Universal prediction of cell cycle position using transfer learning

ABSTRACTThe cell cycle is a highly conserved, continuous process which controls faithful replication and division of cells. Single-cell technologies have enabled increasingly precise measurements of the cell cycle as both as a biological process of interest and as a possible confounding factor. Despite its importance and conservation, there is no universally applicable approach to infer position in the cell cycle with high-resolution from single-cell RNA-seq data. Here, we present tricycle, an R/Bioconductor package, to address this challenge by leveraging key features of the biology of the cell cycle, the mathematical properties of principal component analysis of periodic functions, and the ubiquitous applicability of transfer learning. We show that tricycle can predict any cell’s position in the cell cycle regardless of the cell type, species of origin, and even sequencing assay. The accuracy of tricycle compares favorably to gold-standard experimental assays which generally require specialized measurements in specifically constructed in vitro systems. Unlike gold-standard assays, tricycle is easily applicable to any single-cell RNA-seq dataset. Tricycle is highly scalable, universally accurate, and eminently pertinent for atlas-level data.

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BRD4 PROTAC degrader ARV-825 inhibits T-cell acute lymphoblastic leukemia by targeting 'Undruggable' Myc-pathway genes

Cancer Cell International ◽

10.1186/s12935-021-01908-w ◽

2021 ◽

Vol 21 (1) ◽

Author(s):

Shuiyan Wu ◽

You Jiang ◽

Yi Hong ◽

Xinran Chu ◽

Zimu Zhang ◽

...

Keyword(s):

Cell Cycle ◽

Cell Proliferation ◽

Acute Lymphoblastic Leukemia ◽

Caspase 3 ◽

Lymphoblastic Leukemia ◽

Rna Seq ◽

Cell Acute Lymphoblastic Leukemia ◽

Bet Protein

Abstract Background T-cell acute lymphoblastic leukemia (T-ALL) is an aggressive disease with a high risk of induction failure and poor outcomes, with relapse due to drug resistance. Recent studies show that bromodomains and extra-terminal (BET) protein inhibitors are promising anti-cancer agents. ARV-825, comprising a BET inhibitor conjugated with cereblon ligand, was recently developed to attenuate the growth of multiple tumors in vitro and in vivo. However, the functional and molecular mechanisms of ARV-825 in T-ALL remain unclear. This study aimed to investigate the therapeutic efficacy and potential mechanism of ARV-825 in T-ALL. Methods Expression of the BRD4 were determined in pediatric T-ALL samples and differential gene expression after ARV-825 treatment was explored by RNA-seq and quantitative reverse transcription-polymerase chain reaction. T-ALL cell viability was measured by CCK8 assay after ARV-825 administration. Cell cycle was analyzed by propidium iodide (PI) staining and apoptosis was assessed by Annexin V/PI staining. BRD4, BRD3 and BRD2 proteins were detected by western blot in cells treated with ARV-825. The effect of ARV-825 on T-ALL cells was analyzed in vivo. The functional and molecular pathways involved in ARV-825 treatment of T-ALL were verified by western blot and chromatin immunoprecipitation (ChIP). Results BRD4 expression was higher in pediatric T-ALL samples compared with T-cells from healthy donors. High BRD4 expression indicated a poor outcome. ARV-825 suppressed cell proliferation in vitro by arresting the cell cycle and inducing apoptosis, with elevated poly-ADP ribose polymerase and cleaved caspase 3. BRD4, BRD3, and BRD2 were degraded in line with reduced cereblon expression in T-ALL cells. ARV-825 had a lower IC50 in T-ALL cells compared with JQ1, dBET1 and OTX015. ARV-825 perturbed the H3K27Ac-Myc pathway and reduced c-Myc protein levels in T-ALL cells according to RNA-seq and ChIP. In the T-ALL xenograft model, ARV-825 significantly reduced tumor growth and led to the dysregulation of Ki67 and cleaved caspase 3. Moreover, ARV-825 inhibited cell proliferation by depleting BET and c-Myc proteins in vitro and in vivo. Conclusions BRD4 indicates a poor prognosis in T-ALL. The BRD4 degrader ARV-825 can effectively suppress the proliferation and promote apoptosis of T-ALL cells via BET protein depletion and c-Myc inhibition, thus providing a new strategy for the treatment of T-ALL.

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Single cell organization and cell cycle characterization of DNA stained multicellular tumor spheroids

Scientific Reports ◽

10.1038/s41598-021-96288-6 ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

Karl Olofsson ◽

Valentina Carannante ◽

Madoka Takai ◽

Björn Önfelt ◽

Martin Wiklund

Keyword(s):

Cell Cycle ◽

Single Cell ◽

Drug Distribution ◽

In Vitro Models ◽

Biological Information ◽

Dimensional Structure ◽

Multicellular Tumor Spheroids ◽

Tumor Spheroids ◽

Nuclear Segmentation

AbstractMulticellular tumor spheroids (MCTSs) can serve as in vitro models for solid tumors and have become widely used in basic cancer research and drug screening applications. The major challenges when studying MCTSs by optical microscopy are imaging and analysis due to light scattering within the 3-dimensional structure. Herein, we used an ultrasound-based MCTS culture platform, where A498 renal carcinoma MCTSs were cultured, DAPI stained, optically cleared and imaged, to connect nuclear segmentation to biological information at the single cell level. We show that DNA-content analysis can be used to classify the cell cycle state as a function of position within the MCTSs. We also used nuclear volumetric characterization to show that cells were more densely organized and perpendicularly aligned to the MCTS radius in MCTSs cultured for 96 h compared to 24 h. The method presented herein can in principle be used with any stochiometric DNA staining protocol and nuclear segmentation strategy. Since it is based on a single counter stain a large part of the fluorescence spectrum is free for other probes, allowing measurements that correlate cell cycle state and nuclear organization with e.g., protein expression or drug distribution within MCTSs.

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miRNA-mediated Drug Repurposing Unveiled Potential Candidate Drugs for Prolactinoma Treatment

Neuroendocrinology ◽

10.1159/000515801 ◽

2021 ◽

Author(s):

Büşra Aydin ◽

Sema Arslan ◽

Fatih Bayraklı ◽

Betül Karademir ◽

Kazim Yalcin Arga

Keyword(s):

Cell Cycle ◽

Data Integration ◽

Cell Viability ◽

Drug Repurposing ◽

Serum Prolactin ◽

Drug Candidates ◽

Mirna Level ◽

Level Data ◽

Cell Cycle Phases

Introduction: Prolactinomas, also called lactotroph adenomas, are the most encountered type of hormone-secreting pituitary neuroendocrine tumors (PitNET) in the clinic. The preferred first-line therapy is a medical treatment with dopamine agonists (DA), mainly cabergoline, to reduce serum prolactin levels, tumor volume, and mass effect. However, in some cases, patients have displayed DA-resistance with aggressive tumor behavior or are faced with recurrence after drug withdrawal. Also, currently used therapeutics have notorious side effects and impair the life quality of the patients. Methods: Since the amalgamation of clinical and laboratory data besides tumor histopathogenesis and transcriptional regulatory features of the tumor emerge to exhibit essential roles in the behavior and progression of prolactinomas, in this work, we integrated mRNA and microRNA (miRNA) level transcriptome data that exploit disease-specific signatures in addition to biological and pharmacological data to elucidate a rational prioritization of pathways and drugs in prolactinoma. Results: We identified eight drug candidates through drug repurposing based on mRNA-miRNA level data integration and evaluated their potential through in vitro assays in the MMQ cell line. Seven re-purposed drugs including 5-flourocytosine, nortriptyline, neratinib, puromycin, taxifolin, vorinostat, and zileuton were proposed as potential drug candidates for the treatment of prolactinoma. We further hypothesized possible mechanisms of drug action on MMQ cell viability through analyzing PI3K/Akt signaling pathway and cell cycle arrest via flow cytometry and western blotting. Discussion: We presented the transcriptomic landscape of prolactinoma through miRNA and mRNA level data integration and proposed repurposed drug candidates based on this integration. We validated our findings through testing cell viability, cell cycle phases, and PI3K/Akt protein expressions. Effects of the drugs on cell cycle phases and inhibition of PI3K/Akt pathway by all drugs gave us promising output for further studies using these drugs in the treatment of prolactinoma. This is the first study that reports miRNA-mediated repurposed drugs for prolactinoma treatment via in vitro experiments.

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Abstract 14391: Transient Cell Cycle Induction in Cardiomyocytes is a Promising Approach to Treat Ischemia Induced Heart Failure

Circulation ◽

10.1161/circ.142.suppl_3.14391 ◽

2020 ◽

Vol 142 (Suppl_3) ◽

Author(s):

Riham Abouleisa ◽

Qinghui Ou ◽

Xian-liang Tang ◽

Mitesh Solanki ◽

Yiru Guo ◽

...

Keyword(s):

Cell Cycle ◽

Cardiac Function ◽

Single Cell ◽

Ischemia Reperfusion Injury ◽

Ischemia Reperfusion ◽

Cardiomyocyte Proliferation ◽

Specific Expression ◽

Control Virus

Rationale: The regenerative capacity of the heart to repair itself after myocardial infarction (MI)is limited. Our previous study showed that ectopic introduction of Cdk1/CyclinB1 andCdk4/CyclinD1 complexes (4F) promotes cardiomyocyte proliferation in vitro and in vivo andimproves cardiac function after MI. However, its clinical application is limited due to the concernsfor tumorigenic potential in other organs. Objectives: To first, identify on a single cell transcriptomic basis the necessary reprogrammingsteps that cardiomyocytes need to undertake to progress through the proliferation processfollowing 4F overexpression, and then, to determine the pre-clinical efficacy of transient andcardiomyocyte specific expression of 4F in improving cardiac function after MI in small and largeanimals. Methods and Results: Temporal bulk and single cell RNAseq of mature hiPS-CMs treated with4F or LacZ control for 24, 48, or 72 h revealed full cell cycle reprogramming in 15% of thecardiomyocyte population which was associated with sarcomere disassembly and metabolicreprogramming. Transient overexpression of 4F specifically in cardiomyocytes was achievedusing non-integrating lentivirus (NIL) driven by TNNT2 (TNNT2-4F-NIL). One week after inductionof ischemia-reperfusion injury in rats or pigs, TNNT2-4F-NIL or control virus was injectedintramyocardially. Compared with controls, rats or pigs treated with TNNT2-4F-NIL showed a 20-30% significant improvement in ejection fraction and scar size four weeks after treatment, asassessed by echocardiography and histological analysis. Quantification of cardiomyocyteproliferation in pigs using a novel cytokinesis reporter showed that ~10% of the cardiomyocyteswithin the injection site were labelled as daughter cells following injection with TNNT2-4F-NILcompared with ~0.5% background labelling in control groups. Conclusions: We provide the first understanding of the process of forced cardiomyocyteproliferation and advanced the clinical applicability of this approach through minimization ofoncogenic potential of the cell cycle factors using a novel transient and cardiomyocyte-specificviral construct.

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Live-cell time-lapse imaging and single-cell tracking of in vitro cultured neural stem cells – Tools for analyzing dynamics of cell cycle, migration, and lineage selection

Methods ◽

10.1016/j.ymeth.2017.10.003 ◽

2018 ◽

Vol 133 ◽

pp. 81-90 ◽

Cited By ~ 11

Author(s):

Katja M. Piltti ◽

Brian J. Cummings ◽

Krystal Carta ◽

Ayla Manughian-Peter ◽

Colleen L. Worne ◽

...

Keyword(s):

Cell Cycle ◽

Stem Cells ◽

Neural Stem Cells ◽

Single Cell ◽

Cell Tracking ◽

Time Lapse ◽

Live Cell ◽

Time Lapse Imaging

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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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High Mobility Group A1 Chromatin Regulators Function As Critical Drivers of Leukemogenesis in Preclinical Models of Relapsed, Pediatric B-Cell ALL

Blood ◽

10.1182/blood-2019-130261 ◽

2019 ◽

Vol 134 (Supplement_1) ◽

pp. 3946-3946

Author(s):

Liping Li ◽

Katharina Hayer ◽

Lingling Xian ◽

Li Luo ◽

Leslie Cope ◽

...

Keyword(s):

Cell Cycle ◽

Cell Lines ◽

Cell Cycle Progression ◽

High Mobility ◽

Transcriptional Networks ◽

Rna Seq ◽

Cycle Progression ◽

Short Hairpin ◽

Reh Cells

Introduction: Acute B-cell lymphoblastic leukemia (B-ALL) is the most common form of childhood leukemia and the leading cause of death in children with cancer. While therapy is often curative, about 10-15% of children will relapse with recurrent disease and abysmal outcomes. Actionable mechanisms that mediate relapse remain largely unknown. The gene encoding the High Mobility Group A1(HMGA1) chromatin regulator is overexpressed in diverse malignancies where high levels portend poor outcomes. In murine models, we discovered thatHmga1 overexpression is sufficient for clonal expansion and progression to aggressive acute lymphoid leukemia (Cancer Res 2008,68:10121, 2018,78:1890; Nature Comm 2017,8:15008). Further, HMGA1 is overexpressed in pediatric B-ALL (pB-ALL) blasts with highest levels in children who relapse early compared to those who achieve chronic remissions. Together, these findings suggest that HMGA1 is required for leukemogenesis and may foster relapse in B-ALL. We therefore sought to: 1) test the hypothesis that HMGA1 is a key epigenetic regulator required for leukemogenesis and relapse in pB-ALL, and, 2) elucidate targetable mechanisms mediated by HMGA1 in leukemogenesis. Methods: We silenced HMGA1 via lentiviral delivery of short hairpin RNAs targeting 2 different sequences in cell lines derived from relapsed pB-ALL (REH, 697). REH cells harbor the TEL-AML1 fusion; 697 cells express BCL2, BCL3, and cMYC. Next, we assessed leukemogenic phenotypes in vitro (proliferation, cell cycle progression, apoptosis, and clonogenicity) and leukemogenesis invivo. To dissect molecular mechanisms underlying HMGA1, we performed RNA-Seq and applied in silico pathway analysis. Results: There is abundant HMGA1 mRNA and protein in both pB-ALL cell lines and HMGA1 was effectively silenced by short hairpin RNA. Further, silencing HMGA1 dramatically halts proliferation in both cell lines, leading to a decrease in cells in S phase with a concurrent increase in G0/S1. Apoptosis also increased by 5-10% after HMGA1 silencing based on flow cytometry for Annexin V. In colony forming assays, silencing HMGA1 impaired clonogenicity in both pB-ALL cell lines. To assess HMGA1 function in leukemogenesis in vivo, we implanted control pB-ALL cells (transduced with control lentivirus) or those with HMGA1 silencing via tail vein injection into immunosuppressed mice (NOD/SCID/IL2 receptor γ). All mice receiving control REH cells succumbed to leukemia with a median survival of only 29 days. At the time of death, mice had marked splenomegaly along with leukemic cells circulating in the peripheral blood and infiltrating both the spleen and bone marrow. In contrast, mice injected with REH cells with HMGA1 silencing survived for >40 days (P<0.001) and had a significant decrease in tumor burden in the peripheral blood, spleen, and bone marrow. Similar results were obtained with 697 cells, although this model was more fulminant with control mice surviving for a median of only 17 days. To determine whether the leukemic blasts found in mice injected with ALL cells after HMGA1 silencing represented a clone that expanded because it escaped HMGA1 silencing, we assessed HMGA1 levels and found that cells capable of establishing leukemia had high HMGA1 expression, with levels similar to those observed in control cells without HMGA1 silencing. RNA-Seq analyses from REH and 697 cell lines with and without HMGA1 silencing revealed that HMGA1 up-regulates transcriptional networks involved in RAS/MAPK/ERK signaling while repressing the IDH1 metabolic gene, the latter of which functions in DNA and histone methylation. Studies are currently underway to identify effective agents to target HMGA1 pathways. Conclusions: Silencing HMGA1 dramatically disrupts leukemogenic phenotypes in vitro and prevents the development of leukemia in mice. Mechanistically, RNA-Seq analyses revealed that HMGA amplifies transcriptional networks involved cell cycle progression and epigenetic modifications. Our findings highlight the critical role for HMGA1 as a molecular switch required for leukemic transformation in pB-ALL and a rational therapeutic target that may be particularly relevant for relapsed B-ALL. Disclosures No relevant conflicts of interest to declare.

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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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