TY - JOUR A1 - Riaño-Pachón, Diego Mauricio A1 - Kleessen, Sabrina A1 - Neigenfind, Jost A1 - Durek, Pawel A1 - Weber, Elke A1 - Engelsberger, Wolfgang R. A1 - Walther, Dirk A1 - Selbig, Joachim A1 - Schulze, Waltraud X. A1 - Kersten, Birgit T1 - Proteome-wide survey of phosphorylation patterns affected by nuclear DNA polymorphisms in Arabidopsis thaliana JF - BMC Genomics N2 - Background: Protein phosphorylation is an important post-translational modification influencing many aspects of dynamic cellular behavior. Site-specific phosphorylation of amino acid residues serine, threonine, and tyrosine can have profound effects on protein structure, activity, stability, and interaction with other biomolecules. Phosphorylation sites can be affected in diverse ways in members of any species, one such way is through single nucleotide polymorphisms (SNPs). The availability of large numbers of experimentally identified phosphorylation sites, and of natural variation datasets in Arabidopsis thaliana prompted us to analyze the effect of non-synonymous SNPs (nsSNPs) onto phosphorylation sites. Results: From the analyses of 7,178 experimentally identified phosphorylation sites we found that: (i) Proteins with multiple phosphorylation sites occur more often than expected by chance. (ii) Phosphorylation hotspots show a preference to be located outside conserved domains. (iii) nsSNPs affected experimental phosphorylation sites as much as the corresponding non-phosphorylated amino acid residues. (iv) Losses of experimental phosphorylation sites by nsSNPs were identified in 86 A. thaliana proteins, among them receptor proteins were overrepresented. These results were confirmed by similar analyses of predicted phosphorylation sites in A. thaliana. In addition, predicted threonine phosphorylation sites showed a significant enrichment of nsSNPs towards asparagines and a significant depletion of the synonymous substitution. Proteins in which predicted phosphorylation sites were affected by nsSNPs (loss and gain), were determined to be mainly receptor proteins, stress response proteins and proteins involved in nucleotide and protein binding. Proteins involved in metabolism, catalytic activity and biosynthesis were less affected. Conclusions: We analyzed more than 7,100 experimentally identified phosphorylation sites in almost 4,300 protein-coding loci in silico, thus constituting the largest phosphoproteomics dataset for A. thaliana available to date. Our findings suggest a relatively high variability in the presence or absence of phosphorylation sites between different natural accessions in receptor and other proteins involved in signal transduction. Elucidating the effect of phosphorylation sites affected by nsSNPs on adaptive responses represents an exciting research goal for the future. KW - Gene Ontology KW - Phosphorylation Site KW - phosphorylated amino acid KW - slim term KW - single nucleotide polymorphism mapping Y1 - 2010 U6 - https://doi.org/10.1186/1471-2164-11-411 SN - 1471-2164 VL - 11 PB - Biomed Central CY - London 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 - 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 - Jargosch, M. A1 - Kroeger, S. A1 - Gralinska, E. A1 - Klotz, Ulrike A1 - Fang, Z. A1 - Chen, W. A1 - Leser, U. A1 - Selbig, Joachim A1 - Groth, Detlef A1 - Baumgrass, Ria T1 - Data integration for identification of important transcription factors of STAT6-mediated cell fate decisions JF - Genetics and molecular research N2 - Data integration has become a useful strategy for uncovering new insights into complex biological networks. We studied whether this approach can help to delineate the signal transducer and activator of transcription 6 (STAT6)-mediated transcriptional network driving T helper (Th) 2 cell fate decisions. To this end, we performed an integrative analysis of publicly available RNA-seq data of Stat6-knockout mouse studies together with STAT6 ChIP-seq data and our own gene expression time series data during Th2 cell differentiation. We focused on transcription factors (TFs), cytokines, and cytokine receptors and delineated 59 positively and 41 negatively STAT6-regulated genes, which were used to construct a transcriptional network around STAT6. The network illustrates that important and well-known TFs for Th2 cell differentiation are positively regulated by STAT6 and act either as activators for Th2 cells (e.g., Gata3, Atf3, Satb1, Nfil3, Maf, and Pparg) or as suppressors for other Th cell subpopulations such as Th1 (e.g., Ar), Th17 (e.g., Etv6), or iTreg (e.g., Stat3 and Hifla) cells. Moreover, our approach reveals 11 TFs (e.g., Atf5, Creb3l2, and Asb2) with unknown functions in Th cell differentiation. This fact together with the observed enrichment of asthma risk genes among those regulated by STAT6 underlines the potential value of the data integration strategy used here. Thus, our results clearly support the opinion that data integration is a useful tool to delineate complex physiological processes. KW - Data integration KW - Th2 cells KW - Gene regulatory network KW - STAT6 KW - Transcription factors Y1 - 2016 U6 - https://doi.org/10.4238/gmr.15028493 SN - 1676-5680 VL - 15 PB - FUNPEC CY - Ribeirao Preto ER - TY - JOUR A1 - Edlich-Muth, Christian A1 - Muraya, Moses M. A1 - Altmann, Thomas A1 - Selbig, Joachim T1 - Phenomic prediction of maize hybrids JF - Biosystems : journal of biological and information processing sciences N2 - Phenomic experiments are carried out in large-scale plant phenotyping facilities that acquire a large number of pictures of hundreds of plants simultaneously. With the aid of automated image processing, the data are converted into genotype-feature matrices that cover many consecutive days of development. Here, we explore the possibility of predicting the biomass of the fully grown plant from early developmental stage image-derived features. We performed phenomic experiments on 195 inbred and 382 hybrid maizes varieties and followed their progress from 16 days after sowing (DAS) to 48 DAS with 129 image-derived features. By applying sparse regression methods, we show that 73% of the variance in hybrid fresh weight of fully-grown plants is explained by about 20 features at the three-leaf-stage or earlier. Dry weight prediction explained over 90% of the variance. When phenomic features of parental inbred lines were used as predictors of hybrid biomass, the proportion of variance explained was 42 and 45%, for fresh weight and dry weight models consisting of 35 and 36 features, respectively. These models were very robust, showing only a small amount of variation in performance over the time scale of the experiment. We also examined mid-parent heterosis in phenomic features. Feature heterosis displayed a large degree of variance which resulted in prediction performance that was less robust than models of either parental or hybrid predictors. Our results show that phenomic prediction is a viable alternative to genomic and metabolic prediction of hybrid performance. In particular, the utility of early-stage parental lines is very encouraging. (C) 2016 Elsevier Ireland Ltd. All rights reserved. KW - Hybrid prediction KW - LASSO KW - Regression KW - Maize KW - Phenomics Y1 - 2016 U6 - https://doi.org/10.1016/j.biosystems.2016.05.008 SN - 0303-2647 SN - 1872-8324 VL - 146 SP - 102 EP - 109 PB - Elsevier CY - Oxford ER - TY - JOUR A1 - Kanzleiter, Timo A1 - Jaehnert, Markus A1 - Schulze, Gunnar A1 - Selbig, Joachim A1 - Hallahan, Nicole A1 - Schwenk, Robert Wolfgang A1 - Schürmann, Annette T1 - Exercise training alters DNA methylation patterns in genes related to muscle growth and differentiation in mice JF - American journal of physiology : Endocrinology and metabolism N2 - The adaptive response of skeletal muscle to exercise training is tightly controlled and therefore requires transcriptional regulation. DNA methylation is an epigenetic mechanism known to modulate gene expression, but its contribution to exercise-induced adaptations in skeletal muscle is not well studied. Here, we describe a genome-wide analysis of DNA methylation in muscle of trained mice (n = 3). Compared with sedentary controls, 2,762 genes exhibited differentially methylated CpGs (P < 0.05, meth diff >5%, coverage > 10) in their putative promoter regions. Alignment with gene expression data (n = 6) revealed 200 genes with a negative correlation between methylation and expression changes in response to exercise training. The majority of these genes were related to muscle growth and differentiation, and a minor fraction involved in metabolic regulation. Among the candidates were genes that regulate the expression of myogenic regulatory factors (Plexin A2) as well as genes that participate in muscle hypertrophy (Igfbp4) and motor neuron innervation (Dok7). Interestingly, a transcription factor binding site enrichment study discovered significantly enriched occurrence of CpG methylation in the binding sites of the myogenic regulatory factors MyoD and myogenin. These findings suggest that DNA methylation is involved in the regulation of muscle adaptation to regular exercise training. KW - DNA methylation KW - regular exercise training KW - muscle development Y1 - 2015 U6 - https://doi.org/10.1152/ajpendo.00289.2014 SN - 0193-1849 SN - 1522-1555 VL - 308 IS - 10 SP - E912 EP - E920 PB - American Chemical Society CY - Bethesda ER - TY - JOUR A1 - Bordag, Natalie A1 - Klie, Sebastian A1 - Jürchott, Kathrin A1 - Vierheller, Janine A1 - Schiewe, Hajo A1 - Albrecht, Valerie A1 - Tonn, Jörg-Christian A1 - Schwartz, Christoph A1 - Schichor, Christian A1 - Selbig, Joachim T1 - Glucocorticoid (dexamethasone)-induced metabolome changes in healthy males suggest prediction of response and side effects JF - Scientific reports N2 - Glucocorticoids are indispensable anti-inflammatory and decongestant drugs with high prevalence of use at (similar to)0.9% of the adult population. Better holistic insights into glucocorticoid-induced changes are crucial for effective use as concurrent medication and management of adverse effects. The profiles of 214 metabolites from plasma of 20 male healthy volunteers were recorded prior to and after ingestion of a single dose of 4 mg dexamethasone (+20 mg pantoprazole). Samples were drawn at three predefined time points per day: seven untreated (day 1 midday - day 3 midday) and four treated (day 3 evening - day 4 evening) per volunteer. Statistical analysis revealed tremendous impact of dexamethasone on the metabolome with 150 of 214 metabolites being significantly deregulated on at least one time point after treatment (ANOVA, Benjamini-Hochberg corrected, q < 0.05). Inter-person variability was high and remained uninfluenced by treatment. The clearly visible circadian rhythm prior to treatment was almost completely suppressed and deregulated by dexamethasone. The results draw a holistic picture of the severe metabolic deregulation induced by single-dose, short-term glucocorticoid application. The observed metabolic changes suggest a potential for early detection of severe side effects, raising hope for personalized early countermeasures increasing quality of life and reducing health care costs. Y1 - 2015 U6 - https://doi.org/10.1038/srep15954 SN - 2045-2322 VL - 5 PB - Nature Publ. Group CY - London 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 - Klie, Sebastian A1 - Nikoloski, Zoran A1 - Selbig, Joachim T1 - Biological cluster evaluation for gene function prediction JF - Journal of computational biology N2 - Recent advances in high-throughput omics techniques render it possible to decode the function of genes by using the "guilt-by-association" principle on biologically meaningful clusters of gene expression data. However, the existing frameworks for biological evaluation of gene clusters are hindered by two bottleneck issues: (1) the choice for the number of clusters, and (2) the external measures which do not take in consideration the structure of the analyzed data and the ontology of the existing biological knowledge. Here, we address the identified bottlenecks by developing a novel framework that allows not only for biological evaluation of gene expression clusters based on existing structured knowledge, but also for prediction of putative gene functions. The proposed framework facilitates propagation of statistical significance at each of the following steps: (1) estimating the number of clusters, (2) evaluating the clusters in terms of novel external structural measures, (3) selecting an optimal clustering algorithm, and (4) predicting gene functions. The framework also includes a method for evaluation of gene clusters based on the structure of the employed ontology. Moreover, our method for obtaining a probabilistic range for the number of clusters is demonstrated valid on synthetic data and available gene expression profiles from Saccharomyces cerevisiae. Finally, we propose a network-based approach for gene function prediction which relies on the clustering of optimal score and the employed ontology. Our approach effectively predicts gene function on the Saccharomyces cerevisiae data set and is also employed to obtain putative gene functions for an Arabidopsis thaliana data set. KW - algorithms KW - biochemical networks KW - combinatorics KW - computational molecular biology KW - databases KW - functional genomics KW - gene expression KW - NP-completeness Y1 - 2014 U6 - https://doi.org/10.1089/cmb.2009.0129 SN - 1066-5277 SN - 1557-8666 VL - 21 IS - 6 SP - 428 EP - 445 PB - Liebert CY - New Rochelle ER - TY - JOUR A1 - Guo, Ke-Tai A1 - Fu, Peng A1 - Juerchott, Kathrin A1 - Motaln, Helena A1 - Selbig, Joachim A1 - Lah, Tamara T. A1 - Tonn, Jörg-Christian A1 - Schichor, Christian T1 - The expression of Wnt-inhibitor DKK1 (Dickkopf 1) is determined by intercellular crosstalk and hypoxia in human malignant gliomas JF - Journal of cancer research and clinical oncology : official organ of the Deutsche Krebsgesellschaft N2 - Objective Wnt signalling pathways regulate proliferation, motility and survival in a variety of human cell types. Dickkopf 1 (DKK1) gene codes for a secreted Wnt inhibitory factor. It functions as tumour suppressor gene in breast cancer and as a pro-apoptotic factor in glioma cells. In this study, we aimed to demonstrate whether the different expression of DKK1 in human glioma-derived cells is dependent on microenvironmental factors like hypoxia and regulated by the intercellular crosstalk with bone-marrow-derived mesenchymal stem cells (bmMSCs). Methods Glioma cell line U87-MG, three cell lines from human glioblastoma grade IV (glioma-derived mesenchymal stem cells) and three bmMSCs were selected for the experiment. The expression of DKK1 in cell lines under normoxic/hypoxic environment or co-culture condition was measured using real-time PCR and enzyme-linked immunoadsorbent assay. The effect of DKK1 on cell migration and proliferation was evaluated by in vitro wound healing assays and sulphorhodamine assays, respectively. Results Glioma-derived cells U87-MG displayed lower DKK1 expression compared with bmMSCs. Hypoxia led to an overexpression of DKK1 in bmMSCs and U87-MG when compared to normoxic environment, whereas co-culture of U87-MG with bmMSCs induced the expression of DKK1 in both cell lines. Exogenous recombinant DKK1 inhibited cell migration on all cell lines, but did not have a significant effect on cell proliferation of bmMSCs and glioma cell lines. Conclusion In this study, we showed for the first time that the expression of DKK1 was hypoxia dependent in human malignant glioma cell lines. The induction of DKK1 by intracellular crosstalk or hypoxia stimuli sheds light on the intense adaption of glial tumour cells to environmental alterations. KW - Dickkopf 1 KW - Intercellular crosstalk KW - Hypoxia KW - Gliomas Y1 - 2014 U6 - https://doi.org/10.1007/s00432-014-1642-2 SN - 0171-5216 SN - 1432-1335 VL - 140 IS - 8 SP - 1261 EP - 1270 PB - Springer CY - New York ER -