AAV-delivered suppressor tRNA overcomes a nonsense mutation in mice.

Gene therapy is a potentially curative medicine for many currently untreatable diseases, and recombinant adeno-associated virus (rAAV) is the most successful gene delivery vehicle for in vivo applications1-3. However, rAAV-based gene therapy suffers from several limitations, such as constrained DNA cargo size and toxicities caused by non-physiological expression of a transgene4-6. Here we show that rAAV delivery of a suppressor tRNA (rAAV.sup-tRNA) safely and efficiently rescued a genetic disease in a mouse model carrying a nonsense mutation, and effects lasted for more than 6 months after a single treatment. Mechanistically, this was achieved through a synergistic effect of premature stop codon readthrough and inhibition of nonsense-mediated mRNA decay. rAAV.sup-tRNA had a limited effect on global readthrough at normal stop codons and did not perturb endogenous tRNA homeostasis, as determined by ribosome profiling and tRNA sequencing, respectively. By optimizing the AAV capsid and the route of administration, therapeutic efficacy in various target tissues was achieved, including liver, heart, skeletal muscle and brain. This study demonstrates the feasibility of developing a toolbox of AAV-delivered nonsense suppressor tRNAs operating on premature termination codons (AAV-NoSTOP) to rescue pathogenic nonsense mutations and restore gene function under endogenous regulation. As nonsense mutations account for 11% of pathogenic mutations, AAV-NoSTOP can benefit a large number of patients. AAV-NoSTOP obviates the need to deliver a full-length protein-coding gene that may exceed the rAAV packaging limit, elicit adverse immune responses or cause transgene-related toxicities. It therefore represents a valuable addition to gene therapeutics.

Intratracheally administered LNA gapmer antisense oligonucleotides induce robust gene silencing in mouse lung fibroblasts.

The lung is a complex organ with various cell types having distinct roles. Antisense oligonucleotides (ASOs) have been studied in the lung, but it has been challenging to determine their effectiveness in each cell type due to the lack of appropriate analytical methods. We employed three distinct approaches to study silencing efficacy within different cell types. First, we used lineage markers to identify cell types in flow cytometry, and simultaneously measured ASO-induced silencing of cell-surface proteins CD47 or CD98. Second, we applied single-cell RNA sequencing (scRNA-seq) to measure silencing efficacy in distinct cell types; to the best of our knowledge, this is the first time scRNA-seq has been applied to measure the efficacy of oligonucleotide therapeutics. In both approaches, fibroblasts were the most susceptible to locally delivered ASOs, with significant silencing also in endothelial cells. Third, we confirmed that the robust silencing in fibroblasts is broadly applicable by silencing two targets expressed mainly in fibroblasts, Mfap4 and Adam33. Across independent approaches, we demonstrate that intratracheally administered LNA gapmer ASOs robustly induce gene silencing in lung fibroblasts. ASO-induced gene silencing in fibroblasts was durable, lasting 4-8 weeks after a single dose. Thus, lung fibroblasts are well aligned with ASOs as therapeutics.

Genomic Characterization of Endothelial Enhancers Reveals a Multifunctional Role for NR2F2 in Regulation of Arteriovenous Gene Expression.

RATIONALE: Significant progress has revealed transcriptional inputs that underlie regulation of artery and vein endothelial cell fates. However, little is known concerning genome-wide regulation of this process. Therefore, such studies are warranted to address this gap. OBJECTIVE: To identify and characterize artery- and vein-specific endothelial enhancers in the human genome, thereby gaining insights into mechanisms by which blood vessel identity is regulated. METHODS AND RESULTS: Using chromatin immunoprecipitation and deep sequencing for markers of active chromatin in human arterial and venous endothelial cells, we identified several thousand artery- and vein-specific regulatory elements. Computational analysis revealed that NR2F2 (nuclear receptor subfamily 2, group F, member 2) sites were overrepresented in vein-specific enhancers, suggesting a direct role in promoting vein identity. Subsequent integration of chromatin immunoprecipitation and deep sequencing data sets with RNA sequencing revealed that NR2F2 regulated 3 distinct aspects related to arteriovenous identity. First, consistent with previous genetic observations, NR2F2 directly activated enhancer elements flanking cell cycle genes to drive their expression. Second, NR2F2 was essential to directly activate vein-specific enhancers and their associated genes. Our genomic approach further revealed that NR2F2 acts with ERG (ETS-related gene) at many of these sites to drive vein-specific gene expression. Finally, NR2F2 directly repressed only a small number of artery enhancers in venous cells to prevent their activation, including a distal element upstream of the artery-specific transcription factor, HEY2 (hes related family bHLH transcription factor with YRPW motif 2). In arterial endothelial cells, this enhancer was normally bound by ERG, which was also required for arterial HEY2 expression. By contrast, in venous endothelial cells, NR2F2 was bound to this site, together with ERG, and prevented its activation. CONCLUSIONS: By leveraging a genome-wide approach, we revealed mechanistic insights into how NR2F2 functions in multiple roles to maintain venous identity. Importantly, characterization of its role at a crucial artery enhancer upstream of HEY2 established a novel mechanism by which artery-specific expression can be achieved.

DolphinNext: a distributed data processing platform for high throughput genomics.

BACKGROUND: The emergence of high throughput technologies that produce vast amounts of genomic data, such as next-generation sequencing (NGS) is transforming biological research. The dramatic increase in the volume of data, the variety and continuous change of data processing tools, algorithms and databases make analysis the main bottleneck for scientific discovery. The processing of high throughput datasets typically involves many different computational programs, each of which performs a specific step in a pipeline. Given the wide range of applications and organizational infrastructures, there is a great need for highly parallel, flexible, portable, and reproducible data processing frameworks. Several platforms currently exist for the design and execution of complex pipelines. Unfortunately, current platforms lack the necessary combination of parallelism, portability, flexibility and/or reproducibility that are required by the current research environment. To address these shortcomings, workflow frameworks that provide a platform to develop and share portable pipelines have recently arisen. We complement these new platforms by providing a graphical user interface to create, maintain, and execute complex pipelines. Such a platform will simplify robust and reproducible workflow creation for non-technical users as well as provide a robust platform to maintain pipelines for large organizations. RESULTS: To simplify development, maintenance, and execution of complex pipelines we created DolphinNext. DolphinNext facilitates building and deployment of complex pipelines using a modular approach implemented in a graphical interface that relies on the powerful Nextflow workflow framework by providing 1. A drag and drop user interface that visualizes pipelines and allows users to create pipelines without familiarity in underlying programming languages. 2. Modules to execute and monitor pipelines in distributed computing environments such as high-performance clusters and/or cloud 3. Reproducible pipelines with version tracking and stand-alone versions that can be run independently. 4. Modular process design with process revisioning support to increase reusability and pipeline development efficiency. 5. Pipeline sharing with GitHub and automated testing 6. Extensive reports with R-markdown and shiny support for interactive data visualization and analysis. CONCLUSION: DolphinNext is a flexible, intuitive, web-based data processing and analysis platform that enables creating, deploying, sharing, and executing complex Nextflow pipelines with extensive revisioning and interactive reporting to enhance reproducible results.

DEBrowser: interactive differential expression analysis and visualization tool for count data.

BACKGROUND: Sequencing data has become a standard measure of diverse cellular activities. For example, gene expression is accurately measured by RNA sequencing (RNA-Seq) libraries, protein-DNA interactions are captured by chromatin immunoprecipitation sequencing (ChIP-Seq), protein-RNA interactions by crosslinking immunoprecipitation sequencing (CLIP-Seq) or RNA immunoprecipitation (RIP-Seq) sequencing, DNA accessibility by assay for transposase-accessible chromatin (ATAC-Seq), DNase or MNase sequencing libraries. The processing of these sequencing techniques involves library-specific approaches. However, in all cases, once the sequencing libraries are processed, the result is a count table specifying the estimated number of reads originating from each genomic locus. Differential analysis to determine which loci have different cellular activity under different conditions starts with the count table and iterates through a cycle of data assessment, preparation and analysis. Such complex analysis often relies on multiple programs and is therefore a challenge for those without programming skills. RESULTS: We developed DEBrowser as an R bioconductor project to interactively visualize every step of the differential analysis, without programming. The application provides a rich and interactive web based graphical user interface built on R's shiny infrastructure. DEBrowser allows users to visualize data with various types of graphs that can be explored further by selecting and re-plotting any desired subset of data. Using the visualization approaches provided, users can determine and correct technical variations such as batch effects and sequencing depth that affect differential analysis. We show DEBrowser's ease of use by reproducing the analysis of two previously published data sets. CONCLUSIONS: DEBrowser is a flexible, intuitive, web-based analysis platform that enables an iterative and interactive analysis of count data without any requirement of programming knowledge.

Predicting the impact of mutations on the specific activity of Bacillus thermocatenulatus lipase using a combined approach of docking and molecular dynamics.

Lipases are important biocatalysts owing to their ability to catalyze diverse reactions with exceptional substrate specificities. A combined docking and molecular dynamics (MD) approach was applied to study the chain-length selectivity of Bacillus thermocatenulatus lipase (BTL2) towards its natural substrates (triacylglycerols). A scoring function including electrostatic, van der Waals (vdW) and desolvation energies along with conformational entropy was developed to predict the impact of mutation. The native BTL2 and its 6 mutants (F17A, V175A, V175F, D176F, T178V and I320F) were experimentally analyzed to determine their specific activities towards tributyrin (C4) or tricaprylin (C8), which were used to test our approach. Our scoring methodology predicted the chain-length selectivity of BTL2 with 85.7% (6/7) accuracy with a positive correlation between the calculated scores and the experimental activity values (r = 0.82, p = 0.0004). Additionally, the impact of mutation on activity was predicted with 75% (9/12) accuracy. The described study represents a fast and reliable approach to accurately predict the effect of mutations on the activity and selectivity of lipases and also of other enzymes. Copyright © 2016 John Wiley & Sons, Ltd.

An atlas of cell types in the mouse epididymis and vas deferens.

Following testicular spermatogenesis, mammalian sperm continue to mature in a long epithelial tube known as the epididymis, which plays key roles in remodeling sperm protein, lipid, and RNA composition. To understand the roles for the epididymis in reproductive biology, we generated a single-cell atlas of the murine epididymis and vas deferens. We recovered key epithelial cell types including principal cells, clear cells, and basal cells, along with associated support cells that include fibroblasts, smooth muscle, macrophages and other immune cells. Moreover, our data illuminate extensive regional specialization of principal cell populations across the length of the epididymis. In addition to region-specific specialization of principal cells, we find evidence for functionally specialized subpopulations of stromal cells, and, most notably, two distinct populations of clear cells. Our dataset extends on existing knowledge of epididymal biology, and provides a wealth of information on potential regulatory and signaling factors that bear future investigation.

An improved zebrafish transcriptome annotation for sensitive and comprehensive detection of cell type-specific genes.

The zebrafish is ideal for studying embryogenesis and is increasingly applied to model human disease. In these contexts, RNA-sequencing (RNA-seq) provides mechanistic insights by identifying transcriptome changes between experimental conditions. Application of RNA-seq relies on accurate transcript annotation for a genome of interest. Here, we find discrepancies in analysis from RNA-seq datasets quantified using Ensembl and RefSeq zebrafish annotations. These issues were due, in part, to variably annotated 3' untranslated regions and thousands of gene models missing from each annotation. Since these discrepancies could compromise downstream analyses and biological reproducibility, we built a more comprehensive zebrafish transcriptome annotation that addresses these deficiencies. Our annotation improves detection of cell type-specific genes in both bulk and single cell RNA-seq datasets, where it also improves resolution of cell clustering. Thus, we demonstrate that our new transcriptome annotation can outperform existing annotations, providing an important resource for zebrafish researchers.