Integrating LCM-Based Spatio-Temporal Transcriptomics Uncovers Conceptus and Endometrial Luminal Epithelium Communication that Coordinates the Conceptus Attachment in Pigs.
IF: 6.208
Cited by: 10


Attachment of conceptus to the endometrial luminal epithelium (LE) is a critical event for early placentation in Eutheria. Since the attachment occurs at a particular site within the uterus, a coordinated communication between three spatially distinct compartments (conceptus and endometrial LE from two anatomical regions of the uterus to which conceptus attaches and does not attach) is essential but remains to be fully characterized. Using the laser capture microdissection (LCM) technique, we firstly developed an approach that can allow us to pair the pig conceptus sample with its nearby endometrial epithelium sample without losing the native spatial information. Then, a comprehensive spatio-temporal transcriptomic profile without losing the original conceptus-endometrium coordinates was constructed. The analysis shows that an apparent difference in transcriptional responses to the conceptus exists between the endometrial LE from the two anatomically distinct regions in the uterus. In addition, we identified the communication pathways that link the conceptus and endometrial LE and found that these pathways have important roles in conceptus attachment. Furthermore, a number of genes whose expression is spatially restricted in the two different anatomical regions within the uterus were characterized for the first time and two of them (SULT2A1 and MEP1B) may cooperatively contribute to establish conceptus attachment in pigs. The results from our study have implications in understanding of conceptus/embryo attachment in pigs and other large polytocous species.


Temporal Transcriptomics
conceptus attachment
endometrial luminal epithelium
laser capture microdissection
spatio-temporal transcriptomics

MeSH terms

Cell Communication
Embryo Implantation
Embryo, Mammalian
Laser Capture Microdissection


Wang, Feiyu
Zhao, Shilei
Deng, Dadong
Wang, Weiwei
Xu, Xuewen
Liu, Xiaolei
Zhao, Shuhong
Yu, Mei

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