GEO series
Alternative splicing and differential gene expression during changes in endometrial receptivity in patients with recurrent implantation failure
GSE287072
Homo sapiens (human)
RNA-seq (gene expression)
73 samples
Submitted 2025/10/15
Platform GPL24676
At a glance
RNA-seq (gene expression) · human · 73 samples
- What it is
- RNA-seq (gene expression)Gene activity measured by sequencing. The summary does not mention single-cell work, so this is most likely bulk: one average per sample, the usual starting point for comparing groups.
- Organism
- Homo sapiens (human)
- Samples
- 73 samples: 6 conditions, mostly with about 18 replicates eachGroups are read from the sample names, not from the paper. Check the list below.
- Data you can get
- A processed table (series matrix) and supplementary files from NCBI; the raw sequencing reads from ENA. Which of these hold counts depends on the study, so check the file list.
- Paper
- Alternative splicing and differential gene expression during changes in endometrial receptivity in patients with recurrent implantation failureScientific reports · 2026
Summary (written by the submitters)
Study question : Are there changes in transcript levels as endometrial receptivity changes in patients with recurrent implantation failure (RIF), particularly in alternative splicing events (ASEs), differential expression genes (DEGs) and immune cells levels? Summary answer: Changes in endometrial receptivity affect alternative splicing (AS), differential gene expression and immune cells, and the RNA-binding protein (RBP) KHDRBS3 likelymaybe？ Likely？ is involved in the dysregulation of alternative splicing.
Read the full summary ↓
What is known already: Endometrial receptivity is critical for RIF patients. Researchers have developed transcript level-based models to predict personalized endometrial assessment at WOI. Investigating alternative splicing dysregulation, immune cells and other transcriptional biomarkers in RIF patients may further help to predict endometrial receptivity and improve embryo implantation success. Study design, size, duration: 90 endometrial samples were collected from fertile healthy controls (HC) during the menstrual cycle, including pre-receptive (PR) (luteinising hormone (LH)+3 days/LH+5 days), receptive (R) (LH+7 days) and post-receptive (PS) (LH+9 days) phases. 73 endometrial samples were taken from RIF patients on hormone replacement therapy (HRT) cycles, including PR (progesterone (P)+3 days), R (P+5 days) and PS (P+7 days) phases. Participants/materials, setting, methods: Total RNA was extracted and sequenced for all 163 endometrial samples . Bioinformatic analysis was used to comprehensively investigate the endometrial transcriptome at different stages of receptivity. We elucidated the biological significance of the universal alteration of alternative splicing in endometrial receptivity and further analyzed the role of immune cells and gene expression in this process. In addition, an ASEs-RBPs correlation network was constructed in the endometrial receptive period to evaluate the dysregulation of AS by RBPs. Main results and the role of chance: Global splicing profiling of the four subgroups (HC: PR vs. R; HC: PS vs. R; RIF: PR vs. R; RIF: PS vs. R) consistently showed that skipped exons (SE) and mutually exclusive exons (MXE) were the most common changes in splicing events. These different ASEs occurred at high frequency and some of them could affect the coding potential of a transcript. A greater number of genes with different alternative splicing events (ASEGs) were identified between PR and R phases than between PS and R phases, and the same trend was observed for differentially expressed genes (DEGs). Both ASEGs and DEGs showed enrichment for pathways associated with cell function and adhesion, while DEGs were also enriched for cytokine and immune-related pathways. Immune cell prediction shows that changes in endometrial receptivity phases result in differences in the levels of CD8 T cells, resting NK cells and other immune cells. During the R phase, there was a significant decrease in CD8 T cells and resting NK cells, whereas monocytes and M0 macrophages were significantly increased compared to the endometrial PR phase in RIF patients. Similarly, analysis of immune cells showed a significant increase in CD8 T cells, M1 and M2 macrophages and a significant decrease in activated NK cells in the R phase compared to the PS phase of the endometrium in RIF patients. Some of these immune cells, such as NK cells and monocytes, are highly correlated with certain ASEs. Investigation of ASEs-RBPs networks suggested that KHDRBS3 may be a key regulator of splicing events. Limitations, reasons for caution: The sample size needs to be increased and cover a variety of situations, such as different age, pathology, dietary habits, etc., and alsothe molecular experimental validation needs to be considered. The lack of direct comparisons between natural and HRT cycles in the same sample and molecular experimental validation need to be considered. Wider implications of the findings: Comprehensive transcriptional analysis of the endometrium provide valuable insight into potential biomarkers related to endometrial receptivity and potential treatments for RIF patients. Study funding/competing interest(s): This study was supported by Supported by the Program of National Natural Science of China (Grant No. 81701409). All authors declared that they have no conflicts of interest.
Published in
Wang ML, Lu BJ, Lu X et al.
· Scientific reports 2026
· PMID 41708805
· doi:10.1038/s41598-026-40386-w
This dataset
Download · which file do I need?
Direct links to NCBI and ENA, no account and no request form. Pick by what you want to do: take the small processed table to look, the supplementary files to re-analyse, or the original raw data to start over.
1 · Just have a look
Processed table
The series matrix: one table of values per sample as the submitters processed it. The smallest download, and it opens in Excel or R. Start here to see what the data look like.
2 · Re-analyse it
Supplementary files
The count tables and other files the authors uploaded. Take only the samples you need, or the whole study as GSE287072_RAW.tar (it can run to tens of gigabytes).
3 · Start from the raw reads
Raw sequencing reads
The original FASTQ files, straight from the sequencer, held at ENA. Large, and you align them yourself, so only choose this if you need to re-process the study from scratch.
What the files usually look like: For RNA-seq the counts are usually a table among the supplementary files (look for 'counts', 'expression', 'FPKM' or 'TPM' in the file name). The series matrix of a sequencing study is sometimes nearly empty.
Also filed as BioProject PRJNA1211091 and SRA study SRP557588. Searching any of these in the dataset finder brings you back here.
Study design
6 conditions, mostly with about 18 replicates each
Endometrial cells, P+5, ×20
Endometrial cells, P+3, ×18
Endometrial cells, P+7, ×18
Endometrial cells,p3, ×6
Endometrial cells,p5, ×6
Endometrial cells,p7, ×5
Supports a between-group comparison across 73 samples.
How we read this: 6 replicated groups read from 73 sample titles; they account for 73 of them. These groups are guessed from the sample names, not taken from the paper, so check them against the sample list below before relying on them.
Samples in this study
- GSM8738142 Endometrial cells,p3,110 Endometrial cells,p3,
- GSM8738143 Endometrial cells,p5,111 Endometrial cells,p5,
- GSM8738144 Endometrial cells,p7,112 Endometrial cells,p7,
- GSM8738145 Endometrial cells,p3,113 Endometrial cells,p3,
- GSM8738146 Endometrial cells,p5,114 Endometrial cells,p5,
- GSM8738147 Endometrial cells,p3,115 Endometrial cells,p3,
- GSM8738148 Endometrial cells,p5,116 Endometrial cells,p5,
- GSM8738149 Endometrial cells,p7,117 Endometrial cells,p7,
- GSM8738150 Endometrial cells,p3,118 Endometrial cells,p3,
- GSM8738151 Endometrial cells,p5,119 Endometrial cells,p5,
- GSM8738152 Endometrial cells,p7,120 Endometrial cells,p7,
- GSM8738153 Endometrial cells,p3,121 Endometrial cells,p3,
- GSM8738154 Endometrial cells,p5,122 Endometrial cells,p5,
- GSM8738155 Endometrial cells,p7,123 Endometrial cells,p7,
- GSM8738156 Endometrial cells,p3,124 Endometrial cells,p3,
- GSM8738157 Endometrial cells,p5,125 Endometrial cells,p5,
- GSM8738158 Endometrial cells,p7,126 Endometrial cells,p7,
- GSM8738159 Endometrial cells, P+3, 838 Endometrial cells, P+3,
- GSM8738160 Endometrial cells, P+5, 839 Endometrial cells, P+5,
- GSM8738161 Endometrial cells, P+3, 840 Endometrial cells, P+3,
- GSM8738162 Endometrial cells, P+5, 841 Endometrial cells, P+5,
- GSM8738163 Endometrial cells, P+7, 842 Endometrial cells, P+7,
- GSM8738164 Endometrial cells, P+3, 843 Endometrial cells, P+3,
- GSM8738165 Endometrial cells, P+5, 844 Endometrial cells, P+5,
- GSM8738166 Endometrial cells, P+7, 845 Endometrial cells, P+7,
- GSM8738167 Endometrial cells, P+3, 846 Endometrial cells, P+3,
- GSM8738168 Endometrial cells, P+5, 847 Endometrial cells, P+5,
- GSM8738169 Endometrial cells, P+7, 848 Endometrial cells, P+7,
- GSM8738170 Endometrial cells, P+3, 849 Endometrial cells, P+3,
- GSM8738171 Endometrial cells, P+5, 850 Endometrial cells, P+5,
- GSM8738172 Endometrial cells, P+7, 851 Endometrial cells, P+7,
- GSM8738173 Endometrial cells, P+3, 852 Endometrial cells, P+3,
- GSM8738174 Endometrial cells, P+5, 853 Endometrial cells, P+5,
- GSM8738175 Endometrial cells, P+7, 854 Endometrial cells, P+7,
- GSM8738176 Endometrial cells, P+3, 855 Endometrial cells, P+3,
- GSM8738177 Endometrial cells, P+5, 856 Endometrial cells, P+5,
- GSM8738178 Endometrial cells, P+7, 857 Endometrial cells, P+7,
- GSM8738179 Endometrial cells, P+3, 858 Endometrial cells, P+3,
- GSM8738180 Endometrial cells, P+5, 859 Endometrial cells, P+5,
- GSM8738181 Endometrial cells, P+7, 860 Endometrial cells, P+7,
+ 33 more — browse all 73 samples with per-sample file links →
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- GSE305811 Immune and Transcriptional Landscape of Endometrial Receptivity at P+5 Phase: A Triad Analysis of EIN, RIF, and Control Endometrial Profiles 92 samples shares endometrial, receptivity
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- GSE248784 Glandular Epithelium and Unexplained Recurrent Implantation Failure 21 samples shares implantation, recurrent
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Share this dataset
Metadata from NCBI GEO, cached and refreshed periodically — the NCBI page above is authoritative. Downloads link straight to NCBI/ENA; nothing is proxied through BioTransfer.