized and grouped depending on breeding objectives and strategies. Tools for identification of plants that synthesize PE exist, but bear decisive disadvantages or need to be advanced. These tools are exploited for germplasm management and food safety strategies. The objectives of this study were to i) examine the variation of relevant traits among genotypes and between germplasm pools, ii) estimate phenotypic and genotypic trait correlations, iii) investigate location effects and genotype by environment interactions, iv) investigate parental and heterotic effects of genotypes from different germplasm pools as well as the effect of the mating type on expression of relevant traits, and v) develop recommendations for implementation of the findings in jatropha breeding programs. In the first two publications, stress response was investigated. Leaf chlorophyll content (SPAD) was used as a dynamic trait that can be influenced by e.g. water stress and nutrient deficiency. Different genotypes were screened at several locations and at different time points. High genetic diversity was found not only in stress response but also in SPAD value. The fast and non-destructive method is highly promising to be applied in further screenings or stress response studies. In the second publication, genotypic differences in aluminum tolerance were found among seedlings in a greenhouse trial. The rapid test method is applicable in further screenings. However, it needs to be proven that aluminum tolerance at the seedling stage observed under greenhouse conditions is expressed also at later plant developmental stages in the field. In the consecutive three publications, several traits were assessed on seeds and seedlings to detect significant differences between genotypes and/or between germplasm pools. Such traits would be highly valuable for germplasm management. We found that random variation is a disadvantage of quantitative traits and hinders clear assignment of each experimental unit to the respective germplasm pool. Thus, qualitative traits might be favored, such as the “silver shimmer inside the seed testa” that differentiated toxic from non-toxic seeds with a low error rate. However, these results need to be validated. Another application area of the investigated traits is the identification of self-fertilized material within hybrid progeny. In our study, self-fertilized seeds could be differentiated from cross-fertilized ones in specific genotype combinations. Similarly, many seedling traits showed heterotic effects. In the sixth publication, genotype by environment interactions were investigated and recommendations for breeding programs elaborated. A large set of genotypes was grown for four years at three different locations. We showed that selection at only one testing location is highly risky because cultivars with low yield stability could be selected. Therefore, it is indispensable for breeders to work in a network of testing locations that differ in edapho-climatic conditions and apply appropriate experimental designs and statistical tools. In the final publication, several parameters related to the nutritional value of kernels of non-toxic genotypes grown at two locations were assessed. The high nutritional value of this material was presented and compared to soybean, peanut, hazelnut, and corn. Furthermore, preliminary conclusions related to location effects and product processing were drawn. The findings of this thesis contribute to characterization of this novel crop with regard to stress tolerances, seed and seedling characteristics as well as food quality, and help to increase breeding efficiency by presenting simple methods for fast genotype screening as well as grouping of germplasm and by efficient exploitation of testing facilities.
Characterization of genetic variation among Ethiopian barley (Hoerdeum vulgare L.) genotypes
(2019) Abtew, Wosene Gebreselassie; Knierim, Andrea
Barley (Hordeum vulgare L.) is a major cereal crop in Ethiopia and accounts for 8% of the total cereal production based on cultivation area. Farmers may face unpredictable rainfall and drought stress patterns such as terminal drought where rainfall ends before crops have completed their physiological maturity, which then poses a challenge to crop production. The absence of efficient weather forecasts and a lack of efficient communication channels for resource-poor farmers ask for the development of varieties that are robust to such irregularities. A goal of plant breeding for areas with variable climate and limited resources for agricultural inputs is to produce stable varieties with higher average yield across diverse environments and growing conditions. Genotype by environment (G x E) interactions, however, frequently interfere with the selection of widely adapted genotypes. Knowledge about the yield stability of existing Ethiopian barley varieties and landraces under changing environmental variables is important for the future development of barley varieties with high and stable yields. In addition, yield components are quantitative with substantial influence of environment. Yield components also compensate each other in trait correlation dynamics. Since grain yield is a more complex trait than its components, environmental effects and genotype-by-environment (G x E) interactions for grain yield are stronger than for its components. Therefore, indirect selection of yield components may be more efficient than selection on grain yield per se to obtain higher yielding and stable cultivars. A study, therefore, was initiated to 1) characterize the response of a diverse set of barley genotypes to different locations and variable planting dates and identify genotypes with wide adaptation and stable performance and/or genotypes with specific altitude and planting date 2) determine traits that contribute to high and stable yields across a range of different environments and planting dates 3) determine the pattern of population structure and genetic parameters among genotypes conserved in Ethiopian and German gene banks in for different period of time as well as currently growing in farmers’ field. In order to meet the objectives 18 genotypes were tested at four different sowing dates with 15 days interval in different locations (Ambo and Jimma) and years (2012 and 2013). The tested genotypes revealed a wide variation for both static and dynamic yield stability measures. Compared to improved cultivars, farmers landraces displayed higher average static stability and similar superiority indices (dynamic stability). These landraces are therefore a source of germplasm for breeding resilient barley cultivars. Staggered planting proved to be a useful method for evaluating genotype stability across environmental factors beyond location and season. In addition, we also noticed that compensatory relationship between kernels per spike and thousand kernel weight in landraces. Kernels per spike and number of fertile tillers can be proposed as robust traits in barley breeding for a wider adaptation as they had significant and consistent positive total effects on grain yield. In order to determine the pattern of population structure and genetic parameters among genotypes of different origin and gene banks, DNA samples were subject to double-digest by ApeK1 and Hind III enzymes. After sequencing, raw read was checked for major quality parameters. Sequence reads were then filtered for sequencing artifacts and low quality reads (preprocessing). The pre-processed reads were aligned to genome of barley cultivar Morex to call SNPs. Values of observed heterozygosity (Ho) ranged from 0.250 to 0.337 and were higher than the expected heterozygosity (He) that varied from 0.180 to 0.242 in genotypes of all origins. The inbreeding coefficient (FIS) values that ranged between -0.240 and -0.639 across the regions were also higher and negative suggesting existence of excess outcrossing than expected. Based on the inferred clusters by the ADMIXTURE, high Fst values were observed between clusters suggesting high genetic differentiation among the genotypes tested though differentiation was not based on location. In addition, genetic differentiation computed based on the predetermined location, altitude and source of genotypes suggested weak differentiation among the groups. These results indicate that, in Ethiopia, barley genetic variation between regions and altitudes were less pronounced than within region and altitude variations. This calls for the germplasm collection strategies to be cautious in considering location and altitude as a main factor of variation thus strategies should focus on exploiting the within region variation also for better germplasm conservation and utilization. The static yield stability of landrace has to be utilized by breeders for their wider recommendations for those farmers who cannot afford use of farm inputs and specific cultivars. In addition, the relative robustness as well as plasticity of traits sorted by the current study can be incorporated in the breeding strategy of barley in Ethiopia.
Comparison of omics technologies for hybrid prediction
(2019) Westhues, Matthias; Melchinger, Albrecht E.
One of the great challenges for plant breeders is dealing with the vast number of putative candidates, which cannot be tested exhaustively in multi-environment field trials. Using pedigree records helped breeders narrowing down the number of candidates substantially. With pedigree information, only a subset of candidates need to be subjected to exhaustive tests of their phenotype whereas the phenotype of the majority of untested relatives is inferred from their common pedigree. A caveat of pedigree information is its inability to capture Mendelian sampling and to accurately reflect relationships among individuals. This shortcoming was mitigated with the advent of marker assays covering regions harboring causal quantitative trait loci. Today, the prediction of untested candidates using information from genomic markers, called genomic prediction, is a routine procedure in larger plant breeding companies. Genomic prediction has revolutionized the prediction of traits with complex genetic architecture but, just as pedigree, cannot properly capture physiological epistasis, referring to complex interactions among genes and endophenotypes, such as RNA, proteins and metabolites. Given their intermediate position in the genotype-phenotype cascade, endophenotypes are expected to represent some of the information missing from the genome, thereby potentially improving predictive abilities. In a first study we explored the ability of several predictor types to forecast genetic values for complex agronomic traits recorded on maize hybrids. Pedigree and genomic information were included as the benchmark for evaluating the merit of metabolites and gene expression data in genetic value prediction. Metabolites, sampled from maize plants grown in field trials, were poor predictors for all traits. Conversely, root-metabolites, grown under controlled conditions, were moderate to competitive predictors for the traits fat as well as dry matter yield. Gene expression data outperformed other individual predictors for the prediction of genetic values for protein and the economically most relevant trait dry matter yield. A genome-wide association study suggested that gene expression data integrated SNP interactions. This might explain the superior performance of this predictor type in the prediction of protein and dry matter yield. Small RNAs were probed for their potential as predictors, given their involvement in transcriptional, post-transcriptional and post-translational regulation. Regardless of the trait, small RNAs could not outperform other predictors. Combinations of predictors did not considerably improve the predictive ability of the best single predictor for any trait but improved the stability of their performance across traits. By assigning different weights to each predictor, we evaluated each predictors optimal contribution for attaining maximum predictive ability. This approach revealed that pedigree, genomic information and gene expression data contribute equally when maximizing predictive ability for grain dry matter content. When attempting to maximize predictive ability for grain yield, pedigree information was superfluous. For genotypes having only genomic information, gene expression data were imputed by using genotypes having both, genomic as well as gene expression data. Previously, this single-step prediction framework was only used for qualitative predictors. Our study revealed that this framework can be employed for improving the cost-effectiveness of quantitative endophenotypes in hybrid prediction. We hope that these studies will further promote exploring endophenotypes as additional predictor types in breeding.
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.
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.
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.
Dissection of the genetic architecture of stalk mechanical strength and in vivo haploid induction in maize
(2016) Hu, Haixiao; Melchinger, Albrecht E.
Stalk lodging causes yield losses in maize cultivation ranging from 5 to 20% annually worldwide and stalk mechanical strength is widely accepted as an indirect indicator for its measurement. QTL mapping can reveal the genetic basis of stalk strength and provide information about markers suitable for marker-assisted selection (MAS). Constantly increasing market demands urge maize geneticists and breeders not only to enhance the field performance of new hybrids, but also to improve the breeding process. During the last decade, advances in the double haploid (DH) technology based on in vivo haploid induction (HI) shifted the breeding paradigm and greatly accelerated the breeding process in maize. Further spread of DH technology urgently demands a simple but efficient way for developing new inducers, which could be achieved by introducing the mandatory QTL/gene(s) of HI to advanced breeding lines. Therefore, the main goal of my thesis was to dissect the genetic architecture of stalk strength and detect the mandatory genomic region(s) of HI using genome-wide molecular markers. Several methods have been developed and applied in the literature to evaluate stalk mechanical strength, among which the rind penetrometer resistance (RPR) is a simple, rapid and non-destructive measurement during data collection, whereas stalk bending strength (SBS) is more closely associated with stalk lodging in the field. According to common knowledge in the mechanics of materials, SBS is reflected by the maximum load exerted to breaking (Fmax), the breaking moment (Mmax) and the critical stress (σmax). Thus, to have a complete understanding of the genetic architecture of stalk strength in maize, RPR and SBS (measured by Fmax, Mmax and σmax) were used to characterize stalk strength in our study. Utilizing a segregating population with 216 recombinant inbred lines, our analysis showed that stalk strength traits, RPR and SBS, have high heritability, ranging from 0.75 to 0.91. Nine QTL and one epistatic interaction between QTL were detected for RPR. Two, three and two QTL were detected for Fmax, Mmax and σmax, respectively. All QTL showed minor effects and only one QTL on chromosome 10 had overlapping support intervals between RPR and SBS. Co-locations of QTL and high positive correlations between stalk strength traits and other stalk traits suggested presence of pleiotropism and a complex genetic architecture of stalk strength. Owing to lack of major QTL, MAS solely based on molecular markers was found to be less effective than classical phenotypic selection for stalk strength. However, for SBS we observed considerably higher proportions of genetic variance explained by a genomic selection approach than obtained in QTL mapping with cross validation. Therefore, genomic selection might be a promising tool to improve the efficiency of breeding for stalk strength. All QTL mapping studies conducted hitherto for unraveling the genetic architecture of HI rate detected a major QTL, termed qhir1, in bin 1.04. Dong et al. (2013) further narrowed down this QTL to a 243 kb region. Considering the complex genetic architecture of HI and genetic background noise possibly affecting fine mapping of qhir1, we attempted to validate these results with an alternative approach before embarking on map-based gene isolation. Utilizing 51 maize haploid inducers and 1,482 non-inducers collected worldwide, we were able to investigate the genetic diversity between inducers and non-inducers and detect genomic regions mandatory for HI. The genetic diversity analyses indicated that the inducer group was clearly separated from other germplasm groups and had high familial relatedness. Analyzing our data by a case-control association approach failed because the segregation of HI was heavily confounded with population structure. Moreover, selective sweep approaches commonly used in the literature that are designed for capturing selective sweeps in a long-term evolutionary context failed due to high familial relatedness among inducers. To solve this problem, we developed a novel genome scan approach to detect fixed segments among inducers. With this approach, we detected a segment, termed qhir12, 4.0 Mb in length, within the support interval of the qhir1. This segment was the longest genomic segment detected by our novel approach and was entirely absent in all non-inducers analyzed. However, qhir12 has no overlap with the fine mapping region of Dong et al. (2013), termed qhir11. This indicates that the genomic region harboring the mandatory gene of HI should be confirmed by further experiments to corroborate its existence and identify its location in the maize genome.
Der Einfluss von Ölgehalt und Fettsäuremuster auf die Lagerfähigkeit von Saatgut
(2007) Ghiasvand Ghiasi, Kambiz; Kruse, Michael
Seed storage with the objective of maintaining the quality for the later sowing is a constant challenge, not only in gene banks but also in agriculture, forestry and horticulture. In 1980 ELLIS and ROBERTS established ?The improved seed viability equation? for the prediction of the storability of seeds. With this equation the loss-of-germination-curve can be computed as a function of the initial seed germination, the storage temperature and the seed moisture content for each species. However, with oil-rich seeds the equation very often misses its aim. With this seeds, the variety and lot specific oil content considerably determines water activity and aging rate. Therefore the objective of the present work was to describe the influence of oil content on the aging behavior of seeds of the oil crops during storage quantitatively, to integrate this influence in the most reasonable way into the viability equation and to improve accuracy of its prediction. The investigation was carried out with storage experiments under controlled conditions in the laboratory at higher temperatures and running times between a few days and six months. First it was examined, whether the usually determined oil content of the entire seed is an informative parameter for water activity in the embryo axis. Experiments with sunflowers with an oil content between 28 and 48 % showed that oil-rich seeds need an about 1 % higher seed moisture content than seeds with lower oil content to have the same water activity in the embryonic axis. The storage of these seeds as well as the seeds of rape with oil contents between 39 and 50 % and flax with oil contents between 36 and 43 % showed that the loss of germination is more consistent with uniform water activity than with uniform seed moisture content. This has not been taken into account in the previous viability equation, so that its prediction contains systematic errors. Therefore extensive storage experiments were carried out with altogether 28 seed lots of rape, sunflower, flax and corn with different moisture contents and a uniform temperature of 45°C. Only for few of the stored lots the prediction of the seed viability equation was found to be correct. To include the oil content into the seed viability equation eight different suggestions were compiled. These were applied in three nonlinear regression models with different restrictions to the results of the storage experiments. The first model permitted the species specific determination of the weighing factors (constants) for the seed viability equation. The second model only allowed to determine the weighing factors for the absolute term and the seed moisture content specifically. Oil content was provided however with a species-nonspecific weighing factor. In the third model all weighing factors were species-nonspecific determined. All eight suggestions achieved better estimations for the aging rate in the species-specific models than the previous viability equation. Where this could be examined statistically, the improvements were significant. The same was found for the models with species-nonspecific weighting factors for the oil content. However, not all suggestions led to a converging result of the regression analysis. All examined species-nonspecific models did not improve the adjustment compared to the previous viability equation. The suggestions were then validated with a new and independent dataset with a storage temperature of seeds of 32°C. It was shown that the change of the temperature reduced the accuracy of the estimations of the nonlinear regression models. The new suggestions nevertheless corresponded better to the observed results than the previous viability equation. Based on these results a suggestion was then selected for the extension of the viability equation by ELLIS and ROBERT, which does not introduce a new weighing factor to the equation as the weighing factor might potentially contribute to a decrease of the precision of a prediction due to its standard error. Finally it was examined whether the fatty acid composition before storage in addition to the oil content affects the aging rate and whether the change of the fatty acid composition is directly connected to the loss of germination during storage. Only with rape, significant relations between the proportion of the fatty acid 14:0, 18:0, 20:0, 22:0 and the aging rate of the seed lots were determined. A uniform change of the fatty acid composition of all examined species could not be observed. Therefore this characteristic could not contribute to the further improvement of the prediction accuracy of the seed viability equation. To summarize, a suggestion to include the oil content into the viability equation was designed that clearly improves the accuracy of the prediction of the viability equation for oil-rich seeds and that contributes to a more appropriate and efficient storage of seeds.
Entwicklung, Charakterisierung und Kartierung von Mikrosatellitenmarkern bei der Zuckerrübe (Beta vulgaris L.)
(2001) Dörnte, Jost; Geiger, Hartwig H.
Simple sequence repeats (SSRs) or microsatellites were isolated from a sugarbeet (Beta vulgaris L.) genomic phage library. The size-fractionated library was screened for the occurrence of the motifes (GA)n, (GT)n, (TGA)n, (AGA)n and (CCG)n. The motifes (GA)n and (GT)n were found to occur most frequently in the sugarbeet genome (every 225 kb). In contrast, the trimer motifes were half as frequent (every 527 kb). A total of 217 microsatellite sequences were found in the sequenced clones. Most of the repeats were imperfect and/or compound. Sequence comparison revealed that 23% of the clones wich containing the (GT)n motif are variants of a previously described satellite DNA (SCHMIDT et al. 1991). Of 102 primer pairs tested on sugarbeet DNA, 71 gave a single product in the expected size. On 23 sugarbeet samples 64 of the 71 SSR-markers reveald length polymorphisms. The number of detected alleles per marker ranged from 2 to 13 (average 4,9) and the PIC-values ranged from 0,17 to 0,86 (average 0,58). A cluster analysis of the 23 samples confirms the pedigree data. The developed SSR markers were compared with RFLP and AFLP markers. Therefore nine sugarbeet lines, each with five single plants per line, were analysed. The SSR analyse shows the lowest similarity between the nine lines. The similarity inside the lines revealed no differences between the marker assays. Thirtythree SSR markers were genetically mapped into the RFLP framework maps of 2 F2-populations. The markers are randomly distributed over eight linkage groups of sugar beet.
Evaluation of association mapping and genomic prediction in diverse barley and cauliflower breeding material
(2018) Thorwarth, Patrick; Schmid, Karl J.
Due to the advent of new sequencing technologies and high-throughput phenotyping an almost unlimited amount of data is available. In combination with statistical methods such as Genome-wide association mapping (GWAM) and Genomic prediction (GP), these information can provide valuable insight into the genetic potential of individuals and support selection and crossing decisions in a breeding program. In this thesis we focused on the evaluation of the aforementioned methods in diverse barley (Hordeum vulgare L.) and cauliflower (Brassica oleracea var. botrytis) populations consisting of elite material and genetic resources. We concentrated on the dissection of the influence of specific parameters such as marker type, statistical models, influence of population structure and kinship, on the performance of GWAM and GP. For parts of this thesis, we additionally used simulated data to support findings based on empirical data. First, we compared four different GWAM methods that either use single-marker or haplotypes for the detection of quantitative trait loci in a barley population. To find out the required population size and marker density to detect QTLs of varying effect size, we performed a simulation study based on parameter estimates of the empirical population. We could demonstrate that already in small populations of about 100 individuals, QTLs with a large effect can be detected and that at least 500 individuals are necessary to detect QTLs with an effect < 10%. Furthermore, we demonstrated an increased power of haplotpye based methods in the detection of very small QTLs. In a second study we used a barley population consisting of 750 individuals as training set to compare different GP models, that are currently used by scientists and plant breeders. From the training set 33 offspring families were derived with a total of 750 individuals. This enabled us to assess the prediction ability not only based on cross-validation but also in a large offspring population with varying degree of relatedness to the training population. We investigated the effects of linkage disequilibrium and linkage phase, population structure and relatedness of individuals, on the prediction ability. We could demonstrate a strong effect of the population structure on the prediction ability and show that about 11,203 evenly spaced SNP markers are necessary to predict even genetically distant populations. This implies that at the current marker density prediction ability is based on the relatedness of the individuals. In a third study we focused on the evaluation of GWAM and GP in cauliflower. We focused on the evaluation of genotyping-by-sequencing and compared the influence of imputation methods on the prediction ability and the number of significant associations. We obtained a total 120,693 SNPs in a random collection of 174 cauliflower genebank accessions. We demonstrated that imputation did not increase prediction ability and that the number of detected QTLs only slightly differed between the imputed and the unimputed data set. GP performed well even in such a diverse gene bank sample, but population structure again influenced the prediction ability. We could demonstrate the usefulness and limitations of Genome-wide association mapping and genomic prediction in two species. Even though a lot of research in the field of statistical genetics has provided valuable insight, the usage of Genomic prediction should still be applied with care and only as a supporting tool for classical breeding methods.
Experimental and simulation studies on introgressing genomic segments from exotic into elite germplasm of rye (Secale cereale L.) by marker-assisted backcrossing
(2005) Susic, Zoran; Geiger, Hartwig H.
The introgression of exotic germplasm is a promising approach to increase the genetic diversity of elite rye breeding materials. Even though exotic germplasm may contain genomic segments that can improve oligo- and polygenically inherited traits, it has not been intensively utilized in modern rye breeding due to its agronomically inferior phenotypes and low performance level. Introgression of exotic germplasm requires techniques that would minimize negative side effects attributable to genetic interactions between recipient and donor. This appears achievable by the introgression library approach involving the systematic transfer of donor chromosome (DC) segments from an agriculturally unadapted source (donor) into an elite line (recipient, recurrent parent). A set of introgression lines (ILs) is thus developed, in which introgression is restricted to one or a few short DC segments. Ideally, the introgressed DC segments are evenly distributed over the whole recipient genome and the total genome of the exotic donor is comprised in the established set of ILs. The systematic development of an introgression library in rye has not been described yet. The main objectives of this study were to i) establish two rye introgression libraries by marker-assisted backcrossing, comprising of ILs each harbouring one to three DC segments and jointly covering most of the donor genome (DG), and ii) apply computer simulations to develop a highly effective and cost-efficient marker-assisted introgression strategy for the creation of introgression libraries in rye. A cross between a homozygous elite rye inbred line L2053-N (recurrent parent) and a heterozygous Iranian primitive rye population Altevogt 14160 (donor) was used as base material to generate the two libraries (F and G). Repeated backcrossing (BC) and subsequent selfing (S) until generation BC2S3 were chosen as the introgression method. The AFLP and SSR markers were employed to select individuals carrying desired DC segments, starting from generation BC1 to generation BC2S2. The chromosomal localization of DC segments, the number of DC segments per IL, and the proportion of recurrent parent genome were used as criteria to select parent individuals. This procedure resulted in the first two rye introgression libraries worldwide, comprising 40 BC2S3 ILs per library and covering 72% of the total DG in library F and 63% in library G (jointly approximately 80%). Most of the established ILs harboured one to three homozygous DC segments (on average 2.2 in both libraries), with a mean length of 18.3 cM in library F and 14.3 cM in library G. Computer simulations were conducted using the software PLABSIM version 2 to evaluate and optimize strategies for developing an introgression library in rye. Simulations were based on map-length estimates obtained from genotyping the BC1 generation of population F (7 chromosome pairs, genome size 665 cM). Six strategies differing in the number of BC and S generations were analysed, by setting the restrictions of sufficient DG coverage and RPG recovery. The medium-long BC3S1 strategy proved to be the most recommendable. It allows to achieve close to 100% DG coverage with moderate progeny sizes (19 individual per IL) in the individual generations and an acceptable total number of marker data points (52700), thus providing a good compromise between the cost and speed of an introgression procedure. Longer strategies are somewhat more cost-efficient but too time-demanding. The reverse is true for shorter strategies. An optimal allocation of resources is achieved by starting an introgression strategy with a small BC1 population (between 60 and 200 individuals) and stepwise increasing the progeny size per IL from about 15 to about 25-35 individuals in the succeeding generations. Targeting longer DC segments and using genetic maps with lower marker density allow a remarkable reduction in resources. This approach, however, possesses shortcomings when implementation in breeding is considered. The longer DC segments more likely carry i) unfavourable loci as well, ii) more than one gene controlling the trait in question, or iii) many additional loci affecting other traits. The major disadvantage of genetic maps with large marker distances is the unknown information about possible double cross-overs within marker intervals. All above-mentioned disadvantages may cause problems in the process of identification and isolation of genes controlling the trait of interest. Thus, a lower initial effort for the establishment of an introgression library will later on require additional efforts for using the ILs in breeding and genomics. Since the results of the simulation study became available after the marker-assisted establishment of the two rye introgression libraries had been finished, the dimensioning of the experimental study deviated from the optimum dimensioning determined in the simulation study: i) The BC2S2 introgression strategy was used in the empirical approach, whereas the BC3S1 strategy proved to be most recommendable in the simulation study. ii) The BC1 population sizes of libraries F and G (68 and 69, respectively) were far below the optimum value (200) determined in the simulation study for the chosen BC2S2 strategy. iii) The mean progeny sizes per IL from generation BC2 onwards varied between 7 and 21, whereas the optimum progeny size would have been two to three times higher. iv) The total number of analysed individuals (690 in library F, 684 in library G) was considerably lower than the optimum determined in the simulation study (3440). As a consequence, the coverage of the donor genome in the two libraries was incomplete and most ILs harboured more than a single DC segment. The potential application of the results of the simulation study would have increased the value of the developed ILs (higher DG coverage, lower number of DC segments per IL) considerably, despite limited resources. The effects of the introgressed DC segments on agronomically important qualitative and quantitative traits still need to be examined in multi-environmental field experiments. Introgression lines with beneficial DC segments may directly be used in practical hybrid rye breeding programs. Moreover, such ILs may be further backcrossed to create near isogenic lines (NILs) each carrying a single marker-characterized short DC segment. These NILs are an ideal starting point for high-resolution mapping and for the isolation and functional characterisation of candidate genes. The two rye introgression libraries and the results of the simulation study mark important milestones for the targeted exploitation of exotic rye germplasm and provide a promising opportunity to proceed towards functional genomics in rye.
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.
Factors influencing the accuracy of genomic prediction in plant breeding
(2017) Schopp, Pascal; Melchinger, Albrecht E.
Genomic prediction (GP) is a novel statistical tool to estimate breeding values of selection candidates without the necessity to evaluate them phenotypically. The method calibrates a prediction model based on data of phenotyped individuals that were also genotyped with genome-wide molecular markers. The renunciation of an explicit identification of causal polymorphisms in the DNA sequence allows GP to explain significantly larger amounts of the genetic variance of complex traits than previous mapping-based approaches employed for marker-assisted selection. For these reasons, GP rapidly revolutionized dairy cattle breeding, where the method was originally developed and first implemented. By comparison, plant breeding is characterized by often intensively structured populations and more restricted resources routinely available for model calibration. This thesis addresses important issues related to these peculiarities to further promote an efficient integration of GP into plant breeding.

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