TY - GEN A1 - Meyer, Rhonda Christiane A1 - Kusterer, Barbara A1 - Lisec, Jan A1 - Steinfath, Matthias A1 - Becher, Martina A1 - Scharr, Hanno A1 - Melchinger, Albrecht E. A1 - Selbig, Joachim A1 - Schurr, Ulrich A1 - Willmitzer, Lothar A1 - Altmann, Thomas T1 - QTL analysis of early stage heterosis for biomass in Arabidopsis T2 - Zweitveröffentlichungen der Universität Potsdam : Mathematisch-Naturwissenschaftliche Reihe N2 - The main objective of this study was to identify genomic regions involved in biomass heterosis using QTL, generation means, and mode-of-inheritance classification analyses. In a modified North Carolina Design III we backcrossed 429 recombinant inbred line and 140 introgression line populations to the two parental accessions, C24 and Col-0, whose F 1 hybrid exhibited 44% heterosis for biomass. Mid-parent heterosis in the RILs ranged from −31 to 99% for dry weight and from −58 to 143% for leaf area. We detected ten genomic positions involved in biomass heterosis at an early developmental stage, individually explaining between 2.4 and 15.7% of the phenotypic variation. While overdominant gene action was prevalent in heterotic QTL, our results suggest that a combination of dominance, overdominance and epistasis is involved in biomass heterosis in this Arabidopsis cross. T3 - Zweitveröffentlichungen der Universität Potsdam : Mathematisch-Naturwissenschaftliche Reihe - 1330 KW - Quantitative Trait Locus KW - recombinant inbred line KW - Quantitative Trait Locus analysis KW - dominance effect KW - recombinant inbred line population Y1 - 2009 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-431272 SN - 1866-8372 IS - 1330 ER - TY - JOUR A1 - Meyer, Rhonda Christiane A1 - Kusterer, Barbara A1 - Lisec, Jan A1 - Steinfath, Matthias A1 - Becher, Martina A1 - Scharr, Hanno A1 - Melchinger, Albrecht E. A1 - Selbig, Joachim A1 - Schurr, Ulrich A1 - Willmitzer, Lothar A1 - Altmann, Thomas T1 - QTL analysis of early stage heterosis for biomass in Arabidopsis JF - Theoretical and applied genetics N2 - The main objective of this study was to identify genomic regions involved in biomass heterosis using QTL, generation means, and mode-of-inheritance classification analyses. In a modified North Carolina Design III we backcrossed 429 recombinant inbred line and 140 introgression line populations to the two parental accessions, C24 and Col-0, whose F 1 hybrid exhibited 44% heterosis for biomass. Mid-parent heterosis in the RILs ranged from −31 to 99% for dry weight and from −58 to 143% for leaf area. We detected ten genomic positions involved in biomass heterosis at an early developmental stage, individually explaining between 2.4 and 15.7% of the phenotypic variation. While overdominant gene action was prevalent in heterotic QTL, our results suggest that a combination of dominance, overdominance and epistasis is involved in biomass heterosis in this Arabidopsis cross. KW - Quantitative Trait Locus KW - recombinant inbred line KW - Quantitative Trait Locus analysis KW - dominance effect KW - recombinant inbred line population Y1 - 2009 U6 - https://doi.org/10.1007/s00122-009-1074-6 SN - 1432-2242 SN - 0040-5752 VL - 129 IS - 2 SP - 227 EP - 237 PB - Springer Nature CY - Berlin ER - TY - GEN A1 - Steinfath, Matthias A1 - Gärtner, Tanja A1 - Lisec, Jan A1 - Meyer, Rhonda C. A1 - Altmann, Thomas A1 - Willmitzer, Lothar A1 - Selbig, Joachim T1 - Prediction of hybrid biomass in Arabidopsis thaliana by selected parental SNP and metabolic markers T2 - Zweitveröffentlichungen der Universität Potsdam : Mathematisch-Naturwissenschaftliche Reihe N2 - A recombinant inbred line (RIL) population, derived from two Arabidopsis thaliana accessions, and the corresponding testcrosses with these two original accessions were used for the development and validation of machine learning models to predict the biomass of hybrids. Genetic and metabolic information of the RILs served as predictors. Feature selection reduced the number of variables (genetic and metabolic markers) in the models by more than 80% without impairing the predictive power. Thus, potential biomarkers have been revealed. Metabolites were shown to bear information on inherited macroscopic phenotypes. This proof of concept could be interesting for breeders. The example population exhibits substantial mid-parent biomass heterosis. The results of feature selection could therefore be used to shed light on the origin of heterosis. In this respect, mainly dominance effects were detected. T3 - Zweitveröffentlichungen der Universität Potsdam : Mathematisch-Naturwissenschaftliche Reihe - 1324 KW - Quantitative Trait Locus KW - feature selection KW - Partial Little Square KW - recombinant inbred line KW - Quantitative Trait Locus analysis Y1 - 2009 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-431115 SN - 1866-8372 IS - 1324 ER - TY - JOUR A1 - Steinfath, Matthias A1 - Gärtner, Tanja A1 - Lisec, Jan A1 - Meyer, Rhonda Christiane A1 - Altmann, Thomas A1 - Willmitzer, Lothar A1 - Selbig, Joachim T1 - Prediction of hybrid biomass in Arabidopsis thaliana by selected parental SNP and metabolic markers JF - Theoretical and applied genetics : TAG ; international journal of plant breeding research N2 - A recombinant inbred line (RIL) population, derived from two Arabidopsis thaliana accessions, and the corresponding testcrosses with these two original accessions were used for the development and validation of machine learning models to predict the biomass of hybrids. Genetic and metabolic information of the RILs served as predictors. Feature selection reduced the number of variables (genetic and metabolic markers) in the models by more than 80% without impairing the predictive power. Thus, potential biomarkers have been revealed. Metabolites were shown to bear information on inherited macroscopic phenotypes. This proof of concept could be interesting for breeders. The example population exhibits substantial mid-parent biomass heterosis. The results of feature selection could therefore be used to shed light on the origin of heterosis. In this respect, mainly dominance effects were detected. KW - Quantitative Trait Locus KW - feature selection KW - Partial Little Square KW - recombinant inbred line KW - Quantitative Trait Locus analysis Y1 - 2009 U6 - https://doi.org/10.1007/s00122-009-1191-2 SN - 0040-5752 SN - 1432-2242 VL - 120 SP - 239 EP - 247 PB - Springer CY - Berlin ER - TY - JOUR A1 - de Abreu e Lima, Francisco Anastacio A1 - Li, Kun A1 - Wen, Weiwei A1 - Yan, Jianbing A1 - Nikoloski, Zoran A1 - Willmitzer, Lothar A1 - Brotman, Yariv T1 - Unraveling lipid metabolism in maize with time-resolved multi-omics data JF - The plant journal N2 - Maize is the cereal crop with the highest production worldwide, and its oil is a key energy resource. Improving the quantity and quality of maize oil requires a better understanding of lipid metabolism. To predict the function of maize genes involved in lipid biosynthesis, we assembled transcriptomic and lipidomic data sets from leaves of B73 and the high-oil line By804 in two distinct time-series experiments. The integrative analysis based on high-dimensional regularized regression yielded lipid-transcript associations indirectly validated by Gene Ontology and promoter motif enrichment analyses. The co-localization of lipid-transcript associations using the genetic mapping of lipid traits in leaves and seedlings of a B73 x By804 recombinant inbred line population uncovered 323 genes involved in the metabolism of phospholipids, galactolipids, sulfolipids and glycerolipids. The resulting association network further supported the involvement of 50 gene candidates in modulating levels of representatives from multiple acyl-lipid classes. Therefore, the proposed approach provides high-confidence candidates for experimental testing in maize and model plant species. KW - Zea mays KW - lipid metabolism KW - omics KW - GFLASSO KW - QTL Y1 - 2018 U6 - https://doi.org/10.1111/tpj.13833 SN - 0960-7412 SN - 1365-313X VL - 93 IS - 6 SP - 1102 EP - 1115 PB - Wiley CY - Hoboken ER - TY - JOUR A1 - de Abreu e Lima, Francisco Anastacio A1 - Willmitzer, Lothar A1 - Nikoloski, Zoran T1 - Classification-driven framework to predict maize hybrid field performance from metabolic profiles of young parental roots JF - PLoS one N2 - Maize (Zea mays L.) is a staple food whose production relies on seed stocks that largely comprise hybrid varieties. Therefore, knowledge about the molecular determinants of hybrid performance (HP) in the field can be used to devise better performing hybrids to address the demands for sustainable increase in yield. Here, we propose and test a classification-driven framework that uses metabolic profiles from in vitro grown young roots of parental lines from the Dent x Flint maize heterotic pattern to predict field HP. We identify parental analytes that best predict the metabolic inheritance patterns in 328 hybrids. We then demonstrate that these analytes are also predictive of field HP (0.64 >= r >= 0.79) and discriminate hybrids of good performance (accuracy of 87.50%). Therefore, our approach provides a cost-effective solution for hybrid selection programs. Y1 - 2018 U6 - https://doi.org/10.1371/journal.pone.0196038 SN - 1932-6203 VL - 13 IS - 4 PB - PLoS CY - San Fransisco ER - TY - GEN A1 - Hische, Manuela A1 - Larhlimi, Abdelhalim A1 - Schwarz, Franziska A1 - Fischer-Rosinský, Antje A1 - Bobbert, Thomas A1 - Assmann, Anke A1 - Catchpole, Gareth S. A1 - Pfeiffer, Andreas F. H. A1 - Willmitzer, Lothar A1 - Selbig, Joachim A1 - Spranger, Joachim T1 - A distinct metabolic signature predictsdevelopment of fasting plasma glucose T2 - Postprints der Universität Potsdam : Mathematisch Naturwissenschaftliche Reihe N2 - Background High blood glucose and diabetes are amongst the conditions causing the greatest losses in years of healthy life worldwide. Therefore, numerous studies aim to identify reliable risk markers for development of impaired glucose metabolism and type 2 diabetes. However, the molecular basis of impaired glucose metabolism is so far insufficiently understood. The development of so called 'omics' approaches in the recent years promises to identify molecular markers and to further understand the molecular basis of impaired glucose metabolism and type 2 diabetes. Although univariate statistical approaches are often applied, we demonstrate here that the application of multivariate statistical approaches is highly recommended to fully capture the complexity of data gained using high-throughput methods. Methods We took blood plasma samples from 172 subjects who participated in the prospective Metabolic Syndrome Berlin Potsdam follow-up study (MESY-BEPO Follow-up). We analysed these samples using Gas Chromatography coupled with Mass Spectrometry (GC-MS), and measured 286 metabolites. Furthermore, fasting glucose levels were measured using standard methods at baseline, and after an average of six years. We did correlation analysis and built linear regression models as well as Random Forest regression models to identify metabolites that predict the development of fasting glucose in our cohort. Results We found a metabolic pattern consisting of nine metabolites that predicted fasting glucose development with an accuracy of 0.47 in tenfold cross-validation using Random Forest regression. We also showed that adding established risk markers did not improve the model accuracy. However, external validation is eventually desirable. Although not all metabolites belonging to the final pattern are identified yet, the pattern directs attention to amino acid metabolism, energy metabolism and redox homeostasis. Conclusions We demonstrate that metabolites identified using a high-throughput method (GC-MS) perform well in predicting the development of fasting plasma glucose over several years. Notably, not single, but a complex pattern of metabolites propels the prediction and therefore reflects the complexity of the underlying molecular mechanisms. This result could only be captured by application of multivariate statistical approaches. Therefore, we highly recommend the usage of statistical methods that seize the complexity of the information given by high-throughput methods. T3 - Zweitveröffentlichungen der Universität Potsdam : Mathematisch-Naturwissenschaftliche Reihe - 850 KW - prediction KW - fasting glucose KW - type 2 diabetes KW - metabolomics KW - plasma KW - random forest KW - metabolite KW - regression KW - biomarker Y1 - 2020 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-427400 SN - 1866-8372 IS - 850 ER - TY - JOUR A1 - Feher, Kristen A1 - Lisec, Jan A1 - Roemisch-Margl, Lilla A1 - Selbig, Joachim A1 - Gierl, Alfons A1 - Piepho, Hans-Peter A1 - Nikoloski, Zoran A1 - Willmitzer, Lothar T1 - Deducing hybrid performance from parental metabolic profiles of young primary roots of maize by using a multivariate diallel approach JF - PLoS one Y1 - 2014 U6 - https://doi.org/10.1371/journal.pone.0085435 SN - 1932-6203 VL - 9 IS - 1 PB - PLoS CY - San Fransisco ER - TY - JOUR A1 - Tenenboim, Hezi A1 - Smirnova, Julia A1 - Willmitzer, Lothar A1 - Steup, Martin A1 - Brotman, Yariv T1 - VMP1-deficient Chlamydomonas exhibits severely aberrant cell morphology and disrupted cytokinesies JF - BMC plant biology N2 - Background: The versatile Vacuole Membrane Protein 1 (VMP1) has been previously investigated in six species. It has been shown to be essential in macroautophagy, where it takes part in autophagy initiation. In addition, VMP1 has been implicated in organellar biogenesis; endo-, exo- and phagocytosis, and protein secretion; apoptosis; and cell adhesion. These roles underly its proven involvement in pancreatitis, diabetes and cancer in humans. Results: In this study we analyzed a VMP1 homologue from the green alga Chlamydomonas reinhardtii. CrVMP1 knockdown lines showed severe phenotypes, mainly affecting cell division as well as the morphology of cells and organelles. We also provide several pieces of evidence for its involvement in macroautophagy. KW - VMP1 KW - Autophagy KW - Cytokinesis Y1 - 2014 U6 - https://doi.org/10.1186/1471-2229-14-121 SN - 1471-2229 VL - 14 PB - BioMed Central CY - London ER - TY - JOUR A1 - Mettler, Tabea A1 - Mühlhaus, Timo A1 - Hemme, Dorothea A1 - Schöttler, Mark Aurel A1 - Rupprecht, Jens A1 - Idoine, Adam A1 - Veyel, Daniel A1 - Pal, Sunil Kumar A1 - Yaneva-Roder, Liliya A1 - Winck, Flavia Vischi A1 - Sommer, Frederik A1 - Vosloh, Daniel A1 - Seiwert, Bettina A1 - Erban, Alexander A1 - Burgos, Asdrubal A1 - Arvidsson, Samuel Janne A1 - Schoenfelder, Stephanie A1 - Arnold, Anne A1 - Guenther, Manuela A1 - Krause, Ursula A1 - Lohse, Marc A1 - Kopka, Joachim A1 - Nikoloski, Zoran A1 - Müller-Röber, Bernd A1 - Willmitzer, Lothar A1 - Bock, Ralph A1 - Schroda, Michael A1 - Stitt, Mark T1 - Systems analysis of the response of photosynthesis, metabolism, and growth to an increase in irradiance in the photosynthetic model organism chlamydomonas reinhardtii JF - The plant cell N2 - We investigated the systems response of metabolism and growth after an increase in irradiance in the nonsaturating range in the algal model Chlamydomonas reinhardtii. In a three-step process, photosynthesis and the levels of metabolites increased immediately, growth increased after 10 to 15 min, and transcript and protein abundance responded by 40 and 120 to 240 min, respectively. In the first phase, starch and metabolites provided a transient buffer for carbon until growth increased. This uncouples photosynthesis from growth in a fluctuating light environment. In the first and second phases, rising metabolite levels and increased polysome loading drove an increase in fluxes. Most Calvin-Benson cycle (CBC) enzymes were substrate-limited in vivo, and strikingly, many were present at higher concentrations than their substrates, explaining how rising metabolite levels stimulate CBC flux. Rubisco, fructose-1,6-biosphosphatase, and seduheptulose-1,7-bisphosphatase were close to substrate saturation in vivo, and flux was increased by posttranslational activation. In the third phase, changes in abundance of particular proteins, including increases in plastidial ATP synthase and some CBC enzymes, relieved potential bottlenecks and readjusted protein allocation between different processes. Despite reasonable overall agreement between changes in transcript and protein abundance (R-2 = 0.24), many proteins, including those in photosynthesis, changed independently of transcript abundance. Y1 - 2014 U6 - https://doi.org/10.1105/tpc.114.124537 SN - 1040-4651 SN - 1532-298X VL - 26 IS - 6 SP - 2310 EP - 2350 PB - American Society of Plant Physiologists CY - Rockville ER -