Single nucleotide polymorphism analysis reveals heterogeneity within a seedling tree population of a polyembryonic mango cultivar
Bibliographic record
Abstract
Within a polyembryonic mango seedling tree population, the genetic background of individuals should be identical because vigorous plants for cultivation are expected to develop from nucellar embryos representing maternal clones. Due to the fact that the mango cultivar 'Hôi' is assigned to the polyembryonic ecotype, an intra-cultivar variability of ethylene receptor genes was unexpected. Ethylene receptors in plants are conserved, but the number of receptors or receptor isoforms is variable regarding different plant species. However, it is shown here that the ethylene receptor MiETR1 is present in various isoforms within the mango cultivar 'Hôi'. The investigation of single nucleotide polymorphisms revealed that different MiETR1 isoforms can not be discriminated simply by individual single nucleotide exchanges but by the specific arrangement of single nucleotide polymorphisms at certain positions in the exons of MiETR1. Furthermore, an MiETR1 isoform devoid of introns in the genomic sequence was identified. The investigation demonstrates some limitations of high resolution melting and ScreenClust analysis and points out the necessity of sequencing to identify individual isoforms and to determine the variability within the tree population.
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 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 | 0.000 |
| 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) | 0.001 | 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".