Lingonberry (Vaccinium vitis-idaea L.) species origin and subspecies divergence through genome sequencing and assembly
Bibliographic record
Abstract
Lingonberry (Vaccinium vitis-idaea L.) produces tiny red berries that are tart and nutty in flavour. It grows widely in the circumpolar region, including Scandinavia, northern parts of Eurasia, Alaska, and Canada. Although cultivation is currently limited, the plant has a long history of cultural use among indigenous communities. Given its potential as a food source, genomic resources for lingonberry are significantly lacking. To advance genomic knowledge, the genomes for two subspecies of lingonberry (V. vitis-idaea ssp. minus and ssp. vitis-idaea var. ‘Red Candy’) were sequenced and de novo assembled into contig-level assemblies. The assemblies were scaffolded using the bilberry genome (V. myrtillus) to generate chromosome-anchored reference genome consisting of 12 chromosomes each with total length 548.071 Mbp (contig N50 = 1.170 Mbp, BUSCO (C%) = 96.5%) for ssp. vitis-idaea, and 518.704 Mbp (contig N50 = 1.400 Mbp, BUSCO (C%) = 96.9%) for ssp. minus. RNA sequencing based gene annotation identified 27,243 genes on the ssp. vitis-idaea assembly, and transposable element detection methods found that 45.82% of the genome was repeats. Phylogenetic analysis confirmed that lingonberry is most closely related to bilberry and is more closely related to blueberries than cranberries. Estimates of past effective population size suggested a continuous decline over the past 1-3 MYA, possibly due to the impacts of repeated glacial cycles during Pleistocene leading to frequent population fragmentation. The genomic resource created in this study can be used to identify industry relevant genes (e.g., flavonoid genes), infer phylogeny, and call sequence-level variants (e.g., SNPs) in future research.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".