Hepatic cystadenoma is a rare disease, accounting for about 5% of all cystic lesions, with a high tendency of malignant transformation. The preoperative diagnosis of cystadenoma is difficult, and some cystadenomas are easily misdiagnosed as hepatic cysts at first. Hepatic cyst is a relatively common liver disease, most of which are benign, but large hepatic cysts can lead to pressure on the bile duct, resulting in abnormal liver function. To better understand the difference between the microenvironment of cystadenomas and hepatic cysts, we performed single-nuclei RNA-sequencing on cystadenoma and hepatic cysts samples. In addition, we performed spatial transcriptome sequencing of hepatic cysts. Based on nucleus RNA-sequencing data, a total of seven major cell types were identified. Here we described the tumor microenvironment of cystadenomas and hepatic cysts, particularly the transcriptome signatures and regulators of immune cells and stromal cells. By inferring copy number variation, it was found that the malignant degree of hepatic stellate cells in cystadenoma was higher. Pseudotime trajectory analysis demonstrated dynamic transformation of hepatocytes in hepatic cysts and cystadenomas. Cystadenomas had higher immune infiltration than hepatic cysts, and T cells had a more complex regulatory mechanism in cystadenomas than hepatic cysts. Immunohistochemistry confirms a cystadenoma-specific T-cell immunoregulatory mechanism. These results provided a single-cell atlas of cystadenomas and hepatic cyst, revealed a more complex microenvironment in cystadenomas than in hepatic cysts, and provided new perspective for the molecular mechanisms of cystadenomas and hepatic cyst.

In humans, uric acid is an end-product of purine metabolism. Urate excretion from the human kidney is tightly regulated by reabsorption and secretion. At least eleven genes have been identified as human renal urate transporters. However, it remains unclear whether all renal tubular cells express the same set of urate transporters. Here, we show renal tubular cells are divided into three distinct cell populations for urate handling. Analysis of healthy human kidneys at single-cell resolution revealed that not all tubular cells expressed the same set of urate transporters. Only 32% of tubular cells were related to both reabsorption and secretion, while the remaining tubular cells were related to either reabsorption or secretion at 5% and 63%, respectively. These results provide physiological insight into the molecular function of the transporters and renal urate handling on single-cell units. Our findings suggest that three different cell populations cooperate to regulate urate excretion from the human kidney, and our proposed framework is a step forward in broadening the view from the molecular to the cellular level of transport capacity.

UNASSIGNED: Despite the critical role of the cardiovascular system, our understanding of its cellular and transcriptional diversity remains limited. We therefore sought to characterize the cellular composition, phenotypes, molecular pathways, and communication networks between cell types at the tissue and sub-tissue level across the cardiovascular system of the healthy Wistar rat, an important model in preclinical cardiovascular research. We obtained high quality tissue samples under controlled conditions that reveal a level of cellular detail so far inaccessible in human studies.
UNASSIGNED: We performed single nucleus RNA-sequencing in 78 samples in 10 distinct regions including the four chambers of the heart, ventricular septum, sinoatrial node, atrioventricular node, aorta, pulmonary artery, and pulmonary veins (PV), which produced an aggregate map of 505,835 nuclei. We identified 26 distinct cell types and additional subtypes, including a number of rare cell types such as PV cardiomyocytes and non-myelinating Schwann cells (NMSCs), and unique groups of vascular smooth muscle cells (VSMCs), endothelial cells (ECs) and fibroblasts (FBs), which gave rise to a detailed cell type distribution across tissues. We demonstrated differences in the cellular composition across different cardiac regions and tissue-specific differences in transcription for each cell type, highlighting the molecular diversity and complex tissue architecture of the cardiovascular system. Specifically, we observed great transcriptional heterogeneities among ECs and FBs. Importantly, several cell subtypes had a unique regional localization such as a subtype of VSMCs enriched in the large vasculature. We found the cellular makeup of PV tissue is closer to heart tissue than to the large arteries. We further explored the ligand-receptor repertoire across cell clusters and tissues, and observed tissue-enriched cellular communication networks, including heightened Nppa - Npr1/2/3 signaling in the sinoatrial node.
UNASSIGNED: Through a large single nucleus sequencing effort encompassing over 500,000 nuclei, we broadened our understanding of cellular transcription in the healthy cardiovascular system. The existence of tissue-restricted cellular phenotypes suggests regional regulation of cardiovascular physiology. The overall conservation in gene expression and molecular pathways across rat and human cell types, together with our detailed transcriptional characterization of each cell type, offers the potential to identify novel therapeutic targets and improve preclinical models of cardiovascular disease.

UNASSIGNED: Proliferative vitreoretinopathy (PVR) is the most common cause of failure of retinal reattachment surgery, and the molecular changes leading to this aberrant wound healing process are currently unknown. Our ultimate goal is to study PVR pathogenesis by employing single-cell transcriptomics to dissect cellular heterogeneity.
UNASSIGNED: Here we aimed to compare single-cell RNA sequencing (scRNA-seq)  and single-nucleus RNA-sequencing (snRNA-seq) of retinal PVR samples in the rabbit model.
UNASSIGNED: Unilateral induction of PVR lesions in rabbit eyes with contralateral eyes serving as controls.
UNASSIGNED: Proliferative vitreoretinopathy was induced unilaterally in Dutch Belted rabbits. At different timepoints after PVR induction, retinas were dissociated into either cells or nuclei suspension and processed for scRNA-seq or snRNA-seq.
UNASSIGNED: Single cell and nuclei transcriptomic profiles of retinas after PVR induction.
UNASSIGNED: Single-cell RNA sequencing and snRNA-seq were conducted on retinas at 4 hours and 14 days after disease induction. Although the capture rate of unique molecular identifiers and genes were greater in scRNA-seq samples, overall gene expression profiles of individual cell types were highly correlated between scRNA-seq and snRNA-seq. A major disparity between the 2 sequencing modalities was the cell type capture rate, however, with glial cell types overrepresented in scRNA-seq, and inner retinal neurons were enriched by snRNA-seq. Furthermore, fibrotic Müller glia were overrepresented in snRNA-seq samples, whereas reactive Müller glia were overrepresented in scRNA-seq samples. Trajectory analyses were similar between the 2 methods, allowing for the combined analysis of the scRNA-seq and snRNA-seq data sets.
UNASSIGNED: These findings highlight limitations of both scRNA-seq and snRNA-seq analysis and imply that use of both techniques together can more accurately identify transcriptional networks critical for aberrant fibrogenesis in PVR than using either in isolation.
UNASSIGNED: Proprietary or commercial disclosure may be found after the references.

Deconvolution of cell mixtures in \"bulk\" transcriptomic samples from homogenate human tissue is important for understanding the pathologies of diseases. However, several experimental and computational challenges remain in developing and implementing transcriptomics-based deconvolution approaches, especially those using a single cell/nuclei RNA-seq reference atlas, which are becoming rapidly available across many tissues. Notably, deconvolution algorithms are frequently developed using samples from tissues with similar cell sizes. However, brain tissue or immune cell populations have cell types with substantially different cell sizes, total mRNA expression, and transcriptional activity. When existing deconvolution approaches are applied to these tissues, these systematic differences in cell sizes and transcriptomic activity confound accurate cell proportion estimates and instead may quantify total mRNA content. Furthermore, there is a lack of standard reference atlases and computational approaches to facilitate integrative analyses, including not only bulk and single cell/nuclei RNA-seq data, but also new data modalities from spatial -omic or imaging approaches. New multi-assay datasets need to be collected with orthogonal data types generated from the same tissue block and the same individual, to serve as a \"gold standard\" for evaluating new and existing deconvolution methods. Below, we discuss these key challenges and how they can be addressed with the acquisition of new datasets and approaches to analysis.

Single cell sequencing of human heart tissue is technically challenging and methods to cryopreserve heart tissue for obtaining single cell information have not been standardized. Studies published to date have used varying methods to preserve and process human heart tissue, and have generated interesting datasets, but development of a biobanking standard has not yet been achieved. Heart transcription patterns are known to be regionally diverse, and there are few single cell datasets for normal human heart tissue.
Using pig tissue, we developed a rigorous and reproducible method for tissue mincing and cryopreservation that allowed recovery of high quality single nuclei RNA. We subsequently tested this protocol on normal human heart tissue obtained from organ donors and were able to recover high quality nuclei for generation of single nuclei RNA-seq datasets, using a commercially available platform from 10× Genomics. We analyzed these datasets using standard software packages such as CellRanger and Seurat.
Human heart tissue preserved with our method consistently yielded nuclear RNA with RNA Integrity Numbers of greater than 8.5. We demonstrate the utility of this method for single nuclei RNA-sequencing of the normal human interventricular septum and delineating its cellular diversity. The human IVS showed unexpected diversity with detection of 23 distinct cell clusters that were subsequently categorized into different cell types. Cardiomyocytes and fibroblasts were the most commonly identified cell types and could be further subdivided into 5 different cardiomyocyte subtypes and 6 different fibroblast subtypes that differed by gene expression patterns. Ingenuity Pathway analysis of these gene expression patterns suggested functional diversity in these cell subtypes.
Here we report a simple technical method for cryopreservation and subsequent nuclear isolation of human interventricular septum tissue that can be done with common laboratory equipment. We show how this method can be used to generate single nuclei transcriptomic datasets that rival those already published by larger groups in terms of cell diversity and complexity and suggest that this simple method can provide guidance for biobanking of human myocardial tissue for complex genomic analysis.