Genetic Dissection of Intermated Recombinant Inbred Lines Using a New Genetic Map of Maize
Bibliographic record
Abstract
A new genetic map of maize, ISU-IBM Map4, that integrates 2029 existing markers with 1329 new indel polymorphism (IDP) markers has been developed using intermated recombinant inbred lines (IRILs) from the intermated B73xMo17 (IBM) population. The website http://magi.plantgenomics.iastate.edu provides access to IDP primer sequences, sequences from which IDP primers were designed, optimized marker-specific PCR conditions, and polymorphism data for all IDP markers. This new gene-based genetic map will facilitate a wide variety of genetic and genomic research projects, including map-based genome sequencing and gene cloning. The mosaic structures of the genomes of 91 IRILs, an important resource for identifying and mapping QTL and eQTL, were defined. Analyses of segregation data associated with markers genotyped in three B73/Mo17-derived mapping populations (F2, Syn5, and IBM) demonstrate that allele frequencies were significantly altered during the development of the IBM IRILs. The observations that two segregation distortion regions overlap with maize flowering-time QTL suggest that the altered allele frequencies were a consequence of inadvertent selection. Detection of two-locus gamete disequilibrium provides another means to extract functional genomic data from well-characterized plant RILs.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".