Simultaneous cellular and molecular phenotyping of embryonic mutants using single-cell regulatory trajectories
Developmental progression and cellular diversity are largely driven by transcription factors (TFs); yet, characterizing their loss-of-function phenotypes remains challenging and often disconnected from their underlying molecular mechanisms. Here, we combine single-cell regulatory genomics with loss-...
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| Hauptverfasser: | , , , , |
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| Dokumenttyp: | Article (Journal) |
| Sprache: | Englisch |
| Veröffentlicht: |
16 February 2022
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| In: |
Developmental cell
Year: 2022, Jahrgang: 57, Heft: 4, Pages: 496-511, e1-e8 |
| ISSN: | 1878-1551 |
| DOI: | 10.1016/j.devcel.2022.01.016 |
| Online-Zugang: | Verlag, lizenzpflichtig, Volltext: https://doi.org/10.1016/j.devcel.2022.01.016 Verlag, lizenzpflichtig, Volltext: https://www.sciencedirect.com/science/article/pii/S1534580722000557 
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| Verfasserangaben: | Stefano Secchia, Mattia Forneris, Tobias Heinen, Oliver Stegle, Eileen E.M. Furlong |
| Zusammenfassung: | Developmental progression and cellular diversity are largely driven by transcription factors (TFs); yet, characterizing their loss-of-function phenotypes remains challenging and often disconnected from their underlying molecular mechanisms. Here, we combine single-cell regulatory genomics with loss-of-function mutants to jointly assess both cellular and molecular phenotypes. Performing sci-ATAC-seq at eight overlapping time points during Drosophila mesoderm development could reconstruct the developmental trajectories of all major muscle types and reveal the TFs and enhancers involved. To systematically assess mutant phenotypes, we developed a single-nucleus genotyping strategy to process embryo pools of mixed genotypes. Applying this to four TF mutants could identify and quantify their characterized phenotypes de novo and discover new ones, while simultaneously revealing their regulatory input and mode of action. Our approach is a general framework to dissect the functional input of TFs in a systematic, unbiased manner, identifying both cellular and molecular phenotypes at a scale and resolution that has not been feasible before. |
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| Beschreibung: | Gesehen am 18.05.2022 |
| Beschreibung: | Online Resource |
| ISSN: | 1878-1551 |
| DOI: | 10.1016/j.devcel.2022.01.016 |