scholarly journals Single-Cell RNA-Seq of Mouse Decidual Leukocytes Reveals Intriguing Gestational Changes in the Immune Cell Landscape and Effects of SRC-1/-2 Double-Deficiency

2021 ◽  
Vol 5 (Supplement_1) ◽  
pp. A753-A754
Author(s):  
Jingfei Chen ◽  
Jialei Duan ◽  
Alina Montalbano ◽  
Boxun Li ◽  
Gary Hon ◽  
...  
Keyword(s):  
Gene Expression ◽  
Single Cell ◽  
Immune Cell ◽  
Expression Patterns ◽  
Critical Role ◽  
Fetal Lung ◽  
Specific Gene ◽  
Rna Seq ◽  
Cell Clusters ◽  
Pregnant Mice

Abstract Single-cell RNA-seq of Mouse Decidual Leukocytes Reveals Intriguing Gestational Changes in the Immune Cell Landscape and Effects of SRC-1/-2 Double-DeficiencyOur previous findings suggest that the fetus signals the mother when it is ready to be born through secretion of surfactant components/immune modulators, surfactant protein A (SP-A) and platelet-activating factor (PAF) by the fetal lung into amniotic fluid (AF). This occurs with increased proinflammatory cytokine expression by fetal AF macrophages (Mϕ), increased myometrial NF-κB activation and contractile (CAP) gene expression. Steroid receptor coactivator (Src)-1 and Src-2 are critical for developmental induction SP-A and PAF by the fetal lung. The finding that pregnant wild-type (WT) mice carrying Src-1 and Src-2 double-deficient fetuses (Src-1/-2d/d) manifested a marked delay (~38h) in parturition, further suggests that signals for parturition arise from the fetus and that Src-1 and Src-2 serve a critical role. Infiltrating leukocytes at the maternal-fetal interface (MFI)/decidua are known to play a central role in pregnancy maintenance and parturition timing. However, there is limited knowledge regarding gestational changes in immune cell composition toward term. To analyze gestational changes in the composition of immune cells within decidua and effects of Src-1/-2d/d, we conducted single-cell RNA-seq of ~17,000 decidual leukocytes (CD45+) from pregnant mice at 15.5 and 18.5 dpc carrying WT or Src-1/-2d/d fetuses. Unsupervised clustering identified 22 distinct decidual immune cell clusters, comprised of Mϕ, B cells, natural killer cells, neutrophils, dendritic cells and monocytes. Significant differences in cell type composition and transcriptional profiles were found across study groups (WT @ 15.5 dpc vs. 18.5 dpc; Src-1/-2d/dvs. WT @15.5 dpc and 18.5 dpc). Interestingly, in deciduas of pregnant mice carrying WT fetuses, Mϕ and B cell clusters markedly increased between 15.5 and 18.5 dpc, whereas, neutrophils declined; however, these gestational changes did not occur in pregnant mice carrying Src-1/-2d/d fetuses. Differential gene expression and gene ontology enrichment analyses revealed specific gene expression patterns distinguishing these immune cell subtypes to uncover their putative functions. These findings highlight the complexity and dynamics of the decidual immune cell landscape during the transition from myometrial quiescence to contractility, and the fetal-maternal interactions leading to parturition. Support: NIH grants R01-HL050022 (CRM) and P01-HD087150 (CRM), Burroughs Wellcome Preterm Birth Grant #1019823 (CRM).

scholarly journals Finding cell-specific expression patterns in the early Ciona embryo with single-cell RNA-seq

2017 ◽  
Author(s):  
Garth R. Ilsley ◽  
Ritsuko Suyama ◽  
Takeshi Noda ◽  
Nori Satoh ◽  
Nicholas M. Luscombe
Keyword(s):  
Gene Expression ◽  
Single Cell ◽  
Expression Patterns ◽  
Cell Types ◽  
Specific Gene ◽  
Rna Seq ◽  
Cell Stage ◽  
Specific Expression ◽  
Temporal Gene Expression

AbstractSingle-cell RNA-seq has been established as a reliable and accessible technique enabling new types of analyses, such as identifying cell types and studying spatial and temporal gene expression variation and change at single-cell resolution. Recently, single-cell RNA-seq has been applied to developing embryos, which offers great potential for finding and characterising genes controlling the course of development along with their expression patterns. In this study, we applied single-cell RNA-seq to the 16-cell stage of the Ciona embryo, a marine chordate and performed a computational search for cell-specific gene expression patterns. We recovered many known expression patterns from our single-cell RNA-seq data and despite extensive previous screens, we succeeded in finding new cell-specific patterns, which we validated by in situ and single-cell qPCR.

scholarly journals Single cell RNA-seq study of wild type and Hox9,10,11 mutant developing uterus

2018 ◽  
Author(s):  
Michael L. Mucenski ◽  
Robert Mahoney ◽  
Mike Adam ◽  
Andrew S. Potter ◽  
S. Steven Potter
Keyword(s):  
Gene Expression ◽  
Single Cell ◽  
Hox Genes ◽  
Expression Patterns ◽  
Wild Type Mouse ◽  
Cell Types ◽  
Specific Gene ◽  
Rna Seq ◽  
Wild Type ◽  
Mouse Uterus

AbstractThe uterus is a remarkable organ that must guard against infections while maintaining the ability to support growth of a fetus without rejection. The Hoxa10 and Hoxa11 genes have previously been shown to play essential roles in uterus development and function. In this report we show that the Hoxc9,10,11 genes play a redundant role in the formation of uterine glands. In addition, we use single cell RNA-seq to create a high resolution gene expression atlas of the developing wild type mouse uterus. Cell types and subtypes are defined, for example dividing endothelial cells into arterial, venous, capillary, and lymphatic, while epithelial cells separate into luminal and glandular subtypes. Further, a surprising heterogeneity of stromal and myocyte cell types are identified. Transcription factor codes and ligand/receptor interactions are characterized. We also used single cell RNA-seq to globally define the altered gene expression patterns in all developing uterus cell types for two Hox mutants, with 8 or 9 mutant Hox genes. The mutants show a striking disruption of Wnt signaling as well as the Cxcl12/Cxcr4 ligand/receptor axis.Summary statementA single cell RNA-seq study of the developing mouse uterus defines cellular heterogeneities, lineage specific gene expression programs and perturbed pathways in Hox9,10,11 mutants.

scholarly journals ROSeq: Modeling expression ranks for noise-tolerant differential expression analysis of scRNA-Seq data

2018 ◽  
Author(s):  
Krishan Gupta ◽  
Manan Lalit ◽  
Aditya Biswas ◽  
Ujjwal Maulik ◽  
Sanghamitra Bandyopadhyay ◽  
...  
Keyword(s):  
Gene Expression ◽  
Single Cell ◽  
Differential Expression ◽  
Negative Binomial ◽  
Single Cells ◽  
Expression Patterns ◽  
Critical Role ◽  
Differential Expression Analysis ◽  
Parametric Models ◽  
Specific Gene

1AbstractSystematic delineation of complex biological systems is an ever-challenging and resource-intensive process. Single cell transcriptomics allows us to study cell-to-cell variability in complex tissues at an unprecedented resolution. Accurate modeling of gene expression plays a critical role in the statistical determination of tissue-specific gene expression patterns. In the past few years, considerable efforts have been made to identify appropriate parametric models for single cell expression data. The zero-inflated version of Poisson/Negative Binomial and Log-Normal distributions have emerged as the most popular alternatives due to their ability to accommodate high dropout rates, as commonly observed in single cell data. While the majority of the parametric approaches directly model expression estimates, we explore the potential of modeling expression-ranks, as robust surrogates for transcript abundance. Here we examined the performance of the Discrete Generalized Beta Distribution (DGBD) on real data and devised a Wald-type test for comparing gene expression across two phenotypically divergent groups of single cells. We performed a comprehensive assessment of the proposed method, to understand its advantages as compared to some of the existing best practice approaches. Besides striking a reasonable balance between Type 1 and Type 2 errors, we concluded that ROSeq, the proposed differential expression test is exceptionally robust to expression noise and scales rapidly with increasing sample size. For wider dissemination and adoption of the method, we created an R package called ROSeq, and made it available on the Bioconductor platform.

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 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 Comprehensive characterization of tissue-specific chromatin accessibility in L2 Caenorhabditis elegans nematodes

2020 ◽  
Author(s):  
Timothy J. Durham ◽  
Riza M. Daza ◽  
Louis Gevirtzman ◽  
Darren A. Cusanovich ◽  
William Stafford Noble ◽  
...  
Keyword(s):  
Gene Expression ◽  
Single Cell ◽  
Expression Patterns ◽  
Cell Types ◽  
Chromatin Accessibility ◽  
Gene Expression Patterns ◽  
Rna Seq ◽  
Cell Type ◽  
Tissue Specific ◽  
C Elegans

AbstractRecently developed single cell technologies allow researchers to characterize cell states at ever greater resolution and scale. C. elegans is a particularly tractable system for studying development, and recent single cell RNA-seq studies characterized the gene expression patterns for nearly every cell type in the embryo and at the second larval stage (L2). Gene expression patterns are useful for learning about gene function and give insight into the biochemical state of different cell types; however, in order to understand these cell types, we must also determine how these gene expression levels are regulated. We present the first single cell ATAC-seq study in C. elegans. We collected data in L2 larvae to match the available single cell RNA-seq data set, and we identify tissue-specific chromatin accessibility patterns that align well with existing data, including the L2 single cell RNA-seq results. Using a novel implementation of the latent Dirichlet allocation algorithm, we leverage the single-cell resolution of the sci-ATAC-seq data to identify accessible loci at the level of individual cell types, providing new maps of putative cell type-specific gene regulatory sites, with promise for better understanding of cellular differentiation and gene regulation in the worm.

scholarly journals SCDC: bulk gene expression deconvolution by multiple single-cell RNA sequencing references

2020 ◽  
Author(s):  
Meichen Dong ◽  
Aatish Thennavan ◽  
Eugene Urrutia ◽  
Yun Li ◽  
Charles M Perou ◽  
...  
Keyword(s):  
Gene Expression ◽  
Single Cell ◽  
Rna Sequencing ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Specific Gene ◽  
Rna Seq ◽  
Cell Type ◽  
Mixed Cell ◽  
Single Cell Rna Sequencing

Abstract Recent advances in single-cell RNA sequencing (scRNA-seq) enable characterization of transcriptomic profiles with single-cell resolution and circumvent averaging artifacts associated with traditional bulk RNA sequencing (RNA-seq) data. Here, we propose SCDC, a deconvolution method for bulk RNA-seq that leverages cell-type specific gene expression profiles from multiple scRNA-seq reference datasets. SCDC adopts an ENSEMBLE method to integrate deconvolution results from different scRNA-seq datasets that are produced in different laboratories and at different times, implicitly addressing the problem of batch-effect confounding. SCDC is benchmarked against existing methods using both in silico generated pseudo-bulk samples and experimentally mixed cell lines, whose known cell-type compositions serve as ground truths. We show that SCDC outperforms existing methods with improved accuracy of cell-type decomposition under both settings. To illustrate how the ENSEMBLE framework performs in complex tissues under different scenarios, we further apply our method to a human pancreatic islet dataset and a mouse mammary gland dataset. SCDC returns results that are more consistent with experimental designs and that reproduce more significant associations between cell-type proportions and measured phenotypes.

scholarly journals SCRIBE: a new approach to dropout imputation and batch effects correction for single-cell RNA-seq data

2019 ◽  
Author(s):  
Yiliang Zhang ◽  
Kexuan Liang ◽  
Molei Liu ◽  
Yue Li ◽  
Hao Ge ◽  
...  
Keyword(s):  
Gene Expression ◽  
Data Analysis ◽  
Single Cell ◽  
Single Cells ◽  
Expression Patterns ◽  
Dropout Rate ◽  
Biological Variation ◽  
Specific Gene ◽  
Batch Effects ◽  
Cell Recovery

AbstractSingle-cell RNA sequencing technologies are widely used in recent years as a powerful tool allowing the observation of gene expression at the resolution of single cells. Two of the major challenges in scRNA-seq data analysis are dropout events and batch effects. The inflation of zero(dropout rate) varies substantially across single cells. Evidence has shown that technical noise, including batch effects, explains a notable proportion of this cell-to-cell variation. To capture biological variation, it is necessary to quantify and remove technical variation. Here, we introduce SCRIBE (Single-Cell Recovery Imputation with Batch Effects), a principled framework that imputes dropout events and corrects batch effects simultaneously. We demonstrate, through real examples, that SCRIBE outperforms existing scRNA-seq data analysis tools in recovering cell-specific gene expression patterns, removing batch effects and retaining biological variation across cells. Our software is freely available online at https://github.com/YiliangTracyZhang/SCRIBE.

scholarly journals SCDC: Bulk Gene Expression Deconvolution by Multiple Single-Cell RNA Sequencing References

2019 ◽  
Author(s):  
Meichen Dong ◽  
Aatish Thennavan ◽  
Eugene Urrutia ◽  
Yun Li ◽  
Charles M. Perou ◽  
...  
Keyword(s):  
Gene Expression ◽  
Single Cell ◽  
Rna Sequencing ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Specific Gene ◽  
Rna Seq ◽  
Cell Type ◽  
Mixed Cell ◽  
Single Cell Rna Sequencing

AbstractRecent advances in single-cell RNA sequencing (scRNA-seq) enable characterization of transcriptomic profiles with single-cell resolution and circumvent averaging artifacts associated with traditional bulk RNA sequencing (RNA-seq) data. Here, we propose SCDC, a deconvolution method for bulk RNA-seq that leverages cell-type specific gene expression profiles from multiple scRNA-seq reference datasets. SCDC adopts an ENSEMBLE method to integrate deconvolution results from different scRNA-seq datasets that are produced in different laboratories and at different times, implicitly addressing the problem of batch-effect confounding. SCDC is benchmarked against existing methods using both in silico generated pseudo-bulk samples and experimentally mixed cell lines, whose known cell-type compositions serve as ground truths. We show that SCDC outperforms existing methods with improved accuracy of cell-type decomposition under both settings. To illustrate how the ENSEMBLE framework performs in complex tissues under different scenarios, we further apply our method to a human pancreatic islet dataset and a mouse mammary gland dataset. SCDC returns results that are more consistent with experimental designs and that reproduce more significant associations between cell-type proportions and measured phenotypes.

Mesonephric cell migration induces testis cord formation and Sertoli cell differentiation in the mammalian gonad

Development ◽  
1999 ◽  
Vol 126 (13) ◽  
pp. 2883-2890 ◽  
Author(s):  
C. Tilmann ◽  
B. Capel
Keyword(s):  
Gene Expression ◽  
Cell Migration ◽  
Single Gene ◽  
Expression Patterns ◽  
Critical Role ◽  
Cell Types ◽  
Specific Gene ◽  
Specific Gene Expression ◽  
Male Specific ◽  
Testis Cord

In mammals a single gene on the Y chromosome, Sry, controls testis formation. One of the earliest effects of Sry expression is the induction of somatic cell migration from the mesonephros into the XY gonad. Here we show that mesonephric cells are required for cord formation and male-specific gene expression in XY gonads in a stage-specific manner. Culturing XX gonads with an XY gonad at their surface, as a ‘sandwich’, resulted in cell migration into the XX tissue. Analysis of sandwich gonads revealed that in the presence of migrating cells, XX gonads organized cord structures and acquired male-specific gene expression patterns. From these results, we conclude that mesonephric cell migration plays a critical role in the formation of testis cords and the differentiation of XY versus XX cell types.

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