24 research outputs found
Phenotype and Tissue Expression as a Function of Genetic Risk in Polycystic Ovary Syndrome.
No full textGenome-wide association studies and replication analyses have identified (n = 5) or replicated (n = 10) DNA variants associated with risk for polycystic ovary syndrome (PCOS) in European women. However, the causal gene and underlying mechanism for PCOS risk at these loci have not been determined. We hypothesized that analysis of phenotype, gene expression and metformin response as a function of genotype would identify candidate genes and pathways that could provide insight into the underlying mechanism for risk at these loci. To test the hypothesis, subjects with PCOS (n = 427) diagnosed according to the NIH criteria (< 9 menses per year and clinical or biochemical hyperandrogenism) and controls (n = 407) with extensive phenotyping were studied. A subset of subjects (n = 38) underwent a subcutaneous adipose tissue biopsy for RNA sequencing and were subsequently treated with metformin for 12 weeks with standardized outcomes measured. Data were analyzed according to genotype at PCOS risk loci and adjusted for the false discovery rate. A gene variant in the THADA locus was associated with response to metformin and metformin was a predicted upstream regulator at the same locus. Genotype at the FSHB locus was associated with LH levels. Genes near the PCOS risk loci demonstrated differences in expression as a function of genotype in adipose including BLK and NEIL2 (GATA4 locus), GLIPR1 and PHLDA1 (KRR1 locus). Based on the phenotypes, expression quantitative trait loci (eQTL), and upstream regulatory and pathway analyses we hypothesize that there are PCOS subtypes. FSHB, FHSR and LHR loci may influence PCOS risk based on their relationship to gonadotropin levels. The THADA, GATA4, ERBB4, SUMO1P1, KRR1 and RAB5B loci appear to confer risk through metabolic mechanisms. The IRF1, SUMO1P1 and KRR1 loci may confer PCOS risk in development. The TOX3 and GATA4 loci appear to be involved in inflammation and its consequences. The data suggest potential PCOS subtypes and point to the need for additional studies to replicate these findings and identify personalized diagnosis and treatment options for PCOS
CTCF and Rad21 act as host cell restriction factors for Kaposi's sarcoma-associated herpesvirus (KSHV) lytic replication by modulating viral gene transcription.
No full textKaposi's sarcoma-associated herpesvirus (KSHV) is a human herpesvirus that causes Kaposi's sarcoma and is associated with the development of lymphoproliferative diseases. KSHV reactivation from latency and virion production is dependent on efficient transcription of over eighty lytic cycle genes and viral DNA replication. CTCF and cohesin, cellular proteins that cooperatively regulate gene expression and mediate long-range DNA interactions, have been shown to bind at specific sites in herpesvirus genomes. CTCF and cohesin regulate KSHV gene expression during latency and may also control lytic reactivation, although their role in lytic gene expression remains incompletely characterized. Here, we analyze the dynamic changes in CTCF and cohesin binding that occur during the process of KSHV viral reactivation and virion production by high resolution chromatin immunoprecipitation and deep sequencing (ChIP-Seq) and show that both proteins dissociate from viral genomes in kinetically and spatially distinct patterns. By utilizing siRNAs to specifically deplete CTCF and Rad21, a cohesin component, we demonstrate that both proteins are potent restriction factors for KSHV replication, with cohesin knockdown leading to hundred-fold increases in viral yield. High-throughput RNA sequencing was used to characterize the transcriptional effects of CTCF and cohesin depletion, and demonstrated that both proteins have complex and global effects on KSHV lytic transcription. Specifically, both proteins act as positive factors for viral transcription initially but subsequently inhibit KSHV lytic transcription, such that their net effect is to limit KSHV RNA accumulation. Cohesin is a more potent inhibitor of KSHV transcription than CTCF but both proteins are also required for efficient transcription of a subset of KSHV genes. These data reveal novel effects of CTCF and cohesin on transcription from a relatively small genome that resemble their effects on the cellular genome by acting as gene-specific activators of some promoters, but differ in acting as global negative regulators of transcription
Effect of CTCF and Rad21 depletion on the KSHV lytic gene transcriptional profile defined by RNA-Seq.
No full text<p>A. Transcriptome of iSLK cells at 24(C) are shown on the y-axis and the KSHV genome position on the x axis. Sites where CTCF or Rad21 knockdown leads to increased transcription compared to control are represented above the x-axis in blue. Regions where CTCF or Rad21 knockdown leads to decreased transcription compared to control are shown below the x-axis in red. Black bars show gene groups where the effects of CTCF and Rad21 differ and blue bars show genes that are CTCF and Rad21 dependent rather than repressed (see text). B. Effect of CTCF depletion on KSHV mRNAs. The effect of CTCF depletion on each annotated KSHV transcript is depicted as the log<sub>2</sub> ratio of its RNA abundance in the absence versus presence of CTCF at 48 h after induction. Transcripts whose levels increase with CTCF knockdown are thus shown above the x-axis and transcripts that decrease in abundance with CTCF knockdown are shown below. C. Effect of Rad21 depletion on KSHV mRNAs. The effect of Rad21 depletion on each annotated KSHV transcript is depicted as the log<sub>2</sub> ratio of its RNA abundance in the absence versus presence of Rad21 at 48 h after induction as described in panel (B) above.</p
LH and the LH:FSH ratio as a function of genotype at rs11031006 in PCOS and control subjects.
No full text*p<0.05.</p
KSHV virus production in cells depleted of Rad21.
No full text<p>A. KSHV-infected iSLK cells were transfected with either control siRNA (NC Si) or Rad21-specific siRNA (Rad21 Si), and KSHV replication was induced by treatment with doxycycline. Supernatants from induced cells were used to infect 293 cells. Virus passage was quantitated by flow cytometry of GFP-positive 293 cells. Each transfection/induction was performed in triplicate and three replicate infections were performed with each supernatant. B. CTCF knockdown (CTCF Si) and Rad21 knockdown (Rad21 Si) were performed on iSLK cells in parallel with control siRNA transfection (NC Si). Lytic replication was induced and virus production was measured by passage of virus to KSHV-negative 293 cells as in (A) above. C. CTCF, Rad21 and negative control knockdown were performed in iSLK cells as in (B) above and DNA was isolated from cell pellets. KSHV genome copy number was measured by qPCR. Cells were either untreated (−D) or treated with doxycycline (+D) to induce replication. RQ (relative quantitation). D. Immunoblotting of lysates from cells used in virus production experiments in panel B above was performed with anti-CTCF and anti-Rad21 antibodies to verify completeness of CTCF and Rad21 depletion. Lysates were prepared from cells harvested at the time of replication induction with doxycycline.</p
Top five networks identified by gene expression patterns at each polycystic ovary syndrome genetic risk locus.
No full textTop five networks identified by gene expression patterns at each polycystic ovary syndrome genetic risk locus.</p
Effect of CTCF depletion on KSHV lytic cycle gene expression.
No full text<p>KSHV-iSLK cells were depleted of CTCF (CTCF Si) or mock-depleted (NC Si) by siRNA transfection followed by treatment with doxycycline (−D, mock treatment; +D, doxycycline treatment) to induce lytic replication. RNA was prepared 48 h after induction of replication and relative quantification of mRNA expression (RQ) for each lytic gene was determined by qPCR. Results for ORF57 (A), ORF6 (B), ORF59 (C), ORF25 (D) and PAN (E) are shown. Each transfection was performed in triplicate and qPCR was performed with three technical replicates per sample. The level of expression for each RNA was normalized to the level of expression in uninduced cells.</p
