Additional file 2 of Lower viral evolutionary pressure under stable versus fluctuating conditions in subzero Arctic brines
Notice bibliographique
Résumé
Additional file 2: Figure S1. Sampling site of Arctic cryopeg brine, sea-ice brine, and seawater near Utqiaġvik, Alaska. The CB samples were collected about 7 m below the permafrost surface (see Methods for more sampling details). SB and CB17 were sampled in 2017, while SW and CB18 were sampled in 2018. Abbreviations: CB, cryopeg brine; SB, sea-ice brine; SW, seawater. Figure S2. Rarefaction curves illustrate the changes of vOTU number across different sequencing depths in cryopeg brine, sea-ice brine, and seawater samples. Figure S3. Rank abundance curves of the top 100 abundant vOTUs in cryopeg brine samples from successive years (CB17 and CB18). The relative abundances of vOTUs (per each community) are ranked by their abundance in the sample CB17. Figure S4. Network clusters of viruses from this study (in green; A, CB; B, SB/SW), RefSeq database, and the 250 tested environmental metagenomes. Each node represents one viral genome/contig; the edge between nodes represents a significant relationship between two viral contigs/genomes with the shorter lengths accounting for stronger connection strength. The sources of viral contigs/genomes are indicated by colors. The details of VC clustering and statistical results are provided in Table S5. Figure S5. Community distributions of cryopeg brine, sea-ice brine, seawater, and GOV2 samples. Viruses in this study and the GOV2 dataset were combined and dereplicated to vOTUs, which were then used as baits to recruit the metagenomic reads generated in this study and GOV2 datasets to create an abundance table of all vOTUs (normalized to 1Gb of sequencing depth in each sample). Then the abundance table was used for generating a Bray Curtis distance matrix to visualize viral community distribution using a NMDS ordination. Sample types are indicated by colors. Figure S6. Phylogenetic tree of the vEpsG and mEpsG genes. The tree was inferred using maximum likelihood method with the EpsG protein sequences. Bootstrap values (expressed as percentages of 1000 replications) ≥40 are shown at the branch points. The scale bar indicates a distance of 1.0. The vEpsG sequence is indicated in red. The mEpsG sequences from CB microbial metagenomes [10] and NCBI nr database are indicated in purple and black, respectively. Figure S7. Multiple alignments of vEpsG and mEpsG protein sequences. The alignments include protein sequences from one vEpsG (numbered as 1), 11 brine mEpsG (numbered as 2–12), and the 10 closest mEpsG (to the vEpsG) from the NCBI nr database (numbered as 13–22). The protein sequences were aligned using MAFFT (v.7.458) with the E-INS-I strategy for 1000 iterations. The position numbers of aligned sequences are indicated at the top of alignments. The conserved motifs were identified by the tool MEME using default parameters and indicated by black boxes over the alignments. Figure S8. Comparisons of microdiversity among samples. (A) Genome-level microdiversity indicated by SNP density. (B) Percentage of genes that have at least one SNP. (C) Gene-level microdiversity indicated by SNP density.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,002 | 0,024 |
| Méta-épidémiologie (sens strict) | 0,002 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,002 | 0,004 |
| Études des sciences et des technologies | 0,002 | 0,000 |
| Communication savante | 0,003 | 0,003 |
| Science ouverte | 0,003 | 0,002 |
| Intégrité de la recherche | 0,002 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,848 | 0,142 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».