Determining the effects of paternal obesity on sperm chromatin at histone H3 lysine 4 tri-methylation in relation to the placental transcriptome and cellular composition
- Department of Pharmacology and Therapeutics, Faculty of Medicine, McGill University, Canada
- Department of Biochemistry and Biomedical Sciences, McMaster University, Canada
- Departments of Anatomy & Cell Biology and Oncology, Western University, Canada
- Farncombe Family Digestive Health Research Institute, McMaster University Hamilton, Canada
- Departments of Obstetrics and Gynecology, and Pediatrics, McMaster University, Canada
- Department of Pathology and Molecular Biology, University of Montreal, University of Montreal Hospital Research Center, Canada
Figures
Figure 1
Experimental design showing the timeline and methods used to study the consequences of an obesity-induced altered sperm epigenome on the placenta.
(A) Six-week-old C57BL/6J sires were fed either a control or high-fat diet (CON or HFD, respectively) for 8–10 weeks. Males were then time-mated with CON-fed C57BL/6J females to generate …
Figure 2 with 1 supplement
Histone H3 lysine 4 tri-methylation (H3K4me3) signal profile at obesity-sensitive regions in sperm.
(A) Heatmap of log2 normalized counts for obesity-sensitive regions in sperm (n=1760). Columns (samples) and rows (genomic regions) are arranged by hierarchical clustering with complete-linkage …
Figure 2—figure supplement 1
Sperm histone H3 lysine 4 tri-methylation (H3K4me3) ChIP-sequencing data quality and normalization.
(A) Histogram showing frequency distributions of read abundances of genome-wide 150 bp windows. The vertical red line indicates the cut-off where windows with low read counts were filtered out …
Figure 3 with 1 supplement
Enriched motifs at obesity-sensitive regions in sperm.
(A) Top 10 significantly enriched known motifs at obesity-sensitive regions with increased histone H3 lysine 4 tri-methylation (H3K4me3) enrichment in high-fat diet (HFD)-sperm. Motifs are clustered …
Figure 3—figure supplement 1
Obesity-sensitive regions in sperm are found at tissue-specific enhancers important for development.
(A–B) Upset plots showing annotations for tissue-specific enhancers overlapping with differentially expressed histone H3 lysine 4 tri-methylation (deH3K4me3) regions with decreased enrichment in …
Figure 4 with 1 supplement
Paternal obesity alters the F1 placental transcriptome in a sex-specific manner.
(A–B) Heatmaps of normalized counts scaled by row (z-score) for transcripts that code for the detected differentially expressed genes (Lancaster p<0.05) in female (A, n=2035 genes) and male (B, …
Figure 4—figure supplement 1
Placenta RNA-sequencing data quality assessment.
(A) Spearman correlation heatmap on variance stabilized transcripts. The color gradient represents the Spearman correlation coefficient for each sample pairwise comparison. (B–C) Principal component …
Figure 5 with 3 supplements
Paternal obesity-induced changes in placental cellular composition and differential expression.
(A) Boxplots showing sample-specific proportions for the top 5 cell types with highest proportions detected in the bulk RNA-sequencing (RNA-seq) data deconvolution analysis across experimental …
Figure 5—figure supplement 1
Cell-type-specific marker genes selection using reference mouse embryonic day (E)14.5 placenta single-cell RNA-sequencing dataset.
(A) Principal component analysis (PCA) plot of 4346 single cells from mouse E14.5 placenta, with the 28 different cell types previously identified within the placenta (Han et al., 2018). The number …
Figure 5—figure supplement 2
Estimated cell-type proportions across experimental groups for male and female embryonic day (E)14.5 bulk placenta tissues derived from control (CON)- and high-fat diet (HFD)-fed sires.
(A) Boxplots showing sample-specific proportions for the remaining cell types detected in the bulk RNA-sequencing (RNA-seq) data deconvolution analysis across experimental groups (n=4 per sex per …
Figure 5—figure supplement 3
Principal component analysis (PCA) of estimated cell-type proportions.
(A–F) Principal component results for female (A–C) and male (D–F) placentas. (A and D) PCA plot of cell proportions. Confidence ellipses are drawn around mean points for each experimental group. (B …
Figure 6 with 1 supplement
Hypoxia-induced growth restriction is associated with changes in placental cellular composition and differential expression.
(A) Boxplots showing sample-specific proportions for the top 10 cell types with highest proportions detected in the bulk RNA-sequencing data deconvolution analysis across experimental groups (n=5 …
Figure 6—figure supplement 1
Quality assessment, processing, differential analysis, and deconvolution of RNA-sequencing data from mouse placenta in a hypoxia-induced intrauterine growth restriction mouse model.
(A) Spearman correlation heatmap on variance stabilized transcripts. The color gradient represents the Spearman correlation coefficient for each sample pairwise comparison. (B) Principal component …
Tables
Key resources table
| Reagent type (species) or resource | Designation | Source or reference | Identifiers | Additional information |
|---|---|---|---|---|
| Biological sample (Mus musculus, male) | Spermatozoa | C57BL/6J, The Jackson Laboratory | Isolated from Mus musculus (C57BL/6J) | |
| Biological sample (Mus musculus) | Placenta | C57BL/6J, The Jackson Laboratory | Isolated from Mus musculus (C57BL/6J) | |
| Antibody | Tri-Methyl-Histone H3 (Lys4) (C42D8) (Rabbit monoclonal) | Cell Signaling Technology | Cat#:9751 | (5 µg) |
| Commercial assay or kit | ChIP DNA Clean and Concentrator | Zymo Research | Cat#:D5201 | |
| Commercial assay or kit | RNeasy Mini Kit | QIAGEN | Cat#:74104 | |
| Chemical compound, drug | Dithiothreitol | Bio Shop | Cat#:3483-12-3 | |
| Chemical compound, drug | Micrococcal nuclease (MNase) | Roche | Cat#:10107921001 | |
| Chemical compound, drug | Complete Tablets EASYpack | Roche | Cat#:04693116001 | |
| Chemical compound, drug | DynaBeads, Protein A | Thermo Fisher Scientific | Cat#:10002D | |
| Chemical compound, drug | Bovine Serum Albumin (BSA) | Sigma-Aldrich | Cat#:BP1600-100 | |
| Chemical compound, drug | RNase A | Sigma-Aldrich | Cat#:10109169001 | |
| Chemical compound, drug | Proteinase K | Sigma-Aldrich | Cat#:P2308 | |
| Software, algorithm | R (version 4.0.2) | R Core Team, 2018 | ||
| Software, algorithm | Python (version 3.7.4) | Van Rossum and Drake, 2009 | ||
| Software, algorithm | Trimmomatic (version 0.36) | Bolger et al., 2014 | ||
| Software, algorithm | Bowtie2 (version 2.3.4) | Langmead and Salzberg, 2012 | ||
| Software, algorithm | SAMtools (version 1.9) | Li et al., 2009 | ||
| Software, algorithm | Deeptools (version 3.2.1) | Ramírez et al., 2016 | ||
| Software, algorithm | Trim Galore (version 0.5.0) | Krueger, 2015 | ||
| Software, algorithm | Hisat2 (version 2.1.0) | Kim et al., 2015 | ||
| Software, algorithm | Stringtie (version 2.1.2) | Pertea et al., 2015 | ||
| Software, algorithm | Seaborn (version 0.9.0) | Waskom, 2021 | ||
| Software, algorithm | Betareg (version 3.1–4) | Ferrari and Cribari-Neto, 2004 | ||
| Software, algorithm | Csaw (version 1.22.1) | Lun and Smyth, 2016 | ||
| Software, algorithm | Sva (version 3.36.0) | Leek et al., 2012; Zhang et al., 2020 | ||
| Software, algorithm | topGO (version 2.40.0) | Alexa et al., 2006 | ||
| Software, algorithm | trackplot | Bolger et al., 2014 | ||
| Software, algorithm | Rtracklayer (version 1.48.0) | Lawrence et al., 2009 | ||
| Software, algorithm | HOMER (version 4.10.4) | Heinz et al., 2010 | ||
| Software, algorithm | ViSEAGO (version 1.2.0) | Brionne et al., 2019 | ||
| Software, algorithm | DESeq2 (version 1.28.1) | Love et al., 2014 | ||
| Software, algorithm | Aggregation (version 1.0.1) | Yi et al., 2018 | ||
| Software, algorithm | Corrplot (version 0.88) | Taiyun and Simko, 2021 | ||
| Software, algorithm | Pheatmap (version 1.0.12) | Kolde, 2019 | ||
| Software, algorithm | Numpy (version 1.17.2) | Harris et al., 2020 | ||
| Software, algorithm | Pandas (version 0.25.2) | McKinney, 2010 | ||
| Software, algorithm | Pickle (version 4.0) | Van Rossum, 2020 | ||
| Software, algorithm | Scanpy (version 1.8.2) | Wolf et al., 2018 | ||
| Software, algorithm | Scipy (version 1.7.3) | Virtanen et al., 2020 | ||
| Software, algorithm | Autogenes (version 1.0.4) | Aliee and Theis, 2021 |
Additional files
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Supplementary file 1
Data quality statistics and gene ontology analysis.
(a) ChIP-sequencing sample information and read statistics. (b) Significant gene ontology terms enriched in high-fat diet (HFD)-sperm differentially expressed histone H3 lysine 4 tri-methylation (deH3K4me3) regions at promoters detected in our previous study and this study, related to Figure 2—figure supplement 1E. (c) Significant gene ontology terms enriched in HFD-sperm at regions showing a decrease in H3K4me3 at promoters, related to Figure 2—figure supplement 1E. (d) Significant gene ontology terms enriched in HFD-sperm at regions showing an increase in H3K4me3 at promoters, related to Figure 2—figure supplement 1E. (e) Significant gene ontology terms enriched in differentially expressed genes in female placentas derived from HFD-sires, related to Figure 4C. (f) Significant gene ontology terms enriched in differentially expressed genes in male placentas derived from HFD-sires, related to Figure 4D. (g) Reference single-cell RNA-sequencing data information (from Han et al., 2018) – number of cells per cell type, related to Figure 5—figure supplement 1.
- https://cdn.elifesciences.org/articles/83288/elife-83288-supp1-v2.xlsx
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Supplementary file 2
Interactive heatmap for significant gene ontology terms enriched in high-fat diet (HFD)-sperm deH3K4me3 regions at promoters detected in our previous study (Pepin et al., 2022) and this study, related to Figure 2—figure supplement 1E.
- https://cdn.elifesciences.org/articles/83288/elife-83288-supp2-v2.png
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Supplementary file 3
Motif analysis, showing significantly enriched known motifs in regions gaining H3K4me3 in high-fat diet (HFD)-sperm, related to Figure 3.
- https://cdn.elifesciences.org/articles/83288/elife-83288-supp3-v2.zip
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MDAR checklist
- https://cdn.elifesciences.org/articles/83288/elife-83288-mdarchecklist1-v2.docx
