Search bioRxiv⌕ Search

bioRxiv · 10.1101/2023.11.09.566464

A Proximal Sox2 Enhancer Cluster is Required for the Anterior Regional Identity of Neural Progenitors

Abstract

Embryonic development depends on spatially and temporally orchestrated gene regulatory networks. Expressed in neural stem and progenitor cells (NSPCs), the transcription factor sex-determining region Y box 2 (Sox2) is critical for embryogenesis and stem cell maintenance in neural development. Whereas Sox2 is regulated by a distal cluster of enhancers in embryonic stem cells (ESCs), enhancers closer to the gene have been implicated in Sox2 transcriptional regulation in the neural lineage. Using functional genomics data, and deletion analysis we show that a downstream enhancer cluster regulates Sox2 transcription in NSPCs derived from mouse ESCs. By generating allelic mutants using CRISPR-Cas9 mediated deletions, we show that this proximal enhancer cluster, termed Sox2 regulatory regions 2-18 (SRR2-18), is a cis regulator of Sox2 transcription during neural differentiation. Transcriptome analyses demonstrate that loss of even one copy of SRR2-18 disrupts the region-specific identity of NSPCs. Biallelic deletion of this Sox2 neural enhancer cluster causes reduced SOX2 protein, less frequent interaction with transcriptional machinery, and leads to perturbed chromatin accessibility genome-wide further affecting the expression of neurodevelopmental and anterior-posterior regionalization genes. Furthermore, homozygous NSPC deletants exhibit self-renewal defects and impaired differentiation into cell types found in the brain. Altogether, our data define a cis-regulatory enhancer cluster controlling Sox2 transcription in NSPCs and highlight the sensitivity of neural differentiation processes to decreased Sox2 transcription, which influences their differentiation into posterior neural fates, specifically the caudal neural tube.

Source connections

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Tobias, I. C., Moorthy, S. D., Shchuka, V. M., Langroudi, L., Gillespie, Z. E., Duncan, A. G., Tian, R., Cherednychenko, M., Gajewska, N. A., Di Roberto, R. B., Mitchell, J. A.. 2023-11-10. A Proximal Sox2 Enhancer Cluster is Required for the Anterior Regional Identity of Neural Progenitors. https://doi.org/10.1101/2023.11.09.566464

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related preprints

Generation of a transgenic cephalopod

Coleoid cephalopods (cuttlefish, octopus, and squid) are marine mollusks with elaborate nervous systems that support a diverse repertoire of complex behaviors. These include the neural control of the color, pattern, and texture of the skin, facilitating both adaptive camouflage and innate patterning that may reflect internal state. The development of transgenic cephalopods expressing fluorescent proteins, optogenetic actuators, and reporters of neural activity would contribute a new and important technology to cephalopod biology. The generation of transgenic cephalopods, however, has remained a major challenge. Here, we report the development of stable transgenic dwarf cuttlefish (Ascarosepion bandense) expressing ubiquitous nuclear-localized mScarlet, a red fluorescent protein. We evaluated multiple strategies for transgenesis, and established cuttlefish lines using both CRISPR and the transposons Sleeping Beauty and Minos. The stable expression of transgenes enabled live imaging of cell dynamics during embryonic development. The Minos transposon emerged as the most efficient transgenesis strategy and is adaptable to promoters and transgenes of choice. These strategies now enable the generation of diverse genetic tools for mechanistic studies of cephalopod biology.

genetics↗

Large language model-based bibliometric evaluation of population descriptors in human genetics

As the use of population descriptors such as race, ethnicity, and ancestry have become increasingly common in modern genetics research, there have been growing calls to critically examine their use. Most notably, in 2023, the National Academies of Science, Engineering, and Medicine (NASEM) published a report titled Using Population Descriptors in Genetics and Genomics Research: A New Framework for an Evolving Field, which included eight specific and actionable recommendations for researchers to implement the ethical and accurate use of population descriptors in genetic research. Here, we use the 2023 NASEM report as a benchmark to analyze the use of population descriptors in genome-wide association studies (GWAS). We develop a general toolkit for large language model-based bibliometrics, operationalize the report's recommendations into an evaluation framework, and apply this framework to evaluate all 4,007 papers from the GWAS Catalog published between 2007 and 2025 with full text available on PubMedCentral. We find significant improvements in adherence to NASEM report recommendations over time. However, most improvements predate the publication of the NASEM report itself, suggesting the report functioned primarily as a synthesis of existing best practices rather than a catalyst for change. We conclude by highlighting opportunities for growth in the field of human genetics.

genetics↗

Mitigating biases of rescaling in forward-in-time population genetic simulations

Forward-in-time population genetic simulations are widely used in evolutionary analyses, but simulating large populations and long genomic regions remains computationally demanding. To reduce this cost, parameter rescaling is widely employed, in which the original evolutionary process is approximated by one with a smaller population size and fewer generations. Recently, several studies using the SLiM simulator have raised concerns about the accuracy of this rescaling approach. In this study, we show that many of the biases reported in these studies can be mitigated by using a different simulation algorithm. These results reveal that the accuracy of parameter rescaling depends on how well the simulation algorithm preserves diffusion-limit properties under rescaling.

genetics↗