@misc{ChristakoudiPagoniFerrarietal.2020,
  author    = {Christakoudi, Sofia and Pagoni, Panagiota and Ferrari, Pietro and Cross, Amanda J. and Tzoulaki, Ioanna and Muller, David C. and Weiderpass, Elisabete and Freisling, Heinz and Murphy, Neil and Dossus, Laure and Turzanski Fortner, Renee and Agudo, Antonio and Overvad, Kim and Perez-Cornago, Aurora and Key, Timothy J. and Brennan, Paul and Johansson, Mattias and Tjonneland, Anne and Halkjaer, Jytte and Boutron-Ruault, Marie-Christine and Artaud, Fanny and Severi, Gianluca and Kaaks, Rudolf and Schulze, Matthias Bernd and Bergmann, Manuela M. and Masala, Giovanna and Grioni, Sara and Simeon, Vittorio and Tumino, Rosario and Sacerdote, Carlotta and Skeie, Guri and Rylander, Charlotta and Borch, Kristin Benjaminsen and Quiros, J. Ramon and Rodriguez-Barranco, Miguel and Chirlaque, Maria-Dolores and Ardanaz, Eva and Amiano, Pilar and Drake, Isabel and Stocks, Tanja and Haggstrom, Christel and Harlid, Sophia and Ellingjord-Dale, Merete and Riboli, Elio and Tsilidis, Konstantinos K.},
  title     = {Weight change in middle adulthood and risk of cancer in the European Prospective Investigation into Cancer and Nutrition (EPIC) cohort},
  series = {Zweitver{\"o}ffentlichungen der Universit{\"a}t Potsdam : Mathematisch-Naturwissenschaftliche Reihe},
  journal   = {Zweitver{\"o}ffentlichungen der Universit{\"a}t Potsdam : Mathematisch-Naturwissenschaftliche Reihe},
  number    = {7},
  issn      = {1866-8372},
  doi       = {10.25932/publishup-57360},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-573609},
  pages     = {17},
  year      = {2020},
  abstract  = {Obesity is a risk factor for several major cancers. Associations of weight change in middle adulthood with cancer risk, however, are less clear. We examined the association of change in weight and body mass index (BMI) category during middle adulthood with 42 cancers, using multivariable Cox proportional hazards models in the European Prospective Investigation into Cancer and Nutrition cohort. Of 241 323 participants (31\% men), 20\% lost and 32\% gained weight (>0.4 to 5.0 kg/year) during 6.9 years (average). During 8.0 years of follow-up after the second weight assessment, 20 960 incident cancers were ascertained. Independent of baseline BMI, weight gain (per one kg/year increment) was positively associated with cancer of the corpus uteri (hazard ratio [HR] = 1.14; 95\% confidence interval: 1.05-1.23). Compared to stable weight (+/- 0.4 kg/year), weight gain (>0.4 to 5.0 kg/year) was positively associated with cancers of the gallbladder and bile ducts (HR = 1.41; 1.01-1.96), postmenopausal breast (HR = 1.08; 1.00-1.16) and thyroid (HR = 1.40; 1.04-1.90). Compared to maintaining normal weight, maintaining overweight or obese BMI (World Health Organisation categories) was positively associated with most obesity-related cancers. Compared to maintaining the baseline BMI category, weight gain to a higher BMI category was positively associated with cancers of the postmenopausal breast (HR = 1.19; 1.06-1.33), ovary (HR = 1.40; 1.04-1.91), corpus uteri (HR = 1.42; 1.06-1.91), kidney (HR = 1.80; 1.20-2.68) and pancreas in men (HR = 1.81; 1.11-2.95). Losing weight to a lower BMI category, however, was inversely associated with cancers of the corpus uteri (HR = 0.40; 0.23-0.69) and colon (HR = 0.69; 0.52-0.92). Our findings support avoiding weight gain and encouraging weight loss in middle adulthood.},
  language  = {en}
}
@article{WinckArvidssonMauricioRianoPachonetal.2013,
  author    = {Winck, Flavia Vischi and Arvidsson, Samuel Janne and Mauricio Riano-Pachon, Diego and Hempel, Sabrina and Koseska, Aneta and Nikoloski, Zoran and Urbina Gomez, David Alejandro and Rupprecht, Jens and M{\"u}ller-R{\"o}ber, Bernd},
  title     = {Genome-wide identification of regulatory elements and reconstruction of gene regulatory networks of the green alga chlamydomonas reinhardtii under carbon deprivation},
  series = {PLoS one},
  volume    = {8},
  journal   = {PLoS one},
  number    = {11},
  publisher = {PLoS},
  address   = {San Fransisco},
  issn      = {1932-6203},
  doi       = {10.1371/journal.pone.0079909},
  pages     = {16},
  year      = {2013},
  abstract  = {The unicellular green alga Chlamydomonas reinhardtii is a long-established model organism for studies on photosynthesis and carbon metabolism-related physiology. Under conditions of air-level carbon dioxide concentration [CO2], a carbon concentrating mechanism (CCM) is induced to facilitate cellular carbon uptake. CCM increases the availability of carbon dioxide at the site of cellular carbon fixation. To improve our understanding of the transcriptional control of the CCM, we employed FAIRE-seq (formaldehyde-assisted Isolation of Regulatory Elements, followed by deep sequencing) to determine nucleosome-depleted chromatin regions of algal cells subjected to carbon deprivation. Our FAIRE data recapitulated the positions of known regulatory elements in the promoter of the periplasmic carbonic anhydrase (Cah1) gene, which is upregulated during CCM induction, and revealed new candidate regulatory elements at a genome-wide scale. In addition, time series expression patterns of 130 transcription factor (TF) and transcription regulator (TR) genes were obtained for cells cultured under photoautotrophic condition and subjected to a shift from high to low [CO2]. Groups of co-expressed genes were identified and a putative directed gene-regulatory network underlying the CCM was reconstructed from the gene expression data using the recently developed IOTA (inner composition alignment) method. Among the candidate regulatory genes, two members of the MYB-related TF family, Lcr1 (Low-CO2 response regulator 1) and Lcr2 (Low-CO2 response regulator 2), may play an important role in down-regulating the expression of a particular set of TF and TR genes in response to low [CO2]. The results obtained provide new insights into the transcriptional control of the CCM and revealed more than 60 new candidate regulatory genes. Deep sequencing of nucleosome-depleted genomic regions indicated the presence of new, previously unknown regulatory elements in the C. reinhardtii genome. Our work can serve as a basis for future functional studies of transcriptional regulator genes and genomic regulatory elements in Chlamydomonas.},
  language  = {en}
}
@article{OmranianEloundouMbebiMuellerRoeberetal.2016,
  author    = {Omranian, Nooshin and Eloundou-Mbebi, Jeanne Marie Onana and M{\"u}ller-R{\"o}ber, Bernd and Nikoloski, Zoran},
  title     = {Gene regulatory network inference using fused LASSO on multiple data sets},
  series = {Scientific reports},
  volume    = {6},
  journal   = {Scientific reports},
  publisher = {Nature Publ. Group},
  address   = {London},
  issn      = {2045-2322},
  doi       = {10.1038/srep20533},
  pages     = {14},
  year      = {2016},
  abstract  = {Devising computational methods to accurately reconstruct gene regulatory networks given gene expression data is key to systems biology applications. Here we propose a method for reconstructing gene regulatory networks by simultaneous consideration of data sets from different perturbation experiments and corresponding controls. The method imposes three biologically meaningful constraints: (1) expression levels of each gene should be explained by the expression levels of a small number of transcription factor coding genes, (2) networks inferred from different data sets should be similar with respect to the type and number of regulatory interactions, and (3) relationships between genes which exhibit similar differential behavior over the considered perturbations should be favored. We demonstrate that these constraints can be transformed in a fused LASSO formulation for the proposed method. The comparative analysis on transcriptomics time-series data from prokaryotic species, Escherichia coli and Mycobacterium tuberculosis, as well as a eukaryotic species, mouse, demonstrated that the proposed method has the advantages of the most recent approaches for regulatory network inference, while obtaining better performance and assigning higher scores to the true regulatory links. The study indicates that the combination of sparse regression techniques with other biologically meaningful constraints is a promising framework for gene regulatory network reconstructions.},
  language  = {en}
}
@article{OmranianKlieMuellerRoeberetal.2013,
  author    = {Omranian, Nooshin and Klie, Sebastian and M{\"u}ller-R{\"o}ber, Bernd and Nikoloski, Zoran},
  title     = {Network-based segmentation of biological multivariate time series},
  series = {PLoS one},
  volume    = {8},
  journal   = {PLoS one},
  number    = {5},
  publisher = {PLoS},
  address   = {San Fransisco},
  issn      = {1932-6203},
  doi       = {10.1371/journal.pone.0062974},
  pages     = {10},
  year      = {2013},
  abstract  = {Molecular phenotyping technologies (e.g., transcriptomics, proteomics, and metabolomics) offer the possibility to simultaneously obtain multivariate time series (MTS) data from different levels of information processing and metabolic conversions in biological systems. As a result, MTS data capture the dynamics of biochemical processes and components whose couplings may involve different scales and exhibit temporal changes. Therefore, it is important to develop methods for determining the time segments in MTS data, which may correspond to critical biochemical events reflected in the coupling of the system's components. Here we provide a novel network-based formalization of the MTS segmentation problem based on temporal dependencies and the covariance structure of the data. We demonstrate that the problem of partitioning MTS data into k segments to maximize a distance function, operating on polynomially computable network properties, often used in analysis of biological network, can be efficiently solved. To enable biological interpretation, we also propose a breakpoint-penalty (BP-penalty) formulation for determining MTS segmentation which combines a distance function with the number/length of segments. Our empirical analyses of synthetic benchmark data as well as time-resolved transcriptomics data from the metabolic and cell cycles of Saccharomyces cerevisiae demonstrate that the proposed method accurately infers the phases in the temporal compartmentalization of biological processes. In addition, through comparison on the same data sets, we show that the results from the proposed formalization of the MTS segmentation problem match biological knowledge and provide more rigorous statistical support in comparison to the contending state-of-the-art methods.},
  language  = {en}
}
@article{OmranianMuellerRoeberNikoloski2015,
  author    = {Omranian, Nooshin and M{\"u}ller-R{\"o}ber, Bernd and Nikoloski, Zoran},
  title     = {Segmentation of biological multivariate time-series data},
  series = {Scientific reports},
  volume    = {5},
  journal   = {Scientific reports},
  publisher = {Nature Publ. Group},
  address   = {London},
  issn      = {2045-2322},
  doi       = {10.1038/srep08937},
  pages     = {6},
  year      = {2015},
  abstract  = {Time-series data from multicomponent systems capture the dynamics of the ongoing processes and reflect the interactions between the components. The progression of processes in such systems usually involves check-points and events at which the relationships between the components are altered in response to stimuli. Detecting these events together with the implicated components can help understand the temporal aspects of complex biological systems. Here we propose a regularized regression-based approach for identifying breakpoints and corresponding segments from multivariate time-series data. In combination with techniques from clustering, the approach also allows estimating the significance of the determined breakpoints as well as the key components implicated in the emergence of the breakpoints. Comparative analysis with the existing alternatives demonstrates the power of the approach to identify biologically meaningful breakpoints in diverse time-resolved transcriptomics data sets from the yeast Saccharomyces cerevisiae and the diatom Thalassiosira pseudonana.},
  language  = {en}
}
@article{OmranianMuellerRoeberNikoloski2012,
  author    = {Omranian, Nooshin and M{\"u}ller-R{\"o}ber, Bernd and Nikoloski, Zoran},
  title     = {PageRank-based identification of signaling crosstalk from transcriptomics data the case of Arabidopsis thaliana},
  series = {Molecular BioSystems},
  volume    = {8},
  journal   = {Molecular BioSystems},
  number    = {4},
  publisher = {Royal Society of Chemistry},
  address   = {Cambridge},
  issn      = {1742-206X},
  doi       = {10.1039/c2mb05365a},
  pages     = {1121 -- 1127},
  year      = {2012},
  abstract  = {The levels of cellular organization, from gene transcription to translation to protein-protein interaction and metabolism, operate via tightly regulated mutual interactions, facilitating organismal adaptability and various stress responses. Characterizing the mutual interactions between genes, transcription factors, and proteins involved in signaling, termed crosstalk, is therefore crucial for understanding and controlling cells' functionality. We aim at using high-throughput transcriptomics data to discover previously unknown links between signaling networks. We propose and analyze a novel method for crosstalk identification which relies on transcriptomics data and overcomes the lack of complete information for signaling pathways in Arabidopsis thaliana. Our method first employs a network-based transformation of the results from the statistical analysis of differential gene expression in given groups of experiments under different signal-inducing conditions. The stationary distribution of a random walk (similar to the PageRank algorithm) on the constructed network is then used to determine the putative transcripts interrelating different signaling pathways. With the help of the proposed method, we analyze a transcriptomics data set including experiments from four different stresses/signals: nitrate, sulfur, iron, and hormones. We identified promising gene candidates, downstream of the transcription factors (TFs), associated to signaling crosstalk, which were validated through literature mining. In addition, we conduct a comparative analysis with the only other available method in this field which used a biclustering-based approach. Surprisingly, the biclustering-based approach fails to robustly identify any candidate genes involved in the crosstalk of the analyzed signals. We demonstrate that our proposed method is more robust in identifying gene candidates involved downstream of the signaling crosstalk for species for which large transcriptomics data sets, normalized with the same techniques, are available. Moreover, unlike approaches based on biclustering, our approach does not rely on any hidden parameters.},
  language  = {en}
}
@article{EngqvistSchmitzGertzmannetal.2015,
  author    = {Engqvist, Martin K. M. and Schmitz, Jessica and Gertzmann, Anke and Florian, Alexandra and Jaspert, Nils and Arif, Muhammad and Balazadeh, Salma and M{\"u}ller-R{\"o}ber, Bernd and Fernie, Alisdair and Maurino, Veronica G.},
  title     = {GLYCOLATE OXIDASE3, a Glycolate Oxidase Homolog of Yeast L-Lactate Cytochrome c Oxidoreductase, Supports L-Lactate Oxidation in Roots of Arabidopsis},
  series = {Plant physiology : an international journal devoted to physiology, biochemistry, cellular and molecular biology, biophysics and environmental biology of plants},
  volume    = {169},
  journal   = {Plant physiology : an international journal devoted to physiology, biochemistry, cellular and molecular biology, biophysics and environmental biology of plants},
  number    = {2},
  publisher = {American Society of Plant Physiologists},
  address   = {Rockville},
  issn      = {0032-0889},
  doi       = {10.1104/pp.15.01003},
  pages     = {1042 -- 1061},
  year      = {2015},
  abstract  = {In roots of Arabidopsis (Arabidopsis thaliana), L-lactate is generated by the reduction of pyruvate via L-lactate dehydrogenase, but this enzyme does not efficiently catalyze the reverse reaction. Here, we identify the Arabidopsis glycolate oxidase (GOX) paralogs GOX1, GOX2, and GOX3 as putative L-lactate-metabolizing enzymes based on their homology to CYB2, the L-lactate cytochrome c oxidoreductase from the yeast Saccharomyces cerevisiae. We found that GOX3 uses L-lactate with a similar efficiency to glycolate; in contrast, the photorespiratory isoforms GOX1 and GOX2, which share similar enzymatic properties, use glycolate with much higher efficiencies than L-lactate. The key factor making GOX3 more efficient with L-lactate than GOX1 and GOX2 is a 5- to 10-fold lower Km for the substrate. Consequently, only GOX3 can efficiently metabolize L-lactate at low intracellular concentrations. Isotope tracer experiments as well as substrate toxicity tests using GOX3 loss-of-function and overexpressor plants indicate that L-lactate is metabolized in vivo by GOX3. Moreover, GOX3 rescues the lethal growth phenotype of a yeast strain lacking CYB2, which cannot grow on L-lactate as a sole carbon source. GOX3 is predominantly present in roots and mature to aging leaves but is largely absent from young photosynthetic leaves, indicating that it plays a role predominantly in heterotrophic rather than autotrophic tissues, at least under standard growth conditions. In roots of plants grown under normoxic conditions, loss of function of GOX3 induces metabolic rearrangements that mirror wild-type responses under hypoxia. Thus, we identified GOX3 as the enzyme that metabolizes L-lactate to pyruvate in vivo and hypothesize that it may ensure the sustainment of low levels of L-lactate after its formation under normoxia.},
  language  = {en}
}
@article{WangTohgeIvakovetal.2015,
  author    = {Wang, Ting and Tohge, Takayuki and Ivakov, Alexander and M{\"u}ller-R{\"o}ber, Bernd and Fernie, Alisdair and Mutwil, Marek and Schippers, Jos H. M. and Persson, Staffan},
  title     = {Salt-Related MYB1 Coordinates Abscisic Acid Biosynthesis and Signaling during Salt Stress in Arabidopsis},
  series = {Plant physiology : an international journal devoted to physiology, biochemistry, cellular and molecular biology, biophysics and environmental biology of plants},
  volume    = {169},
  journal   = {Plant physiology : an international journal devoted to physiology, biochemistry, cellular and molecular biology, biophysics and environmental biology of plants},
  number    = {2},
  publisher = {American Society of Plant Physiologists},
  address   = {Rockville},
  issn      = {0032-0889},
  doi       = {10.1104/pp.15.00962},
  pages     = {1027 -- +},
  year      = {2015},
  abstract  = {Abiotic stresses, such as salinity, cause global yield loss of all major crop plants. Factors and mechanisms that can aid in plant breeding for salt stress tolerance are therefore of great importance for food and feed production. Here, we identified a MYB-like transcription factor, Salt-Related MYB1 (SRM1), that negatively affects Arabidopsis (Arabidopsis thaliana) seed germination under saline conditions by regulating the levels of the stress hormone abscisic acid (ABA). Accordingly, several ABA biosynthesis and signaling genes act directly downstream of SRM1, including SALT TOLERANT1/NINE-CIS-EPOXYCAROTENOID DIOXYGENASE3, RESPONSIVE TO DESICCATION26, and Arabidopsis NAC DOMAIN CONTAINING PROTEIN19. Furthermore, SRM1 impacts vegetative growth and leaf shape. We show that SRM1 is an important transcriptional regulator that directly targets ABA biosynthesis and signaling-related genes and therefore may be regarded as an important regulator of ABA-mediated salt stress tolerance.},
  language  = {en}
}
@misc{DurgudGuptaIvanovetal.2018,
  author    = {Durgud, Meriem and Gupta, Saurabh and Ivanov, Ivan and Omidbakhshfard, Mohammad Amin and Benina, Maria and Alseekh, Saleh and Staykov, Nikola and Hauenstein, Mareike and Dijkwel, Paul P. and Hortensteiner, Stefan and Toneva, Valentina and Brotman, Yariv and Fernie, Alisdair and M{\"u}ller-R{\"o}ber, Bernd and Gechev, Tsanko S.},
  title     = {Molecular mechanisms preventing senescence in response to prolonged darkness in a desiccation-tolerant plant},
  series = {Postprints der Universit{\"a}t Potsdam Mathematisch-Naturwissenschaftliche Reihe},
  journal   = {Postprints der Universit{\"a}t Potsdam Mathematisch-Naturwissenschaftliche Reihe},
  number    = {778},
  doi       = {10.25932/publishup-43758},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-437588},
  pages     = {1319 -- 1338},
  year      = {2018},
  abstract  = {The desiccation-tolerant plant Haberlea rhodopensis can withstand months of darkness without any visible senescence. Here, we investigated the molecular mechanisms of this adaptation to prolonged (30 d) darkness and subsequent return to light. H. rhodopensis plants remained green and viable throughout the dark treatment. Transcriptomic analysis revealed that darkness regulated several transcription factor (TF) genes. Stress-and autophagy-related TFs such as ERF8, HSFA2b, RD26, TGA1, and WRKY33 were up-regulated, while chloroplast-and flowering-related TFs such as ATH1, COL2, COL4, RL1, and PTAC7 were repressed. PHYTOCHROME INTERACTING FACTOR4, a negative regulator of photomorphogenesis and promoter of senescence, also was down-regulated. In response to darkness, most of the photosynthesis-and photorespiratory-related genes were strongly down-regulated, while genes related to autophagy were up-regulated. This occurred concomitant with the induction of SUCROSE NON-FERMENTING1-RELATED PROTEIN KINASES (SnRK1) signaling pathway genes, which regulate responses to stress-induced starvation and autophagy. Most of the genes associated with chlorophyll catabolism, which are induced by darkness in dark-senescing species, were either unregulated (PHEOPHORBIDE A OXYGENASE, PAO; RED CHLOROPHYLL CATABOLITE REDUCTASE, RCCR) or repressed (STAY GREEN-LIKE, PHEOPHYTINASE, and NON-YELLOW COLORING1). Metabolite profiling revealed increases in the levels of many amino acids in darkness, suggesting increased protein degradation. In darkness, levels of the chloroplastic lipids digalactosyldiacylglycerol, monogalactosyldiacylglycerol, phosphatidylglycerol, and sulfoquinovosyldiacylglycerol decreased, while those of storage triacylglycerols increased, suggesting degradation of chloroplast membrane lipids and their conversion to triacylglycerols for use as energy and carbon sources. Collectively, these data show a coordinated response to darkness, including repression of photosynthetic, photorespiratory, flowering, and chlorophyll catabolic genes, induction of autophagy and SnRK1 pathways, and metabolic reconfigurations that enable survival under prolonged darkness.},
  language  = {en}
}
@misc{MaZhangTurečkovaetal.2018,
  author    = {Ma, Xuemin and Zhang, Youjun and Turečkov{\´a}, Veronika and Xue, Gang-Ping and Fernie, Alisdair and M{\"u}ller-R{\"o}ber, Bernd and Balazadeh, Salma},
  title     = {The NAC transcription factor SlNAP2 regulates leaf senescence and fruit yield in tomato},
  series = {Postprints der Universit{\"a}t Potsdam Mathematisch-Naturwissenschaftliche Reihe},
  journal   = {Postprints der Universit{\"a}t Potsdam Mathematisch-Naturwissenschaftliche Reihe},
  number    = {787},
  issn      = {1866-8372},
  doi       = {10.25932/publishup-43764},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-437643},
  pages     = {17},
  year      = {2018},
  abstract  = {Leaf senescence is an essential physiological process in plants that supports the recycling of nitrogen and other nutrients to support the growth of developing organs, including young leaves, seeds, and fruits. Thus, the regulation of senescence is crucial for evolutionary success in wild populations and for increasing yield in crops. Here, we describe the influence of a NAC transcription factor, SlNAP2 (Solanum lycopersicum NAC-like, activated by Apetala3/Pistillata), that controls both leaf senescence and fruit yield in tomato (S. lycopersicum). SlNAP2 expression increases during age-dependent and dark-induced leaf senescence. We demonstrate that SlNAP2 activates SlSAG113 (S. lycopersicum SENESCENCE-ASSOCIATED GENE113), a homolog of Arabidopsis (Arabidopsis thaliana) SAG113, chlorophyll degradation genes such as SlSGR1 (S. lycopersicum senescence-inducible chloroplast stay-green protein 1) and SlPAO (S. lycopersicum pheide a oxygenase), and other downstream targets by directly binding to their promoters, thereby promoting leaf senescence. Furthermore, SlNAP2 directly controls the expression of genes important for abscisic acid (ABA) biosynthesis, S. lycopersicum 9-cis-epoxycarotenoid dioxygenase 1 (SlNCED1); transport, S. lycopersicum ABC transporter G family member 40 (SlABCG40); and degradation, S. lycopersicum ABA 8'-hydroxylase (SlCYP707A2), indicating that SlNAP2 has a complex role in establishing ABA homeostasis during leaf senescence. Inhibiting SlNAP2 expression in transgenic tomato plants impedes leaf senescence but enhances fruit yield and sugar content likely due to prolonged leaf photosynthesis in aging tomato plants. Our data indicate that SlNAP2 has a central role in controlling leaf senescence and fruit yield in tomato.},
  language  = {en}
}