Ayers TN et al. (2023), Parallels and contrasts between the cnidarian a...

ECB-ART-51301

PLoS Genet 2023 Jul 01;197:e1010845. doi: 10.1371/journal.pgen.1010845.

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Parallels and contrasts between the cnidarian and bilaterian maternal-to-zygotic transition are revealed in Hydractinia embryos.

Ayers TN , Nicotra ML , Lee MT .

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Embryogenesis requires coordinated gene regulatory activities early on that establish the trajectory of subsequent development, during a period called the maternal-to-zygotic transition (MZT). The MZT comprises transcriptional activation of the embryonic genome and post-transcriptional regulation of egg-inherited maternal mRNA. Investigation into the MZT in animals has focused almost exclusively on bilaterians, which include all classical models such as flies, worms, sea urchin, and vertebrates, thus limiting our capacity to understand the gene regulatory paradigms uniting the MZT across all animals. Here, we elucidate the MZT of a non-bilaterian, the cnidarian Hydractinia symbiolongicarpus. Using parallel poly(A)-selected and non poly(A)-dependent RNA-seq approaches, we find that the Hydractinia MZT is composed of regulatory activities similar to many bilaterians, including cytoplasmic readenylation of maternally contributed mRNA, delayed genome activation, and separate phases of maternal mRNA deadenylation and degradation that likely depend on both maternally and zygotically encoded clearance factors, including microRNAs. But we also observe massive upregulation of histone genes and an expanded repertoire of predicted H4K20 methyltransferases, aspects thus far particular to the Hydractinia MZT and potentially underlying a novel mode of early embryonic chromatin regulation. Thus, similar regulatory strategies with taxon-specific elaboration underlie the MZT in both bilaterian and non-bilaterian embryos, providing insight into how an essential developmental transition may have arisen in ancestral animals.

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	Fig 1. RNA-seq with rRNA depletion reveals the timing and extent of genome activation.(A) Schematic of Hydractinia embryonic development comparing hours post fertilization (h.p.f.) with approximate cell count, based on Kraus et al [52]. Gastrulation likely completes prior to 20 h.p.f. (B) Biplots of log2 TPM RNA-seq expression levels between unfertilized eggs (x axis) and subsequent developmental time points. Top panels represent RNA-seq with rRNA depletion, bottom panels represent RNA-seq with poly(A)+ selection. Genes >2-fold significantly different (DESeq2 adjusted P < 0.05, TPM > 1) are highlighted in orange. (C) Meta plots of rRNA-depleted RNA-seq coverage over introns of activated genes, as measured 3, 4, and 7 hours post fertilization. (D) Stacked barplots showing the proportion of annotated genes at different time points that are maternally provided with no additional activation (pink), maternally provided with additional expression from the embryonic genome (purple), and de novo transcribed in the embryo (blue). (E) Browser tracks showing rRNA-depleted RNA-seq intronic coverage appearing at 4 hours post fertilization (arrows). TPM = transcripts per million. RPM = reads per million.
	Fig 2. Histone genes are strongly activated early.(A) Browser tracks showing a cluster of tandemly repeated histone genes and the increase in RNA-seq coverage at 3–4 hours post fertilization (h.p.f.). The scale at 4 h.p.f. is discontinuous. Gray regions represent coverage of interspersed non-coding genes that are maternally provided. (B) Heatmap (log10 scale) showing strong expression increase of the core replication-dependent histones (bolded) over time. (C) Stacked barplots showing the proportion of the transcriptome that encodes each of the 5 histone classes (linker H1, H2A, H2B, H3, and H4) over time in embryos of Hydractinia (left) and four bilaterian species. (D) Net activation of all histones (blue lines) compared to all other genes (gray dashed lines) relative to maternal levels during early development in five species. Activation trajectories of microRNAs miR-430 and miR-427 are shown in red for zebrafish and Xenopus, respectively. TPM = transcripts per million, RPM = reads per million.
	Fig 3. Predicted H4K20 methyltransferase genes broadly activate.(A) Heatmap showing expression levels of predicted H4K20 methyltransferase genes over time, grouped according to when activation is observed. (B) Protein domain schematics for the predicted H4K20 methyltransferases showing positions of the SETD8 SET domain (orange), as predicted by CD-Search. Other domains are indicated in other colors as shown in the legend. Reference H4K20 methyltransferases in other species are shown in the upper right. TPM = transcripts per million.
	Fig 4. Stage-specific gene expression is observed throughout the timecourse.(A) Heatmap showing relative expression levels of genes, grouped according to the time point that expression level peaks. (B) Heatmap showing expression levels across time of maternal-specific highly-expressed predicted transcription factors. Each Hydractinia gene is annotated with the best UniProt / SwissProt BLAST hit, species, and DNA binding domain for select factors (hs = human, mm = mouse, galGal = chicken, xenLae = Xenopus laevis, bosTau = cow, rn = rat, takRub = Takifugu, danRer = zebrafish, dm = Drosophila). Bold = E < 1x10-50, italics = 1x10-25 < E < 1x10-10. TPM = transcripts per million.
	Fig 5. Maternal mRNA are cleared with different dynamics.(A) Bubble chart showing the timing of clearance. Each square shows the number of genes with >2-fold expression decrease relative to egg (proportional to size of the circle), according to the time point (h.p.f.) when the decrease is observed in the poly(A)+ RNA-seq (x-axis coordinate) versus the rRNA-depleted RNA-seq (y-axis coordinate). The shaded squares are time point combinations where decreases are observed in the poly(A)+ RNA-seq before they are observed in the rRNA-depleted RNA-seq. (B) Average profiles of log2 fold difference relative to egg (0 h.p.f.) of genes grouped according to when expression decreases are observed in the poly(A)+ RNA-seq (2–7+ h.p.f.). Each gene group is plotted for poly(A)+ RNA-seq (left panel) and rRNA-depleted RNA-seq (right panel). Full trajectories for all genes in each group are shown as small insets, 2–7+ h.p.f. from top to bottom. (C) Browser track showing asymmetric timing of RNA-seq coverage decreases observed in poly(A)+ RNA-seq (top) versus rRNA-depleted RNA-seq. (D) Biplots showing the effect of Triptolide treatment on mRNA clearance as measured using poly(A)+ RNA-seq (left panels) and rRNA-depleted RNA-seq (right panels). Top panels show genes whose clearance was detected 2–4 h.p.f. in poly(A)+ RNA-seq (“Early cleared”), bottom panels ≥5 h.p.f. (“Late cleared”). Genes experiencing equivalent clearance with or without Triptolide treatment would fall on the diagonal. Genes with inhibited clearance would be above the diagonal. (E) Quantification of differential clearance with and without Triptolide treatment. Top boxplots are for early-cleared genes, bottom boxplots for late-cleared genes. P values are from Wilcoxon signed-rank tests. h.p.f. = Hours post fertilization.
	Fig 6. Clearance may be mediated by RNA-binding proteins and microRNAs.(A) Motifs found in the 3’UTRs of genes whose clearance is detected 2–4 hours post fertilization (h.p.f.) (left) versus ≥ 5 h.p.f. (right). P values are based on enrichment over a background set of stable mRNA, as calculated by the MEME Suite. (B) Predicted mature miRNAs (bold) in the precursor hairpin structural context of the primary transcripts that encode them. Red arrows mark predicted Dicer (loop proximal) and Drosha cleavage sites according to canonical processing. Asterisks mark base differences relative to predicted H. echinata miRNAs. Expression levels of each primary transcript from 0–7 h.p.f. are shown to the right. (C) RNA-seq expression levels of each predicted miRNA primary transcript in the presence or absence of Triptolide. P values are calculated by DESeq2 with FDR adjustment. (D) RNA-seq expression levels of predicted mRNA targets of miRNAs in the presence or absence of Triptolide, as compared to maternal levels in the egg. P values are calculated by DESeq2 with FDR adjustment. (E) Base-pairing of predicted miRNAs with their predicted mRNA targets. Coordinates are relative to the mature mRNA. TPM = transcript per million.
	Fig 7. The maternal-to-zygotic transition in Hydractinia compared to other taxa.(A) In Hydractinia, prior to genome activation, maternal mRNA are subject to either poly(A) tail lengthening, or shortening as part of the maternal clearance program. After genome activation, histone mRNA predominate in the transcriptome, and an expanded repertoire of H4K20 methyltransferases as well as unknown clearance factors and predicted miRNAs are also de novo transcribed. These clearance factors likely initiate the mRNA degradation phase of maternal clearance. (B) Table comparing features of the Hydractinia maternal-to-zygotic transition shared or not shared with other taxa. A blue checkmark indicates the feature applies to the taxon, magenta “x” indicates it does not apply, empty boxes indicate undetermined or not definitively known–e.g., M. leidyi and N. vectensis may have delayed genome activation, but sufficient temporal resolution is currently lacking to determine this for sure. Evolutionary relationships between the taxa are represented by the cladogram above, with the Ctenophora and Cnidaria phyla and the Bilateria clade labeled.

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