Gene expression variation in arabidopsis embryos at single-nucleus resolution

Soon after fertilization of egg and sperm, plant genomes become transcriptionally activated and drive a series of coordinated cell divisions to form the basic body plan during embryogenesis. Early embryonic cells rapidly diversify from each other, and investigation of the corresponding gene expression dynamics can help elucidate underlying cellular differentiation programs. However, current plant embryonic transcriptome datasets either lack cell-specific information or have RNA contamination from surrounding non-embryonic tissues. We have coupled fluorescence-activated nuclei sorting together with single-nucleus mRNA sequencing to construct a gene expression atlas of Arabidopsis thaliana early embryos at single-cell resolution. In addition to characterizing cell-specific transcriptomes, we found evidence that distinct epigenetic and transcriptional regulatory mechanisms operate across emerging embryonic cell types. These datasets and analyses, as well as the approach we devised, are expected to facilitate the discovery of molecular mechanisms underlying pattern formation in plant embryos.

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Gene Expression Variation in Arabidopsis Embryos at Single-Nucleus Resolution

10.1101/2021.03.26.437151 ◽

2021 ◽

Author(s):

Ping Kao ◽

Michael A Schon ◽

Magdalena Mosiolek ◽

Michael D Nodine

Keyword(s):

Gene Expression ◽

Molecular Mechanisms ◽

Cell Types ◽

Embryonic Cell ◽

Specific Information ◽

Embryonic Cells ◽

Basic Body ◽

Expression Atlas ◽

Single Nucleus ◽

Transcriptional Regulatory Mechanisms

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Is maternal mRNA a determinant of tissue-specific proteins in ascidian embryos?

Development ◽

10.1242/dev.97.supplement.1 ◽

1986 ◽

Vol 97 (Supplement) ◽

pp. 1-14

Author(s):

W. R. Jeffery ◽

W. R Bates ◽

R. L. Beach ◽

C. R. Tomlinson

Keyword(s):

Gene Expression ◽

Cell Types ◽

Embryonic Cell ◽

Specific Cell ◽

Embryonic Cells ◽

Tissue Specific ◽

Maternal Mrna ◽

Cell Diversity ◽

Zygotic Gene ◽

Cytoplasmic Determinants

The generation of different cell types during embryonic development is thought to be mediated by the combined activity of cytoplasmic factors (determinants), which are localized in the egg, and inductive interactions, which occur between different embryonic cells and tissues. Ascidians, animals that exhibit rapid and exceptionally autonomous development (reviewed by Jeffery, 1985), appear to employ cytoplasmic determinants to generate embryonic cell diversity. Although determinants have not been identified in ascidians or other animals, it is hypothesized that they function in at least two different ways. First, as initially pointed out by Morgan (1934), determinants may be regulatory factors which promote differential gene expression in specific cell lineages. Consistent with this possibility, inhibitors of transcription, added prior to gastrulation, block the appearance of some ascidian tissue-specific enzymes and morphological markers whose expression is regulated by the activity of cytoplasmic determinants (Whittaker, 1973; Crowther & Whittaker, 1984). Second, determinants may be localized factors which promote cell diversification independent of zygotic gene expression.

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Single-nucleus RNA-seq resolves spatiotemporal developmental trajectories in the tomato shoot apex

10.1101/2020.09.20.305029 ◽

2020 ◽

Cited By ~ 1

Author(s):

Caihuan Tian ◽

Qingwei Du ◽

Mengxue Xu ◽

Fei Du ◽

Yuling Jiao

Keyword(s):

Gene Expression ◽

Single Cell ◽

Rna Sequencing ◽

Shoot Apex ◽

Developmental Trajectories ◽

Gene Expression Pattern ◽

Cell Types ◽

Plant Research ◽

Expression Atlas ◽

Single Nucleus

Single cell transcriptomics is revolutionizing our understanding of development and response to environmental cues1–3. Recent advances in single cell RNA sequencing (scRNA-seq) technology have enabled profiling gene expression pattern of heterogenous tissues and organs at single cellular level and have been widely applied in human and animal research4,5. Nevertheless, the existence of cell walls significantly encumbered its application in plant research. Protoplasts have been applied for scRNA-seq analysis, but mostly restricted to tissues amenable for wall digestion, such as root tips6–10. However, many cell types are resistant to protoplasting, and protoplasting may yield ectopic gene expression and bias proportions of cell types. Here we demonstrate a method with minimal artifacts for high-throughput single-nucleus RNA sequencing (snRNA-Seq) that we use to profile tomato shoot apex cells. The obtained high-resolution expression atlas identifies numerous distinct cell types covering major shoot tissues and developmental stages, delineates developmental trajectories of mesophyll cells, vasculature cells, epidermal cells, and trichome cells. In addition, we identify key developmental regulators and reveal their hierarchy. Collectively, this study demonstrates the power of snRNA-seq to plant research and provides an unprecedented spatiotemporal gene expression atlas of heterogeneous shoot cells.

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Genetic analysis of amyotrophic lateral sclerosis identifies contributing pathways and cell types

Science Advances ◽

10.1126/sciadv.abd9036 ◽

2021 ◽

Vol 7 (3) ◽

pp. eabd9036

Author(s):

Sara Saez-Atienzar ◽

Sara Bandres-Ciga ◽

Rebekah G. Langston ◽

Jonggeol J. Kim ◽

Shing Wan Choi ◽

...

Keyword(s):

Amyotrophic Lateral Sclerosis ◽

Membrane Trafficking ◽

Molecular Mechanisms ◽

Cell Types ◽

Polygenic Risk Score ◽

Genome Wide ◽

Genome Wide Data ◽

Data Driven Approach ◽

Single Nucleus ◽

Lateral Sclerosis

Despite the considerable progress in unraveling the genetic causes of amyotrophic lateral sclerosis (ALS), we do not fully understand the molecular mechanisms underlying the disease. We analyzed genome-wide data involving 78,500 individuals using a polygenic risk score approach to identify the biological pathways and cell types involved in ALS. This data-driven approach identified multiple aspects of the biology underlying the disease that resolved into broader themes, namely, neuron projection morphogenesis, membrane trafficking, and signal transduction mediated by ribonucleotides. We also found that genomic risk in ALS maps consistently to GABAergic interneurons and oligodendrocytes, as confirmed in human single-nucleus RNA-seq data. Using two-sample Mendelian randomization, we nominated six differentially expressed genes (ATG16L2, ACSL5, MAP1LC3A, MAPKAPK3, PLXNB2, and SCFD1) within the significant pathways as relevant to ALS. We conclude that the disparate genetic etiologies of this fatal neurological disease converge on a smaller number of final common pathways and cell types.

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MO262THE SINGLE-CELL TRANSCRIPTOMICS OF HUMAN IGA NEPHROPATHY

Nephrology Dialysis Transplantation ◽

10.1093/ndt/gfab104.0020 ◽

2021 ◽

Vol 36 (Supplement_1) ◽

Author(s):

Yong Zhong ◽

Xiangcheng Xiao

Keyword(s):

Gene Expression ◽

Single Cell ◽

Signaling Pathways ◽

Iga Nephropathy ◽

Molecular Mechanisms ◽

Mesangial Cells ◽

Therapeutic Targets ◽

Cell Types ◽

Receptor Crosstalk ◽

Overt Proteinuria

Abstract Background and Aims The exact molecular mechanisms underlying IgA nephropathy (IgAN) remains incompletely defined. Therefore, it is necessary to further elucidate the mechanism of IgA nephropathy and find novel therapeutic targets. Method Single-cell RNA sequencing (scRNA-seq) was applied to kidney biopsies from 4 IgAN and 1 control subjects to define the transcriptomic landscape at the single-cell resolution. Unsupervised clustering analysis of kidney specimens was used to identify distinct cell clusters. Differentially expressed genes and potential signaling pathways involved in IgAN were also identified. Results Our analysis identified 14 cell subsets in kidney biopsies from IgAN patients, and analyzed changing gene expression in distinct renal cell types. We found increased mesangial expression of several novel genes including MALAT1, GADD45B, SOX4 and EDIL3, which were related to proliferation and matrix accumulation and have not been reported in IgAN previously. The overexpressed genes in tubule cells of IgAN were mainly enriched in inflammatory pathways including TNF signaling, IL-17 signaling and NOD-like receptor signaling. Moreover, the receptor-ligand crosstalk analysis revealed potential interactions between mesangial cells and other cells in IgAN. Specifically, IgAN with overt proteinuria displayed elevated genes participating in several signaling pathways which may be involved in pathogenesis of progression of IgAN. Conclusion The comprehensive analysis of kidney biopsy specimen demonstrated different gene expression profile, potential pathologic ligand-receptor crosstalk, signaling pathways in human IgAN. These results offer new insight into pathogenesis and identify new therapeutic targets for patients with IgA nephropathy.

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Single-cell transcriptomic analysis elucidates APOE genotype specific changes across cell types in two brain regions in Alzheimer’s disease

10.21203/rs.3.rs-291648/v1 ◽

2021 ◽

Author(s):

Stella Belonwu ◽

Yaqiao Li ◽

Daniel Bunis ◽

Arjun Arkal Rao ◽

Caroline Warly Solsberg ◽

...

Keyword(s):

Alzheimer’S Disease ◽

Alzheimer's Disease ◽

Single Cell ◽

Molecular Mechanisms ◽

Apoe Genotype ◽

Cell Types ◽

Brain Regions ◽

Single Cell Level ◽

Cell Level ◽

Single Nucleus

Abstract Alzheimer’s Disease (AD) is a complex neurodegenerative disease that gravely affects patients and imposes an immense burden on caregivers. Apolipoprotein E4 (APOE4) has been identified as the most common genetic risk factor for AD, yet the molecular mechanisms connecting APOE4 to AD are not well understood. Past transcriptomic analyses in AD have revealed APOE genotype-specific transcriptomic differences; however, these differences have not been explored at a single-cell level. Here, we leverage the first two single-nucleus RNA sequencing AD datasets from human brain samples, including nearly 55,000 cells from the prefrontal and entorhinal cortices. We observed more global transcriptomic changes in APOE4 positive AD cells and identified differences across APOE genotypes primarily in glial cell types. Our findings highlight the differential transcriptomic perturbations of APOE isoforms at a single-cell level in AD pathogenesis and have implications for precision medicine development in the diagnosis and treatment of AD.

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Enhancing droplet-based single-nucleus RNA-seq resolution using the semi-supervised machine learning classifier DIEM

10.1101/786285 ◽

2019 ◽

Cited By ~ 4

Author(s):

Marcus Alvarez ◽

Elior Rahmani ◽

Brandon Jew ◽

Kristina M. Garske ◽

Zong Miao ◽

...

Keyword(s):

Gene Expression ◽

Single Cell ◽

Cell Types ◽

Supervised Machine Learning ◽

Data Sets ◽

Rna Seq ◽

Novel Approach ◽

Single Nucleus ◽

Downstream Analysis

AbstractSingle-nucleus RNA sequencing (snRNA-seq) measures gene expression in individual nuclei instead of cells, allowing for unbiased cell type characterization in solid tissues. Contrary to single-cell RNA seq (scRNA-seq), we observe that snRNA-seq is commonly subject to contamination by high amounts of extranuclear background RNA, which can lead to identification of spurious cell types in downstream clustering analyses if overlooked. We present a novel approach to remove debris-contaminated droplets in snRNA-seq experiments, called Debris Identification using Expectation Maximization (DIEM). Our likelihood-based approach models the gene expression distribution of debris and cell types, which are estimated using EM. We evaluated DIEM using three snRNA-seq data sets: 1) human differentiating preadipocytes in vitro, 2) fresh mouse brain tissue, and 3) human frozen adipose tissue (AT) from six individuals. All three data sets showed various degrees of extranuclear RNA contamination. We observed that existing methods fail to account for contaminated droplets and led to spurious cell types. When compared to filtering using these state of the art methods, DIEM better removed droplets containing high levels of extranuclear RNA and led to higher quality clusters. Although DIEM was designed for snRNA-seq data, we also successfully applied DIEM to single-cell data. To conclude, our novel method DIEM removes debris-contaminated droplets from single-cell-based data fast and effectively, leading to cleaner downstream analysis. Our code is freely available for use at https://github.com/marcalva/diem.

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Misregulation of SDF1-CXCR4 Signaling Impairs Early Cardiac Neural Crest Cell Migration Leading to Conotruncal Defects

Circulation Research ◽

10.1161/circresaha.113.301333 ◽

2013 ◽

Vol 113 (5) ◽

pp. 505-516 ◽

Cited By ~ 52

Author(s):

Sophie Escot ◽

Cédrine Blavet ◽

Sonja Härtle ◽

Jean-Loup Duband ◽

Claire Fournier-Thibault

Keyword(s):

Neural Crest ◽

Molecular Mechanisms ◽

Heart Diseases ◽

Smooth Muscles ◽

Neural Crest Cell ◽

Cell Types ◽

Ventricular Septum ◽

Embryonic Cells ◽

Loss Of Function ◽

Cardiac Neural Crest

Rationale: Cardiac neural crest cells (NCs) contribute to heart morphogenesis by giving rise to a variety of cell types from mesenchyme of the outflow tract, ventricular septum, and semilunar valves to neurons of the cardiac ganglia and smooth muscles of the great arteries. Failure in cardiac NC development results in outflow and ventricular septation defects commonly observed in congenital heart diseases. Cardiac NCs derive from the vagal neural tube, which also gives rise to enteric NCs that colonize the gut; however, so far, molecular mechanisms segregating these 2 populations and driving cardiac NC migration toward the heart have remained elusive. Objective: Stromal-derived factor-1 (SDF1) is a chemokine that mediates oriented migration of multiple embryonic cells and mice deficient for Sdf1 or its receptors, Cxcr4 and Cxcr7 , exhibit ventricular septum defects, raising the possibility that SDF1 might selectively drive cardiac NC migration toward the heart via a chemotactic mechanism. Methods and Results : We show in the chick embryo that Sdf1 expression is tightly coordinated with the progression of cardiac NCs expressing Cxcr4 . Cxcr4 loss-of-function causes delayed migration and enhanced death of cardiac NCs, whereas Sdf1 misexpression results in their diversion from their normal pathway, indicating that SDF1 acts as a chemoattractant for cardiac NCs. These alterations of SDF1 signaling result in severe cardiovascular defects. Conclusions: These data identify Sdf1 and its receptor Cxcr4 as candidate genes responsible for cardiac congenital pathologies in human.

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scMontage: Fast and Robust Gene Expression Similarity Search for Massive Single-cell Data

10.1101/2020.08.30.271395 ◽

2020 ◽

Cited By ~ 1

Author(s):

Tomoya Mori ◽

Naila Shinwari ◽

Wataru Fujibuchi

Keyword(s):

Gene Expression ◽

Single Cell ◽

Similarity Search ◽

Rank Correlation ◽

Cell Types ◽

Specific Information ◽

Link Type ◽

Spearman’S Rank Correlation ◽

Spearman’S Rank Correlation Coefficient ◽

Additional Cell

AbstractSingle-cell RNA-seq (scRNA-seq) analysis is widely used to characterize cell types or detect heterogeneity of cell states at much higher resolutions than ever before. Here we introduce scMontage (https://scmontage.stemcellinformatics.org), a gene expression similarity search server dedicated to scRNA-seq data, which can rapidly compare a query with thousands of samples within a few seconds. The scMontage search is based on Spearman’s rank correlation coefficient and its robustness is ensured by introducing Fisher’s Z-transformation and Z-test. Furthermore, search results are linked to a human cell database SHOGoiN (http://shogoin.stemcellinformatics.org), which enable users to fast access to additional cell-type specific information. The scMontage is available not only as a web server but also as a stand-alone application for user’s own data, and thus it enhances the reliability and throughput of cell analysis and helps users gain new insights into their research.

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Single cell and single nucleus RNA-Seq reveal cellular heterogeneity and homeostatic regulatory networks in adult mouse stria vascularis

10.1101/756635 ◽

2019 ◽

Author(s):

Soumya Korrapati ◽

Ian Taukulis ◽

Rafal Olszewski ◽

Madeline Pyle ◽

Shoujun Gu ◽

...

Keyword(s):

Single Cell ◽

Gene Regulatory Networks ◽

Regulatory Networks ◽

Molecular Mechanisms ◽

Stria Vascularis ◽

Cell Types ◽

Cellular Heterogeneity ◽

Genetic Mechanisms ◽

Single Nucleus ◽

Gene Regulatory

AbstractThe stria vascularis (SV) generates the endocochlear potential (EP) in the inner ear and is necessary for proper hair cell mechanotransduction and hearing. While channels belonging to SV cell types are known to play crucial roles in EP generation, relatively little is known about gene regulatory networks that underlie the ability of the SV to generate and maintain the EP. Using single cell and single nucleus RNA-sequencing, we identify and validate known and rare cell populations in the SV. Furthermore, we establish a basis for understanding molecular mechanisms underlying SV function by identifying potential gene regulatory networks as well as druggable gene targets. Finally, we associate known deafness genes with adult SV cell types. This work establishes a basis for dissecting the genetic mechanisms underlying the role of the SV in hearing and will serve as a basis for designing therapeutic approaches to hearing loss related to SV dysfunction.

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