Abstract 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.
Abstract Background Protein truncating mutations in the titin gene are associated with increased risk of atrial fibrillation (AF). However, little is known regarding the underlying pathophysiology. Methods We identified a heterozygous titin truncating variant in a patient with unexplained early-onset AF using whole exome sequencing. We used atrial and ventricular patient induced pluripotent stem cell-derived cardiomyocytes (iPSC-CMs), CRISPR/Cas9 genetic correction, and engineered heart tissue (EHT) constructs to evaluate the impact of the titin truncating variant on electrophysiology, sarcomere structure, contractility, and gene expression. Results We generated atrial and ventricular iPSC-CMs from the AF patient with the titin truncating variant and a CRISPR/Cas9 genome corrected isogenic control. We demonstrate that the titin truncating variant increases susceptibility to pacing-induced arrhythmia (prevalence of arrhythmogenic phenotypes, 85.7% versus 14.2%; P = 0.03), promotes sarcomere disorganization (mean ± SEM, 66.3 ± 6.8% versus 88.0 ± 2.9%; P = 0.04) in atrial iPSC-CMs, and reduces contractile force (0.013 ± 0.003 mN versus 0.027 ± 0.004 mN; P < 0.01) in atrial EHTs compared to isogenic controls. In ventricular iPSC-CMs, this variant led to altered electrophysiology (90.0% versus 33.3%; P = 0.02) and sarcomere organization (62.0 ± 3.9% versus 82.9 ± 2.9%; P < 0.01) with no change in EHT contractility compared to isogenic controls. RNA-sequencing revealed an upregulation of cell adhesion and extracellular matrix genes in the presence of the titin truncating variant for both atrial and ventricular EHTs. Conclusions In a patient with early-onset unexplained AF and normal ventricular function, iPSC-CMs with a titin truncating variant showed structural and electrophysiological abnormalities in both atrial and ventricular preparations, while only atrial EHTs demonstrated reduced contractility. Whole transcriptome sequencing showed upregulation of genes involved in cell-cell and cell-matrix interactions in both atrial and ventricular EHTs. Together, these findings suggest titin truncating variants promote the development of AF through remodeling of atrial cardiac tissue and provide insight into the chamber-specific effects of titin truncating variants.
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 Background Caenorhabditis 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. Results Liquid 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. Conclusions The 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.
Abstract Fertility preservation following pediatric cancer therapy programs has become a major avenue of infertility research. In vitro spermatogenesis (IVS) aims to generate sperm from banked prepubertal testicular tissues in a lab setting using specialized culture conditions. While successful using rodent tissues, progress with human tissues is limited by the scarcity of human prepubertal testicular tissues for research. This study posits that human induced pluripotent stem cells (hiPSCs) can model human prepubertal testicular tissue to facilitate the development of human IVS conditions. Testicular cells derived from hiPSCs are characterized for phenotype markers and profiled transcriptionally. HiPSC‐derived testicular cells are bioprinted into core–shell constructs representative of testis cytoarchitecture and found to capture functional aspects of prepubertal testicular tissues within 7 days under xeno‐free conditions. Moreover, hiPSC‐derived Sertoli cells illustrate the capacity to mature under pubertal‐like conditions. The utility of the model is tested by comparing 2 methods of supplementing retinoic acid (RA), the vitamin responsible for inducing spermatogenesis. The model reveals a significant gain in activity under microsphere‐released RA compared to RA medium supplementation, indicating that the fragility of free RA in vitro may be a contributing factor to the molecular dysfunction observed in human IVS studies to date.
Abstract Motivation A patient’s disease phenotype can be driven and determined by specific groups of cells whose marker genes are either unknown, or can only be detected at late-stage using conventional bulk assays such as RNA-Seq technology. Recent advances in single-cell RNA sequencing (scRNA-seq) enable gene expression profiling in cell-level resolution, and therefore have the potential to identify those cells driving the disease phenotype even while the number of these cells is small. However, most existing methods rely heavily on accurate cell type detection, and the number of available annotated samples is usually too small for training deep learning predictive models. Results Here we propose the method ScRAT for clinical phenotype prediction using scRNA-seq data. To train ScRAT with a limited number of samples of different phenotypes, such as COVID and non-COVID, ScRAT first applies a mixup module to increase the number of training samples. A multi-head attention mechanism is employed to learn the most informative cells for each phenotype without relying on a given cell type annotation. Using three public COVID datasets, we show that ScRAT outperforms other phenotype prediction methods. The performance edge of ScRAT over its competitors increases as the number of training samples decreases, indicating the efficacy of our sample mixup. Critical cell types detected based on high-attention cells also support novel findings in the original papers and the recent literature. This suggests that ScRAT overcomes the challenge of missing marker genes and limited sample number with great potential revealing novel molecular mechanisms and/or therapies.
Abstract The vast majority of disease-associated single nucleotide polymorphisms identified from genome-wide association study (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 number of variants tested per loci. Using this strategy, we interrogated 70 of 140 known prostate cancer (PCa) risk-associated loci and demonstrated that 26 (37%) of them harbor 36 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.
Abstract 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.
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