Effects of Linkage and Epistasis on Intergeneration Correlations in Self‐Pollinated Species
Bibliographic record
Abstract
In breeding for self‐pollinated crop cultivars, early generation testing and selection (EGT) is desirable because it allows for more resources to test superior lines and helps avoid the loss of desirable alleles that would occur if EGT is delayed. However, high intergeneration correlations (IGCs) are required for effective EGT. This study is conducted to determine the effects of linkage and epistasis on IGCs. The covariance between genetic means of lines at early and late selfing generations with both linkage and epistasis is derived. Intergeneration correlations are calculated for different levels of coupling and repulsion linkages and for 10 nonepistatic and epistatic models. Intergeneration correlations are moderate to high in the presence of only additive and dominance effects at unlinked and nonepistatic loci but can be very low (<0.2) in tight repulsion linkages or some allelic and nonallelic effects. Epistasis may mimic or counteract the effects of linkage on changes in IGCs. Thus linkage or epistasis can be an important cause of low IGCs and such genetic causes cannot be changed through testing of more environments. This study points out the need to consider both genetic and nongenetic causes of low IGCs when evaluating the efficiency of EGT in self‐pollinated species.
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 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".