Claspin is an essential protein for the ATR-dependent activation of the DNA replication checkpoint response in Xenopus and human cells. Here we describe the purification and characterization of human Claspin. The protein has a ring-like structure and binds with high affinity to branched DNA molecules. These findings suggest that Claspin may be a component of the replication ensemble and plays a role in the replication checkpoint by directly associating with replication forks and with the various branched DNA structures likely to form at stalled replication forks because of DNA damage.

Background Androgen receptor (AR) is critical to the initiation, growth, and progression of prostate cancer. Once activated, the AR binds to cis-regulatory enhancer elements on DNA that drive gene expression. Yet, there are 10–100× more binding sites than differentially expressed genes. It is unclear how or if these excess binding sites impact gene transcription. Results To characterize the regulatory logic of AR-mediated transcription, we generated a locus-specific map of enhancer activity by functionally testing all common clinical AR binding sites with Self-Transcribing Active Regulatory Regions sequencing (STARRseq). Only 7% of AR binding sites displayed androgen-dependent enhancer activity. Instead, the vast majority of AR binding sites were either inactive or constitutively active enhancers. These annotations strongly correlated with enhancer-associated features of both in vitro cell lines and clinical prostate cancer samples. Evaluating the effect of each enhancer class on transcription, we found that AR-regulated enhancers frequently interact with promoters and form central chromosomal loops that are required for transcription. Somatic mutations of these critical AR-regulated enhancers often impact enhancer activity. Conclusions Using a functional map of AR enhancer activity, we demonstrated that AR-regulated enhancers act as a regulatory hub that increases interactions with other AR binding sites and gene promoters.

BackgroundCaenorhabditis elegans provides a genetically tractable model organism to investigate the network of genes involved in fat metabolism and how regulation is perturbed to produce the complex phenotype of obesity. C. elegans possess the full range of desaturases, including the Δ9 desaturases expressed by fat-5, fat-6 and fat-7. They regulate the biosynthesis of monounsaturated fatty acids, used for the synthesis of lipids including phospholipids, triglycerides and cholesteryl esters.ResultsLiquid chromatography mass spectrometry (LC-MS), gas chromatography mass spectrometry (GC-MS) and nuclear magnetic resonance (NMR) spectroscopy were used to define the metabolome of all the possible knock-outs for the Δ9 desaturases, including for the first time intact lipids. Despite the genes having similar enzymatic roles, excellent discrimination was achievable for all single and viable double mutants highlighting the distinctive roles of fat-6 and fat-7, both expressing steroyl-CoA desaturases. The metabolomic changes extend to aqueous metabolites demonstrating the influence Δ9 desaturases have on regulating global metabolism and highlighting how comprehensive metabolomics is more discriminatory than classically used dyes for fat staining.ConclusionsThe propagation of metabolic changes across the network of metabolism demonstrates that modification of the Δ9 desaturases places C.elegans into a catabolic state compared with wildtype controls.

Well-differentiated papillary mesothelioma (WDPM) is an uncommon mesothelial proliferation that is most commonly encountered as an incidental finding in the peritoneal cavity. There is controversy in the literature about whether WDPM is a neoplasm or a reactive process and, if neoplastic, whether it is a variant or precursor of epithelial malignant mesothelioma or is a different entity. Using whole exome sequencing of five WDPMs of the peritoneum, we have identified distinct mutations in EHD1, ATM, FBXO10, SH2D2A, CDH5, MAGED1, and TP73 shared by WDPM cases but not reported in malignant mesotheliomas. Furthermore, we show that WDPM is strongly enriched with C > A transversion substitution mutations, a pattern that is also not found in malignant mesotheliomas. The WDPMs lacked the alterations involving BAP1, SETD2, NF2, CDKN2A/B, LASTS1/2, PBRM1, and SMARCC1 that are frequently found in malignant mesotheliomas. We conclude that WDPMs are neoplasms that are genetically distinct from malignant mesotheliomas and, based on observed mutations, do not appear to be precursors of malignant mesotheliomas.

Abstract. Based on direct sequencing information from 5H UTR and NS5B regions, we identified subtype 1b as a predominant hepatitis C virus genome in Turkey, which affected more than 91% of 79 patients studied. Next, the full genome sequence of a Turkish 1b isolate was obtained by the cloning of polypeptide-encoding region into 7 overlapping fragments. Turkish 1b isolate, which was named HCV-TR1, comprises 9361 nucleotides, including 306 nucleotides of 5 H UTR, a single long open reading frame of 9033 nucleotides, and 22 nucleotides of 3 H UTR. When compared to HCV 1b polypeptide sequences available at GenBank, the predicted polypeptide displayed a total of 36 amino acid substitutions, of which 16 was specific for HCV-TR1 isolate. Despite these changes, major structural and functional motifs of HCV proteins were maintained in HCV-TR1. In contrast, HCV-TR1 displayed amino acid substitutions in 6 out of 9 major cytotoxic T-cell epitopes. These data suggest that HCV-TR1 encodes functionally intact viral proteins, but it also encodes altered viral epitopes, which may affect host immune-response.

Androgen receptor (AR) is critical to the initiation, growth and progression of almost all prostate cancers. Once activated, the AR binds to cis-regulatory enhancer elements on DNA that drive gene expression. Yet, there are 10-100x more binding sites than differentially expressed genes. It still remains unclear how individual sites contribute to AR-mediated transcription. While descriptive functional genomic approaches broadly correlate with enhancer activity, they do not provide the locus-specific resolution needed to delineate the underlying regulatory logic of AR- mediated transcription. Therefore, we functionally tested all commonly occuring clinical AR binding sites with Self-Transcribing Active Regulatory Regions sequencing (STARRseq) to generate the first map of intrinsic AR enhancer activity. This approach is not significantly affected by endogenous chromatin modifications and measures the potential enhancer activity at each cis- regulatory element. Interestingly we found that only 7% of AR binding sites displayed increased enhancer activity upon hormonal stimulation. Instead, the vast majority of AR binding sites were either inactive (81%) or constitutively active enhancers (11%). These annotations strongly correlated with enhancer-associated features in both cell line and clinical prostate cancer. With these validated annotations we next investigated the effect of each enhancer class on transcription and found that AR-driven inducible enhancers frequently interacted with promoters, forming central chromosomal loops critical for gene transcription. We demonstrated that these inducible enhancers act as regulatory hubs that increase contacts with both other AR binding sites and gene promoters. This functional map was used to identify a somatic mutation that significantly reduces the expression of a commonly mutated AR-regulated tumour suppressor. Together, our data reveal a complex interplay between different AR binding sites that work in a highly coordinated manner to drive gene transcription.

Heart disease is the leading cause of global morbidity and mortality. This is in part because, despite an abundance of animal and in vitro models, it has been a challenge to date to study human heart tissue with sufficient depth and resolution to develop disease-modifying therapies for common cardiac conditions. Single-nucleus RNA sequencing (snRNA-seq) has emerged as a powerful tool capable of analyzing cellular function and signaling in health and disease, and has already contributed to significant advances in areas such as oncology and hematology. Employing snRNA-seq technology on flash-frozen human tissue has the potential to unlock novel disease mechanisms and pathways in any organ. Studying the human heart using snRNA-seq is a key priority for the field of cardiovascular sciences; however, progress to date has been slowed by numerous barriers. One key challenge is the fact that the human heart is very resistant to shearing and stress, making tissue dissociation and nuclear isolation difficult. Here, we describe a tissue dissociation method allowing the efficient and costeffective isolation of high-quality nuclei from flash-frozen human heart tissue collected in surgical operating rooms. Our protocol addresses the challenge of nuclear isolation from human hearts, enables snRNA-seq of the human heart, and paves the way for an improved understanding of the human heart in health and disease. Ultimately, this will be key to uncovering signaling pathways and networks amenable to therapeutic intervention and the development of novel biomarkers and disease-modifying therapies.

The vast majority of disease-associated single nucleotide polymorphisms (SNP) identified from genome-wide association studies (GWAS) are localized in non-coding regions. A significant fraction of these variants impact transcription factors binding to enhancer elements and alter gene expression. To functionally interrogate the activity of such variants we developed snpSTARRseq, a high-throughput experimental method that can interrogate the functional impact of hundreds to thousands of non-coding variants on enhancer activity. snpSTARRseq dramatically improves signal-to-noise by utilizing a novel sequencing and bioinformatic approach that increases both insert size and the number of variants tested per loci. Using this strategy, we interrogated known prostate cancer (PCa) risk-associated loci and demonstrated that 35% of them harbor SNPs that significantly altered enhancer activity. Combining these results with chromosomal looping data we could identify interacting genes and provide a mechanism of action for 20 PCa GWAS risk regions. When benchmarked to orthogonal methods, snpSTARRseq showed a strong correlation with in vivo experimental allelic-imbalance studies whereas there was no correlation with predictive in silico approaches. Overall, snpSTARRseq provides an integrated experimental and computational framework to functionally test non-coding genetic variants.