The coordinated spatial and temporal regulation of gene expression in the vertebrate neural tube determines the identity of neural progenitors and the function and physiology of the neurons they generate. Progress has been made deciphering the gene regulatory programmes that are responsible for this process; however, the complexity of the tissue has hampered the systematic analysis of the network and the underlying mechanisms. To address this, we used single cell mRNA sequencing to profile cervical and thoracic regions of the developing mouse neural tube between embryonic days 9.5-13.5. We confirmed that the data accurately recapitulates neural tube development, allowing us to identify new markers for specific progenitor and neuronal populations. In addition, the analysis highlighted a previously underappreciated temporal component to the mechanisms that generate neuronal diversity, and revealed common features in the sequence of transcriptional events that lead to the differentiation of specific neuronal subtypes. Together, the data offer insight into the mechanisms that are responsible for neuronal specification and provide a compendium of gene expression for classifying spinal cord cell types that will support future studies of neural tube development, function and disease.

Single cell transcriptomics reveals spatial and temporal dynamics of gene expression in the developing mouse spinal cord.

The vertebrate spinal cord comprises multiple functionally distinct neuronal cell types arranged in characteristic positions. During development, these different types of neurons differentiate from transcriptionally distinct neural progenitors that are arrayed in discrete domains along the dorsal-ventral and anterior-posterior axes of the embryonic spinal cord. This organization arises in response to morphogen gradients acting upstream of a gene regulatory network, the architecture of which determines the spatial and temporal pattern of gene expression. In recent years, substantial progress has been made in deciphering the regulatory network that underlies the specification of distinct progenitor and neuronal cell identities. In this Review, we outline how distinct neuronal cell identities are established in response to spatial and temporal patterning systems, and outline novel experimental approaches to study the emergence and function of neuronal diversity in the spinal cord.

/pdf/establishing-neuronal-diversity-in-the-spinal-cord-a-time-5fbo6ju72m.pdf

Establishing neuronal diversity in the spinal cord: a time and a place

Although many molecular mechanisms controlling developmental processes are evolutionarily conserved, the speed at which the embryo develops can vary substantially between species. For example, the same genetic program, comprising sequential changes in transcriptional states, governs the differentiation of motor neurons in mouse and human, but the tempo at which it operates differs between species. Using in vitro directed differentiation of embryonic stem cells to motor neurons, we show that the program runs more than twice as fast in mouse as in human. This is not due to differences in signaling, nor the genomic sequence of genes or their regulatory elements. Instead, there is an approximately two-fold increase in protein stability and cell cycle duration in human cells compared with mouse cells. This can account for the slower pace of human development and suggests that differences in protein turnover play a role in interspecies differences in developmental tempo.

Species-specific pace of development is associated with differences in protein stability

The coordinated spatial and temporal regulation of gene expression in the vertebrate neural tube determines the identity of neural progenitors and the function and physiology of the neurons they generate. Progress has been made deciphering the gene regulatory programmes responsible for this process, however, the complexity of the tissue has hampered the systematic analysis of the network and the underlying mechanisms. To address this, we used single cell mRNA sequencing to profile cervical and thoracic regions of the developing mouse neural tube between embryonic days (e)9.5-e13.5. We confirmed the data accurately recapitulates neural tube development, allowing us to identify new markers for specific progenitor and neuronal populations. In addition, the analysis highlighted a previously underappreciated temporal component to the mechanisms generating neuronal diversity and revealed common features in the sequence of transcriptional events that lead to the differentiation of specific neuronal subtypes. Together the data offer insight into the mechanisms responsible for neuronal specification and provide a compendium of gene expression for classifying spinal cord cell types that will support future studies of neural tube development, function, and disease.

https://www.biorxiv.org/content/biorxiv/early/2018/11/16/472415.full.pdf

Single cell transcriptomics reveals spatial and temporal dynamics of gene expression in the developing mouse spinal cord

Recent advances have enabled gene expression profiling of single cells at lower cost. As more data is produced there is an increasing need to integrate diverse datasets and better analyse underutilised data to gain biological insights. However, analysis of single cell RNA-seq data is challenging due to biological and technical noise which not only varies between laboratories but also between batches. Here for the first time, we apply a new generative deep learning approach called Generative Adversarial Networks (GAN) to biological data. We show that it is possible to integrate diverse skin (epidermal) datasets and in doing so, our generative model is able to simulate realistic scRNA-seq data that covers the full diversity of cell types. In contrast to many machine-learning approaches, we are able to interpret internal parameters in a biologically meaningful manner. These include using internal GAN learned features for improved dimensionality reduction. Using our generative model we are able to obtain a universal representation of epidermal differentiation and use this to predict the effect of cell state perturbations on gene expression at high time-resolution. We show that our trained neural networks identify biological state-determining genes and through analysis of these networks we can obtain inferred gene regulatory relationships. In combination these attributes provide a powerful framework to progress the analysis of scRNA-seq data beyond exploratory analysis of cell clusters and towards integration of multiple datasets regardless of origin.

pdf/generative-adversarial-networks-uncover-epidermal-regulators-3zmd0esmch.pdf

Generative adversarial networks uncover epidermal regulators and predict single cell perturbations

During tissue development, multipotent progenitors differentiate into specific cell types in characteristic spatial and temporal patterns. We address the mechanism linking progenitor identity and differentiation rate in the neural tube, where motor neuron (MN) progenitors differentiate more rapidly than other progenitors. Using single cell transcriptomics, we define the transcriptional changes associated with the transition of neural progenitors into MNs. Reconstruction of gene expression dynamics from these data indicate a pivotal role for the MN determinant Olig2 just prior to MN differentiation. Olig2 represses expression of the Notch signaling pathway effectors Hes1 and Hes5. Olig2 repression of Hes5 appears to be direct, via a conserved regulatory element within the Hes5 locus that restricts expression from MN progenitors. These findings reveal a tight coupling between the regulatory networks that control patterning and neuronal differentiation, and demonstrate how Olig2 acts as the developmental pacemaker coordinating the spatial and temporal pattern of MN generation.

https://www.biorxiv.org/content/biorxiv/early/2017/11/03/104307.full.pdf

Olig2 and Hes regulatory dynamics during motor neuron differentiation revealed by single cell transcriptomics

During tissue development, multipotent progenitors differentiate into specific cell types in characteristic spatial and temporal patterns. We addressed the mechanism linking progenitor identity and differentiation rate in the neural tube, where motor neuron (MN) progenitors differentiate more rapidly than other progenitors. Using single cell transcriptomics, we defined the transcriptional changes associated with the transition of neural progenitors into MNs. Reconstruction of gene expression dynamics from these data indicate a pivotal role for the MN determinant Olig2 just prior to MN differentiation. Olig2 represses expression of the Notch signaling pathway effectors Hes1 and Hes5. Olig2 repression of Hes5 appears to be direct, via a conserved regulatory element within the Hes5 locus that restricts expression from MN progenitors. These findings reveal a tight coupling between the regulatory networks that control patterning and neuronal differentiation and demonstrate how Olig2 acts as the developmental pacemaker coordinating the spatial and temporal pattern of MN generation.

/pdf/olig2-and-hes-regulatory-dynamics-during-motor-neuron-5gtbw18ekt.pdf

Olig2 and Hes regulatory dynamics during motor neuron differentiation revealed by single cell transcriptomics.

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Olig2 and Hes regulatory dynamics during motor neuron differentiation revealed by single cell transcriptomics

Olig2 and Hes regulatory dynamics during motor neuron differentiation revealed by single cell transcriptomics.