Co-localization of quantitative trait loci for pod and kernel traits and development of molecular marker for kernel weight on chromosome Arahy05 in peanut (Arachis hypogaea L.)
Bibliographic record
Abstract
KEY MESSAGE: Stable QTL for pod and kernel traits were co-localized on chromosome Arahy05, and an INDEL marker at 106,411,957 on Arahy05 was developed and validated to be useful for marker-assisted selection of kernel weight. Pod and kernel traits, such as hundred pod weight (HPW), and hundred kernel weight (HKW), along with pod and kernel sizes, are pivotal determinants of yield in peanut breeding programs. This study sought to identify quantitative trait loci (QTL) that are associated with these pod and kernel traits in peanuts. To achieve this, a recombinant inbred line (RIL) population, was derived from a cross between Yuhua15, a cultivar known for its high yield, and a germplasm accession W1202. The investigation uncovered stable and major QTL that are significantly associated with both pod and kernel weight and were consistently co-localized on chromosomes Arahy05 and Arahy08. Furthermore, an INDEL marker was identified and characterized in the QTL interval on Arahy05. An extensive re-sequencing analysis comprising 395 germplasm accessions led to the discovery of two principal haplotypes within a 500-kb window flanking the aforementioned INDEL marker. The haplotypes exhibited a significant correlation with the HKW in our diverse panel of germplasm accessions. Notably, the 170 accessions harboring the haplotype associated with an increased HKW primarily represented botanical varieties, specifically Arachis hypogaea var. hypogaea and A. hypogaea var. hirsuta. On the other hand, the 137 accessions associated with the alternative haplotype, which corresponded to a reduced HKW, were predominately identified as belonging to botanical varieties within A. hypogaea subsp. fastigiata. The INDEL marker located on Arahy05, which demonstrates close linkage to the pod and kernel traits, would be an efficient approach for marker-assisted selection (MAS) of pod and kernel weight in breeding programs.
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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 | 0.000 |
| 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) | 0.001 | 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".