Scanpro is a tool for robust proportion analysis of single-cell resolution data.

In higher organisms, individual cells respond to signals and perturbations by epigenetic regulation and transcriptional adaptation. However, in addition to shifting the expression level of individual genes, the adaptive response of cells can also lead to shifts in the proportions of different cell types. Recent methods such as scRNA-seq allow for the interrogation of expression on the single-cell level, and can quantify individual cell type clusters within complex tissue samples. In order to identify clusters showing differential composition between different biological conditions, differential proportion analysis has recently been introduced. However, bioinformatics tools for robust proportion analysis of both replicated and unreplicated single-cell datasets are critically missing. In this manuscript, we present Scanpro, a modular tool for proportion analysis, seamlessly integrating into widely accepted frameworks in the Python environment. Scanpro is fast, accurate, supports datasets without replicates, and is intended to be used by bioinformatics experts and beginners alike.

Endocardial HDAC3 is required for myocardial trabeculation.

Failure of proper ventricular trabeculation is often associated with congenital heart disease. Support from endocardial cells, including the secretion of extracellular matrix and growth factors is critical for trabeculation. However, it is poorly understood how the secretion of extracellular matrix and growth factors is initiated and regulated by endocardial cells. We find that genetic knockout of histone deacetylase 3 in the endocardium in mice results in early embryo lethality and ventricular hypotrabeculation. Single cell RNA sequencing identifies significant downregulation of extracellular matrix components in histone deacetylase 3 knockout endocardial cells. Secretome from cultured histone deacetylase 3 knockout mouse cardiac endothelial cells lacks transforming growth factor ß3 and shows significantly reduced capacity in stimulating cultured cardiomyocyte proliferation, which is remarkably rescued by transforming growth factor ß3 supplementation. Mechanistically, we identify that histone deacetylase 3 knockout induces transforming growth factor ß3 expression through repressing microRNA-129-5p. Our findings provide insights into the pathogenesis of congenital heart disease and conceptual strategies to promote myocardial regeneration.

Uncovering uncharacterized binding of transcription factors from ATAC-seq footprinting data.

Transcription factors (TFs) are crucial epigenetic regulators, which enable cells to dynamically adjust gene expression in response to environmental signals. Computational procedures like digital genomic footprinting on chromatin accessibility assays such as ATACseq can be used to identify bound TFs in a genome-wide scale. This method utilizes short regions of low accessibility signals due to steric hindrance of DNA bound proteins, called footprints (FPs), which are combined with motif databases for TF identification. However, while over 1600 TFs have been described in the human genome, only ~ 700 of these have a known binding motif. Thus, a substantial number of FPs without overlap to a known DNA motif are normally discarded from FP analysis. In addition, the FP method is restricted to organisms with a substantial number of known TF motifs. Here we present DENIS (DE Novo motIf diScovery), a framework to generate and systematically investigate the potential of de novo TF motif discovery from FPs. DENIS includes functionality (1) to isolate FPs without binding motifs, (2) to perform de novo motif generation and (3) to characterize novel motifs. Here, we show that the framework rediscovers artificially removed TF motifs, quantifies de novo motif usage during an early embryonic development example dataset, and is able to analyze and uncover TF activity in organisms lacking canonical motifs. The latter task is exemplified by an investigation of a scATAC-seq dataset in zebrafish which covers different cell types during hematopoiesis.

The homeobox transcription factor DUXBL controls exit from totipotency.

In mice, exit from the totipotent two-cell (2C) stage embryo requires silencing of the 2C-associated transcriptional program. However, the molecular mechanisms involved in this process remain poorly understood. Here we demonstrate that the 2C-specific transcription factor double homeobox protein (DUX) mediates an essential negative feedback loop by inducing the expression of DUXBL to promote this silencing. We show that DUXBL gains accessibility to DUX-bound regions specifically upon DUX expression. Furthermore, we determine that DUXBL interacts with TRIM24 and TRIM33, members of the TRIM superfamily involved in gene silencing, and colocalizes with them in nuclear foci upon DUX expression. Importantly, DUXBL overexpression impairs 2C-associated transcription, whereas Duxbl inactivation in mouse embryonic stem cells increases DUX-dependent induction of the 2C-transcriptional program. Consequently, DUXBL deficiency in embryos results in sustained expression of 2C-associated transcripts leading to early developmental arrest. Our study identifies DUXBL as an essential regulator of totipotency exit enabling the first divergence of cell fates.

Endocardial HDAC3 is required for myocardial trabeculation.

BACKGROUND: Trabeculation, a key process in early heart development, is the formation of myocardial trabecular meshwork. The failure of trabeculation often leads to embryonic lethality. Support from endocardial cells, including the secretion of extracellular matrix (ECM) and growth factors is critical for trabeculation; however, it is unknown how the secretion of ECM and growth factors is initiated and regulated by endocardial cells. METHODS: Various cellular and mouse models in conjunction with biochemical and molecular tools were employed to study the role of histone deacetylase 3 (HDAC3) in the developing endocardium. RESULTS: We found that genetic deletion of Hdac3 in endocardial cells in mice resulted in early embryo lethality presenting as a hypotrabeculation cardiac phenotype. Single cell RNA sequencing identified several ECM components including collagens that were significantly downregulated in Hdac3 knockout (KO) endocardial cells. When cultured with supernatant from Hdac3 KO mouse cardiac endothelial cells (MCECs), wild-type mouse embryonic cardiomyocytes showed decreased proliferation, suggesting that growth signaling from Hdac3 KO MCECs is disrupted. Subsequent transcriptomic analysis revealed that transforming growth factor ß3 (TGFß3) was significantly downregulated in Hdac3 KO MCECs and Hdac3 cardiac endothelial KO hearts. Mechanistically, we identified that microRNA (miR)-129-5p was significantly upregulated in Hdac3 KO MCECs and Hdac3 cardiac endothelial KO hearts. Overexpression of miR-129-5p repressed Tgfß3 expression in wild-type MCECs, whereas knockdown of miR-129-5p restored Tgfß3 expression in Hdac3 KO MCECs. CONCLUSION: Our findings reveal a critical signaling pathway in which endocardial HDAC3 promotes trabecular myocardium growth by stimulating TGFß signaling through repressing miR-129-5p, providing novel insights into the etiology of congenital heart disease and conceptual strategies to promote myocardial regeneration.

TF-COMB - Discovering grammar of transcription factor binding sites.

Cooperativity between transcription factors is important to regulate target gene expression. In particular, the binding grammar of TFs in relation to each other, as well as in the context of other genomic elements, is crucial for TF functionality. However, tools to easily uncover co-occurrence between DNA-binding proteins, and investigate the regulatory modules of TFs, are limited. Here we present TF-COMB (Transcription Factor Co-Occurrence using Market Basket analysis) - a tool to investigate co-occurring TFs and binding grammar within regulatory regions. We found that TF-COMB can accurately identify known co-occurring TFs from ChIP-seq data, as well as uncover preferential localization to other genomic elements. With the use of ATAC-seq footprinting and TF motif locations, we found that TFs exhibit both preferred orientation and distance in relation to each other, and that these are biologically significant. Finally, we extended the analysis to not only investigate individual TF pairs, but also TF pairs in the context of networks, which enabled the investigation of TF complexes and TF hubs. In conclusion, TF-COMB is a flexible tool to investigate various aspects of TF binding grammar.

i2dash: Creation of Flexible, Interactive, and Web-based Dashboards for Visualization of Omics Data.

Data visualization and interactive data exploration are important aspects of illustrating complex concepts and results from analyses of omics data. A suitable visualization has to be intuitive and accessible. Web-based dashboards have become popular tools for the arrangement, consolidation, and display of such visualizations. However, the combination of automated data processing pipelines handling omics data and dynamically generated, interactive dashboards is poorly solved. Here, we present i2dash, an R package intended to encapsulate functionality for the programmatic creation of customized dashboards. It supports interactive and responsive (linked) visualizations across a set of predefined graphical layouts. i2dash addresses the needs of data analysts/software developers for a tool that is compatible and attachable to any R-based analysis pipeline, thereby fostering the separation of data visualization on one hand and data analysis tasks on the other hand. In addition, the generic design of i2dash enables the development of modular extensions for specific needs. As a proof of principle, we provide an extension of i2dash optimized for single-cell RNA sequencing analysis, supporting the creation of dashboards for the visualization needs of such experiments. Equipped with these features, i2dash is suitable for extensive use in large-scale sequencing/bioinformatics facilities. Along this line, we provide i2dash as a containerized solution, enabling a straightforward large-scale deployment and sharing of dashboards using cloud services. i2dash is freely available via the R package archive CRAN (https://CRAN.R-project.org/package=i2dash).

multicrispr: gRNA design for prime editing and parallel targeting of thousands of targets.

Targeting the coding genome to introduce nucleotide deletions/insertions via the CRISPR/Cas9 technology has become a standard procedure. It has quickly spawned a multitude of methods such as prime editing, APEX proximity labeling, or homology directed repair, for which supporting bioinformatics tools are, however, lagging behind. New CRISPR/Cas9 applications often require specific gRNA design functionality, and a generic tool is critically missing. Here, we introduce multicrispr, an R/bioconductor tool, intended to design individual gRNAs and complex gRNA libraries. The package is easy to use; detects, scores, and filters gRNAs on both efficiency and specificity; visualizes and aggregates results per target or CRISPR/Cas9 sequence; and finally returns both genomic ranges and sequences of gRNAs. To be generic, multicrispr defines and implements a genomic arithmetic framework as a basis for facile adaptation to techniques recently introduced such as prime editing or yet to arise. Its performance and design concepts such as target set-specific filtering render multicrispr a tool of choice when dealing with screening-like approaches.

ATAC-seq footprinting unravels kinetics of transcription factor binding during zygotic genome activation.

While footprinting analysis of ATAC-seq data can theoretically enable investigation of transcription factor (TF) binding, the lack of a computational tool able to conduct different levels of footprinting analysis has so-far hindered the widespread application of this method. Here we present TOBIAS, a comprehensive, accurate, and fast footprinting framework enabling genome-wide investigation of TF binding dynamics for hundreds of TFs simultaneously. We validate TOBIAS using paired ATAC-seq and ChIP-seq data, and find that TOBIAS outperforms existing methods for bias correction and footprinting. As a proof-of-concept, we illustrate how TOBIAS can unveil complex TF dynamics during zygotic genome activation in both humans and mice, and propose how zygotic Dux activates cascades of TFs, binds to repeat elements and induces expression of novel genetic elements.

AP-1 Contributes to Chromatin Accessibility to Promote Sarcomere Disassembly and Cardiomyocyte Protrusion During Zebrafish Heart Regeneration.

RATIONALE: The adult human heart is an organ with low regenerative potential. Heart failure following acute myocardial infarction is a leading cause of death due to the inability of cardiomyocytes to proliferate and replenish lost cardiac muscle. While the zebrafish has emerged as a powerful model to study endogenous cardiac regeneration, the molecular mechanisms by which cardiomyocytes respond to damage by disassembling sarcomeres, proliferating, and repopulating the injured area remain unclear. Furthermore, we are far from understanding the regulation of the chromatin landscape and epigenetic barriers that must be overcome for cardiac regeneration to occur. OBJECTIVE: To identify transcription factor regulators of the chromatin landscape, which promote cardiomyocyte regeneration in zebrafish, and investigate their function. METHODS AND RESULTS: Using the Assay for Transposase-Accessible Chromatin coupled to high-throughput sequencing (ATAC-Seq), we first find that the regenerating cardiomyocyte chromatin accessibility landscape undergoes extensive changes following cryoinjury, and that activator protein-1 (AP-1) binding sites are the most highly enriched motifs in regions that gain accessibility during cardiac regeneration. Furthermore, using bioinformatic and gene expression analyses, we find that the AP-1 response in regenerating adult zebrafish cardiomyocytes is largely different from the response in adult mammalian cardiomyocytes. Using a cardiomyocyte-specific dominant negative approach, we show that blocking AP-1 function leads to defects in cardiomyocyte proliferation as well as decreased chromatin accessibility at the fbxl22 and ilk loci, which regulate sarcomere disassembly and cardiomyocyte protrusion into the injured area, respectively. We further show that overexpression of the AP-1 family members Junb and Fosl1 can promote changes in mammalian cardiomyocyte behavior in vitro. CONCLUSIONS: AP-1 transcription factors play an essential role in the cardiomyocyte response to injury by regulating chromatin accessibility changes, thereby allowing the activation of gene expression programs that promote cardiomyocyte dedifferentiation, proliferation, and protrusion into the injured area.

WIlsON: Web-based Interactive Omics VisualizatioN.

MOTIVATION: High throughput (HT) screens in the omics field are typically analyzed by automated pipelines that generate static visualizations and comprehensive spreadsheet data for scientists. However, exploratory and hypothesis driven data analysis are key aspects of the understanding of biological systems, both generating extensive need for customized and dynamic visualization. RESULTS: Here we describe WIlsON, an interactive workbench for analysis and visualization of multi-omics data. It is primarily intended to empower screening platforms to offer access to pre-calculated HT screen results to the non-computational scientist. Facilitated by an open file format, WIlsON supports all types of omics screens, serves results via a web-based dashboard, and enables end users to perform analyses and generate publication-ready plots. AVAILABILITY AND IMPLEMENTATION: We implemented WIlsON in R with a focus on extensibility using the modular Shiny and Plotly frameworks. A demo of the interactive workbench without limitations may be accessed at http://loosolab.mpi-bn.mpg.de. A standalone Docker container as well as the source code of WIlsON are freely available from our Docker hub https://hub.docker. com/r/loosolab/wilson, CRAN https://cran.r-project.org/web/packages/wilson/, and GitHub repository https://github.molgen.mpg.de/loosolab/wilson-apps, respectively.