Transcriptomics in human cumulus cells during oocyte in vitro maturation
Data files
Aug 19, 2025 version files 1.16 GB
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Dryad_microarray_Human_cumulus_cells_IVM.zip
1.16 GB
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README.md
4.11 KB
Abstract
Advancing human oocyte in vitro maturation (IVM) requires understanding the mechanisms that govern this process. The cumulus cells (CCs) that surround the oocyte play a crucial role. Our study focused on identifying specific genes in human CCs contributing to oocyte maturation in vitro.
We used microarrays to detail the global transcriptome underlying oocyte maturation in cumulus cells and identified distinct up-and-down-regulated genes and signaling pathways during this process. Cumulus cells were removed from immatures (germinal vesicle - GV) cumulus-oocyte complexes (COCs) before IVM (Fresh GV, n = 5) and immature (GV) and mature (MII) COCs after IVM (GV-IVM, n=8; and MII-IVM, n=12). All the samples were collected ex vivo from 8 women who underwent unilateral ovariectomy and ovarian tissue cryopreservation for fertility preservation. Women did not receive prior ovarian stimulation
https://doi.org/10.5061/dryad.66t1g1k9d
Description of the data and file structure
Advancing human oocyte in vitro maturation (IVM) requires understanding the mechanisms that govern this process. The cumulus cells (CCs) surrounding the oocyte play a crucial role. Our study focused on identifying specific genes in human CCs that may contribute to oocyte maturation in vitro.
Microarray (ClariomTM D arrays with GeneChipTM Whole Transcript (WT) PLUS Reagent Kit) was used to evaluate the overall gene expression of CCs from fresh immature (germinal vesicle - GV) human oocytes (Fresh-GV) and CCs from immature (GV) and mature (metaphase II - MII) oocytes after in vitro maturation (GV-IVM and MII-IVM, respectively).
All the samples were collected ex vivo from the surplus ovarian medulla tissue of 8 women who underwent unilateral ovariectomy and ovarian tissue cryopreservation for fertility preservation. None of them had prior ovarian stimulation. All women gave informed consent to donate their surplus ovarian tissue for research purposes.
Files and variables
Dryad_microarray_Human_cumulus_cells_IVM.zip
Description:
1) CEL files
2) CHP files
File naming convention for CEL and CHP files:
[JCMor]-[RH]-[oocyte number]-[Condition]-[IVM treatment]-[Letter A-H]-[Clariom_D_Human-a1].CEL/CHP
Where:
[JCMor] = Person that generated the date - contributor (Jesús Cadenas Moreno)
[RH] = Hospital where the array was performed (Rigshospitalet, University Hospital of Copenhagen, Denmark)
[Oocyte number] = Internal oocyte ID
[Condition] = Oocyte maturation stage: GV before IVM (GV_Fresh), GV after IVM (GV), or MII after IVM (MII)
[IVM-treatment] = Indicates whether the IVM medium contained the growth factor Midkine (MDK) or no (No MDK)
[Letter A-H]: Internal patient ID. The same letter indicates the cells originated from the same patient. Each letter correspond to a random internal identification patient number (e.g., A = patient 1382)
Description of columns and possible values:
- Condition: Developmental stage of the oocytes; Fresh GV* *(immature before IVM), GV (immature after IVM), or MII (matured in vitro).
- IVM treatment: Whether the oocytes were exposed to the growth factor Midkine during IVM (MDK or No MDK) or collected before IVM (No IVM).
- Patient ID: Random internal code assigned to each patient (e.g.,, 1382,1384, 1390, etc.)
- Diagnosis: Clinical group of the patient (e.g., Breast cancer or Hodgkins lymphoma)
Code/Software
Transcriptome Analysis Console (TAC, v4.0.2.15, Applied Biosystems, Thermo Fisher Scientific) is needed to import (CEL files) or open (CHP files)
Before using TAC, you must install the required library: Click on the preferences tab, click browse, select Clariom_D_Human library, and download it.
You can find them on the product webpage Clariom™ D Assay, human 10 arrays | thermofisher.com in the Section Support Files. They are titled Library Files: Clariom™ D Array, human TAC Analysis Files, r1.
Download the files and Unzip the zipped library folder as well as the folder TAC_CONFIG.zip therein. Then transfer all the contents to the TAC library folder, as specified under Preferences in TAC.
Access information
Non-applicable. The data does not derive from another source
Human subjects data
<p>All patients provided explicit informed consent to donate their surplus ovarian tissue for research purposes, including the potential publication of de-identified data in the public domain.</p>
<p>The data shared in this submission has been fully de-identified. No personal identifiers (e.g., names, social security numbers, etc.) were collected or accessed. Patients were assigned random internal identification numbers that cannot be traced back to individuals. The only other available information includes diagnosis, which is not sufficient to identify any individual participant.</p>
Total RNA was individually extracted and purified from each sample with TRIzol® reagent and 1-bromo-3-chloropropane and, subsequently, with RNeasy® Minikit 250 (Qiagen, Denmark) according to the manufacturer’s instructions. All steps were performed on ice. RNA quality and quantity were assessed by DeNovix DS-11 FX spectrophotometer and Bioanalyzer RNA 6000 Pico Kit, respectively. Only samples with RNA integrity (RIN) values ≥ 6 were included in the study. Moreover, 25 samples were selected based on their RIN values to ensure a similar distribution across all groups: Fresh GV (mean RIN 8.9, n = 5), GV (mean RIN 7.9, n = 8), and MII (mean RIN 8, n = 12) (Supplementary Table S2). The selected samples were further processed using the ClariomTM D arrays with GeneChipTM Whole Transcript (WT) PLUS Reagent Kit according to the manufacturer’s instructions. The array was washed and stained with phycoerythrin-conjugated streptavidin using the Affymetrix Fluidics Station 450 and then scanned with the Affymetrix GeneChipTM Scanner 3000 7G System to generate fluorescent images. The Expression Console Software generated cell intensity files (.CEL files). The raw CEL files were imported into the Transcriptome Analysis Console (TAC, v4.0.2.15, Applied Biosystems). Data summarization, normalization, gene summaries, and statistical analysis were performed in one analysis flow. Normalization was performed by the signal space transduction-robust multi-array average (SST-RMA) approach. The differential expression analysis among CC groups (Fresh GV, GV-IVM, and MII-IVM) was set up using ANOVA ebayes comparison and an overall false discovery rate (FDR) <0.05. For differential expression between groups, an FDR < 0.05 combined with a gene level fold change (FC) <−2 or >2 was considered significant. Furthermore, pathway analysis, principal component analysis (PCA), and hierarchical clustering were performed in TAC.