Publications by authors named "Junhyong Kim"

83 Publications

Single cell regulatory landscape of the mouse kidney highlights cellular differentiation programs and disease targets.

Nat Commun 2021 04 15;12(1):2277. Epub 2021 Apr 15.

Renal, Electrolyte, and Hypertension Division, Department of Medicine, University of Pennsylvania, Perelman School of Medicine, Philadelphia, PA, USA.

Determining the epigenetic program that generates unique cell types in the kidney is critical for understanding cell-type heterogeneity during tissue homeostasis and injury response. Here, we profile open chromatin and gene expression in developing and adult mouse kidneys at single cell resolution. We show critical reliance of gene expression on distal regulatory elements (enhancers). We reveal key cell type-specific transcription factors and major gene-regulatory circuits for kidney cells. Dynamic chromatin and expression changes during nephron progenitor differentiation demonstrates that podocyte commitment occurs early and is associated with sustained Foxl1 expression. Renal tubule cells follow a more complex differentiation, where Hfn4a is associated with proximal and Tfap2b with distal fate. Mapping single nucleotide variants associated with human kidney disease implicates critical cell types, developmental stages, genes, and regulatory mechanisms. The single cell multi-omics atlas reveals key chromatin remodeling events and gene expression dynamics associated with kidney development.
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http://dx.doi.org/10.1038/s41467-021-22266-1DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8050063PMC
April 2021

The Nuclear Receptor ESRRA Protects from Kidney Disease by Coupling Metabolism and Differentiation.

Cell Metab 2021 02 9;33(2):379-394.e8. Epub 2020 Dec 9.

Renal, Electrolyte, and Hypertension Division, Department of Medicine, University of Pennsylvania, Perelman School of Medicine, Philadelphia, PA 19104, USA; Institute for Diabetes, Obesity, and Metabolism, University of Pennsylvania, Perelman School of Medicine, Philadelphia, PA 19104, USA. Electronic address:

Kidney disease is poorly understood because of the organ's cellular diversity. We used single-cell RNA sequencing not only in resolving differences in injured kidney tissue cellular composition but also in cell-type-specific gene expression in mouse models of kidney disease. This analysis highlighted major changes in cellular diversity in kidney disease, which markedly impacted whole-kidney transcriptomics outputs. Cell-type-specific differential expression analysis identified proximal tubule (PT) cells as the key vulnerable cell type. Through unbiased cell trajectory analyses, we show that PT cell differentiation is altered in kidney disease. Metabolism (fatty acid oxidation and oxidative phosphorylation) in PT cells showed the strongest and most reproducible association with PT cell differentiation and disease. Coupling of cell differentiation and the metabolism was established by nuclear receptors (estrogen-related receptor alpha [ESRRA] and peroxisomal proliferation-activated receptor alpha [PPARA]) that directly control metabolic and PT-cell-specific gene expression in mice and patient samples while protecting from kidney disease in the mouse model.
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http://dx.doi.org/10.1016/j.cmet.2020.11.011DOI Listing
February 2021

Insertion variants missing in the human reference genome are widespread among human populations.

BMC Biol 2020 11 13;18(1):167. Epub 2020 Nov 13.

Department of Integrated Omics for Biomedical Science, WCU Graduate School, Yonsei University, Seoul, Republic of Korea.

Background: Structural variants comprise diverse genomic arrangements including deletions, insertions, inversions, and translocations, which can generally be detected in humans through sequence comparison to the reference genome. Among structural variants, insertions are the least frequently identified variants, mainly due to ascertainment bias in the reference genome, lack of previous sequence knowledge, and low complexity of typical insertion sequences. Though recent developments in long-read sequencing deliver promise in annotating individual non-reference insertions, population-level catalogues on non-reference insertion variants have not been identified and the possible functional roles of these hidden variants remain elusive.

Results: To detect non-reference insertion variants, we developed a pipeline, InserTag, which generates non-reference contigs by local de novo assembly and then infers the full-sequence of insertion variants by tracing contigs from non-human primates and other human genome assemblies. Application of the pipeline to data from 2535 individuals of the 1000 Genomes Project helped identify 1696 non-reference insertion variants and re-classify the variants as retention of ancestral sequences or novel sequence insertions based on the ancestral state. Genotyping of the variants showed that individuals had, on average, 0.92-Mbp sequences missing from the reference genome, 92% of the variants were common (allele frequency > 5%) among human populations, and more than half of the variants were major alleles. Among human populations, African populations were the most divergent and had the most non-reference sequences, which was attributed to the greater prevalence of high-frequency insertion variants. The subsets of insertion variants were in high linkage disequilibrium with phenotype-associated SNPs and showed signals of recent continent-specific selection.

Conclusions: Non-reference insertion variants represent an important type of genetic variation in the human population, and our developed pipeline, InserTag, provides the frameworks for the detection and genotyping of non-reference sequences missing from human populations.
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http://dx.doi.org/10.1186/s12915-020-00894-1DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7666470PMC
November 2020

Static array of droplets and on-demand recovery for biological assays.

Biomicrofluidics 2020 Sep 15;14(5):051302. Epub 2020 Sep 15.

Department of Chemical and Biomolecular Engineering, University of Pennsylvania, Philadelphia, Pennsylvania 19104, USA.

Microfluidics has revolutionized several research areas by providing compact yet powerful microanalytical devices that in many cases outperform conventional systems. Among different microfluidics technologies, droplet microfluidics has emerged as a powerful platform to enable analyses of biological samples and phenomena because of its simplicity and versatility. Droplet microfluidics enables high-throughput encapsulation, manipulation, and analysis of single cells while drastically reducing the cost and time required by conventional technologies. For many of these microanalysis systems, manipulation of individual droplets is extremely important as it enables multiplexed high dimensional phenotyping of the targets, going beyond surface phenotyping. One of the key manipulation steps that needs to be implemented with high precision is enabling long-term observation of droplets and recovery of a subset of these droplets for further analysis. This Perspective highlights the recent advances and provides an outlook on future developments that will enable highly complex analyses of biological samples.
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http://dx.doi.org/10.1063/5.0022383DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7494362PMC
September 2020

Lamin B2 Levels Regulate Polyploidization of Cardiomyocyte Nuclei and Myocardial Regeneration.

Dev Cell 2020 04 27;53(1):42-59.e11. Epub 2020 Feb 27.

Division of Cardiology, Pediatric Institute for Heart Regeneration and Therapeutics (I-HRT), UPMC Children's Hospital of Pittsburgh and Department of Pediatrics, University of Pittsburgh, Pittsburgh, PA 15224, USA; McGowan Institute of Regenerative Medicine, Pittsburgh, PA 15219, USA. Electronic address:

Heart regeneration requires cardiomyocyte proliferation. It is thought that formation of polyploid nuclei establishes a barrier for cardiomyocyte proliferation, but the mechanisms are largely unknown. Here, we show that the nuclear lamina filament Lamin B2 (Lmnb2), whose expression decreases in mice after birth, is essential for nuclear envelope breakdown prior to progression to metaphase and subsequent division. Inactivating Lmnb2 decreased metaphase progression, which led to formation of polyploid cardiomyocyte nuclei in neonatal mice, which, in turn, decreased myocardial regeneration. Increasing Lmnb2 expression promoted cardiomyocyte M-phase progression and cytokinesis and improved indicators of myocardial regeneration in neonatal mice. Inactivating LMNB2 in human iPS cell-derived cardiomyocytes reduced karyokinesis and increased formation of polyploid nuclei. In primary cardiomyocytes from human infants with heart disease, modifying LMNB2 expression correspondingly altered metaphase progression and ploidy of daughter nuclei. In conclusion, Lmnb2 expression is essential for karyokinesis in mammalian cardiomyocytes and heart regeneration.
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http://dx.doi.org/10.1016/j.devcel.2020.01.030DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7346764PMC
April 2020

IgSF11 regulates osteoclast differentiation through association with the scaffold protein PSD-95.

Bone Res 2020 10;8. Epub 2020 Feb 10.

1Department of Pathology and Laboratory Medicine, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA 19104 USA.

Osteoclasts are multinucleated, giant cells derived from myeloid progenitors. While receptor activator of NF-κB ligand (RANKL) stimulation is the primary driver of osteoclast differentiation, additional signaling further contributes to osteoclast maturation. Here, we demonstrate that immunoglobulin superfamily member 11 (IgSF11), whose expression increases during osteoclast differentiation, regulates osteoclast differentiation through interaction with postsynaptic density protein 95 (PSD-95), a scaffold protein with multiple protein interaction domains. IgSF11 deficiency in vivo results in impaired osteoclast differentiation and bone resorption but no observed defect in bone formation. Consequently, IgSF11-deficient mice exhibit increased bone mass. Using in vitro osteoclast culture systems, we show that IgSF11 functions through homophilic interactions. Additionally, we demonstrate that impaired osteoclast differentiation in IgSF11-deficient cells is rescued by full-length IgSF11 and that the IgSF11-PSD-95 interaction requires the 75 C-terminal amino acids of IgSF11. Our findings reveal a critical role for IgSF11 during osteoclast differentiation and suggest a role for IgSF11 in a receptor- and signal transduction molecule-containing protein complex.
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http://dx.doi.org/10.1038/s41413-019-0080-9DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7010662PMC
February 2020

Photoactivated Selective Release of Droplets from Microwell Arrays.

ACS Appl Mater Interfaces 2020 Jan 8;12(3):3936-3944. Epub 2020 Jan 8.

Droplet microfluidics has enabled a significant reduction in reaction volume and analysis time, which in turn has led to transformative advances in high-capacity screening and assays. By arranging droplets into a static array, it is possible to monitor dynamic events that occur within these microchambers over an extended period of time, facilitating the identification of rare events and cell types. In many instances, it is highly desirable to recover a small number of droplets that contain unique analytes or cells for further analyses; however, few techniques allow for selective recovery of droplets from such an array without using a complex network of physical valves, which also require a large number of control units external to the microfluidic device. In this report, we present photoactivated selective release of droplets from a static microwell array enabled by a photoresponsive polymer layer integrated into the microfluidic device. This photoresponsive layer is placed in between a microwell array that traps a large number of droplets and a PDMS slab with or without a top flow channel that can be used for recovery. By using focused light, the photoresponsive layer can either be punctured for release-up recovery or induced to create a bubble by local heating to selectively push-down release droplets. We show that the photoresponsive layer is optically transparent within the visible spectrum and thus does not interfere with optical observation of droplets. The type of photoacoustic dye and the physical properties of the photoresponsive layer can be engineered to induce either puncture of the photoresponsive layer or pushing of droplets out of the microwell arrays with low thermal impact on the droplets. We believe that the photoresponsive layer will have a broad impact in the field of soft lithography-based microfluidic devices for various applications including photoresponsive valves as well as high-throughput single-cell sequencing.
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http://dx.doi.org/10.1021/acsami.9b17575DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7207024PMC
January 2020

Single-Cell Profiling Reveals Sex, Lineage, and Regional Diversity in the Mouse Kidney.

Dev Cell 2019 11;51(3):399-413.e7

Department of Stem Cell Biology and Regenerative Medicine, Eli and Edythe Broad Center for Regenerative Medicine and Stem Cell Research, Keck School of Medicine of the University of Southern California, Los Angeles, CA 90089, USA. Electronic address:

Chronic kidney disease affects 10% of the population with notable differences in ethnic and sex-related susceptibility to kidney injury and disease. Kidney dysfunction leads to significant morbidity and mortality and chronic disease in other organ systems. A mouse-organ-centered understanding underlies rapid progress in human disease modeling and cellular approaches to repair damaged systems. To enhance an understanding of the mammalian kidney, we combined anatomy-guided single-cell RNA sequencing of the adult male and female mouse kidney with in situ expression studies and cell lineage tracing. These studies reveal cell diversity and marked sex differences, distinct organization and cell composition of nephrons dependent on the time of nephron specification, and lineage convergence, in which contiguous functionally related cell types are specified from nephron and collecting system progenitor populations. A searchable database, Kidney Cell Explorer (https://cello.shinyapps.io/kidneycellexplorer/), enables gene-cell relationships to be viewed in the anatomical framework of the kidney.
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http://dx.doi.org/10.1016/j.devcel.2019.10.005DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6948019PMC
November 2019

Control of cytokinesis by β-adrenergic receptors indicates an approach for regulating cardiomyocyte endowment.

Sci Transl Med 2019 10;11(513)

Division of Cardiology, Department of Pediatrics, UPMC Children's Hospital of Pittsburgh, University of Pittsburgh School of Medicine, Pittsburgh, PA 15224, USA.

One million patients with congenital heart disease (CHD) live in the United States. They have a lifelong risk of developing heart failure. Current concepts do not sufficiently address mechanisms of heart failure development specifically for these patients. Here, analysis of heart tissue from an infant with tetralogy of Fallot with pulmonary stenosis (ToF/PS) labeled with isotope-tagged thymidine demonstrated that cardiomyocyte cytokinesis failure is increased in this common form of CHD. We used single-cell transcriptional profiling to discover that the underlying mechanism of cytokinesis failure is repression of the cytokinesis gene ECT2, downstream of β-adrenergic receptors (β-ARs). Inactivation of the β-AR genes and administration of the β-blocker propranolol increased cardiomyocyte division in neonatal mice, which increased the number of cardiomyocytes (endowment) and conferred benefit after myocardial infarction in adults. Propranolol enabled the division of ToF/PS cardiomyocytes in vitro. These results suggest that β-blockers could be evaluated for increasing cardiomyocyte division in patients with ToF/PS and other types of CHD.
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http://dx.doi.org/10.1126/scitranslmed.aaw6419DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8132604PMC
October 2019

Understanding the kidney one cell at a time.

Kidney Int 2019 10 26;96(4):862-870. Epub 2019 Jul 26.

Renal, Electrolyte, and Hypertension Division, Department of Medicine, Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA. Electronic address:

A revolution in cellular measurement technology is underway. Whereas prior studies have been able to analyze only the averaged outputs from renal tissue, we now can accurately monitor genome-wide gene expression, regulation, function, cellular history, and cellular interactions in thousands of individual cells in a single experiment. These methods are key drivers in changing our previous morphotype-based organ and disease descriptions to unbiased genomic definitions and therefore improving our understanding of kidney development, homeostasis, and disease.
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http://dx.doi.org/10.1016/j.kint.2019.03.035DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6777841PMC
October 2019

A lineage-resolved molecular atlas of embryogenesis at single-cell resolution.

Science 2019 09 5;365(6459). Epub 2019 Sep 5.

Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.

is an animal with few cells but a wide diversity of cell types. In this study, we characterize the molecular basis for their specification by profiling the transcriptomes of 86,024 single embryonic cells. We identify 502 terminal and preterminal cell types, mapping most single-cell transcriptomes to their exact position in ' invariant lineage. Using these annotations, we find that (i) the correlation between a cell's lineage and its transcriptome increases from middle to late gastrulation, then falls substantially as cells in the nervous system and pharynx adopt their terminal fates; (ii) multilineage priming contributes to the differentiation of sister cells at dozens of lineage branches; and (iii) most distinct lineages that produce the same anatomical cell type converge to a homogenous transcriptomic state.
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http://dx.doi.org/10.1126/science.aax1971DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7428862PMC
September 2019

Avian Primordial Germ Cells Contribute to and Interact With the Extracellular Matrix During Early Migration.

Front Cell Dev Biol 2019 28;7:35. Epub 2019 Mar 28.

Department of Radiology, Children's Hospital Los Angeles, Los Angeles, CA, United States.

During early avian development, primordial germ cells (PGC) are highly migratory, moving from the central area pellucida of the blastoderm to the anterior extra-embryonic germinal crescent. The PGCs soon move into the forming blood vessels by intravasation and travel in the circulatory system to the genital ridges where they participate in the organogenesis of the gonads. This complex cellular migration takes place in close association with a nascent extracellular matrix that matures in a precise spatio-temporal pattern. We first compiled a list of quail matrisome genes by bioinformatic screening of human matrisome orthologs. Next, we used single cell RNA-seq analysis (scRNAseq) to determine that PGCs express numerous ECM and ECM-associated genes in early embryos. The expression of select ECM transcripts and proteins in PGCs were verified by fluorescent hybridization (FISH) and immunofluorescence (IF). Live imaging of transgenic quail embryos injected with fluorescent antibodies against fibronectin and laminin, showed that germinal crescent PGCs display rapid shape changes and morphological properties such as blebbing and filopodia while surrounded by, or in close contact with, an ECM fibril meshwork that is itself in constant motion. Injection of anti-β1 integrin CSAT antibodies resulted in a reduction of mature fibronectin and laminin fibril meshwork in the germinal crescent at HH4-5 but did not alter the active motility of the PGCs or their ability to populate the germinal crescent. These results suggest that integrin β1 receptors are important, but not required, for PGCs to successfully migrate during embryonic development, but instead play a vital role in ECM fibrillogenesis and assembly.
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http://dx.doi.org/10.3389/fcell.2019.00035DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6447691PMC
March 2019

Multi-Dimensional Mapping of Brain-Derived Extracellular Vesicle MicroRNA Biomarker for Traumatic Brain Injury Diagnostics.

J Neurotrauma 2020 11 6;37(22):2424-2434. Epub 2019 May 6.

Department of Bioengineering, University of Pennsylvania, Philadelphia, Pennsylvania, USA.

The diagnosis and prognosis of traumatic brain injury (TBI) is complicated by variability in the type and severity of injuries and the multiple endophenotypes that describe each patient's response and recovery to the injury. It has been challenging to capture the multiple dimensions that describe an injury and its recovery to provide clinically useful information. To address this challenge, we have performed an open-ended search for panels of microRNA (miRNA) biomarkers, packaged inside of brain-derived extracellular vesicles (EVs), that can be combined algorithmically to accurately classify various states of injury. We mapped GluR2+ EV miRNA across a variety of injury types, injury intensities, history of injuries, and time elapsed after injury, and sham controls in a pre-clinical murine model ( = 116), as well as in clinical samples ( = 36). We combined next-generation sequencing with a technology recently developed by our lab, Track Etched Magnetic Nanopore (TENPO) sorting, to enrich for GluR2+ EVs and profile their miRNA. By mapping and comparing brain-derived EV miRNA between various injuries, we have identified signaling pathways in the packaged miRNA that connect these biomarkers to underlying mechanisms of TBI. Many of these pathways are shared between the pre-clinical model and the clinical samples, and present distinct signatures across different injury models and times elapsed after injury. Using this map of EV miRNA, we applied machine learning to define a panel of biomarkers to successfully classify specific states of injury, paving the way for a prognostic blood test for TBI. We generated a panel of eight miRNAs (miR-150-5p, miR-669c-5p, miR-488-3p, miR-22-5p, miR-9-5p, miR-6236, miR-219a.2-3p, miR-351-3p) for injured mice versus sham mice and four miRNAs (miR-203b-5p, miR-203a-3p, miR-206, miR-185-5p) for TBI patients versus healthy controls.
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http://dx.doi.org/10.1089/neu.2018.6220DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7698852PMC
November 2020

Genomic evidence for shared common ancestry of East African hunting-gathering populations and insights into local adaptation.

Proc Natl Acad Sci U S A 2019 03 19;116(10):4166-4175. Epub 2019 Feb 19.

Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104;

Anatomically modern humans arose in Africa ∼300,000 years ago, but the demographic and adaptive histories of African populations are not well-characterized. Here, we have generated a genome-wide dataset from 840 Africans, residing in western, eastern, southern, and northern Africa, belonging to 50 ethnicities, and speaking languages belonging to four language families. In addition to agriculturalists and pastoralists, our study includes 16 populations that practice, or until recently have practiced, a hunting-gathering (HG) lifestyle. We observe that genetic structure in Africa is broadly correlated not only with geography, but to a lesser extent, with linguistic affiliation and subsistence strategy. Four East African HG (EHG) populations that are geographically distant from each other show evidence of common ancestry: the Hadza and Sandawe in Tanzania, who speak languages with clicks classified as Khoisan; the Dahalo in Kenya, whose language has remnant clicks; and the Sabue in Ethiopia, who speak an unclassified language. Additionally, we observed common ancestry between central African rainforest HGs and southern African San, the latter of whom speak languages with clicks classified as Khoisan. With the exception of the EHG, central African rainforest HGs, and San, other HG groups in Africa appear genetically similar to neighboring agriculturalist or pastoralist populations. We additionally demonstrate that infectious disease, immune response, and diet have played important roles in the adaptive landscape of African history. However, while the broad biological processes involved in recent human adaptation in Africa are often consistent across populations, the specific loci affected by selective pressures more often vary across populations.
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http://dx.doi.org/10.1073/pnas.1817678116DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6410815PMC
March 2019

Comprehensive catalog of dendritically localized mRNA isoforms from sub-cellular sequencing of single mouse neurons.

BMC Biol 2019 01 24;17(1). Epub 2019 Jan 24.

Graduate Program in Genomics and Computational Biology, Biomedical Graduate Studies, University of Pennsylvania, 160 BRB II/III - 421 Curie Blvd, Philadelphia, PA, 19104-6064, USA.

Background: RNA localization involves cis-motifs that are recognized by RNA-binding proteins (RBP), which then mediate localization to specific sub-cellular compartments. RNA localization is critical for many different cell functions, e.g., in neuronal dendrites, localization is a critical step for long-lasting synaptic potentiation. However, there is little consensus regarding which RNAs are localized and the role of alternative isoforms in localization. A comprehensive catalog of localized RNA can help dissect RBP/RNA interactions and localization motifs. Here, we utilize a single cell sub-cellular RNA sequencing approach to profile differentially localized RNAs from individual cells across multiple single cells to help identify a consistent set of localized RNA in mouse neurons.

Results: Using independent RNA sequencing from soma and dendrites of the same neuron, we deeply profiled the sub-cellular transcriptomes to assess the extent and variability of dendritic RNA localization in individual hippocampal neurons, including an assessment of differential localization of alternative 3'UTR isoforms. We identified 2225 dendritic RNAs, including 298 cases of 3'UTR isoform-specific localization. We extensively analyzed the localized RNAs for potential localization motifs, finding that B1 and B2 SINE elements are up to 5.7 times more abundant in localized RNA 3'UTRs than non-localized, and also functionally characterized the localized RNAs using protein structure analysis.

Conclusion: We integrate our list of localized RNAs with the literature to provide a comprehensive list of known dendritically localized RNAs as a resource. This catalog of transcripts, including differentially localized isoforms and computationally hypothesized localization motifs, will help investigators further dissect the genome-scale mechanism of RNA localization.
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http://dx.doi.org/10.1186/s12915-019-0630-zDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6344992PMC
January 2019

Exosomal PD-L1 contributes to immunosuppression and is associated with anti-PD-1 response.

Nature 2018 08 8;560(7718):382-386. Epub 2018 Aug 8.

Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.

Tumour cells evade immune surveillance by upregulating the surface expression of programmed death-ligand 1 (PD-L1), which interacts with programmed death-1 (PD-1) receptor on T cells to elicit the immune checkpoint response. Anti-PD-1 antibodies have shown remarkable promise in treating tumours, including metastatic melanoma. However, the patient response rate is low. A better understanding of PD-L1-mediated immune evasion is needed to predict patient response and improve treatment efficacy. Here we report that metastatic melanomas release extracellular vesicles, mostly in the form of exosomes, that carry PD-L1 on their surface. Stimulation with interferon-γ (IFN-γ) increases the amount of PD-L1 on these vesicles, which suppresses the function of CD8 T cells and facilitates tumour growth. In patients with metastatic melanoma, the level of circulating exosomal PD-L1 positively correlates with that of IFN-γ, and varies during the course of anti-PD-1 therapy. The magnitudes of the increase in circulating exosomal PD-L1 during early stages of treatment, as an indicator of the adaptive response of the tumour cells to T cell reinvigoration, stratifies clinical responders from non-responders. Our study unveils a mechanism by which tumour cells systemically suppress the immune system, and provides a rationale for the application of exosomal PD-L1 as a predictor for anti-PD-1 therapy.
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http://dx.doi.org/10.1038/s41586-018-0392-8DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6095740PMC
August 2018

miRNA Profiling of Magnetic Nanopore-Isolated Extracellular Vesicles for the Diagnosis of Pancreatic Cancer.

Cancer Res 2018 07 7;78(13):3688-3697. Epub 2018 May 7.

Department of Bioengineering, School of Engineering and Applied Sciences, University of Pennsylvania, Philadelphia, Pennsylvania.

Improved diagnostics for pancreatic ductal adenocarcinoma (PDAC) to detect the disease at earlier, curative stages and to guide treatments is crucial to progress against this disease. The development of a liquid biopsy for PDAC has proven challenging due to the sparsity and variable phenotypic expression of circulating biomarkers. Here we report methods we developed for isolating specific subsets of extracellular vesicles (EV) from plasma using a novel magnetic nanopore capture technique. In addition, we present a workflow for identifying EV miRNA biomarkers using RNA sequencing and machine-learning algorithms, which we used in combination to classify distinct cancer states. Applying this approach to a mouse model of PDAC, we identified a biomarker panel of 11 EV miRNAs that could distinguish mice with PDAC from either healthy mice or those with precancerous lesions in a training set of = 27 mice and a user-blinded validation set of = 57 mice (88% accuracy in a three-way classification). These results provide strong proof-of-concept support for the feasibility of using EV miRNA profiling and machine learning for liquid biopsy. These findings present a panel of extracellular vesicle miRNA blood-based biomarkers that can detect pancreatic cancer at a precancerous stage in a transgenic mouse model. .
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http://dx.doi.org/10.1158/0008-5472.CAN-17-3703DOI Listing
July 2018

Rare Cell Detection by Single-Cell RNA Sequencing as Guided by Single-Molecule RNA FISH.

Cell Syst 2018 Feb 14;6(2):171-179.e5. Epub 2018 Feb 14.

Department of Bioengineering, University of Pennsylvania, Philadelphia, PA, USA; Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA; Epigenetics Institute, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA. Electronic address:

Although single-cell RNA sequencing can reliably detect large-scale transcriptional programs, it is unclear whether it accurately captures the behavior of individual genes, especially those that express only in rare cells. Here, we use single-molecule RNA fluorescence in situ hybridization as a gold standard to assess trade-offs in single-cell RNA-sequencing data for detecting rare cell expression variability. We quantified the gene expression distribution for 26 genes that range from ubiquitous to rarely expressed and found that the correspondence between estimates across platforms improved with both transcriptome coverage and increased number of cells analyzed. Further, by characterizing the trade-off between transcriptome coverage and number of cells analyzed, we show that when the number of genes required to answer a given biological question is small, then greater transcriptome coverage is more important than analyzing large numbers of cells. More generally, our report provides guidelines for selecting quality thresholds for single-cell RNA-sequencing experiments aimed at rare cell analyses.
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http://dx.doi.org/10.1016/j.cels.2018.01.014DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6078200PMC
February 2018

Coordination of olfactory receptor choice with guidance receptor expression and function in olfactory sensory neurons.

PLoS Genet 2018 01 31;14(1):e1007164. Epub 2018 Jan 31.

Department of Neuroscience, Perelman School of Medicine, University of Pennsylvania Philadelphia, PA, United States of America.

Olfactory sensory neurons choose to express a single odorant receptor (OR) from a large gene repertoire and extend axons to reproducible, OR-specific locations within the olfactory bulb. This developmental process produces a topographically organized map of odorant experience in the brain. The axon guidance mechanisms that generate this pattern of connectivity, as well as those that coordinate OR choice and axonal guidance receptor expression, are incompletely understood. We applied the powerful approach of single-cell RNA-seq on newly born olfactory sensory neurons (OSNs) in young zebrafish larvae to address these issues. Expression profiles were generated for 56 individual Olfactory Marker Protein (OMP) positive sensory neurons by single-cell (SC) RNA-seq. We show that just as in mouse OSNs, mature zebrafish OSNs typically express a single predominant OR transcript. Our previous work suggests that OSN targeting is related to the OR clade from which a sensory neuron chooses to express its odorant receptor. We categorized each of the mature cells based on the clade of their predominantly expressed OR. Transcripts expressed at higher levels in each of three clade-related categories were identified using Penalized Linear Discriminant Analysis (PLDA). A genome-wide approach was used to identify membrane-associated proteins that are most likely to have guidance-related activity. We found that OSNs that choose to express an OR from a particular clade also express specific subsets of potential axon guidance genes and transcription factors. We validated our identification of candidate axon guidance genes for one clade of OSNs using bulk RNA-seq from a subset of transgene-labeled neurons that project to a single protoglomerulus. The differential expression patterns of selected candidate guidance genes were confirmed using fluorescent in situ hybridization. Most importantly, we observed axonal mistargeting in knockouts of three candidate axonal guidance genes identified in this analysis: nrp1a, nrp1b, and robo2. In each case, targeting errors were detected in the subset of axons that normally express these transcripts at high levels, and not in the axons that express them at low levels. Our findings demonstrate that specific, functional, axonal guidance related genes are expressed in subsets of OSNs that that can be categorized by their patterns of OR expression.
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http://dx.doi.org/10.1371/journal.pgen.1007164DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5809090PMC
January 2018

PIVOT: platform for interactive analysis and visualization of transcriptomics data.

BMC Bioinformatics 2018 01 5;19(1). Epub 2018 Jan 5.

Department of Biology, University of Pennsylvania, Philadelphia, PA, USA.

Background: Many R packages have been developed for transcriptome analysis but their use often requires familiarity with R and integrating results of different packages requires scripts to wrangle the datatypes. Furthermore, exploratory data analyses often generate multiple derived datasets such as data subsets or data transformations, which can be difficult to track.

Results: Here we present PIVOT, an R-based platform that wraps open source transcriptome analysis packages with a uniform user interface and graphical data management that allows non-programmers to interactively explore transcriptomics data. PIVOT supports more than 40 popular open source packages for transcriptome analysis and provides an extensive set of tools for statistical data manipulations. A graph-based visual interface is used to represent the links between derived datasets, allowing easy tracking of data versions. PIVOT further supports automatic report generation, publication-quality plots, and program/data state saving, such that all analysis can be saved, shared and reproduced.

Conclusions: PIVOT will allow researchers with broad background to easily access sophisticated transcriptome analysis tools and interactively explore transcriptome datasets.
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http://dx.doi.org/10.1186/s12859-017-1994-0DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5756333PMC
January 2018

Pervasive within-Mitochondrion Single-Nucleotide Variant Heteroplasmy as Revealed by Single-Mitochondrion Sequencing.

Cell Rep 2017 Dec;21(10):2706-2713

Department of Pharmacology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA. Electronic address:

A number of mitochondrial diseases arise from single-nucleotide variant (SNV) accumulation in multiple mitochondria. Here, we present a method for identification of variants present at the single-mitochondrion level in individual mouse and human neuronal cells, allowing for extremely high-resolution study of mitochondrial mutation dynamics. We identified extensive heteroplasmy between individual mitochondrion, along with three high-confidence variants in mouse and one in human that were present in multiple mitochondria across cells. The pattern of variation revealed by single-mitochondrion data shows surprisingly pervasive levels of heteroplasmy in inbred mice. Distribution of SNV loci suggests inheritance of variants across generations, resulting in Poisson jackpot lines with large SNV load. Comparison of human and mouse variants suggests that the two species might employ distinct modes of somatic segregation. Single-mitochondrion resolution revealed mitochondria mutational dynamics that we hypothesize to affect risk probabilities for mutations reaching disease thresholds.
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http://dx.doi.org/10.1016/j.celrep.2017.11.031DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5771502PMC
December 2017

Accounting for technical noise in differential expression analysis of single-cell RNA sequencing data.

Nucleic Acids Res 2017 Nov;45(19):10978-10988

Department of Statistics, University of Pennsylvania Wharton School, Philadelphia, PA 19104, USA.

Recent technological breakthroughs have made it possible to measure RNA expression at the single-cell level, thus paving the way for exploring expression heterogeneity among individual cells. Current single-cell RNA sequencing (scRNA-seq) protocols are complex and introduce technical biases that vary across cells, which can bias downstream analysis without proper adjustment. To account for cell-to-cell technical differences, we propose a statistical framework, TASC (Toolkit for Analysis of Single Cell RNA-seq), an empirical Bayes approach to reliably model the cell-specific dropout rates and amplification bias by use of external RNA spike-ins. TASC incorporates the technical parameters, which reflect cell-to-cell batch effects, into a hierarchical mixture model to estimate the biological variance of a gene and detect differentially expressed genes. More importantly, TASC is able to adjust for covariates to further eliminate confounding that may originate from cell size and cell cycle differences. In simulation and real scRNA-seq data, TASC achieves accurate Type I error control and displays competitive sensitivity and improved robustness to batch effects in differential expression analysis, compared to existing methods. TASC is programmed to be computationally efficient, taking advantage of multi-threaded parallelization. We believe that TASC will provide a robust platform for researchers to leverage the power of scRNA-seq.
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http://dx.doi.org/10.1093/nar/gkx754DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5737676PMC
November 2017

Single cell transcriptomics of noncoding RNAs and their cell-specificity.

Wiley Interdiscip Rev RNA 2017 11 1;8(6). Epub 2017 Aug 1.

Department of Biology, Penn Program in Single Cell Biology, University of Pennsylvania, Philadelphia, PA, USA.

Recent developments of single cell transcriptome profiling methods have led to the realization that many seemingly homogeneous cells have surprising levels of expression variability. The biological implications of the high degree of variability is unclear but one possibility is that many genes are restricted in expression to small lineages of cells, suggesting the existence of many more cell types than previously estimated. Noncoding RNA (ncRNA) are thought to be key parts of gene regulatory processes and their single cell expression patterns may help to dissect the biological function of single cell variability. Technology for measuring ncRNA in single cell is still in development and most of the current single cell datasets have reliable measurements for only long noncoding RNA (lncRNA). Most works report that lncRNAs show lineage-specific restricted expression patterns, which suggest that they might determine, at least in part, lineage fates and cell subtypes. However, evidence is still inconclusive as to whether lncRNAs and other ncRNAs are more lineage-specific than protein-coding genes. Nevertheless, measurement of ncRNAs in single cells will be important for studies of cell types and single cell function. WIREs RNA 2017, 8:e1433. doi: 10.1002/wrna.1433 For further resources related to this article, please visit the WIREs website.
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http://dx.doi.org/10.1002/wrna.1433DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5675046PMC
November 2017

Challenges and emerging directions in single-cell analysis.

Genome Biol 2017 05 8;18(1):84. Epub 2017 May 8.

Broad Institute of MIT and Harvard, Cambridge, MA, USA.

Single-cell analysis is a rapidly evolving approach to characterize genome-scale molecular information at the individual cell level. Development of single-cell technologies and computational methods has enabled systematic investigation of cellular heterogeneity in a wide range of tissues and cell populations, yielding fresh insights into the composition, dynamics, and regulatory mechanisms of cell states in development and disease. Despite substantial advances, significant challenges remain in the analysis, integration, and interpretation of single-cell omics data. Here, we discuss the state of the field and recent advances and look to future opportunities.
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http://dx.doi.org/10.1186/s13059-017-1218-yDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5421338PMC
May 2017

CYCLOPS reveals human transcriptional rhythms in health and disease.

Proc Natl Acad Sci U S A 2017 05 24;114(20):5312-5317. Epub 2017 Apr 24.

Department of Biology, University of Pennsylvania, Philadelphia, PA 19104.

Circadian rhythms modulate many aspects of physiology. Knowledge of the molecular basis of these rhythms has exploded in the last 20 years. However, most of these data are from model organisms, and translation to clinical practice has been limited. Here, we present an approach to identify molecular rhythms in humans from thousands of unordered expression measurements. Our algorithm, cyclic ordering by periodic structure (CYCLOPS), uses evolutionary conservation and machine learning to identify elliptical structure in high-dimensional data. From this structure, CYCLOPS estimates the phase of each sample. We validated CYCLOPS using temporally ordered mouse and human data and demonstrated its consistency on human data from two independent research sites. We used this approach to identify rhythmic transcripts in human liver and lung, including hundreds of drug targets and disease genes. Importantly, for many genes, the circadian variation in expression exceeded variation from genetic and other environmental factors. We also analyzed hepatocellular carcinoma samples and show these solid tumors maintain circadian function but with aberrant output. Finally, to show how this method can catalyze medical translation, we show that dosage time can temporally segregate efficacy from dose-limiting toxicity of streptozocin, a chemotherapeutic drug. In sum, these data show the power of CYCLOPS and temporal reconstruction in bridging basic circadian research and clinical medicine.
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http://dx.doi.org/10.1073/pnas.1619320114DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5441789PMC
May 2017

Complete fold annotation of the human proteome using a novel structural feature space.

Sci Rep 2017 04 13;7:46321. Epub 2017 Apr 13.

Genomics and Computational Biology Program, University of Pennsylvania, Philadelphia, PA 19104, USA.

Recognition of protein structural fold is the starting point for many structure prediction tools and protein function inference. Fold prediction is computationally demanding and recognizing novel folds is difficult such that the majority of proteins have not been annotated for fold classification. Here we describe a new machine learning approach using a novel feature space that can be used for accurate recognition of all 1,221 currently known folds and inference of unknown novel folds. We show that our method achieves better than 94% accuracy even when many folds have only one training example. We demonstrate the utility of this method by predicting the folds of 34,330 human protein domains and showing that these predictions can yield useful insights into potential biological function, such as prediction of RNA-binding ability. Our method can be applied to de novo fold prediction of entire proteomes and identify candidate novel fold families.
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http://dx.doi.org/10.1038/srep46321DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5390313PMC
April 2017

The purinergic receptor P2X5 regulates inflammasome activity and hyper-multinucleation of murine osteoclasts.

Sci Rep 2017 03 15;7(1):196. Epub 2017 Mar 15.

Department of Pathology and Laboratory Medicine, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, 19104, USA.

Excessive bone resorption by osteoclasts (OCs) can result in serious clinical outcomes, including bone loss that may weaken skeletal or periodontal strength. Proper bone homeostasis and skeletal strength are maintained by balancing OC function with the bone-forming function of osteoblasts. Unfortunately, current treatments that broadly inhibit OC differentiation or function may also interfere with coupled bone formation. We therefore identified a factor, the purinergic receptor P2X5 that is highly expressed during the OC maturation phase, and which we show here plays no apparent role in early bone development and homeostasis, but which is required for osteoclast-mediated inflammatory bone loss and hyper-multinucleation of OCs. We further demonstrate that P2X5 is required for ATP-mediated inflammasome activation and IL-1β production by OCs, and that P2X5-deficient OC maturation is rescued in vitro by addition of exogenous IL-1β. These findings identify a mechanism by which OCs react to inflammatory stimuli, and may identify purinergic signaling as a therapeutic target for bone loss-related inflammatory conditions.
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http://dx.doi.org/10.1038/s41598-017-00139-2DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5427844PMC
March 2017

Primary Cell Culture of Live Neurosurgically Resected Aged Adult Human Brain Cells and Single Cell Transcriptomics.

Cell Rep 2017 01;18(3):791-803

Department of Pharmacology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA. Electronic address:

Investigation of human CNS disease and drug effects has been hampered by the lack of a system that enables single-cell analysis of live adult patient brain cells. We developed a culturing system, based on a papain-aided procedure, for resected adult human brain tissue removed during neurosurgery. We performed single-cell transcriptomics on over 300 cells, permitting identification of oligodendrocytes, microglia, neurons, endothelial cells, and astrocytes after 3 weeks in culture. Using deep sequencing, we detected over 12,000 expressed genes, including hundreds of cell-type-enriched mRNAs, lncRNAs and pri-miRNAs. We describe cell-type- and patient-specific transcriptional hierarchies. Single-cell transcriptomics on cultured live adult patient derived cells is a prime example of the promise of personalized precision medicine. Because these cells derive from subjects ranging in age into their sixties, this system permits human aging studies previously possible only in rodent systems.
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http://dx.doi.org/10.1016/j.celrep.2016.12.066DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5316103PMC
January 2017

Assessing characteristics of RNA amplification methods for single cell RNA sequencing.

BMC Genomics 2016 11 24;17(1):966. Epub 2016 Nov 24.

Department of Bioengineering, University of California at San Diego, La Jolla, CA, USA.

Background: Recently, measurement of RNA at single cell resolution has yielded surprising insights. Methods for single-cell RNA sequencing (scRNA-seq) have received considerable attention, but the broad reliability of single cell methods and the factors governing their performance are still poorly known.

Results: Here, we conducted a large-scale control experiment to assess the transfer function of three scRNA-seq methods and factors modulating the function. All three methods detected greater than 70% of the expected number of genes and had a 50% probability of detecting genes with abundance greater than 2 to 4 molecules. Despite the small number of molecules, sequencing depth significantly affected gene detection. While biases in detection and quantification were qualitatively similar across methods, the degree of bias differed, consistent with differences in molecular protocol. Measurement reliability increased with expression level for all methods and we conservatively estimate measurements to be quantitative at an expression level greater than ~5-10 molecules.

Conclusions: Based on these extensive control studies, we propose that RNA-seq of single cells has come of age, yielding quantitative biological information.
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http://dx.doi.org/10.1186/s12864-016-3300-3DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5122016PMC
November 2016

High-resolution transcriptome analysis reveals neuropathic pain gene-expression signatures in spinal microglia after nerve injury.

Pain 2016 Apr;157(4):964-976

Pain Cognitive Function Research Center, Seoul National University, Seoul, Republic of Korea Dental Research Institute and Department of Neurobiology and Physiology, School of Dentistry, Seoul National University, Seoul, Republic of Korea Department of Biology, University of Pennsylvania, Philadelphia, PA, USA Medical Genomics Research Center, Korea Research Institute of Bioscience & Biotechnology, Daejeon, Korea Department of Cell Biology and Neuroscience, Rutgers University, Piscataway, NJ, USA Pain Research Laboratory, Institute of Nautical Medicine, Nantong University, Nantong, Jiangsu, China Department of Computer and Information Science, University of Pennsylvania, Philadelphia, PA, USA Department of Brain and Cognitive Sciences, College of Natural Sciences, Seoul National University, Seoul, Republic of Korea.

Microglial cells, the resident immune cells of the spinal cord, become activated in response to peripheral nerve injury. Microglia activation contributes to the development of neuropathic pain. Here we employed microarray analysis of individually collected pools of 10 spinal microglia cells to identify changes of levels and cell-to-cell expression variance of microglial genes during their activation after peripheral nerve injury. The analysis of microglia on postoperative day 1 (POD1) identified miR-29c as a critical factor for microglial activation and the development of neuropathic pain. Early POD1 microglia exhibited a very distinct expression profile compared to late POD7 microglia, possibly leading to the transition from initiation to maintenance of neuropathic pain. We found sample variance patterns that were consistent with the hypothesis that microglia were highly heterogeneous at the level of individual cells, and variation analysis identified 56 microglial genes potentially linked to the maintenance of neuropathic pain which included Gria1. This study provides insights into spinal microglial biology and reveals novel microglial targets for the treatment of neuropathic pain.
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http://dx.doi.org/10.1097/j.pain.0000000000000470DOI Listing
April 2016