Reporter genes integrated into the genome are a powerful tool to reveal effects of regulatory elements and local chromatin context on gene expression. However, so far such reporter assays have been of low throughput. Here, we describe a multiplexing approach for the parallel monitoring of transcriptional activity of thousands of randomly integrated reporters. More than 27,000 distinct reporter integrations in mouse embryonic stem cells, obtained with two different promoters, show ∼1,000-fold variation in expression levels. Data analysis indicates that lamina-associated domains act as attenuators of transcription, likely by reducing access of transcription factors to binding sites. Furthermore, chromatin compaction is predictive of reporter activity. We also found evidence for crosstalk between neighboring genes and estimate that enhancers can influence gene expression on average over ∼20 kb. The multiplexed reporter assay is highly flexible in design and can be modified to query a wide range of aspects of gene regulation.

The most common risk factor for developing hepatocellular carcinoma (HCC) is chronic infection with hepatitis B virus (HBV). To better understand the evolutionary forces driving HCC we performed a near saturating transposon mutagenesis screen in a mouse HBV model of HCC. This screen identified 21 candidate early stage drivers, and a bewildering number (2860) of candidate later stage drivers, that were enriched for genes mutated, deregulated, or that function in signaling pathways important for human HCC, with a striking 1199 genes linked to cellular metabolic processes. Our study provides a comprehensive overview of the genetic landscape of HCC.

The ability of retroviruses and transposons to insert their genetic material into host DNA makes them widely used tools in molecular biology, cancer research and gene therapy. However, these systems have biases that may strongly affect research outcomes. To address this issue, we generated very large datasets consisting of to unselected integrations in the mouse genome for the Sleeping Beauty (SB) and piggyBac (PB) transposons, and the Mouse Mammary Tumor Virus (MMTV). We analyzed (epi)genomic features to generate bias maps at both local and genome-wide scales. MMTV showed a remarkably uniform distribution of integrations across the genome. More distinct preferences were observed for the two transposons, with PB showing remarkable resemblance to bias profiles of the Murine Leukemia Virus. Furthermore, we present a model where target site selection is directed at multiple scales. At a large scale, target site selection is similar across systems, and defined by domain-oriented features, namely expression of proximal genes, proximity to CpG islands and to genic features, chromatin compaction and replication timing. Notable differences between the systems are mainly observed at smaller scales, and are directed by a diverse range of features. To study the effect of these biases on integration sites occupied under selective pressure, we turned to insertional mutagenesis (IM) screens. In IM screens, putative cancer genes are identified by finding frequently targeted genomic regions, or Common Integration Sites (CISs). Within three recently completed IM screens, we identified 7%–33% putative false positive CISs, which are likely not the result of the oncogenic selection process. Moreover, results indicate that PB, compared to SB, is more suited to tag oncogenes.

Key Points Hdac1 and Hdac2 are dosage-dependent tumor suppressors. Hdac1 and Hdac2 regulate p53-modulating genes as a barrier to prevent Myc-driven tumorigenesis.