bioRxivGenomicsPreprint
A Multiomics, Spatiotemporal, and Single Cell Atlas for Mapping Cell-Type-Specific Dysregulation at the Maternal-Fetal Interface
Cheng WangiD, Yan ZhouiD, Yuejun Jessie WangiD, Tuhin Kumar GuhaiD, Zhida Luo, Tara I. McIntyreiD, Marisa Eve SchwabiD, Brittany R. DavidsoniD, Gabriella C. ReederiD, Ronald J. WongiD, Sarah K. EnglandiD, Juan Manuel GonzaleziD, Robert H. BlellochiD, Alexis J. CombesiD, Linda C. GiudiceiD, Adrian ErlebacheriD, Tippi C. MacKenzieiD, David K. StevensoniD, Gary Michael ShawiD, Michael P. SnyderiD, Susan J. FisheriD, Virginia D. WinniD, Jingjing LiiD
Abstract
The placenta, the first organ to functionally mature, undergoes disordered development in many pregnancy complications. Molecular investigations have been hampered by the extreme cellular heterogeneity of the placenta, and this complexity is further exaggerated at the maternal-fetal interface where maternal and fetal cells co-mingle. We generated the paired single nucleus epigenomes and transcriptome for each of [~]200,000 cells at the human maternal-fetal interface from early pregnancy to term. These data identified cell-type-specific transcriptional regulatory programs and uncovered key transcription factors driving the lineage differentiation of placental cytotrophoblasts. Integrating spatial single cell proteomics profiling, we localized the observed cell types in situ, and characterized the dynamic stages and distinct features of endothelial cells of maternal spiral arteries remodeled by extravillous cytotrophoblasts. Integrative analyses of the single cell data across gestation enabled fine-mapping of the developmental trajectories of cytotrophoblasts and decidual stromal cells, and defining the signature molecular profiles of known and novel cell (sub)types. To demonstrate clinical value, we integrated the reference single cell data with large-scale population genomes from pregnancy complications and identified the most vulnerable maternal and fetal cell types in preeclampsia, preterm birth, and miscarriage. This study presents the most comprehensive placental and decidual single cell resource across gestation to date, reveals new insights into the drivers of normal human placentation, and uncovers the cellular basis of dysfunction associated with common pregnancy complications.
- organism: human
- assay: scRNA-seq
- assay: spatial transcriptomics
- assay: DNA methylation
- research focus: cell type annotation
- research focus: trajectory inference
- research focus: differential expression
- research focus: database / resource
- approach: statistical model
- approach: machine learning (classical)
- Citations
- 1
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