Translational specialization in pluripotency by RBPMS poises future lineage-decisions
Bartsch, D.; Kalamkar, K.; Ahuja, G.; Bazzi, H.; Papantonis, A.; Kurian, L.
10.1101/2021.04.12.439420 bioRxivShow abstract
The blueprints for developing organs are preset at the early stages of embryogenesis. Transcriptional and epigenetic mechanisms are proposed to preset developmental trajectories. However, we reveal that the competence for future cardiac fate of human embryonic stem cells (hESCs) is preset in pluripotency by a specialized mRNA translation circuit controlled by RBPMS. RBPMS is recruited to active ribosomes in hESCs to control the translation of essential factors needed for cardiac commitment program, including WNT signaling. Consequently, RBPMS loss specifically and severely impedes cardiac mesoderm specification leading to patterning and morphogenesis defects in human cardiac organoids. Mechanistically, RBPMS specializes mRNA translation, selectively via 3UTR binding and globally by promoting translation initiation. Accordingly, RBPMS loss causes translation initiation defects highlighted by aberrant retention of the EIF3 complex and depletion of EIF5A from mRNAs, thereby abrogating ribosome recruitment. We reveal how future fate trajectories are preprogrammed during embryogenesis by specialized mRNA translation. Teaser: Cardiac fate competence is preprogrammed in pluripotency by specialized mRNA translation of factors initiating cardiogenesis
Matching journals
The top 5 journals account for 50% of the predicted probability mass.
Similar papers in this journal
Similar papers in this journal
- A functional screen of translated pancreatic lncRNAs identifies a microprotein-independent role for LINC00261 in endocrine cell differentiation 95%
- Genome-wide mapping of native co-localized G4s and R-loops in living cells 95%
- TGFβ signalling is required to maintain pluripotency of human naïve pluripotent stem cells 95%
Similar papers in this journal
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.