Activation of the Aryl Hydrocarbon Receptor Interferes with Early Embryonic Development.

The transcriptional program of early embryonic development is tightly regulated by a set of well-defined transcription factors that suppress premature expression of differentiation genes and sustain the pluripotent identity. It is generally accepted that this program can be perturbed by environmental factors such as chemical pollutants; however, the precise molecular mechanisms remain unknown. The aryl hydrocarbon receptor (AHR) is a widely expressed nuclear receptor that senses environmental stimuli and modulates target gene expression. Here, we have investigated the AHR interactome in embryonic stem cells by mass spectrometry and show that ectopic activation of AHR during early differentiation disrupts the differentiation program via the chromatin remodeling complex NuRD (nucleosome remodeling and deacetylation). The activated AHR/NuRD complex altered the expression of differentiation-specific genes that control the first two developmental decisions without affecting the pluripotency program. These findings identify a mechanism that allows environmental stimuli to disrupt embryonic development through AHR signaling

A roadmap for the Human Developmental Cell Atlas

The Human Developmental Cell Atlas (HDCA) initiative, which is part of the Human Cell Atlas, aims to create a comprehensive reference map of cells during development. This will be critical to understanding normal organogenesis, the effect of mutations, environmental factors and infectious agents on human development, congenital and childhood disorders, and the cellular basis of ageing, cancer and regenerative medicine. Here we outline the HDCA initiative and the challenges of mapping and modelling human development using state-of-the-art technologies to create a reference atlas across gestation. Similar to the Human Genome Project, the HDCA will integrate the output from a growing community of scientists who are mapping human development into a unified atlas. We describe the early milestones that have been achieved and the use of human stem-cell-derived cultures, organoids and animal models to inform the HDCA, especially for prenatal tissues that are hard to acquire. Finally, we provide a roadmap towards a complete atlas of human development

Pairing of Homologous Regions in the Mouse Genome Is Associated with Transcription but Not Imprinting Status

This work was funded by the BBSRC, grant BB/H088071/1 (www.bbsrc.ac.uk), MRC, grant G0700760 (www.mrc.ac.uk), Wellcome Trust, grant 095645/Z/11/Z (www.wellcome.ac.uk) and the EU through EpiGeneSys (www.epigenesys.eu) and Blueprint (www.blueprint-epigenome.eu). C.K. was funded by the DFG, personal fellowship KR 3317/2-1 (www.dfg.de) and CTR, personal short term fellowship (www.trophoblast.cam.ac.uk). M.J.H. received funding through grant NCI/NIH 2RO1 CA089426 (www.nih.gov)

A multi-objective optimization model for hub network design under uncertainty: An inexact rough-interval fuzzy approach

International audienceThis article proposes a multi-objective mixed-integer model to optimize the location of hubs within a hub network design problem under uncertainty. The considered objectives include minimizing the maximum accumulated travel time, minimizing the total costs including transportation, fuel consumption and greenhouse emissions costs, and finally maximizing the minimum service reliability. In the proposed model, it is assumed that for connecting two nodes, there are several types of arc in which their capacity, transportation mode, travel time, and transportation and construction costs are different. Moreover, in this model, determining the capacity of the hubs is part of the decision-making procedure and balancing requirements are imposed on the network. To solve the model, a hybrid solution approach is utilized based on inexact programming, interval-valued fuzzy programming and rough interval programming. Furthermore, a hybrid multi-objective metaheuristic algorithm, namely multi-objective invasive weed optimization (MOIWO), is developed for the given problem. Finally, various computational experiments are carried out to assess the proposed model and solution approaches