Cortical Development: Do progenitors play dice?
Understanding how the many different cell types that make up an adult organism emerge from the successive divisions of a single cell is a central question in biology. In particular, given the numerous random interactions that happen between and within cells (Vogt, 2015; Symmons and Raj, 2016; Hiesinger and Hassan, 2018), how do these multiple cell types reproducibly organize themselves into a robust body structure?
Consider the neocortex, a region of the brain that is involved in higher-order functions such as cognition and language. The neocortex contains a large number of different types of nerve cells called neurons, which are organized into six distinct layers. Neurons within each layer express specific genes and have distinct patterns of connections, which are key features for establishing proper brain circuitry (Jabaudon, 2017).
As the embryo develops, neurons are generated from mother cells called progenitors located below the neocortex: deep-layer neurons are born first, followed by superficial-layer neurons, in an 'inside-out' pattern during neocortical development. Although molecularly distinct mature neocortical neurons have been identified within each of the six layers (Tasic et al., 2016), a corresponding set of molecularly diverse neocortical progenitors has not been found (Telley et al., 2019). Thus, it remains unclear how exactly distinct neuron types emerge from a seemingly more uniform pool of progenitor cells.
Now, in eLife, Oscar Marín from King’s College London and co-workers – including Alfredo Llorca as first author – report that stochastic, random processes may explain how single progenitors are able to generate a wide range of neuron types (Llorca et al., 2019). The team – which includes researchers at King's College, the IST in Austria, the University of Freiburg and the University of Sussex – used three different techniques to genetically label progenitor cells, and then mapped the lineages (i.e. the neocortical clone) produced by each progenitor, focusing on progenitors that started generating neurons early during neocortical development. Of the clones that Llorca et al. were able to characterize, ~80% had daughter neurons in both the deep and superficial layers of the neocortex, while only ~20% had daughter neurons restricted to one of these two tiers. The neurons generated from individual progenitors also showed various axonal projection patterns and molecular identities, which corresponded to their layer position.
While this type of analyses has been done previously (Gao et al., 2014), these results provide important and thorough cross-validations of experimentally challenging approaches. In addition, Llorca et al. went one step further and developed mathematical models that could emulate their biological observations. They found that a model containing two types of progenitor cell which could randomly generate diverse ranges of neuron types was the best fit for their experimental results. These computer simulations suggest that a limited number of progenitors with a stochastic neuronal output can in principle account for the diverse clone types observed in the adult neocortex (Figure 1).
Stochastic events are critical for other developmental processes (Vogt, 2015; Symmons and Raj, 2016; Hiesinger and Hassan, 2018), including the fate choices of blood cell progenitors (Chang et al., 2008). However, distinguishing genuinely stochastic processes from unidentified deterministic processes is difficult. While modern technologies are becoming more sensitive, their signal-to-noise ratio is not infinite, which means that complex deterministic processes involving multiple factors can appear to be stochastic.
Although the stochastic hypothesis of Llorca et al. is based on simulations, it is provocative and raises exciting questions that can be experimentally tested. For example, can the two progenitor subtypes proposed by the model be molecularly identified? Do stochastic events occur within progenitors themselves or in their neuronal progenies? And when it comes to shaping the fate of a neuronal cell, what are the relative contributions of stochastic and deterministic processes?
Most importantly perhaps, this study highlights the limits of a reductionist, cell-by-cell description of neocortical and embryo development. If dynamic cellular features are predictable at a population rather than single-cell level, developmental processes may be most efficiently addressed by understanding the emergent properties of populations of cells rather than by a detailed account of their individual components.
References
-
The evolution of variability and robustness in neural developmentTrends in Neurosciences 41:577–586.https://doi.org/10.1016/j.tins.2018.05.007
-
Fate and freedom in developing neocortical circuitsNature Communications 8:16042.https://doi.org/10.1038/ncomms16042
-
Adult mouse cortical cell taxonomy revealed by single cell transcriptomicsNature Neuroscience 19:335–346.https://doi.org/10.1038/nn.4216
Article and author information
Author details
Publication history
- Version of Record published: January 17, 2020 (version 1)
Copyright
© 2020, Klingler and Jabaudon
This article is distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use and redistribution provided that the original author and source are credited.
Metrics
-
- 1,822
- Page views
-
- 283
- Downloads
-
- 7
- Citations
Article citation count generated by polling the highest count across the following sources: Crossref, PubMed Central, Scopus.
Download links
Downloads (link to download the article as PDF)
Open citations (links to open the citations from this article in various online reference manager services)
Cite this article (links to download the citations from this article in formats compatible with various reference manager tools)
Further reading
-
- Developmental Biology
- Neuroscience
Down syndrome (DS) is characterized by skeletal and brain structural malformations, cognitive impairment, altered hippocampal metabolite concentration and gene expression imbalance. These alterations were usually investigated separately, and the potential rescuing effects of green tea extracts enriched in epigallocatechin-3-gallate (GTE-EGCG) provided disparate results due to different experimental conditions. We overcame these limitations by conducting the first longitudinal controlled experiment evaluating genotype and GTE-EGCG prenatal chronic treatment effects before and after treatment discontinuation. Our findings revealed that the Ts65Dn mouse model reflected the pleiotropic nature of DS, exhibiting brachycephalic skull, ventriculomegaly, neurodevelopmental delay, hyperactivity, and impaired memory robustness with altered hippocampal metabolite concentration and gene expression. GTE-EGCG treatment modulated most systems simultaneously but did not rescue DS phenotypes. On the contrary, the treatment exacerbated trisomic phenotypes including body weight, tibia microarchitecture, neurodevelopment, adult cognition, and metabolite concentration, not supporting the therapeutic use of GTE-EGCG as a prenatal chronic treatment. Our results highlight the importance of longitudinal experiments assessing the co-modulation of multiple systems throughout development when characterizing preclinical models in complex disorders and evaluating the pleiotropic effects and general safety of pharmacological treatments.
-
- Developmental Biology
- Neuroscience
Mammals harbor a limited number of sound-receptor hair cells (HCs) that cannot be regenerated after damage. Thus, investigating the underlying molecular mechanisms that maintain HC survival is crucial for preventing hearing impairment. Intriguingly, Pou4f3-/- or Gfi1-/- HCs form initially but then rapidly degenerate, whereas Rbm24-/- HCs degenerate considerably later. However, the transcriptional cascades involving Pou4f3, Gfi1, and Rbm24 remain undescribed. Here, we demonstrate that Rbm24 expression is completely repressed in Pou4f3-/- HCs but unaltered in Gfi1-/- HCs, and further that the expression of both POU4F3 and GFI1 is intact in Rbm24-/- HCs. Moreover, by using in vivo mouse transgenic reporter assays, we identify three Rbm24 enhancers to which POU4F3 binds. Lastly, through in vivo genetic testing of whether Rbm24 restoration alleviates the degeneration of Pou4f3-/- HCs, we show that ectopic Rbm24 alone cannot prevent Pou4f3-/- HCs from degenerating. Collectively, our findings provide new molecular and genetic insights into how HC survival is regulated.