Genome-wide signatures in flax pinpoint to adaptive evolution along its ecological gradient
Bibliographic record
Abstract
BACKGROUND: Flax is one of the eight founder crops of agriculture. It is believed to have been domesticated as a long-day plant that has since spread to survive in a wide range of eco-geographic regions extending from the warm Indian subcontinent to the low latitude east African highlands and to the cool and high-latitude Eurasia. Understanding the genetic basis underlying its adaptation and selection events throughout its dispersion is essential to develop cultivars adapted to local environmental conditions. METHODS: Here we detected genetic signatures of local adaptation and selection events of flax based on 385 accessions from all major flax growing regions of the world using genome scan methods and three genomic datasets: (1) a genome-wide dataset of more than 275K single nucleotide polymorphisms (SNPs), (2) a filtered dataset of 23K SNPs with minor allele frequency >10% and, (3) a 34K exon-derived SNP dataset. RESULTS: Principal component (PC) and fixation index (FST)-based genome scans yielded consistent outlier SNP loci on chromosomes 1, 8, 9 and 12. Additional loci on chromosomes 3, 7, 8, 10, 11, 13 and 14 were detected using both the PC and FST methods in two of the three datasets. A genome-environment association (GEA) analysis using the 23K dataset and the first PC of cropping season temperature, day-length and latitude identified significant SNPs on chromosomes 3, 7, 9 and 13. CONCLUSIONS: Most of the loci detected by the three methods harbored relevant genes for local adaptation, including some that play roles in day-length, light and other biotic and abiotic stresses responses. Such genetic signatures may help to select pre-breeding materials potentially adapted to specific growing niches prior to field performance trials. Given the current low genotyping cost and freely available environmental data, the genome scans along with GEA can readily provide opportunity to sort out materials suitable to various environmental conditions from large set of germplasm in gene banks and/or in situ, thereby assisting the breeding and genetic conservation efforts.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 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) | 0.002 | 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".