Whole genome sequencing of three mesorhizobia isolated from northern Canada to identify genomic adaptations promoting nodulation in cold climates
Bibliographic record
Abstract
ABSTRACT The N2-fixing symbiosis between rhizobia and legumes is negatively impacted by numerous stresses, including low temperatures. To identify genomic features and biochemical pathways of rhizobia that could foster improved symbiotic function under low temperatures, we isolated and characterized three Mesorhizobium strains from legume nodules collected at two distant northern Canadian sites. Whereas the classical determinants of nodulation and nitrogen fixation are located on the chromosome of most mesorhizobia, whole genome sequencing revealed that these genes are on a large symbiotic megaplasmid in all three of the newly isolated strains. A pangenome-wide association study identified 25 genes putatively associated with mesorhizobia isolated from arctic or subarctic environments, with the genomic location of many of these genes implying a relationship with legume symbiosis. Phylogenetic and sequence analyses of the common nodulation genes revealed alleles that are highly conserved amongst mesorhizobia isolated from northern climates but uncommon in mesorhizobia isolated from similar plant hosts in other climatic regions, suggesting potential functional adaptive differences and the horizontal transfer of these alleles between northern rhizobia. We speculate that nod sequence divergence was driven by climatic factors, and that the encoded proteins may be particularly stable and/or active at low temperatures.
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".