Marker Assisted Introgression of drought tolerance QTLs into popular high yielding varieties of rice
Bibliographic record
Abstract
Rice is the major staple cereal of India cultivated in about 44 million hectares area. In recent years, the increased occurrence and severity of drought stress has led to a yield decline in rice. This calls for development of varieties with higher yield potential combining drought tolerance. Even though many QTLs have been identified for various drought-related traits in rice; there are only few efforts to introgress them to develop improved breeding lines. Hence, the present research work aimed to transfer three QTL regions viz. qDTY1.1, qDTY2.2 and qDTY4.1 from Drt1IR-64 through marker-assisted breeding with the strategy of improving the grain yield of popular high yielding varieties of rice (MTU1010 and NLR34449) under reproductive stage drought stress. The parents (Drt1IR64, MTU1010 and NLR34449) were screened with flanking markers of the targeted QTLs. Among all, RM551 (qDTY4.1) showed clear polymorphism between drought tolerant (DrtIR64) and susceptible lines (MTU1010 and NLR34449).The flanking markers of qDTY2.2 (RM555, RM279 and RM492) showed polymorphism of DrtIR64 with MTU1010 and NLR34449.Using these polymorphic markers as foreground markers, the BC 1 F 1 plants obtained from MTU1010/DrtIR64 (Donor for qDTY1.1, qDTY2.2 and qDTY4.1) and NLR34449/DrtIR64 were confirmed for the presence of the targeted genes. Later, the confirmed BC 1 F 1 plants of two crosses will be backcrossed with recipient parents. Screening of the parents is being carried out at molecular level employing SSR markers that spanned the total genome, for identification of polymorphic markers. These will be used as background markers to test the recovery of recurrent genome content in the BC 2 F 2 progeny.
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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 | 0.001 | 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".