Identification of the distribution of human endogenous retroviruses K (HML-2) by PCR-based target enrichment sequencing
Bibliographic record
Abstract
BACKGROUND: Human endogenous retroviruses (HERVs), suspected to be transposition-defective, may reshape the transcriptional network of the human genome by regulatory elements distributed in their long terminal repeats (LTRs). HERV-K (HML-2), the most preserved group with the least number of accumulated of mutations, has been associated with aberrant gene expression in tumorigenesis and autoimmune diseases. Because of the high sequence similarity between different HERV-Ks, current methods have limitations in providing genome-wide mapping specific for individual HERV-K (HML-2) members, a major barrier in delineating HERV-K (HML-2) function. RESULTS: In an attempt to obtain detailed distribution information of HERV-K (HML-2), we utilized a PCR-based target enrichment sequencing protocol for HERV-K (HML-2) (PTESHK) loci, which not only maps the presence of reference loci, but also identifies non-reference loci, enabling determination of the genome-wide distribution of HERV-K (HML-2) loci. Here we report on the genomic data obtained from three individuals. We identified a total of 978 loci using this method, including 30 new reference loci and 5 non-reference loci. Among the 3 individuals in our study, 14 polymorphic HERV-K (HML-2) loci were identified, and solo-LTR330 and N6p21.32 were identified as polymorphic for the first time. CONCLUSIONS: Interestingly, PTESHK provides an approach for the identification of the genome-wide distribution of HERV-K (HML-2) and can be used for the identification of polymorphic loci. Since polymorphic HERV-K (HML-2) integrations are suspected to be related to various diseases, PTESHK can supplement other emerging techniques in accessing polymorphic HERV-K (HML-2) elements in cancer and autoimmune diseases.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 teacher head, 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".