Integration Targeting by Avian Sarcoma-Leukosis Virus and Human Immunodeficiency Virus in the Chicken Genome
Bibliographic record
Abstract
We have analyzed the placement of sites of integration of avian sarcoma-leukosis virus (ASLV) and human immunodeficiency virus (HIV) DNA in the draft chicken genome sequence, with the goals of assessing species-specific effects on integration and allowing comparison to the distribution of chicken endogenous retroviruses (ERVs). We infected chicken embryo fibroblasts (CEF) with ASLV or HIV and sequenced 863 junctions between host and viral DNA. The relationship with cellular gene activity was analyzed by transcriptional profiling of uninfected or ASLV-infected CEF cells. ASLV weakly favored integration in active transcription units (TUs), and HIV strongly favored active TUs, trends seen previously for integration in human cells. The ERVs, in contrast, accumulated mostly outside TUs, including ERVs related to ASLV. The minority of ERVs present within TUs were mainly in the antisense orientation; consequently, the viral splicing and polyadenylation signals would not disrupt cellular mRNA synthesis. In contrast, de novo ASLV integration sites within TUs showed no orientation bias. Comparing the distribution of de novo ASLV integration sites to ERVs indicated that purifying selection against gene disruption, and not initial integration targeting, probably determined the ERV distribution. Further analysis indicated that ERVs in humans, mice, and rats showed similar distributions, suggesting purifying selection dictated their distributions as well.
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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 | 0.000 | 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) | 0.000 | 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".