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Discovery of progenitor cell signatures by time-series synexpression analysis during Drosophila embryonic cell immortalization.


ABSTRACT: The use of time series profiling to identify groups of functionally related genes (synexpression groups) is a powerful approach for the discovery of gene function. Here we apply this strategy during Ras(V12) immortalization of Drosophila embryonic cells, a phenomenon not well characterized. Using high-resolution transcriptional time-series datasets, we generated a gene network based on temporal expression profile similarities. This analysis revealed that common immortalized cells are related to adult muscle precursors (AMPs), a stem cell-like population contributing to adult muscles and sharing properties with vertebrate satellite cells. Remarkably, the immortalized cells retained the capacity for myogenic differentiation when treated with the steroid hormone ecdysone. Further, we validated in vivo the transcription factor CG9650, the ortholog of mammalian Bcl11a/b, as a regulator of AMP proliferation predicted by our analysis. Our study demonstrates the power of time series synexpression analysis to characterize Drosophila embryonic progenitor lines and identify stem/progenitor cell regulators.

SUBMITTER: Dequeant ML 

PROVIDER: S-EPMC4620889 | biostudies-literature | 2015 Oct

REPOSITORIES: biostudies-literature

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Discovery of progenitor cell signatures by time-series synexpression analysis during Drosophila embryonic cell immortalization.

Dequéant Mary-Lee ML   Fagegaltier Delphine D   Hu Yanhui Y   Spirohn Kerstin K   Simcox Amanda A   Hannon Gregory J GJ   Perrimon Norbert N  

Proceedings of the National Academy of Sciences of the United States of America 20151005 42


The use of time series profiling to identify groups of functionally related genes (synexpression groups) is a powerful approach for the discovery of gene function. Here we apply this strategy during Ras(V12) immortalization of Drosophila embryonic cells, a phenomenon not well characterized. Using high-resolution transcriptional time-series datasets, we generated a gene network based on temporal expression profile similarities. This analysis revealed that common immortalized cells are related to  ...[more]

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