Gains and losses in DNA methylation are prominent features of mammalian cell types. To gain insight into mechanisms that could promote shifts in DNA methylation and contribute to cell fate changes, including malignant transformation, we performed genome-wide mapping of 5-methylcytosine and 5-hydroxymethylcytosine in purified murine hematopoietic stem cells. We discovered extended regions of low methylation (Canyons) that span conserved domains frequently containing transcription factors and are distinct from CpG islands and shores. The genes in about half of these methylation Canyons are coated with repressive histone marks while the remainder are covered by activating histone marks and are highly expressed in HSCs. Canyon borders are demarked by 5-hydroxymethylcytosine and become eroded in the absence of DNA methyltransferase 3a (Dnmt3a). Genes dysregulated in human leukemias are enriched for Canyon-associated genes. The novel epigenetic landscape we describe may provide a mechanism for the regulation of hematopoiesis and may contribute to leukemia development.
Chromosomal double-strand breaks (DSBs) are resected by 5′-nucleases to form 3′ single-strand DNA (ssDNA) substrates for binding by homologous recombination and DNA damage checkpoint proteins. Two redundant pathways of extensive resection were described both in cells 1-3 and in vitro 4-6, one relying on Exo1 exonuclease and the other on Sgs1 helicase and Dna2 nuclease. However, it remains unknown how resection proceeds within the context of chromatin where histones and histone-bound proteins represent barriers for resection enzymes. Here, we have identified the yeast nucleosome remodeling enzyme Fun30 as novel factor promoting DSB end resection. Fun30 is the major nucleosome remodeler promoting extensive Exo1- and Sgs1-dependent resection of DSBs while the RSC and INO80 chromatin remodeling complexes play redundant roles with Fun30 in resection adjacent to DSB ends. ATPase and helicase domains of Fun30, which are needed for nucleosome remodeling 7, are also required for resection. Fun30 is robustly recruited to DNA breaks and spreads around the DSB coincident with resection. Fun30 becomes less important for resection in the absence of the histone-bound Rad9 checkpoint adaptor protein known to block 5′ strand processing 8 and in the absence of either histone H3 K79 methylation or γ-H2A, which mediate recruitment of the Rad9 9, 10. Together these data suggest that Fun30 helps to overcome the inhibitory effect of Rad9 on DNA resection.
Identification of drug-target interactions is an important process in drug discovery. Although high-throughput screening and other biological assays are becoming available, experimental methods for drug-target interaction identification remain to be extremely costly, time-consuming and challenging even nowadays. Therefore, various computational models have been developed to predict potential drug-target associations on a large scale. In this review, databases and web servers involved in drug-target identification and drug discovery are summarized. In addition, we mainly introduced some state-of-the-art computational models for drug-target interactions prediction, including network-based method, machine learning-based method and so on. Specially, for the machine learning-based method, much attention was paid to supervised and semi-supervised models, which have essential difference in the adoption of negative samples. Although significant improvements for drug-target interaction prediction have been obtained by many effective computational models, both network-based and machine learning-based methods have their disadvantages, respectively. Furthermore, we discuss the future directions of the network-based drug discovery and network approach for personalized drug discovery based on personalized medicine, genome sequencing, tumor clone-based network and cancer hallmark-based network. Finally, we discussed the new evaluation validation framework and the formulation of drug-target interactions prediction problem by more realistic regression formulation based on quantitative bioactivity data.
Mutations in the epigenetic modifiers DNMT3A and TET2 non-randomly co-occur in lymphoma and leukemia despite their epistasis in the methylation-hydroxymethylation pathway. Using Dnmt3a and Tet2 double knock-out (DKO) mice in which malignancy development is accelerated, we show that the DKO methylome reflects regions of independent, competitive and cooperative activity. Expression of lineage-specific transcription factors, including the erythroid regulator Klf1 is upregulated in DKO HSCs. DNMT3A and TET2 both repress Klf1 suggesting a model of cooperative inhibition by the epigenetic modifiers. These data demonstrate a dual role for TET2 in promoting and inhibiting HSC differentiation, loss of which, along with DNMT3A, obstructs differentiation leading to transformation.
Comprehensive studies have shown that DNA methylation plays vital roles in both loss of pluripotency and governance of the transcriptome during embryogenesis and subsequent developmental processes. Aberrant DNA methylation patterns have been widely observed in tumorigenesis, ageing and neurodegenerative diseases, highlighting the importance of a systematic understanding of DNA methylation and the dynamic changes of methylomes during disease onset and progression. Here we describe a facile and convenient approach for efficient targeted DNA methylation by fusing inactive Cas9 (dCas9) with an engineered prokaryotic DNA methyltransferase MQ1. Our study presents a rapid and efficient strategy to achieve locus-specific cytosine modifications in the genome without obvious impact on global methylation in 24 h. Finally, we demonstrate our tool can induce targeted CpG methylation in mice by zygote microinjection, thereby demonstrating its potential utility in early development.
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