Transcriptome analysis reveals higher levels of mobile element-associated abnormal gene transcripts in temporal lobe epilepsy patients
Bibliographic record
Abstract
Abstract Objective To determine role of abnormal splice variants associated with mobile elements in epilepsy. Methods Publicly available human RNA-seq-based transcriptome data for laser-captured dentate granule cells of post-mortem hippocampal tissues from temporal lobe epilepsy patients with (TLE, N=14 for 7 subjects) and without hippocampal sclerosis (TLE-HS, N=8 for 5 subjects) and healthy individuals (N=51), surgically resected bulk neocortex tissues from TLE patients (TLE-NC, N=17). For each individual sample, de novo transcriptome assembly was performed followed by identification of spliced gene transcripts containing mobile element (ME) sequences (ME-transcripts) to compare the ME-transcript frequency across the sample groups. Enrichment analysis for genes associated with ME-transcripts and detailed sequence examination for representative epileptic genes were performed to analyze the pattern and mechanism of ME-transcripts on gene function. Results We observed significantly higher levels of ME-transcripts in the hippocampal tissues of epileptic patients, particularly in TLE-HS. Among ME classes, SINEs were shown to be the most frequent contributor to ME-transcripts followed by LINEs and DNA transposons. These ME sequences almost in all cases represent older MEs normally located in the intron sequences, leading abnormal splicing variants. For protein coding genes, ME sequences were mostly found in the 3’-UTR regions, with a significant portion also in the coding sequences (CDS) leading to reading frame disruption. Genes associated with ME-transcripts showed enrichment for involvement in the mRNA splicing process in all sample groups, with bias towards neural and epilepsy-associated genes in the epileptic transcriptomes. Significance Our data suggest that abnormal splicing involving MEs, leading to loss of function in critical genes, plays a role in epilepsy, particularly in TLE-HS, providing a novel insight on the molecular mechanisms underlying epileptogenesis. Key points box Significantly higher rates of abnormal splicing variants involving mobile elements (MEs) were observed in the hippocampal tissues of epilepsy patients. SINEs/Alus are most frequently observed in ME-transcripts followed by LINEs and DNA transposons. For protein coding genes, MEs mostly locate in 3’ UTR, but also in coding regions, causing open reading frame disruption, with a bias for neural and epileptic genes. Abnormal splicing involving MEs may be a contributing factor in epileptogenesis.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".