SUMMARY The Hippo/YAP signaling pathway is a crucial regulator of tissue growth, stem cell activity and tumorigenesis. However, the mechanism by which YAP controls transcription remains to be fully elucidated. Here, we utilize global chromatin occupancy analyses to demonstrate that robust YAP binding is restricted to a relatively small number of distal regulatory elements in the genome. YAP-occupancy defines a subset of enhancers and super-enhancers with the highest transcriptional outputs. YAP modulates transcription from these elements predominantly by regulating promoter-proximal Polymerase II (PolII) pause release. Mechanistically, YAP interacts and recruits the Mediator complex to enhancers, allowing the recruitment of the CDK9 elongating kinase. Genetic and chemical perturbation experiments demonstrate the requirement for Mediator and CDK9 in YAP-driven phenotypes of overgrowth and tumorigenesis. Our results here uncover the molecular mechanisms employed by YAP to exert its growth and oncogenic functions, and suggest strategies for intervention.

Overexpression of the histone methyltransferase MMSET in t(4;14)+ multiple myeloma patients is believed to be the driving factor in the pathogenesis of this subtype of myeloma. MMSET catalyzes dimethylation of lysine 36 on histone H3 (H3K36me2), and its overexpression causes a global increase in H3K36me2, redistributing this mark in a broad, elevated level across the genome. Here, we demonstrate that an increased level of MMSET also induces a global reduction of lysine 27 trimethylation on histone H3 (H3K27me3). Despite the net decrease in H3K27 methylation, specific genomic loci exhibit enhanced recruitment of the EZH2 histone methyltransferase and become hypermethylated on this residue. These effects likely contribute to the myeloma phenotype since MMSET-overexpressing cells displayed increased sensitivity to EZH2 inhibition. Furthermore, we demonstrate that such MMSET-mediated epigenetic changes require a number of functional domains within the protein, including PHD domains that mediate MMSET recruitment to chromatin. In vivo, targeting of MMSET by an inducible shRNA reversed histone methylation changes and led to regression of established tumors in athymic mice. Together, our work elucidates previously unrecognized interplay between MMSET and EZH2 in myeloma oncogenesis and identifies domains to be considered when designing inhibitors of MMSET function.

The role of the Hippo pathway effector YAP1 in soft tissue sarcomas is poorly defined. Here we report that YAP1 activity is elevated in human embryonal rhabdomyosarcoma (ERMS). In mice, sustained YAP1 hyperactivity in activated, but not quiescent, satellite cells induces ERMS with high penetrance and short latency. Via its transcriptional program with TEAD1, YAP1 directly regulates several major hallmarks of ERMS. YAP1-TEAD1 upregulate pro-proliferative and oncogenic genes and maintain the ERMS differentiation block by interfering with MYOD1 and MEF2 pro-differentiation activities. Normalization of YAP1 expression reduces tumor burden in human ERMS xenografts and allows YAP1-driven ERMS to differentiate in situ. Collectively, our results identify YAP1 as a potent ERMS oncogenic driver and a promising target for differentiation therapy.

Enhancement of structure-borne wave energy harvesting is investigated by exploiting metamaterial-based and metamaterial-inspired electroelastic systems. The concepts of wave focusing, localization, and funneling are leveraged to establish novel metamaterial energy harvester (MEH) configurations. The MEH systems transform the incoming structure-borne wave energy into electrical energy by coupling the metamaterial and electroelastic domains. The energy harvesting component of the work employs piezoelectric transduction due to the high power density and ease of application offered by piezoelectric materials. Therefore, in all MEH configurations studied in this work, the metamaterial system is combined with piezoelectric energy harvesting for enhanced electricity generation from waves propagating in elastic structures. Experiments are conducted to validate the dramatic performance enhancement in MEH systems as compared to using the same volume of piezoelectric patch in the absence of the metamaterial component. It is shown that MEH systems can be used for both broadband and tuned wave energy harvesting. The MEH concepts covered in this paper are (1) wave focusing using a metamaterial-inspired parabolic acoustic mirror (for broadband energy harvesting), (2) energy localization using an imperfection in a 2D lattice structure (for tuned energy harvesting), and (3) wave guiding using an acoustic funnel (for narrow-to-broadband energy harvesting). It is shown that MEH systems can boost the harvested power by more than an order of magnitude.

Background. Gene fusions arising from chromosomal translocations have been implicated in cancer. RNA-seq has the potential to discover such rearrangements generating functional proteins (chimera/fusion). Recently, many methods for chimeras detection have been published. However, specificity and sensitivity of those tools were not extensively investigated in a comparative way. Results. We tested eight fusion-detection tools (FusionHunter, FusionMap, FusionFinder, MapSplice, deFuse, Bellerophontes, ChimeraScan, and TopHat-fusion) to detect fusion events using synthetic and real datasets encompassing chimeras. The comparison analysis run only on synthetic data could generate misleading results since we found no counterpart on real dataset. Furthermore, most tools report a very high number of false positive chimeras. In particular, the most sensitive tool, ChimeraScan, reports a large number of false positives that we were able to significantly reduce by devising and applying two filters to remove fusions not supported by fusion junction-spanning reads or encompassing large intronic regions. Conclusions. The discordant results obtained using synthetic and real datasets suggest that synthetic datasets encompassing fusion events may not fully catch the complexity of RNA-seq experiment. Moreover, fusion detection tools are still limited in sensitivity or specificity; thus, there is space for further improvement in the fusion-finder algorithms.

PRDM family members are transcriptional regulators involved in tissue specific differentiation. PRDM5 has been reported to predominantly repress transcription, but a characterization of its molecular functions in a relevant biological context is lacking. We demonstrate here that Prdm5 is highly expressed in developing bones; and, by genome-wide mapping of Prdm5 occupancy in pre-osteoblastic cells, we uncover a novel and unique role for Prdm5 in targeting all mouse collagen genes as well as several SLRP proteoglycan genes. In particular, we show that Prdm5 controls both Collagen I transcription and fibrillogenesis by binding inside the Col1a1 gene body and maintaining RNA polymerase II occupancy. In vivo, Prdm5 loss results in delayed ossification involving a pronounced impairment in the assembly of fibrillar collagens. Collectively, our results define a novel role for Prdm5 in sustaining the transcriptional program necessary to the proper assembly of osteoblastic extracellular matrix.

BackgroundRNA-seq has the potential to discover genes created by chromosomal rearrangements. Fusion genes, also known as "chimeras", are formed by the breakage and re-joining of two different chromosomes. It is known that chimeras have been implicated in the development of cancer. Few publications in the past showed the presence of fusion events also in normal tissue, but with very limited overlaps between their results. More recently, two fusion genes in normal tissues were detected using both RNA-seq and protein data.Due to heterogeneous results in identifying chimeras in normal tissue, we decided to evaluate the efficacy of state of the art fusion finders in detecting chimeras in RNA-seq data from normal tissues.ResultsWe compared the performance of six fusion-finder tools: FusionHunter, FusionMap, FusionFinder, MapSplice, deFuse and TopHat-fusion. To evaluate the sensitivity we used a synthetic dataset of fusion-products, called positive dataset; in these experiments FusionMap, FusionFinder, MapSplice, and TopHat-fusion are able to detect more than 78% of fusion genes. All tools were error prone with high variability among the tools, identifying some fusion genes not present in the synthetic dataset. To better investigate the false discovery chimera detection rate, synthetic datasets free of fusion-products, called negative datasets, were used. The negative datasets have different read lengths and quality scores, which allow detecting dependency of the tools on both these features. FusionMap, FusionFinder, mapSplice, deFuse and TopHat-fusion were error-prone. Only FusionHunter results were free of false positive. FusionMap gave the best compromise in terms of specificity in the negative dataset and of sensitivity in the positive dataset.ConclusionsWe have observed a dependency of the tools on read length, quality score and on the number of reads supporting each chimera. Thus, it is important to carefully select the software on the basis of the structure of the RNA-seq data under analysis. Furthermore, the sensitivity of chimera detection tools does not seem to be sufficient to provide results consistent with those obtained in normal tissues on the basis of fusion events extracted from published data.

Given the neurotoxic role of β-amyloid in AD, dysregulation of the BACE1/BACE1-AS/β-amyloid axis might be relevant in HF pathogenesis, further implicating ncRNAs in the complex scenario of proteotoxicity in cardiac dysfunction.