Integrated eQTL mapping approach reveals genomic regions regulating candidate genes of the E8-r3 locus in soybean
Bibliographic record
Abstract
Deciphering the gene regulatory networks of critical quantitative trait loci associated with early maturity provides information for breeders to unlock soybean’s ( Glycine max (L.) Merr.) northern potential and expand its cultivation range. The E8-r3 locus is a genomic region regulating the number of days to maturity under constant short-day photoperiodic conditions in two early-maturing soybean populations (QS15524 F2:F3 and QS15544 RIL ) belonging to maturity groups MG00 and MG000. In this study, we developed a combinatorial expression quantitative trait loci mapping approach using three algorithms (ICIM, IM, and GCIM) to identify the regions that regulate three candidate genes of the E8-r3 locus ( Glyma.04G167900 / GmLHCA4a , Glyma.04G166300 / GmPRR1a , and Glyma.04G159300 / GmMDE04 ). Using this approach, a total of 2,218 trans (2,061 genes)/7 cis (7 genes) and 4,073 trans (2,842 genes)/3,083 cis (2,418 genes) interactions were mapped in the QS15524 F2:F3 and QS15544 RIL populations, respectively. From these interactions, we successfully identified two hotspots (F2_GM15:49,385,092-49,442,237 and F2_GM18:1,434,182-1,935,386) and three minor regions (RIL_GM04:17,227,512-20,251,662, RIL_GM04:31,408,946-31,525,671 and RIL_GM13:37,289,785-38,620,690) regulating the candidate genes of E8-r3 and several of their homologs. Based on co-expression network and single nucleotide variant analyses, we identified ALTERED PHLOEM DEVELOPMENT ( Glyma.15G263700 ) and DOMAIN-CONTAINING PROTEIN 21 ( Glyma.18G025600 ) as the best candidates for the F2_GM15:49,385,092-49,442,237 and F2_GM18:1,434,182-1,935,386 hotspots. These findings demonstrate that a few key regions are involved in the regulation of the E8-r3 candidates GmLHCA4a , GmPRR1a , and GmMDE04 .
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| 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".