In an online, early PNAS article, researchers led by Pascal Hersen from the Centre National de la Recherche Scientiﬁque and Université Paris Diderot in France present a method to monitor and control gene expression at the single-cell and population levels over a number of generations. "We developed a platform for real-time, closed-loop control of gene expression in yeast that integrates microscopy for monitoring gene expression at the cell level, microﬂuidics to manipulate the cells' environment, and original software for automated imaging, quantiﬁcation, and model predictive control," Hersen and his colleagues write.
Also in an online PNAS article, researchers Massachusetts General Hospital's Kasper Lage and colleagues examine genetic and environmental risk factors for congenital heart disease. Drawing on data from human and model organism-based studies of congenital heart disease, the researchers studied whether the genes identified in those datasets converge either directly or functionally. "We uncovered functional convergence among thousands of CHD risk factors," the researchers report. "Surprisingly, although genetic and environmental factors involved in CHD impact genes that participate across many different molecular pathways, these seemingly unrelated risk factors affect pathways that participate in larger, but discrete, protein interaction networks that drive the development of specific cardiac structures." They found no evidence of direct convergence.
Finally, researchers in The Netherlands present their work using an algorithm to predict nucleosome position. The model is "based on assigning a probability score to each dinucleotide that depends only on the phasing of the dinucleotide. The resulting nucleosome-positioning likelihood map is converted to a sequence-specific energy landscape for nucleosome binding, predicting relative nucleosome affinities with high accuracy," the authors say.