The human RNA methyltransferase like 1 gene (RNMTL1) is one of thirteen newly discovered genes within a 116 Kb segment of the chromosome 17pl3.3 that suffers from a high frequent loss of heterozygosity in human hepato...The human RNA methyltransferase like 1 gene (RNMTL1) is one of thirteen newly discovered genes within a 116 Kb segment of the chromosome 17pl3.3 that suffers from a high frequent loss of heterozygosity in human hepatocellular carcinoma in China[1-5]. To understand the molecular mechanisms underlying transcription control of the RNMTL1 gene in human cancers, we decline using of the conventional approach where the cis-elements bound by the known transcription factors are primary targets, and carried out the systematic analyses to dissect the promoter structure and identify/characterize the key cis-elements that are responsible for its strong expression in cell. The molecular approaches applied included 1, the primer extension for mapping of the transcription starts; 2, the transient transfection/reporter assays on a large number of deletion and site-specific mutants of the promoter segment for defining the minimal promoter and the crucial elements within; and 3, the electrophoresis mobility shift assay with specific antibodies for reconfirming the nature of the transcription factors and their cognate cis-elements. We have shown that the interaction of an ATF/CREB element (-38 to -31) and its cognate transcription factors play a predominant role in the promoter activity of the RNMTL1 gene. The secondary DNA structures of the ATF/CREB element play a more vital role in the protein-DNA interaction. Finally, we reported a novel mechanism underlying the YY1 mediated transcription repression, namely, the ATF/CREB dependent transcription-repression by YY1 is executed in absence of its own sequence-specific binding.展开更多
Chromatin immtmoprecipitation followed by sequencing （ChlP-sec0 is increasingly being used for genome-wide profiling of transcriptional regulation, as this technique enables dissection of the gene regulatory networks...Chromatin immtmoprecipitation followed by sequencing （ChlP-sec0 is increasingly being used for genome-wide profiling of transcriptional regulation, as this technique enables dissection of the gene regulatory networks. With input as control, a variety of statistical methods have been proposed for identifying the enriched regions in the genome, i.e., the transcriptional factor binding sites and chromatin modifications. However, when there are no controls, whether peak calling is still reliable awaits systematic evaluations. To address this question, we used a Bayesian framework approach to show the effectiveness of peak calling without controls （PCWC）. Using several different types of ChlP-seq data, we demonstrated the relatively high accuracy of PCWC with less than a 5% false discovery rate （FDR）. Compared with previously published methods, e.g., the model-based analysis of ChlP-seq （MACS）, PCWC is reliable with lower FDR. Furthermore, to interpret the biological significance of the called peaks, in combination with microarray gene expression data, gene ontology annotation and subsequent motif discovery, our results indicate PCWC possesses a high efficiency. Additionally, using in silico data, only a small number of peaks were identified, suggesting the significantly low FDR for PCWC.展开更多
基金This work is supported by the 973 projects of China (G1998051004) to Jingde Zhu and (G199805l200) to Dafang Wan, respectively.Thanks are due to Hongyu Zhang and other mem-bers in Jingde Zhu's lab for assistance and helps onnumerous occasions.
文摘The human RNA methyltransferase like 1 gene (RNMTL1) is one of thirteen newly discovered genes within a 116 Kb segment of the chromosome 17pl3.3 that suffers from a high frequent loss of heterozygosity in human hepatocellular carcinoma in China[1-5]. To understand the molecular mechanisms underlying transcription control of the RNMTL1 gene in human cancers, we decline using of the conventional approach where the cis-elements bound by the known transcription factors are primary targets, and carried out the systematic analyses to dissect the promoter structure and identify/characterize the key cis-elements that are responsible for its strong expression in cell. The molecular approaches applied included 1, the primer extension for mapping of the transcription starts; 2, the transient transfection/reporter assays on a large number of deletion and site-specific mutants of the promoter segment for defining the minimal promoter and the crucial elements within; and 3, the electrophoresis mobility shift assay with specific antibodies for reconfirming the nature of the transcription factors and their cognate cis-elements. We have shown that the interaction of an ATF/CREB element (-38 to -31) and its cognate transcription factors play a predominant role in the promoter activity of the RNMTL1 gene. The secondary DNA structures of the ATF/CREB element play a more vital role in the protein-DNA interaction. Finally, we reported a novel mechanism underlying the YY1 mediated transcription repression, namely, the ATF/CREB dependent transcription-repression by YY1 is executed in absence of its own sequence-specific binding.
基金Foundation items： This study was supported by the National 973 project of China （2011CBA01101） and the National Natural Science Foundation of China （30871343 and 31130051 ） Acknowledgments： We are thankful to Shao-Bin XU （Kunming Institute of Zoology, CAS） for his support on super-computing service, and to Yu-qi ZHAO （Kunming Institute of Zoology, CAS） for his helpful discussion.
文摘Chromatin immtmoprecipitation followed by sequencing （ChlP-sec0 is increasingly being used for genome-wide profiling of transcriptional regulation, as this technique enables dissection of the gene regulatory networks. With input as control, a variety of statistical methods have been proposed for identifying the enriched regions in the genome, i.e., the transcriptional factor binding sites and chromatin modifications. However, when there are no controls, whether peak calling is still reliable awaits systematic evaluations. To address this question, we used a Bayesian framework approach to show the effectiveness of peak calling without controls （PCWC）. Using several different types of ChlP-seq data, we demonstrated the relatively high accuracy of PCWC with less than a 5% false discovery rate （FDR）. Compared with previously published methods, e.g., the model-based analysis of ChlP-seq （MACS）, PCWC is reliable with lower FDR. Furthermore, to interpret the biological significance of the called peaks, in combination with microarray gene expression data, gene ontology annotation and subsequent motif discovery, our results indicate PCWC possesses a high efficiency. Additionally, using in silico data, only a small number of peaks were identified, suggesting the significantly low FDR for PCWC.
