Conserved cell types with divergent features between human and mouse cortex

AbstractElucidating the cellular architecture of the human neocortex is central to understanding our cognitive abilities and susceptibility to disease. Here we applied single nucleus RNA-sequencing to perform a comprehensive analysis of cell types in the middle temporal gyrus of human cerebral cortex. We identify a highly diverse set of excitatory and inhibitory neuronal types that are mostly sparse, with excitatory types being less layer-restricted than expected. Comparison to a similar mouse cortex single cell RNA-sequencing dataset revealed a surprisingly well-conserved cellular architecture that enables matching of homologous types and predictions of human cell type properties. Despite this general conservation, we also find extensive differences between homologous human and mouse cell types, including dramatic alterations in proportions, laminar distributions, gene expression, and morphology. These species-specific features emphasize the importance of directly studying human brain.

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Single Cell, Single Nucleus and Spatial RNA Sequencing of the Human Liver Identifies Hepatic Stellate Cell and Cholangiocyte Heterogeneity

10.1101/2021.03.27.436882 ◽

2021 ◽

Author(s):

Tallulah S Andrews ◽

Jawairia Atif ◽

Jeff C Liu ◽

Catia T Perciani ◽

Xue-Zhong Ma ◽

...

Keyword(s):

Single Cell ◽

Rna Sequencing ◽

Human Liver ◽

Stellate Cell ◽

Parenchymal Cell ◽

Cell Types ◽

Cell Populations ◽

Healthy Human ◽

Single Nucleus

The critical functions of the human liver are coordinated through the interactions of hepatic parenchymal and non-parenchymal cells. Recent advances in single cell transcriptional approaches have enabled an examination of the human liver with unprecedented resolution. However, dissociation related cell perturbation can limit the ability to fully capture the human liver's parenchymal cell fraction, which limits the ability to comprehensively profile this organ. Here, we report the transcriptional landscape of 73,295 cells from the human liver using matched single-cell RNA sequencing (scRNA-seq) and single-nucleus RNA sequencing (snRNA-seq). The addition of snRNA-seq enabled the characterization of interzonal hepatocytes at single-cell resolution, revealed the presence of rare subtypes of hepatic stellate cells previously only seen in disease, and detection of cholangiocyte progenitors that had only been observed during in vitro differentiation experiments. However, T and B lymphocytes and NK cells were only distinguishable using scRNA-seq, highlighting the importance of applying both technologies to obtain a complete map of tissue-resident cell-types. We validated the distinct spatial distribution of the hepatocyte, cholangiocyte and stellate cell populations by an independent spatial transcriptomics dataset and immunohistochemistry. Our study provides a systematic comparison of the transcriptomes captured by scRNA-seq and snRNA-seq and delivers a high-resolution map of the parenchymal cell populations in the healthy human liver.

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EPCO-07. HYBRID NEURO-GLIAL CELLULAR ARCHITECTURE IN HIGH-GRADE GLIOMA DRIVEN BY H3-G34R MUTATION

Neuro-Oncology ◽

10.1093/neuonc/noab196.006 ◽

2021 ◽

Vol 23 (Supplement_6) ◽

pp. vi2-vi2

Author(s):

Julie Laffy ◽

Masashi Nomura ◽

Chen He ◽

Lillian Bussema ◽

Michal Slyper ◽

...

Keyword(s):

Young Adults ◽

Rna Sequencing ◽

Developmental Trajectories ◽

High Grade Glioma ◽

Cerebral Hemispheres ◽

High Grade ◽

Malignant Cells ◽

Aberrant Expression ◽

Cellular Architecture ◽

Single Nucleus

Abstract High-grade gliomas (HGG) with histone H3.3 G34R mutation are rare intractable tumours in the cerebral hemispheres that preferentially affect adolescents and young adults, but have unknown mechanisms of neuroanatomical specificity and tumourigenesis. Here, we performed single-nucleus RNA-sequencing of twenty patient samples, encompassing twelve tumours with G34R mutation and eight H3.3 wildtype HGGs, age- and location-matched. Both classes of HGG were heterogeneous, with malignant cells in multiple states, recapitulating neural and glial developmental trajectories. G34R HGG is distinguished by lack of malignant cells in the oligodendroglial lineage, and aberrant expression of neuronal programs superimposed over cellular states, resulting in hybrid glio-neuronal malignant programs. Singe-cell barcoding supports plasticity between cellular states in HGG with multiple possible transitions. CRISPR-correction of G34R in HGG models followed by scRNA-seq supports that the G34R mutation directly drives these aberrant programs. Our study provides a framework for studying the origin and tumourigenesis of paediatric gliomas.

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Single-nucleus RNA-seq identifies transcriptional heterogeneity in multinucleated skeletal myofibers

Nature Communications ◽

10.1038/s41467-020-20063-w ◽

2020 ◽

Vol 11 (1) ◽

Author(s):

Michael J. Petrany ◽

Casey O. Swoboda ◽

Chengyi Sun ◽

Kashish Chetal ◽

Xiaoting Chen ◽

...

Keyword(s):

Skeletal Muscle ◽

Neuromuscular Junction ◽

Postnatal Development ◽

Rna Sequencing ◽

Cell Types ◽

Myotendinous Junction ◽

Rna Seq ◽

Muscle Biology ◽

Single Nucleus ◽

Aging Muscle

AbstractWhile the majority of cells contain a single nucleus, cell types such as trophoblasts, osteoclasts, and skeletal myofibers require multinucleation. One advantage of multinucleation can be the assignment of distinct functions to different nuclei, but comprehensive interrogation of transcriptional heterogeneity within multinucleated tissues has been challenging due to the presence of a shared cytoplasm. Here, we utilized single-nucleus RNA-sequencing (snRNA-seq) to determine the extent of transcriptional diversity within multinucleated skeletal myofibers. Nuclei from mouse skeletal muscle were profiled across the lifespan, which revealed the presence of distinct myonuclear populations emerging in postnatal development as well as aging muscle. Our datasets also provided a platform for discovery of genes associated with rare specialized regions of the muscle cell, including markers of the myotendinous junction and functionally validated factors expressed at the neuromuscular junction. These findings reveal that myonuclei within syncytial muscle fibers possess distinct transcriptional profiles that regulate muscle biology.

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Single-nucleus RNA sequencing of mouse auditory cortex reveals critical period triggers and brakes

Proceedings of the National Academy of Sciences ◽

10.1073/pnas.1920433117 ◽

2020 ◽

Vol 117 (21) ◽

pp. 11744-11752 ◽

Cited By ~ 6

Author(s):

Brian T. Kalish ◽

Tania R. Barkat ◽

Erin E. Diel ◽

Elizabeth J. Zhang ◽

Michael E. Greenberg ◽

...

Keyword(s):

Gene Expression ◽

Auditory Cortex ◽

Rna Sequencing ◽

Critical Period ◽

Neural Circuit ◽

Developmental Process ◽

Brain Plasticity ◽

Cell Types ◽

Altered Expression ◽

Single Nucleus

Auditory experience drives neural circuit refinement during windows of heightened brain plasticity, but little is known about the genetic regulation of this developmental process. The primary auditory cortex (A1) of mice exhibits a critical period for thalamocortical connectivity between postnatal days P12 and P15, during which tone exposure alters the tonotopic topography of A1. We hypothesized that a coordinated, multicellular transcriptional program governs this window for patterning of the auditory cortex. To generate a robust multicellular map of gene expression, we performed droplet-based, single-nucleus RNA sequencing (snRNA-seq) of A1 across three developmental time points (P10, P15, and P20) spanning the tonotopic critical period. We also tone-reared mice (7 kHz pips) during the 3-d critical period and collected A1 at P15 and P20. We identified and profiled both neuronal (glutamatergic and GABAergic) and nonneuronal (oligodendrocytes, microglia, astrocytes, and endothelial) cell types. By comparing normal- and tone-reared mice, we found hundreds of genes across cell types showing altered expression as a result of sensory manipulation during the critical period. Functional voltage-sensitive dye imaging confirmed GABA circuit function determines critical period onset, while Nogo receptor signaling is required for its closure. We further uncovered previously unknown effects of developmental tone exposure on trajectories of gene expression in interneurons, as well as candidate genes that might execute tonotopic plasticity. Our single-nucleus transcriptomic resource of developing auditory cortex is thus a powerful discovery platform with which to identify mediators of tonotopic plasticity.

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

Bioinformatics ◽

10.1093/bioinformatics/btz592 ◽

2019 ◽

Cited By ~ 7

Author(s):

Feiyang Ma ◽

Matteo Pellegrini

Keyword(s):

Neural Network ◽

Single Cell ◽

Rna Sequencing ◽

Immune Cell ◽

Cell Types ◽

Mouse Cell ◽

Supplementary Information ◽

Cell Type ◽

Human T Cell ◽

Single Cell Rna Sequencing

Abstract Motivation 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. Results 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. Availability and implementation 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 information Supplementary data are available at Bioinformatics online.

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LEVELS OF IL-10 ALTER NF-KAPPA B ACTIVATION THROUGH REGULATION OF I KAPPA KINASE (IKK) IN BOTH HUMAN AND MOUSE CELL TYPES

Critical Care Medicine ◽

10.1097/00003246-200212001-00193 ◽

2002 ◽

Vol 30 (Supplement) ◽

pp. A56

Author(s):

Randall M Schwartz ◽

Bin Zhao ◽

Alvin G Denenberg ◽

Thomas P Shanley

Keyword(s):

Cell Types ◽

Mouse Cell ◽

Nf Kappa B ◽

Human And Mouse

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FR-Match: Robust matching of cell type clusters from single cell RNA sequencing data using the Friedman-Rafsky non-parametric test

10.1101/2020.05.01.073445 ◽

2020 ◽

Author(s):

Yun Zhang ◽

Brian D. Aevermann ◽

Trygve E. Bakken ◽

Jeremy A. Miller ◽

Rebecca D. Hodge ◽

...

Keyword(s):

Human Brain ◽

Single Cell ◽

Rna Sequencing ◽

Cell Types ◽

R Package ◽

Brain Regions ◽

Cortical Layer ◽

Middle Temporal Gyrus ◽

Cell Type ◽

Sequencing Data

AbstractSingle cell/nucleus RNA sequencing (scRNAseq) is emerging as an essential tool to unravel the phenotypic heterogeneity of cells in complex biological systems. While computational methods for scRNAseq cell type clustering have advanced, the ability to integrate datasets to identify common and novel cell types across experiments remains a challenge. Here, we introduce a cluster-to-cluster cell type matching method – FR-Match – that utilizes supervised feature selection for dimensionality reduction and incorporates shared information among cells to determine whether two cell type clusters share the same underlying multivariate gene expression distribution. FR-Match is benchmarked with existing cell-to-cell and cell-to-cluster cell type matching methods using both simulated and real scRNAseq data. FR-Match proved to be a stringent method that produced fewer erroneous matches of distinct cell subtypes and had the unique ability to identify novel cell phenotypes in new datasets. In silico validation demonstrated that the proposed workflow is the only self-contained algorithm that was robust to increasing numbers of true negatives (i.e. non-represented cell types). FR-Match was applied to two human brain scRNAseq datasets sampled from cortical layer 1 and full thickness middle temporal gyrus. When mapping cell types identified in specimens isolated from these overlapping human brain regions, FR-Match precisely recapitulated the laminar characteristics of matched cell type clusters, reflecting their distinct neuroanatomical distributions. An R package and Shiny application are provided at https://github.com/JCVenterInstitute/FRmatch for users to interactively explore and match scRNAseq cell type clusters with complementary visualization tools.

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Equivalent high-resolution identification of neuronal cell types with single-nucleus and single-cell RNA-sequencing

10.1101/239749 ◽

2017 ◽

Cited By ~ 6

Author(s):

Trygve E. Bakken ◽

Rebecca D. Hodge ◽

Jeremy M. Miller ◽

Zizhen Yao ◽

Thuc N. Nguyen ◽

...

Keyword(s):

High Resolution ◽

Single Cell ◽

Rna Sequencing ◽

Transcriptional Profiling ◽

Neuronal Cell ◽

Cell Types ◽

Matched Pair ◽

Rna Seq ◽

Nuclear Rna ◽

Single Nucleus

AbstractTranscriptional profiling of complex tissues by RNA-sequencing of single nuclei presents some advantages over whole cell analysis. It enables unbiased cellular coverage, lack of cell isolation-based transcriptional effects, and application to archived frozen specimens. Using a well-matched pair of single-nucleus RNA-seq (snRNA-seq) and single-cell RNA-seq (scRNA-seq) SMART-Seq v4 datasets from mouse visual cortex, we demonstrate that similarly high-resolution clustering of closely related neuronal types can be achieved with both methods if intronic sequences are included in nuclear RNA-seq analysis. More transcripts are detected in individual whole cells (∼11,000 genes) than nuclei (∼7,000 genes), but the majority of genes have similar detection across cells and nuclei. We estimate that the nuclear proportion of total cellular mRNA varies from 20% to over 50% for large and small pyramidal neurons, respectively. Together, these results illustrate the high information content of nuclear RNA for characterization of cellular diversity in brain tissues.

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An atlas of silencer elements for the human and mouse genomes

10.1101/252304 ◽

2018 ◽

Cited By ~ 1

Author(s):

Naresh Doni Jayavelu ◽

Ajay Jajodia ◽

Arpit Mishra ◽

R. David Hawkins

Keyword(s):

Cell Types ◽

Regulatory Elements ◽

Mouse Cell ◽

Support Vector ◽

General Strategy ◽

Gene Promoters ◽

Genome Wide ◽

A Genome ◽

Silencer Elements ◽

Human And Mouse

ABSTRACTThe study of gene regulation is dominated by a focus on the control of gene activation or controlling an increase in the level of expression. Just as critical is the process of gene repression or silencing. Chromatin signatures have allowed for the global mapping of enhancer cis-regulatory elements, however, the identification of silencer elements by computational or experimental approaches in a genome-wide manner are lacking. We present a simple but powerful computational approach to identify putative silencers genome-wide. We used a series of consortia data to predict silencers in over 100 human and mouse cell or tissue types. We performed several analyses to determine if these elements exhibited characteristics expected of a silencers. Motif enrichment analyses on putative silencers determined that motifs belonging to known transcriptional repressors are enriched, as well as overlapping known transcription repressor binding sites. Leveraging promoter capture HiC data from several human and mouse cell types, we found that over 50% of putative silencer elements are interacting with gene promoters having very low to no expression. Next, to validate our silencer predictions, we quantified silencer activity using massively parallel reporter assays (MPRAs) on 7500 selected elements in K562 cells. We trained a support vector machine model classifier on MPRA data and used it to refine potential silencers in other cell types. We also show that similar to enhancer elements, silencer elements are enriched in disease-associated variants. Our results suggest a general strategy for genome-wide identification and characterization of silencer elements.

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Comparison of reprogramming factor targets reveals both species-specific and conserved mechanisms in early iPS cells

10.1101/225326 ◽

2017 ◽

Author(s):

Kai Fu ◽

Constantinos Chronis ◽

Abdenour Soufi ◽

Giancarlo Bonora ◽

Miguel Edwards ◽

...

Keyword(s):

Regulatory Networks ◽

Target Genes ◽

Human Fibroblasts ◽

Mouse Cell ◽

Binding Motifs ◽

Reprogramming Factors ◽

Early Mouse ◽

Species Specific ◽

Human And Mouse ◽

Syntenic Regions

AbstractBoth human and mouse fibroblasts can be reprogrammed to pluripotency with Oct4, Sox2, Klf4, and c-Myc (OSKM) transcription factors. While both systems generate pluripotency, human reprogramming takes considerably longer than mouse. To assess additional similarities and differences, we sought to compare the binding of the reprogramming factors between the two systems. In human fibroblasts, the OSK factors initially target many more closed chromatin sites compared to mouse. Despite this difference, the intra- and intergenic distribution of target sites, target genes, primary binding motifs, and combinatorial binding patterns between the reprogramming factors are largely shared. However, while many OSKM binding events in early mouse cell reprogramming occur in syntenic regions, only a limited number is conserved in human. In summary, these findings suggest similar general effects of OSKM binding across these two species, even though the detailed regulatory networks have diverged significantly.

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