bioRxivEvolutionary BiologyPreprint
Evolution of maternal and early zygotic transcript regulation across Drosophila
Abstract
The complements of mRNAs in early embryonic development are crucial for setting up developmental trajectories across all animals. The earliest stages of development are regulated by mRNAs deposited into the egg by the mother, until the zygote can become competent to transcribe its own genome. Previously, we showed that the set of maternally deposited and early transcribed zygotic mRNAs in Drosophila are generally conserved across species, but with some notable variation. We also showed that a majority of regulators of these two types of transcripts are shared. In this study, we examine the differences in regulatory motifs associated with maternal deposition and early zygotic transcription across species of Drosophila. For maternal transcripts, while the regulators are mostly conserved, we find the Drosophila pseudoobscura species subgroup appears to contain numerous novel regulatory motifs unique to these species. These novel motifs are enriched in transposable elements exclusive to this group. As this species group had been previously identified as having an exceptional amount of divergence in early embryonic transcripts, this change in regulation may be responsible. However, transcripts that are present at the maternal stage only in these species are equally enriched in novel (group-specific) and conserved binding sites, so the novel regulation is not the sole cause of regulatory divergence in these species. At the zygotic stage, we observe a wide variety of species-specific motifs. Additionally, at both stages we observe motifs conserved across species having different effects on gene expression in different species, and regulating different sets of genes in different species. By examining changes in motif content across species, we find that changes in motif content alone is generally insufficient to drive gene expression changes across species.
- organism: Drosophila
- assay: bulk RNA-seq
- research focus: chromatin & epigenetic regulation
- approach: statistical model
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