ARID1A loss impairs enhancer-mediated gene regulation and drives colon cancer in mice

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Abstract

Charles Roberts and colleagues show that deletion of Arid1a from mouse intestinal epithelium results in invasive adenocarcinomas resembling human colorectal cancer. They further show that ARID1A loss impairs SWI/SNF targeting and enhancer-mediated gene regulation.

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Most cited references 28

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Molecular genetics of colorectal cancer.

Eric R. Fearon (2011)

Over the past three decades, molecular genetic studies have revealed some critical mutations underlying the pathogenesis of the sporadic and inherited forms of colorectal cancer (CRC). A relatively limited number of oncogenes and tumor-suppressor genes-most prominently the APC, KRAS, and p53 genes-are mutated in a sizeable fraction of CRCs, and a larger collection of genes that are mutated in subsets of CRC have begun to be defined. Together with DNA-methylation and chromatin-structure changes, the mutations act to dysregulate conserved signaling networks that exert context-dependent effects on critical cell phenotypes, including the regulation of cellular metabolism, proliferation, differentiation, and survival. Much work remains to be done to fully understand the nature and significance of the individual and collective genetic and epigenetic defects in CRC. Some key concepts for the field have emerged, two of which are emphasized in this review. Specifically, the gene defects in CRC often target proteins and pathways that exert pleiotropic effects on the cancer cell phenotype, and particular genetic and epigenetic alterations are linked to biologically and clinically distinct subsets of CRC.

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Design and analysis of ChIP-seq experiments for DNA-binding proteins

Peter V. Kharchenko, Michael Tolstorukov, Peter Park (2008)

Recent progress in massively parallel sequencing platforms has allowed for genome-wide measurements of DNA-associated proteins using a combination of chromatin immunoprecipitation and sequencing (ChIP-seq). While a variety of methods exist for analysis of the established microarray alternative (ChIP-chip), few approaches have been described for processing ChIP-seq data. To fill this gap, we propose an analysis pipeline specifically designed to detect protein binding positions with high accuracy. Using three separate datasets, we illustrate new methods for improving tag alignment and correcting for background signals. We also compare sensitivity and spatial precision of several novel and previously described binding detection algorithms. Finally, we analyze the relationship between the depth of sequencing and characteristics of the detected binding positions, and provide a method for estimating the sequencing depth necessary for a desired coverage of protein binding sites.