scholarly journals Molecular hallmarks of heterochronic parabiosis at single cell resolution

2020 ◽  
Author(s):  
Róbert Pálovics ◽  
Andreas Keller ◽  
Nicholas Schaum ◽  
Weilun Tan ◽  
Tobias Fehlmann ◽  
...  
Keyword(s):  
Gene Expression ◽  
Single Cell ◽  
Disease Risk ◽  
Global Gene Expression ◽  
Cell Types ◽  
The Body ◽  
Hematopoietic Stem ◽  
Gene Sets ◽  
Genes Encoding ◽  
Systemic Understanding

Slowing or reversing biological ageing would have major implications for mitigating disease risk and maintaining vitality. While an increasing number of interventions show promise for rejuvenation, the effectiveness on disparate cell types across the body and the molecular pathways susceptible to rejuvenation remain largely unexplored. We performed single-cell RNA-sequencing on 13 organs to reveal cell type specific responses to young or aged blood in heterochronic parabiosis. Adipose mesenchymal stromal cells, hematopoietic stem cells, hepatocytes, and endothelial cells from multiple tissues appear especially responsive. On the pathway level, young blood invokes novel gene sets in addition to reversing established ageing patterns, with the global rescue of genes encoding electron transport chain subunits pinpointing a prominent role of mitochondrial function in parabiosis-mediated rejuvenation. Intriguingly, we observed an almost universal loss of gene expression with age that is largely mimicked by parabiosis: aged blood reduces global gene expression, and young blood restores it. Altogether, these data lay the groundwork for a systemic understanding of the interplay between blood-borne factors and cellular integrity.

scholarly journals Aortic heterogeneity across segments and under high fat/salt/glucose conditions at the single-cell level

2020 ◽  
Vol 7 (5) ◽  
pp. 881-896 ◽  
Author(s):  
Dongxu He ◽  
Aiqin Mao ◽  
Chang-Bo Zheng ◽  
Hao Kan ◽  
Ka Zhang ◽  
...  
Keyword(s):  
Gene Expression ◽  
Single Cell ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Cell Types ◽  
The Body ◽  
Dietary Salt ◽  
High Fat ◽  
High Blood Glucose ◽  
Thoracic And Abdominal

Abstract The aorta, with ascending, arch, thoracic and abdominal segments, responds to the heartbeat, senses metabolites and distributes blood to all parts of the body. However, the heterogeneity across aortic segments and how metabolic pathologies change it are not known. Here, a total of 216 612 individual cells from the ascending aorta, aortic arch, and thoracic and abdominal segments of mouse aortas under normal conditions or with high blood glucose levels, high dietary salt, or high fat intake were profiled using single-cell RNA sequencing. We generated a compendium of 10 distinct cell types, mainly endothelial (EC), smooth muscle (SMC), stromal and immune cells. The distributions of the different cells and their intercommunication were influenced by the hemodynamic microenvironment across anatomical segments, and the spatial heterogeneity of ECs and SMCs may contribute to differential vascular dilation and constriction that were measured by wire myography. Importantly, the composition of aortic cells, their gene expression profiles and their regulatory intercellular networks broadly changed in response to high fat/salt/glucose conditions. Notably, the abdominal aorta showed the most dramatic changes in cellular composition, particularly involving ECs, fibroblasts and myeloid cells with cardiovascular risk factor-related regulons and gene expression networks. Our study elucidates the nature and range of aortic cell diversity, with implications for the treatment of metabolic pathologies.

MLL-AF9 Initiates Leukemia from a Single Committed Hematopoietic Progenitor.

Blood ◽  
2006 ◽  
Vol 108 (11) ◽  
pp. 2534-2534
Author(s):  
Andrei V. Krivtsov ◽  
Matthew C. Stubbs ◽  
Renee Wright ◽  
Zhaohui Feng ◽  
Andrew L. Kung ◽  
...  
Keyword(s):  
Gene Expression ◽  
Stem Cells ◽  
Single Cell ◽  
Prognostic Significance ◽  
Cell Types ◽  
Stem Cell Population ◽  
Leukemia Stem Cells ◽  
Cell Of Origin ◽  
Median Latency ◽  
Hematopoietic Stem

Abstract Recent experiments have demonstrated that MLL-translocation associated fusion proteins can transform either hematopoietic stem cells (HSC) or granulocyte macrophage progenitors (GMP) into leukemia stem cells. However, it may be that leukemogenic process differs when HSC are the cell of origin as compared to myeloid progenitors. We transduced either HSC or GMP with a retrovirus expressing MLL-AF9 and GFP followed by single cell sorting of transduced cells. Approximately 80% of singly sorted MLL-AF9 transduced GMP (MLL-AF9-GMP) and about 25% of MLL-AF9 transduced HSC (MLL-AF9-HSC) could be serially re-plated over 9 passages. Upon transplantation into syngeneic mice, 83% (n=12) of MLL-AF9-HSC single cell derived clones induced AML with a median latency 70 days. Approximately 30% (n=20) of MLL-AF9-GMP single cell derived clones induced AML, with median latency 112 days. When MLL-AF9-GMP single cell derived clones were co-infected with an empty retrovirus (to provide additional oncogenic events as a result of retroviral integration) before transplantation into recipient mice, 93% of the transplanted mice (n=15) developed AML with mean latency 65 days, similar to leukemia initiated from HSC. This suggests that either single GMP or HSC can be transformed into leukemia initiating cells. However, extra mutations appear to be required to induce leukemia from committed progenitors. Consistent with this hypothesis, southern blot analysis performed on leukemias initiated from 5,000 and 15,000 MLL-AF9 transduced HSC or GMP demonstrated polyclonal AML arising from HSC compared to oligoclonal AML arising from GMP. Next, we used bioluminescent imaging to follow disease kinetics. When 15,000 MLL-AF9 transduced HSC were injected into recipient mice, the disease accumulated in a linear fashion over 42 days. However, when 15,000 MLL-AF9 transduced GMP were injected the disease developed more slowly over 75 days. Immunophenotypic analysis of the resultant leukemias demonstrated that the HSC-derived and GMP-derived leukemias were quite similar, with a GMP-like population containing LSC in both cases. Globally, the two cell types were also very similar with their gene expression profile being more similar to GMP than any other progenitor or stem cell population. However, we found that in addition to the previously reported 363-gene “self-renewal associated signature” LSC derived from HSC also possessed high-level expression of genes such as Flt3, Mcl1, and Notch-1. Preliminary analysis also suggests that gene expression differences between HSC and GMP-derived leukemia stem cells may have prognostic significance in human AML. These data suggest that AML derived from different cells of origin, while globally quite similar, require a different number of genetic events, and have gene expression differences that may influence drug response.

scholarly journals Single Cell Transcriptomic Analysis of the Histone H3 K27M Mutation in Pre-Leukemic Hematopoietic Stem Cells

Blood ◽  
2019 ◽  
Vol 134 (Supplement_1) ◽  
pp. 3773-3773
Author(s):  
Meaghan Boileau ◽  
Selin Jessa ◽  
Samantha Worme ◽  
Damien Faury ◽  
Nada Jabado ◽  
...  
Keyword(s):  
Gene Expression ◽  
Stem Cells ◽  
Hematopoietic Stem Cells ◽  
Single Cell ◽  
Histone H3 ◽  
Cell Types ◽  
Clonal Expansion ◽  
Transcriptomic Analysis ◽  
Hematopoietic Stem ◽  
K27m Mutation

Acute myeloid leukemia (AML) develops in a step-wise manner from pre-leukemic clonal expansion to full-blown disease driven by aberrant epigenetic changes. Indeed, regulators of the epigenome such as DNMT3A, TET2, IDH1/2, EZH2 and ASXL1 are often mutated in pre-leukemia and myeloid malignancies. We and others identified K27M/I mutations in histone H3 in AML (Boileau et al. Nat Commun, 2019; Lehnertz et al. Blood, 2017). We demonstrated that K27 mutations are found in pre-leukemic hematopoietic stem cells (HSCs), are enriched in secondary AML, expand the functional human HSC pool and increase leukemic aggressiveness. Transcriptomic and epigenomic analysis determined that K27 mutations alter gene expression through a global decrease in promoter H3K27 tri-methylation and a gene-specific increase in H3K27 acetylation in leukemic cells (Boileau et al. Nat Commun, 2019). Here, we have analyzed the effects of the K27M mutation on HSCs at the single-cell level to understand its role in pre-leukemic clonal expansion. Healthy CD34+CD38- human cord blood cells were transduced with HIST1H3H WT or K27M and injected intrafemorally into sub-lethally irradiated NSG mice. After 14 weeks, bone marrow cells from the femur were collected and sorted for CD34+ transduced (GFP+) cells. Single-cell transcriptomics were performed by generating gene expression libraries from ~8,000 CD34+ cells using the 10X Genomics technology and sequenced using HiSeq4000. We have performed initial clustering and dimensionality reduction (t-SNE and UMAP) and identified 10 and 11 distinct clusters in the WT and K27M samples, respectively. Gene sets distinguishing the individual clusters have been determined. Using published gene lists for primitive hematopoietic cell types, the clusters have been assigned to specific cell types such as HSC, granulocyte-monocyte progenitors (GMP), common myeloid progenitors (CMP), multi-lymphoid progenitors (MLP) and megakaryocyte-erythroid progenitors (MEP) (Laurenti et al. Nat Immunol, 2013). Preliminary joint clustering analysis indicates the presence of two distinct clusters for the WT and K27M samples that were both assigned as "HSCs" in individual clustering. Further analysis to identify the differences in the clusters and cell populations between WT and K27M samples is being performed and will be presented at this meeting. Overall, this single-cell transcriptomic analysis will aid in determining the mechanism of action of the K27M mutant histone in pre-leukemic HSC clonal expansion. In addition, we will be performing similar single-cell analysis on HSCs expressing mutant ASXL1 as a comparison. Further understanding of the role of mutations in epigenetic regulators, such as histone H3 and ASXL1, in pre-leukemic clonal hematopoiesis will provide valuable insight on how to better prevent and treat AML and other myeloid malignancies. Disclosures No relevant conflicts of interest to declare.

scholarly journals The changing mouse embryo transcriptome at whole tissue and single-cell resolution

2020 ◽  
Author(s):  
Peng He ◽  
Brian A. Williams ◽  
Diane Trout ◽  
Georgi K. Marinov ◽  
Henry Amrhein ◽  
...  
Keyword(s):  
Gene Expression ◽  
Single Cell ◽  
Differential Gene Expression ◽  
Promoter Sequence ◽  
Cell Types ◽  
Tissue Level ◽  
Sequence Motifs ◽  
Gene Sets ◽  
Differential Gene ◽  
State Models

AbstractIn mammalian embryogenesis differential gene expression gradually builds the identity and complexity of each tissue and organ system. We systematically quantified mouse polyA-RNA from embryo day E10.5 to birth, sampling 17 whole tissues, enhanced with single-cell measurements for the developing limb. The resulting developmental transcriptome is globally structured by dynamic cytodifferentiation, body-axis and cell-proliferation gene sets, characterized by their promoters’ transcription factor (TF) motif codes. We decomposed the tissue-level transcriptome using scRNA-seq and found that neurogenesis and haematopoiesis dominate at both the gene and cellular levels, jointly accounting for 1/3 of differential gene expression and over 40% of identified cell types. Integrating promoter sequence motifs with companion ENCODE epigenomic profiles identified a promoter de-repression mechanism unique to neuronal expression clusters and attributable to known and novel repressors. Focusing on the developing limb, scRNA-seq identified 25 known and candidate novel cell types, including progenitor and differentiating states with computationally inferred lineage relationships. We extracted cell type TF networks and complementary sets of candidate enhancer elements by de-convolving whole-tissue IDEAS epigenome chromatin state models. These ENCODE reference data, computed network components and IDEAS chromatin segmentations, are companion resources to the matching epigenomic developmental matrix, available for researchers to further mine and integrate.

scholarly journals Identifying cell types from single-cell data based on similarities and dissimilarities between cells

2021 ◽  
Vol 22 (S3) ◽  
Author(s):  
Yuanyuan Li ◽  
Ping Luo ◽  
Yi Lu ◽  
Fang-Xiang Wu
Keyword(s):  
Gene Expression ◽  
Single Cell ◽  
Spectral Clustering ◽  
Incidence Matrix ◽  
Expression Patterns ◽  
Cell Types ◽  
Clustering Method ◽  
Different Types ◽  
Cell Data ◽  
Spectral Clustering Method

Abstract Background With the development of the technology of single-cell sequence, revealing homogeneity and heterogeneity between cells has become a new area of computational systems biology research. However, the clustering of cell types becomes more complex with the mutual penetration between different types of cells and the instability of gene expression. One way of overcoming this problem is to group similar, related single cells together by the means of various clustering analysis methods. Although some methods such as spectral clustering can do well in the identification of cell types, they only consider the similarities between cells and ignore the influence of dissimilarities on clustering results. This methodology may limit the performance of most of the conventional clustering algorithms for the identification of clusters, it needs to develop special methods for high-dimensional sparse categorical data. Results Inspired by the phenomenon that same type cells have similar gene expression patterns, but different types of cells evoke dissimilar gene expression patterns, we improve the existing spectral clustering method for clustering single-cell data that is based on both similarities and dissimilarities between cells. The method first measures the similarity/dissimilarity among cells, then constructs the incidence matrix by fusing similarity matrix with dissimilarity matrix, and, finally, uses the eigenvalues of the incidence matrix to perform dimensionality reduction and employs the K-means algorithm in the low dimensional space to achieve clustering. The proposed improved spectral clustering method is compared with the conventional spectral clustering method in recognizing cell types on several real single-cell RNA-seq datasets. Conclusions In summary, we show that adding intercellular dissimilarity can effectively improve accuracy and achieve robustness and that improved spectral clustering method outperforms the traditional spectral clustering method in grouping cells.

scholarly journals Optimizing expression quantitative trait locus mapping workflows for single-cell studies

2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Anna S. E. Cuomo ◽  
Giordano Alvari ◽  
Christina B. Azodi ◽  
Davis J. McCarthy ◽  
Marc Jan Bonder ◽  
...  
Keyword(s):  
Gene Expression ◽  
Quantitative Trait Locus ◽  
Single Cell ◽  
Quantitative Trait ◽  
Cell Types ◽  
Expression Quantitative Trait Locus ◽  
Eqtl Mapping ◽  
Trait Locus ◽  
The Impact

Abstract Background Single-cell RNA sequencing (scRNA-seq) has enabled the unbiased, high-throughput quantification of gene expression specific to cell types and states. With the cost of scRNA-seq decreasing and techniques for sample multiplexing improving, population-scale scRNA-seq, and thus single-cell expression quantitative trait locus (sc-eQTL) mapping, is increasingly feasible. Mapping of sc-eQTL provides additional resolution to study the regulatory role of common genetic variants on gene expression across a plethora of cell types and states and promises to improve our understanding of genetic regulation across tissues in both health and disease. Results While previously established methods for bulk eQTL mapping can, in principle, be applied to sc-eQTL mapping, there are a number of open questions about how best to process scRNA-seq data and adapt bulk methods to optimize sc-eQTL mapping. Here, we evaluate the role of different normalization and aggregation strategies, covariate adjustment techniques, and multiple testing correction methods to establish best practice guidelines. We use both real and simulated datasets across single-cell technologies to systematically assess the impact of these different statistical approaches. Conclusion We provide recommendations for future single-cell eQTL studies that can yield up to twice as many eQTL discoveries as default approaches ported from bulk studies.

scholarly journals Histone modifications form a cell-type-specific chromosomal bar code that persists through the cell cycle

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
John A. Halsall ◽  
Simon Andrews ◽  
Felix Krueger ◽  
Charlotte E. Rutledge ◽  
Gabriella Ficz ◽  
...  
Keyword(s):  
Gene Expression ◽  
Cell Cycle ◽  
Histone Modifications ◽  
Expression Patterns ◽  
Cell Types ◽  
Cell Type ◽  
Bar Code ◽  
Genes Encoding ◽  
Cell Type Specific ◽  
Rolling Windows

AbstractChromatin configuration influences gene expression in eukaryotes at multiple levels, from individual nucleosomes to chromatin domains several Mb long. Post-translational modifications (PTM) of core histones seem to be involved in chromatin structural transitions, but how remains unclear. To explore this, we used ChIP-seq and two cell types, HeLa and lymphoblastoid (LCL), to define how changes in chromatin packaging through the cell cycle influence the distributions of three transcription-associated histone modifications, H3K9ac, H3K4me3 and H3K27me3. We show that chromosome regions (bands) of 10–50 Mb, detectable by immunofluorescence microscopy of metaphase (M) chromosomes, are also present in G1 and G2. They comprise 1–5 Mb sub-bands that differ between HeLa and LCL but remain consistent through the cell cycle. The same sub-bands are defined by H3K9ac and H3K4me3, while H3K27me3 spreads more widely. We found little change between cell cycle phases, whether compared by 5 Kb rolling windows or when analysis was restricted to functional elements such as transcription start sites and topologically associating domains. Only a small number of genes showed cell-cycle related changes: at genes encoding proteins involved in mitosis, H3K9 became highly acetylated in G2M, possibly because of ongoing transcription. In conclusion, modified histone isoforms H3K9ac, H3K4me3 and H3K27me3 exhibit a characteristic genomic distribution at resolutions of 1 Mb and below that differs between HeLa and lymphoblastoid cells but remains remarkably consistent through the cell cycle. We suggest that this cell-type-specific chromosomal bar-code is part of a homeostatic mechanism by which cells retain their characteristic gene expression patterns, and hence their identity, through multiple mitoses.

scholarly journals Identification of leukemic and pre-leukemic stem cells by clonal tracking from single-cell transcriptomics

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Lars Velten ◽  
Benjamin A. Story ◽  
Pablo Hernández-Malmierca ◽  
Simon Raffel ◽  
Daniel R. Leonce ◽  
...  
Keyword(s):  
Gene Expression ◽  
Stem Cells ◽  
Cancer Stem Cells ◽  
Single Cell ◽  
Lineage Tracing ◽  
Specific Gene ◽  
Leukemic Stem Cells ◽  
Hematopoietic Stem ◽  
Mutational Status

AbstractCancer stem cells drive disease progression and relapse in many types of cancer. Despite this, a thorough characterization of these cells remains elusive and with it the ability to eradicate cancer at its source. In acute myeloid leukemia (AML), leukemic stem cells (LSCs) underlie mortality but are difficult to isolate due to their low abundance and high similarity to healthy hematopoietic stem cells (HSCs). Here, we demonstrate that LSCs, HSCs, and pre-leukemic stem cells can be identified and molecularly profiled by combining single-cell transcriptomics with lineage tracing using both nuclear and mitochondrial somatic variants. While mutational status discriminates between healthy and cancerous cells, gene expression distinguishes stem cells and progenitor cell populations. Our approach enables the identification of LSC-specific gene expression programs and the characterization of differentiation blocks induced by leukemic mutations. Taken together, we demonstrate the power of single-cell multi-omic approaches in characterizing cancer stem cells.

MO262THE SINGLE-CELL TRANSCRIPTOMICS OF HUMAN IGA NEPHROPATHY

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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