The pan-cancer analysis of whole genomes The expansion of whole-genome sequencing studies from individual ICGC and TCGA working groups presented the opportunity to undertake a meta-analysis of genomic features across tumour types. To achieve this, the PCAWG Consortium was established. A Technical Working Group implemented the informatics analyses by aggregating the raw sequencing data from different working groups that studied individual tumour types, aligning the sequences to the human genome and delivering a set of high-quality somatic mutation calls for downstream analysis (Extended Data Fig. 1). Given the recent meta-analysis

No abstract

Highlights d Proteogenomics characterization of 218 pediatric brain tumor samples of 7 histologies d Proteomic clusters reveal actionable biological features spanning histological boundaries d Proteomics reveal downstream effects of DNA alterations not evident in transcriptomics d Kinase activity analyses provide insights into pathway activities and druggable targets

The virulence of Mycobacterium tuberculosis depends on the ability of the bacilli to switch between replicative (growth) and non-replicative (dormancy) states in response to host immunity. However, the gene regulatory events associated with transition to dormancy are largely unknown. To address this question, we have assembled the largest M. tuberculosis transcriptional-regulatory network to date, and characterized the temporal response of this network during adaptation to stationary phase and hypoxia, using published microarray data. Distinct sets of transcriptional subnetworks (origons) were responsive at various stages of adaptation, showing a gradual progression of network response under both conditions. Most of the responsive origons were in common between the two conditions and may help define a general transcriptional signature of M. tuberculosis growth arrest. These results open the door for a systems-level understanding of transition to non-replicative persistence, a phenotypic state that prevents sterilization of infection by the host immune response and promotes the establishment of latent M. tuberculosis infection, a condition found in two billion people worldwide.

Multiscale methods are becoming increasingly promising as a way to characterize the dynamics of large protein systems on biologically relevant time-scales. The underlying assumption in multiscale simulations is that it is possible to move reliably between different resolutions. We present a method that efficiently generates realistic all-atom protein structures starting from the C(alpha) atom positions, as obtained for instance from extensive coarse-grain simulations. The method, a reconstruction algorithm for coarse-grain structures (RACOGS), is validated by reconstructing ensembles of coarse-grain structures obtained during folding simulations of the proteins src-SH3 and S6. The results show that RACOGS consistently produces low energy, all-atom structures. A comparison of the free energy landscapes calculated using the coarse-grain structures versus the all-atom structures shows good correspondence and little distortion in the protein folding landscape.