Showing papers on "Transcriptome published in 2019"

U1 snRNP regulates cancer cell migration and invasion

Abstract: Stimulated cells and cancer cells have widespread shortening of mRNA 3’-utranslated regions (3’UTRs) and switches to shorter mRNA isoforms due to usage of more proximal polyadenylation signals (PASs) in the last exon and in introns. U1 snRNA (U1), vertebrates’ most abundant non-coding (spliceosomal) small nuclear RNA, silences proximal PASs and its inhibition with antisense morpholino oligonucleotides (U1 AMO) triggers widespread mRNA shortening. Here we show that U1 AMO also modulates cancer cells’ phenotype, dose-dependently increasing migration and invasion in vitro by up to 500%, whereas U1 over-expression has the opposite effect. In addition to 3’UTR length, numerous transcriptome changes that could contribute to this phenotype are observed, including alternative splicing, and mRNA expression levels of proto-oncogenes and tumor suppressors. These findings reveal an unexpected link between U1 regulation and oncogenic and activated cell states, and suggest U1 as a potential target for their modulation.

Transcriptome-scale super-resolved imaging in tissues by RNA seqFISH

Abstract: Imaging the transcriptome in situ with high accuracy has been a major challenge in single-cell biology, which is particularly hindered by the limits of optical resolution and the density of transcripts in single cells1-5. Here we demonstrate an evolution of sequential fluorescence in situ hybridization (seqFISH+). We show that seqFISH+ can image mRNAs for 10,000 genes in single cells-with high accuracy and sub-diffraction-limit resolution-in the cortex, subventricular zone and olfactory bulb of mouse brain, using a standard confocal microscope. The transcriptome-level profiling of seqFISH+ allows unbiased identification of cell classes and their spatial organization in tissues. In addition, seqFISH+ reveals subcellular mRNA localization patterns in cells and ligand-receptor pairs across neighbouring cells. This technology demonstrates the ability to generate spatial cell atlases and to perform discovery-driven studies of biological processes in situ.

Single-Cell Transcriptomic Analysis of Human Lung Provides Insights into the Pathobiology of Pulmonary Fibrosis.

Abstract: Rationale: The contributions of diverse cell populations in the human lung to pulmonary fibrosis pathogenesis are poorly understood. Single-cell RNA sequencing can reveal changes within individual cell populations during pulmonary fibrosis that are important for disease pathogenesis. Objectives: To determine whether single-cell RNA sequencing can reveal disease-related heterogeneity within alveolar macrophages, epithelial cells, or other cell types in lung tissue from subjects with pulmonary fibrosis compared with control subjects. Methods: We performed single-cell RNA sequencing on lung tissue obtained from eight transplant donors and eight recipients with pulmonary fibrosis and on one bronchoscopic cryobiospy sample from a patient with idiopathic pulmonary fibrosis. We validated these data using in situ RNA hybridization, immunohistochemistry, and bulk RNA-sequencing on flow-sorted cells from 22 additional subjects. Measurements and Main Results: We identified a distinct, novel population of profibrotic alveolar macrophages exclusively in patients with fibrosis. Within epithelial cells, the expression of genes involved in Wnt secretion and response was restricted to nonoverlapping cells. We identified rare cell populations including airway stem cells and senescent cells emerging during pulmonary fibrosis. We developed a web-based tool to explore these data. Conclusions: We generated a single-cell atlas of pulmonary fibrosis. Using this atlas, we demonstrated heterogeneity within alveolar macrophages and epithelial cells from subjects with pulmonary fibrosis. These results support the feasibility of discovery-based approaches using next-generation sequencing technologies to identify signaling pathways for targeting in the development of personalized therapies for patients with pulmonary fibrosis.

Genetic compensation triggered by mutant mRNA degradation

Abstract: Genetic robustness, or the ability of an organism to maintain fitness in the presence of harmful mutations, can be achieved via protein feedback loops. Previous work has suggested that organisms may also respond to mutations by transcriptional adaptation, a process by which related gene(s) are upregulated independently of protein feedback loops. However, the prevalence of transcriptional adaptation and its underlying molecular mechanisms are unknown. Here, by analysing several models of transcriptional adaptation in zebrafish and mouse, we uncover a requirement for mutant mRNA degradation. Alleles that fail to transcribe the mutated gene do not exhibit transcriptional adaptation, and these alleles give rise to more severe phenotypes than alleles displaying mutant mRNA decay. Transcriptome analysis in alleles displaying mutant mRNA decay reveals the upregulation of a substantial proportion of the genes that exhibit sequence similarity with the mutated gene's mRNA, suggesting a sequence-dependent mechanism. These findings have implications for our understanding of disease-causing mutations, and will help in the design of mutant alleles with minimal transcriptional adaptation-derived compensation.

High-throughput sequencing of the transcriptome and chromatin accessibility in the same cell.

Abstract: Single-cell RNA sequencing can reveal the transcriptional state of cells, yet provides little insight into the upstream regulatory landscape associated with open or accessible chromatin regions. Joint profiling of accessible chromatin and RNA within the same cells would permit direct matching of transcriptional regulation to its outputs. Here, we describe droplet-based single-nucleus chromatin accessibility and mRNA expression sequencing (SNARE-seq), a method that can link a cell's transcriptome with its accessible chromatin for sequencing at scale. Specifically, accessible sites are captured by Tn5 transposase in permeabilized nuclei to permit, within many droplets in parallel, DNA barcode tagging together with the mRNA molecules from the same cells. To demonstrate the utility of SNARE-seq, we generated joint profiles of 5,081 and 10,309 cells from neonatal and adult mouse cerebral cortices, respectively. We reconstructed the transcriptome and epigenetic landscapes of major and rare cell types, uncovered lineage-specific accessible sites, especially for low-abundance cells, and connected the dynamics of promoter accessibility with transcription level during neurogenesis.

A deep proteome and transcriptome abundance atlas of 29 healthy human tissues

Abstract: Genome-, transcriptome- and proteome-wide measurements provide insights into how biological systems are regulated. However, fundamental aspects relating to which human proteins exist, where they ar ...

METTL3 facilitates tumor progression via an m6A-IGF2BP2-dependent mechanism in colorectal carcinoma

Abstract: Colorectal carcinoma (CRC) is one of the most common malignant tumors, and its main cause of death is tumor metastasis. RNA N6-methyladenosine (m6A) is an emerging regulatory mechanism for gene expression and methyltransferase-like 3 (METTL3) participates in tumor progression in several cancer types. However, its role in CRC remains unexplored. Western blot, quantitative real-time PCR (RT-qPCR) and immunohistochemical (IHC) were used to detect METTL3 expression in cell lines and patient tissues. Methylated RNA immunoprecipitation sequencing (MeRIP-seq) and transcriptomic RNA sequencing (RNA-seq) were used to screen the target genes of METTL3. The biological functions of METTL3 were investigated in vitro and in vivo. RNA pull-down and RNA immunoprecipitation assays were conducted to explore the specific binding of target genes. RNA stability assay was used to detect the half-lives of the downstream genes of METTL3. Using TCGA database, higher METTL3 expression was found in CRC metastatic tissues and was associated with a poor prognosis. MeRIP-seq revealed that SRY (sex determining region Y)-box 2 (SOX2) was the downstream gene of METTL3. METTL3 knockdown in CRC cells drastically inhibited cell self-renewal, stem cell frequency and migration in vitro and suppressed CRC tumorigenesis and metastasis in both cell-based models and PDX models. Mechanistically, methylated SOX2 transcripts, specifically the coding sequence (CDS) regions, were subsequently recognized by the specific m6A “reader”, insulin-like growth factor 2 mRNA binding protein 2 (IGF2BP2), to prevent SOX2 mRNA degradation. Further, SOX2 expression positively correlated with METTL3 and IGF2BP2 in CRC tissues. The combined IHC panel, including “writer”, “reader”, and “target”, exhibited a better prognostic value for CRC patients than any of these components individually. Overall, our study revealed that METTL3, acting as an oncogene, maintained SOX2 expression through an m6A-IGF2BP2-dependent mechanism in CRC cells, and indicated a potential biomarker panel for prognostic prediction in CRC.

Advantages of Single-Nucleus over Single-Cell RNA Sequencing of Adult Kidney: Rare Cell Types and Novel Cell States Revealed in Fibrosis

Abstract: Background A challenge for single-cell genomic studies in kidney and other solid tissues is generating a high-quality single-cell suspension that contains rare or difficult-to-dissociate cell types and is free of both RNA degradation and artifactual transcriptional stress responses. Methods We compared single-cell RNA sequencing (scRNA-seq) using the DropSeq platform with single-nucleus RNA sequencing (snRNA-seq) using sNuc-DropSeq, DroNc-seq, and 10X Chromium platforms on adult mouse kidney. We validated snRNA-seq on fibrotic kidney from mice 14 days after unilateral ureteral obstruction (UUO) surgery. Results A total of 11,391 transcriptomes were generated in the comparison phase. We identified ten clusters in the scRNA-seq dataset, but glomerular cell types were absent, and one cluster consisted primarily of artifactual dissociation – induced stress response genes. By contrast, snRNA-seq from all three platforms captured a diversity of kidney cell types that were not represented in the scRNA-seq dataset, including glomerular podocytes, mesangial cells, and endothelial cells. No stress response genes were detected. Our snRNA-seq protocol yielded 20-fold more podocytes compared with published scRNA-seq datasets (2.4% versus 0.12%, respectively). Unexpectedly, single-cell and single-nucleus platforms had equivalent gene detection sensitivity. For validation, analysis of frozen day 14 UUO kidney revealed rare juxtaglomerular cells, novel activated proximal tubule and fibroblast cell states, and previously unidentified tubulointerstitial signaling pathways. Conclusions snRNA-seq achieves comparable gene detection to scRNA-seq in adult kidney, and it also has substantial advantages, including reduced dissociation bias, compatibility with frozen samples, elimination of dissociation-induced transcriptional stress responses, and successful performance on inflamed fibrotic kidney.

Quality and quantity control of gene expression by nonsense-mediated mRNA decay

Abstract: Nonsense-mediated mRNA decay (NMD) is one of the best characterized and most evolutionarily conserved cellular quality control mechanisms. Although NMD was first found to target one-third of mutated, disease-causing mRNAs, it is now known to also target ~10% of unmutated mammalian mRNAs to facilitate appropriate cellular responses — adaptation, differentiation or death — to environmental changes. Mutations in NMD genes in humans are associated with intellectual disability and cancer. In this Review, we discuss how NMD serves multiple purposes in human cells by degrading both mutated mRNAs to protect the integrity of the transcriptome and normal mRNAs to control the quantities of unmutated transcripts. Nonsense-mediated mRNA decay (NMD) is a quality and quantity control mechanism for degrading mutated mRNAs to protect the integrity of the transcriptome and proteome and unmutated mRNAs to control their quantity. NMD dysfunction in humans is associated with intellectual disability and cancer.

Long Non-Coding RNAs in the Regulation of Gene Expression: Physiology and Disease

Abstract: The identification of RNAs that are not translated into proteins was an important breakthrough, defining the diversity of molecules involved in eukaryotic regulation of gene expression. These non-coding RNAs can be divided into two main classes according to their length: short non-coding RNAs, such as microRNAs (miRNAs), and long non-coding RNAs (lncRNAs). The lncRNAs in association with other molecules can coordinate several physiological processes and their dysfunction may impact in several pathologies, including cancer and infectious diseases. They can control the flux of genetic information, such as chromosome structure modulation, transcription, splicing, messenger RNA (mRNA) stability, mRNA availability, and post-translational modifications. Long non-coding RNAs present interaction domains for DNA, mRNAs, miRNAs, and proteins, depending on both sequence and secondary structure. The advent of new generation sequencing has provided evidences of putative lncRNAs existence; however, the analysis of transcriptomes for their functional characterization remains a challenge. Here, we review some important aspects of lncRNA biology, focusing on their role as regulatory elements in gene expression modulation during physiological and disease processes, with implications in host and pathogens physiology, and their role in immune response modulation.

Spatial transcriptome profiling by MERFISH reveals subcellular RNA compartmentalization and cell cycle-dependent gene expression.

Abstract: The expression profiles and spatial distributions of RNAs regulate many cellular functions. Image-based transcriptomic approaches provide powerful means to measure both expression and spatial information of RNAs in individual cells within their native environment. Among these approaches, multiplexed error-robust fluorescence in situ hybridization (MERFISH) has achieved spatially resolved RNA quantification at transcriptome scale by massively multiplexing single-molecule FISH measurements. Here, we increased the gene throughput of MERFISH and demonstrated simultaneous measurements of RNA transcripts from ∼10,000 genes in individual cells with ∼80% detection efficiency and ∼4% misidentification rate. We combined MERFISH with cellular structure imaging to determine subcellular compartmentalization of RNAs. We validated this approach by showing enrichment of secretome transcripts at the endoplasmic reticulum, and further revealed enrichment of long noncoding RNAs, RNAs with retained introns, and a subgroup of protein-coding mRNAs in the cell nucleus. Leveraging spatially resolved RNA profiling, we developed an approach to determine RNA velocity in situ using the balance of nuclear versus cytoplasmic RNA counts. We applied this approach to infer pseudotime ordering of cells and identified cells at different cell-cycle states, revealing ∼1,600 genes with putative cell cycle-dependent expression and a gradual transcription profile change as cells progress through cell-cycle stages. Our analysis further revealed cell cycle-dependent and cell cycle-independent spatial heterogeneity of transcriptionally distinct cells. We envision that the ability to perform spatially resolved, genome-wide RNA profiling with high detection efficiency and accuracy by MERFISH could help address a wide array of questions ranging from the regulation of gene expression in cells to the development of cell fate and organization in tissues.

Single-cell expression profiling reveals dynamic flux of cardiac stromal, vascular and immune cells in health and injury.

Abstract: Besides cardiomyocytes (CM), the heart contains numerous interstitial cell types which play key roles in heart repair, regeneration and disease, including fibroblast, vascular and immune cells. However, a comprehensive understanding of this interactive cell community is lacking. We performed single-cell RNA-sequencing of the total non-CM fraction and enriched (Pdgfra-GFP+) fibroblast lineage cells from murine hearts at days 3 and 7 post-sham or myocardial infarction (MI) surgery. Clustering of >30,000 single cells identified >30 populations representing nine cell lineages, including a previously undescribed fibroblast lineage trajectory present in both sham and MI hearts leading to a uniquely activated cell state defined in part by a strong anti-WNT transcriptome signature. We also uncovered novel myofibroblast subtypes expressing either pro-fibrotic or anti-fibrotic signatures. Our data highlight non-linear dynamics in myeloid and fibroblast lineages after cardiac injury, and provide an entry point for deeper analysis of cardiac homeostasis, inflammation, fibrosis, repair and regeneration.

An atlas of the aging lung mapped by single cell transcriptomics and deep tissue proteomics.

Abstract: Aging promotes lung function decline and susceptibility to chronic lung diseases, which are the third leading cause of death worldwide. Here, we use single cell transcriptomics and mass spectrometry-based proteomics to quantify changes in cellular activity states across 30 cell types and chart the lung proteome of young and old mice. We show that aging leads to increased transcriptional noise, indicating deregulated epigenetic control. We observe cell type-specific effects of aging, uncovering increased cholesterol biosynthesis in type-2 pneumocytes and lipofibroblasts and altered relative frequency of airway epithelial cells as hallmarks of lung aging. Proteomic profiling reveals extracellular matrix remodeling in old mice, including increased collagen IV and XVI and decreased Fraser syndrome complex proteins and collagen XIV. Computational integration of the aging proteome with the single cell transcriptomes predicts the cellular source of regulated proteins and creates an unbiased reference map of the aging lung. Aging impacts lung functionality and makes it more susceptible to chronic diseases. Combining proteomics and single cell transcriptomics, the authors chart molecular and cellular changes in the aging mouse lung, discover aging hallmarks, and predict the cellular sources of regulated proteins.

Single-cell RNA-seq reveals TOX as a key regulator of CD8+ T cell persistence in chronic infection.

Abstract: Progenitor-like CD8+ T cells mediate long-term immunity to chronic infection and cancer and respond potently to immune checkpoint blockade. These cells share transcriptional regulators with memory precursor cells, including T cell-specific transcription factor 1 (TCF1), but it is unclear whether they adopt distinct programs to adapt to the immunosuppressive environment. By comparing the single-cell transcriptomes and epigenetic profiles of CD8+ T cells responding to acute and chronic viral infections, we found that progenitor-like CD8+ T cells became distinct from memory precursor cells before the peak of the T cell response. We discovered a coexpression gene module containing Tox that exhibited higher transcriptional activity associated with more abundant active histone marks in progenitor-like cells than memory precursor cells. Moreover, thymocyte selection-associated high mobility group box protein TOX (TOX) promoted the persistence of antiviral CD8+ T cells and was required for the programming of progenitor-like CD8+ T cells. Thus, long-term CD8+ T cell immunity to chronic viral infection requires unique transcriptional and epigenetic programs associated with the transcription factor TOX.

rnaSPAdes: a de novo transcriptome assembler and its application to RNA-Seq data.

Abstract: Background The possibility of generating large RNA-sequencing datasets has led to development of various reference-based and de novo transcriptome assemblers with their own strengths and limitations. While reference-based tools are widely used in various transcriptomic studies, their application is limited to the organisms with finished and well-annotated genomes. De novo transcriptome reconstruction from short reads remains an open challenging problem, which is complicated by the varying expression levels across different genes, alternative splicing, and paralogous genes. Results Herein we describe the novel transcriptome assembler rnaSPAdes, which has been developed on top of the SPAdes genome assembler and explores computational parallels between assembly of transcriptomes and single-cell genomes. We also present quality assessment reports for rnaSPAdes assemblies, compare it with modern transcriptome assembly tools using several evaluation approaches on various RNA-sequencing datasets, and briefly highlight strong and weak points of different assemblers. Conclusions Based on the performed comparison between different assembly methods, we infer that it is not possible to detect the absolute leader according to all quality metrics and all used datasets. However, rnaSPAdes typically outperforms other assemblers by such important property as the number of assembled genes and isoforms, and at the same time has higher accuracy statistics on average comparing to the closest competitors.

Single-Cell RNA Sequencing Resolves Molecular Relationships Among Individual Plant Cells.

Abstract: Single-cell RNA sequencing (scRNA-seq) has been used extensively to study cell-specific gene expression in animals, but it has not been widely applied to plants. Here, we describe the use of a commercially available droplet-based microfluidics platform for high-throughput scRNA-seq to obtain single-cell transcriptomes from protoplasts of more than 10,000 Arabidopsis (Arabidopsis thaliana) root cells. We find that all major tissues and developmental stages are represented in this single-cell transcriptome population. Further, distinct subpopulations and rare cell types, including putative quiescent center cells, were identified. A focused analysis of root epidermal cell transcriptomes defined developmental trajectories for individual cells progressing from meristematic through mature stages of root-hair and nonhair cell differentiation. In addition, single-cell transcriptomes were obtained from root epidermis mutants, enabling a comparative analysis of gene expression at single-cell resolution and providing an unprecedented view of the impact of the mutated genes. Overall, this study demonstrates the feasibility and utility of scRNA-seq in plants and provides a first-generation gene expression map of the Arabidopsis root at single-cell resolution.

A genome-wide transcriptomic analysis of protein-coding genes in human blood cells

Abstract: INTRODUCTION Blood is the predominant source for molecular analyses in humans, both in clinical and research settings, and is the target for many therapeutic strategies, emphasizing the need for comprehensive molecular maps of the cells constituting human blood.The Human Protein Atlas program (www.proteinatlas.org) is an open-access database that aims to map all human proteins by integrating various omics technologies, including antibody-based imaging. Previously, the Human Protein Atlas included gene expression information from peripheral blood mononuclear cells but not the many subpopulations of blood cells within this cell type. To increase the resolution, we performed an in-depth characterization of the constituent cells in blood to provide a detailed view of the gene expression in individual human blood cells and relate these to the other tissues in the body. RATIONALE A quantitative transcriptomics-based expression analysis was performed in 18 canonical immune cell populations (Fig. 1) isolated by flow cytometric sorting. The blood cell expression profiles are presented in combination with expression profiles of tissues, including transcriptomics data from external sources to expand the number of tissue types as well as brain regions included in the database. A genome-wide classification of the protein-coding genes has been performed in terms of expression specificity and distribution, both in blood cells and tissues. RESULTS We present an atlas of the expression of all protein-coding genes in human blood cells, integrated with a classification of the specificity and distribution of all protein-coding genes in all major tissues and organs in the human body. A genome-wide analysis of blood cell RNA expression profiles allowed the identification of genes with elevated expression in various immune cells, confirming well-known protein markers, but also identified novel targets for in-depth analysis. There are 1448 protein-coding genes that have enriched expression in a single immune cell type. It will be interesting to study the corresponding proteins further to explore the biological functions linked to the respective cell phenotypes. A network plot of all cell type–enriched and group-enriched genes (Fig. 1B) reveals that many of the cell type–enriched genes are in neutrophils, eosinophils, and plasmacytoid dendritic cells, while many of the elevated genes in T and B cells are group-enriched across subpopulations of these lymphocytes. To illustrate the usefulness of this resource, we show the cellular distribution of genes known to cause primary immunodeficiencies in humans and find that many of these genes are expressed in cells not currently implicated in these diseases, illustrating how this global atlas can help us better understand the function of specific genes across cells and tissues in humans. CONCLUSION In this study, we have performed a genome-wide transcriptomic analysis of protein-coding genes in sorted blood immune cell populations to characterize the expression levels of each individual gene across all cell types. All data are presented in an interactive, open-access Blood Atlas as part of the Human Protein Atlas and are integrated with expression profiles across all major tissues to provide spatial classification of all protein-coding genes. This allows for a genome-wide exploration of the expression profiles across human immune cell populations and all major human tissues and organs.

Aberrant RNA Splicing in Cancer

Abstract: RNA splicing, the enzymatic process of removing segments of premature RNA to produce mature RNA, is a key mediator of proteome diversity and regulator of gene expression. Increased systematic sequencing of the genome and transcriptome of cancers has identified a variety of means by which RNA splicing is altered in cancer relative to normal cells. These findings, in combination with the discovery of recurrent change-of-function mutations in splicing factors in a variety of cancers, suggest that alterations in splicing are drivers of tumorigenesis. Greater characterization of altered splicing in cancer parallels increasing efforts to pharmacologically perturb splicing and early-phase clinical development of small molecules that disrupt splicing in patients with cancer. Here we review recent studies of global changes in splicing in cancer, splicing regulation of mitogenic pathways critical in cancer transformation, and efforts to therapeutically target splicing in cancer.

Single-cell multiomic analysis identifies regulatory programs in mixed-phenotype acute leukemia

Abstract: Identifying the causes of human diseases requires deconvolution of abnormal molecular phenotypes spanning DNA accessibility, gene expression and protein abundance1–3. We present a single-cell framework that integrates highly multiplexed protein quantification, transcriptome profiling and analysis of chromatin accessibility. Using this approach, we establish a normal epigenetic baseline for healthy blood development, which we then use to deconvolve aberrant molecular features within blood from patients with mixed-phenotype acute leukemia4,5. Despite widespread epigenetic heterogeneity within the patient cohort, we observe common malignant signatures across patients as well as patient-specific regulatory features that are shared across phenotypic compartments of individual patients. Integrative analysis of transcriptomic and chromatin-accessibility maps identified 91,601 putative peak-to-gene linkages and transcription factors that regulate leukemia-specific genes, such as RUNX1-linked regulatory elements proximal to the marker gene CD69. These results demonstrate how integrative, multiomic analysis of single cells within the framework of normal development can reveal both distinct and shared molecular mechanisms of disease from patient samples. Analyzing DNA accessibility, transcriptome and protein expression in single cells uncovers cancer-regulatory programs.

An ultra high-throughput method for single-cell joint analysis of open chromatin and transcriptome.

Abstract: Simultaneous profiling of transcriptome and chromatin accessibility within single cells is a powerful approach to dissect gene regulatory programs in complex tissues. However, current tools are limited by modest throughput. We now describe an ultra high-throughput method, Paired-seq, for parallel analysis of transcriptome and accessible chromatin in millions of single cells. We demonstrate the utility of Paired-seq for analyzing the dynamic and cell-type-specific gene regulatory programs in complex tissues by applying it to mouse adult cerebral cortex and fetal forebrain. The joint profiles of a large number of single cells allowed us to deconvolute the transcriptome and open chromatin landscapes in the major cell types within these brain tissues, infer putative target genes of candidate enhancers, and reconstruct the trajectory of cellular lineages within the developing forebrain. Paired-seq allows parallel analysis of transcriptome and accessible chromatin in millions of single cells and can be used to study dynamic and cell-type-specific gene regulatory programs in complex tissues, as demonstrated here for mouse adult cerebral cortex and fetal forebrain.

A single-nucleus RNA-sequencing pipeline to decipher the molecular anatomy and pathophysiology of human kidneys.

Abstract: Defining cellular and molecular identities within the kidney is necessary to understand its organization and function in health and disease. Here we demonstrate a reproducible method with minimal artifacts for single-nucleus Droplet-based RNA sequencing (snDrop-Seq) that we use to resolve thirty distinct cell populations in human adult kidney. We define molecular transition states along more than ten nephron segments spanning two major kidney regions. We further delineate cell type-specific expression of genes associated with chronic kidney disease, diabetes and hypertension, providing insight into possible targeted therapies. This includes expression of a hypertension-associated mechano-sensory ion channel in mesangial cells, and identification of proximal tubule cell populations defined by pathogenic expression signatures. Our fully optimized, quality-controlled transcriptomic profiling pipeline constitutes a tool for the generation of healthy and diseased molecular atlases applicable to clinical samples.

A single-cell transcriptome atlas of the adult human retina

Abstract: The retina is a specialized neural tissue that senses light and initiates image processing. Although the functional organization of specific retina cells has been well studied, the molecular profile of many cell types remains unclear in humans. To comprehensively profile the human retina, we performed single-cell RNA sequencing on 20,009 cells from three donors and compiled a reference transcriptome atlas. Using unsupervised clustering analysis, we identified 18 transcriptionally distinct cell populations representing all known neural retinal cells: rod photoreceptors, cone photoreceptors, Muller glia, bipolar cells, amacrine cells, retinal ganglion cells, horizontal cells, astrocytes, and microglia. Our data captured molecular profiles for healthy and putative early degenerating rod photoreceptors, and revealed the loss of MALAT1 expression with longer post-mortem time, which potentially suggested a novel role of MALAT1 in rod photoreceptor degeneration. We have demonstrated the use of this retina transcriptome atlas to benchmark pluripotent stem cell-derived cone photoreceptors and an adult Muller glia cell line. This work provides an important reference with unprecedented insights into the transcriptional landscape of human retinal cells, which is fundamental to understanding retinal biology and disease.

Reconstituting the transcriptome and DNA methylome landscapes of human implantation.

Abstract: Implantation is a milestone event during mammalian embryogenesis. Implantation failure is a considerable cause of early pregnancy loss in humans1. Owing to the difficulty of obtaining human embryos early after implantation in vivo, it remains unclear how the gene regulatory network and epigenetic mechanisms control the implantation process. Here, by combining an in vitro culture system for the development human embryos after implantation and single-cell multi-omics sequencing technologies, more than 8,000 individual cells from 65 human peri-implantation embryos were systematically analysed. Unsupervised dimensionality reduction and clustering algorithms of the transcriptome data show stepwise implantation routes for the epiblast, primitive endoderm and trophectoderm lineages, suggesting robust preparation for the proper establishment of a mother-to-offspring connection during implantation. Female embryos showed initiation of random X chromosome inactivation based on analysis of parental allele-specific expression of X-chromosome-linked genes during implantation. Notably, using single-cell triple omics sequencing analysis, the re-methylation of the genome in cells from the primitive endoderm lineage was shown to be much slower than in cells of both epiblast and trophectoderm lineages during the implantation process, which indicates that there are distinct re-establishment features in the DNA methylome of the epiblast and primitive endoderm—even though both lineages are derived from the inner cell mass. Collectively, our work provides insights into the complex molecular mechanisms that regulate the implantation of human embryos, and helps to advance future efforts to understanding early embryonic development and reproductive medicine. Transcriptomics and DNA methylomics are used to study the implantation process of human embryos at single-cell resolution.