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Abstract Background Aging has been associated with widespread changes at the gene expression level in multiple mammalian tissues. We have used high density oligonucleotide arrays and novel statistical methods to identify specific transcriptional classes that may uncover biological processes that play a central role in mammalian aging. Results We identified 712 transcripts that are differentially expressed in young (5 month old) and old (25-month old) mouse skeletal muscle. Caloric restriction (CR) completely or partially reversed 87% of the changes in expression. Examination of individual genes revealed a transcriptional profile indicative of increased p53 activity in the older muscle. To determine whether the increase in p53 activity is associated with transcriptional activation of apoptotic targets, we performed RT-PCR on four well known mediators of p53-induced apoptosis: puma, noxa, tnfrsf10b and bok. Expression levels for these proapoptotic genes increased significantly with age (P < 0.05), while CR significantly lowered expression levels for these genes as compared to control fed old mice (P < 0.05). Age-related induction of p53-related genes was observed in multiple tissues, but was not observed in young SOD2+/- and GPX4+/- mice, suggesting that oxidative stress does not induce the expression of these genes. Western blot analysis confirmed that protein levels for both p21 and GADD45a, two established transcriptional targets of p53, were higher in the older muscle tissue. Conclusion These observations support a role for p53-mediated transcriptional program in mammalian aging and suggest that mechanisms other than reactive oxygen species are involved in the age-related transcriptional activation of p53 targets.

Identifying the genetic basis of complex traits remains an important and challenging problem with the potential to affect a broad range of biological endeavors. A number of statistical methods are available for mapping quantitative trait loci (QTL), but their application to high-throughput phenotypes has been limited as most require user input and interaction. Recently, methods have been developed specifically for expression QTL (eQTL)mapping, but they too are limited in that they do not allow for interactions and QTL of moderate effect. We here propose an automated model-selection-based approach that identifies multiple eQTL in experimental populations, allowing for eQTL of moderate effect and interactions. Output can be used to identify groups of transcripts that are likely coregulated, as demonstrated in a study of diabetes in mouse. [ABSTRACT FROM AUTHOR]

Diffuse midline glioma, H3 K27-altered (DMG) are highly aggressive malignancies of the central nervous system (CNS) that primarily affect the pediatric population. Large scale spatial transcriptomic studies have implicated that tumor microenvironmental landscape plays an important role in determining the phenotypic differences in tumor presentation and clinical course, however, data connecting overall transcriptomic changes to the protein level is lacking. The NanoString GeoMx ™  Digital Spatial Profiler platform was used to determine the spatial transcriptomic and proteomic landscape in a cohort of both pediatric and adult H3 K27-altered DMG biopsy samples. Three fluorescently labeled antibodies targeting immune cells (CD45), epithelial cells (PanCK), tumor cells (H3 K27M) and a nucleic acid stain (SYTO-13) were used to establish regions of interest (ROI) for genomic and proteomic analysis. We found genetic alterations within the tumor which can be delineated across patient age and spatial location. We show that the H3 K27M mutation itself has a profound impact on tumor cells transcriptomics and interestingly we found limited fidelity between overall transcriptome and proteome. Our data also validate a previously described genomic signature at the proteomic level and reveal a special shift in the signature based on the local TME composition., (© 2024. The Author(s).)

Asthma is a complex disease caused by genetic and environmental factors. Studies show that wheezing during rhinovirus infection correlates with childhood asthma development. Over 150 non-coding risk variants for asthma have been identified, many affecting gene regulation in T cells, but the effects of most risk variants remain unknown. We hypothesized that airway epithelial cells could also mediate genetic susceptibility to asthma given they are the first line of defense against respiratory viruses and allergens. We integrated genetic data with transcriptomics of airway epithelial cells subject to different stimuli. We demonstrate that rhinovirus infection significantly upregulates childhood-onset asthma-associated genes, particularly in non-ciliated cells. This enrichment is also observed with influenza infection but not with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) or cytokine activation. Overall, our results suggest that rhinovirus infection is an environmental factor that interacts with genetic risk factors through non-ciliated airway epithelial cells to drive childhood-onset asthma., Competing Interests: Declaration of interests J.A.B. has served on scientific advisory boards for Siolta Therapeutics, Third Harmonic Bio, and Sanofi/Aventis. N.A.B. has served on scientific advisory boards for Regeneron., (Copyright © 2024 The Author(s). Published by Elsevier Inc. All rights reserved.)

Human papillomaviruses (HPV), most commonly HPV16, are associated with a subset of head and neck squamous cell carcinoma (HNSCC) tumors, primarily oropharyngeal carcinomas, with integration of viral genomes into host chromosomes associated with worse survival outcomes. We analyzed TCGA data and found that HPV+ HNSCC expressed higher transcript levels of the bromodomain and extra terminal domain (BET) family of transcriptional coregulators. The role of BET protein-mediated transcription of viral-cellular genes in the viral-HNSCC genomes needs to be better understood. Using a combination of TAME-Seq, qRT-PCR, and immunoblot analyses, we show that BET inhibition downregulates E6 and E7 significantly, with heterogeneity in the downregulation of viral transcription across different HPV+ HNSCC cell lines. Chemical BET inhibition was phenocopied with the knockdown of BRD4, mirroring the downregulation of viral E6 and E7 expression. We found that BET inhibition directly downregulated c-Myc and E2F expression and induced CDKN1A (p21) expression, leading to a G1-cell cycle arrest with apoptotic activity. Overall, our studies demonstrate that BET inhibition regulates both E6 and E7 viral and key cellular cell cycle regulator E2F gene expression and cellular gene expression in HPV-associated HNSCC and highlight the potential of BET inhibitors as a therapeutic strategy for this disease while also underscoring the importance of considering the heterogeneity in cellular responses to BET inhibition., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2024 Rao, Stosic, Mohanty, Suresh, Wang, Lee, Nickel, Chandrashekar, Kimple, Lambert, Kendziorski, Rounge and Iyer.)

Granuloma annulare (GA) is an idiopathic condition characterized by granulomatous inflammation in the skin. Prior studies have suggested that GA develops from various triggers, leading to a complex interplay involving innate and adaptive immunity, tissue remodeling, and fibrosis. Macrophages are the major immune cells comprising GA granulomas; however, the molecular drivers and inflammatory signaling cascade behind macrophage activation are poorly understood. Histologically, GA exhibits both palisaded and interstitial patterns on histology; however, the molecular composition of GA at the spatial level remains unexplored. GA is a condition without Food and Drug Administration-approved therapies despite the significant impact of GA on QOL. Spatial transcriptomics is a valuable tool for profiling localized, genome-wide gene expression changes across tissues, with emerging applications in clinical medicine. To improve our understanding of the spatially localized gene expression patterns underlying GA, we profiled the spatial gene expression landscape from 6 patients with GA. Our findings revealed mixed T helper 1 and T helper 2 signals comprising the GA microenvironment and spatially distinct M1 and M2 macrophage polarization characteristics. IFN-γ and TNF signals emerged as important regulators of GA granulomatous inflammation, and IL-32 emerged as a key driver of granulomatous inflammation. Overall, our spatial transcriptomics data indicate that GA exhibits mixed immune and macrophage polarization., (Copyright © 2024 The Authors. Published by Elsevier Inc. All rights reserved.)

Microbiota play a critical role in the development and training of host innate and adaptive immunity. We present the cellular landscape of the upper airway, specifically the larynx, by establishing a reference single-cell atlas, while dissecting the role of microbiota in cell development and function at single-cell resolution. We highlight the larynx's cellular heterogeneity with the identification of 16 cell types and 34 distinct subclusters. Our data demonstrate that commensal microbiota have extensive impact on the laryngeal immune system by regulating cell differentiation, increasing the expression of genes associated with host defense, and altering gene regulatory networks. We uncover macrophages, innate lymphoid cells, and multiple secretory epithelial cells, whose cell proportions and expressions vary with microbial exposure. These cell types play pivotal roles in maintaining laryngeal and upper airway health and provide specific guidance into understanding the mechanism of immune system regulation by microbiota in laryngeal health and disease., Competing Interests: The authors declare no competing interests., (© 2024 The Authors.)

Stereotactic radiosurgery (SRS) has been shown to be efficacious for the treatment of limited brain metastasis (BM); however, the effects of SRS on human brain metastases have yet to be studied. We performed genomic analysis on resected brain metastases from patients whose resected lesion was previously treated with SRS. Our analyses demonstrated for the first time that patients possess a distinct genomic signature based on type of treatment failure including local failure, leptomeningeal spread, and radio-necrosis. Examination of the center and peripheral edge of the tumors treated with SRS indicated differential DNA damage distribution and an enrichment for tumor suppressor mutations and DNA damage repair pathways along the peripheral edge. Furthermore, the two clinical modalities used to deliver SRS, LINAC and GK, demonstrated differential effects on the tumor landscape even between controlled primary sites. Our study provides, in human, biological evidence of differential effects of SRS across BM's., Competing Interests: The authors declare no competing interests., (© 2024 The Author(s).)

Motivation: Spatial transcriptomics (ST) experiments provide spatially localized measurements of genome-wide gene expression allowing for an unprecedented opportunity to investigate cellular heterogeneity and organization within a tissue. Statistical and computational frameworks exist that implement robust methods for pre-processing and analyzing data in ST experiments. However, the lack of an interactive suite of tools for visualizing ST data and results currently limits the full potential of ST experiments., Results: To fill the gap, we developed SpatialView, an open-source web browser-based interactive application for visualizing data and results from multiple 10× Genomics Visium ST experiments. We anticipate SpatialView will be useful to a broad array of clinical and basic science investigators utilizing ST to study disease., Availability and Implementation: SpatialView is available at https://github.com/kendziorski-lab/SpatialView (and https://doi.org/10.5281/zenodo.10223907); a demo application is available at https://www.biostat.wisc.edu/˜kendzior/spatialviewdemo/., (Published by Oxford University Press 2024.)

Predicting which patients will progress to metastatic disease after surgery for non-metastatic clear cell renal cell carcinoma (ccRCC) is difficult; however, recent data suggest that tumor immune cell infiltration could be used as a biomarker. We evaluated the quantity and type of immune cells infiltrating ccRCC tumors for associations with metastatic progression following attempted curative surgery. We quantified immune cell densities in the tumor microenvironment and validated our findings in two independent patient cohorts with multi-region sampling to investigate the impact of heterogeneity on prognostic accuracy. For non-metastatic ccRCC, increased CD8 + T cell infiltration was associated with a reduced likelihood of progression to metastatic disease. Interestingly, patients who progressed to metastatic disease also had increased percentages of exhausted CD8 + T cells. Finally, we evaluated the spatial heterogeneity of the immune infiltration and demonstrated that patients without metastatic progression had CD8 + T cells in closer proximity to ccRCC cells. These data strengthen the evidence for CD8 + T cell infiltration as a prognostic biomarker in non-metastatic ccRCC and demonstrate that multi-region sampling may be necessary to fully characterize immune infiltration within heterogeneous tumors. Tumor CD8 + T cell infiltration should be investigated as a biomarker in adjuvant systemic therapy clinical trials for high-risk non-metastatic RCC.

Spatial transcriptomics, the technology of visualizing cellular gene expression landscape in a cells native tissue location, has emerged as a powerful tool that allows us to address scientific questions that were elusive just a few years ago. This technological advance is a decisive jump in the technological evolution that is revolutionizing studies of tissue structure and function in health and disease through the introduction of an entirely new dimension of data, spatial context. Perhaps the organ within the body that relies most on spatial organization is the brain. The central nervous system's complex microenvironmental and spatial architecture is tightly regulated during development, is maintained in health, and is detrimental when disturbed by pathologies. This inherent spatial complexity of the central nervous system makes it an exciting organ to study using spatial transcriptomics for pathologies primarily affecting the brain, of which Glioblastoma is one of the worst. Glioblastoma is a hyper-aggressive, incurable, neoplasm and has been hypothesized to not only integrate into the spatial architecture of the surrounding brain, but also possess an architecture of its own that might be actively remodeling the surrounding brain. In this review we will examine the current landscape of spatial transcriptomics in glioblastoma, outline novel findings emerging from the rising use of spatial transcriptomics, and discuss future directions and ultimate clinical/translational avenues., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. The author(s) declared that MD and AQH are presently editorial board members for frontier journals but neither was involved in any way in the review or editing of this particular manuscript., (Copyright © 2023 Shireman, Cheng, Goel, Garcia, Partha, Quiñones-Hinojosa, Kendziorski and Dey.)

Rhinoviruses infect ciliated airway epithelial cells, and rhinoviruses' nonstructural proteins quickly inhibit and divert cellular processes for viral replication. However, the epithelium can mount a robust innate antiviral immune response. Therefore, we hypothesized that uninfected cells contribute significantly to the antiviral immune response in the airway epithelium. Using single-cell RNA sequencing, we demonstrate that both infected and uninfected cells upregulate antiviral genes (e.g. MX1, IFIT2, IFIH1, and OAS3) with nearly identical kinetics, whereas uninfected non-ciliated cells are the primary source of proinflammatory chemokines. Furthermore, we identified a subset of highly infectable ciliated epithelial cells with minimal interferon responses and determined that interferon responses originate from distinct subsets of ciliated cells with moderate viral replication. These findings suggest that the composition of ciliated airway epithelial cells and coordinated responses of infected and uninfected cells could determine the risk of more severe viral respiratory illnesses in children with asthma, chronic obstructive pulmonary disease, and genetically susceptible individuals., (Copyright © 2023 The Authors. Published by Elsevier Inc. All rights reserved.)

Recent advances in spatially resolved transcriptomics technologies enable both the measurement of genome-wide gene expression profiles and their mapping to spatial locations within a tissue. A first step in spatial transcriptomics data analysis is identifying genes with expression that varies spatially, and robust statistical methods exist to address this challenge. While useful, these methods do not detect spatial changes in the coordinated expression within a group of genes. To this end, we present SpatialCorr, a method for identifying sets of genes with spatially varying correlation structure. Given a collection of gene sets pre-defined by a user, SpatialCorr tests for spatially induced differences in the correlation of each gene set within tissue regions, as well as between and among regions. An application to cutaneous squamous cell carcinoma demonstrates the power of the approach for revealing biological insights not identified using existing methods., Competing Interests: The authors declare no competing interests., (© 2022 The Authors.)

The larynx, trachea, and esophagus share origin and proximity during embryonic development. Clinical and experimental evidence support the existence of neurophysiological, structural, and functional interdependencies before birth. This investigation provides the first comprehensive transcriptional profile of all three organs during embryonic organogenesis, where differential gene expression gradually assembles the identity and complexity of these proximal organs from a shared origin in the anterior foregut. By applying bulk RNA sequencing and gene network analysis of differentially expressed genes (DEGs) within and across developing embryonic mouse larynx, esophagus, and trachea, we identified co-expressed modules of genes enriched for key biological processes. Organ-specific temporal patterns of gene activity corresponding to gene modules within and across shared tissues during embryonic development (E10.5-E18.5) are described, and the laryngeal transcriptome during vocal fold development and maturation from birth to adulthood is characterized in the context of laryngeal organogenesis. The findings of this study provide new insights into interrelated gene sets governing the organogenesis of this tripartite organ system within the aerodigestive tract. They are relevant to multiple families of disorders defined by cardiocraniofacial syndromes., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Wendt, Brown, Lungova, Mohad, Kendziorski and Thibeault.)

Spatial transcriptomics is a powerful and widely used approach for profiling the gene expression landscape across a tissue with emerging applications in molecular medicine and tumor diagnostics. Recent spatial transcriptomics experiments utilize slides containing thousands of spots with spot-specific barcodes that bind RNA. Ideally, unique molecular identifiers (UMIs) at a spot measure spot-specific expression, but this is often not the case in practice due to bleed from nearby spots, an artifact we refer to as spot swapping. To improve the power and precision of downstream analyses in spatial transcriptomics experiments, we propose SpotClean, a probabilistic model that adjusts for spot swapping to provide more accurate estimates of gene-specific UMI counts. SpotClean provides substantial improvements in marker gene analyses and in clustering, especially when tissue regions are not easily separated. As demonstrated in multiple studies of cancer, SpotClean improves tumor versus normal tissue delineation and improves tumor burden estimation thus increasing the potential for clinical and diagnostic applications of spatial transcriptomics technologies., (© 2022. The Author(s).)

Considerable effort has been devoted to refining experimental protocols to reduce levels of technical variability and artifacts in single-cell RNA-sequencing data (scRNA-seq). We here present evidence that equalizing the concentration of cDNA libraries prior to pooling, a step not consistently performed in single-cell experiments, improves gene detection rates, enhances biological signals, and reduces technical artifacts in scRNA-seq data. To evaluate the effect of equalization on various protocols, we developed Scaffold, a simulation framework that models each step of an scRNA-seq experiment. Numerical experiments demonstrate that equalization reduces variation in sequencing depth and gene-specific expression variability. We then performed a set of experiments in vitro with and without the equalization step and found that equalization increases the number of genes that are detected in every cell by 17-31%, improves discovery of biologically relevant genes, and reduces nuisance signals associated with cell cycle. Further support is provided in an analysis of publicly available data., (© The Author(s) 2021. Published by Oxford University Press on behalf of Nucleic Acids Research.)

Motivation: Normalization to remove technical or experimental artifacts is critical in the analysis of single-cell RNA-sequencing experiments, even those for which unique molecular identifiers are available. The majority of methods for normalizing single-cell RNA-sequencing data adjust average expression for library size (LS), allowing the variance and other properties of the gene-specific expression distribution to be non-constant in LS. This often results in reduced power and increased false discoveries in downstream analyses, a problem which is exacerbated by the high proportion of zeros present in most datasets., Results: To address this, we present Dino, a normalization method based on a flexible negative-binomial mixture model of gene expression. As demonstrated in both simulated and case study datasets, by normalizing the entire gene expression distribution, Dino is robust to shallow sequencing, sample heterogeneity and varying zero proportions, leading to improved performance in downstream analyses in a number of settings., Availability and Implementation: The R package, Dino, is available on GitHub at https://github.com/JBrownBiostat/Dino. The Dino package is further archived and freely available on Zenodo at https://doi.org/10.5281/zenodo.4897558., Supplementary Information: Supplementary data are available at Bioinformatics online., (© The Author(s) 2021. Published by Oxford University Press.)

The transcription factor NFATC2 induces β cell proliferation in mouse and human islets. However, the genomic targets that mediate these effects have not been identified. We expressed active forms of Nfatc2 and Nfatc1 in human islets. By integrating changes in gene expression with genomic binding sites for NFATC2, we identified approximately 2200 transcriptional targets of NFATC2. Genes induced by NFATC2 were enriched for transcripts that regulate the cell cycle and for DNA motifs associated with the transcription factor FOXP. Islets from an endocrine-specific Foxp1, Foxp2, and Foxp4 triple-knockout mouse were less responsive to NFATC2-induced β cell proliferation, suggesting the FOXP family works to regulate β cell proliferation in concert with NFATC2. NFATC2 induced β cell proliferation in both mouse and human islets, whereas NFATC1 did so only in human islets. Exploiting this species difference, we identified approximately 250 direct transcriptional targets of NFAT in human islets. This gene set enriches for cell cycle-associated transcripts and includes Nr4a1. Deletion of Nr4a1 reduced the capacity of NFATC2 to induce β cell proliferation, suggesting that much of the effect of NFATC2 occurs through its induction of Nr4a1. Integration of noncoding RNA expression, chromatin accessibility, and NFATC2 binding sites enabled us to identify NFATC2-dependent enhancer loci that mediate β cell proliferation.

Loss of mature β-cell function and identity, or β-cell dedifferentiation, is seen in both type 1 and type 2 diabetes. Two competing models explain β-cell dedifferentiation in diabetes. In the first model, β-cells dedifferentiate in the reverse order of their developmental ontogeny. This model predicts that dedifferentiated β-cells resemble β-cell progenitors. In the second model, β-cell dedifferentiation depends on the type of diabetogenic stress. This model, which we call the "Anna Karenina" model, predicts that in each type of diabetes, β-cells dedifferentiate in their own way, depending on how their mature identity is disrupted by any particular diabetogenic stress. We directly tested the two models using a β-cell-specific lineage-tracing system coupled with RNA sequencing in mice. We constructed a multidimensional map of β-cell transcriptional trajectories during the normal course of β-cell postnatal development and during their dedifferentiation in models of both type 1 diabetes (NOD) and type 2 diabetes (BTBR- Lep ob/ob ). Using this unbiased approach, we show here that despite some similarities between immature and dedifferentiated β-cells, β-cell dedifferentiation in the two mouse models is not a reversal of developmental ontogeny and is different between different types of diabetes., (© 2021 by the American Diabetes Association.)

Background: Colony-stimulating factor 1 (CSF1) expression in the central nervous system (CNS) increases in response to a variety of stimuli, and CSF1 is overexpressed in many CNS diseases. In young adult mice, we previously showed that CSF1 overexpression in the CNS caused the proliferation of IBA1 + microglia without promoting the expression of M2 polarization markers., Methods: Immunohistochemical and molecular analyses were performed to further examine the impact of CSF1 overexpression on glia in both young and aged mice., Results: As CSF1 overexpressing mice age, IBA1 + cell numbers are constrained by a decline in proliferation rate. Compared to controls, there were no differences in expression of the M2 markers ARG1 and MRC1 (CD206) in CSF1 overexpressing mice of any age, indicating that even prolonged exposure to increased CSF1 does not impact M2 polarization status in vivo. Moreover, RNA-sequencing confirmed the lack of increased expression of markers of M2 polarization in microglia exposed to CSF1 overexpression but did reveal changes in expression of other immune-related genes. Although treatment with inhibitors of the CSF1 receptor, CSF1R, has been shown to impact other glia, no increased expression of oligodendrocyte lineage or astrocyte markers was observed in CSF1 overexpressing mice., Conclusions: Our study indicates that microglia are the primary glial lineage impacted by CSF1 overexpression in the CNS and that microglia ultimately adapt to the presence of the CSF1 mitogenic signal., (© 2021. The Author(s).)

On the problem of scoring genes for evidence of changes in the distribution of single-cell expression, we introduce an empirical Bayesian mixture approach and evaluate its operating characteristics in a range of numerical experiments. The proposed approach leverages cell-subtype structure revealed in cluster analysis in order to boost gene-level information on expression changes. Cell clustering informs gene-level analysis through a specially-constructed prior distribution over pairs of multinomial probability vectors; this prior meshes with available model-based tools that score patterns of differential expression over multiple subtypes. We derive an explicit formula for the posterior probability that a gene has the same distribution in two cellular conditions, allowing for a gene-specific mixture over subtypes in each condition. Advantage is gained by the compositional structure of the model not only in which a host of gene-specific mixture components are allowed but also in which the mixing proportions are constrained at the whole cell level. This structure leads to a novel form of information sharing through which the cell-clustering results support gene-level scoring of differential distribution. The result, according to our numerical experiments, is improved sensitivity compared to several standard approaches for detecting distributional expression changes.

Human pluripotent stem cells hold significant promise for regenerative medicine. However, long differentiation protocols and immature characteristics of stem cell-derived cell types remain challenges to the development of many therapeutic applications. In contrast to the slow differentiation of human stem cells in vitro that mirrors a nine-month gestation period, mouse stem cells develop according to a much faster three-week gestation timeline. Here, we tested if co-differentiation with mouse pluripotent stem cells could accelerate the differentiation speed of human embryonic stem cells. Following a six-week RNA-sequencing time course of neural differentiation, we identified 929 human genes that were upregulated earlier and 535 genes that exhibited earlier peaked expression profiles in chimeric cell cultures than in human cell cultures alone. Genes with accelerated upregulation were significantly enriched in Gene Ontology terms associated with neurogenesis, neuron differentiation and maturation, and synapse signaling. Moreover, chimeric mixed samples correlated with in utero human embryonic samples earlier than human cells alone, and acceleration was dose-dependent on human-mouse co-culture ratios. The altered gene expression patterns and developmental rates described in this report have implications for accelerating human stem cell differentiation and the use of interspecies chimeric embryos in developing human organs for transplantation., Competing Interests: The authors have declared that no competing interests exist.

Background: Single-cell RNA-seq (scRNA-seq) enables the profiling of genome-wide gene expression at the single-cell level and in so doing facilitates insight into and information about cellular heterogeneity within a tissue. This is especially important in cancer, where tumor and tumor microenvironment heterogeneity directly impact development, maintenance, and progression of disease. While publicly available scRNA-seq cancer data sets offer unprecedented opportunity to better understand the mechanisms underlying tumor progression, metastasis, drug resistance, and immune evasion, much of the available information has been underutilized, in part, due to the lack of tools available for aggregating and analysing these data., Results: We present CHARacterizing Tumor Subpopulations (CHARTS), a web application for exploring publicly available scRNA-seq cancer data sets in the NCBI's Gene Expression Omnibus. More specifically, CHARTS enables the exploration of individual gene expression, cell type, malignancy-status, differentially expressed genes, and gene set enrichment results in subpopulations of cells across tumors and data sets. Along with the web application, we also make available the backend computational pipeline that was used to produce the analyses that are available for exploration in the web application., Conclusion: CHARTS is an easy to use, comprehensive platform for exploring single-cell subpopulations within tumors across the ever-growing collection of public scRNA-seq cancer data sets. CHARTS is freely available at charts.morgridge.org.

Study of vocal fold (VF) mucosal biology requires essential human vocal fold epithelial cell (hVFE) lines for use in appropriate model systems. We steadily transfected a retroviral construct containing human telomerase reverse transcriptase (hTERT) into primary normal hVFE to establish a continuously replicating hVFE cell line. Immortalized hVFE across passages have cobblestone morphology, express epithelial markers cytokeratin 4, 13 and 14, induced hTERT gene and protein expression, have similar RNAseq profiling, and can continuously grow for more than 8 months. DNA fingerprinting and karyotype analysis demonstrated that immortalized hVFE were consistent with the presence of a single cell line. Validation of the hVFE, in a three-dimensional in vitro VF mucosal construct revealed a multilayered epithelial structure with VF epithelial cell markers. Wound scratch assay revealed higher migration capability of the immortalized hVFE on the surface of collagen-fibronectin and collagen gel containing human vocal fold fibroblasts (hVFF). Collectively, our report demonstrates the first immortalized hVFE from true VFs providing a novel and invaluable tool for the study of epithelial cell-fibroblast interactions that dictate disease and health of this specialized tissue., (© 2021 The Authors. The FASEB Journal published by Wiley Periodicals LLC on behalf of Federation of American Societies for Experimental Biology.)

Background: Alternatively-activated macrophages (AAMs), an anti-inflammatory macrophage subpopulation, have been implicated in the progression of high grade serous ovarian carcinoma (HGSOC). Increased levels of AAMs are correlated with poor HGSOC survival rates, and AAMs increase the attachment and spread of HGSOC cells in vitro. However, the mechanism by which monocytes in the HGSOC tumor microenvironment are differentiated and polarized to AAMs remains unknown., Methods: Using an in vitro co-culture device, we cultured naïve, primary human monocytes with a panel of five HGSOC cell lines over the course of 7 days. An empirical Bayesian statistical method, EBSeq, was used to couple RNA-seq with observed monocyte-derived cell phenotype to explore which HGSOC-derived soluble factors supported differentiation to CD68+ macrophages and subsequent polarization towards CD163+ AAMs. Pathways of interest were interrogated using small molecule inhibitors, neutralizing antibodies, and CRISPR knockout cell lines., Results: HGSOC cell lines displayed a wide range of abilities to generate AAMs from naïve monocytes. Much of this variation appeared to result from differential ability to generate CD68+ macrophages, as most CD68+ cells were also CD163+. Differences in tumor cell potential to generate macrophages was not due to a MCSF-dependent mechanism, nor variance in established pro-AAM factors. TGFα was implicated as a potential signaling molecule produced by tumor cells that could induce macrophage differentiation, which was validated using a CRISPR knockout of TGFA in the OVCAR5 cell line., Conclusions: HGSOC production of TGFα drives monocytes to differentiate into macrophages, representing a central arm of the mechanism by which AAMs are generated in the tumor microenvironment.

As newer single-cell protocols generate increasingly more cells at reduced sequencing depths, the value of a higher read depth may be overlooked. Using data from three different single-cell RNA-seq protocols that lend themselves to having either higher read depth (Smart-seq) or many cells (MARS-seq and 10X), we evaluate their ability to recapitulate biological signals in the context of spatial reconstruction. Overall, we find gene expression profiles after spatial reconstruction analysis are highly reproducible between datasets despite being generated by different protocols and using different computational algorithms. While UMI-based protocols such as 10X and MARS-seq allow for capturing more cells, Smart-seq's higher sensitivity and read-depth allow for analysis of lower expressed genes and isoforms. Additionally, we evaluate trade-offs for each protocol by performing subsampling analyses and find that optimizing the balance between sequencing depth and number of cells within a protocol is necessary for efficient use of resources. Our analysis emphasizes the importance of selecting a protocol based on the biological questions and features of interest., Competing Interests: I have read the journal's policy and the authors of this manuscript have the following competing interests: N.L. is currently employed by Genentech. This does not alter our adherence to PLOS ONE policies on sharing data and materials.

An important challenge in pre-processing data from droplet-based single-cell RNA sequencing protocols is distinguishing barcodes associated with real cells from those binding background reads. Existing methods test barcodes individually and consequently do not leverage the strong cell-to-cell correlation present in most datasets. To improve cell detection, we introduce CB2, a cluster-based approach for distinguishing real cells from background barcodes. As demonstrated in simulated and case study datasets, CB2 has increased power for identifying real cells which allows for the identification of novel subpopulations and improves the precision of downstream analyses.