scholarly journals Runx2-Twist1 interaction coordinates cranial neural crest guidance of soft palate myogenesis

eLife ◽  
2021 ◽  
Vol 10 ◽  
Author(s):  
Xia Han ◽  
Jifan Feng ◽  
Tingwei Guo ◽  
Yong-Hwee Eddie Loh ◽  
Yuan Yuan ◽  
...  

Cranial neural crest (CNC) cells give rise to bone, cartilage, tendons, and ligaments of the vertebrate craniofacial musculoskeletal complex, as well as regulate mesoderm-derived craniofacial muscle development through cell-cell interactions. Using the mouse soft palate as a model, we performed an unbiased single-cell RNA-seq analysis to investigate the heterogeneity and lineage commitment of CNC derivatives during craniofacial muscle development. We show that Runx2, a known osteogenic regulator, is expressed in the CNC-derived perimysial and progenitor populations. Loss of Runx2 in CNC-derivatives results in reduced expression of perimysial markers (Aldh1a2 and Hic1) as well as soft palate muscle defects in Osr2-Cre;Runx2fl/fl mice. We further reveal that Runx2 maintains perimysial marker expression through suppressing Twist1, and that myogenesis is restored in Osr2-Cre;Runx2fl/fl;Twist1fl/+ mice. Collectively, our findings highlight the roles of Runx2, Twist1, and their interaction in regulating the fate of CNC-derived cells as they guide craniofacial muscle development through cell-cell interactions.

2019 ◽  
Author(s):  
Qianqian Song ◽  
Gregory A. Hawkins ◽  
Leonard Wudel ◽  
Ping-Chieh Chou ◽  
Elizabeth Forbes ◽  
...  

2019 ◽  
Author(s):  
Qianqian Song ◽  
Gregory A. Hawkins ◽  
Leonard Wudel ◽  
Ping-Chieh Chou ◽  
Elizabeth Forbes ◽  
...  

Development ◽  
1995 ◽  
Vol 121 (7) ◽  
pp. 2219-2232 ◽  
Author(s):  
R. Schnabel

During the first four cleavage rounds of the Caenorhabditis elegans embryo, five somatic founder cells AB, MS, E, C and D are born, which later form the tissues of the embryo. The classical criterion for a cell-autonomous specification of a tissue is the capability of primordial cells to produce this tissue in isolation from the remainder of the embryo. By this criterion, the somatic founder cells MS, C and D develop cell-autonomously. Laser ablation experiments, however, reveal that within the embryonic context these blastomeres form a network of duelling cellular interactions. During normal development, the blastomere D inhibits muscle specification in the MS and the C lineage inhibits muscle specification in the D lineage. These inhibitory interactions are counteracted by two activating inductions. As described before the inhibition of body wall muscle in MS is counteracted by an activating signal from the ABa lineage. Body wall muscle in the D lineage is induced by MS descendants, which suppress an inhibitory activity of the C lineage. The interaction between the D and the MS lineage occurs through the C lineage. An interesting feature of these cell-cell interactions is that they do not serve to discriminate between equivalent cells but are permissive or nonpermissive inductions. No evidence was found that the C-derived body wall muscle also depends on an induction, which suggests that possibly three different pathways coexist in the early embryo to specify body wall muscle, two of which are, in different ways, influenced by cell-cell interactions and a third that is autonomous. This work supplies evidence that cells may acquire transient states during embryogenesis that influence the specification of other cells in the embryo. These states, however, may not be reflected in the developmental potentials of the cells themselves. They can only be scored indirectly by their action on the specification of other cells in the embryo. Blastomeres that behave cell-autonomously in isolation are nevertheless subjected to cell-cell interactions in the embryonic context. Why this should be is an intriguing question. The classical notion has been that blastomeres are specified autonomously in nematodes. In recent years, it was established that at least five inductions are required to determine the AB descendants of C. elegans, whereas the P1 descendants have been typically viewed to develop more autonomously. It appears now that inductions also play a major role during the determination of P1-derived blastomeres.


Cell Reports ◽  
2018 ◽  
Vol 25 (6) ◽  
pp. 1458-1468.e4 ◽  
Author(s):  
Manu P. Kumar ◽  
Jinyan Du ◽  
Georgia Lagoudas ◽  
Yang Jiao ◽  
Andrew Sawyer ◽  
...  

Author(s):  
Dongshunyi Li ◽  
Jun Ding ◽  
Ziv Bar-Joseph

Abstract Motivation Recent technological advances enable the profiling of spatial single-cell expression data. Such data present a unique opportunity to study cell–cell interactions and the signaling genes that mediate them. However, most current methods for the analysis of these data focus on unsupervised descriptive modeling, making it hard to identify key signaling genes and quantitatively assess their impact. Results We developed a Mixture of Experts for Spatial Signaling genes Identification (MESSI) method to identify active signaling genes within and between cells. The mixture of experts strategy enables MESSI to subdivide cells into subtypes. MESSI relies on multi-task learning using information from neighboring cells to improve the prediction of response genes within a cell. Applying the methods to three spatial single-cell expression datasets, we show that MESSI accurately predicts the levels of response genes, improving upon prior methods and provides useful biological insights about key signaling genes and subtypes of excitatory neuron cells. Availability and implementation MESSI is available at: https://github.com/doraadong/MESSI


2001 ◽  
Vol 65 (3) ◽  
pp. 195-207 ◽  
Author(s):  
J.P. Hugnot ◽  
K. Mellodew ◽  
H. Pilcher ◽  
D. Uwanogho ◽  
J. Price ◽  
...  

2011 ◽  
Vol 60 (1) ◽  
pp. 57-68 ◽  
Author(s):  
Kyoko Oka ◽  
Masaki J. Honda ◽  
Eichi Tsuruga ◽  
Yuji Hatakeyama ◽  
Keitaro Isokawa ◽  
...  

2021 ◽  
Vol 15 ◽  
Author(s):  
Rachel A. Keuls ◽  
Ronald J. Parchem

Neural crest development involves a series of dynamic, carefully coordinated events that result in human disease when not properly orchestrated. Cranial neural crest cells acquire unique multipotent developmental potential upon specification to generate a broad variety of cell types. Studies of early mammalian neural crest and nervous system development often use the Cre-loxP system to lineage trace and mark cells for further investigation. Here, we carefully profile the activity of two common neural crest Cre-drivers at the end of neurulation in mice. RNA sequencing of labeled cells at E9.5 reveals that Wnt1-Cre2 marks cells with neuronal characteristics consistent with neuroepithelial expression, whereas Sox10-Cre predominantly labels the migratory neural crest. We used single-cell mRNA and single-cell ATAC sequencing to profile the expression of Wnt1 and Sox10 and identify transcription factors that may regulate the expression of Wnt1-Cre2 in the neuroepithelium and Sox10-Cre in the migratory neural crest. Our data identify cellular heterogeneity during cranial neural crest development and identify specific populations labeled by two Cre-drivers in the developing nervous system.


Cell Reports ◽  
2021 ◽  
Vol 37 (12) ◽  
pp. 110140
Author(s):  
David Tatarakis ◽  
Zixuan Cang ◽  
Xiaojun Wu ◽  
Praveer P. Sharma ◽  
Matthew Karikomi ◽  
...  

2020 ◽  
Author(s):  
M Tran ◽  
S Yoon ◽  
ST Min ◽  
S Andersen ◽  
K Devitt ◽  
...  

AbstractThe ability to study cancer-immune cell communication across the whole tumor section without tissue dissociation is important to understand molecular mechanisms of cancer immunotherapy and drug targets. Current experimental methods such as immunohistochemistry allow researchers to investigate a small number of cells or a limited number of ligand-receptor pairs at tissue scale with limited cellular resolution. In this work, we developed a powerful experimental and analytical pipeline that allows for the genome-wide discovery and targeted validation of cellular communication. By profiling thousands of genes, spatial transcriptomic and single-cell RNA sequencing data show genes that are possibly involved in interactions. The expression of the candidate genes could be visualized by single-molecule in situ hybridization and droplet digital PCR. We developed a computational pipeline called STRISH that enables us to quantitatively model cell-cell interactions by automatically scanning for local expression of RNAscope data to recapitulate an interaction landscape across the whole tissue. Furthermore, we showed the strong correlation of microscopic RNAscope imaging data analyzed by STRISH with the gene expression values measured by droplet digital PCR. We validated the unique ability of this approach to discover new cell-cell interactions in situ through analysis of two types of cancer, basal cell carcinoma and squamous cell carcinoma. We expect that the approach described here will help to discover and validate ligand receptor interactions in different biological contexts such as immune-cancer cell interactions within a tumor.


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