scholarly journals MAB21L1 modulates gene expression and DNA metabolic processes in the lens placode

2021 ◽  
Author(s):  
Ryuichi Yamada ◽  
Akira Oguri ◽  
Katsunori Fujiki ◽  
Katsuhiko Shirahige ◽  
Yoshikazu Hirate ◽  
...  
Keyword(s):  
Gene Expression ◽  
Single Cell ◽  
Housekeeping Genes ◽  
Nucleotide Metabolism ◽  
Specific Gene ◽  
Metabolic Processes ◽  
Lens Formation ◽  
Lens Placode ◽  
Placode Formation ◽  
Immunohistochemical Analyses

Mutations in human MAB21L1 cause aberrations in lens ectoderm morphogenesis and lead to congenital cerebellar, ocular, craniofacial, and genital (COFG) syndrome. Murine Mab21l1-null mutations cause severe cell-autonomous defects in lens formation leading to microphthalmia, and therefore is used as a mouse model for COFG syndrome. In this study, we investigated the early-onset, single-cell-level phenotypes of murine Mab21l1-null lens ectoderms using electron microscopy (EM) and single-cell RNA sequencing (scRNA-seq). EM and immunohistochemical analyses indicated endoplasmic reticulum stress in the 24- to 26-somite stage in Mab21l1-null lens placodes. scRNA-seq analysis revealed that 131 genes were downregulated and 148 were upregulated in Mab21l1-null lens ectoderms relative to the wild type. We successfully identified 21 lens-specific genes that were downregulated in Mab21l1-null cells including three key genes involved in lens formation: Pitx3, Maf, and Sfrp2. Moreover, gene ontology analysis of the 279 differentially expressed genes indicated enrichment in housekeeping genes associated with DNA/nucleotide metabolism prior to cell death. These findings suggest that MAB21L1 acts as a nuclear factor that modulates not only lens-specific gene expression but also DNA/nucleotide metabolic processes during lens placode formation.

scholarly journals Identification of leukemic and pre-leukemic stem cells by clonal tracking from single-cell transcriptomics

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Lars Velten ◽  
Benjamin A. Story ◽  
Pablo Hernández-Malmierca ◽  
Simon Raffel ◽  
Daniel R. Leonce ◽  
...  
Keyword(s):  
Gene Expression ◽  
Stem Cells ◽  
Cancer Stem Cells ◽  
Single Cell ◽  
Lineage Tracing ◽  
Specific Gene ◽  
Leukemic Stem Cells ◽  
Hematopoietic Stem ◽  
Mutational Status

AbstractCancer stem cells drive disease progression and relapse in many types of cancer. Despite this, a thorough characterization of these cells remains elusive and with it the ability to eradicate cancer at its source. In acute myeloid leukemia (AML), leukemic stem cells (LSCs) underlie mortality but are difficult to isolate due to their low abundance and high similarity to healthy hematopoietic stem cells (HSCs). Here, we demonstrate that LSCs, HSCs, and pre-leukemic stem cells can be identified and molecularly profiled by combining single-cell transcriptomics with lineage tracing using both nuclear and mitochondrial somatic variants. While mutational status discriminates between healthy and cancerous cells, gene expression distinguishes stem cells and progenitor cell populations. Our approach enables the identification of LSC-specific gene expression programs and the characterization of differentiation blocks induced by leukemic mutations. Taken together, we demonstrate the power of single-cell multi-omic approaches in characterizing cancer stem cells.

scholarly journals Enabling out-of-clinic human immunity studies via single-cell profiling of capillary blood

2020 ◽  
Author(s):  
Tatyana Dobreva ◽  
David Brown ◽  
Jong Hwee Park ◽  
Matt Thomson
Keyword(s):  
Gene Expression ◽  
Immune System ◽  
Environmental Factors ◽  
Single Cell ◽  
Immune Cell ◽  
Cell Types ◽  
Capillary Blood ◽  
Specific Gene ◽  
Human Immune ◽  
Over Time

AbstractAn individual’s immune system is driven by both genetic and environmental factors that vary over time. To better understand the temporal and inter-individual variability of gene expression within distinct immune cell types, we developed a platform that leverages multiplexed single-cell sequencing and out-of-clinic capillary blood extraction to enable simplified, cost-effective profiling of the human immune system across people and time at single-cell resolution. Using the platform, we detect widespread differences in cell type-specific gene expression between subjects that are stable over multiple days.SummaryIncreasing evidence implicates the immune system in an overwhelming number of diseases, and distinct cell types play specific roles in their pathogenesis.1,2 Studies of peripheral blood have uncovered a wealth of associations between gene expression, environmental factors, disease risk, and therapeutic efficacy.4 For example, in rheumatoid arthritis, multiple mechanistic paths have been found that lead to disease, and gene expression of specific immune cell types can be used as a predictor of therapeutic non-response.12 Furthermore, vaccines, drugs, and chemotherapy have been shown to yield different efficacy based on time of administration, and such findings have been linked to the time-dependence of gene expression in downstream pathways.21,22,23 However, human immune studies of gene expression between individuals and across time remain limited to a few cell types or time points per subject, constraining our understanding of how networks of heterogeneous cells making up each individual’s immune system respond to adverse events and change over time.

scholarly journals Molecular diversity and lineage commitment of human interneuron progenitors

2021 ◽  
Author(s):  
Dmitry Velmeshev ◽  
Manideep Chavali ◽  
Tomasz Jan Nowakowski ◽  
Mohini Bhade ◽  
Simone Mayer ◽  
...  
Keyword(s):  
Gene Expression ◽  
Single Cell ◽  
Autism Spectrum ◽  
Lineage Commitment ◽  
Proper Function ◽  
Specific Gene ◽  
Specific Cell ◽  
Cortical Interneurons ◽  
Human Specific ◽  
Interneuron Development

Cortical interneurons are indispensable for proper function of neocortical circuits. Changes in interneuron development and function are implicated in human disorders, such as autism spectrum disorder and epilepsy. In order to understand human-specific features of cortical development as well as the origins of neurodevelopmental disorders it is crucial to identify the molecular programs underlying human interneuron development and subtype specification. Recent studies have explored gene expression programs underlying mouse interneuron specification and maturation. We applied single-cell RNA sequencing to samples of second trimester human ganglionic eminence and developing cortex to identify molecularly defined subtypes of human interneuron progenitors and immature interneurons. In addition, we integrated this data from the developing human ganglionic eminences and neocortex with single-nucleus RNA-seq of adult cortical interneurons in order to elucidate dynamic molecular changes associated with commitment of progenitors and immature interneurons to mature interneuron subtypes. By comparing our data with published mouse single-cell genomic data, we discover a number of divergent gene expression programs that distinguish human interneuron progenitors from mouse. Moreover, we find that a number of transcription factors expressed during prenatal development become restricted to adult interneuron subtypes in the human but not the mouse, and these adult interneurons express species- and lineage-specific cell adhesion and synaptic genes. Therefore, our study highlights that despite the similarity of main principles of cortical interneuron development and lineage commitment between mouse and human, human interneuron genesis and subtype specification is guided by species-specific gene programs, contributing to human-specific features of cortical inhibitory interneurons.

scholarly journals Compartment-specific transcriptomics of ozone-exposed murine lungs reveals sex and cell type-associated perturbations relevant to mucoinflammatory lung diseases

2020 ◽  
Author(s):  
Ishita Choudhary ◽  
Thao Vo ◽  
Kshitiz Paudel ◽  
Sonika Patial ◽  
Yogesh Saini
Keyword(s):  
Gene Expression ◽  
Dna Repair ◽  
Cell Division ◽  
Mucous Cell ◽  
Ozone Exposure ◽  
Specific Gene ◽  
Cell Type ◽  
Distinct Cell Type ◽  
Airway Injury ◽  
Immunohistochemical Analyses

Ozone is known to cause lung injury and resident cells of the respiratory tract, i.e., epithelial cells and macrophages, respond to inhaled ozone in a variety of ways that affect their survival, morphology, and functioning. However, a complete understanding of the sex-associated and the cell type-specific gene expression changes in response to ozone exposure is still limited. Through transcriptomics, we aimed to analyze gene expression alterations and associated enrichment of biological pathways enrichment in three distinct cell type-enriched compartments of ozone-exposed murine lungs. We sub-chronically exposed adult males and females to 0.8ppm ozone or filtered air. RNA-Seq was performed on airway epithelium-enriched airways, parenchyma, and purified airspace macrophages. Differential gene expression and biological pathway analyses were performed and supported by cellular and immunohistochemical analyses. While a majority of differentially expressed genes (DEGs) in ozone-exposed versus air-exposed groups were common between both sexes, sex-specific DEGs were also identified in all the three tissue compartments. As compared to ozone-exposed males, ozone-exposed females had significant alterations in gene expression in three compartments. Pathways relevant to cell division and DNA repair were enriched in the ozone-exposed airways indicating ozone-induced airway injury and repair which was further supported by immunohistochemical analyses. In addition to cell division and DNA repair pathways, inflammatory pathways were also enriched within the parenchyma supporting contribution by both epithelial and immune cells. Finally, immune response and cytokine-cytokine receptor interactions were enriched in macrophages, indicating ozone-induced macrophage activation. Lastly, our analyses also revealed ozone-induced upregulation of mucoinflammation- and mucous cell metaplasia-associated pathways.

scholarly journals Single-cell genomic atlas of great ape cerebral organoids uncovers human-specific features of brain development

2019 ◽  
Author(s):  
Sabina Kanton ◽  
Michael James Boyle ◽  
Zhisong He ◽  
Malgorzata Santel ◽  
Anne Weigert ◽  
...  
Keyword(s):  
Gene Expression ◽  
Single Cell ◽  
Expression Patterns ◽  
Adult Brain ◽  
The Other ◽  
Specific Gene ◽  
Great Ape ◽  
Specific Gene Expression ◽  
Gene Regulatory ◽  
Human Specific

ABSTRACTThe human brain has changed dramatically since humans diverged from our closest living relatives, chimpanzees and the other great apes1–5. However, the genetic and developmental programs underlying this divergence are not fully understood6–8. Here, we have analyzed stem cell-derived cerebral organoids using single-cell transcriptomics (scRNA-seq) and accessible chromatin profiling (scATAC-seq) to explore gene regulatory changes that are specific to humans. We first analyze cell composition and reconstruct differentiation trajectories over the entire course of human cerebral organoid development from pluripotency, through neuroectoderm and neuroepithelial stages, followed by divergence into neuronal fates within the dorsal and ventral forebrain, midbrain and hindbrain regions. We find that brain region composition varies in organoids from different iPSC lines, yet regional gene expression patterns are largely reproducible across individuals. We then analyze chimpanzee and macaque cerebral organoids and find that human neuronal development proceeds at a delayed pace relative to the other two primates. Through pseudotemporal alignment of differentiation paths, we identify human-specific gene expression resolved to distinct cell states along progenitor to neuron lineages in the cortex. We find that chromatin accessibility is dynamic during cortex development, and identify instances of accessibility divergence between human and chimpanzee that correlate with human-specific gene expression and genetic change. Finally, we map human-specific expression in adult prefrontal cortex using single-nucleus RNA-seq and find developmental differences that persist into adulthood, as well as cell state-specific changes that occur exclusively in the adult brain. Our data provide a temporal cell atlas of great ape forebrain development, and illuminate dynamic gene regulatory features that are unique to humans.

scholarly journals Exploring and analysing single cell multi-omics data with VDJView

2019 ◽  
Author(s):  
Jerome Samir ◽  
Simone Rizzetto ◽  
Money Gupta ◽  
Fabio Luciani
Keyword(s):  
Gene Expression ◽  
T Cells ◽  
B Cells ◽  
Hypothesis Testing ◽  
Single Cell ◽  
Single Cells ◽  
Cellular Heterogeneity ◽  
Specific Gene ◽  
T And B Cells ◽  
Gene Signatures

Abstract Background Single cell RNA sequencing provides unprecedented opportunity to simultaneously explore the transcriptomic and immune receptor diversity of T and B cells. However, there are limited tools available that simultaneously analyse large multi-omics datasets integrated with metadata such as patient and clinical information.Results We developed VDJView, which permits the simultaneous or independent analysis and visualisation of gene expression, immune receptors, and clinical metadata of both T and B cells. This tool is implemented as an easy-to-use R shiny web-application, which integrates numerous gene expression and TCR analysis tools, and accepts data from plate-based sorted or high-throughput single cell platforms. We utilised VDJView to analyse several 10X scRNA-seq datasets, including a recent dataset of 150,000 CD8+ T cells with available gene expression, TCR sequences, quantification of 15 surface proteins, and 44 antigen specificities (across viruses, cancer, and self-antigens). We performed quality control, filtering of tetramer non-specific cells, clustering, random sampling and hypothesis testing to discover antigen specific gene signatures which were associated with immune cell differentiation states and clonal expansion across the pathogen specific T cells. We also analysed 563 single cells (plate-based sorted) obtained from 11 subjects, revealing clonally expanded T and B cells across primary cancer tissues and metastatic lymph-node. These immune cells clustered with distinct gene signatures according to the breast cancer molecular subtype. VDJView has been tested in lab meetings and peer-to-peer discussions, showing effective data generation and discussion without the need to consult bioinformaticians.Conclusions VDJView enables researchers without profound bioinformatics skills to analyse immune scRNA-seq data, integrating and visualising this with clonality and metadata profiles, thus accelerating the process of hypothesis testing, data interpretation and discovery of cellular heterogeneity. VDJView is freely available at https://bitbucket.org/kirbyvisp/vdjview .

scholarly journals dynDeepDRIM: a dynamic deep learning model to infer direct regulatory interactions using single cell time-course gene expression data

2021 ◽  
Author(s):  
Yu Xu ◽  
Jiaxing Chen ◽  
Aiping Lyu ◽  
William K Cheung ◽  
Lu Zhang
Keyword(s):  
Gene Expression ◽  
Single Cell ◽  
Gene Expression Data ◽  
Time Course ◽  
Target Genes ◽  
Neighborhood Context ◽  
Specific Gene ◽  
Expression Data ◽  
Regulatory Interactions ◽  
Gene Functions

Time-course single-cell RNA sequencing (scRNA-seq) data have been widely applied to reconstruct the cell-type-specific gene regulatory networks by exploring the dynamic changes of gene expression between transcription factors (TFs) and their target genes. The existing algorithms were commonly designed to analyze bulk gene expression data and could not deal with the dropouts and cell heterogeneity in scRNA-seq data. In this paper, we developed dynDeepDRIM that represents gene pair joint expression as images and considers the neighborhood context to eliminate the transitive interactions. dynDeepDRIM integrated the primary image, neighbor images with time-course into a four-dimensional tensor and trained a convolutional neural network to predict the direct regulatory interactions between TFs and genes. We evaluated the performance of dynDeepDRIM on five time-course gene expression datasets. dynDeepDRIM outperformed the state-of-the-art methods for predicting TF-gene direct interactions and gene functions. We also observed gene functions could be better performed if more neighbor images were involved.

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