mBISON: Finding miRNA target over-representation in gene lists from ChIP-sequencing data

Transcriptional changes through menstrual cycle reveal a global transcriptional derepression underlying the molecular mechanism involved in the window of implantation

The human endometrium is a dynamic tissue that only is receptive to host the embryo during a brief time in the middle secretory phase, called the window of implantation (WOI). Despite its importance, regulation of the menstrual cycle remains incompletely understood. The aim of this study was to characterize the gene cooperation and regulation of menstrual cycle progression, to dissect the molecular complexity underlying acquisition of endometrial receptivity for a successful pregnancy, and to provide the scientific community with detailed gene co-expression information throughout the menstrual cycle on a user-friendly web-tool database. A retrospective gene co-expression analysis was performed based on the endometrial receptivity array (ERarray) gene signature from 523 human endometrial samples collected across the menstrual cycle, including during the WOI. Gene co-expression analysis revealed the WOI as having the significantly smallest proportion of negative correlations for transcriptional profiles associated with successful pregnancies compared to other cycle stages, pointing to a global transcriptional derepression being involved in acquisition of endometrial receptivity. Regulation was greatest during the transition between proliferative and secretory endometrial phases. Further, we prioritized nuclear hormone receptors as major regulators of this derepression and proved that some genes and transcription factors involved in this process were dysregulated in patients with recurrent implantation failure. We also compiled the wealth of gene co-expression data to stimulate hypothesis-driven single-molecule endometrial studies in a user-friendly database: Menstrual Cycle Gene Co-expression Network (www.menstrualcyclegcn.com). This study revealed a global transcriptional repression across the menstrual cycle, which relaxes when the WOI opens for transcriptional profiles associated with successful pregnancies. These findings suggest that a global transcriptional derepression is needed for embryo implantation and early development.

[Establishment and gene expression analysis of drug-resistant cell lines in hepatocellular carcinoma induced by sorafenib]

OBJECTIVE

To establish the drug-resistant cell lines of hepatocellular carcinoma (HCC) induced by sorafenib, and to screen out the high expression genes in drug-resistant cell lines of HCC induced by sorafenib, then to explore the genes related to sorafenib resistance in hepatocellular carcinoma.

METHODS

The human PLC and Huh7 cell lines were obtained, then the PLC and Huh7 drug-resistant cell lines were induced with sorafenib by using intermittent induction in vitro. CCK8 assay was used to detect the IC50 value of sorafenib for evaluation of drug sensitivity of hepatocellular carcinoma cell lines in PLC and Huh7. All the up regulated genes in PLC and Huh7 drug-resistant cell lines induced by sorafenib were screened out using high-throughput cDNA sequencing (RNA-Seq), Ualcan database was used to analyze the correlations between the up regulated genes in PLC and Huh7 drug-resistant cell lines induced and four clinical biological characteristics of hepatocellular carcinoma, including the gene expressions between normal samples and tumor samples, tumor stage, tumor grade, and patient overall survival, to find the genes that might be involved in the mechanism of sorafenib resistance of hepatocellular carcinoma.

RESULTS

All the up regulated genes detected by the using high-throughput cDNA sequencing (RNA-Seq) in PLC and Huh7 drug-resistant cell lines were further screened out by following conditions:(1) genes co-expressed in PLC and Huh7 drug-resistant cells induced by sorafenib, (2) the fold change was more than 4 times and the difference was statistically significant (P <0.05), the top 12 up regulated genes in PLC and Huh7 drug-resistant cell lines were found, which were TPSG1, CBX4, CLC, CLEC18C, LGI4, F2RL1, S100A6, HABP2, C15ORF48, ZG16, FOLH1, and EPCAM. Compared with the correlations between the twelve genes and the clinical biological characteristics by Ualcan database, the potentially significant gene CBX4 was screened out.

CONCLUSION

The human PLC and Huh7 drug-resistant cell lines of hepatocellular carcinoma induced by sorafenib were successfully established. CBX4, the gene related to sorafenib resistance in hepatocellular carcinoma, was screened out by the high-throughput cDNA sequencing (RNA-Seq) and further analysis using Ualcan database, which is providing a powerful basis for further research on the mechanism of sorafenib resistance of hepatocellular carcinoma.

Gene set analysis methods for the functional interpretation of non-mRNA data—Genomic range and ncRNA data

Gene set analysis (GSA) is one of the methods of choice for analyzing the results of current omics studies; however, it has been mainly developed to analyze mRNA (microarray, RNA-Seq) data. The following review includes an update regarding general methods and resources for GSA and then emphasizes GSA methods and tools for non-mRNA omics datasets, specifically genomic range data (ChIP-Seq, SNP and methylation) and ncRNA data (miRNAs, lncRNAs and others). In the end, the state of the GSA field for non-mRNA datasets is discussed, and some current challenges and trends are highlighted, especially the use of network approaches to face complexity issues.