TY - GEN A1 - Repsilber, Dirk A1 - Kern, Sabine A1 - Telaar, Anna A1 - Walzl, Gerhard A1 - Black, Gillian F. A1 - Selbig, Joachim A1 - Parida, Shreemanta K. A1 - Kaufmann, Stefan H. E. A1 - Jacobsen, Marc T1 - Biomarker discovery in heterogeneous tissue samples BT - taking the in-silico deconfounding approach T2 - Postprints der Universität Potsdam : Mathematisch-Naturwissenschaftliche Reihe N2 - Background: For heterogeneous tissues, such as blood, measurements of gene expression are confounded by relative proportions of cell types involved. Conclusions have to rely on estimation of gene expression signals for homogeneous cell populations, e.g. by applying micro-dissection, fluorescence activated cell sorting, or in-silico deconfounding. We studied feasibility and validity of a non-negative matrix decomposition algorithm using experimental gene expression data for blood and sorted cells from the same donor samples. Our objective was to optimize the algorithm regarding detection of differentially expressed genes and to enable its use for classification in the difficult scenario of reversely regulated genes. This would be of importance for the identification of candidate biomarkers in heterogeneous tissues. Results: Experimental data and simulation studies involving noise parameters estimated from these data revealed that for valid detection of differential gene expression, quantile normalization and use of non-log data are optimal. We demonstrate the feasibility of predicting proportions of constituting cell types from gene expression data of single samples, as a prerequisite for a deconfounding-based classification approach. Classification cross-validation errors with and without using deconfounding results are reported as well as sample-size dependencies. Implementation of the algorithm, simulation and analysis scripts are available. Conclusions: The deconfounding algorithm without decorrelation using quantile normalization on non-log data is proposed for biomarkers that are difficult to detect, and for cases where confounding by varying proportions of cell types is the suspected reason. In this case, a deconfounding ranking approach can be used as a powerful alternative to, or complement of, other statistical learning approaches to define candidate biomarkers for molecular diagnosis and prediction in biomedicine, in realistically noisy conditions and with moderate sample sizes. T3 - Zweitveröffentlichungen der Universität Potsdam : Mathematisch-Naturwissenschaftliche Reihe - 854 KW - differential gene expression KW - quantile normalization KW - heterogeneous tissue KW - gene expression matrix KW - homogeneous cell population KW - selection KW - microdissection Y1 - 2020 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-429343 SN - 1866-8372 IS - 854 ER - TY - JOUR A1 - Andorf, Sandra A1 - Meyer, Rhonda C. A1 - Selbig, Joachim A1 - Altmann, Thomas A1 - Repsilber, Dirk T1 - Integration of a systems biological network analysis and QTL results for biomass heterosis in arabidopsis thaliana JF - PLoS one N2 - To contribute to a further insight into heterosis we applied an integrative analysis to a systems biological network approach and a quantitative genetics analysis towards biomass heterosis in early Arabidopsis thaliana development. The study was performed on the parental accessions C24 and Col-0 and the reciprocal crosses. In an over-representation analysis it was tested if the overlap between the resulting gene lists of the two approaches is significantly larger than expected by chance. Top ranked genes in the results list of the systems biological analysis were significantly over-represented in the heterotic QTL candidate regions for either hybrid as well as regarding mid-parent and best-parent heterosis. This suggests that not only a few but rather several genes that influence biomass heterosis are located within each heterotic QTL region. Furthermore, the overlapping resulting genes of the two integrated approaches were particularly enriched in biomass related pathways. A chromosome-wise over-representation analysis gave rise to the hypothesis that chromosomes number 2 and 4 probably carry a majority of the genes involved in biomass heterosis in the early development of Arabidopsis thaliana. Y1 - 2012 U6 - https://doi.org/10.1371/journal.pone.0049951 SN - 1932-6203 VL - 7 IS - 11 PB - PLoS CY - San Fransisco ER - TY - JOUR A1 - Meyer, Rhonda C. A1 - Witucka-Wall, Hanna A1 - Becher, Martina A1 - Blacha, Anna Maria A1 - Boudichevskaia, Anastassia A1 - Dörmann, Peter A1 - Fiehn, Oliver A1 - Friedel, Svetlana A1 - von Korff, Maria A1 - Lisec, Jan A1 - Melzer, Michael A1 - Repsilber, Dirk A1 - Schmidt, Renate A1 - Scholz, Matthias A1 - Selbig, Joachim A1 - Willmitzer, Lothar A1 - Altmann, Thomas T1 - Heterosis manifestation during early Arabidopsis seedling development is characterized by intermediate gene expression and enhanced metabolic activity in the hybrids JF - The plant journal N2 - Heterosis-associated cellular and molecular processes were analyzed in seeds and seedlings of Arabidopsis thaliana accessions Col-0 and C24 and their heterotic hybrids. Microscopic examination revealed no advantages in terms of hybrid mature embryo organ sizes or cell numbers. Increased cotyledon sizes were detectable 4 days after sowing. Growth heterosis results from elevated cell sizes and numbers, and is well established at 10 days after sowing. The relative growth rates of hybrid seedlings were most enhanced between 3 and 4 days after sowing. Global metabolite profiling and targeted fatty acid analysis revealed maternal inheritance patterns for a large proportion of metabolites in the very early stages. During developmental progression, the distribution shifts to dominant, intermediate and heterotic patterns, with most changes occurring between 4 and 6 days after sowing. The highest incidence of heterotic patterns coincides with establishment of size differences at 4 days after sowing. In contrast, overall transcript patterns at 4, 6 and 10 days after sowing are characterized by intermediate to dominant patterns, with parental transcript levels showing the largest differences. Overall, the results suggest that, during early developmental stages, intermediate gene expression and higher metabolic activity in the hybrids compared to the parents lead to better resource efficiency, and therefore enhanced performance in the hybrids. KW - heterosis KW - seedlings KW - metabolite profiling KW - transcript profiling KW - morphological analysis KW - Arabidopsis thaliana KW - biomass Y1 - 2012 U6 - https://doi.org/10.1111/j.1365-313X.2012.05021.x SN - 0960-7412 VL - 71 IS - 4 SP - 669 EP - 683 PB - Wiley-Blackwell CY - Hoboken ER -