Biology OpenDevelopmental BiologyPeer-reviewed journal article
SRRM2 splicing factor modulates cell fate in early development
Sílvia CarvalhoiD, Luna Zea-RedondoiD, Tsz Ching Chloe TangiD, Philipp Stachel-BraumiD, Duncan C. MilleriD, Paulo CaldasiD, Alexander KukaleviD, Sebastian DieckeiD, Stefanie GrosswendtiD, Ana Rita GrossoiD, Ana PomboiD
Abstract
Embryo development is an orchestrated process that relies on tight regulation of gene expression to guide cell differentiation and fate decisions. Alternative splicing is modulated during development as an additional layer of regulation to reprogram gene expression patterns. The Srrm2 splicing factor has recently been implicated in developmental disorders and diseases, but its role in early mammalian development remains unexplored. Here, we show that Srrm2 dosage is critical for maintaining embryonic stem cell pluripotency and cell identity. Srrm2 heterozygosity promotes loss of stemness, characterized by the coexistence of cells expressing naive and formative pluripotency markers, together with extensive changes in gene expression, including genes regulated by serum- response transcription factor and differentiation-related genes. Depletion of Srrm2 by RNA interference in embryonic stem cells shows that the earliest effects of Srrm2 half-dosage are specific alternative splicing events on a small number of genes, followed by expression changes in metabolism and differentiation-related genes. Our findings unveil molecular and cellular roles of Srrm2 in stemness and lineage commitment, shedding light on the roles of splicing regulators in early embryogenesis, developmental diseases and tumorigenesis. Summary statementThis article emphasizes the importance of splicing regulators in early mammalian development by uncovering roles of SRRM2 splicing factor dosage in pluripotency, providing novel insights for a better understanding of Srrm2-related diseases.
- organism: mouse
- assay: bulk RNA-seq
- research focus: cell type annotation
- research focus: differential expression
- research focus: gene regulatory network inference
- approach: statistical model
- approach: experimental assay
- Citations
- 6
- FWCI
- 0.81
- Field percentile
- top 33%
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