358 research outputs found

    The DAXX co-repressor is directly recruited to active regulatory elements genome-wide to regulate autophagy programs in a model of human prostate cancer.

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    While carcinoma of the prostate is the second most common cause of cancer death in the US, current methods and markers used to predict prostate cancer (PCa) outcome are inadequate. This study was aimed at understanding the genome-wide binding and regulatory role of the DAXX transcriptional repressor, recently implicated in PCa. ChIP-Seq analysis of genome-wide distribution of DAXX in PC3 cells revealed over 59,000 DAXX binding sites, found at regulatory enhancers and promoters. ChIP-Seq analysis of DNA methyltransferase 1 (DNMT1), which is a key epigenetic partner for DAXX repression, revealed that DNMT1 binding was restricted to a small number of DAXX sites. DNMT1 and DAXX bound close to transcriptional activator motifs. DNMT1 sites were found to be dependent on DAXX for recruitment by analyzing DNMT1 ChIP-Seq following DAXX knockdown (K/D), corroborating previous findings that DAXX recruits DNMT1 to repress its target genes. Massively parallel RNA sequencing (RNA-Seq) was used to compare the transcriptomes of WT and DAXX K/D PC3 cells. Genes induced by DAXX K/D included those involved in autophagy, and DAXX ChIP-Seq peaks were found close to the transcription start sites (TSS) of autophagy genes, implying they are more likely to be regulated by DAXX. In conclusion, DAXX binds active regulatory elements and co-localizes with DNMT1 in the prostate cancer genome. Given DAXX's putative regulatory role in autophagy, future studies may consider DAXX as a candidate marker and therapeutic target for prostate cancer

    Land Grant Application- Benner, Christopher (Dennysville)

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    Land grant application submitted to the Maine Land Office for Christopher Benner for service in the Revolutionary War.https://digitalmaine.com/revolutionary_war_me_land_office/1082/thumbnail.jp

    Control of VEGF-A transcriptional programs by pausing and genomic compartmentalization.

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    Vascular endothelial growth factor A (VEGF-A) is a master regulator of angiogenesis, vascular development and function. In this study we investigated the transcriptional regulation of VEGF-A-responsive genes in primary human aortic endothelial cells (HAECs) and human umbilical vein endothelial cells (HUVECs) using genome-wide global run-on sequencing (GRO-Seq). We demonstrate that half of VEGF-A-regulated gene promoters are characterized by a transcriptionally competent paused RNA polymerase II (Pol II). We show that transition into productive elongation is a major mechanism of gene activation of virtually all VEGF-regulated genes, whereas only ∼40% of the genes are induced at the level of initiation. In addition, we report a comprehensive chromatin interaction map generated in HUVECs using tethered conformation capture (TCC) and characterize chromatin interactions in relation to transcriptional activity. We demonstrate that sites of active transcription are more likely to engage in chromatin looping and cell type-specific transcriptional activity reflects the boundaries of chromatin interactions. Furthermore, we identify large chromatin compartments with a tendency to be coordinately transcribed upon VEGF-A stimulation. We provide evidence that these compartments are enriched for clusters of regulatory regions such as super-enhancers and for disease-associated single nucleotide polymorphisms (SNPs). Collectively, these findings provide new insights into mechanisms behind VEGF-A-regulated transcriptional programs in endothelial cells

    Inexact Solves in Interpolatory Model Reduction

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    We investigate the use of inexact solves for interpolatory model reduction and consider associated perturbation effects on the underlying model reduction problem. We give bounds on system perturbations induced by inexact solves and relate this to termination criteria for iterative solution methods. We show that when a Petrov-Galerkin framework is employed for the inexact solves, the associated reduced order model is an exact interpolatory model for a nearby full-order system; thus demonstrating backward stability. We also give evidence that for \h2-optimal interpolation points, interpolatory model reduction is robust with respect to perturbations due to inexact solves. Finally, we demonstrate the effecitveness of direct use of inexact solves in optimal H2{\mathcal H}_2 approximation. The result is an effective model reduction strategy that is applicable in realistically large-scale settings.Comment: 42 pages, 5 figure
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