Regulation of proneural gene expression and cell fate during neuroblast segregation in the Drosophila embryo

The Drosophila embryonic central nervous system develops from sets of progenitor neuroblasts which segregate from the neuroectoderm during early embryogenesis. Cells within this region can follow either the neural or epidermal developmental pathway, a decision guided by two opposing classes of genes. The proneural genes, including the members of the achaete-scute complex (AS-C), promote neurogenesis, while the neurogenic genes prevent neurogenesis and facilitate epidermal development. To understand the role that proneural gene expression and regulation play in the choice between neurogenesis and epidermogenesis, we examined the temporal and spatial expression pattern of the achaete (ac) regulatory protein in normal and neurogenic mutant embryos. The ac protein is first expressed in a repeating pattern of four ectodermal cell clusters per hemisegment. Even though 5–7 cells initially express ac in each cluster, only one, the neuroblast, continues to express ac. The repression of ac in the remaining cells of the cluster requires zygotic neurogenic gene function. In embryos lacking any one of five genes, the restriction of ac expression to single cells does not occur; instead, all cells of each cluster continue to express ac, enlarge, delaminate and become neuroblasts. It appears that one key function of the neurogenic genes is to silence proneural gene expression within the nonsegregating cells of the initial ectodermal clusters, thereby permitting epidermal development.

Download Full-text

Genes that control dorsoventral polarity affect gene expression along the anteroposterior axis of the Drosophila embryo

Development ◽

10.1242/dev.99.3.327 ◽

1987 ◽

Vol 99 (3) ◽

pp. 327-332 ◽

Cited By ~ 1

Author(s):

S.B. Carroll ◽

G.M. Winslow ◽

V.J. Twombly ◽

M.P. Scott

Keyword(s):

Gene Expression ◽

Cell Fate ◽

Maternal Effect ◽

Positional Information ◽

Drosophila Embryo ◽

Dorsoventral Polarity ◽

Anteroposterior Axis ◽

Positional Marker ◽

Control Pattern ◽

The Relationship

At least 13 genes control the establishment of dorsoventral polarity in the Drosophila embryo and more than 30 genes control the anteroposterior pattern of body segments. Each group of genes is thought to control pattern formation along one body axis, independently of the other group. We have used the expression of the fushi tarazu (ftz) segmentation gene as a positional marker to investigate the relationship between the dorsoventral and anteroposterior axes. The ftz gene is normally expressed in seven transverse stripes. Changes in the striped pattern in embryos mutant for other genes (or progeny of females homozygous for maternal-effect mutations) can reveal alterations of cell fate resulting from such mutations. We show that in the absence of any of ten maternal-effect dorsoventral polarity gene functions, the characteristic stripes of ftz protein are altered. Normally there is a difference between ftz stripe spacing on the dorsal and ventral sides of the embryo; in dorsalized mutant embryos the ftz stripes appear to be altered so that dorsal-type spacing occurs on all sides of the embryo. These results indicate that cells respond to dorsoventral positional information in establishing early patterns of gene expression along the anteroposterior axis and that there may be more significant interactions between the different axes of positional information than previously determined.

Download Full-text

Shaping development by stochasticity and dynamics in gene regulation

Open Biology ◽

10.1098/rsob.170030 ◽

2017 ◽

Vol 7 (5) ◽

pp. 170030 ◽

Cited By ~ 8

Author(s):

Peng Dong ◽

Zhe Liu

Keyword(s):

Gene Expression ◽

Gene Regulation ◽

Single Cell ◽

Cell Fate ◽

Single Molecule ◽

Large Scale ◽

Single Cells ◽

Individual Gene ◽

Functional Specification ◽

Spatio Temporal

Animal development is orchestrated by spatio-temporal gene expression programmes that drive precise lineage commitment, proliferation and migration events at the single-cell level, collectively leading to large-scale morphological change and functional specification in the whole organism. Efforts over decades have uncovered two ‘seemingly contradictory’ mechanisms in gene regulation governing these intricate processes: (i) stochasticity at individual gene regulatory steps in single cells and (ii) highly coordinated gene expression dynamics in the embryo. Here we discuss how these two layers of regulation arise from the molecular and the systems level, and how they might interplay to determine cell fate and to control the complex body plan. We also review recent technological advancements that enable quantitative analysis of gene regulation dynamics at single-cell, single-molecule resolution. These approaches outline next-generation experiments to decipher general principles bridging gaps between molecular dynamics in single cells and robust gene regulations in the embryo.

Download Full-text

Influence of Drosophila ventral epidermal development by the CNS midline cells and spitz class genes

Development ◽

10.1242/dev.118.3.893 ◽

1993 ◽

Vol 118 (3) ◽

pp. 893-901 ◽

Cited By ~ 15

Author(s):

S.H. Kim ◽

S.T. Crews

Keyword(s):

Gene Expression ◽

Drosophila Melanogaster ◽

Cell Fate ◽

Epidermal Cell ◽

Gene Function ◽

Gene Expression Analysis ◽

Cns Midline ◽

Midline Cells ◽

Enhancer Trap Lines ◽

Epidermal Development

The ventral epidermis of Drosophila melanogaster is derived from longitudinal rows of ectodermal precursor cells that divide and expand to form the ventral embryonic surface. The spitz class genes are required for the proper formation of the larval ventral cuticle. Using a group of enhancer trap lines that stain subsets of epidermal cells, it is shown here that spitz class gene function is necessary for ventral epidermal development and gene expression. Analysis of single-minded mutant embryos implies that ventral epidermal cell fate is influenced by the CNS midline cells.

Download Full-text

Timing of gene expression in a cell-fate decision system

10.1101/197103 ◽

2017 ◽

Author(s):

Delphine Aymoz ◽

Carme Solé ◽

Jean-Jerrold Pierre ◽

Marta Schmitt ◽

Eulàlia de Nadal ◽

...

Keyword(s):

Gene Expression ◽

Cell Fate ◽

Mapk Pathway ◽

Single Cells ◽

Cell Fate Decision ◽

Decision System ◽

Mating Partner ◽

Mating Pathway ◽

Fate Decision ◽

Kinetics Of

AbstractDuring development, morphogens provide extracellular cues allowing cells to select a specific fate by inducing complex transcriptional programs. The mating pathway in budding yeast offers simplified settings to understand this process. Pheromone secreted by the mating partner triggers the activity of a MAPK pathway, which results in the expression of hundreds of genes. Using a dynamic expression reporter, we quantified the kinetics of gene expression in single cells upon exogenous pheromone stimulation and in the physiological context of mating. In both conditions, we observed striking differences in the timing of induction of mating-responsive promoters. Biochemical analyses and generation of synthetic promoter variants demonstrated how the interplay between transcription factor binding and nucleosomes contribute to determine the kinetics of transcription in a simplified cell-fate decision system.One Sentence SummaryQuantitative and dynamic single cell measurements in the yeast mating pathway uncover a complex temporal orchestration of gene expression events.

Download Full-text

Mapping Vector Field of Single Cells

10.1101/696724 ◽

2019 ◽

Cited By ~ 10

Author(s):

Xiaojie Qiu ◽

Yan Zhang ◽

Dian Yang ◽

Shayan Hosseinzadeh ◽

Li Wang ◽

...

Keyword(s):

Gene Expression ◽

Vector Field ◽

Cell Fate ◽

Single Cells ◽

Mathematical Framework ◽

Cell State ◽

Global Mapping ◽

A Cell ◽

Short Time

AbstractUnderstanding how gene expression in single cells progress over time is vital for revealing the mechanisms governing cell fate transitions. RNA velocity, which infers immediate changes in gene expression by comparing levels of new (unspliced) versus mature (spliced) transcripts (La Manno et al. 2018), represents an important advance to these efforts. A key question remaining is whether it is possible to predict the most probable cell state backward or forward over arbitrary time-scales. To this end, we introduce an inclusive model (termed Dynamo) capable of predicting cell states over extended time periods, that incorporates promoter state switching, transcription, splicing, translation and RNA/protein degradation by taking advantage of scRNA-seq and the co-assay of transcriptome and proteome. We also implement scSLAM-seq by extending SLAM-seq to plate-based scRNA-seq (Hendriks et al. 2018; Erhard et al. 2019; Cao, Zhou, et al. 2019) and augment the model by explicitly incorporating the metabolic labelling of nascent RNA. We show that through careful design of labelling experiments and an efficient mathematical framework, the entire kinetic behavior of a cell from this model can be robustly and accurately inferred. Aided by the improved framework, we show that it is possible to reconstruct the transcriptomic vector field from sparse and noisy vector samples generated by single cell experiments. The reconstructed vector field further enables global mapping of potential landscapes that reflects the relative stability of a given cell state, and the minimal transition time and most probable paths between any cell states in the state space. This work thus foreshadows the possibility of predicting long-term trajectories of cells during a dynamic process instead of short time velocity estimates. Our methods are implemented as an open source tool, dynamo (https://github.com/aristoteleo/dynamo-release).

Download Full-text

True time series of gene expression from multinucleate single cells reveal essential information on the regulatory dynamics of cell differentiation

10.1101/2020.09.16.299578 ◽

2020 ◽

Author(s):

Anna Pretschner ◽

Sophie Pabel ◽

Markus Haas ◽

Monika Heiner ◽

Wolfgang Marwan

Keyword(s):

Gene Expression ◽

Time Series ◽

Cell Differentiation ◽

Markov Chains ◽

Cell Fate ◽

Single Cells ◽

Expression Patterns ◽

Essential Information ◽

Cell Fate Decisions ◽

True Time

AbstractDynamics of cell fate decisions are commonly investigated by inferring temporal sequences of gene expression states by assembling snapshots of individual cells where each cell is measured once. Ordering cells according to minimal differences in expression patterns and assuming that differentiation occurs by a sequence of irreversible steps, yields unidirectional, eventually branching Markov chains with a single source node. In an alternative approach, we used multinucleate cells to follow gene expression taking true time series. Assembling state machines, each made from single-cell trajectories, gives a network of highly structured Markov chains of states with different source and sink nodes including cycles, revealing essential information on the dynamics of regulatory events. We argue that the obtained networks depict aspects of the Waddington landscape of cell differentiation and characterize them as reachability graphs that provide the basis for the reconstruction of the underlying gene regulatory network.

Download Full-text

Highly multiplexed spatially resolved gene expression profiling of mouse organogenesis

10.1101/2020.11.20.391896 ◽

2020 ◽

Author(s):

T. Lohoff ◽

S. Ghazanfar ◽

A. Missarova ◽

N. Koulena ◽

N. Pierson ◽

...

Keyword(s):

Gene Expression ◽

High Resolution ◽

Single Cell ◽

Cell Fate ◽

Target Genes ◽

Single Cells ◽

Spatial Context ◽

Sequencing Data ◽

Cell Fate Decisions ◽

Spatially Resolved

AbstractTranscriptional and epigenetic profiling of single-cells has advanced our knowledge of the molecular bases of gastrulation and early organogenesis. However, current approaches rely on dissociating cells from tissues, thereby losing the crucial spatial context that is necessary for understanding cell and tissue interactions during development. Here, we apply an image-based single-cell transcriptomics method, seqFISH, to simultaneously and precisely detect mRNA molecules for 387 selected target genes in 8-12 somite stage mouse embryo tissue sections. By integrating spatial context and highly multiplexed transcriptional measurements with two single-cell transcriptome atlases we accurately characterize cell types across the embryo and demonstrate how spatially-resolved expression of genes not profiled by seqFISH can be imputed. We use this high-resolution spatial map to characterize fundamental steps in the patterning of the midbrain-hindbrain boundary and the developing gut tube. Our spatial atlas uncovers axes of resolution that are not apparent from single-cell RNA sequencing data – for example, in the gut tube we observe early dorsal-ventral separation of esophageal and tracheal progenitor populations. In sum, by computationally integrating high-resolution spatially-resolved gene expression maps with single-cell genomics data, we provide a powerful new approach for studying how and when cell fate decisions are made during early mammalian development.

Download Full-text

Neurogenic genes control gene expression at the transcriptional level in early neurogenesis and in mesectoderm specification

Development ◽

10.1242/dev.121.1.219 ◽

1995 ◽

Vol 121 (1) ◽

pp. 219-224 ◽

Cited By ~ 7

Author(s):

M.D. Martin-Bermudo ◽

A. Carmena ◽

F. Jimenez

Keyword(s):

Posttranscriptional Regulation ◽

Drosophila Embryo ◽

Transcriptional Level ◽

Proneural Gene ◽

Proneural Genes ◽

Protein Levels ◽

Neurogenic Genes ◽

The Central Nervous System ◽

Early Neurogenesis ◽

The Relationship

The development of the central nervous system in the Drosophila embryo is initiated by the acquisition of neural potential by clusters of ectodermal cells, promoted by the activity of proneural genes. Proneural gene function is antagonized by neurogenic genes, resulting in the realization of the neural potential in a single cell per cluster. To analyse the relationship between proneural and neurogenic genes, we have studied, in specific proneural clusters and neuroblasts of wild-type and neurogenic mutants embryos, the expression at the RNA and protein levels of lethal of scute, the most important known proneural gene in central neurogenesis. We find that the restriction of lethal of scute expression that accompanies the restriction of the neural potential to the delaminating neuroblast is regulated at the transcriptional level by neurogenic genes. These genes, however, do not control the size of proneural clusters. Moreover, available antibodies do not provide evidence for an hypothetical posttranscriptional regulation of proneural proteins by neurogenic genes. We also find that neurogenic genes are required for the specification of the mesectoderm. This has been shown for neuralized and Notch, and could also be the case for Delta and for the Enhancer of split gene complex. Neurogenic genes would control at the transcriptional level the repression of proneural genes and the activation of single-minded in the anlage of the mesectoderm.

Download Full-text

Gene Regulatory Networks Governing Hematopoietic Stem Cell Development and Identity

Blood ◽

10.1182/blood.v118.21.sci-30.sci-30 ◽

2011 ◽

Vol 118 (21) ◽

pp. SCI-30-SCI-30 ◽

Cited By ~ 1

Author(s):

Tariq Enver

Keyword(s):

Gene Expression ◽

Cell Fate ◽

Single Cells ◽

Transcriptional Regulators ◽

Gata Factor ◽

Hematopoietic Stem ◽

Cell Fate Decisions ◽

Genome Wide ◽

A Genome ◽

Custom Made

Abstract Abstract SCI-30 Several studies have addressed questions about transcriptional regulation within particular hematopoietic cell compartments. Few, however, have attempted to capture the transcriptional changes that occur during the dynamic transition from one compartment to another. We have profiled gene expression as multipotential progenitors underwent commitment and differentiation to two alternative lineages, focusing on the first 3 days of differentiation when the majority of decisions about cell fate are made. We have combined this with genome-wide identification of the targets of three key transcription factors before and after differentiation; GATA-2, usually associated with the stem/progenitor compartment; GATA-1 (erythroid); and PU.1 (myeloid). These data have been compiled into a custom-made queryable database, designed to be intuitive to use and to provide tools to interrogate the data on many levels. We used correlation analyses to associate transcription factor binding with particular modules of co-expressed genes, alongside detailed sequence analysis of bound regions. These approaches have informed our understanding of GATA factor switching, and highlighted novel roles for both GATA-2 and Pu.1 in erythroid cells. Overall, the data reveal greater degree of complexity in the interplay between these three factors in regulating hematopoiesis than has hitherto been described, and highlights the importance of a genome-wide approach to understanding complex regulatory systems. A significant challenge in the field is how to relate these types of population-based data to the action of transcriptional regulators within single cells where cell fate decisions ultimately are affected. As a step toward this, we have generated single cell profiles of gene expression for a limited set of transcriptional regulators in self-renewing and committed blood cells and used these data to build a stochastic computational model, which affords exploration of commitment scenarios in silico. Disclosures: No relevant conflicts of interest to declare.

Download Full-text

Forecasting when cells die during antibiotic exposure using stochastic gene expression

10.1101/494161 ◽

2018 ◽

Cited By ~ 1

Author(s):

Nicholas A. Rossi ◽

Imane El Meouche ◽

Mary J. Dunlop

Keyword(s):

Gene Expression ◽

Single Cell ◽

Cell Fate ◽

Single Cells ◽

Strong Relationship ◽

Antibiotic Exposure ◽

Survival Times ◽

Time To Death ◽

Cellular Processes ◽

Expression Of Genes

AbstractAntibiotic killing does not occur at a single, precise time for all cells within a population. Variability in time to death can be caused by stochastic expression of genes, resulting in differences in endogenous stress-resistance levels between individual cells in a population. This variability can be part of a bet-hedging strategy where cells leverage noise to ensure a subset of the population can tolerate the drug, while decreasing the overall cost of expressing resistance genes. We asked whether single-cell differences in gene expression prior to antibiotic addition were related to cell survival times after antibiotic exposure for a range of genes of diverse function. We quantified the time to death of single cells under antibiotic exposure in combination with expression of reporters. For some reporters, the time to cell death had a strong relationship with the initial expression level of the genes. Reporters that could forecast cell fate included stress response genes, but also genes involved in a variety of other cellular processes like metabolism. Our results highlight the single-cell level non-uniformity of antibiotic killing and also provide examples of key genes where cell-to-cell variation in expression prior to antibiotic exposure is strongly linked to extended durations of antibiotic survival.

Download Full-text