scholarly journals Principles of Spatial Transcriptomics Analysis: A Practical Walk-Through in Kidney Tissue

2022 ◽  
Vol 12 ◽  
Author(s):  
Teia Noel ◽  
Qingbo S. Wang ◽  
Anna Greka ◽  
Jamie L. Marshall
Keyword(s):  
Kidney Tissue ◽  
Cell Types ◽  
Cell Type ◽  
Computational Tools ◽  
Genome Wide ◽  
Distinct Cell ◽  
Type Classes ◽  
Tissue Space ◽  
Genetic Profiles ◽  
Spatial Cell

Spatial transcriptomic technologies capture genome-wide readouts across biological tissue space. Moreover, recent advances in this technology, including Slide-seqV2, have achieved spatial transcriptomic data collection at a near-single cell resolution. To-date, a repertoire of computational tools has been developed to discern cell type classes given the transcriptomic profiles of tissue coordinates. Upon applying these tools, we can explore the spatial patterns of distinct cell types and characterize how genes are spatially expressed within different cell type contexts. The kidney is one organ whose function relies upon spatially defined structures consisting of distinct cellular makeup. Thus, the application of Slide-seqV2 to kidney tissue has enabled us to elucidate spatially characteristic cellular and genetic profiles at a scale that remains largely unexplored. Here, we review spatial transcriptomic technologies, as well as computational approaches for cell type mapping and spatial cell type and transcriptomic characterizations. We take kidney tissue as an example to demonstrate how the technologies are applied, while considering the nuances of this architecturally complex tissue.

scholarly journals Simultaneous profiling of multiple chromatin proteins in the same cells

2021 ◽  
Author(s):  
Sneha Gopalan ◽  
Yuqing Wang ◽  
Nicholas W. Harper ◽  
Manuel Garber ◽  
Thomas G Fazzio
Keyword(s):  
Rna Polymerase Ii ◽  
Direct Analysis ◽  
Cell Types ◽  
Regulatory Elements ◽  
Genome Wide ◽  
Distinct Cell ◽  
Direct Measurements ◽  
Cell Type Specific ◽  
Chromatin Proteins

Methods derived from CUT&RUN and CUT&Tag enable genome-wide mapping of the localization of proteins on chromatin from as few as one cell. These and other mapping approaches focus on one protein at a time, preventing direct measurements of co-localization of different chromatin proteins in the same cells and requiring prioritization of targets where samples are limiting. Here we describe multi-CUT&Tag, an adaptation of CUT&Tag that overcomes these hurdles by using antibody-specific barcodes to simultaneously map multiple proteins in the same cells. Highly specific multi-CUT&Tag maps of histone marks and RNA Polymerase II uncovered sites of co-localization in the same cells, active and repressed genes, and candidate cis-regulatory elements. Single-cell multi-CUT&Tag profiling facilitated identification of distinct cell types from a mixed population and characterization of cell type-specific chromatin architecture. In sum, multi-CUT&Tag increases the information content per cell of epigenomic maps, facilitating direct analysis of the interplay of different proteins on chromatin.

scholarly journals Independent glial subtypes delay development and extend healthy lifespan upon reduced insulin-PI3K signalling

BMC Biology ◽  
2020 ◽  
Vol 18 (1) ◽  
Author(s):  
Nathaniel S. Woodling ◽  
Arjunan Rajasingam ◽  
Lucy J. Minkley ◽  
Alberto Rizzo ◽  
Linda Partridge
Keyword(s):  
Glial Cell ◽  
Cell Types ◽  
Therapeutic Interventions ◽  
Developmental Timing ◽  
Cell Type ◽  
Specific Effects ◽  
Trade Offs ◽  
Distinct Cell ◽  
Pi3k Signalling ◽  
Cell Type Specific

Abstract Background The increasing age of global populations highlights the urgent need to understand the biological underpinnings of ageing. To this end, inhibition of the insulin/insulin-like signalling (IIS) pathway can extend healthy lifespan in diverse animal species, but with trade-offs including delayed development. It is possible that distinct cell types underlie effects on development and ageing; cell-type-specific strategies could therefore potentially avoid negative trade-offs when targeting diseases of ageing, including prevalent neurodegenerative diseases. The highly conserved diversity of neuronal and non-neuronal (glial) cell types in the Drosophila nervous system makes it an attractive system to address this possibility. We have thus investigated whether IIS in distinct glial cell populations differentially modulates development and lifespan in Drosophila. Results We report here that glia-specific IIS inhibition, using several genetic means, delays development while extending healthy lifespan. The effects on lifespan can be recapitulated by adult-onset IIS inhibition, whereas developmental IIS inhibition is dispensable for modulation of lifespan. Notably, the effects we observe on both lifespan and development act through the PI3K branch of the IIS pathway and are dependent on the transcription factor FOXO. Finally, IIS inhibition in several glial subtypes can delay development without extending lifespan, whereas the same manipulations in astrocyte-like glia alone are sufficient to extend lifespan without altering developmental timing. Conclusions These findings reveal a role for distinct glial subpopulations in the organism-wide modulation of development and lifespan, with IIS in astrocyte-like glia contributing to lifespan modulation but not to developmental timing. Our results enable a more complete picture of the cell-type-specific effects of the IIS network, a pathway whose evolutionary conservation in humans make it tractable for therapeutic interventions. Our findings therefore underscore the necessity for cell-type-specific strategies to optimise interventions for the diseases of ageing.

CHANGES IN ADENOHYPOPHYSEAL CYTOLOGY AND NUCLEIC ACID CONTENT IN THE RAT 32 DAYS AFTER BILATERAL ADRENALECTOMY AND THE CHRONIC INJECTION OF CORTISOL

1967 ◽  
Vol 45 (6) ◽  
pp. 947-956 ◽  
Author(s):  
Jacob Kraicer ◽  
Marc Herlant ◽  
Pierre Duclos
Keyword(s):  
Cell Types ◽  
Bilateral Adrenalectomy ◽  
Synthetic Activity ◽  
Nucleic Acid Content ◽  
Cell Type ◽  
Cytological Evidence ◽  
Histological Techniques ◽  
Dna And Rna ◽  
Distinct Cell ◽  
Chronic Injection

Control, adrenalectomized, and cortisol-treated rats were maintained under rigidly controlled conditions, and the adenohypophyses were examined histologically with two staining procedures which differentiate six distinct cell types. Only one cell type demonstrated cytological evidence of increased synthetic activity 32 days after adrenalectomy (the changes were, however, minimal) and decreased synthetic activity following the chronic injection of cortisol. This cell type, which we designate as the corticotroph, would be classed as a chromophobe (no stainable granules) with use of standard histological techniques, but is, in fact, as Herlant's Tetrachrome demonstrates, a distinct acidophilic cell type different from the prolactin cell and the somatotroph. The determination of adenohypophyseal DNA and RNA revealed no evidence of increased protein synthetic activity following bilateral adrenalectomy, but did reveal evidence of decreased protein synthetic activity following the chronic injection of cortisol.

scholarly journals Evaluating the contribution of cell-type specific alternative splicing to variation in lipid levels

2019 ◽  
Author(s):  
K.A.B. Gawronski ◽  
W. Bone ◽  
Y. Park ◽  
E. Pashos ◽  
X. Wang ◽  
...  
Keyword(s):  
Alternative Splicing ◽  
Quantitative Trait ◽  
Cell Types ◽  
Genome Wide Association ◽  
Genome Wide Association Studies ◽  
Lipid Levels ◽  
Cell Type ◽  
Genome Wide ◽  
Genetic Mechanisms ◽  
Cell Type Specific

AbstractBackgroundGenome-wide association studies have identified 150+ loci associated with lipid levels. However, the genetic mechanisms underlying most of these loci are not well-understood. Recent work indicates that changes in the abundance of alternatively spliced transcripts contributes to complex trait variation. Consequently, identifying genetic loci that associate with alternative splicing in disease-relevant cell types and determining the degree to which these loci are informative for lipid biology is of broad interest.Methods and ResultsWe analyze gene splicing in 83 sample-matched induced pluripotent stem cell (iPSC) and hepatocyte-like cell (HLC) lines (n=166), as well as in an independent collection of primary liver tissues (n=96). We observe that transcript splicing is highly cell-type specific, and the genes that are differentially spliced between iPSCs and HLCs are enriched for metabolism pathway annotations. We identify 1,381 HLC splicing quantitative trait loci (sQTLs) and 1,462 iPSC sQTLs and find that sQTLs are often shared across cell types. To evaluate the contribution of sQTLs to variation in lipid levels, we conduct colocalization analysis using lipid genome-wide association data. We identify 19 lipid-associated loci that colocalize either with an HLC expression quantitative trait locus (eQTL) or sQTL. Only one locus colocalizes with both an sQTL and eQTL, indicating that sQTLs contribute information about GWAS loci that cannot be obtained by analysis of steady-state gene expression alone.ConclusionsThese results provide an important foundation for future efforts that use iPSC and iPSC-derived cells to evaluate genetic mechanisms influencing both cardiovascular disease risk and complex traits in general.

scholarly journals Enhancement and Imputation of Peak Signal Enables Accurate Cell-Type Classification in scATAC-seq

2021 ◽  
Vol 12 ◽  
Author(s):  
Zhe Cui ◽  
Ya Cui ◽  
Yan Gao ◽  
Tao Jiang ◽  
Tianyi Zang ◽  
...  
Keyword(s):  
Single Cell ◽  
Mononuclear Cells ◽  
Cell Types ◽  
Chromatin Accessibility ◽  
Support Vector ◽  
Cell Type ◽  
Peripheral Blood Mononuclear ◽  
Copy Numbers ◽  
Genome Wide ◽  
Accessible Chromatin

Single-cell Assay Transposase Accessible Chromatin sequencing (scATAC-seq) has been widely used in profiling genome-wide chromatin accessibility in thousands of individual cells. However, compared with single-cell RNA-seq, the peaks of scATAC-seq are much sparser due to the lower copy numbers (diploid in humans) and the inherent missing signals, which makes it more challenging to classify cell type based on specific expressed gene or other canonical markers. Here, we present svmATAC, a support vector machine (SVM)-based method for accurately identifying cell types in scATAC-seq datasets by enhancing peak signal strength and imputing signals through patterns of co-accessibility. We applied svmATAC to several scATAC-seq data from human immune cells, human hematopoietic system cells, and peripheral blood mononuclear cells. The benchmark results showed that svmATAC is free of literature-based markers and robust across datasets in different libraries and platforms. The source code of svmATAC is available at https://github.com/mrcuizhe/svmATAC under the MIT license.

scholarly journals Systematic evaluation of cell-type deconvolution pipelines for sequencing-based bulk DNA methylomes

2021 ◽  
Author(s):  
Yunhee Jeong ◽  
Reka Toth ◽  
Marlene Ganslmeier ◽  
Kersten Breuer ◽  
Christoph Plass ◽  
...  
Keyword(s):  
Cell Types ◽  
Systematic Evaluation ◽  
Cell Type ◽  
Factors Affecting ◽  
Genome Wide ◽  
Cell Type Composition ◽  
Type Composition ◽  
Level Information ◽  
Genomic Regions ◽  
The Impact

DNA methylation sequencing is becoming increasingly popular, yielding genome-wide methylome data at single-base pair resolution through the novel cost- and labor-optimized protocols. It has tremendous potential for cell-type heterogeneity analysis, particularly in tumors, due to intrinsic read-level information. Although diverse deconvolution methods were developed to infer cell-type composition based on bulk sequencing-based methylomes, their systematic evaluation has not been performed so far. Here, we thoroughly review and evaluate five previously published deconvolution methods: Bayesian epiallele detection (BED), PRISM, csmFinder + coMethy, ClubCpG and MethylPurify, together with two array-based methods, MeDeCom and Houseman as a comparison group. Sequencing-based deconvolution methods consist of two main steps, informative region selection and cell-type composition estimation. Accordingly, we individually assessed the performance of each step and demonstrated the impact of the former step upon the performance of the following one. In conclusion, we demonstrate the best method showing the highest accuracy in different samples, and infer factors affecting cell-type deconvolution performance according to the number of cell types in the mixture. We found that cell-type deconvolution performance is influenced by different factors according to the number of components in the mixture. Whereas selecting similar genomic regions to DMRs generally contributed to increasing the performance in bi-component mixtures, the uniformity of cell-type distribution showed a high correlation with the performance in five cell-type bulk analyses.

scholarly journals Cell segmentation-free inference of cell types from in situ transcriptomics data

2019 ◽  
Author(s):  
Jeongbin Park ◽  
Wonyl Choi ◽  
Sebastian Tiesmeyer ◽  
Brian Long ◽  
Lars E. Borm ◽  
...  
Keyword(s):  
Tissue Characterization ◽  
Cell Types ◽  
Cell Segmentation ◽  
Cell Type ◽  
Computational Framework ◽  
Transcriptomics Data ◽  
Novel Method ◽  
2D And 3D ◽  
Spatial Cell

AbstractMultiplexed fluorescence in situ hybridization techniques have enabled cell-type identification, linking transcriptional heterogeneity with spatial heterogeneity of cells. However, inaccurate cell segmentation reduces the efficacy of cell-type identification and tissue characterization. Here, we present a novel method called Spot-based Spatial cell-type Analysis by Multidimensional mRNA density estimation (SSAM), a robust cell segmentation-free computational framework for identifying cell-types and tissue domains in 2D and 3D. SSAM is applicable to a variety of in situ transcriptomics techniques and capable of integrating prior knowledge of cell types. We apply SSAM to three mouse brain tissue images: the somatosensory cortex imaged by osmFISH, the hypothalamic preoptic region by MERFISH, and the visual cortex by multiplexed smFISH. We found that SSAM detects regions occupied by known cell types that were previously missed and discovers new cell types.

scholarly journals Inferring relevant tissues and cell types for complex traits in genome-wide association studies

2021 ◽  
Author(s):  
Rujin Wang ◽  
Danyu Lin ◽  
Yuchao Jiang
Keyword(s):  
Single Cell ◽  
Complex Traits ◽  
Association Studies ◽  
Cell Types ◽  
Genome Wide Association ◽  
Genome Wide Association Studies ◽  
Cell Type ◽  
Disease Etiology ◽  
Genome Wide ◽  
Cell Type Specific

More than a decade of genome-wide association studies (GWASs) have identified genetic risk variants that are significantly associated with complex traits. Emerging evidence suggests that the function of trait-associated variants likely acts in a tissue- or cell-type-specific fashion. Yet, it remains challenging to prioritize trait-relevant tissues or cell types to elucidate disease etiology. Here, we present EPIC (cEll tyPe enrIChment), a statistical framework that relates large-scale GWAS summary statistics to cell-type-specific omics measurements from single-cell sequencing. We derive powerful gene-level test statistics for common and rare variants, separately and jointly, and adopt generalized least squares to prioritize trait-relevant tissues or cell types while accounting for the correlation structures both within and between genes. Using enrichment of loci associated with four lipid traits in the liver and enrichment of loci associated with three neurological disorders in the brain as ground truths, we show that EPIC outperforms existing methods. We extend our framework to single-cell transcriptomic data and identify cell types underlying type 2 diabetes and schizophrenia. The enrichment is replicated using independent GWAS and single-cell datasets and further validated using PubMed search and existing bulk case-control testing results.

scholarly journals Single-Cell Epigenomics and Functional Fine-Mapping of Atherosclerosis GWAS Loci

2021 ◽  
Author(s):  
Tiit Örd ◽  
Kadri Õunap ◽  
Lindsey Stolze ◽  
Rédouane Aherrahrou ◽  
Valtteri Nurminen ◽  
...  
Keyword(s):  
Smooth Muscle ◽  
Smooth Muscle Cells ◽  
Muscle Cells ◽  
Cell Types ◽  
Regulatory Elements ◽  
Chromatin Accessibility ◽  
Cell Type ◽  
Atherosclerotic Lesions ◽  
Genome Wide ◽  
Single Nucleus

Rationale: Genome-wide association studies (GWAS) have identified hundreds of loci associated with coronary artery disease (CAD). Many of these loci are enriched in cis-regulatory elements (CREs) but not linked to cardiometabolic risk factors nor to candidate causal genes, complicating their functional interpretation. Objective: Single nucleus chromatin accessibility profiling of the human atherosclerotic lesions was used to investigate cell type-specific patterns of CREs, to understand transcription factors establishing cell identity and to interpret CAD-relevant, non-coding genetic variation. Methods and Results: We used single nucleus ATAC-seq to generate DNA accessibility maps in > 7,000 cells derived from human atherosclerotic lesions. We identified five major lesional cell types including endothelial cells, smooth muscle cells, monocyte/macrophages, NK/T-cells and B-cells and further investigated subtype characteristics of macrophages and smooth muscle cells transitioning into fibromyocytes. We demonstrated that CAD associated genetic variants are particularly enriched in endothelial and smooth muscle cell-specific open chromatin. Using single cell co-accessibility and cis-eQTL information, we prioritized putative target genes and candidate regulatory elements for ~30% of all known CAD loci. Finally, we performed genome-wide experimental fine-mapping of the CAD GWAS variants using epigenetic QTL analysis in primary human aortic endothelial cells and STARR-Seq massively parallel reporter assay in smooth muscle cells. This analysis identified potential causal SNP(s) and the associated target gene for over 30 CAD loci. We present several examples where the chromatin accessibility and gene expression could be assigned to one cell type predicting the cell type of action for CAD loci. Conclusions: These findings highlight the potential of applying snATAC-seq to human tissues in revealing relative contributions of distinct cell types to diseases and in identifying genes likely to be influenced by non-coding GWAS variants.

scholarly journals A Radioautographic Study of Hemopoietic Repopulation Using Irradiated Parabiotic Rats

Blood ◽  
1966 ◽  
Vol 28 (6) ◽  
pp. 873-890 ◽  
Author(s):  
RUTH W. CAFFREY TYLER ◽  
N. B. EVERETT
Keyword(s):  
Bone Marrow ◽  
Stem Cell ◽  
Lymph Nodes ◽  
Cell Lines ◽  
Cell Types ◽  
Cell Type ◽  
Distinct Cell ◽  
Major Cell Type

Abstract These radioautographic studies using parabiotic rats and partial marrow shielding showed that cells responsible for recovery of irradiated bone marrow had their origin in the shielded marrow. Three morphologically distinct cell types appeared in the blood of these parabionts, mature granulocytes, small lymphocytes and monocytoid cells. The monocytoid was the major cell type which crossed from the shielded to nonshielded marrow, and the observations suggested that it is this cell which served as a stem cell for both the erythrocytic and granulocytic cell lines. Labeled erythroblasts and myeloblasts were observed in the recovering marrow, and the labeling intensity of these cells indicated that they were the second or third division products of labeled immigrant cells. The effect of marrow shielding upon the recovery of lymphopoiesis in spleen, thymus, lymph nodes and bone marrow is also discussed.

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