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Cas13bt3 knockdown of VEGFA mRNA in mammalian cells and mouse retina [RNA-Seq]

GSE259220 Homo sapiens (human) RNA-seq (gene expression) 61 samples Submitted 2024/03/01 Platform GPL24676Platform GPL24247
At a glance

RNA-seq (gene expression) · human · 61 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
61 samples: 17 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.
Summary (written by the submitters)
Purpose: We report expression of a new Cas13 enzyme in retinal cells and evaluate its efficacy in targeting the VEGFA mRNA to establish safety and efficacy of the enzyme for anti-VEGFA therapy. Methods: Mammalian cells (HEK293FT) or mouse retina were treated with shRNA, CasRx or Cas13bt3 carrying VEGFA targeting sgRNA. Total RNA was collected for RNA seqeuencing to study VEGFA mRNA expression and well as off-target genes.
Read the full summary ↓
Results: Significant knockdown of VEGFA mRNA was observed with no effect on predicted off-target genes in mammalina cells and mouse retina. No loss of mouse VEGFA was also detected. Conclusions: AAV2.7m8 can be used for retina-wide transduction, and Cas13bt3 may be a potential new tool for control of VEGFA.
This dataset
Open GSE259220 in finder → Find more 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 GSE259220_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 PRJNA1077071 and SRA study SRP491550. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
17 conditions, mostly in triplicate
batch4_mm_XNT ×6 batch4_mm_VEGFA ×6 batch1_hs_XNT ×4 batch1_hs_XVEGF ×4 batch1_hs_XVEGFAR ×4 batch4_mm_mCherry ×4 batch2_hs_Control ×3 batch2_hs_RXNT ×3 +9 more

Supports a between-group comparison across 61 samples.

How we read this: 17 replicated groups read from 61 sample titles; they account for 61 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

+ 21 more — browse all 61 samples with per-sample file links →

Datasets on a similar topic

Search all RNA-seq datasets in GEO →

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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.