Phylogenetic measures of indel rate variation among the HIV-1 group M subtypes
Bibliographic record
Abstract
The transmission and pathogenesis of human immunodeficiency virus type 1 (HIV-1) is disproportionately influenced by evolution in the five variable regions of the virus surface envelope glycoprotein (gp120). Insertions and deletions (indels) are a significant source of evolutionary change in these regions. However, the influx of indels relative to nucleotide substitutions has not yet been quantified through a comparative analysis of HIV-1 sequence data. Here we develop and report results from a phylogenetic method to estimate indel rates for the gp120 variable regions across five major subtypes and two circulating recombinant forms (CRFs) of HIV-1 group M. We processed over 26,000 published HIV-1 gp120 sequences, from which we extracted 6,605 sequences for phylogenetic analysis. In brief, our method employs maximum likelihood to reconstruct phylogenies scaled in time and fits a Poisson model to the observed distribution of indels between closely related pairs of sequences in the tree (cherries). The rate estimates ranged from 3.0e-5 to 1.5e-3 indels/nt/year and varied significantly among variable regions and subtypes. Indel rates were significantly lower in the region encoding variable loop V3, and also lower for HIV-1 subtype B relative to other subtypes. We also found that variable loops V1, V2 and V4 tended to accumulate significantly longer indels. Further, we observed that the nucleotide composition of indel sequences was significantly distinct from that of the flanking sequence in HIV-1 gp120. Indels affected potential N-linked glycosylation sites substantially more often in V1 and V2 than expected by chance, which is consistent with positive selection on glycosylation patterns within these regions of gp120. These results represent the first comprehensive measures of indel rates in HIV-1 gp120 across multiple subtypes and CRFs, and identifies novel and unexpected patterns for further research in the molecular evolution of HIV-1.
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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 | 0.003 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".