Browsing by Author "Luo, Ximei"

Now showing 1 - 3 of 3
  • Thumbnail Image
    Item
    An all-to-all approach to the identification of sequence-specific readers for epigenetic DNA modifications on cytosine
    (Springer Nature, 2021-02-04) Song, Guang; Wang, Guohua; Luo, Ximei; Cheng, Ying; Song, Qifeng; Wan, Jun; Moore, Cedric; Song, Hongjun; Jin, Peng; Qian, Jiang; Zhu, Heng; Medical and Molecular Genetics, School of Medicine
    Epigenetic modifications of DNA play important roles in many biological processes. Identifying readers of these epigenetic marks is a critical step towards understanding the underlying mechanisms. Here, we present an all-to-all approach, dubbed digital affinity profiling via proximity ligation (DAPPL), to simultaneously profile human TF-DNA interactions using mixtures of random DNA libraries carrying different epigenetic modifications (i.e., 5-methylcytosine, 5-hydroxymethylcytosine, 5-formylcytosine, and 5-carboxylcytosine) on CpG dinucleotides. Many proteins that recognize consensus sequences carrying these modifications in symmetric and/or hemi-modified forms are identified. We further demonstrate that the modifications in different sequence contexts could either enhance or suppress TF binding activity. Moreover, many modifications can affect TF binding specificity. Furthermore, symmetric modifications show a stronger effect in either enhancing or suppressing TF-DNA interactions than hemi-modifications. Finally, in vivo evidence suggests that USF1 and USF2 might regulate transcription via hydroxymethylcytosine-binding activity in weak enhancers in human embryonic stem cells.
  • Thumbnail Image
    Item
    Author Correction: An all-to-all approach to the identification of sequence-specific readers for epigenetic DNA modifications on cytosine
    (Springer Nature, 2021-02-23) Song, Guang; Wang, Guohua; Luo, Ximei; Cheng, Ying; Song, Qifeng; Wan, Jun; Moore, Cedric; Song, Hongjun; Jin, Peng; Qian, Jiang; Zhu, Heng; Medical and Molecular Genetics, School of Medicine
    Correction to: Nature Communications 10.1038/s41467-021-20950-w, published online 04 February 2021. In the original version of this Article, the “Methods” section “Genome-wide hmC profiling of human embryonic stem cell H1” incorrectly stated “"Human embryonic stem cell H1 was purchased from WiCell Research Institute (WiCell) and the ethics approval was obtained from the Robert-Koch Institute, Berlin, Germany.”. Ethical approval was not required for the use of hESC H1 cells purchased from WiCell Research Institute. The statement has been corrected to “Human embryonic stem cell H1 was purchased from WiCell Research Institute (WiCell).” This has been corrected in the HTML and PDF version of this Article.
  • Thumbnail Image
    Item
    MeDReaders: a database for transcription factors that bind to methylated DNA
    (Oxford Academic, 2018-01-04) Wang, Guohua; Luo, Ximei; Wang, Jianan; Wan, Jun; Xia, Shuli; Zhu, Heng; Qian, Jiang; Wang, Yadong; Medical and Molecular Genetics, School of Medicine
    Understanding the molecular principles governing interactions between transcription factors (TFs) and DNA targets is one of the main subjects for transcriptional regulation. Recently, emerging evidence demonstrated that some TFs could bind to DNA motifs containing highly methylated CpGs both in vitro and in vivo. Identification of such TFs and elucidation of their physiological roles now become an important stepping-stone toward understanding the mechanisms underlying the methylation-mediated biological processes, which have crucial implications for human disease and disease development. Hence, we constructed a database, named as MeDReaders, to collect information about methylated DNA binding activities. A total of 731 TFs, which could bind to methylated DNA sequences, were manually curated in human and mouse studies reported in the literature. In silico approaches were applied to predict methylated and unmethylated motifs of 292 TFs by integrating whole genome bisulfite sequencing (WGBS) and ChIP-Seq datasets in six human cell lines and one mouse cell line extracted from ENCODE and GEO database. MeDReaders database will provide a comprehensive resource for further studies and aid related experiment designs. The database implemented unified access for users to most TFs involved in such methylation-associated binding actives. The website is available at http://medreader.org/.