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Background and aims:The atherosclerotic plaque microenvironment is highly complex, and selective agents that modulate plaque stability are not yet available. We sought to develop a scRNA-seq analysis workflow to investigate this environment and uncover potential therapeutic approaches. We designed a user-friendly, reproducible workflow that will be applicable to other disease-specific scRNA-seq datasets. Methods: Here we incorporated automated cell labeling, pseudotemporal ordering, ligand-receptor evaluation, and drug-gene interaction analysis into a ready-to-deploy workflow. We applied this pipeline to further investigate a previously published human coronary single-cell dataset by Wirka et al. Notably, we developed an interactive web application to enable further exploration and analysis of this and other cardiovascular single-cell datasets.Results: We revealed distinct derivations of fibroblast-like cells from smooth muscle cells (SMCs), and showed the key changes in gene expression along their de-differentiation path. We highlighted several key ligand-receptor interactions within the atherosclerotic environment through functional expression profiling and revealed several avenues for future pharmacological development for precision medicine. Further, our interactive web application, PlaqView (www.plaqview.com), allows lay scientists to explore this and other datasets and compare scRNA-seq tools without prior coding knowledge. Conclusions: This publicly available workflow and application will allow for more systematic and user-friendly analysis of scRNA datasets in other disease and developmental systems. Our analysis pipeline provides many hypothesis-generating tools to unravel the etiology of coronary artery disease. We also highlight potential

Fat stored in the form of lipid droplets has long been considered a defining characteristic of cytoplasm. However, recent studies have shown that nuclear lipid droplets occur in multiple cells and tissues, including in human patients with fatty liver disease. The function(s) of stored fat in the nucleus has not been determined, and it is possible that nuclear fat is beneficial in some situations. Conversely, nuclear lipid droplets might instead be deleterious by disrupting nuclear organization or triggering aggregation of hydrophobic proteins. We show here that nuclear lipid droplets occur normally in C. elegans intestinal cells and germ cells, but appear to be associated with damage only in the intestine. Lipid droplets in intestinal nuclei can be associated with novel bundles of microfilaments (nuclear actin) and membrane tubules that might have roles in damage repair. To increase the normal, low frequency of nuclear lipid droplets in wild-type animals, we used a forward genetic screen to isolate mutants with abnormally large or abundant nuclear lipid droplets. Genetic analysis and cloning of three such mutants showed that the genes encode the lipid regulator SEIP-1/seipin, the inner nuclear membrane protein NEMP-1/Nemp1/TMEM194A, and a component of COPI vesicles called COPA-1/α-COP. We present several lines of evidence that the nuclear lipid droplet phenotype of copa-1 mutants results from a defect in retrieving mislocalized membrane proteins that normally reside in the endoplasmic reticulum. The seip-1 mutant causes most germ cells to have nuclear lipid droplets, the largest of which occupy more than a third of the nuclear volume. Nevertheless, the nuclear lipid droplets do not trigger apoptosis, and the germ cells differentiate into gametes that produce viable, healthy progeny. Thus, our results suggest that nuclear lipid droplets are detrimental to intestinal nuclei, but have no obvious deleterious effect on germ nuclei.

Coronary artery disease (CAD) is a complex inflammatory disease involving genetic influences across several cell types. Genome-wide association studies (GWAS) have identified over 170 loci associated with CAD, where the majority of risk variants reside in noncoding DNA sequences impacting cis-regulatory elements (CREs). Here, we applied single-cell ATAC-seq to profile 28,316 cells across coronary artery segments from 41 patients with varying stages of CAD, which revealed 14 distinct cellular clusters. We mapped ~320,000 accessible sites across all cells, identified cell type-specific elements, transcription factors, and prioritized functional CAD risk variants via quantitative trait locus and sequence-based predictive modeling. We identified a number of candidate mechanisms for smooth muscle cell transition states and identified putative binding sites for risk variants. We further employed DNA element to gene linkage to nominate disease-associated key driver transcription factors such as PRDM16 and TBX2. This single cell atlas provides a critical step towards interpreting cis-regulatory mechanisms in the vessel wall across the continuum of CAD risk.

In the version of this article initially published, Johan L. M. Björkegren's surname was misspelled as Björkgren. The error has been corrected in the HTML and PDF versions of the article.

Background Epigenome analysis relies on defined sets of genomic regions output by widely used assays such as ChIP-seq and ATAC-seq. Statistical analysis and visualization of genomic region sets is essential to answer biological questions in gene regulation. As the epigenomics community continues generating data, there will be an increasing need for software tools that can efficiently deal with more abundant and larger genomic region sets. Here, we introduce GenomicDistributions, an R package for fast and easy summarization and visualization of genomic region data. Results GenomicDistributions offers a broad selection of functions to calculate properties of genomic region sets, such as feature distances, genomic partition overlaps, and more. GenomicDistributions functions are meticulously optimized for best-in-class speed and generally outperform comparable functions in existing R packages. GenomicDistributions also offers plotting functions that produce editable ggplot objects. All GenomicDistributions functions follow a uniform naming scheme and can handle either single or multiple region set inputs. Conclusions GenomicDistributions offers a fast and scalable tool for exploratory genomic region set analysis and visualization. GenomicDistributions excels in user-friendliness, flexibility of outputs, breadth of functions, and computational performance. GenomicDistributions is available from Bioconductor (https://bioconductor.org/packages/release/bioc/html/GenomicDistributions.html).

Atherosclerosis is a complex inflammatory process driven by plaque formation in the major elastic arteries and often leads to reduced blood flow, coronary artery disease (CAD), myocardial infarction and stroke. CAD progression involves complex interactions and phenotypic plasticity within and between distinct vascular and immune cell lineages. Several single-cell RNA-seq (scRNA-seq) studies have highlighted lineage-specific transcriptomic signatures however there remains variability on the reported cell phenotypes in humans. In this study we meta-analyzed scRNA-seq datasets across four publications to create a comprehensive map of human atherosclerosis cell diversity. We applied standardized QC, processing, and integration benchmarking to harmonize 118,578 high-quality cells for this atlas. Beyond characterizing vascular and immune cell diversity, we derived insights into smooth muscle cell (SMC) phenotypic modulation through pseudotime, transcription factor activity inference and cell-cell communication analyses. We also integrated genome-wide association study (GWAS) data to identify etiologic cell types for GWAS diseases and traits, which uncovered a critical role for modulated SMC phenotypes in CAD and coronary artery calcification. Finally, we identified candidate markers (e.g., CRTAC1) of synthetic and osteochondrogenic SMCs that may serve as proxies of atherosclerosis progression. Together, this represents an important step towards creating a unified cellular map of atherosclerosis to inform cell state-specific mechanistic and translational studies of cardiovascular diseases.

Vascular calcification (VC) is concomitant with atherosclerosis, yet it remains uncertain why rupture-prone high-risk plaques do not typically show extensive calcification. Intraplaque hemorrhage (IPH) deposits erythrocyte-derived cholesterol enlarging the necrotic core and promoting the high-risk plaque development. Pro-atherogenic CD163 + alternative macrophages engulf hemoglobin-haptoglobin (HH) complexes at IPH sites. However, their role in VC has never been examined. Here we show, in human arteries, the distribution of CD163 + macrophages correlates inversely with VC. In vitro experiments using vascular smooth muscle cells (VSMC) cultured with HH-exposed human macrophages supernatant (M(Hb)) reduced calcification, while arteries from ApoE -/-CD163 -/mice showed greater VC. M(Hb) supernatant-exposed VSMC showed activated NFκB, while blocking NFκB attenuated the anti-calcific effect of M(Hb) on VSMCs. CD163 + macrophages altered VC through NFκB-induced transcription of hyaluronan synthase (HAS), an enzyme which catalyzes the formation of the extracellular matrix glycosaminoglycan, hyaluronan, within VSMCs. M(Hb) supernatants enhanced HAS production in VSMC, while knocking-down HAS attenuated its anti-calcific effect. NFκB blockade in ApoE -/mice reduced hyaluronan and increased VC. In human arteries, hyaluronan/HAS were increased in areas of CD163 + macrophage presence. Our findings highlight an important mechanism by which CD163 + macrophages inhibit VC through NFκB-induced HAS augmentation and thus promote the high-risk plaques development.