Cell ReportsDevelopmental BiologyPeer-reviewed journal article
Sequential regulation of maternal mRNAs through a conserved cis-acting element in their 3’UTRs
Pooja FloraiD, Siu Wah Wong-Deyrup, Elliot Todd MartiniD, Ryan J. PalumboiD, Mohamad Ali NasrallahiD, Andrew Oligney, Patrick Blatt, Dhruv PateliD, Gabriele FuchsiD, Prashanth RanganiD
Abstract
Maternal mRNAs are synthesized during oogenesis to initiate the development of future generations. Some maternal mRNAs are determinants of somatic or germline fate and must be translationally repressed until embryogenesis. However, the translational repressors themselves are also temporally regulated. We use polar granule component (pgc), a Drosophila maternal mRNA, as a model system to ask how maternal mRNAs are repressed while the regulatory landscape is continually shifting. pgc, a potent transcriptional silencer and germline determinant, is translationally regulated throughout oogenesis. We find that the 3UTR of pgc mRNA contains a conserved ten-nucleotide sequence that is bound by different conserved RNA binding proteins (RBPs) at different stages of oogenesis to continuously repress translation except for a brief expression in the stem cell daughter. Pumilio (Pum) binds to this sequence in undifferentiated and early differentiating oocytes and recruits other temporally restricted translational regulators to block pgc translation. After differentiation, Pum levels diminish and Bruno (Bru) levels increase, allowing Bru to bind the same 3UTR sequence and take over translational repression of pgc mRNA. We have identified a class of maternal mRNAs regulated during oogenesis by both Pum and Bru, including Zelda, activator of the zygotic genome, which contain this core 10-nt regulatory sequence. Our data suggests that this hand off mechanism is more generally utilized to inhibit translation of maternal mRNAs during oogenesis.
- organism: Drosophila
- assay: metagenomics
- research focus: cell type annotation
- research focus: differential expression
- research focus: gene regulatory network inference
- research focus: cell-cell communication
- approach: statistical model
- approach: experimental assay
- Citations
- 33
- FWCI
- 0.98
- Field percentile
- top 26%
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