ALBERT

Description: Cell cycle-dependent gene expression is often controlled on the transcriptional level. Genes like cyclin B, CDC2 and CDC25C are regulated by cell cycle-dependent element (CDE) and cell cycle genes homology region (CHR) promoter elements mainly through repression in G 0 /G 1 . It had been suggested that E2F4 binding to CDE sites is central to transcriptional regulation. However, some promoters are only controlled by a CHR. We identify the DREAM complex binding to the CHR of mouse and human cyclin B2 promoters in G 0 . Association of DREAM and cell cycle-dependent regulation is abrogated when the CHR is mutated. Although E2f4 is part of the complex, a CDE is not essential but can enhance binding of DREAM. We show that the CHR element is not only necessary for repression of gene transcription in G 0 /G 1 , but also for activation in S, G 2 and M phases. In proliferating cells, the B-myb-containing MMB complex binds the CHR of both promoters independently of the CDE. Bioinformatic analyses identify many genes which contain conserved CHR elements in promoters binding the DREAM complex. With Ube2c as an example from that screen, we show that inverse CHR sites are functional promoter elements that can bind DREAM and MMB. Our findings indicate that the CHR is central to DREAM/MMB-dependent transcriptional control during the cell cycle.

Description: Developing accurate analysis techniques to combine various probes of cosmology is essential to tighten constraints on cosmological parameters and to check for inconsistencies in our model of the Universe. In this paper we develop a joint analysis framework for six different second-order statistics calculated from three tracers of the dark matter density field, namely galaxy position, shear, and magnification. We extend a data compression scheme developed in the context of shear–shear statistics (the so-called COSEBIs) to the other five second-order statistics, thereby significantly reducing the number of data points in the joint data vector. We use C osmo L ike , a newly developed software framework for joint likelihood analyses, to forecast parameter constraints for the Dark Energy Survey. The simulated Monte Carlo Markov Chains cover a five-dimensional cosmological parameter space comparing the information content of the individual probes to several combined probes (CP) data vectors. Given the significant correlations of these second-order statistics we model all cross-terms in the covariance matrix; furthermore, we go beyond the Gaussian covariance approximation and use the halo model to include higher order correlations of the density field. We find that adding magnification information (including cross-probes with shear and clustering) noticeably increases the information content and that the correct modelling of the covariance (i.e. accounting for non-Gaussianity and cross-terms) is essential for accurate likelihood contours from the CP data vector. We also identify several null tests based on the degeneracy of magnification and shear statistics which can be used to quantify the contamination of data sets by astrophysical systematics and/or calibration issues.

Description: We report the first measurement of the diminutive lensing signal arising from matter underdensities associated with cosmic voids. While undetectable individually, by stacking the weak gravitational shear estimates around 901 voids detected in Sloan Digital Sky Survey DR7 by Sutter et al., we find substantial evidence for a depression of the lensing signal compared to the cosmic mean. This depression is most pronounced at the void radius, in agreement with analytical models of void matter profiles. Even with the largest void sample and imaging survey available today, we cannot put useful constraints on the radial dark matter void profile. We invite independent investigations of our findings by releasing data and analysis code to the public at https://github.com/pmelchior/void-lensing .