Identification of lncRNAs involved in maternal‐to‐zygotic transition of in vitro‐produced porcine embryos by single cell RNA‐seq

Single cell analysis reveals the impact of age and maturation stage on the human oocyte transcriptome

10.1101/2020.09.25.309658 ◽

2020 ◽

Author(s):

Silvia Llonch ◽

Montserrat Barragán ◽

Paula Nieto ◽

Anna Mallol ◽

Marc Elosua-Bayes ◽

...

Keyword(s):

Single Cell ◽

Chromosome Segregation ◽

Maternal Age ◽

Maturation Stage ◽

P Value ◽

Rna Seq ◽

Transcript Levels ◽

Human Oocytes ◽

The Impact

AbstractStudy questionTo which degree does maternal age affect the transcriptome of human oocytes at the germinal vesicle (GV) stage or at metaphase II after maturation in vitro (IVM-MII)?Summary answerWhile the oocytes’ transcriptome is predominantly determined by maturation stage, transcript levels of genes related to chromosome segregation, mitochondria and RNA processing are affected by age after in vitro maturation of denuded oocytes.What is known alreadyFemale fertility is inversely correlated with maternal age due to both a depletion of the oocyte pool and a reduction in oocyte developmental competence. Few studies have addressed the effect of maternal age on the human mature oocyte (MII) transcriptome, which is established during oocyte growth and maturation, and the pathways involved remain unclear. Here, we characterize and compare the transcriptomes of a large cohort of fully grown GV and IVM-MII oocytes from women of varying reproductive age.Study design, size, durationIn this prospective molecular study, 37 women were recruited from May 2018 to June 2019. The mean age was 28.8 years (SD=7.7, range 18-43). A total of 72 oocytes were included in the study at GV stage after ovarian stimulation, and analyzed as GV (n=40) and in vitro matured oocytes (IVM-MII; n=32).Participants/materials, setting, methodsDenuded oocytes were included either as GV at the time of ovum pick-up or as IVM-MII after in vitro maturation for 30 hours in G2™ medium, and processed for transcriptomic analysis by single-cell RNA-seq using the Smart-seq2 technology. Cluster and maturation stage marker analysis were performed using the Seurat R package. Genes with an average fold change greater than 2 and a p-value < 0.01 were considered maturation stage markers. A Pearson correlation test was used to identify genes whose expression levels changed progressively with age. Those genes presenting a correlation value (R) >= |0.3| and a p-value < 0.05 were considered significant.Main results and the role of chanceFirst, by exploration of the RNA-seq data using tSNE dimensionality reduction, we identified two clusters of cells reflecting the oocyte maturation stage (GV and IVM-MII) with 4,445 and 324 putative marker genes, respectively. Next we identified genes, for which RNA levels either progressively increased or decreased with age. This analysis was performed independently for GV and IVM-MII oocytes. Our results indicate that the transcriptome is more affected by age in IVM-MII oocytes (1,219 genes) than in GV oocytes (596 genes). In particular, we found that genes involved in chromosome segregation and RNA splicing significantly increase in transcript levels with age, while genes related to mitochondrial activity present lower transcript levels with age. Gene regulatory network analysis revealed potential upstream master regulator functions for genes whose transcript levels present positive (GPBP1, RLF, SON, TTF1) or negative (BNC1, THRB) correlation with age.Limitations, reasons for cautionIVM-MII oocytes used in this study were obtained after in vitro maturation of denuded GV oocytes, therefore, their transcriptome might not be fully representative of in vivo matured MII oocytes.The Smart-seq2 methodology used in this study detects polyadenylated transcripts only and we could therefore not assess non-polyadenylated transcripts.Wider implications of the findingsOur analysis suggests that advanced maternal age does not globally affect the oocyte transcriptome at GV or IVM-MII stages. Nonetheless, hundreds of genes displayed altered transcript levels with age, particularly in IVM-MII oocytes. Especially affected by age were genes related to chromosome segregation and mitochondrial function, pathways known to be involved in oocyte ageing. Our study thereby suggests that misregulation of chromosome segregation and mitochondrial pathways also at the RNA-level might contribute to the age-related quality decline in human oocytes.Study funding/competing interest(s)This study was funded by the AXA research fund, the European commission, intramural funding of Clinica EUGIN, the Spanish Ministry of Science, Innovation and Universities, the Catalan Agència de Gestió d’Ajuts Universitaris i de Recerca (AGAUR) and by contributions of the Spanish Ministry of Economy, Industry and Competitiveness (MEIC) to the EMBL partnership and to the “Centro de Excelencia Severo Ochoa”.The authors have no conflict of interest to declare.

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Single cell RNA sequencing of calvarial and long bone endocortical cells

10.1101/849224 ◽

2019 ◽

Cited By ~ 1

Author(s):

Ugur M. Ayturk ◽

Joseph P. Scollan ◽

Alexander Vesprey ◽

Christina M. Jacobsen ◽

Paola Divieti Pajevic ◽

...

Keyword(s):

Gene Expression ◽

Single Cell ◽

Cultured Cells ◽

Neutralizing Antibody ◽

Long Bone ◽

Appendicular Skeleton ◽

Rna Seq ◽

Isolated Cells

ABSTRACTSingle cell RNA-seq (scRNA-seq) is emerging as a powerful technology to examine transcriptomes of individual cells. We determined whether scRNA-seq could be used to detect the effect of environmental and pharmacologic perturbations on osteoblasts. We began with a commonly used in vitro system in which freshly isolated neonatal mouse calvarial cells are expanded and induced to produce a mineralized matrix. We used scRNA-seq to compare the relative cell type abundances and the transcriptomes of freshly isolated cells to those that had been cultured for 12 days in vitro. We observed that the percentage of macrophage-like cells increased from 6% in freshly isolated calvarial cells to 34% in cultured cells. We also found that Bglap transcripts were abundant in freshly isolated osteoblasts but nearly undetectable in the cultured calvarial cells. Thus, scRNA-seq revealed significant differences between heterogeneity of cells in vivo and in vitro. We next performed scRNA-seq on freshly recovered long bone endocortical cells from mice that received either vehicle or Sclerostin-neutralizing antibody for 1 week. Bone anabolism-associated transcripts were also not significantly increased in immature and mature osteoblasts recovered from Sclerostin-neutralizing antibody treated mice; this is likely a consequence of being underpowered to detect modest changes in gene expression, since only 7% of the sequenced endocortical cells were osteoblasts, and a limited portion of their transcriptomes were sampled. We conclude that scRNA-seq can detect changes in cell abundance, identity, and gene expression in skeletally derived cells. In order to detect modest changes in osteoblast gene expression at the single cell level in the appendicular skeleton, larger numbers of osteoblasts from endocortical bone are required.

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Enhancing droplet-based single-nucleus RNA-seq resolution using the semi-supervised machine learning classifier DIEM

10.1101/786285 ◽

2019 ◽

Cited By ~ 4

Author(s):

Marcus Alvarez ◽

Elior Rahmani ◽

Brandon Jew ◽

Kristina M. Garske ◽

Zong Miao ◽

...

Keyword(s):

Gene Expression ◽

Single Cell ◽

Cell Types ◽

Supervised Machine Learning ◽

Data Sets ◽

Rna Seq ◽

Novel Approach ◽

Single Nucleus ◽

Downstream Analysis

AbstractSingle-nucleus RNA sequencing (snRNA-seq) measures gene expression in individual nuclei instead of cells, allowing for unbiased cell type characterization in solid tissues. Contrary to single-cell RNA seq (scRNA-seq), we observe that snRNA-seq is commonly subject to contamination by high amounts of extranuclear background RNA, which can lead to identification of spurious cell types in downstream clustering analyses if overlooked. We present a novel approach to remove debris-contaminated droplets in snRNA-seq experiments, called Debris Identification using Expectation Maximization (DIEM). Our likelihood-based approach models the gene expression distribution of debris and cell types, which are estimated using EM. We evaluated DIEM using three snRNA-seq data sets: 1) human differentiating preadipocytes in vitro, 2) fresh mouse brain tissue, and 3) human frozen adipose tissue (AT) from six individuals. All three data sets showed various degrees of extranuclear RNA contamination. We observed that existing methods fail to account for contaminated droplets and led to spurious cell types. When compared to filtering using these state of the art methods, DIEM better removed droplets containing high levels of extranuclear RNA and led to higher quality clusters. Although DIEM was designed for snRNA-seq data, we also successfully applied DIEM to single-cell data. To conclude, our novel method DIEM removes debris-contaminated droplets from single-cell-based data fast and effectively, leading to cleaner downstream analysis. Our code is freely available for use at https://github.com/marcalva/diem.

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CellMap: Characterizing the types and composition of iPSC-derived cells from RNA-seq data

10.1101/2021.05.24.445360 ◽

2021 ◽

Author(s):

Zhengyu Ouyang ◽

Nathanael Bourgeois ◽

Eugenia Lyashenko ◽

Paige Cundiff ◽

Patrick F Cullen ◽

...

Keyword(s):

Single Cell ◽

Induced Pluripotent Stem Cell ◽

Cell Types ◽

Model Systems ◽

Rna Seq ◽

Cell Type ◽

Fine Grained ◽

Single Nucleus ◽

Induced Pluripotent

Induced pluripotent stem cell (iPSC) derived cell types are increasingly employed as in vitro model systems for drug discovery. For these studies to be meaningful, it is important to understand the reproducibility of the iPSC-derived cultures and their similarity to equivalent endogenous cell types. Single-cell and single-nucleus RNA sequencing (RNA-seq) are useful to gain such understanding, but they are expensive and time consuming, while bulk RNA-seq data can be generated quicker and at lower cost. In silico cell type decomposition is an efficient, inexpensive, and convenient alternative that can leverage bulk RNA-seq to derive more fine-grained information about these cultures. We developed CellMap, a computational tool that derives cell type profiles from publicly available single-cell and single-nucleus datasets to infer cell types in bulk RNA-seq data from iPSC-derived cell lines.

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Uncoupling p53 from an Embryonic Regulome Exhausts Quiescent CML Stem Cells through Inhibition of a HIF1alpha Molecular Program

Blood ◽

10.1182/blood-2021-150372 ◽

2021 ◽

Vol 138 (Supplement 1) ◽

pp. 1541-1541

Author(s):

Mary T Scott ◽

Wei Liu ◽

Rebecca Mitchell ◽

Cassie Clarke ◽

Hassan Almasoudi ◽

...

Keyword(s):

Stem Cells ◽

Single Cell ◽

Research Funding ◽

Embryonic Stem ◽

Rna Seq ◽

Combination Drug ◽

Human Cd34 ◽

Molecular Features ◽

Cd34 Cells

Abstract Although it has been recognized for many years that cancer stem cells and embryonic stem cells (ESC) share molecular features, identifying ways to exploit this therapeutically has proved challenging. To date, these shared features have not been examined in the leukemic stem cells (LSC) found in patients with chronic myeloid leukemia (CML). By integrating known ES regulatory circuitry with transcriptomics datasets, including deep single-cell RNA-seq profiling of 15,670 LSC from five patients with CML, we identified a core ESC regulome in the LSC containing 1243 genes. The significant majority of this regulome (1102 genes) was up-regulated in cycling LSC, whilst quiescent LSC showed up-regulation of a characteristic set of 101 genes, unique to cells with high ESC identity and with regulatory circuitry enriched for c-Myc and Nanog modules. Membership of the ESC regulome included the TP53 gene which was transcriptionally repressed and detected at a lower frequency in quiescent LSC compared to cycling ones (11.8% vs 43.6%). We also demonstrated that tyrosine kinase inhibitors (TKI) repress the ESC regulome and TP53 expression in LSC, suggesting that the regulome safeguards against high levels of TP53 expression, thus promoting survival of quiescent LSC in the presence of TKI. We hypothesized that overcoming the influence of the regulome on TP53 expression would provide an opportunity to eradicate quiescent LSC. To this end, we used an MDM2 inhibitor (MDM2i), RG7388 (idasanutlin) or RG7112, to stabilize the p53 protein, examining its potential in combination with nilotinib (NIL) to eradicate CML LSC in vitro and in vivo, with RG7388 being the most optimized and furthest in development. The combination of NIL plus MDM2i in vitro was more effective at targeted LSC from primary patient samples than NIL treatment alone, as evidenced by reduced CFC and LTC-IC outputs (p<0.05, 0.01 respectively). Intriguingly, the combination of NIL plus MDM2i did not result in significant reductions in the number of LSC compared to NIL only, when we quantified them at the end of drug treatments in pre-clinical mouse models. Instead, we observed a functional decline of the LSC as evidenced by diminished engraftment potential in 2 o recipient mice (p<0.05; SCLtTA x BCR-ABL1 transgenic model) or diminished colony-plating potential (p<0.05). This was followed by near complete depletion of the LSC population (p<0.05) 28 days after cessation of combination drug treatment (patient-derived xenografts/PDX in immunocompromised mice). In order to understand the molecular events underpinning these drug effects on LSC, we performed RNA-seq analysis of drug-treated CD34 + cells in vitro (bulk cells), or of human CD34 + cells obtained from PDX (single cell RNA-seq). CD34 + cells treated with NIL plus MDM2i in vitro showed evidence of increased p53 stabilization and activation of p53 target genes, and this was accompanied by repression of the ESC regulome beyond that normally observed with NIL only. Similarly, in PDX we observed increased repression of the ESC regulome in human CD34 + cells exposed to the combination of NIL plus MDM2i that included repression of HIF1alpha and a signature of genes required for cellular adaptations to hypoxia, and growth factor-mediated resistance to TKI therapy. Further, single cell analysis of differentiated human CD45 + cells from our PDX model, provided compelling evidence that acquisition of this repressive signature in the LSC, through combined NIL plus MDM2i treatment, re-wires them towards a basophilic fate, consistent with functional exhaustion of the LSC compartment. In conclusion, we have identified an ESC regulome in CML LSC and demonstrate that a combination of a TKI plus an MDM2i leads to p53 upregulation which antagonizes this regulome, providing a highly effective strategy to target near complete loss of functional LSC in pre-clinical models. Our study has revealed a new therapeutic paradigm to examine in other cancer stem cell populations that utilize ESC regulatory programs. Disclosures Higgins: Roche/Genentech: Current Employment, Current equity holder in publicly-traded company. Copland: Astellas: Honoraria, Speakers Bureau; Novartis: Honoraria, Speakers Bureau; Pfizer: Honoraria, Speakers Bureau; Incyte: Honoraria, Research Funding, Speakers Bureau; Cyclacel Ltd: Research Funding; Jazz: Honoraria, Speakers Bureau.

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Kidney organoid reproducibility across multiple human iPSC lines and diminished off target cells after transplantation revealed by single cell transcriptomics

10.1101/516807 ◽

2019 ◽

Cited By ~ 4

Author(s):

Ayshwarya Subramanian ◽

Eriene-Heidi Sidhom ◽

Maheswarareddy Emani ◽

Nareh Sahakian ◽

Katherine Vernon ◽

...

Keyword(s):

Single Cell ◽

Human Kidney ◽

Cell Types ◽

Mouse Kidney ◽

Target Cells ◽

Rna Seq ◽

Kidney Capsule ◽

Human Ipsc ◽

Kidney Organoids

AbstractHuman iPSC-derived kidney organoids have the potential to revolutionize discovery, but assessing their consistency and reproducibility across iPSC lines, and reducing the generation of off-target cells remain an open challenge. Here, we used single cell RNA-Seq (scRNA-Seq) to profile 415,775 cells to show that organoid composition and development are comparable to human fetal and adult kidneys. Although cell classes were largely reproducible across iPSC lines, time points, protocols, and replicates, cell proportions were variable between different iPSC lines. Off-target cell proportions were the most variable. Prolonged in vitro culture did not alter cell types, but organoid transplantation under the mouse kidney capsule diminished off-target cells. Our work shows how scRNA-seq can help score organoids for reproducibility, faithfulness and quality, that kidney organoids derived from different iPSC lines are comparable surrogates for human kidney, and that transplantation enhances their formation by diminishing off-target cells.

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Single Cell RNA-Seq Characterises Pre-Leukemic Transformation Driven By CEBPA N321D in the Hoxb8-FL Cell Line

Blood ◽

10.1182/blood-2018-99-110626 ◽

2018 ◽

Vol 132 (Supplement 1) ◽

pp. 3887-3887

Author(s):

Moosa Qureshi ◽

Fernando Calero-Nieto ◽

Iwo Kucinski ◽

Sarah Kinston ◽

George Giotopoulos ◽

...

Keyword(s):

Dendritic Cell ◽

Single Cell ◽

Cell Line ◽

Single Cells ◽

Mutant Form ◽

Rna Seq ◽

Wild Type ◽

Leukemic Transformation

Abstract The C/EBPα transcription factor plays a pivotal role in myeloid differentiation and E2F-mediated cell cycle regulation. Although CEBPA mutations are common in acute myeloid leukaemia (AML), little is known regarding pre-leukemic alterations caused by mutated CEBPA. Here, we investigated early events involved in pre-leukemic transformation driven by CEBPA N321D in the LMPP-like cell line Hoxb8-FL (Redecke et al., Nat Methods 2013), which can be maintained in vitro as a self-renewing LMPP population using Flt3L and estradiol, as well as differentiated both in vitro and in vivo into myeloid and lymphoid cell types. Hoxb8-FL cells were retrovirally transduced with Empty Vector (EV), wild-type CEBPA (CEBPA WT) or its N321D mutant form (CEBPA N321D). CEBPA WT-transduced cells showed increased expression of cd11b and SIRPα and downregulation of c-kit, suggesting that wild-type CEBPA was sufficient to promote differentiation even under LMPP growth conditions. Interestingly, we did not observe the same phenotype in CEBPA N321D-transduced cells. Upon withdrawal of estradiol, both EV and CEBPA WT-transduced cells differentiated rapidly into a conventional dendritic cell (cDC) phenotype by day 7 and died within 12 days. By contrast, CEBPA N321D-transduced cells continued to grow for in excess of 56 days, with an initial cDC phenotype but by day 30 demonstrating a plasmacytoid dendritic cell precursor phenotype. CEBPA N321D-transduced cells were morphologically distinct from EV-transduced cells. To test leukemogenic potential in vivo, we performed transplantation experiments in lethally irradiated mice. Serial monitoring of peripheral blood demonstrated that Hoxb8-FL derived cells had disappeared by 4 weeks, and did not reappear. However, at 6 months CEBPA N321D-transduced cells could still be detected in bone marrow in contrast to EV-transduced cells but without any leukemic phenotype. To identify early events involved in pre-leukemic transformation, the differentiation profiles of EV, CEBPA WT and CEBPA N321D-transduced cells were examined with single cell RNA-seq (scRNA-seq). 576 single cells were taken from 3 biological replicates at days 0 and 5 post-differentiation, and analysed using the Automated Single-Cell Analysis Pipeline (Gardeux et al., Bioinformatics 2017). Visualisation by t-SNE (Fig 1) demonstrated: (i) CEBPA WT-transduced cells formed a distinct cluster at day 0 before withdrawal of estradiol; (ii) CEBPA N321D-transduced cells separated from EV and CEBPA WT-transduced cells after 5 days of differentiation, (iii) two subpopulations could be identified within the CEBPA N321D-transduced cells at day 5, with a cluster of five CEBPA N321D-transduced single cells distributed amongst or very close to the day 0 non-differentiated cells. Differential expression analysis identified 224 genes upregulated and 633 genes downregulated specifically in the CEBPA N321D-transduced cells when compared to EV cells after 5 days of differentiation. This gene expression signature revealed that CEBPA N321D-transduced cells switched on a HSC/MEP/CMP transcriptional program and switched off a myeloid dendritic cell program. Finally, in order to further dissect the effect of the N321D mutation, the binding profile of endogenous and CEBPA N321D was compared by ChIP-seq before and after 5 days of differentiation. Integration with scRNA-seq data identified 160 genes specifically downregulated in CEBPA N321D-transduced cells which were associated with the binding of the mutant protein. This list of genes included genes previously implicated in dendritic cell differentiation (such as NOTCH2, JAK2), as well as a number of genes not previously implicated in the evolution of AML, representing potentially novel therapeutic targets. Disclosures No relevant conflicts of interest to declare.

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High throughput single cell RNA-seq of developing mouse kidney and human kidney organoids reveals a roadmap for recreating the kidney

10.1101/235499 ◽

2017 ◽

Cited By ~ 10

Author(s):

Alexander N. Combes ◽

Belinda Phipson ◽

Luke Zappia ◽

Kynan T. Lawlor ◽

Pei Xuan Er ◽

...

Keyword(s):

Single Cell ◽

Kidney Tissue ◽

Human Kidney ◽

Population Based ◽

Mouse Kidney ◽

Rna Seq ◽

Kidney Morphogenesis ◽

Human Ipsc ◽

Kidney Organoids

AbstractRecent advances in our capacity to differentiate human pluripotent stem cells to human kidney tissue are moving the field closer to novel approaches for renal replacement. Such protocols have relied upon our current understanding of the molecular basis of mammalian kidney morphogenesis. To date this has depended upon population based-profiling of non-homogenous cellular compartments. In order to improve our resolution of individual cell transcriptional profiles during kidney morphogenesis, we have performed 10x Chromium single cell RNA-seq on over 6000 cells from the E18.5 developing mouse kidney, as well as more than 7000 cells from human iPSC-derived kidney organoids. We identified 16 clusters of cells representing all major cell lineages in the E18.5 mouse kidney. The differentially expressed genes from individual murine clusters were then used to guide the classification of 16 cell clusters within human kidney organoids, revealing the presence of distinguishable stromal, endothelial, nephron, podocyte and nephron progenitor populations. Despite the congruence between developing mouse and human organoid, our analysis suggested limited nephron maturation and the presence of ‘off target’ populations in human kidney organoids, including unidentified stromal populations and evidence of neural clusters. This may reflect unique human kidney populations, mixed cultures or aberrant differentiation in vitro. Analysis of clusters within the mouse data revealed novel insights into progenitor maintenance and cellular maturation in the major renal lineages and will serve as a roadmap to refine directed differentiation approaches in human iPSC-derived kidney organoids.

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CellSIUS provides sensitive and specific detection of rare cell populations from complex single cell RNA-seq data

10.1101/514950 ◽

2019 ◽

Author(s):

Rebekka Wegmann ◽

Marilisa Neri ◽

Sven Schuierer ◽

Bilada Bilican ◽

Huyen Hartkopf ◽

...

Keyword(s):

Single Cell ◽

Cell Populations ◽

Rna Seq ◽

Differentiation Protocol ◽

Layer V ◽

Retzius Cells ◽

Rare Cells ◽

Cell Cycle Status

AbstractComprehensive benchmarking of computational methods for single-cell RNA sequencing (scRNA-seq) analysis is scarce. Using a modular workflow and a large dataset with known cell composition, we benchmarked feature selection and clustering methodologies for scRNA-seq data. Results highlighted a methodology gap for rare cell population identification for which we developed CellSIUS (Cell Subtype Identification from Upregulated gene Sets). CellSIUS outperformed existing approaches, enabled the identification of rare cell populations and, in contrast to other methods, simultaneously revealed transcriptomic signatures indicative of the rare cells’ function. We exemplified the use of our workflow and CellSIUS for the characterization of a human pluripotent cell 3D spheroid differentiation protocol recapitulating deep-layer corticogenesis in vitro. Results revealed lineage bifurcation between Cajal-Retzius cells and layer V/VI neurons as well as rare cell populations that differ by migratory, metabolic, or cell cycle status, including a choroid plexus neuroepithelial subgroup, revealing previously unrecognized complexity in human stem cell-derived cellular populations.

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ColorCells: a database of expression, classification and functions of lncRNAs in single cells

Briefings in Bioinformatics ◽

10.1093/bib/bbaa325 ◽

2020 ◽

Author(s):

Ling-Ling Zheng ◽

Jing-Hua Xiong ◽

Wu-Jian Zheng ◽

Jun-Hao Wang ◽

Zi-Liang Huang ◽

...

Keyword(s):

Single Cell ◽

Tissue Specificity ◽

Single Cells ◽

Noncoding Rnas ◽

Cell Types ◽

Marker Genes ◽

Rna Seq ◽

Expression Variability ◽

Expression Classification

Abstract Although long noncoding RNAs (lncRNAs) have significant tissue specificity, their expression and variability in single cells remain unclear. Here, we developed ColorCells (http://rna.sysu.edu.cn/colorcells/), a resource for comparative analysis of lncRNAs expression, classification and functions in single-cell RNA-Seq data. ColorCells was applied to 167 913 publicly available scRNA-Seq datasets from six species, and identified a batch of cell-specific lncRNAs. These lncRNAs show surprising levels of expression variability between different cell clusters, and has the comparable cell classification ability as known marker genes. Cell-specific lncRNAs have been identified and further validated by in vitro experiments. We found that lncRNAs are typically co-expressed with the mRNAs in the same cell cluster, which can be used to uncover lncRNAs’ functions. Our study emphasizes the need to uncover lncRNAs in all cell types and shows the power of lncRNAs as novel marker genes at single cell resolution.

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