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Somatic mutations in DNMT3A are recurrent events across a range of blood cancers. Dnmt3a loss of function in hematopoietic stem cells (HSCs) skews divisions toward self-renewal at the expense of differentiation. Moreover, DNMT3A mutations can be detected in the blood of aging individuals, indicating that mutant cells outcompete normal HSCs over time. It is important to understand how these mutations provide a competitive advantage to HSCs. Here we show that Dnmt3a-null HSCs can regenerate over at least 12 transplant generations in mice, far exceeding the lifespan of normal HSCs. Molecular characterization reveals that this in vivo immortalization is associated with gradual and focal losses of DNA methylation at key regulatory regions associated with self-renewal genes, producing a highly stereotypical HSC phenotype in which epigenetic features are further buttressed. These findings lend insight into the preponderance of DNMT3A mutations in clonal hematopoiesis and the persistence of mutant clones after chemotherapy.
Pubmed ID: 29617651
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An independent, nonprofit organization focused on mammalian genetics research to advance human health. Their mission is to discover the genetic basis for preventing, treating, and curing human disease, and to enable research for the global biomedical community. Jackson Laboratory breeds and manages colonies of mice as resources for other research institutions and laboratories, along with providing software and techniques. Jackson Lab also conducts genetic research and provides educational material for various educational levels.
View all literature mentionsTHIS RESOURCE IS NO LONGER IN SERVICE. Documented on May 5,2022.Tool that predicts interactions between transcription factors and their regulated genes from binding motifs. Understanding vertebrate development requires unraveling the cis-regulatory architecture of gene regulation. PRISM provides accurate genome-wide computational predictions of transcription factor binding sites for the human and mouse genomes, and integrates the predictions with GREAT to provide functional biological context. Together, accurate computational binding site prediction and GREAT produce for each transcription factor: 1. putative binding sites, 2. putative target genes, 3. putative biological roles of the transcription factor, and 4. putative cis-regulatory elements through which the factor regulates each target in each functional role.
View all literature mentionsMus musculus with name C57BL/6J from IMSR.
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