NBL1 Associates with Renal Phenotypes in Mice, but Partial Nbl1 Reduction Does Not Ameliorate Kidney Disease: Male Mice with XLAS either HET or WT for Nbl1
RNA-seq (gene expression) · mouse · 24 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
- Mus musculus (mouse)
- Samples
- 24 samples: 24 samples, each with a distinct title — no replicated groupsGroups 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
- NBL1 associates with renal phenotypes in mice, but partial Nbl1 reduction does not ameliorate kidney diseaseAmerican journal of physiology. Renal physiology · 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 GSE310901_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 PRJNA1367497 and SRA study SRP647461. Searching any of these in the dataset finder brings you back here.
Any grouping that defines a comparison lives in the sample characteristics, which GEO records separately from the titles.
How we read this: Read from 24 sample titles: 24 distinct titles with little repetition. 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.
- GSM9311526 S_5324_22, Nbl1xCol4a5, HET, Batch 1
- GSM9311527 S_5329_22, Nbl1xCol4a5, HET, Batch 1
- GSM9311528 S_5330_22, Nbl1xCol4a5, HET, Batch 1
- GSM9311529 S_5999_22, Nbl1xCol4a5, HET, Batch 1
- GSM9311530 S_6001_22, Nbl1xCol4a5, HET, Batch 1
- GSM9311531 S_23_23, Nbl1xCol4a5, HET, Batch 1
- GSM9311532 S_928_24, Nbl1xCol4a5, HET, Batch 2
- GSM9311533 S_292_24, Nbl1xCol4a5, HET, Batch 2
- GSM9311534 S_930_24, Nbl1xCol4a5, HET, Batch 2
- GSM9311535 S_931_24, Nbl1xCol4a5, HET Batch 2
- GSM9311536 S_932_24, Nbl1xCol4a5, HET, Batch 2
- GSM9311537 S_933_24, Nbl1xCol4a5, HET, Batch 2
- GSM9311538 S_941_24, Nbl1xCol4a5, HET, Batch 2
- GSM9311539 S_24_23, Nbl1xCol4a5, WT, Batch 1
- GSM9311540 S_5326_22, Nbl1xCol4a5, WT, Batch 1
- GSM9311541 S_5327_22, Nbl1xCol4a5, WT, Batch 1
- GSM9311542 S_5328_22, Nbl1xCol4a5, WT, Batch 1
- GSM9311543 S_5988_22, Nbl1xCol4a5, WT, Batch 1
- GSM9311544 S_6000_22, Nbl1xCol4a5, WT, Batch 1
- GSM9311545 S_934_24, Nbl1xCol4a5, WT, Batch 2
- GSM9311546 S_935_24, Nbl1xCol4a5, WT, Batch 2
- GSM9311547 S_936_24, Nbl1xCol4a5, WT, Batch 2
- GSM9311548 S_938_24, Nbl1xCol4a5, WT, Batch 2
- GSM9311549 S_939_24, Nbl1xCol4a5, WT, Batch 2
- GSE266874 Pan AMPK-activator O304 ameliorates oxidative stress in MASLD, reverses lipid zonation and reveal lobular metabolic heterogeneitites in the murine live 30 samples shares het, ameliorate
- GSE267630 ST36 acupuncture ameliorates immune cell proliferation and polarization by inhibiting sympathetic activity in rheumatoid arthritis 10 samples shares het, ameliorate
- GSE294832 Modular neuroinflammatory network discovery from large-scale phenotypic screening in genetically heterogeneous mice [part10] 1000 samples shares het
- GSE294911 Modular neuroinflammatory network discovery from large-scale phenotypic screening in genetically heterogeneous mice [part14] 1000 samples shares het
- GSE294535 Modular neuroinflammatory network discovery from large-scale phenotypic screening in genetically heterogeneous mice[part5] 1000 samples shares het
- GSE294849 Modular neuroinflammatory network discovery from large-scale phenotypic screening in genetically heterogeneous mice [part13] 1000 samples shares het
- GSE294826 Modular neuroinflammatory network discovery from large-scale phenotypic screening in genetically heterogeneous mice [part9] 1000 samples shares het
- GSE294983 Modular neuroinflammatory network discovery from large-scale phenotypic screening in genetically heterogeneous mice [part20] 1000 samples shares het
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.