SETDB1 enables development beyond cleavage stages by extinguishing the MERVL-driven two-cell totipotency transcriptional program in the mouse embryo
- Department of Epigenetics, Van Andel Institute, United States
- Bioinformatics and Biostatistics Core, Van Andel Institute, United States
- Genomics Core, Van Andel Institute, United States
Figures
Figure 1 with 5 supplements
Maternal SETDB1 is essential for development beyond the eight-cell stage.
(A) Quantification of Setdb1mat-/+ (KO) and Setdb1fl/+ (WT) embryo stages from the following number of total recovered embryos: KO (n=638), WT (n=484) at 1.5 dpc, and KO (n=310) and WT (n=80) at 2.5 dpc. (B) Principal component analysis of single-embryo total RNA-seq data from 2cWT (n=6), 2cKO (n=15), 8cWT (n=8), and 8cKO (n=8) embryos (Figure 1—source data 1). (C) Schematic of four pairwise comparisons defining requirements for normalcy and development. (D) Volcano plots highlighting differentially expressed genes (DEGs) using |log₂FC|>1 and adjusted p<0.05. (E, F) Four-way DEG comparisons (Figure 1—source data 2) visualized by Venn diagrams: (E) downregulated; (F) upregulated. (G–J) Heatmaps of DEGs from Venn compartments, showing stage- and genotype-specific patterns.
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Figure 1—source data 1
Sample information.
Details of all single embryos analyzed in the study, including genotype, developmental stage, and sequencing sample ID.
- https://cdn.elifesciences.org/articles/109248/elife-109248-fig1-data1-v1.xlsx
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Figure 1—source data 2
Differential gene expression (DGE) analysis.
DGE analysis was conducted using the four pairwise comparisons shown in Figure 1C and D, with thresholds of |log₂FC|>1 and adjusted p<0.05. The ‘expression’ columns indicate whether each transcript is up- or downregulated in any given comparison. The ‘FOUR_WAY_UP_COMP’ and ‘FOUR_WAY_DOWN_COMP’ columns assign DEGs to compartments corresponding to the Venn diagrams in Figure 1E and F. Sample columns (TZSC118–TZSC116) contain log₂-transformed counts per million (CPM) values, generated using the cpm function in edgeR (v4.4.1).
- https://cdn.elifesciences.org/articles/109248/elife-109248-fig1-data2-v1.xlsx
Figure 1—figure supplement 1
Normal features of Setdb1 KO embryos.
(A) Morphology. Brightfield images of 2c and 8c WT and KO embryos at 1.5 and 2.5 dpc. Scale bar 50 µM. (B) Transcription. Single-embryo total RNA sequencing results of 2c and 8c WT and KO embryos at 1.5 and 2.5 dpc (n=5). IGV browser views of selected transcripts, with normalized CPM scales shown in brackets.
Figure 1—figure supplement 2
Gene set enrichment analysis (GSEA) of Setdb1 KO differentially expressed genes (DEGs).
(A–D) Bubble plots of GSEA for 2cWT vs. 2cKO, 8cWT vs. 8cKO, 8cWT vs. 2cWT, and 8cKO vs. 2cKO pairwise comparisons (Figure 1—figure supplement 2—source data 1).
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Figure 1—figure supplement 2—source data 1
Gene set enrichment analysis (GSEA) on gene ontology (GO).
GO term enrichment for DEGs identified in the four pairwise comparisons by gseGO in R package ClusterProfiler (v4.14.4).
- https://cdn.elifesciences.org/articles/109248/elife-109248-fig1-figsupp2-data1-v1.xlsx
Figure 1—figure supplement 3
Developmental transcriptional changes independent of maternal SETDB1.
(A, C) Heatmaps of differentially expressed genes (DEGs) commonly downregulated (n=1722) or upregulated (n=828) from 2c to 8c stages. (B, D) Gene ontology (GO) analysis of those DEGs (Figure 1—figure supplement 3—source data 1).
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Figure 1—figure supplement 3—source data 1
Overrepresentation analysis (ORA) against gene ontology (GO) analysis by differentially expressed gene (DEG) Venn compartment.
GO enrichment for DEG subsets defined by intersecting Venn diagram compartments (Figure 1E, F). The analysis was run using the function enrichGO from the R package ClusterProfiler (v4.14.4). Results are shown only for sets with significant enrichment.
- https://cdn.elifesciences.org/articles/109248/elife-109248-fig1-figsupp3-data1-v1.xlsx
Figure 1—figure supplement 4
Developmental misregulation in Setdb1 KO embryos.
(A, C, E) Heatmaps showing differentially expressed genes (DEGs) uniquely changed in KO embryos. (B, D, F) Gene ontology (GO) enrichment analyses of these misregulated gene sets.
Figure 1—figure supplement 5
SETDB1 suppresses transposable elements at cleavage stages.
(A) Principal component analysis (PCA) of multimapped TE profiles. (B) Venn diagram of DE TE families (adjusted p<0.05) (Figure 1—figure supplement 5—source data 1). (C, D) DE TE tallies across pairwise comparisons by TE class. (E, F) DE TE heatmaps across pairwise comparisons by TE class.
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Figure 1—figure supplement 5—source data 1
Differential TE expression (DTE): multimapping reads.
TE expression analysis by DESeq2 (v146.0) using multimapped reads across four comparisons.
- https://cdn.elifesciences.org/articles/109248/elife-109248-fig1-figsupp5-data1-v1.xlsx
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Figure 1—figure supplement 5—source data 2
Differential TE expression (DTE): unimapping reads.
TE expression analysis DESeq2 (v146.0) using uniquely mapped reads across four comparisons.
- https://cdn.elifesciences.org/articles/109248/elife-109248-fig1-figsupp5-data2-v1.xlsx
Figure 2
Maternal SETDB1 extinguishes two-cell transient gene expression.
(A) Bubble plot showing overrepresentation analysis of Database of Transcriptome in Mouse Early Embryos (DBTMEE) (Park et al., 2015)-defined transcript sets among differentially expressed genes (DEGs) identified in the four pairwise comparisons (Figure 2—source data 1). (B) IGV browser snapshots of representative transcripts from the DBTMEE-defined minor ZGA to MGA, two-cell transient, and four-cell transient gene sets across five biological replicates. Venn diagram compartments are indicated above each track. Units in brackets represent normalized counts per million (CPM). Bigwig tracks are shown in the transcriptional direction matching the depicted gene. (C) Boxplots of selected DEGs *(|log₂FC|>1, adjusted p<0.05) from each Venn compartment, based on data from 2cWT (n=6), 2cKO (n=15), 8cWT (n=8), and 8cKO (n=8) embryos.
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Figure 2—source data 1
Overrepresentation analysis (ORA) with Database of Transcriptome in Mouse Early Embryos (DBTMEE) categories.
ORA was performed using DBTMEE-defined (Park et al., 2015) gene sets as in Sakashita et al., 2023 and DEGs up-/downregulated from the pairwise comparisons. The analysis was run using the function enricher from the R package ClusterProfiler (v4.14.4). Results are shown only for sets with significant enrichment.
- https://cdn.elifesciences.org/articles/109248/elife-109248-fig2-data1-v1.xlsx
Figure 3
Maternal SETDB1 regulates MERVL-driven chimeric transcripts.
(A) Boxplots showing normalized counts of multimapped MERVL-int and MT2_Mm elements. (B) Heatmap from Setdb1 KO embryos at MERVL chimeric transcripts classified by Macfarlan et al., 2012. (C, D) Volcano plots marking Macfarlan-defined chimeric transcripts in 2cWT vs. 2cKO and 8cWT vs. 8cKO pairwise comparisons. (E) IGV browser images of MT2B1 LTR-driven MERVL-chimeric transcripts. (F) Venn diagram showing differentially expressed (p<0.05) known and novel TE-driven chimeric transcripts (Figure 3—source data 1).
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Figure 3—source data 1
Chimeric transcript analysis.
Chimeric transcripts previously identified from the datasets of Xue et al., 2013, and Deng et al., 2014 by Modzelewski et al., 2021, and de novo identified ones according to Modzelewski et al., 2021 were analyzed across four pairwise comparisons and annotated with their corresponding Venn diagram compartments from the four-way analysis. Values in the sample columns for the four pairwise DE transcript comparisons (last four sheets) are normalized counts generated using DESeq2 (v1.46.0).
- https://cdn.elifesciences.org/articles/109248/elife-109248-fig3-data1-v1.xlsx
Figure 4
Maternal SETDB1 suppresses MT2 LTR-regulated genes.
(A, B) Heatmaps of H3K9me3 deposition (Wang et al., 2018) at MT2-controlled (Yang et al., 2024) differentially expressed genes (DEGs) (A) and their MT2 elements (B) across early embryonic stages. (C–E) IGV browser views of a representative MERVL and MT2-regulated loci. (F) Heatmap of maternal Setdb1 KO embryos at DEGs classified by MT2i data. (G, H) Volcano plots highlighting MT2-regulated genes in 2cWT vs. 2cKO and 8cWT vs. 8cKO pairwise comparisons.
Figure 5
SETDB1 regulates MT2-activated genes across time.
(A) Heatmaps comparing MT2i-responsive (Yang et al., 2024) early two-cell (E2c) differentially expressed genes (DEGs) with the Setdb1 KO transcriptomes. (B, C) Volcano plots highlighting MT2-regulated E2c DEGs in 2cWT vs. 2cKO and 8cWT vs. 8cKO pairwise comparisons. (D) Heatmaps of MT2i late two-cell (L2c) DEGs. (E) Volcano plot highlighting MT2-regulated L2c DEGs.
Figure 6 with 1 supplement
SETDB1 represses DUXBL-responsive transcripts.
(A) Heatmap of top 50 differentially expressed genes (DEGs) identified in Duxbl KO embryos (Vega-Sendino et al., 2024) analyzed in the Setdb1 KO RNA-seq dataset. (B) Volcano plots marking upregulated/downregulated DUXBL targets in 2cWT vs. 2cKO and 8cWT vs. 8cKO pairwise comparisons. (D, E) IGV browser examples of DUXBL-responsive DEGs with aligned H3K9me3 ChIP-seq data.
Figure 6—figure supplement 1
Examples of DUXBL targets derepressed in Setdb1 KO embryos.
(A–D) IGV images of Duxbl KO DEGs (e.g., Antxr1, Aqr, Nelfa, Zscan4d) with associated H3K9me3 profiles. MERVL insertions upstream or intronic are indicated.
Figure 7
SETDB1 collaborates with DUXBL to repress totipotency programs.
(A) Bubble plot of overrepresentation analysis showing enrichment of previously identified MERVL-chimeric, MT2i-responsive, and Duxbl KO-responsive gene sets (Macfarlan et al., 2012; Vega-Sendino et al., 2024; Yang et al., 2024) in Setdb1 KO pairwise differentially expressed genes (DEGs) (Figure 7—source data 1). (B) Summary model: Maternal SETDB1 deposits H3K9me3 at MT2 elements to silence MERVL-driven two-cell transcripts in coordination with DUXBL, enabling exit from totipotency.
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Figure 7—source data 1
ORA with MERVL-chimeric, MT2i, and Duxbl KO gene sets.
Overrepresentation analysis of up/down pairwise DEGs using gene sets from Macfarlan et al., 2012 (MERVL-chimeric), Yang et al., 2024 (MT2i), and Vega-Sendino et al., 2024 (Duxbl KO). ORA was performed if there were more than 50 genes using function enricher from R package ClusterProfiler (v4.14.4). Results are shown only for sets with significant enrichment.
- https://cdn.elifesciences.org/articles/109248/elife-109248-fig7-data1-v1.xlsx
Tables
Key resources table
| Reagent type (species) or resource | Designation | Source or reference | Identifiers | Additional information |
|---|---|---|---|---|
| Gene (Mus musculus) | Setdb1 | NCBI | Gene: 84505 | |
| Genetic reagent (M. musculus) | Setdb1tm1a(EUCOMM)Wtsi | European Mouse Mutant Archive | EMMA ID EM:04814 | Skarnes et al., 2011 |
| Genetic reagent (M. musculus) | B6.Cg-Tg(Pgk1-flpo)10Sykr/J | The Jackson Laboratory | RRID:IMSR_JAX:011065 | Wu et al., 2009 |
| Genetic reagent (M. musculus) | C57BL/6-Tg(Zp3-cre)93Knw/J | The Jackson Laboratory | RRID:IMSR_JAX:003651 | de Vries et al., 2000 |
| Software, algorithm | StringTie2 | https://github.com/skovaka/stringtie2 | RRID:SCR_016338 | Kovaka et al., 2019 |
| Software, algorithm | Trim Galore (v0.60) | https://github.com/FelixKrueger/TrimGalore | RRID:SCR_011847 | Krueger, 2025 Martin, 2011 |
| Software, algorithm | edgeR (v4.4.1) | https://bioconductor.org/packages/edgeR/ | RRID:SCR_012802 | Chen et al., 2016; McCarthy et al., 2012; Robinson et al., 2010 |
| Software, algorithm | ClusterProfiler (v4.14.4) | https://bioconductor.org/packages/clusterProfiler/ | RRID:SCR_016884 | Wu et al., 2021 |
| Software, algorithm | STAR (v2.7.8) | https://github.com/alexdobin/STAR | RRID:SCR_004463 | Dobin et al., 2013 |
| Software, algorithm | Samtools (v1.17) | https://github.com/samtools/samtools/ | RRID:SCR_002105 | Li et al., 2009 |
| Software, algorithm | FeatureCounts (Subread v2.0.0) | https://subread.sourceforge.net/featureCounts.html | RRID:SCR_012919 | Liao et al., 2014 |
| Software, algorithm | DESeq2 (v1.46.0) | https://github.com/thelovelab/DESeq2 | RRID:SCR_000154 | Love et al., 2014 |
| Software, algorithm | BWA (v0.7.1) | https://github.com/lh3/bwa | RRID:SCR_010910 | Li and Durbin, 2009 |
| Software, algorithm | deepTools2 v3.5.2 | https://github.com/deeptools/deepTools | RRID:SCR_016366 | Ramírez et al., 2016 |
| Software, algorithm | ggplot2 | https://ggplot2.tidyverse.org | RRID:SCR_014601 | Wickham, 2016 |
| Software, algorithm | ComplexHeatmap (R) | https://jokergoo.github.io/ComplexHeatmap-reference/book/ | RRID:SCR_017270 | Gu et al., 2016 |
| Software, algorithm | ggvenn (v0.1.10) | https://github.com/yanlinlin82/ggvenn | RRID:SCR_025300 | Yan, 2023 |
| Software, algorithm | TEtranscripts (v2.2.3) | https://github.com/mhammell-laboratory/TEtranscripts | RRID:SCR_015687 | Jin et al., 2015 |
| Chemical compound, drug | CARD HyperOva | Cosmo Bio | Cat. No. KYD-010-EX | |
| Commercial assay or kit | SMART-Seq Stranded Kit | Takara Biosciences USA, Mountain View CA | Cat. No. 634444 | |
| Commercial assay or kit | RNA-Bee | Amsbio | Cat. No. CS-105B | |
| Peptide, recombinant protein | RNasin ribonuclease inhibitor | Promega | Cat. No. N2515 | |
| Commercial assay or kit | DNA-free Kit | Ambion | Cat. No. AM1906 | |
| Commercial assay or kit | Agilent High Sensitivity DNA Kit | Agilent Technologies, Inc. | Part Number:5067-4626 | |
| Commercial assay or kit | QuantiFluor dsDNA System | Promega Corp., Madison, WI, USA | Cat. No. E2671 | |
| Commercial assay or kit | Kapa Illumina Library Quantification qPCR assays | Kapa Biosystems | Cat. No. KR0405 |
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SETDB1 enables development beyond cleavage stages by extinguishing the MERVL-driven two-cell totipotency transcriptional program in the mouse embryo
eLife 15:RP109248.
https://doi.org/10.7554/eLife.109248.2
