Anti-Histone H3 (di methyl K4) polyclonal antibody

Epstein-Barr Virus (EBV) Nuclear Antigen 1 (EBNA1)-mediated origin of plasmid replication (oriP) DNA episome maintenance is essential for EBV-mediated tumorigenesis. We have now found that EBNA1 binds to Ribosome Protein L4 (RPL4). RPL4 shRNA knockdown decreased EBNA1 activation of an oriP luciferase reporter, EBNA1 DNA binding in lymphoblastoid cell lines, and EBV genome number per lymphoblastoid cell line. EBV infection increased RPL4 expression and redistributed RPL4 to cell nuclei. RPL4 and Nucleolin (NCL) were a scaffold for an EBNA1-induced oriP complex. The RPL4 N terminus cooperated with NCL-K429 to support EBNA1 and oriP-mediated episome binding and maintenance, whereas the NCL C-terminal K380 and K393 induced oriP DNA H3K4me2 modification and promoted EBNA1 activation of oriP-dependent transcription. These observations provide new insights into the mechanisms by which EBV uses NCL and RPL4 to establish persistent B-lymphoblastoid cell infection.

Characterization of distinct histone methylation and acetylation binding patterns in promoters and prediction of novel regulatory regions remains an important area of genomic research, as it is hypothesized that distinct chromatin signatures may specify unique genomic functions. However, methods that have been proposed in the literature are either descriptive in nature or are fully parametric and hence more restrictive in pattern discovery. In this article, we propose a two-step non-parametric statistical inference procedure to characterize unique histone modification patterns and apply it to analyzing the binding patterns of four histone marks, H3K4me2, H3K4me3, H3K9ac, and H4K20me1, in human B-lymphoblastoid cells. In the first step, we used a functional principal component analysis method to represent the concatenated binding patterns of these four histone marks around the transcription start sites as smooth curves. In the second step, we clustered these curves to reveal several unique classes of binding patterns. These uncovered patterns were used in turn to scan the whole-genome to predict novel and alternative promoters. Our analyses show that there are three distinct promoter binding patterns of active genes. Further, 19654 regions not within known gene promoters were found to overlap with human ESTs, CpG islands, or common SNPs, indicative of their potential role in gene regulation, including being potential novel promoter regions.