Comparative analysis of butternut (Juglans cinerea) and Japanese walnut (Juglans ailantifolia) chloroplast genomes
Bibliographic record
Abstract
Juglans cinerea L. (2n = 16), commonly known as butternut, is a diploid species native to the eastern forests of the United States and Canada. It plays a crucial ecological role as a food source for wildlife and is traditionally used as a medicine by tribal communities. Butternut populations have severely declined over 50 years due to butternut canker disease (BCD). The ability of butternut to hybridize with Japanese walnut, which exhibits resistance to BCD, complicates hybrid identification based on morphological traits alone. In this study, we assembled the chloroplast genome of butternut using next-generation sequencing, resulting in a genome size of 160,289 bp. The genome comprises 112 genes, including 78 protein-coding genes, 30 tRNA genes, and four rRNA genes, with a GC content of 36%. Comparative analysis revealed 1,156 SNPs, including 500 species-specific SNPs between 13 butternut and 6 Japanese walnut accessions. Of these, 367 SNPs were in coding regions, 32 of which exhibited unique variations causing codon and amino acid changes between the two species. We developed and validated 12 species-specific CAPS markers in matK and ycf1 genes for assessing the genetic background of Juglans species. The ycf1 gene displayed the highest variability, harboring 37 unique SNPs, many resulting in non-synonymous mutations. The newly sequenced chloroplast genome of J. cinerea and the identified SNP resources provide valuable genetic tools for characterizing butternut’s genetic diversity and distinguishing it from Japanese walnut. These findings enhance our understanding of Juglans species and contribute significantly to plant genetics and genomics by comprehensively analyzing chloroplast genomes and SNP variation, addressing a critical gap in previous studies.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".