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Effects of knockdowns in SERF related proteins on gene expression

GSE249527 Homo sapiens (human) RNA-seq (gene expression) 18 samples Submitted 2024/05/15 Platform GPL24676
At a glance

RNA-seq (gene expression) · human · 18 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
18 samples: 6 conditions, mostly in triplicateGroups 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
Protein G-quadruplex interactions and their effects on phase transitions and protein aggregationNucleic acids research · 2024
Summary (written by the submitters)
SERF family proteins were originally discovered by their ability to accelerate amyloid formation. Human Znf706 and SERF2 proteins are poorly characterized and their physiological function are enigmatic. To get some ideas as to the roles these well conserved proteins play, we analyzed the changes in gene expression that occur upon the knockdown of the encoded genes.
Published in
Protein G-quadruplex interactions and their effects on phase transitions and protein aggregation
Sahoo BR, Kocman V, Clark N et al. · Nucleic acids research 2024 · PMID 38572746 · doi:10.1093/nar/gkae229
This dataset
Open GSE249527 in finder → Find more human RNA-seq datasets →
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.

Series matrix ↓
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 GSE249527_RAW.tar (it can run to tens of gigabytes).

All supplementary files ↗ Whole study · RAW.tar ↓
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.

Raw reads on ENA ↗

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 PRJNA1049439 and SRA study SRP476241. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 38572746) ↗
Study design
6 conditions, mostly in triplicate
HeLa siCTRL ×3 HeLa siZNF706 ×3 HEK293T siCTRL ×3 HEK293T siZNF706 ×3 HeLa siSERF2 ×3 HEK293T siSERF2 ×3

Supports a between-group comparison across 18 samples.

How we read this: 6 replicated groups read from 18 sample titles; they account for 18 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
Datasets on a similar topic

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