Sequence Diversity and Encoded Enzymatic Differences of Monocistronic L1 ORF2 mRNA Variants in the Aged Normal and Alzheimer's Disease Brain
Bibliographic record
Abstract
Reverse transcriptase (RT) activity in the human brain has been inferred through somatic retroinsertion/retrotransposition events; however, actual endogenous enzymatic activities and sources remain unclear. L1 (LINE-1) retrotransposons bicistronically express ORF2, containing RT and endonuclease (EN) domains, and RNA-binding protein ORF1, together enabling L1 retrotransposition and contributing to somatic genomic mosaicism. Here, we assessed endogenous RT activities and L1 mRNA diversity from cerebral cortex samples of 31 Alzheimer's disease (AD) and nondiseased (ND) brains (both sexes) using enzymatic functional assays, targeted PacBio HiFi long-read sequencing, and quantitative spatial transcriptomics. Expected bicistronic, full-length L1 transcripts were absent from most samples, constituting <0.01% of L1 sequences, of which >80% were noncoding. Monocistronic ORF1 and ORF2 transcripts were identified across all samples, consistent with quantitative spatial transcriptomics that identified discordant ORF2 and ORF1 expression in neurons. All brains had RT activity, with AD samples showing less activity, consistent with neuronal loss of terminal AD versus aged ND donors. Brain RT activity was higher in the gray matter and correlated with increased neuronal ORF2 expression, further supporting neuronal contributions. Remarkably, >550 protein-encoding, poly(A + ) ORF2 sequence variants were identified, over two times more than identified in the human reference genome (hg38). Experimental overexpression of full-length and truncated ORF2 variants revealed ∼50-fold RT and ∼1.3-fold EN activity ranges, supporting endogenous functional capacity of monocistronic ORF2 variants in the human brain. The vast sequence diversity of monocistronic ORF2 mRNAs could underlie functional differences in RT-mediated somatic gene recombination/retroinsertion and resulting genomic mosaicism in the normal and diseased brain.
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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 | 0.001 | 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".