High-throughput sequencing of polyA+ RNA (RNA-Seq) in human cancer shows remarkable potential to identify both novel markers of disease and uncharacterized aspects of tumor biology, particularly non-coding RNA (ncRNA) species. We employed RNA-Seq on a cohort of 102 prostate tissues and cells lines and performed ab initio transcriptome assembly to discover unannotated ncRNAs. We nominated 121 such Prostate Cancer Associated Transcripts (PCATs) with cancer-specific expression patterns. Among these, we characterized PCAT-1 as a novel prostate-specific regulator of cell proliferation and target of the Polycomb Repressive Complex 2 (PRC2). We further found that high PCAT-1 and PRC2 expression stratified patient tissues into molecular subtypes distinguished by expression signatures of PCAT-1-repressed target genes. Taken together, the findings presented herein identify PCAT-1 as a novel transcriptional repressor implicated in subset of prostate cancer patients. These findings establish the utility of RNA-Seq to identify disease-associated ncRNAs that may improve the stratification of cancer subtypes.

The human skeleton is affected by mutations in Low-density lipoprotein Receptor-related Protein 5 (LRP5). To understand how LRP5 influences bone properties, we generated mice with inducible Lrp5 mutations that cause high bone mass and low bone mass phenotypes in humans. We conditionally-induced Lrp5 mutations in osteocytes and found that bone properties in these mice were comparable to bone properties in mice with inherited mutations. We also conditionally-induced an Lrp5 mutation in cells that contribute to the appendicular skeleton, and not to the axial skeleton, and we observed bone properties were altered in the limbs, and not in the spine. These data indicate that Lrp5 signaling functions locally and suggest increasing LRP5 signaling in mature bone cells as a strategy to treat human low bone mass disorders, such as osteoporosis.

Steady-state gene expression is a coordination of synthesis and decay of RNA through epigenetic regulation, transcription factors, micro RNAs (miRNAs), and RNA-binding proteins. Here, we present bromouride labeling and sequencing (Bru-Seq) and bromouridine pulse-chase and sequencing (BruChase-Seq) to assess genomewide changes to RNA synthesis and stability in human fibroblasts at homeostasis and after exposure to the proinflammatory tumor necrosis factor (TNF). The inflammatory response in human cells involves rapid and dramatic changes in gene expression, and the Bru-Seq and BruChase-Seq techniques revealed a coordinated and complex regulation of gene expression both at the transcriptional and posttranscriptional levels. The combinatory analysis of both RNA synthesis and stability using Bru-Seq and BruChase-Seq allows for a much deeper understanding of mechanisms of gene regulation than afforded by the analysis of steady-state total RNA and should be useful in many biological settings.T he acute inflammatory response is critical for the defense against infections and in the healing of damaged tissues (1). The orchestration of the reprogramming of gene expression associated with the acute inflammatory response is complex and involves both transcriptional and posttranscriptional regulation (2-5). Conventional exploration of gene expression using total RNA does not fully capture this complexity because it does not provide insight into the contribution of nascent RNA synthesis or RNA decay to steady-state RNA changes. A number of different approaches have recently been developed to assess nascent RNA synthesis in cells such as global run-on and sequencing (GROSeq) (6), native elongating transcript sequencing (NET-Seq) (7), nascent RNA sequencing (Nascent-Seq) (8), and metabolic labeling of nascent RNA by using microarrays (9) or RNA-Seq (10, 11). By comparing the data obtained with metabolically labeled nascent RNA with the steady-state RNA levels, the rates of degradation of all transcripts can be computationally estimated. The stability of steady-state RNA can also be estimated from the decay rate of steady-state RNA after transcription inhibition (12)(13)(14) or by immunoprecipitation of metabolically labeled steady-state RNA after different chase periods (15, 16). These approaches work well when the system is at homeostasis, but not when conditions are altered by environmental stimuli or stress, such as the induction of the acute inflammatory response, when the rates of decay of transcripts are expected to change (10,11).In this study, we present Bru-Seq and BruChase-Seq based on bromouridine pulse labeling of nascent RNA followed by chases in uridine to obtain RNA populations of specific ages. The Brulabeled RNA is then immunocaptured followed by deep sequencing. These techniques allowed us to assess changes in the rates of both synthesis and degradation of RNA globally after the activation of the proinflammatory response by TNF. Our results provide a comprehensive and complex picture of the contribution of tr...

Beginning with precursor lesions, aberrant DNA methylation marks the entire spectrum of prostate cancer progression. We mapped the global DNA methylation patterns in select prostate tissues and cell lines using MethylPlex-next-generation sequencing (M-NGS). Hidden Markov model-based next-generation sequence analysis identified~68,000 methylated regions per sample. While global CpG island (CGI) methylation was not differential between benign adjacent and cancer samples, overall promoter CGI methylation significantly increased from~12.6% in benign samples to 19.3% and 21.8% in localized and metastatic cancer tissues, respectively (P-value < 2 3 10 -16 ). We found distinct patterns of promoter methylation around transcription start sites, where methylation occurred not only on the CGIs, but also on flanking regions and CGI sparse promoters. Among the 6691 methylated promoters in prostate tissues, 2481 differentially methylated regions (DMRs) are cancer-specific, including numerous novel DMRs. A novel cancer-specific DMR in the WFDC2 promoter showed frequent methylation in cancer (17/22 tissues, 6/6 cell lines), but not in the benign tissues (0/10) and normal PrEC cells. Integration of LNCaP DNA methylation and H3K4me3 data suggested an epigenetic mechanism for alternate transcription start site utilization, and these modifications segregated into distinct regions when present on the same promoter. Finally, we observed differences in repeat element methylation, particularly LINE-1, between ERG gene fusion-positive and -negative cancers, and we confirmed this observation using pyrosequencing on a tissue panel. This comprehensive methylome map will further our understanding of epigenetic regulation in prostate cancer progression.