Nature CommunicationsEvolutionary BiologyPeer-reviewed journal article
Cross-species insights into placental evolution and diseases at the single-cell resolution
Guanghui Tan, Ao Zhang, Xuesha Cao, Jingyu Yang, Youjie Cui, Fei WangiD, Tao ShiiD, Hengkuan Li, Haoping Wang, Huiquan ShaniD, Jilong ReniD, Yaqi Zhou, Menghan Wang, Funong Luo, Xi Guo, Wuqiang Huo, Yingran Liu, Zhannur NiyazbekovaiD, Xihong WangiD, Zhenyu XiaoiD, Yi ZhengiD, Yu JiangiD
Abstract
The placenta is a highly specialized organ in mammals, mediating the exchange of nutrients, gases, and waste between the mother and the fetus while orchestrating intricate immunological interactions to sustain a successful pregnancy. Despite its essential roles, the molecular evolution underlying the diversity of placentas across mammalian species remains largely elusive. Here, we constructed a comprehensive mammalian placental single-cell transcriptomic atlas from approximately 300,000 cells spanning ten species that could well represent the four primary placental types: (discoid, cotyledonary, diffuse, and zonary. Our cross-species analysis highlights trophoblast lineages as key drivers for placental evolution. By reconstructing differentiation trajectories, we elucidate the gene expression dynamics and regulatory networks shaping trophoblast development across diverse placental architectures. Besides, we propose that the association of human trophoblasts with conditions such as pre-eclampsia and miscarriage arises from their unique gene expression profile, which distinguishes them from trophoblasts of other species. The functional experiments further demonstrate that TGIF1 acts as an upstream regulator of key functional genes in extravillous trophoblast cells, modulating their growth, invasion, and migration. Additionally, TGIF1, along with its target genes, such as ADAM12, WNT3A, and ZNF831, is associated with preeclampsia and pregnancy loss. Collectively, these findings provide a high-resolution framework to understand the molecular evolution of the placenta and its role in reproductive success and diseases.
- organism: human
- organism: mouse
- organism: rat
- assay: scRNA-seq
- research focus: cell type annotation
- research focus: gene regulatory network inference
- research focus: differential expression
- approach: deep learning
- approach: statistical model
- Citations
- 1
- FWCI
- 8.96
- Field percentile
- top 4%
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