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Transposable element exonization by non-canonical splicing generates a diversity reservoir of functional protein isoforms

GSE234223 Homo sapiens (human) RNA-seq (gene expression) 106 samples Submitted 2024/12/12 Platform GPL24676
At a glance

RNA-seq (gene expression) · human · 106 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
106 samples: 25 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.
Summary (written by the submitters)
mRNA splicing enlarges the diversity of the protein repertoire, mainly through alternative exon retention or skipping. Although non-canonical splicing variants that exonize intronic regions were recently identified at the mRNA level, their contribution to the cellular proteome remains unclear. Here, we describe a population of 1300 unannotated protein isoforms generated by non-canonical splicing between exons and transposable elements (TE) using a combination of transcriptome assembly, ribosome profiling, and mass spectrometry.
Read the full summary ↓
Despite being shorter and expressed at lower levels, their translation efficiency is similar to that of canonical isoforms, and they are shared between individuals. Functional analyses of 5 different non-canonical isoforms show stable expression, specific intracellular localization, and modified functions, as compared to the corresponding canonical isoforms. Non-canonical isoforms derive mainly from evolutionarily ancient genes and are a preferential source of alternative splicing upon which natural selection can act. We conclude that recently exonized TE isoforms are potentially functional and represent a diversity reservoir of novel protein isoforms.
This dataset
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.

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 GSE234223_RAW.tar (it can run to tens of gigabytes).

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.

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 PRJNA980573 and SRA study SRP441330. Searching any of these in the dataset finder brings you back here.

Study design
25 conditions, mostly with about 5 replicates each
HeLa mNG1-10+, PTEN-JET+, ×5 HeLa mNG1-10+, PTEN-CAN+, ×5 HeLa mNG1-10+, WWOX-JET+, ×5 HeLa mNG1-10+, WWOX-CAN+, ×5 HeLa mNG1-10+, ×5 H1650, SSO13, ×5 H1650, SSO56, ×5 H1650, Scramble, ×5 +19 more

Supports a between-group comparison across 104 samples.

How we read this: 25 replicated groups read from 106 sample titles; they account for 104 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

+ 66 more — browse all 106 samples with per-sample file links →

Datasets on a similar topic

Search all human 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.