Search

Pathologic alterations in epigenetic regulation have long been considered a hallmark of many cancers, including hepatocellular carcinoma (HCC). In a healthy individual, the relationship between DNA methylation and microRNA (miRNA) expression maintains a fine balance; however, disruptions in this harmony can aid in the genesis of cancer or the propagation of existing cancers. The balance between DNA methylation and microRNA expression and its potential disturbance in HCC can vary by race. There is emerging evidence linking epigenetic events including DNA methylation and miRNA expression to cancer disparities. In this paper, we evaluate the epigenetic mechanisms of racial heterogenity in HCC through an integrated analysis of DNA methylation, miRNA, and combined regulation of gene expression. Specifically, we generated DNA methylation, mRNA-seq, and miRNA-seq data through the analysis of tumor and adjacent non-tumor liver tissues from African Americans (AA) and European Americans (EA) with HCC. Using mixed ANOVA, we identified cytosine-phosphate-guanine (CpG) sites, mRNAs, and miRNAs that are significantly altered in HCC vs. adjacent non-tumor tissue in a race-specific manner. We observed that the methylome was drastically changed in EA with a significantly larger number of differentially methylated and differentially expressed genes than in AA. On the other hand, the miRNA expression was altered to a larger extent in AA than in EA. Pathway analysis functionally linked epigenetic regulation in EA to processes involved in immune cell maturation, inflammation, and vascular remodeling. In contrast, cellular proliferation, metabolism, and growth pathways are found to predominate in AA as a result of this epigenetic analysis. Furthermore, through integrative analysis, we identified significantly differentially expressed genes in HCC with disparate epigenetic regulation, associated with changes in miRNA expression for AA and DNA methylation for EA.

Pathologic alterations in epigenetic regulation have long been considered a hallmark of many cancers, including hepatocellular carcinoma (HCC). In a healthy individual, the relationship between DNA methylation and microRNA (miRNA) expression maintains a fine balance; however, disruptions in this harmony can aid in the genesis of cancer or the propagation of existing cancers. The balance between DNA methylation and microRNA expression and its potential disturbance in HCC can vary by race. There is emerging evidence linking epigenetic events including DNA methylation and miRNA expression to cancer disparities. In this paper, we evaluate the epigenetic mechanisms of racial heterogenity in HCC through an integrated analysis of DNA methylation, miRNA, and combined regulation of gene expression. Specifically, we generated DNA methylation, mRNA-seq, and miRNA-seq data through the analysis of tumor and adjacent non-tumor liver tissues from African Americans (AA) and European Americans (EA) with HCC. Using mixed ANOVA, we identified cytosine-phosphate-guanine (CpG) sites, mRNAs, and miRNAs that are significantly altered in HCC vs. adjacent non-tumor tissue in a race-specific manner. We observed that the methylome was drastically changed in EA with a significantly larger number of differentially methylated and differentially expressed genes than in AA. On the other hand, the miRNA expression was altered to a larger extent in AA than in EA. Pathway analysis functionally linked epigenetic regulation in EA to processes involved in immune cell maturation, inflammation, and vascular remodeling. In contrast, cellular proliferation, metabolism, and growth pathways are found to predominate in AA as a result of this epigenetic analysis. Furthermore, through integrative analysis, we identified significantly differentially expressed genes in HCC with disparate epigenetic regulation, associated with changes in miRNA expression for AA and DNA methylation for EA. [ABSTRACT FROM AUTHOR]

The role of genomic variation in differentiation is currently not well understood. Here, the genomic variations were determined with the whole-genome sequencing for three pairs of pluripotent stem cell lines and their corresponding BMP4-induced trophoblast cell lines. We identified ∼3,500 single nucleotide variations and ∼4,500 indels by comparing the genome sequenced data between the stem cell lines and the matched BMP4-induced trophoblast cell lines and annotated them by integrating the epigenomic and transcriptomic datasets. Relatively, introns enrich more variations. We found ∼45% (42 genes) of the differentially expressed genes in trophoblasts that associate genomic variations. Six variations, located at transcription factor binding sites where H3K4me3 and H3K27ac are enriched in both H1 and H1_BMP4, were identified. The epigenetic status around the genomic variations in H1 was similar to that in H1_BMP4. This means that the variation-associated gene’s expression change can not be attributed to epigenetic alteration. The genes associated with the six variations were upregulated in differentiation. We inferred that during the differentiation, an increased in the expression level of the MEF2C gene is due to a genomic variation in chromosomes 5: 88179358 A > G, which is at a binding site of TFs KLF16, NR2C2, and ZNF740 to MEF2C. Allele G shows a higher affinity to the TFs in the induced cells. The increased expression of MEF2C leads to an increased expression of TF MEF2C’s target genes, subsequently affecting the differentiation. Although genomic variation should not be a dominant factor in differentiation, we believe that genomic variation could indeed play a role in the differentiation from stem cells into trophoblast.

The role of genomic variation in differentiation is currently not well understood. Here, the genomic variations were determined with the whole-genome sequencing for three pairs of pluripotent stem cell lines and their corresponding BMP4-induced trophoblast cell lines. We identified ∼3,500 single nucleotide variations and ∼4,500 indels by comparing the genome sequenced data between the stem cell lines and the matched BMP4-induced trophoblast cell lines and annotated them by integrating the epigenomic and transcriptomic datasets. Relatively, introns enrich more variations. We found ∼45% (42 genes) of the differentially expressed genes in trophoblasts that associate genomic variations. Six variations, located at transcription factor binding sites where H3K4me3 and H3K27ac are enriched in both H1 and H1_BMP4, were identified. The epigenetic status around the genomic variations in H1 was similar to that in H1_BMP4. This means that the variation-associated gene's expression change can not be attributed to epigenetic alteration. The genes associated with the six variations were upregulated in differentiation. We inferred that during the differentiation, an increased in the expression level of the MEF2C gene is due to a genomic variation in chromosomes 5: 88179358 A > G, which is at a binding site of TFs KLF16, NR2C2, and ZNF740 to MEF2C. Allele G shows a higher affinity to the TFs in the induced cells. The increased expression of MEF2C leads to an increased expression of TF MEF2C's target genes, subsequently affecting the differentiation. Although genomic variation should not be a dominant factor in differentiation, we believe that genomic variation could indeed play a role in the differentiation from stem cells into trophoblast. [ABSTRACT FROM AUTHOR]

Background Psychiatric disorders such as schizophrenia (SZ) and bipolar disorder (BP) are projected to lead the global disease burden within the next decade. Several lines of evidence suggest that epigenetic- or genetic-mediated dysfunction is frequently present in these disorders. To date, the inheritance patterns have been complicated by the problem of integrating epigenomic and transcriptomic factors that have yet to be elucidated. Therefore, there is a need to build a comprehensive database for storing epigenomic and transcriptomic data relating to psychiatric disorders. Description We have developed the PD_NGSAtlas, which focuses on the efficient storage of epigenomic and transcriptomic data based on next-generation sequencing and on the quantitative analyses of epigenetic and transcriptional alterations involved in psychiatric disorders. The current release of the PD_NGSAtlas contains 43 DNA methylation profiles and 37 transcription profiles detected by MeDIP-Seq and RNA-Seq, respectively, in two distinct brain regions and peripheral blood of SZ, BP and non-psychiatric controls. In addition to these data that were generated in-house, we have included, and will continue to include, published DNA methylation and gene expression data from other research groups, with a focus on psychiatric disorders. A flexible query engine has been developed for the acquisition of methylation profiles and transcription profiles for special genes or genomic regions of interest of the selected samples. Furthermore, the PD_NGSAtlas offers online tools for identifying aberrantly methylated and expressed events involved in psychiatric disorders. A genome browser has been developed to provide integrative and detailed views of multidimensional data in a given genomic context, which can help researchers understand molecular mechanisms from epigenetic and transcriptional perspectives. Moreover, users can download the methylation and transcription data for further analyses. Conclusions The PD_NGSAtlas aims to provide storage of epigenomic and transcriptomic data as well as quantitative analyses of epigenetic and transcriptional alterations involved in psychiatric disorders. The PD_NGSAtlas will be a valuable data resource and will enable researchers to investigate the pathophysiology and aetiology of disease in detail. The database is available at http://bioinfo.hrbmu.edu.cn/pd_ngsatlas/. [ABSTRACT FROM AUTHOR]

Keywords: genomic variations; pluripotent stem cells; trophoblast; whole genome sequencing; epigenomic and transcriptomic data EN genomic variations pluripotent stem cells trophoblast whole genome sequencing epigenomic and transcriptomic data 1 1 1 06/02/20 20200528 NES 200528 In the original article, there was an error in the Acknowledgments. Genomic variations, pluripotent stem cells, trophoblast, whole genome sequencing, epigenomic and transcriptomic data. [Extracted from the article]