A spatial transcriptomics dataset of the endometrium from repeated implantation failure patients

Repeated implantation failure (RIF) presents a significant challenge to in vitro fertilization (IVF), and abnormalities in the endometrium often play a crucial role in RIF. To enhance and deepen our understanding of tissue context in the endometrium underlying RIF, we applied spatial transcriptomics (ST) sequencing using the 10x Visium platform to 8 endometrial tissues from 4 normal individuals (CTR) and 4 RIF patients during the mid-luteal phase in this study. We achieved 10131 high-quality spots, with a median detected gene number of 3156. Seven distinct cellular niches (Niche 1-7) with specific characteristics were identified in our data. Deconvolution of ST data was performed by integrating with a public single-cell RNA (scRNA) dataset, and it was found that unciliated Epithelia were the dominant components in our data. To the best of our knowledge, this is the first spatial transcriptomics atlas of endometrial tissue in normal and RIF conditions, and the spatial data can provide a valuable source for further studies investigating the RIF mechanism.

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Publication Details

Journal
Scientific Data
Published
2025-10-29
DOI
https://doi.org/10.1038/s41597-025-05995-6
Primary Topic
Reproductive System and Pregnancy
Type
article
Field-Weighted Citation Impact
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article

A spatial transcriptomics dataset of the endometrium from repeated implantation failure patients

Meimei Zheng, Lingshan Lei, Zhitao Liu, Yan Zhang et al.
Scientific Data
Reproductive System and Pregnancy
article

A spatial transcriptomics dataset of the endometrium from repeated implantation failure patients

Meimei Zheng, Lingshan Lei, Zhitao Liu, Yan Zhang, Haiping Liu, Ruijuan Liu, Junlin Pan, Peng Wang
article en

Abstract

Repeated implantation failure (RIF) presents a significant challenge to in vitro fertilization (IVF), and abnormalities in the endometrium often play a crucial role in RIF. To enhance and deepen our understanding of tissue context in the endometrium underlying RIF, we applied spatial transcriptomics (ST) sequencing using the 10x Visium platform to 8 endometrial tissues from 4 normal individuals (CTR) and 4 RIF patients during the mid-luteal phase in this study. We achieved 10131 high-quality spots, with a median detected gene number of 3156. Seven distinct cellular niches (Niche 1-7) with specific characteristics were identified in our data. Deconvolution of ST data was performed by integrating with a public single-cell RNA (scRNA) dataset, and it was found that unciliated Epithelia were the dominant components in our data. To the best of our knowledge, this is the first spatial transcriptomics atlas of endometrial tissue in normal and RIF conditions, and the spatial data can provide a valuable source for further studies investigating the RIF mechanism.

Scientific DataVol. 12(1)
People's Liberation Army 401 Hospital (CN), Beijing Anding Hospital (CN)
Openalex Percentile: Top 67%
Reproductive System and Pregnancy
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