Root Hair Single Cell Type Specific Profiles of Gene Expression and Alternative Polyadenylation Under Cadmium Stress

Abstract Background Alternative polyadenylation (APA) is emerging as an important mechanism in the post-transcriptional regulation of gene expression across eukaryotic species. Recent studies have shown that APA plays key roles in biological processes, such as cell proliferation and differentiation. Single-cell RNA-seq technologies are widely used in gene expression heterogeneity studies; however, systematic studies of APA at the single-cell level are still lacking. Results Here, we described a novel computational framework, SAPAS, that utilizes 3′-tag-based scRNA-seq data to identify novel poly(A) sites and quantify APA at the single-cell level. Applying SAPAS to the scRNA-seq data of phenotype characterized GABAergic interneurons, we identified cell type-specific APA events for different GABAergic neuron types. Genes with cell type-specific APA events are enriched for synaptic architecture and communications. In further, we observed a strong enrichment of heritability for several psychiatric disorders and brain traits in altered 3′ UTRs and coding sequences of cell type-specific APA events. Finally, by exploring the modalities of APA, we discovered that the bimodal APA pattern of Pak3 could classify chandelier cells into different subpopulations that are from different laminar positions. Conclusions We established a method to characterize APA at the single-cell level. When applied to a scRNA-seq dataset of GABAergic interneurons, the single-cell APA analysis not only identified cell type-specific APA events but also revealed that the modality of APA could classify cell subpopulations. Thus, SAPAS will expand our understanding of cellular heterogeneity.

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Single-cell RNA sequencing of the mammalian pineal gland identifies two pinealocyte subtypes and cell type-specific daily patterns of gene expression

PLoS ONE ◽

10.1371/journal.pone.0205883 ◽

2018 ◽

Vol 13 (10) ◽

pp. e0205883 ◽

Cited By ~ 9

Author(s):

Joseph C. Mays ◽

Michael C. Kelly ◽

Steven L. Coon ◽

Lynne Holtzclaw ◽

Martin F. Rath ◽

...

Keyword(s):

Gene Expression ◽

Pineal Gland ◽

Single Cell ◽

Rna Sequencing ◽

Cell Type ◽

Single Cell Rna Sequencing ◽

Cell Type Specific ◽

Mammalian Pineal Gland ◽

Daily Patterns

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A single cell brain atlas in human Alzheimer’s disease

10.1101/628347 ◽

2019 ◽

Cited By ~ 4

Author(s):

Alexandra Grubman ◽

Gabriel Chew ◽

John F. Ouyang ◽

Guizhi Sun ◽

Xin Yi Choo ◽

...

Keyword(s):

Gene Expression ◽

Transcription Factor ◽

Single Cell ◽

Cell Fate ◽

Expression Patterns ◽

Cell Types ◽

Gene Expression Patterns ◽

Cell Type ◽

Web Resource ◽

Cell Type Specific

AbstractAlzheimer’s disease (AD) is a heterogeneous disease that is largely dependent on the complex cellular microenvironment in the brain. This complexity impedes our understanding of how individual cell types contribute to disease progression and outcome. To characterize the molecular and functional cell diversity in the human AD brain we utilized single nuclei RNA- seq in AD and control patient brains in order to map the landscape of cellular heterogeneity in AD. We detail gene expression changes at the level of cells and cell subclusters, highlighting specific cellular contributions to global gene expression patterns between control and Alzheimer’s patient brains. We observed distinct cellular regulation of APOE which was repressed in oligodendrocyte progenitor cells (OPCs) and astrocyte AD subclusters, and highly enriched in a microglial AD subcluster. In addition, oligodendrocyte and microglia AD subclusters show discordant expression of APOE. Integration of transcription factor regulatory modules with downstream GWAS gene targets revealed subcluster-specific control of AD cell fate transitions. For example, this analysis uncovered that astrocyte diversity in AD was under the control of transcription factor EB (TFEB), a master regulator of lysosomal function and which initiated a regulatory cascade containing multiple AD GWAS genes. These results establish functional links between specific cellular sub-populations in AD, and provide new insights into the coordinated control of AD GWAS genes and their cell-type specific contribution to disease susceptibility. Finally, we created an interactive reference web resource which will facilitate brain and AD researchers to explore the molecular architecture of subtype and AD-specific cell identity, molecular and functional diversity at the single cell level.HighlightsWe generated the first human single cell transcriptome in AD patient brainsOur study unveiled 9 clusters of cell-type specific and common gene expression patterns between control and AD brains, including clusters of genes that present properties of different cell types (i.e. astrocytes and oligodendrocytes)Our analyses also uncovered functionally specialized sub-cellular clusters: 5 microglial clusters, 8 astrocyte clusters, 6 neuronal clusters, 6 oligodendrocyte clusters, 4 OPC and 2 endothelial clusters, each enriched for specific ontological gene categoriesOur analyses found manifold AD GWAS genes specifically associated with one cell-type, and sets of AD GWAS genes co-ordinately and differentially regulated between different brain cell-types in AD sub-cellular clustersWe mapped the regulatory landscape driving transcriptional changes in AD brain, and identified transcription factor networks which we predict to control cell fate transitions between control and AD sub-cellular clustersFinally, we provide an interactive web-resource that allows the user to further visualise and interrogate our dataset.Data resource web interface:http://adsn.ddnetbio.com

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Single-cell RNA-sequencing reveals thoracolumbar vertebra heterogeneity and rib-genesis in pigs

10.1101/2021.05.25.445704 ◽

2021 ◽

Author(s):

Jianbo Li ◽

Ligang Wang ◽

Dawei Yu ◽

Junfeng Hao ◽

Longchao Zhang ◽

...

Keyword(s):

Gene Expression ◽

Single Cell ◽

Lumbar Vertebra ◽

Cell Types ◽

Cell Type ◽

Specific Expression ◽

Coupled Process ◽

Gene Expression Dynamics ◽

Cell Type Specific ◽

Thoracolumbar Vertebra

Thoracolumbar vertebra (TLV) and rib primordium (RP) development is a common evolutionary feature across vertebrates although whole-organism analysis of TLV and RP gene expression dynamics has been lacking. Here we investigated the single-cell transcriptomic landscape of thoracic vertebra (TV), lumbar vertebra (LV), and RP cells from a pig embryo at 27 days post-fertilization (dpf) and identified six cell types with distinct gene-expression signatures. In-depth dissection of the gene-expression dynamics and RNA velocity revealed a coupled process of osteogenesis and angiogenesis during TLV and rib development. Further analysis of cell-type-specific and strand-specific expression uncovered the extremely high levels of HOXA10 3'-UTR sequence specific to osteoblast of LV cells, which may function as anti-HOXA10-antisense by counteracting the HOXA10-antisense effect to determine TLV transition. Thus, this work provides a valuable resource for understanding embryonic osteogenesis and angiogenesis underlying vertebrate TLV and RP development at the cell-type-specific resolution, which serves as a comprehensive view on the transcriptional profile of animal embryo development.

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Dynamics of gene expression in single root cells ofA. thaliana

10.1101/448514 ◽

2018 ◽

Cited By ~ 3

Author(s):

Ken Jean-Baptiste ◽

José L. McFaline-Figueroa ◽

Cristina M. Alexandre ◽

Michael W. Dorrity ◽

Lauren Saunders ◽

...

Keyword(s):

Gene Expression ◽

Single Cell ◽

Developmental Trajectories ◽

Cell Types ◽

Cell Type ◽

Specific Expression ◽

Root Cells ◽

Cell Lineages ◽

Cell Type Specific Expression ◽

Cell Type Specific

ABSTRACTSingle-cell RNA-seq can yield high-resolution cell-type-specific expression signatures that reveal new cell types and the developmental trajectories of cell lineages. Here, we apply this approach toA. thalianaroot cells to capture gene expression in 3,121 root cells. We analyze these data with Monocle 3, which orders single cell transcriptomes in an unsupervised manner and uses machine learning to reconstruct single-cell developmental trajectories along pseudotime. We identify hundreds of genes with cell-type-specific expression, with pseudotime analysis of several cell lineages revealing both known and novel genes that are expressed along a developmental trajectory. We identify transcription factor motifs that are enriched in early and late cells, together with the corresponding candidate transcription factors that likely drive the observed expression patterns. We assess and interpret changes in total RNA expression along developmental trajectories and show that trajectory branch points mark developmental decisions. Finally, by applying heat stress to whole seedlings, we address the longstanding question of possible heterogeneity among cell types in the response to an abiotic stress. Although the response of canonical heat shock genes dominates expression across cell types, subtle but significant differences in other genes can be detected among cell types. Taken together, our results demonstrate that single-cell transcriptomics holds promise for studying plant development and plant physiology with unprecedented resolution.

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ReadZS detects developmentally regulated RNA processing programs in single cell RNA-seq and defines subpopulations independent of gene expression

10.1101/2021.09.29.462469 ◽

2021 ◽

Author(s):

Elisabeth Meyer ◽

Roozbeh Dehghannasiri ◽

Kaitlin Chaung ◽

Julia Salzman

Keyword(s):

Gene Expression ◽

Single Cell ◽

Rna Processing ◽

Single Cells ◽

Alternative Polyadenylation ◽

Cell Type ◽

Computationally Efficient ◽

Developmentally Regulated ◽

Eukaryotic Gene ◽

Human Spermatogenesis

Post-transcriptional regulation of RNA processing (RNAP), including splicing and alternative polyadenylation (APA), controls eukaryotic gene function. Conservative estimates based on bulk tissue studies conclude that at least 50% of mammalian genes undergo APA. Single-cell RNA sequencing (scRNA-seq) could enable a near complete estimate of the extent, function, and regulation of these and other forms of RNA processing. Yet, statistical methods to detect regulated RNAP are limited in their detection power because they suffer from reliance on (a) incomplete annotations of 3' untranslated regions (3' UTRs), (b) peak calling heuristics, (c) analysis based on measurements collapsed over all cells in a cell type (pseudobulking), or (d) APA-specific detection. Here, we introduce ReadZS, a computationally-efficient, and annotation-free statistical approach to identify regulated RNAP, including but not limited to APA, in single cells. ReadZS rediscovers and substantially extends the scope of known cell type-specific RNAP in the human lung and during human spermatogenesis. The unique single-cell resolution and statistical properties of ReadZS enable discovery of new evolutionarily conserved, developmentally regulated RNAP and subpopulations of lung-resident macrophages, homogenous by gene expression alone.

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A single-cell atlas of entorhinal cortex from individuals with Alzheimer’s disease reveals cell-type-specific gene expression regulation

Nature Neuroscience ◽

10.1038/s41593-019-0539-4 ◽

2019 ◽

Vol 22 (12) ◽

pp. 2087-2097 ◽

Cited By ~ 68

Author(s):

Alexandra Grubman ◽

Gabriel Chew ◽

John F. Ouyang ◽

Guizhi Sun ◽

Xin Yi Choo ◽

...

Keyword(s):

Gene Expression ◽

Alzheimer’S Disease ◽

Single Cell ◽

Entorhinal Cortex ◽

Gene Expression Regulation ◽

Expression Regulation ◽

Specific Gene ◽

Cell Type ◽

Specific Gene Expression ◽

Cell Type Specific

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Integration of Single-Cell RNA- and CAGE-seq Reveals Tooth-Enriched Genes

Journal of Dental Research ◽

10.1177/00220345211049785 ◽

2021 ◽

pp. 002203452110497

Author(s):

Y. Chiba ◽

K. Yoshizaki ◽

T. Tian ◽

K. Miyazaki ◽

D. Martin ◽

...

Keyword(s):

Gene Expression ◽

Single Cell ◽

Gene Expression Profile ◽

Expression Profile ◽

Tooth Development ◽

Expression Profiles ◽

Cell Type ◽

Bioinformatics Analyses ◽

Data Set ◽

Cell Type Specific

Organ development is dictated by the regulation of genes preferentially expressed in tissues or cell types. Gene expression profiling and identification of specific genes in organs can provide insights into organogenesis. Therefore, genome-wide analysis is a powerful tool for clarifying the mechanisms of development during organogenesis as well as tooth development. Single-cell RNA sequencing (scRNA-seq) is a suitable tool for unraveling the gene expression profile of dental cells. Using scRNA-seq, we can obtain a large pool of information on gene expression; however, identification of functional genes, which are key molecules for tooth development, via this approach remains challenging. In the present study, we performed cap analysis of gene expression sequence (CAGE-seq) using mouse tooth germ to identify the genes preferentially expressed in teeth. The CAGE-seq counts short reads at the 5′-end of transcripts; therefore, this method can quantify the amount of transcripts without bias related to the transcript length. We hypothesized that this CAGE data set would be of great help for further understanding a gene expression profile through scRNA-seq. We aimed to identify the important genes involved in tooth development via bioinformatics analyses, using a combination of scRNA-seq and CAGE-seq. We obtained the scRNA-seq data set of 12,212 cells from postnatal day 1 mouse molars and the CAGE-seq data set from postnatal day 1 molars. scRNA-seq analysis revealed the spatiotemporal expression of cell type–specific genes, and CAGE-seq helped determine whether these genes are preferentially expressed in tooth or ubiquitously. Furthermore, we identified candidate genes as novel tooth-enriched and dental cell type–specific markers. Our results show that the integration of scRNA-seq and CAGE-seq highlights the genes important for tooth development among numerous gene expression profiles. These findings should contribute to resolving the mechanism of tooth development and establishing the basis for tooth regeneration in the future.

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Implication of specific retinal cell-type involvement and gene expression changes in AMD progression using integrative analysis of single-cell and bulk RNA-seq profiling

Scientific Reports ◽

10.1038/s41598-021-95122-3 ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

Yafei Lyu ◽

Randy Zauhar ◽

Nicholas Dana ◽

Christianne E. Strang ◽

Jian Hu ◽

...

Keyword(s):

Gene Expression ◽

Single Cell ◽

Rna Sequencing ◽

Age Related Macular Degeneration ◽

Specific Gene ◽

Cell Type ◽

Adult Human ◽

Single Cell Rna Sequencing ◽

Cell Type Specific ◽

Cell Data

AbstractAge‐related macular degeneration (AMD) is a blinding eye disease with no unifying theme for its etiology. We used single-cell RNA sequencing to analyze the transcriptomes of ~ 93,000 cells from the macula and peripheral retina from two adult human donors and bulk RNA sequencing from fifteen adult human donors with and without AMD. Analysis of our single-cell data identified 267 cell-type-specific genes. Comparison of macula and peripheral retinal regions found no cell-type differences but did identify 50 differentially expressed genes (DEGs) with about 1/3 expressed in cones. Integration of our single-cell data with bulk RNA sequencing data from normal and AMD donors showed compositional changes more pronounced in macula in rods, microglia, endothelium, Müller glia, and astrocytes in the transition from normal to advanced AMD. KEGG pathway analysis of our normal vs. advanced AMD eyes identified enrichment in complement and coagulation pathways, antigen presentation, tissue remodeling, and signaling pathways including PI3K-Akt, NOD-like, Toll-like, and Rap1. These results showcase the use of single-cell RNA sequencing to infer cell-type compositional and cell-type-specific gene expression changes in intact bulk tissue and provide a foundation for investigating molecular mechanisms of retinal disease that lead to new therapeutic targets.

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