Whole-Genome Characterization of Alfalfa Mosaic Virus Obtained from Metagenomic Analysis of Vinca minor and Wisteria sinensis in Iran: with Implications for the Genetic Structure of the Virus
Bibliographic record
Abstract
Alfalfa mosaic virus (AMV), an economically important pathogen, is present worldwide with a very wide host range. This work reports for the first time the infection of Vinca minor and Wisteria sinensis with AMV using RNA sequencing and reverse transcription polymerase chain reaction confirmation. De novo assembly and annotating of contigs revealed that RNA1, RNA2, and RNA3 genomic fragments consist of 3,690, 2,636, and 2,057 nucleotides (nt) for IR-VM and 3,690, 2,594, and 2,057 nt for IR-WS. RNA1 and RNA3 segments of IR-VM and IR-WS closely resembled those of the Chinese isolate HZ, with 99.23-99.26% and 98.04-98.09% nt identity, respectively. Their RNA2 resembled that of Canadian isolate CaM and American isolate OH-2-2017, with 97.96-98.07% nt identity. The P2 gene revealed more nucleotide diversity compared with other genes. Genes in the AMV genome were under dominant negative selection during evolution, and the P1 and coat protein (CP) proteins were subject to the strongest and weakest purifying selection, respectively. In the population genetic analysis based on the CP gene sequences, all 107 AMV isolates fell into two main clades (A, B) and isolates of clade A were further divided into three groups with significant subpopulation differentiation. The results indicated moderate genetic variation within and no clear geographic or genetic structure between the studied populations, implying moderate gene flow can play an important role in differentiation and distribution of genetic diversity among populations. Several factors have shaped the genetic structure and diversity of AMV: selection, recombination/reassortment, gene flow, and random processes such as founder effects.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| 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".