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

Background Type II DNA topoisomerases (TOP2) regulate DNA topology by generating transient double stranded breaks during replication and transcription. Topoisomerase II beta (TOP2B) facilitates rapid gene expression and functions at the later stages of development and differentiation. To gain new insight into the genome biology of TOP2B, we used proteomics (BioID), chromatin immunoprecipitation, and high-throughput chromosome conformation capture (Hi-C) to identify novel proximal TOP2B protein interactions and characterize the genomic landscape of TOP2B binding at base pair resolution. Results Our human TOP2B proximal protein interaction network included members of the cohesin complex and nucleolar proteins associated with rDNA biology. TOP2B associates with DNase I hypersensitivity sites, allele-specific transcription factor (TF) binding, and evolutionarily conserved TF binding sites on the mouse genome. Approximately half of all CTCF/cohesion-bound regions coincided with TOP2B binding. Base pair resolution ChIP-exo mapping of TOP2B, CTCF, and cohesin sites revealed a striking structural ordering of these proteins along the genome relative to the CTCF motif. These ordered TOP2B-CTCF-cohesin sites flank the boundaries of topologically associating domains (TADs) with TOP2B positioned externally and cohesin internally to the domain loop. Conclusions TOP2B is positioned to solve topological problems at diverse cis-regulatory elements and its occupancy is a highly ordered and prevalent feature of CTCF/cohesin binding sites that flank TADs. Electronic supplementary material The online version of this article (doi:10.1186/s13059-016-1043-8) contains supplementary material, which is available to authorized users.

Summary Targeting bromodomains (BRDs) of the bromo-and-extra-terminal (BET) family offers opportunities for therapeutic intervention in cancer and other diseases. Here, we profile the interactomes of BRD2, BRD3, BRD4, and BRDT following treatment with the pan-BET BRD inhibitor JQ1, revealing broad rewiring of the interaction landscape, with three distinct classes of behavior for the 603 unique interactors identified. A group of proteins associate in a JQ1-sensitive manner with BET BRDs through canonical and new binding modes, while two classes of extra-terminal (ET)-domain binding motifs mediate acetylation-independent interactions. Last, we identify an unexpected increase in several interactions following JQ1 treatment that define negative functions for BRD3 in the regulation of rRNA synthesis and potentially RNAPII-dependent gene expression that result in decreased cell proliferation. Together, our data highlight the contributions of BET protein modules to their interactomes allowing for a better understanding of pharmacological rewiring in response to JQ1.

Understanding the role of a given transcription factor (TF) in regulating gene expression requires precise mapping of its binding sites in the genome. Chromatin immunoprecipitation-exo, an emerging technique using λ exonuclease to digest TF unbound DNA after ChIP, is designed to reveal transcription factor binding site (TFBS) boundaries with near-single nucleotide resolution. Although ChIP-exo promises deeper insights into transcription regulation, no dedicated bioinformatics tool exists to leverage its advantages. Most ChIP-seq and ChIP-chip analytic methods are not tailored for ChIP-exo, and thus cannot take full advantage of high-resolution ChIP-exo data. Here we describe a novel analysis framework, termed MACE (model-based analysis of ChIP-exo) dedicated to ChIP-exo data analysis. The MACE workflow consists of four steps: (i) sequencing data normalization and bias correction; (ii) signal consolidation and noise reduction; (iii) single-nucleotide resolution border peak detection using the Chebyshev Inequality and (iv) border matching using the Gale-Shapley stable matching algorithm. When applied to published human CTCF, yeast Reb1 and our own mouse ONECUT1/HNF6 ChIP-exo data, MACE is able to define TFBSs with high sensitivity, specificity and spatial resolution, as evidenced by multiple criteria including motif enrichment, sequence conservation, direct sequence pileup, nucleosome positioning and open chromatin states. In addition, we show that the fundamental advance of MACE is the identification of two boundaries of a TFBS with high resolution, whereas other methods only report a single location of the same event. The two boundaries help elucidate the in vivo binding structure of a given TF, e.g. whether the TF may bind as dimers or in a complex with other co-factors.