SUV39H1 regulates KLF4 and chromatin remodeling in smooth muscle cell phenotypic plasticity [RNA-Seq]
RNA-seq (gene expression) · human · 28 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
- 28 samples: 14 × HCASMC, siCtrl, vs 5 × HCASMC, siTET2, vs 5 × HCASMC, siKDM4A, vs 4 × HCASMC, siSUV39H1,Groups 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.
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 GSE298510_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 PRJNA1269584 and SRA study SRP590242. Searching any of these in the dataset finder brings you back here.
Supports a between-group comparison across 28 samples.
How we read this: 4 replicated groups read from 28 sample titles; they account for 28 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.
- GSM9015896 HCASMC, siCtrl, Rep1 HCASMC, siCtrl,
- GSM9015897 HCASMC, siCtrl, Rep2 HCASMC, siCtrl,
- GSM9015898 HCASMC, siCtrl, Rep3 HCASMC, siCtrl,
- GSM9015899 HCASMC, siCtrl, Rep4 HCASMC, siCtrl,
- GSM9015900 HCASMC, siSUV39H1, Rep1 HCASMC, siSUV39H1,
- GSM9015901 HCASMC, siSUV39H1, Rep2 HCASMC, siSUV39H1,
- GSM9015902 HCASMC, siSUV39H1, Rep3 HCASMC, siSUV39H1,
- GSM9015903 HCASMC, siSUV39H1, Rep4 HCASMC, siSUV39H1,
- GSM9015906 HCASMC, siCtrl, Replicate 1 HCASMC, siCtrl,
- GSM9015907 HCASMC, siCtrl, Replicate 2 HCASMC, siCtrl,
- GSM9015908 HCASMC, siCtrl, Replicate 3 HCASMC, siCtrl,
- GSM9015909 HCASMC, siCtrl, Replicate 4 HCASMC, siCtrl,
- GSM9015910 HCASMC, siCtrl, Replicate 5 HCASMC, siCtrl,
- GSM9015911 HCASMC, siTET2, Replicate 1 HCASMC, siTET2,
- GSM9015912 HCASMC, siTET2, Replicate 2 HCASMC, siTET2,
- GSM9015913 HCASMC, siTET2, Replicate 3 HCASMC, siTET2,
- GSM9015914 HCASMC, siTET2, Replicate 4 HCASMC, siTET2,
- GSM9015915 HCASMC, siTET2, Replicate 5 HCASMC, siTET2,
- GSM9015916 HCASMC, siCtrl, Rep_1 HCASMC, siCtrl,
- GSM9015917 HCASMC, siCtrl, Rep_2 HCASMC, siCtrl,
- GSM9015918 HCASMC, siCtrl, Rep_3 HCASMC, siCtrl,
- GSM9015919 HCASMC, siCtrl, Rep_4 HCASMC, siCtrl,
- GSM9015920 HCASMC, siCtrl, Rep_5 HCASMC, siCtrl,
- GSM9015921 HCASMC, siKDM4A, Rep_1 HCASMC, siKDM4A,
- GSM9015922 HCASMC, siKDM4A, Rep_2 HCASMC, siKDM4A,
- GSM9015923 HCASMC, siKDM4A, Rep_3 HCASMC, siKDM4A,
- GSM9015924 HCASMC, siKDM4A, Rep_4 HCASMC, siKDM4A,
- GSM9015925 HCASMC, siKDM4A, Rep_5 HCASMC, siKDM4A,
- GSE282925 DNA hypomethylation promotes UHRF1- and SUV39H1/H2-dependent crosstalk between H3K18ub and H3K9me3 to reinforce heterochromatin states [RNA-Seq] 12 samples shares suv39h1, chromatin, rna-seq
- GSE314625 WSTF deficiency reprograms regulatory networks by linking locus‑specific chromatin remodeling to altered isoform expression and misdirected signaling [mRNA-seq] 18 samples shares remodeling, chromatin, rna-seq
- GSE228133 Deficiency of Smooth Muscle ADAR1 RNA Editing Exacerbates Vascular Remodeling and Pulmonary Hypertension [pul43_RNA-seq] 12 samples shares remodeling, rna-seq, smooth
- GSE289466 Intraindividual epigenetic heterogeneity underlying phenotypic subtypes of advanced prostate cancer [RNA-seq] 98 samples shares phenotypic, rna-seq
- GSE327289 Cerebrovascular Single-Nucleus RNA-Seq Reveals Heat Shock Activation and Vascular Remodeling in Alzheimer’s Disease and Primary Tauopathies 76 samples shares remodeling, rna-seq
- GSE249544 Phenotypical states modulate sensitivity and transcriptional reprogramming in patient-derived glioblastoma cells in response to temozolomide and radiation therapy. [RNA-Seq] 48 samples shares phenotypic, rna-seq
- GSE289930 Proteogenomic Characterization of Primary Oral Cancer Unveils Extracellular Matrix Remodeling and Immunosuppressive Microenvironment Linked to Lymph Node Metastasis [RNA-seq] 33 samples shares remodeling, rna-seq
- GSE276503 Myeloid-derived IL1B drives epithelial and stromal cell remodeling during chronic rhinosinusitis and nasal polyps [scRNA-seq] 33 samples shares remodeling, rna-seq
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.