@article{WarringtonBeaumontHorikoshietal.2019,
  author    = {Warrington, Nicole and Beaumont, Robin and Horikoshi, Momoko and Day, Felix R. and Helgeland, {\O}yvind and Laurin, Charles and Bacelis, Jonas and Peng, Shouneng and Hao, Ke and Feenstra, Bjarke and Wood, Andrew R. and Mahajan, Anubha and Tyrrell, Jessica and Robertson, Neil R. and Rayner, N. William and Qiao, Zhen and Moen, Gunn-Helen and Vaudel, Marc and Marsit, Carmen and Chen, Jia and Nodzenski, Michael and Schnurr, Theresia M. and Zafarmand, Mohammad Hadi and Bradfield, Jonathan P. and Grarup, Niels and Kooijman, Marjolein N. and Li-Gao, Ruifang and Geller, Frank and Ahluwalia, Tarunveer Singh and Paternoster, Lavinia and Rueedi, Rico and Huikari, Ville and Hottenga, Jouke-Jan and Lyytik{\"a}inen, Leo-Pekka and Cavadino, Alana and Metrustry, Sarah and Cousminer, Diana L. and Wu, Ying and Thiering, Elisabeth Paula and Wang, Carol A. and Have, Christian Theil and Vilor-Tejedor, Natalia and Joshi, Peter K. and Painter, Jodie N. and Ntalla, Ioanna and Myhre, Ronny and Pitk{\"a}nen, Niina and van Leeuwen, Elisabeth M. and Joro, Raimo and Lagou, Vasiliki and Richmond, Rebecca C. and Espinosa, Ana and Barton, Sheila J. and Inskip, Hazel M. and Holloway, John W. and Santa-Marina, Loreto and Estivill, Xavier and Ang, Wei and Marsh, Julie A. and Reichetzeder, Christoph and Marullo, Letizia and Hocher, Berthold and Lunetta, Kathryn L. and Murabito, Joanne M. and Relton, Caroline L. and Kogevinas, Manolis and Chatzi, Leda and Allard, Catherine and Bouchard, Luigi and Hivert, Marie-France and Zhang, Ge and Muglia, Louis J. and Heikkinen, Jani and Morgen, Camilla S. and van Kampen, Antoine H. C. and van Schaik, Barbera D. C. and Mentch, Frank D. and Langenberg, Claudia and Scott, Robert A. and Zhao, Jing Hua and Hemani, Gibran and Ring, Susan M. and Bennett, Amanda J. and Gaulton, Kyle J. and Fernandez-Tajes, Juan and van Zuydam, Natalie R. and Medina-Gomez, Carolina and de Haan, Hugoline G. and Rosendaal, Frits R. and Kutalik, Zolt{\´a}n and Marques-Vidal, Pedro and Das, Shikta and Willemsen, Gonneke and Mbarek, Hamdi and M{\"u}ller-Nurasyid, Martina and Standl, Marie and Appel, Emil V. R. and Fonvig, Cilius Esmann and Trier, Caecilie and van Beijsterveldt, Catharina E. M. and Murcia, Mario and Bustamante, Mariona and Bon{\`a}s-Guarch, S{\´i}lvia and Hougaard, David M. and Mercader, Josep M. and Linneberg, Allan and Schraut, Katharina E. and Lind, Penelope A. and Medland, Sarah Elizabeth and Shields, Beverley M. and Knight, Bridget A. and Chai, Jin-Fang and Panoutsopoulou, Kalliope and Bartels, Meike and S{\´a}nchez, Friman and Stokholm, Jakob and Torrents, David and Vinding, Rebecca K. and Willems, Sara M. and Atalay, Mustafa and Chawes, Bo L. and Kovacs, Peter and Prokopenko, Inga and Tuke, Marcus A. and Yaghootkar, Hanieh and Ruth, Katherine S. and Jones, Samuel E. and Loh, Po-Ru and Murray, Anna and Weedon, Michael N. and T{\"o}njes, Anke and Stumvoll, Michael and Michaelsen, Kim Fleischer and Eloranta, Aino-Maija and Lakka, Timo A. and van Duijn, Cornelia M. and Kiess, Wieland and Koerner, Antje and Niinikoski, Harri and Pahkala, Katja and Raitakari, Olli T. and Jacobsson, Bo and Zeggini, Eleftheria and Dedoussis, George V. and Teo, Yik-Ying and Saw, Seang-Mei and Montgomery, Grant W. and Campbell, Harry and Wilson, James F. and Vrijkotte, Tanja G. M. and Vrijheid, Martine and de Geus, Eco J. C. N. and Hayes, M. Geoffrey and Kadarmideen, Haja N. and Holm, Jens-Christian and Beilin, Lawrence J. and Pennell, Craig E. and Heinrich, Joachim and Adair, Linda S. and Borja, Judith B. and Mohlke, Karen L. and Eriksson, Johan G. and Widen, Elisabeth E. and Hattersley, Andrew T. and Spector, Tim D. and Kaehoenen, Mika and Viikari, Jorma S. and Lehtimaeki, Terho and Boomsma, Dorret I. and Sebert, Sylvain and Vollenweider, Peter and Sorensen, Thorkild I. A. and Bisgaard, Hans and Bonnelykke, Klaus and Murray, Jeffrey C. and Melbye, Mads and Nohr, Ellen A. and Mook-Kanamori, Dennis O. and Rivadeneira, Fernando and Hofman, Albert and Felix, Janine F. and Jaddoe, Vincent W. V. and Hansen, Torben and Pisinger, Charlotta and Vaag, Allan A. and Pedersen, Oluf and Uitterlinden, Andre G. and Jarvelin, Marjo-Riitta and Power, Christine and Hypponen, Elina and Scholtens, Denise M. and Lowe, William L. and Smith, George Davey and Timpson, Nicholas J. and Morris, Andrew P. and Wareham, Nicholas J. and Hakonarson, Hakon and Grant, Struan F. A. and Frayling, Timothy M. and Lawlor, Debbie A. and Njolstad, Pal R. and Johansson, Stefan and Ong, Ken K. and McCarthy, Mark I. and Perry, John R. B. and Evans, David M. and Freathy, Rachel M.},
  title     = {Maternal and fetal genetic effects on birth weight and their relevance to cardio-metabolic risk factors},
  series = {Nature genetics},
  volume    = {51},
  journal   = {Nature genetics},
  number    = {5},
  publisher = {Nature Publ. Group},
  address   = {New York},
  organization    = {EGG Consortium},
  issn      = {1061-4036},
  pages     = {804 -- +},
  year      = {2019},
  abstract  = {Birth weight variation is influenced by fetal and maternal genetic and non-genetic factors, and has been reproducibly associated with future cardio-metabolic health outcomes. In expanded genome-wide association analyses of own birth weight (n = 321,223) and offspring birth weight (n = 230,069 mothers), we identified 190 independent association signals (129 of which are novel). We used structural equation modeling to decompose the contributions of direct fetal and indirect maternal genetic effects, then applied Mendelian randomization to illuminate causal pathways. For example, both indirect maternal and direct fetal genetic effects drive the observational relationship between lower birth weight and higher later blood pressure: maternal blood pressure-raising alleles reduce offspring birth weight, but only direct fetal effects of these alleles, once inherited, increase later offspring blood pressure. Using maternal birth weight-lowering genotypes to proxy for an adverse intrauterine environment provided no evidence that it causally raises offspring blood pressure, indicating that the inverse birth weight-blood pressure association is attributable to genetic effects, and not to intrauterine programming.},
  language  = {en}
}
@article{AartsAndersonAndersonetal.2015,
  author    = {Aarts, Alexander A. and Anderson, Joanna E. and Anderson, Christopher J. and Attridge, Peter R. and Attwood, Angela and Axt, Jordan and Babel, Molly and Bahnik, Stepan and Baranski, Erica and Barnett-Cowan, Michael and Bartmess, Elizabeth and Beer, Jennifer and Bell, Raoul and Bentley, Heather and Beyan, Leah and Binion, Grace and Borsboom, Denny and Bosch, Annick and Bosco, Frank A. and Bowman, Sara D. and Brandt, Mark J. and Braswell, Erin and Brohmer, Hilmar and Brown, Benjamin T. and Brown, Kristina and Bruening, Jovita and Calhoun-Sauls, Ann and Callahan, Shannon P. and Chagnon, Elizabeth and Chandler, Jesse and Chartier, Christopher R. and Cheung, Felix and Christopherson, Cody D. and Cillessen, Linda and Clay, Russ and Cleary, Hayley and Cloud, Mark D. and Cohn, Michael and Cohoon, Johanna and Columbus, Simon and Cordes, Andreas and Costantini, Giulio and Alvarez, Leslie D. Cramblet and Cremata, Ed and Crusius, Jan and DeCoster, Jamie and DeGaetano, Michelle A. and Della Penna, Nicolas and den Bezemer, Bobby and Deserno, Marie K. and Devitt, Olivia and Dewitte, Laura and Dobolyi, David G. and Dodson, Geneva T. and Donnellan, M. Brent and Donohue, Ryan and Dore, Rebecca A. and Dorrough, Angela and Dreber, Anna and Dugas, Michelle and Dunn, Elizabeth W. and Easey, Kayleigh and Eboigbe, Sylvia and Eggleston, Casey and Embley, Jo and Epskamp, Sacha and Errington, Timothy M. and Estel, Vivien and Farach, Frank J. and Feather, Jenelle and Fedor, Anna and Fernandez-Castilla, Belen and Fiedler, Susann and Field, James G. and Fitneva, Stanka A. and Flagan, Taru and Forest, Amanda L. and Forsell, Eskil and Foster, Joshua D. and Frank, Michael C. and Frazier, Rebecca S. and Fuchs, Heather and Gable, Philip and Galak, Jeff and Galliani, Elisa Maria and Gampa, Anup and Garcia, Sara and Gazarian, Douglas and Gilbert, Elizabeth and Giner-Sorolla, Roger and Gl{\"o}ckner, Andreas and G{\"o}llner, Lars and Goh, Jin X. and Goldberg, Rebecca and Goodbourn, Patrick T. and Gordon-McKeon, Shauna and Gorges, Bryan and Gorges, Jessie and Goss, Justin and Graham, Jesse and Grange, James A. and Gray, Jeremy and Hartgerink, Chris and Hartshorne, Joshua and Hasselman, Fred and Hayes, Timothy and Heikensten, Emma and Henninger, Felix and Hodsoll, John and Holubar, Taylor and Hoogendoorn, Gea and Humphries, Denise J. and Hung, Cathy O. -Y. and Immelman, Nathali and Irsik, Vanessa C. and Jahn, Georg and Jaekel, Frank and Jekel, Marc and Johannesson, Magnus and Johnson, Larissa G. and Johnson, David J. and Johnson, Kate M. and Johnston, William J. and Jonas, Kai and Joy-Gaba, Jennifer A. and Kappes, Heather Barry and Kelso, Kim and Kidwell, Mallory C. and Kim, Seung Kyung and Kirkhart, Matthew and Kleinberg, Bennett and Knezevic, Goran and Kolorz, Franziska Maria and Kossakowski, Jolanda J. and Krause, Robert Wilhelm and Krijnen, Job and Kuhlmann, Tim and Kunkels, Yoram K. and Kyc, Megan M. and Lai, Calvin K. and Laique, Aamir and Lakens, Daniel and Lane, Kristin A. and Lassetter, Bethany and Lazarevic, Ljiljana B. and LeBel, Etienne P. and Lee, Key Jung and Lee, Minha and Lemm, Kristi and Levitan, Carmel A. and Lewis, Melissa and Lin, Lin and Lin, Stephanie and Lippold, Matthias and Loureiro, Darren and Luteijn, Ilse and Mackinnon, Sean and Mainard, Heather N. and Marigold, Denise C. and Martin, Daniel P. and Martinez, Tylar and Masicampo, E. J. and Matacotta, Josh and Mathur, Maya and May, Michael and Mechin, Nicole and Mehta, Pranjal and Meixner, Johannes and Melinger, Alissa and Miller, Jeremy K. and Miller, Mallorie and Moore, Katherine and M{\"o}schl, Marcus and Motyl, Matt and M{\"u}ller, Stephanie M. and Munafo, Marcus and Neijenhuijs, Koen I. and Nervi, Taylor and Nicolas, Gandalf and Nilsonne, Gustav and Nosek, Brian A. and Nuijten, Michele B. and Olsson, Catherine and Osborne, Colleen and Ostkamp, Lutz and Pavel, Misha and Penton-Voak, Ian S. and Perna, Olivia and Pernet, Cyril and Perugini, Marco and Pipitone, R. Nathan and Pitts, Michael and Plessow, Franziska and Prenoveau, Jason M. and Rahal, Rima-Maria and Ratliff, Kate A. and Reinhard, David and Renkewitz, Frank and Ricker, Ashley A. and Rigney, Anastasia and Rivers, Andrew M. and Roebke, Mark and Rutchick, Abraham M. and Ryan, Robert S. and Sahin, Onur and Saide, Anondah and Sandstrom, Gillian M. and Santos, David and Saxe, Rebecca and Schlegelmilch, Rene and Schmidt, Kathleen and Scholz, Sabine and Seibel, Larissa and Selterman, Dylan Faulkner and Shaki, Samuel and Simpson, William B. and Sinclair, H. Colleen and Skorinko, Jeanine L. M. and Slowik, Agnieszka and Snyder, Joel S. and Soderberg, Courtney and Sonnleitner, Carina and Spencer, Nick and Spies, Jeffrey R. and Steegen, Sara and Stieger, Stefan and Strohminger, Nina and Sullivan, Gavin B. and Talhelm, Thomas and Tapia, Megan and te Dorsthorst, Anniek and Thomae, Manuela and Thomas, Sarah L. and Tio, Pia and Traets, Frits and Tsang, Steve and Tuerlinckx, Francis and Turchan, Paul and Valasek, Milan and Van Aert, Robbie and van Assen, Marcel and van Bork, Riet and van de Ven, Mathijs and van den Bergh, Don and van der Hulst, Marije and van Dooren, Roel and van Doorn, Johnny and van Renswoude, Daan R. and van Rijn, Hedderik and Vanpaemel, Wolf and Echeverria, Alejandro Vasquez and Vazquez, Melissa and Velez, Natalia and Vermue, Marieke and Verschoor, Mark and Vianello, Michelangelo and Voracek, Martin and Vuu, Gina and Wagenmakers, Eric-Jan and Weerdmeester, Joanneke and Welsh, Ashlee and Westgate, Erin C. and Wissink, Joeri and Wood, Michael and Woods, Andy and Wright, Emily and Wu, Sining and Zeelenberg, Marcel and Zuni, Kellylynn},
  title     = {Estimating the reproducibility of psychological science},
  series = {Science},
  volume    = {349},
  journal   = {Science},
  number    = {6251},
  publisher = {American Assoc. for the Advancement of Science},
  address   = {Washington},
  organization    = {Open Sci Collaboration},
  issn      = {1095-9203},
  doi       = {10.1126/science.aac4716},
  pages     = {8},
  year      = {2015},
  abstract  = {Reproducibility is a defining feature of science, but the extent to which it characterizes current research is unknown. We conducted replications of 100 experimental and correlational studies published in three psychology journals using high-powered designs and original materials when available. Replication effects were half the magnitude of original effects, representing a substantial decline. Ninety-seven percent of original studies had statistically significant results. Thirty-six percent of replications had statistically significant results; 47\% of original effect sizes were in the 95\% confidence interval of the replication effect size; 39\% of effects were subjectively rated to have replicated the original result; and if no bias in original results is assumed, combining original and replication results left 68\% with statistically significant effects. Correlational tests suggest that replication success was better predicted by the strength of original evidence than by characteristics of the original and replication teams.},
  language  = {en}
}
@article{FeherWhelanMueller2012,
  author    = {Feher, Kristen and Whelan, James and M{\"u}ller, Samuel},
  title     = {Exploring multicollinearity using a random matrix theory approach},
  series = {Statistical applications in genetics and molecular biology},
  volume    = {11},
  journal   = {Statistical applications in genetics and molecular biology},
  number    = {3},
  publisher = {De Gruyter},
  address   = {Berlin},
  issn      = {1544-6115},
  doi       = {10.1515/1544-6115.1668},
  pages     = {35},
  year      = {2012},
  abstract  = {Clustering of gene expression data is often done with the latent aim of dimension reduction, by finding groups of genes that have a common response to potentially unknown stimuli. However, what is poorly understood to date is the behaviour of a low dimensional signal embedded in high dimensions. This paper introduces a multicollinear model which is based on random matrix theory results, and shows potential for the characterisation of a gene cluster's correlation matrix. This model projects a one dimensional signal into many dimensions and is based on the spiked covariance model, but rather characterises the behaviour of the corresponding correlation matrix. The eigenspectrum of the correlation matrix is empirically examined by simulation, under the addition of noise to the original signal. The simulation results are then used to propose a dimension estimation procedure of clusters from data. Moreover, the simulation results warn against considering pairwise correlations in isolation, as the model provides a mechanism whereby a pair of genes with 'low' correlation may simply be due to the interaction of high dimension and noise. Instead, collective information about all the variables is given by the eigenspectrum.},
  language  = {en}
}
@article{FeherWhelanMueller2011,
  author    = {Feher, Kristen and Whelan, James and M{\"u}ller, Samuel},
  title     = {Assessing modularity using a random matrix theory approach},
  series = {Statistical applications in genetics and molecular biology},
  volume    = {10},
  journal   = {Statistical applications in genetics and molecular biology},
  number    = {1},
  publisher = {De Gruyter},
  address   = {Berlin},
  issn      = {2194-6302},
  doi       = {10.2202/1544-6115.1667},
  pages     = {36},
  year      = {2011},
  abstract  = {Random matrix theory (RMT) is well suited to describing the emergent properties of systems with complex interactions amongst their constituents through their eigenvalue spectrums. Some RMT results are applied to the problem of clustering high dimensional biological data with complex dependence structure amongst the variables. It will be shown that a gene relevance or correlation network can be constructed by choosing a correlation threshold in a principled way, such that it corresponds to a block diagonal structure in the correlation matrix, if such a structure exists. The structure is then found using community detection algorithms, but with parameter choice guided by RMT predictions. The resulting clustering is compared to a variety of hierarchical clustering outputs and is found to the most generalised result, in that it captures all the features found by the other considered methods.},
  language  = {en}
}
@article{GajdanowiczGarciaMataGonzalezetal.2009,
  author    = {Gajdanowicz, Pawel and Garcia-Mata, Carlos and Gonzalez, Wendy and Morales-Navarro, Samuel El{\"i}as and Sharma, Tripti and Gonzalez-Nilo, Fernando Danilo and Gutowicz, Jan and M{\"u}ller-R{\"o}ber, Bernd and Blatt, Michael R. and Dreyer, Ingo},
  title     = {Distinct roles of the last transmembrane domain in controlling Arabidopsis K+ channel activity},
  issn      = {0028-646X},
  doi       = {10.1111/j.1469-8137.2008.02749.x},
  year      = {2009},
  abstract  = {The family of voltage-gated potassium channels in plants presumably evolved from a common ancestor and includes both inward-rectifying (K-in) channels that allow plant cells to accumulate K+ and outward-rectifying (K-out) channels that mediate K+ efflux. Despite their close structural similarities, the activity of Kin channels is largely independent of K+ and depends only on the transmembrane voltage, whereas that of K-out channels responds to the membrane voltage and the prevailing extracellular K+ concentration. Gating of potassium channels is achieved by structural rearrangements within the last transmembrane domain (S6). Here we investigated the functional equivalence of the S6 helices of the Kin channel KAT1 and the K-out channel SKOR by domain-swapping and site-directed mutagenesis. Channel mutants and chimeras were analyzed after expression in Xenopus oocytes. We identified two discrete regions that influence gating differently in both channels, demonstrating a lack of functional complementarity between KAT1 and SKOR. Our findings are supported by molecular models of KAT1 and SKOR in the open and closed states. The role of the S6 segment in gating evolved differently during specialization of the two channel subclasses, posing an obstacle for the transfer of the K+-sensor from K-out to K-in channels.},
  language  = {en}
}
@article{MuellerRoeberArvidsson2009,
  author    = {M{\"u}ller-R{\"o}ber, Bernd and Arvidsson, Samuel Janne},
  title     = {Fertility control : the role of magnesium transporters in pollen development},
  issn      = {1001-0602},
  doi       = {10.1038/Cr.2009.82},
  year      = {2009},
  language  = {en}
}
@article{ArvidssonPerezRodriguezMuellerRoeber2011,
  author    = {Arvidsson, Samuel Janne and Perez-Rodriguez, Paulino and M{\"u}ller-R{\"o}ber, Bernd},
  title     = {A growth phenotyping pipeline for Arabidopsis thaliana integrating image analysis and rosette area modeling for robust quantification of genotype effects},
  series = {New phytologist : international journal of plant science},
  volume    = {191},
  journal   = {New phytologist : international journal of plant science},
  number    = {3},
  publisher = {Wiley-Blackwell},
  address   = {Malden},
  issn      = {0028-646X},
  doi       = {10.1111/j.1469-8137.2011.03756.x},
  pages     = {895 -- 907},
  year      = {2011},
  abstract  = {To gain a deeper understanding of the mechanisms behind biomass accumulation, it is important to study plant growth behavior. Manually phenotyping large sets of plants requires important human resources and expertise and is typically not feasible for detection of weak growth phenotypes. Here, we established an automated growth phenotyping pipeline for Arabidopsis thaliana to aid researchers in comparing growth behaviors of different genotypes. The analysis pipeline includes automated image analysis of two-dimensional digital plant images and evaluation of manually annotated information of growth stages. It employs linear mixed-effects models to quantify genotype effects on total rosette area and relative leaf growth rate (RLGR) and ANOVAs to quantify effects on developmental times. Using the system, a single researcher can phenotype up to 7000 plants d(-1). Technical variance is very low (typically < 2\%). We show quantitative results for the growth-impaired starch-excessmutant sex4-3 and the growth-enhancedmutant grf9. We show that recordings of environmental and developmental variables reduce noise levels in the phenotyping datasets significantly and that careful examination of predictor variables (such as d after sowing or germination) is crucial to avoid exaggerations of recorded phenotypes and thus biased conclusions.},
  language  = {en}
}
@article{OmidbakhshfardWinckArvidssonetal.2014,
  author    = {Omidbakhshfard, Mohammad Amin and Winck, Flavia Vischi and Arvidsson, Samuel Janne and Riano-Pachon, Diego M. and M{\"u}ller-R{\"o}ber, Bernd},
  title     = {A step-by-step protocol for formaldehyde-assisted isolation of regulatory elements from Arabidopsis thaliana},
  series = {Journal of integrative plant biology},
  volume    = {56},
  journal   = {Journal of integrative plant biology},
  number    = {6},
  publisher = {Wiley-Blackwell},
  address   = {Hoboken},
  issn      = {1672-9072},
  doi       = {10.1111/jipb.12151},
  pages     = {527 -- 538},
  year      = {2014},
  abstract  = {The control of gene expression by transcriptional regulators and other types of functionally relevant DNA transactions such as chromatin remodeling and replication underlie a vast spectrum of biological processes in all organisms. DNA transactions require the controlled interaction of proteins with DNA sequence motifs which are often located in nucleosome-depleted regions (NDRs) of the chromatin. Formaldehyde-assisted isolation of regulatory elements (FAIRE) has been established as an easy-to-implement method for the isolation of NDRs from a number of eukaryotic organisms, and it has been successfully employed for the discovery of new regulatory segments in genomic DNA from, for example, yeast, Drosophila, and humans. Until today, however, FAIRE has only rarely been employed in plant research and currently no detailed FAIRE protocol for plants has been published. Here, we provide a step-by-step FAIRE protocol for NDR discovery in Arabidopsis thaliana. We demonstrate that NDRs isolated from plant chromatin are readily amenable to quantitative polymerase chain reaction and next-generation sequencing. Only minor modification of the FAIRE protocol will be needed to adapt it to other plants, thus facilitating the global inventory of regulatory regions across species.},
  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{RohrmannTohgeAlbaetal.2011,
  author    = {Rohrmann, Johannes and Tohge, Takayuki and Alba, Rob and Osorio, Sonia and Caldana, Camila and McQuinn, Ryan and Arvidsson, Samuel Janne and van der Merwe, Margaretha J. and Riano-Pachon, Diego Mauricio and M{\"u}ller-R{\"o}ber, Bernd and Fei, Zhangjun and Nesi, Adriano Nunes and Giovannoni, James J. and Fernie, Alisdair R.},
  title     = {Combined transcription factor profiling, microarray analysis and metabolite profiling reveals the transcriptional control of metabolic shifts occurring during tomato fruit development},
  series = {The plant journal},
  volume    = {68},
  journal   = {The plant journal},
  number    = {6},
  publisher = {Wiley-Blackwell},
  address   = {Malden},
  issn      = {0960-7412},
  doi       = {10.1111/j.1365-313X.2011.04750.x},
  pages     = {999 -- 1013},
  year      = {2011},
  abstract  = {Maturation of fleshy fruits such as tomato (Solanum lycopersicum) is subject to tight genetic control. Here we describe the development of a quantitative real-time PCR platform that allows accurate quantification of the expression level of approximately 1000 tomato transcription factors. In addition to utilizing this novel approach, we performed cDNA microarray analysis and metabolite profiling of primary and secondary metabolites using GC-MS and LC-MS, respectively. We applied these platforms to pericarp material harvested throughout fruit development, studying both wild-type Solanum lycopersicum cv. Ailsa Craig and the hp1 mutant. This mutant is functionally deficient in the tomato homologue of the negative regulator of the light signal transduction gene DDB1 from Arabidopsis, and is furthermore characterized by dramatically increased pigment and phenolic contents. We choose this particular mutant as it had previously been shown to have dramatic alterations in the content of several important fruit metabolites but relatively little impact on other ripening phenotypes. The combined dataset was mined in order to identify metabolites that were under the control of these transcription factors, and, where possible, the respective transcriptional regulation underlying this control. The results are discussed in terms of both programmed fruit ripening and development and the transcriptional and metabolic shifts that occur in parallel during these processes.},
  language  = {en}
}
@article{MettlerMuehlhausHemmeetal.2014,
  author    = {Mettler, Tabea and M{\"u}hlhaus, Timo and Hemme, Dorothea and Sch{\"o}ttler, Mark Aurel and Rupprecht, Jens and Idoine, Adam and Veyel, Daniel and Pal, Sunil Kumar and Yaneva-Roder, Liliya and Winck, Flavia Vischi and Sommer, Frederik and Vosloh, Daniel and Seiwert, Bettina and Erban, Alexander and Burgos, Asdrubal and Arvidsson, Samuel Janne and Schoenfelder, Stephanie and Arnold, Anne and Guenther, Manuela and Krause, Ursula and Lohse, Marc and Kopka, Joachim and Nikoloski, Zoran and M{\"u}ller-R{\"o}ber, Bernd and Willmitzer, Lothar and Bock, Ralph and Schroda, Michael and Stitt, Mark},
  title     = {Systems analysis of the response of photosynthesis, metabolism, and growth to an increase in irradiance in the photosynthetic model organism chlamydomonas reinhardtii},
  series = {The plant cell},
  volume    = {26},
  journal   = {The plant cell},
  number    = {6},
  publisher = {American Society of Plant Physiologists},
  address   = {Rockville},
  issn      = {1040-4651},
  doi       = {10.1105/tpc.114.124537},
  pages     = {2310 -- 2350},
  year      = {2014},
  abstract  = {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.},
  language  = {en}
}