Identification and Analysis of lncRNA and circRNA Related to Wheat Grain Development
Bibliographic record
Abstract
The role of lncRNA and circRNA in wheat grain development is still unclear. The objectives of this study were to characterize the lncRNA and circRNA in the wheat grain development and to construct the interaction network among lncRNA, circRNA, and their target miRNA to propose a lncRNA-circRNA-miRNA module related to wheat grain development. Full transcriptome sequencing on two wheat varieties (Annong 0942 and Anke 2005) with significant differences in 1000-grain weight at 10 d (days after pollination), 20 d, and 30 d of grain development were conducted. We detected 650, 736, and 609 differentially expressed lncRNA genes, and 769, 1054, and 1062 differentially expressed circRNA genes in the grains of 10 days, 20 days and 30 days after pollination between Annong 0942 and Anke 2005, respectively. An analysis of the lncRNA-miRNA and circRNA-miRNA targeting networks reveals that circRNAs exhibit a more complex and extensive interaction network in the development of cereal grains and the formation of grain shape. Central to these interactions are tae-miR1177, tae-miR1128, and tae-miR1130b-3p. In contrast, lncRNA genes only form a singular network centered around tae-miR1133 and tae-miR5175-5p when comparing between varieties. Further analysis is conducted on the underlying genes of all target miRNAs, we identified TaNF-YB1 targeted by tae-miR1122a and TaTGW-7B targeted by miR1130a as two pivotal regulatory genes in the development of wheat grains. The quantitative real-time PCR (qRT-PCR) and dual-luciferase reporter assays confirmed the target regulatory relationships between miR1130a-TaTGW-7B and miR1122a-TaNF-YB1. We propose a network of circRNA and miRNA-mediated gene regulation in the development of wheat grains.
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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 | 0.001 | 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".