Genome sequencing studies have shown that human malignancies often bear mutations in four or more driver genes, but it is difficult to recapitulate this degree of genetic complexity in mouse models using conventional breeding. Here we use the CRISPR-Cas9 system of genome editing to overcome this limitation. By delivering combinations of small guide RNAs (sgRNAs) and Cas9 with a lentiviral vector, we modified up to five genes in a single mouse hematopoietic stem cell (HSC), leading to clonal outgrowth and myeloid malignancy. We thereby generated models of acute myeloid leukemia (AML) with cooperating mutations in genes encoding epigenetic modifiers, transcription factors and mediators of cytokine signaling, recapitulating the combinations of mutations observed in patients. Our results suggest that lentivirus-delivered sgRNA:Cas9 genome editing should be useful to engineer a broad array of in vivo cancer models that better reflect the complexity of human disease.
Divergence in gene regulation can play a major role in evolution. Here, we used a phylogenetic framework to measure mRNA profiles in 15 yeast species from the phylum Ascomycota and reconstruct the evolution of their modular regulatory programs along a time course of growth on glucose over 300 million years [corrected]. We found that modules have diverged proportionally to phylogenetic distance, with prominent changes in gene regulation accompanying changes in lifestyle and ploidy, especially in carbon metabolism. Paralogs have significantly contributed to regulatory divergence, typically within a very short window from their duplication. Paralogs from a whole genome duplication (WGD) event have a uniquely substantial contribution that extends over a longer span. Similar patterns occur when considering the evolution of the heat shock regulatory program measured in eight of the species, suggesting that these are general evolutionary principles. DOI:http://dx.doi.org/10.7554/eLife.00603.001.
Understanding the principles governing mammalian gene regulation has been hampered by the difficulty in measuring in vivo binding dynamics of large numbers of transcription factors (TF) to DNA. Here, we develop a high-throughput Chromatin ImmunoPrecipitation (HT-ChIP) method to systematically map protein-DNA interactions. HT-ChIP was applied to define the dynamics of DNA binding by 25 TFs and 4 chromatin marks at 4 time-points following pathogen stimulus of dendritic cells. Analyzing over 180,000 TF-DNA interactions we find that TFs vary substantially in their temporal binding landscapes. This data suggests a model for transcription regulation whereby TF networks are hierarchically organized into cell differentiation factors, factors that bind targets prior to stimulus to prime them for induction, and factors that regulate specific gene programs. Overlaying HT-ChIP data on gene-expression dynamics shows that many TF-DNA interactions are established prior to the stimuli, predominantly at immediate-early genes, and identified specific TF ensembles that coordinately regulate gene-induction.
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