BAP1 dysregulation impairs trophoblast differentiation and contributes to placental dysfunction in preeclampsia
RNA-seq (gene expression) · human · 32 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
- 32 samples: 8 conditions, mostly with about 5 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
- BAP1 dysregulation impairs trophoblast differentiation and contributes to placental dysfunction in preeclampsiaCell death & disease · 2026
Read the full summary ↓
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.
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.
Supplementary files
The count tables and other files the authors uploaded. Take only the samples you need, or the whole study as GSE311483_RAW.tar (it can run to tens of gigabytes).
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 PRJNA1369537 and SRA study SRP648965. Searching any of these in the dataset finder brings you back here.
Supports a between-group comparison across 32 samples.
How we read this: 8 replicated groups read from 32 sample titles; they account for 32 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.
- GSM9325875 Control hTSC_1 Control hTSC
- GSM9325876 Control hTSC_2 Control hTSC
- GSM9325877 Control hTSC_3 Control hTSC
- GSM9325878 Control hTSC_4 Control hTSC
- GSM9325879 Control hTSC_5 Control hTSC
- GSM9325880 BAP1-OE hTSC_10 BAP1-OE hTSC
- GSM9325881 BAP1-OE hTSC_7 BAP1-OE hTSC
- GSM9325882 BAP1-OE hTSC_8 BAP1-OE hTSC
- GSM9325883 BAP1-OE hTSC_9 BAP1-OE hTSC
- GSM9325884 BAP1-OE hTSC_6 BAP1-OE hTSC
- GSM9325885 BAP1-OE STB_10 BAP1-OE STB
- GSM9325886 BAP1-OE STB_6 BAP1-OE STB
- GSM9325887 BAP1-OE STB_7 BAP1-OE STB
- GSM9325888 BAP1-OE STB_8 BAP1-OE STB
- GSM9325889 BAP1-OE STB_9 BAP1-OE STB
- GSM9325890 Control STB_1 Control STB
- GSM9325891 Control STB_2 Control STB
- GSM9325892 Control STB_3 Control STB
- GSM9325893 Control STB_4 Control STB
- GSM9325894 Control STB_5 Control STB
- GSM9325895 BAP1-OE Organoid_1 BAP1-OE Organoid
- GSM9325896 BAP1-OE Organoid_2 BAP1-OE Organoid
- GSM9325897 BAP1-OE Organoid_3 BAP1-OE Organoid
- GSM9325898 BAP1-OE Organoid_4 BAP1-OE Organoid
- GSM9325899 Control Organoid_1 Control Organoid
- GSM9325900 Control Organoid_2 Control Organoid
- GSM9325901 Control Organoid_3 Control Organoid
- GSM9325902 Control Organoid_4 Control Organoid
- GSM9325903 BAP1-OE EVT_3 BAP1-OE EVT
- GSM9325904 BAP1-OE EVT_4 BAP1-OE EVT
- GSM9325905 Control EVT_1 Control EVT
- GSM9325906 Control EVT_2 Control EVT
- GSE255126 Activated PRDM1-CREBBP Axis Contributes to Apoptosis and Impaired Invasion of Trophoblasts: A Novel Mechanism Underlying Preeclampsia 10 samples shares preeclampsia, trophoblast, contributes
- GSE295760 Multi-omics of chorionic villus samples reveals early pregnancy placental dysfunction associated with preeclampsia 38 samples shares preeclampsia, dysfunction, placental
- GSE243579 iPSC-based modeling of preeclampsia identifies defects in extravillous trophoblast differentiation 144 samples shares preeclampsia, trophoblast
- GSE306864 Placental transcriptome profiles in late-onset preeclampsia: a cross-sectional observational analysis stratified by fetal sex 58 samples shares preeclampsia, placental
- GSE303840 Racial discrepancies in placental gene expressions between Black and White healthy and preeclampsia patients of equivalent BMI and blood pressure in a Southeastern USA cohort 24 samples shares preeclampsia, placental
- GSE287645 Maternal cause of early-onset preeclampsia: excessive endometrial gland-derived apolipoprotein D induces placental ferroptosis and developmental abnormalities 16 samples shares preeclampsia, placental
- GSE290578 Searching for the influencers among placental immune cells in preeclampsia. 16 samples shares preeclampsia, placental
- GSE308999 Dysregulation of RNA Editing Contributes to Platinum Resistance in Ovarian Cancer 14 samples shares dysregulation, contributes
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.