Single-cell multimodal analyses reveal epigenomic and transcriptomic basis for birth defects in maternal diabetes

ABSTRACT Maternal diabetes mellitus is among the most frequent environmental contributors to congenital birth defects, including heart defects and craniofacial anomalies, yet the cell types

affected and mechanisms of disruption are largely unknown. Here, using multimodal single-cell analyses, we show that maternal diabetes affects the epigenomic landscape of specific subsets of

cardiac and craniofacial progenitors during embryogenesis. A previously unrecognized cardiac progenitor subpopulation expressing the homeodomain-containing protein ALX3 showed prominent

chromatin accessibility changes and acquired a more posterior identity. Similarly, a subpopulation of neural crest-derived cells in the second pharyngeal arch, which contributes to

craniofacial structures, displayed abnormalities in the epigenetic landscape and axial patterning defects. Chromatin accessibility changes in both populations were associated with increased

retinoic acid signaling, known to establish anterior–posterior identity. This work highlights how an environmental insult can have highly selective epigenomic consequences on discrete cell

types leading to developmental patterning defects. Access through your institution Buy or subscribe This is a preview of subscription content, access via your institution ACCESS OPTIONS

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institutional subscriptions * Read our FAQs * Contact customer support SIMILAR CONTENT BEING VIEWED BY OTHERS SINGLE-CELL TRANSCRIPTOMIC PROFILING UNVEILS DYSREGULATION OF CARDIAC PROGENITOR

CELLS AND CARDIOMYOCYTES IN A MOUSE MODEL OF MATERNAL HYPERGLYCEMIA Article Open access 15 August 2022 SINGLE-CELL CHROMATIN PROFILING OF THE PRIMITIVE GUT TUBE REVEALS REGULATORY DYNAMICS

UNDERLYING LINEAGE FATE DECISIONS Article Open access 26 May 2022 SINGLE-CELL RNA SEQUENCING IDENTIFIES CXADR AS A FATE DETERMINANT OF THE PLACENTAL EXCHANGE SURFACE Article Open access 02

January 2025 DATA AVAILABILITY Data are available in the main text and the supplementary materials. All the sequencing data have been deposited in NCBI’s Gene Expression Omnibus and are

accessible through GEO series accession number GSE198905. Source data are provided with this paper. CODE AVAILABILITY All codes are available on GitHub

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PubMed Central  Google Scholar  Download references ACKNOWLEDGEMENTS We thank members of the Srivastava laboratory for discussion and feedback; B. Taylor from Gladstone Institutes for

editorial and graphics assistance; G. Maki from Gladstone Institutes for graphics assistance; and K. Claiborn from Gladstone Institutes for editorial review. We acknowledge the Center for

Advanced Technology (CAT) for sequencing; the Gladstone Histology and Light Microscopy Core for their technical support; and the Gladstone Animal Facility for support with mouse colonies.

Figures 1a and 5g, Extended Data Fig. 1a and Supplementary Fig. 1a were created with BioRender.com. National Institutes of Health/NHLBI grant P01 HL146366, R01 HL057181, R01 HL015100, R01

HL127240, Roddenberry Foundation, L.K. Whittier Foundation, Dario and Irina Sattui, Younger Family Fund, and Additional Ventures to D.S. The Japan Society for the Promotion of Science

Overseas Research Fellowship to T.N. Additional Ventures to S.S.R. American Heart Association Postdoctoral Fellowship (#899270) to B.J.v.S. National Institutes of Health grant K08 HL157700,

Sarnoff Cardiovascular Research Foundation, Frank A. Campini Foundation and Michael Antonov Charitable Foundation to A. Padmanabhan. AUTHOR INFORMATION AUTHORS AND AFFILIATIONS * Gladstone

Institutes, San Francisco, CA, USA Tomohiro Nishino, Sanjeev S. Ranade, Angelo Pelonero, Benjamin J. van Soldt, Lin Ye, Michael Alexanian, Frances Koback, Yu Huang, Langley Grace Wallace, 

Nandhini Sadagopan, Adrienne Lam, Lyandysha V. Zholudeva, Feiya Li, Arun Padmanabhan, Reuben Thomas, Joke G. van Bemmel, Casey A. Gifford, Mauro W. Costa & Deepak Srivastava *

Roddenberry Center for Stem Cell Biology and Medicine at Gladstone, San Francisco, CA, USA Tomohiro Nishino, Sanjeev S. Ranade, Angelo Pelonero, Benjamin J. van Soldt, Lin Ye, Michael

Alexanian, Frances Koback, Yu Huang, Langley Grace Wallace, Nandhini Sadagopan, Adrienne Lam, Lyandysha V. Zholudeva, Feiya Li, Arun Padmanabhan, Joke G. van Bemmel, Casey A. Gifford, Mauro

W. Costa & Deepak Srivastava * Department of Pediatrics, University of California, San Francisco, San Francisco, CA, USA Michael Alexanian & Deepak Srivastava * Division of

Cardiology, Department of Medicine, University of California, San Francisco, San Francisco, CA, USA Nandhini Sadagopan & Arun Padmanabhan * Chan Zuckerberg Biohub, San Francisco, CA, USA

Arun Padmanabhan * Department of Biochemistry and Biophysics, University of California, San Francisco, San Francisco, CA, USA Deepak Srivastava Authors * Tomohiro Nishino View author

publications You can also search for this author inPubMed Google Scholar * Sanjeev S. Ranade View author publications You can also search for this author inPubMed Google Scholar * Angelo

Pelonero View author publications You can also search for this author inPubMed Google Scholar * Benjamin J. van Soldt View author publications You can also search for this author inPubMed 

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author publications You can also search for this author inPubMed Google Scholar * Feiya Li View author publications You can also search for this author inPubMed Google Scholar * Arun

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search for this author inPubMed Google Scholar CONTRIBUTIONS T.N. and D.S. conceived and directed the study. T.N. and Y.H. performed animal work. T.N., L.G.W. and S.S.R. collected heart

tissues and isolated single cells for subsequent scRNA-seq and scATAC-seq. T.N., S.S.R., A. Pelonero, B.J.v.S. and F.K. analyzed scRNA-seq and scATAT-seq and developed computational methods.

T.N., B.J.v.S., L.V.Z. and F.L. performed RNA in situ hybridization and subsequent tissue clearing and imaging. T.N., L.Y., N.S., A.L., A. Padmanabhan and M.W.C designed, performed and

analyzed luciferase assay and mouse lineage trace experiment. T.N., S.S.R., M.A., A. Pelonero, J.G.v.B, C.A.G., M.W.C. and D.S. interpreted the data. R.T. reviewed statistical methods. T.N.,

M.W.C. and D.S. wrote the manuscript with contributions of M.A. CORRESPONDING AUTHOR Correspondence to Deepak Srivastava. ETHICS DECLARATIONS COMPETING INTERESTS D.S. is a scientific

co-founder, shareholder and director of Tenaya Therapeutics. The remaining authors declare no competing interests. PEER REVIEW PEER REVIEW INFORMATION _Nature Cardiovascular Research_ thanks

Professor Hiroki Kurihara, and the other, anonymous, reviewer for their contribution to the peer review of this work. Primary Handling Editor: Vesna Todorovic, in collaboration with the

_Nature Cardiovascular Research_ team. ADDITIONAL INFORMATION PUBLISHER’S NOTE Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional

affiliations. EXTENDED DATA EXTENDED DATA FIG. 1 HISTOLOGICAL AND MICRO-CT VALIDATION OF THE MATERNAL DIABETES MODEL. (A) The design of the _in vivo_ maternal diabetic model experiment.

After administration of either VEH or STZ, females in the STZ group with confirmed diabetes were mated with normoglycemic males, and heart samples at embryonic day 18.5 (E18.5) or postnatal

day 0 (P0) were collected for histological examination. (B) Representative micro-CT images of the heart phenotypes detected in the diabetic model. The prevalence of each malformation is

shown in Supplementary Table 1. The scale bar represents 500 µm. EXTENDED DATA FIG. 2 SINGLE CELL MULTIMODAL ANALYSIS OF CARDIO-PHARYNGEAL REGION IN MATERNAL DIABETES. (A) Representative

image of E10.5 embryo with detailed micro-dissected region used for scRNA/scATAC-seq experiment. Scale bar represents 1 mm. (B) scRNA-seq (left) or scATAC-seq (right) UMAP presentation

colored by conditions. Different colors overlayed delineate cell type cluster annotations. (C) Expression patterns of representative cell type specific marker genes plotted on UMAP space

shown in Fig. 1b. (D) Heatmap of marker gene scores per cluster of scATAC-seq. (E) Heatmap of Jaccard indices calculated between scRNA-seq and scATAC-seq after integration. Values range from

0 to 1 (higher value represents closer annotation matching between the two modalities). (F) Genomic distribution of all the called peaks color coded by the genomic location as shown. Total

called peaks = 492,330. (G) Distribution of all called peaks based on the distance from transcription start sites. EXTENDED DATA FIG. 3 MATERNAL DIABETES DYSREGULATES EPIGENOMIC LANDSCAPE OF

NEURAL CREST CELLS IN PHARYNGEAL ARCHES 4 AND 6. (A) Population distribution by sub-cell-type normalized to total number of cells per sample in neural crest cell subset data of scRNA-seq.

Numbers inside the barplot represent the percentage of cell types of the total cell number. Statistics performed by permutation test in scRNA-seq data, comparing STZ vs. VEH, for NC-prog,

FDR < 0.001, Log2FD = 1.88; for SMC-prog, FDR < 0.001, Log2FD = −0.33. (B) Heatmap of Jaccard indices calculated between neural crest cell scRNA-seq and scATAC-seq cell annotations

after integration. Values range from 0 to 1 (the higher value represents closer annotation matching between those two modalities). (C) MA plot of DARs in PA3/4/6 population between VEH and

STZ. Red dots represent the more accessible (open) (FDR < = 0.05 & Log2FC > = 1) and blue dots represent less accessible (closed) DARs in STZ (FDR < = 0.05 & Log2FC < = 

−1). (D) Enriched TF binding motifs in more accessible (left) or less accessible (right) DARs in STZ vs. VEH within the PA3/4/6 population. (E) scATAC-seq UMAP representation of neural crest

cell C20 subset population colored by clusters (PA3 – dark red; PA4/6 – dark blue). (F) Heatmap of Gene Scores (GS) of curated marker genes based on scRNA-seq data for PA3 and PA4/6 neural

crest. Scale indicates z-scored GS values. (G) MA plot of DARs between VEH and STZ in PA3 population (left) and PA4/6 population (right). Red dots represent the more accessible (open) (FDR 

< = 0.05 & Log2FC > = 1) and blue dots represent less accessible (closed) DARs in STZ (FDR < = 0.05 & Log2FC < = −1). (H) Enriched TF binding motifs in more accessible

(left) and less accessible (right) DARs in STZ in PA4/6 population. NC-prog, neural crest cell progenitors; PA2, pharyngeal arch 2; PA3, pharyngeal arch 3; PA4/6, pharyngeal arch 4/6; SMC,

smooth muscle cells; SMC-prog, smooth muscle cell progenitors. Source data EXTENDED DATA FIG. 4 MATERNAL DIABETES DYSREGULATES EPIGENOMIC AND TRANSCRIPTIONAL LANDSCAPE ASSOCIATED WITH CELL

DIFFERENTIATION AND PATTERNING IN PHARYNGEAL ARCH 2 NEURAL CREST. (A) Violin plot of _Tfap2a_ expression levels in cluster 0 of UMAP in Fig. 2i across 3 VEH and 3 STZ embryos (Wilcoxon Rank

Sum test). (B) Expression of _Nr2f1_ mRNA on UMAP space for PA2 neural crest cells (VEH – left top; STZ – left bottom). Scale bar indicates z-scored expression values. Violin plot of _Nr2f1_

expression levels in cluster 0 of UMAP in Fig. 2i (right) (Wilcoxon Rank Sum test). (C) Expression of indicated genes on UMAP space for PA2 neural crest cells. Scale bar indicates z-scored

expression values. (D) Violin plots of _Dlx5_ (left) and _Dlx6_ (right) expression levels in cluster 0 of UMAP in Fig. 2i (Wilcoxon Rank Sum test). (E) Enriched GO terms in detected DARs in

PA2 population using GREAT analysis. (F) Enriched GO terms in detected DARs in PA3/4/6 population using GREAT analysis. EXTENDED DATA FIG. 5 IDENTIFICATION OF DISTINCT SUBSETS OF AHF

PROGENITORS. (A) scRNA-seq UMAP representation of mesodermal population (‘Meso/CPP’, ‘Cardiomyocyte’, or ‘Epicardium’ in Fig. 1b) colored by conditions (VEH – blue; STZ – light red). (B)

Heatmap of Jaccard indices between mesoderm cell scRNA-seq and scATAC-seq annotations after integration. Values range from 0 to 1 (the higher value represents closer annotation matching

between those two modalities). CM_V, ventricular cardiomyocyte; CM_AVC, atrioventricular canal cardiomyocyte; CM_A, atrial cardiomyocyte; CM_SV, sinus venosus cardiomyocyte; CM_OFT, outflow

tract cardiomyocyte; pSHF1/2, posterior second heart field 1/2; EndoMT, endothelial mesenchymal transition; EpiC, Epicardium; AHF1/2, anterior heart field 1/2; PharyngealMeso, pharyngeal

mesoderm; ParaxialMeso1/2, paraxial mesoderm 1/2; BrM, branchiomeric muscle. (C) Expression pattern of _Hand2_ (left) and _Rgs5 (right)_ on UMAP space. AHF1 and 2 are circled in red. Scale

bar indicates z-scored expression values. EXTENDED DATA FIG. 6 _ALX3_POS CELLS ARE A DISTINCT SUBSET OF THE AHF POPULATION. (A) Representative images from RNA _in situ_ hybridization for

_Armh4_ (green) and _Alx3_ (red) in an E10.5 embryo from VEH treated female. The scale bar represents 500 µm. (B) Representative images from whole mount RNA _in situ_ hybridization of E10.5

embryos using light sheet microscopy. _Armh4_ (green) and _Alx3_ (red) expression is shown from the dorsal view (D – left) and the right oblique view (O – right). A white bracket (left)

highlights the anterior part of _Alx3_Pos cells. A white dotted oval (right) highlights the _Alx3_Pos cell streak on left side of the embryo from outflow tract (OFT) towards the

posterolateral region. Still images were extracted from Supplementary video 2. Scale bar represents 100 µm. PA2, pharyngeal arch 2; BW, body wall. (C) The distribution of _Alx3_ positive

cells by scRNA-seq between E7.75 and E9.25. (D) scRNA-seq UMAP of cardiac progenitor cells at E9.25 from the same data as (C) color coded by cell type annotation. AHF, anterior heart field;

BM progenitors, branchiomeric muscle progenitors; pSHF, posterior second heart field. (E) Expression of _Alx3_ on the same UMAP as (D). (F) Heatmap of differentially expressed genes (DEGs)

between _Alx3_Neg AHF and _Alx3_Pos AHF at E9.25. All detected DEGs that attained adjusted p-val < 0.05 and Log2FC > 0.25 are shown. Top GO terms enriched in upregulated or

downregulated DEGs are shown with representative genes composing each GO (Fisher’s exact test, corrected for multiple testing using the Benjamini-Hochberg method). Scale bar indicates

z-scored expression values. (G) Heatmap presentation of DEGs between AHF1 and AHF2 at E10.5 using only VEH cells in the scRNA-seq data. All detected DEGs that attained adjusted p-val <

0.05 and Log2FC > 0.25 are shown. Top GO terms enriched in upregulated or downregulated DEGs are shown with representative genes composing each GO (Fisher’s exact test, corrected for

multiple testing using the Benjamini-Hochberg method). Scale bar indicates z-scored expression values. (H) Venn diagram representing the intersect between DEGs shown in (F-G). EXTENDED DATA

FIG. 7 PGDM DISRUPTS ANTERIOR-POSTERIOR PATTERNING IN AHF2. (A) Enriched GO terms in VEH vs. STZ DARs in AHF2 population using GREAT analysis. (B) Heatmap of marker genes of each of three

subclusters found in _Alx3_Pos AHF2. These marker genes were detected using only VEH-treated _Alx3_Pos AHF2 cells (left). All marker genes that attained an adjusted p-val < 0.05 and

Log2FC > 0.25 are shown. Scale bar indicates z-scored expression values. Top GO terms enriched in marker genes for each sub cluster with statistical information and representative maker

genes to corresponding GO term are shown (Fisher’s exact test, corrected for multiple testing using the Benjamini-Hochberg method) (right). (C) Genome browser plots for _Hoxb1_ locus. The

top two rows represent the chromatin accessibility in VEH and in STZ within AHF2. The third track from the top shows the genomic location of the DAR with more accessibility in STZ (red

rectangles, highlighted by yellow box). The second track from the bottom represent the links between peaks and gene (‘Peak2GeneLinks’), calculated by ArchR. Darker lines represent stronger

links. The bottom track shows the gene location and transcriptional direction (red – positive strand; blue – negative strand). EXTENDED DATA FIG. 8 ENHANCED RETINOIC ACID SIGNALING IN

PHARYNGEAL ARCH 2 AND AHF2 IN RESPONSE TO HYPERGLYCEMIA. (A) Box plots of the distribution of ChromVAR deviation score for RAR and RXR transcription factor motifs for each cluster in the

neural crest cell population. PA2 neural crest cells are highlighted in red. The X-axis shows the distribution of the Z-score. (STZ – red; VEH – blue) (n = 6 biological samples. n = 3 VEH

replicates and n = 3 STZ replicates). (B) Box plots of the distribution of ChromVAR deviation score for RAR and RXR transcription factor motifs for each cluster in the mesoderm population.

AHF2 cells are highlighted in red. The X-axis shows the distribution of the Z-score. (STZ – red; VEH – blue) (n = 6 biological samples. n = 3 VEH replicates and n = 3 STZ replicates). In the

box plots, the central line indicates the median, box bounds represent the 25th and 75th percentiles, whiskers extend to values within 1.5 times the interquartile range, and outliers lie

beyond this range. EXTENDED DATA FIG. 9 DISRUPTED RETINOIC ACID SIGNALING IS ASSOCIATED WITH DYSREGULATION OF GENE REGULATORY NETWORKS IN PHARYNGEAL ARCH 2 AND AHF2. (A) Dot plot

demonstrating the distribution of the WGCNA modules per cluster. X axis shows the Z-score differences of WGCNA module score per cluster between STZ and VEH and Y axis shows the statistical

significance of the differences. Modules that are not statistically significant are shown in blue, and those that are statistically significant are shown in green or pink. Red label

highlights selected module used for subsequent analysis. (B) Module scores for a gene module detected in the WGCNA analysis that showed statistically significant variation between VEH and

STZ only in PA2. Linear mixed effects models with mouse id as the random effect was used to test the significance of the mean difference in the module score between VEH and STZ (n = 6

biological samples. n = 3 VEH replicates and n = 3 STZ replicates) (linear mixed-effects model with Benjamini-Hochberg multiple-testing correction). (C) Map of functional protein-protein

interactions (PPI) of genes composing the module described in (B), depicted using STRING. Genes composing a core of the PPI network and being downstream of _Tfap2_ are highlighted in red and

bold. (D) Dot plot demonstrating the distribution of the WGCNA modules per cluster. X axis shows the Z-score differences of WGCNA module score per cluster between STZ and VEH and Y axis

shows the statistical significance of the differences. Modules that are not statistically significant are shown in blue, and those that are statistically significant are shown in green or

pink. Red label highlights selected module used for subsequent analysis. (E) Module scores for a cardiac gene regulatory module detected in the WGCNA analysis that showed statistically

significant variation between VEH and STZ only in AHF2. The same statistical test as (B) was used (n = 6 biological samples. n = 3 VEH replicates and n = 3 STZ replicates) (linear

mixed-effects model with Benjamini-Hochberg multiple-testing correction). (F) Map of PPI of genes composing the module described in (E), depicted using STRING. Genes composing a core of the

PPI network and being critical cardiac TFs or signaling genes are highlighted in red and bold. NC-prog, neural crest cell progenitors; PA2, pharyngeal arch 2; PA3, pharyngeal arch 3; PA4/6,

pharyngeal arch 4/6; SMCs, smooth muscle cells; SMC-Prog, smooth muscle cell progenitors; pSHF1/2, posterior second heart field 1/2; AHF1/2, anterior heart field 1/2; ParaxialMeso1/2,

paraxial mesoderm 1/2. In the box plots, the central line indicates the median, box bounds represent the 25th and 75th percentiles, whiskers extend to values within 1.5 times the

interquartile range, and outliers lie beyond this range. EXTENDED DATA FIG. 10 ANTERIOR EXTENSION OF RETINOIC ACID SIGNALING ACTIVITY IN STZ IN VIVO (COMPLEMENTARY TO FIG. 5E, F). (A) X-gal

staining of RARE-LacZ mouse fetuses at E10.5 from VEH and STZ groups (N = 3 each). Second heart field area and outflow tract area are circled with black lines. Highlighted area in magnified

panels to the right show LacZ positive areas detected by threshold analysis as described in methods. The scale bar represents 1 mm. (B) Measurements of area of second heart field and outflow

tract circled with black line in (A) (N = 3 each). (C) Percentage of LacZ positive area with in the second heart field area and outflow tract area circled with black line in (A) (N = 3

each). Source data SUPPLEMENTARY INFORMATION SUPPLEMENTARY INFORMATION Supplementary Fig. 1, Tables 1–5 and Videos 1–5 and source data for the supplementary figure. REPORTING SUMMARY

SUPPLEMENTARY TABLES SUPPLEMENTARY TABLE 1. CARDIAC PHENOTYPES AT E18.5 FROM VEH- OR STZ-TREATED FEMALES BY MICRO-CT. This table presents the number and types of cardiac phenotypes detected

by micro-CT, including atrial septal defect (ASD), patent foramen ovale (PFO), ventricular septal defect (VSD), atrioventricular septal defect (AVSD) and OFT anomalies, in E18.5 embryos from

VEH- or STZ-treated females after cesarean section. Representative micro-CT images are shown in Extended Data Fig. 1b and Supplementary Video 1a,b. There were significant differences in the

presence of cardiac developmental abnormalities between the VEH and STZ groups by two-sided Fisher’s exact test (_P_ = 0.0004). SUPPLEMENTARY TABLE 2. STATISTICAL RESULTS FOR THE POPULATION

CHANGES IN SCRNA-SEQ AND SCATAC-SEQ DATA FOR FIG. 1G, LEFT (A), FOR FIG. 1G, RIGHT (B), AND FOR FIG. 4B (C). SUPPLEMENTARY TABLE 3. STATISTICAL RESULTS FOR THE CHROMVAR ANALYSIS. This table

presents the statistical results from two-sided Wilcoxon rank-sum test with Benjamini–Hochberg multiple-testing correction to determine the differences between the bias-corrected deviations

for a TF motif between VEH and STZ conditions per each cell type displayed in Extended Data Fig. 9a,b. Gray highlighted cell types show the statistical differences. SUPPLEMENTARY TABLE 4.

PRIMER LISTS. Primers for cloning the candidate distal regulatory regions and deletions discussed in Fig. 5a–d and Extended Data Fig. 7a,b. SUPPLEMENTARY TABLE 5. GUIDE RNA AND HDR TEMPLATE

SEQUENCE USED FOR _ALX3_–CRE TARGET ALLELE GENERATION. SUPPLEMENTARY VIDEO 1A 3D MICRO-CT IMAGES OF E18.5 EMBRYONIC HEARTS FROM VEH AND STZ CONDITIONS. A, 3D micro-CT images of the E18.5

embryonic heart from VEH that is shown in Extended Data Fig. 1b. Pulmonary artery (light green), aorta (light red), right ventricle chamber (dark green) and left ventricle chamber (dark

green) are highlighted. B, 3D micro-CT images of the E18.5 embryonic heart from STZ that is shown in Extended Data Fig. 1b. Pulmonary artery (light green), aorta (light red), right ventricle

chamber (dark green), left ventricle chamber (dark green) and conotruncal ventricular septal defect (purple) are highlighted. SUPPLEMENTARY VIDEO 1B 3D MICRO-CT IMAGES OF E18.5 EMBRYONIC

HEARTS FROM VEH AND STZ CONDITIONS. A, 3D micro-CT images of the E18.5 embryonic heart from VEH that is shown in Extended Data Fig. 1b. Pulmonary artery (light green), aorta (light red),

right ventricle chamber (dark green) and left ventricle chamber (dark green) are highlighted. B, 3D micro-CT images of the E18.5 embryonic heart from STZ that is shown in Extended Data Fig.

1b. Pulmonary artery (light green), aorta (light red), right ventricle chamber (dark green), left ventricle chamber (dark green) and conotruncal ventricular septal defect (purple) are

highlighted. SUPPLEMENTARY VIDEO 2 DISTRIBUTION OF _ALX3_-POSITIVE CELLS IN MEF2C–AHF–CRE:AI6 FETUS AT E10.5. Serial coronal optical sections from ventral to dorsal of whole-mount RNA in

situ hybridization. _Alx3_ (red), ZsGreen (green) and DAPI (blue) are shown. Scale bar, 100 µm. SUPPLEMENTARY VIDEO 3 THE SPATIAL RELATIONSHIP BETWEEN _ALX3_-POSITIVE CELLS AND

_ARMH4_-POSITIVE CELLS. The whole-mount RNA in situ hybridization for _Alx3_ (red), _Armh4_ (green) with DAPI (blue). Scale bar, 300 µm. SUPPLEMENTARY VIDEO 4 THE DISTRIBUTION OF

_ALX3–CRE_:AI6 LINEAGE-TRACED CELLS IN NEONATAL HEARTS. Serial coronal optical sections from dorsal to ventral of the _Alx3_Cre/+:Ai6 mouse neonatal heart shown in Fig. 3g. SUPPLEMENTARY

VIDEO 5A RARE ACTIVITY IS ENHANCED IN THE SECOND HEART FIELD AT E10.5 IN MATERNAL DIABETES. A, The whole-mount RNA in situ hybridization for _Alx3_ (green), LacZ (red) with DAPI (blue) in an

E10.5 RARE–LacZ fetus from VEH-treated female. Scale bar, 300 µm. B, The whole-mount RNA in situ hybridization for _Alx3_ (green), LacZ (red) with DAPI (blue) in an E10.5 RARE–LacZ fetus

from STZ-treated female. Scale bar, 300 µm. SUPPLEMENTARY VIDEO 5B RARE ACTIVITY IS ENHANCED IN THE SECOND HEART FIELD AT E10.5 IN MATERNAL DIABETES. A, The whole-mount RNA in situ

hybridization for _Alx3_ (green), LacZ (red) with DAPI (blue) in an E10.5 RARE–LacZ fetus from VEH-treated female. Scale bar, 300 µm. B, The whole-mount RNA in situ hybridization for _Alx3_

(green), LacZ (red) with DAPI (blue) in an E10.5 RARE–LacZ fetus from STZ-treated female. Scale bar, 300 µm. SOURCE DATA SOURCE DATA FIG. 1 Statistical source data. SOURCE DATA FIG. 4

Statistical source data. SOURCE DATA FIG. 5 Statistical source data. SOURCE DATA EXTENDED DATA FIG. 3 Statistical source data. SOURCE DATA EXTENDED DATA FIG. 10 Statistical source data.

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permissions ABOUT THIS ARTICLE CITE THIS ARTICLE Nishino, T., Ranade, S.S., Pelonero, A. _et al._ Single-cell multimodal analyses reveal epigenomic and transcriptomic basis for birth defects

in maternal diabetes. _Nat Cardiovasc Res_ 2, 1190–1203 (2023). https://doi.org/10.1038/s44161-023-00367-y Download citation * Received: 19 August 2022 * Accepted: 19 October 2023 *

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