| Autor: |
Sanjeev S. Ranade, Sean Whalen, Ivana Zlatanova, Tomohiro Nishino, Benjamin van Soldt, Lin Ye, Angelo Pelonero, Langley Grace Wallace, Yu Huang, Michael Alexanian, Arun Padmanabhan, Barbara Gonzalez-Teran, Pawel Przytycki, Mauro W. Costa, Casey A. Gifford, Brian L. Black, Katherine S. Pollard, Deepak Srivastava |
| Rok vydání: |
2022 |
| Popis: |
Communication between myriad cell types during organ formation underlies proper morphogenesis1. In cardiac development, reciprocal signaling between mesoderm progenitors and neural crest cells is essential, and its disruption leads to congenital heart malformations, the most common human birth defect. However, mechanistic interrogation of temporal gene networks andcisregulatory elements in this crosstalk is limited2,3. Here, we integrated single cell chromatin accessibility and transcriptomics to establish an unbiased and temporal epigenomic map of the embryonic mouse heart over multiple stages and developed machine learning models to predict enhancers for heart and neural crest. We leveraged these advances to determine the consequences of dysregulated signaling at single cell resolution caused by deletion of TBX1, a transcription factor that causes morphogenetic defects of the cardiac outflow tract in humans and functions non-cell autonomously in cardiac mesodermal progenitors to direct pharyngeal neural crest differentiation4–6. Loss of Tbx1 in mice led to broad closure of chromatin regions enriched in cardiac progenitor transcription factor motifs within a narrow subset of cardiac mesodermal progenitors and correlated with diminished expression of numerous members of the fibroblast growth factor, retinoic acid, Notch and Semaphorin pathways. In affected progenitors, ectopic accessibility and expression of posterior heart field factors in the anterior heart field suggested impaired axial patterning. In response, a subset of cardiac neural crest cells displayed epigenomic and transcriptional defects, indicating a failure of differentiation corresponding to dysregulation of the anterior-posterior gradient of pharyngeal Hox gene expression. This study demonstrates that single-cell genomics and machine learning can generate a mechanistic model for how disruptions in cell communication selectively affect spatiotemporally dynamic regulatory networks in cardiogenesis. |
| Databáze: |
OpenAIRE |
| Externí odkaz: |
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