Characterizing the temporal dynamics of gene expression in single cells with sci-fate

AbstractGene expression programs are dynamic, e.g. the cell cycle, response to stimuli, normal differentiation and development, etc. However, nearly all techniques for profiling gene expression in single cells fail to directly capture the dynamics of transcriptional programs, which limits the scope of biology that can be effectively investigated. Towards addressing this, we developed sci-fate, a new technique that combines S4U labeling of newly synthesized mRNA with single cell combinatorial indexing (sci-), in order to concurrently profile the whole and newly synthesized transcriptome in each of many single cells. As a proof-of-concept, we applied sci-fate to a model system of cortisol response and characterized expression dynamics in over 6,000 single cells. From these data, we quantify the dynamics of the cell cycle and glucocorticoid receptor activation, while also exploring their intersection. We furthermore use these data to develop a framework for inferring the distribution of cell state transitions. We anticipate sci-fate will be broadly applicable to quantitatively characterize transcriptional dynamics in diverse systems.

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Sequencing of RNA in single cells reveals a distinct transcriptome signature of hematopoiesis in GATA2 deficiency

Blood Advances ◽

10.1182/bloodadvances.2019001352 ◽

2020 ◽

Vol 4 (12) ◽

pp. 2702-2716

Author(s):

Zhijie Wu ◽

Shouguo Gao ◽

Carrie Diamond ◽

Sachiko Kajigaya ◽

Jinguo Chen ◽

...

Keyword(s):

Gene Expression ◽

Cell Cycle ◽

Stem Cells ◽

Chromosomal Abnormalities ◽

Single Cells ◽

Trisomy 8 ◽

Broad Perspective ◽

Hematopoietic Stem ◽

Gata2 Deficiency ◽

Additional Chromosomal Abnormalities

Abstract Constitutional GATA2 deficiency caused by heterozygous germline GATA2 mutations has a broad spectrum of clinical phenotypes, including systemic infections, lymphedema, cytopenias, and myeloid neoplasms. Genotype–phenotype correlation is not well understood mechanistically in GATA2 deficiency. We performed whole transcriptome sequencing of single hematopoietic stem and progenitor cells from 8 patients, who had pathogenic GATA2 mutations and myelodysplasia. Mapping patients’ cells onto normal hematopoiesis, we observed deficiency in lymphoid/myeloid progenitors, also evident from highly constrained gene correlations. HSPCs of patients exhibited distinct patterns of gene expression and coexpression compared with counterparts from healthy donors. Distinct lineages showed differently altered transcriptional profiles. Stem cells in patients had dysregulated gene expression related to apoptosis, cell cycle, and quiescence; increased expression of erythroid/megakaryocytic priming genes; and decreased lymphoid priming genes. The prominent deficiency in lympho-myeloid lineages in GATA2 deficiency appeared at least partly due to the expression of aberrant gene programs in stem cells prior to lineage commitment. We computationally imputed cells with chromosomal abnormalities and determined their gene expression; DNA repair genes were downregulated in trisomy 8 cells, potentially rendering these cells vulnerable to second-hit somatic mutations and additional chromosomal abnormalities. Cells with complex cytogenetic abnormalities showed defects in genes related to multilineage differentiation and cell cycle. Single-cell RNA sequencing is powerful in resolving transcriptomes of cell subpopulations despite a paucity of cells in marrow failure. Our study discloses previously uncharacterized transcriptome signatures of stem cells and progenitors in GATA2 deficiency, providing a broad perspective of potential mechanisms by which germline mutations modulate early hematopoiesis in a human disease. This trial was registered at www.clinicaltrials.gov as NCT01905826, NCT01861106, and NCT00001620.

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Spatially coordinated dynamic gene transcription in living pituitary tissue

eLife ◽

10.7554/elife.08494 ◽

2016 ◽

Vol 5 ◽

Cited By ~ 34

Author(s):

Karen Featherstone ◽

Kirsty Hey ◽

Hiroshi Momiji ◽

Anne V McNamara ◽

Amanda L Patist ◽

...

Keyword(s):

Gene Expression ◽

Single Cells ◽

Time Estimation ◽

Statistical Modelling ◽

Imaging Data ◽

Pituitary Tissue ◽

Transcriptional Dynamics ◽

Prolactin Gene ◽

Direct Cell ◽

Real Time Estimation

Transcription at individual genes in single cells is often pulsatile and stochastic. A key question emerges regarding how this behaviour contributes to tissue phenotype, but it has been a challenge to quantitatively analyse this in living cells over time, as opposed to studying snap-shots of gene expression state. We have used imaging of reporter gene expression to track transcription in living pituitary tissue. We integrated live-cell imaging data with statistical modelling for quantitative real-time estimation of the timing of switching between transcriptional states across a whole tissue. Multiple levels of transcription rate were identified, indicating that gene expression is not a simple binary ‘on-off’ process. Immature tissue displayed shorter durations of high-expressing states than the adult. In adult pituitary tissue, direct cell contacts involving gap junctions allowed local spatial coordination of prolactin gene expression. Our findings identify how heterogeneous transcriptional dynamics of single cells may contribute to overall tissue behaviour.

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Simultaneous in situ detection of beta-interferon mRNA and DNA in the same cell.

Journal of Histochemistry & Cytochemistry ◽

10.1177/37.5.2703705 ◽

1989 ◽

Vol 37 (5) ◽

pp. 697-701 ◽

Cited By ~ 2

Author(s):

F J Tang ◽

P O Ts'o ◽

S A Lesko

Keyword(s):

Gene Expression ◽

Cell Cycle ◽

In Situ Hybridization ◽

Single Cells ◽

Specific Gene ◽

Whole Cells ◽

Beta Interferon ◽

Ht1080 Cells ◽

In Situ Detection

We report a quantitative method that combines in situ mRNA hybridization with microfluorometric analysis of DNA content to detect gene expression in single cells of a heteroploid cell population. The model was a human fibrosarcoma HT1080 cell line which consisted of diploid and tetraploid cells that were induced with polyI:polyC for production of beta-interferon. The level of beta-interferon mRNA detected by in situ hybridization was found to be two to three times higher in tetraploid compared to diploid HT1080 cells, and correlated with beta-interferon activity in that a subclone of tetraploid HT1080 cells secreted two- to fivefold more beta-interferon than a subclone of diploid HT1080 cells. Interestingly, beta-interferon-related transcripts were detected during S-phase in uninduced tetraploid HT1080 cells. In addition, beta-interferon induced by polyI:polyC was expressed in all phases of the cell cycle as demonstrated with a human diploid fibroblast, HF926. The unique features offered by the combination of microfluorometry and in situ hybridization provide a valuable tool to investigate specific gene expression related to ploidy or cell-cycle stage in the same individual cell of an unsynchronized population. Since the method allows direct observation of morphology, one can be assured that all quantitative measurements were made on whole cells with intact nuclei.

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Spectral recording of gene expression history by fluorescent timer protein

BioTechniques ◽

10.2144/btn-2019-0050 ◽

2019 ◽

Vol 67 (4) ◽

pp. 154-164

Author(s):

Anna R Tröscher ◽

Barbara Werner ◽

Nadia Kaouane ◽

Wulf Haubensak

Keyword(s):

Gene Expression ◽

Fluorescent Proteins ◽

Single Cells ◽

Temporal Patterns ◽

Spectral Shift ◽

Early Gene ◽

Proof Of Concept ◽

Spatio Temporal ◽

Living Organisms ◽

Post Hoc

Monitoring spatio-temporal patterns of gene expression by fluorescent proteins requires longitudinal observation, which is often difficult to implement. Here, we fuse a fluorescent timer (FT) protein with an immediate early gene (IEG) promoter to track live gene expression in single cells. This results in a stimulus- and time-dependent spectral shift from blue to red for subsequent monitoring with fluorescence activated cell sorting (FACS) and live cell imaging. This spectral shift enables imputing the time point of activity post-hoc to dissociate early and late responders from a single snapshot in time. Thus, we provide a tool for tracking stimulus-driven IEG expression and demonstrate proof of concept exploiting promoter::FT fusions, adding new dimensions to experiments that require reconstructing spatio-temporal patterns of gene expression in cells, tissues or living organisms.

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The transcriptome dynamics of single cells during the cell cycle

10.1101/2019.12.23.887570 ◽

2019 ◽

Author(s):

Daniel Schwabe ◽

Sara Formichetti ◽

Jan Philipp Junker ◽

Martin Falcke ◽

Nikolaus Rajewsky

Keyword(s):

Gene Expression ◽

Cell Cycle ◽

Design Principle ◽

Single Cells ◽

High Dimensional ◽

Circular Trajectory ◽

Cellular Processes ◽

Cycling Gene ◽

Third Dimension ◽

Cell Data

AbstractDespite advances in single-cell data analysis, the dynamics and topology of the cell cycle in high-dimensional gene expression space remains largely unknown. Here, we use a linear analysis of transcriptome data to reveal that cells move along a circular trajectory in transcriptome space during the cell cycle. This movement occurs largely independently from other cellular processes. Non-cycling gene expression (changes in environment or epigenetic state) adds a third dimension and causes helical motion on a hollow cylinder. The circular trajectory shape indicates minimal acceleration of transcription, i.e. the cell cycle has evolved to minimize changes of transcriptional activity and its entailing regulatory effort. Thus, we uncover a general design principle of the cell cycle that may be of relevance to many other cellular differentiation processes.One Sentence SummaryCells traverse high-dimensional gene expression space in a 2D circular motion, thus minimizing changes of expression changes (“Acceleration”).

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Gene Expression Profiling of Mycosis Fungoides in Early and Tumor Stage—A Proof-of-Concept Study Using Laser Capture/Single Cell Microdissection and NanoString Analysis

Cells ◽

10.3390/cells10113190 ◽

2021 ◽

Vol 10 (11) ◽

pp. 3190

Author(s):

Justine Lai ◽

Jing Li ◽

Robert Gniadecki ◽

Raymond Lai

Keyword(s):

Gene Expression ◽

Single Cell ◽

Gene Expression Profiling ◽

Mycosis Fungoides ◽

Expression Profiling ◽

Single Cells ◽

Tumor Stage ◽

Proof Of Concept ◽

Opposite Pattern ◽

Laser Capture

A subset of patients with mycosis fungoides (MF) progress to the tumor stage, which correlates with a worse clinical outcome. The molecular events driving this progression are not well-understood. To identify the key molecular drivers, we performed gene expression profiling (GEP) using NanoString. Ten formalin-fixed/paraffin-embedded skin biopsies from six patients (six non-tumor and four tumor MF) were included; non-tumor and tumor samples were available in three patients. Laser capture/single cell microdissection of epidermotropic MF cells was used for non-tumor cases. We found that the RNA extracted from 700–800 single cells was consistently sufficient for GEP, provided that multiplexed target enrichment amplification was used. An un-supervised/hierarchical analysis revealed clustering of non-tumor and tumor cases. Many of the most upregulated or downregulated genes are implicated in the PI3K, RAS, cell cycle/apoptosis and MAPK pathways. Two of the targets, HMGA1 and PTPN11 (encodes SHP2), were validated using immunohistochemistry. HMGA1 was positive in six out of six non-tumor MF samples and negative in five out of five tumor MF samples. An opposite pattern was seen with SHP2. Our study has provided a proof-of-concept that single-cell microdissection/GEP can be applied to archival tissues. Some of our identified gene targets might be key drivers of the disease progression of MF.

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Sequential onset and concurrent expression of miR-9 genomic loci in single cells contributes to the temporal increase of mature miR-9 in zebrafish neurogenesis

10.1101/2020.08.03.233890 ◽

2020 ◽

Author(s):

X. Soto ◽

T. Minchington ◽

R. Lea ◽

J. Lee ◽

N Papalopulu

Keyword(s):

Gene Expression ◽

Neural Development ◽

Time Course ◽

Single Cells ◽

State Transitions ◽

Transcriptional Repressors ◽

Gene Expression Noise ◽

Her Family ◽

Rapid Changes ◽

Temporal And Spatial

AbstractGene expression oscillations of the Hes/Her family members of transcriptional repressors are important for cell state transitions during neural development. The input of miR-9 is necessary to constrain gene expression noise, allowing oscillations to occur and to be decoded by downstream genes. Hes/Her dynamics are sensitive to the amount of miR-9 present in the cell but the mechanism by which miR-9 is quantitatively controlled is not known. In vertebrates, there are several distinct genomic loci that produce the same mature miR-9, leading to a number of possibilities of how the production of mature miR-9 may be regulated.Here, we show that the expression of miR-9 increases spatially and temporarily over zebrafish development. A detailed time course of the expression of 7 pri-miR-9 genomic loci shows that they have distinct temporal and spatial profiles, which may be brought about by different numbers of E/N-boxes in their regulatory regions. Focusing on pairs that are expressed in the same area of the hindbrain region, namely pri-miR-9-1/pri-miR-9-4 and pri-miR-9-1/pri-miR-9-5, we find that they sequentially activated during neurogenesis, concurrent with a known change in Her6 dynamics from noisy to oscillatory. Analysis of expression at the single-cell level shows that although they are sequentially activated, early and late pri-miRs are mostly concurrently transcriptionally active in the same cells. This finding supports the idea that increased mature miR-9 is contributed, at least in part, by overlapping activation of distinct loci. We propose that this may lead to an additive, sharp, increase of mature miR-9 which in turn may lead to rapid changes in Her6 dynamics.

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Changes in dynamic transitions between integrated and segregated states underlie visual hallucinations in Parkinson's disease

10.1101/2021.06.21.449237 ◽

2021 ◽

Author(s):

Angeliki Zarkali ◽

Andrea Luppi ◽

Emmanuel A Stamatakis ◽

Suzanne Reeves ◽

Peter McColgan ◽

...

Keyword(s):

Gene Expression ◽

Visual Processing ◽

Temporal Dynamics ◽

Expression Profiles ◽

Receptor Gene ◽

Structural Connectivity ◽

Brain Regions ◽

State Transitions ◽

Visual Hallucinations ◽

Density Profiles

Background: Visual hallucinations in Parkinsons disease (PD) are transient, suggesting a change in dynamic brain states. However, the causes underlying these dynamic brain changes are not known. Methods: Focusing on fundamental network properties of integration and segregation, we used rsfMRI to examine alterations in temporal dynamics in PD patients with hallucinations (n=16) compared to those without hallucinations (n=75) and a group of normal controls (n=32). We used network control theory to examine how structural connectivity guides transitions between functional states. We then studied the brain regions most involved in these state transitions, and examined corresponding neurotransmitter density profiles and receptor gene expression in health. Results: There were significantly altered temporal dynamics in PD with hallucinations, with an increased proportion of time spent in the Segregated state compared to non-hallucinators and controls; less between-state transitions; and increased dwell time in the Segregated state. The energy cost needed to transition from integrated-to-segregated state was lower in PD-hallucinators compared to non-hallucinators. This was primarily driven by subcortical and transmodal cortical brain regions, including the thalamus and default mode network regions. The regional energy needed to transition from integrated-to-segregated state was significantly correlated with regional neurotransmitter density and gene expression profiles for serotoninergic (including 5HT2A), GABAergic, noradrenergic and cholinergic but not dopaminergic density profiles. Conclusions: We describe the patterns of temporal functional dynamics in PD-hallucinations, and link these with neurotransmitter systems involved in early sensory and complex visual processing. Our findings provide mechanistic insights into visual hallucinations in PD and highlighting potential therapeutic targets.

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Size-dependent increase in RNA Polymerase II initiation rates mediates gene expression scaling with cell size

10.1101/754788 ◽

2019 ◽

Cited By ~ 1

Author(s):

Xi-Ming Sun ◽

Anthony Bowman ◽

Miles Priestman ◽

Francois Bertaux ◽

Amalia Martinez-Segura ◽

...

Keyword(s):

Gene Expression ◽

Cell Cycle ◽

Fission Yeast ◽

Rna Polymerase Ii ◽

Cell Size ◽

Transcription Initiation ◽

Molecular Mechanisms ◽

Single Cells ◽

Yeast Cells ◽

Limiting Factor

ABSTRACTCell size varies during the cell cycle and in response to external stimuli. This requires the tight coordination, or “scaling”, of mRNA and protein quantities with the cell volume in order to maintain biomolecules concentrations and cell density. Evidence in cell populations and single cells indicates that scaling relies on the coordination of mRNA transcription rates with cell size. Here we use a combination of single-molecule fluorescence in situ hybridisation (smFISH), time-lapse microscopy and mathematical modelling in single fission yeast cells to uncover the precise molecular mechanisms that control transcription rates scaling with cell size. Linear scaling of mRNA quantities is apparent in single fission yeast cells during a normal cell cycle. Transcription rates of both constitutive and regulated genes scale with cell size without evidence for transcriptional bursting. Modelling and experimental data indicate that scaling relies on the coordination of RNAPII transcription initiation rates with cell size and that RNAPII is a limiting factor. We show using real-time quantitative imaging that size increase is accompanied by a rapid concentration independent recruitment of RNAPII onto chromatin. Finally, we find that in multinucleated cells, scaling is set at the level of single nuclei and not the entire cell, making the nucleus the transcriptional scaling unit. Integrating our observations in a mechanistic model of RNAPII mediated transcription, we propose that scaling of gene expression with cell size is the consequence of competition between genes for limiting RNAPII.

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