Mouse Cell Types Research Articles

An integrative view of the regulatory and transcriptional landscapes in mouse hematopoiesis.

Thousands of epigenomic data sets have been generated in the past decade, but it is difficult for researchers to effectively use all the data relevant to their projects. Systematic integrative analysis can help meet this need, and the VISION project was established for validated systematic integration of epigenomic data in hematopoiesis. Here, we systematically integrated extensive data recording epigenetic features and transcriptomes from many sources, including individual laboratories and consortia, to produce a comprehensive view of the regulatory landscape of differentiating hematopoietic cell types in mouse. By using IDEAS as our integrative and discriminative epigenome annotation system, we identified and assigned epigenetic states simultaneously along chromosomes and across cell types, precisely and comprehensively. Combining nuclease accessibility and epigenetic states produced a set of more than 200,000 candidate cis-regulatory elements (cCREs) that efficiently capture enhancers and promoters. The transitions in epigenetic states of these cCREs across cell types provided insights into mechanisms of regulation, including decreases in numbers of active cCREs during differentiation of most lineages, transitions from poised to active or inactive states, and shifts in nuclease accessibility of CTCF-bound elements. Regression modeling of epigenetic states at cCREs and gene expression produced a versatile resource to improve selection of cCREs potentially regulating target genes. These resources are available from our VISION website to aid research in genomics and hematopoiesis.

Candidate silencer elements for the human and mouse genomes

The study of gene regulation is dominated by a focus on the control of gene activation or increase in the level of expression. Just as critical is the process of gene repression or silencing. Chromatin signatures have identified enhancers, however, genome-wide identification of silencers by computational or experimental approaches are lacking. Here, we first define uncharacterized cis-regulatory elements likely containing silencers and find that 41.5% of ~7500 tested elements show silencer activity using massively parallel reporter assay (MPRA). We trained a support vector machine classifier based on MPRA data to predict candidate silencers in over 100 human and mouse cell or tissue types. The predicted candidate silencers exhibit characteristics expected of silencers. Leveraging promoter-capture HiC data, we find that over 50% of silencers are interacting with gene promoters having very low to no expression. Our results suggest a general strategy for genome-wide identification and characterization of silencer elements.

Cellular deconvolution of GTEx tissues powers discovery of disease and cell-type associated regulatory variants

The Genotype-Tissue Expression (GTEx) resource has provided insights into the regulatory impact of genetic variation on gene expression across human tissues; however, thus far has not considered how variation acts at the resolution of the different cell types. Here, using gene expression signatures obtained from mouse cell types, we deconvolute bulk RNA-seq samples from 28 GTEx tissues to quantify cellular composition, which reveals striking heterogeneity across these samples. Conducting eQTL analyses for GTEx liver and skin samples using cell composition estimates as interaction terms, we identify thousands of genetic associations that are cell-type-associated. The skin cell-type associated eQTLs colocalize with skin diseases, indicating that variants which influence gene expression in distinct skin cell types play important roles in traits and disease. Our study provides a framework to estimate the cellular composition of GTEx tissues enabling the functional characterization of human genetic variation that impacts gene expression in cell-type-specific manners.

Differences in Potassium Channel Composition Underlie Distinct Action Potential Kinetics in Transcriptomically Identified Neocortical Mouse Cell Types

Neocortical neuronal cell types differ in their intrinsic electrical properties, leading to input - output characteristics tuned to their function. To understand how gene expression in a given cell type gives rise to these electrical characteristics, we established a data generation pipeline using the ‘Patch-seq’ technique - a powerful approach to characterize the electrophysiological, morphological and transcriptomic features from single neurons. We first capture the neuron's passive and active electrical properties in current clamp using a standard set of square pulse, ramp, and noise stimuli. We then extract the cellular contents for downstream RNA-seq processing - ultimately mapping the cell to its transcriptomic type. To narrow the gap between gene expression and electrical behavior, we also characterize macroscopic ion channel properties using the outside-out ‘nucleated’ voltage clamp configuration. Here we use voltage clamp protocols designed to isolate and characterize the fast and slow inactivating potassium ion channel currents. In the mouse primary visual cortex, we find differences in potassium channel current density amplitude and kinetics in cells representing the major inhibitory transcriptomic cell subclasses - Pvalb, Sst, VIP, and Lamp5. Within a major subclass, we find that some specific transcriptomic types can be distinguished by their electrophysiological properties, while others overlap. Interestingly, properties of the macroscopic potassium current correlate with action potential kinetics and the expression of certain ion channels. This richer dataset drives both perturbation experiments to establish a causal link between ion channel currents and active properties as well as a refined taxonomy that incorporates active ion channel currents to further discriminate between cell types.

Meta-Analysis of Human and Mouse Biliary Epithelial Cell Gene Profiles.

Background: Chronic liver diseases are frequently accompanied with activation of biliary epithelial cells (BECs) that can differentiate into hepatocytes and cholangiocytes, providing an endogenous back-up system. Functional studies on BECs often rely on isolations of an BEC cell population from healthy and/or injured livers. However, a consensus on the characterization of these cells has not yet been reached. The aim of this study was to compare the publicly available transcriptome profiles of human and mouse BECs and to establish gene signatures that can identify quiescent and activated human and mouse BECs. Methods: We used publicly available transcriptome data sets of human and mouse BECs, compared their profiles and analyzed co-expressed genes and pathways. By merging both human and mouse BEC-enriched genes, we obtained a quiescent and activation gene signature and tested them on BEC-like cells and different liver diseases using gene set enrichment analysis. In addition, we identified several genes from both gene signatures to identify BECs in a scRNA sequencing data set. Results: Comparison of mouse BEC transcriptome data sets showed that the isolation method and array platform strongly influences their general profile, still most populations are highly enriched in most genes currently associated with BECs. Pathway analysis on human and mouse BECs revealed the KRAS signaling as a new potential pathway in BEC activation. We established a quiescent and activated BEC gene signature that can be used to identify BEC-like cells and detect BEC enrichment in alcoholic hepatitis, non-alcoholic steatohepatitis (NASH) and peribiliary sclerotic livers. Finally, we identified a gene set that can distinguish BECs from other liver cells in mouse and human scRNAseq data. Conclusions: Through a meta-analysis of human and mouse BEC gene profiles we identified new potential pathways in BEC activation and created unique gene signatures for quiescent and activated BECs. These signatures and pathways will help in the further characterization of this progenitor cell type in mouse and human liver development and disease.

ImmGen report: sexual dimorphism in the immune system transcriptome

Sexual dimorphism in the mammalian immune system is manifested as more frequent and severe infectious diseases in males and, on the other hand, higher rates of autoimmune disease in females, yet insights underlying those differences are still lacking. Here we characterize sex differences in the immune system by RNA and ATAC sequence profiling of untreated and interferon-induced immune cell types in male and female mice. We detect very few differentially expressed genes between male and female immune cells except in macrophages from three different tissues. Accordingly, very few genomic regions display differences in accessibility between sexes. Transcriptional sexual dimorphism in macrophages is mediated by genes of innate immune pathways, and increases after interferon stimulation. Thus, the stronger immune response of females may be due to more activated innate immune pathways prior to pathogen invasion.

Cell-type dependent enhancer binding of the EWS/ATF1 fusion gene in clear cell sarcomas

Clear cell sarcoma (CCS) is a rare soft tissue sarcoma caused by the EWS/ATF1 fusion gene. Here, we established induced pluripotent stem cells (iPSCs) from EWS/ATF1-controllable murine CCS cells harboring sarcoma-associated genetic abnormalities. Sarcoma-iPSC mice develop secondary sarcomas immediately after EWS/ATF1 induction, but only in soft tissue. EWS/ATF1 expression induces oncogene-induced senescence in most cell types in sarcoma-iPSC mice but prevents it in sarcoma cells. We identify Tppp3-expressing cells in peripheral nerves as a cell-of-origin for these sarcomas. We show cell type-specific recruitment of EWS/ATF1 to enhancer regions in CCS cells. Finally, epigenetic silencing at these enhancers induces senescence and inhibits CCS cell growth through altered EWS/ATF1 binding. Together, we propose that distinct responses to premature senescence are the basis for the cell type-specificity of cancer development.

Multi-Objective Optimized Fuzzy Clustering for Detecting Cell Clusters from Single-Cell Expression Profiles.

Rapid advance in single-cell RNA sequencing (scRNA-seq) allows measurement of the expression of genes at single-cell resolution in complex disease or tissue. While many methods have been developed to detect cell clusters from the scRNA-seq data, this task currently remains a main challenge. We proposed a multi-objective optimization-based fuzzy clustering approach for detecting cell clusters from scRNA-seq data. First, we conducted initial filtering and SCnorm normalization. We considered various case studies by selecting different cluster numbers ( = 2 to a user-defined number), and applied fuzzy c-means clustering algorithm individually. From each case, we evaluated the scores of four cluster validity index measures, Partition Entropy (), Partition Coefficient (), Modified Partition Coefficient (), and Fuzzy Silhouette Index (). Next, we set the first measure as minimization objective (↓) and the remaining three as maximization objectives (↑), and then applied a multi-objective decision-making technique, TOPSIS, to identify the best optimal solution. The best optimal solution (case study) that had the highest TOPSIS score was selected as the final optimal clustering. Finally, we obtained differentially expressed genes (DEGs) using Limma through the comparison of expression of the samples between each resultant cluster and the remaining clusters. We applied our approach to a scRNA-seq dataset for the rare intestinal cell type in mice [GEO ID: GSE62270, 23,630 features (genes) and 288 cells]. The optimal cluster result (TOPSIS optimal score= 0.858) comprised two clusters, one with 115 cells and the other 91 cells. The evaluated scores of the four cluster validity indices, , , , and for the optimized fuzzy clustering were 0.482, 0.578, 0.607, and 0.215, respectively. The Limma analysis identified 1240 DEGs (cluster 1 vs. cluster 2). The top ten gene markers were Rps21, Slc5a1, Crip1, Rpl15, Rpl3, Rpl27a, Khk, Rps3a1, Aldob and Rps17. In this list, Khk (encoding ketohexokinase) is a novel marker for the rare intestinal cell type. In summary, this method is useful to detect cell clusters from scRNA-seq data.

VirtualCytometry: a webserver for evaluating immune cell differentiation using single-cell RNA sequencing data.

The immune system has diverse types of cells that are differentiated or activated via various signaling pathways and transcriptional regulation upon challenging conditions. Immunophenotyping by flow and mass cytometry are the major approaches for identifying key signaling molecules and transcription factors directing the transition between the functional states of immune cells. However, few proteins can be evaluated by flow cytometry in a single experiment, preventing researchers from obtaining a comprehensive picture of the molecular programs involved in immune cell differentiation. Recent advances in single-cell RNA sequencing (scRNA-seq) have enabled unbiased genome-wide quantification of gene expression in individual cells on a large scale, providing a new and versatile analytical pipeline for studying immune cell differentiation. We present VirtualCytometry, a web-based computational pipeline for evaluating immune cell differentiation by exploiting cell-to-cell variation in gene expression with scRNA-seq data. Differentiating cells often show a continuous spectrum of cellular states rather than distinct populations. VirtualCytometry enables the identification of cellular subsets for different functional states of differentiation based on the expression of marker genes. Case studies have highlighted the usefulness of this subset analysis strategy for discovering signaling molecules and transcription factors for human T-cell exhaustion, a state of T-cell dysfunction, in tumor and mouse dendritic cells activated by pathogens. With more than 226 scRNA-seq datasets precompiled from public repositories covering diverse mouse and human immune cell types in normal and disease tissues, VirtualCytometry is a useful resource for the molecular dissection of immune cell differentiation. www.grnpedia.org/cytometry.

ACTINN: automated identification of cell types in single cell RNA sequencing.

Cell type identification is one of the major goals in single cell RNA sequencing (scRNA-seq). Current methods for assigning cell types typically involve the use of unsupervised clustering, the identification of signature genes in each cluster, followed by a manual lookup of these genes in the literature and databases to assign cell types. However, there are several limitations associated with these approaches, such as unwanted sources of variation that influence clustering and a lack of canonical markers for certain cell types. Here, we present ACTINN (Automated Cell Type Identification using Neural Networks), which employs a neural network with three hidden layers, trains on datasets with predefined cell types and predicts cell types for other datasets based on the trained parameters. We trained the neural network on a mouse cell type atlas (Tabula Muris Atlas) and a human immune cell dataset, and used it to predict cell types for mouse leukocytes, human PBMCs and human T cell sub types. The results showed that our neural network is fast and accurate, and should therefore be a useful tool to complement existing scRNA-seq pipelines. The codes and datasets are available at https://figshare.com/articles/ACTINN/8967116. Tutorial is available at https://github.com/mafeiyang/ACTINN. All codes are implemented in python. Supplementary data are available at Bioinformatics online.

Ubiquitin-specific protease 26 (USP26) is not essential for mouse gametogenesis and fertility.

Ubiquitin-specific protease 26 (USP26) is a deubiquitylating enzyme belonging to the USPs family with a transcription pattern restricted to the male germline. Since protein ubiquitination is an essential regulatory mechanism during meiosis, many efforts have been focused on elucidating the function of USP26 and its relationship with fertility. During the last decade, several studies have reported the presence of different polymorphisms in USP26 in patients with non-obstructive azoospermia (NOA) or severe oligozoospermia suggesting that this gene may be associated with human infertility. However, other studies have revealed the presence of these and novel polymorphisms, including nonsense mutations, in men with normal spermatogenesis as well. Thus, the results remain controversial and its function is unknown. In the present study, we describe the in vivo functional analysis of mice lacking USP26. The phenotypic analysis of two different Usp26-null mutants showed no overt-phenotype with both males and females being fertile. Cytological analysis of spermatocytes showed no defects in synapsis, chromosome dynamics, DNA repair, or recombination. Histopathological analysis revealed a normal distribution and number of the different cell types in both male and female mice. Finally, normal counts were observed in fertility assessments. These results represent the first in vivo evidence showing that USP26 is not essential for mouse gametogenesis.

RNA-seq of Isolated Chromaffin Cells Highlights the Role of Sex-Linked and Imprinted Genes in Adrenal Medulla Development

Adrenal chromaffin cells and sympathetic neurons synthesize and release catecholamines, and both cell types are derived from neural crest precursors. However, they have different developmental histories, with sympathetic neurons derived directly from neural crest precursors while adrenal chromaffin cells arise from neural crest-derived cells that express Schwann cell markers. We have sought to identify the genes, including imprinted genes, which regulate the development of the two cell types in mice. We developed a method of separating the two cell types as early as E12.5, using differences in expression of enhanced yellow fluorescent protein driven from the tyrosine hydroxylase gene, and then used RNA sequencing to confirm the characteristic molecular signatures of the two cell types. We identified genes differentially expressed by adrenal chromaffin cells and sympathetic neurons. Deletion of a gene highly expressed by adrenal chromaffin cells, NIK-related kinase, a gene on the X-chromosome, results in reduced expression of adrenaline-synthesizing enzyme, phenyl-N-methyl transferase, by adrenal chromaffin cells and changes in cell cycle dynamics. Finally, many imprinted genes are up-regulated in chromaffin cells and may play key roles in their development.

Cells of Origin for Prostate Cancer.

Comprehensive knowledge of the normal prostate epithelial lineage hierarchy is a prerequisite to investigate the identity of the cells of origin for prostate cancer. The basal and luminal cells constitute most of the prostate epithelium and have been the major focuses of the study on the cells of origin for prostate cancer. Much progress has been made during the past few decades, mainly using mouse models, to understand the inter-lineage relationship and intra-lineage heterogeneity in adults as well as the lineage plasticity during conditions of stress. These studies have concluded that the adult mouse prostate basal and luminal cells are largely independently sustained under physiological conditions, but both types of cells possess the capacity for bipotent differentiation under stress or artificial experimental conditions. However, the existence or the identity of the putative progenitors within each lineage warrants further investigation. Whether the human prostate lineage hierarchy is completely the same as that of the mouse remains uncertain. Experiments from independent groups have demonstrated that both types of cells in mice and humans can serve as targets for transformation. But controversies remain whether the disease from distinct cells of origin display different clinical behaviors. Further investigation of the intra-lineage heterogeneity will provide new insights into this issue. Understanding the identity of the cells of origin for prostate cancer will help identify novel prognostic markers for early detection of aggressive prostate cancers, provide insights into the therapeutic vulnerability of these tumors, and inspire novel therapeutic strategies.

ScMCA: A Tool to Define Mouse Cell Types Based on Single-Cell Digital Expression.

For decades, people have been trying to define cell type with the combination of expressed genes. The choice of the limited number of genes for the classification limits the precision of this system. Here, we build a "single-cell Mouse Cell Atlas (scMCA) analysis" pipeline based on scRNA-seq datasets covering all mouse cell types. We build the scMCA reference and then use the tool "scMCA" to match single-cell digital expression to its closest cell type.

Putative contributions of the sex chromosome proteins SOX3 and SRY to neurodevelopmental disorders.

The male‐biased prevalence of certain neurodevelopmental disorders and the sex‐biased outcomes associated with stress exposure during gestation have been previously described. Here, we hypothesized that genes distinctively targeted by only one or both homologous proteins highly conserved across therian mammals, SOX3 and SRY, could induce sexual adaptive changes that result in a differential risk for neurodevelopmental disorders. ChIP‐seq/chip data showed that SOX3/SRY gene targets were expressed in different brain cell types in mice. We used orthologous human genes in rodent genomes to extend the number of SOX3/SRY set (1,721). These genes were later found to be enriched in five modules of coexpressed genes during the early and mid‐gestation periods (FDR < 0.05), independent of sexual hormones. Genes with differential expression (24, p < 0.0001) and methylation (40, p < 0.047) between sexes were overrepresented in this set. Exclusive SOX3 or SRY target genes were more associated with the late gestational and postnatal periods. Using autism as a model sex‐biased disorder, the SOX3/SRY set was enriched in autism gene databases (FDR ≤ 0.05), and there were more de novo variations from the male autism spectrum disorder (ASD) samples under the SRY peaks compared to the random peaks (p < 0.024). The comparison of coexpressed networks of SOX3/SRY target genes between male autism and control samples revealed low preservation in gene modules related to stress response (99 genes) and neurogenesis (78 genes). This study provides evidence that while SOX3 is a regulatory mechanism for both sexes, the male‐exclusive SRY also plays a role in gene regulation, suggesting a potential mechanism for sex bias in ASD.

In vitro Methods to Cultivate Spiral Ganglion Cells, and Purification of Cellular Subtypes for Induced Neuronal Reprogramming.

Hearing loss can develop as a consequence of primary auditory neuron degeneration. These neurons are present within the spiral ganglion of the inner ear and co-exist with glial cells that assist in neuronal maintenance and function. There are limited interventions for individuals with hearing impairment, hence novel biological solutions must be explored. Regenerative strategies can benefit from in vitro methods to examine the long-term culture of purified cell populations. The culturing of neuronal, glial, and non-neuronal, non-glial cell types in both neonatal and adult mice is presented along with the whole-organ explant culture of the spiral ganglion. High yields of spiral ganglion glial and non-glial cells were cultured from both neonatal and adult mice. Dissociated spiral ganglion cells from Sox2-EGFP mice were sorted based on EGFP expression using fluorescence activated cell sorting. The EGFP+ fraction included purified glial populations, whereas the EGFP- fraction contained non-glial cells. Purified glial cells could be reprogrammed into induced neurons displaying neuronal markers and morphology at a higher efficiency than non-glial cells. Previous studies have only allowed for the short-term culturing of spiral ganglion cell populations and have placed emphasis on neonatal cells. There has also been a lack of methods able to cultivate pure cell populations. Here, the coupling of transgenic mouse lines, fluorescence activated cell sorting and advanced culture conditions allow cultivation and characterization of neuronal, glial and non-neuronal, non-glial cells from the spiral ganglion. These techniques are used to demonstrate that different spiral ganglion cell subtypes (glial vs. non-glial) display different competencies for direct neuronal reprogramming.

Ensembl 2019.

The Ensembl project (https://www.ensembl.org) makes key genomic data sets available to the entire scientific community without restrictions. Ensembl seeks to be a fundamental resource driving scientific progress by creating, maintaining and updating reference genome annotation and comparative genomics resources. This year we describe our new and expanded gene, variant and comparative annotation capabilities, which led to a 50% increase in the number of vertebrate genomes we support. We have also doubled the number of available human variants and added regulatory regions for many mouse cell types and developmental stages. Our data sets and tools are available via the Ensembl website as well as a through a RESTful webservice, Perl application programming interface and as data files for download.

Revealing the Critical Regulators of Cell Identity in the Mouse Cell Atlas

SUMMARYRecent progress in single-cell technologies has enabled the identification of all major cell types in mouse. However, for most cell types, the regulatory mechanism underlying their identity remains poorly understood. By computational analysis of the recently published mouse cell atlas data, we have identified 202 regulons whose activities are highly variable across different cell types, and more importantly, predicted a small set of essential regulators for each major cell type in mouse. Systematic validation by automated literature and data mining provides strong additional support for our predictions. Thus, these predictions serve as a valuable resource that would be useful for the broad biological community. Finally, we have built a user-friendly, interactive web portal to enable users to navigate this mouse cell network atlas.

From Cellular Diversity to the Roots of Variability

From Cellular Diversity to the Roots of Variability

The Mammalian Spermatogenesis Single-Cell Transcriptome, from Spermatogonial Stem Cells to Spermatids

Spermatogenesis is a complex and dynamic cellular differentiation process critical to male reproductionand sustained by spermatogonial stem cells (SSCs). Although patterns of gene expression have been described for aggregates of certain spermatogenic cell types, the full continuum of gene expression patterns underlying ongoing spermatogenesis in steady state was previously unclear. Here, we catalog single-cell transcriptomes for >62,000 individual spermatogenic cells from immature (postnatal day 6) and adult male mice and adult men. This allowed us to resolve SSC and progenitor spermatogonia, elucidate the full range of gene expression changes during male meiosis and spermiogenesis, and derive unique gene expression signatures for multiple mouse and human spermatogenic cell types and/or subtypes. These transcriptome datasets provide an information-rich resource for studies of SSCs, male meiosis, testicular cancer, male infertility, or contraceptive development, as well as a gene expression roadmap to be emulated in efforts to achieve spermatogenesis invitro.