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Record W2943601499 · doi:10.3389/fmicb.2019.00955

Accurate Phylogenetic Relationships Among Mycobacterium bovis Strains Circulating in France Based on Whole Genome Sequencing and Single Nucleotide Polymorphism Analysis

2019· article· en· W2943601499 on OpenAlexfundno aff
Amandine Hauer, Lorraine Michelet, Thierry Cochard, Maxime Branger, Javier Nuñez, María-Laura Boschiroli, Franck Biet

Bibliographic record

VenueFrontiers in Microbiology · 2019
Typearticle
Languageen
FieldMedicine
TopicMycobacterium research and diagnosis
Canadian institutionsnot available
FundersMinistère de l'Agriculture, des Pêcheries et de l'Alimentation
KeywordsPhylogenetic treeBiologySingle-nucleotide polymorphismGeneticsMycobacterium bovisGenomeWhole genome sequencingPhylogenetic relationshipPolymorphism (computer science)GenotypePhylogeneticsGeneMycobacterium tuberculosisTuberculosisMedicine

Abstract

fetched live from OpenAlex

In recent years the diversity of the French Mycobacterium bovis population responsible for bovine tuberculosis (bTB) outbreaks since 1970 has been described in detail. To further understand bTB evolution in France, we used Single Nucleotide Polymorphisms (SNP) based on whole genome sequence versus classical genotyping methods in order to identify accurate phylogenetic relationships between M. bovis strains. Whole genome sequencing was carried out on a selection of 87 strains which reflect the French M. bovis population’s genetic diversity. Sequences were compared to the M. bovis reference genome AF2221/97. Comparison among the 87 genomes revealed 9,170 sites where at least one strain shows a SNP with respect to the reference genome; 1,172 are intergenic and 7,998 in coding sequences, of which 2,880 are synonymous and 5,118 non-synonymous. SNP-based phylogenetic analysis using these 9,170 SNP is congruent with the cluster defined by spoligotyping and MLVA typing. In addition, some SNPs were identified as specific to genotypic groups. These findings suggest new SNP targets that can be used for the development of high-resolving methods for genotyping as well as for studying M. bovis evolution and transmission patterns. The detection of non-synonymous SNPs on virulence genes enabled us to distinguish different clusters. Our results seem to indicate that genetically differentiated clusters could also display distinctive phenotypic traits.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.410
Threshold uncertainty score0.833

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.020
GPT teacher head0.238
Teacher spread0.218 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations64
Published2019
Admission routes1
Has abstractyes

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