MicroRNAs Involved in Regulatory Cytoplasmic Male Sterility by Analysis RNA-seq and Small RNA-seq in Soybean
Bibliographic record
Abstract
Cytoplasmic male sterility (CMS) is an important plant characteristic for exploiting heterosis to enhance crop traits during breeding. However, the CMS regulatory network remains unclear in plants, even though researchers have attempted to isolate genes associated with CMS. In this study, we performed high-throughput sequencing and degradome analyses to identify microRNAs (miRNAs) and their targets in a soybean CMS line (JLCMS9A) and its maintainer line (JLCMS9B). Additionally, the differentially expressed genes during reproductive development were identified using RNA-seq data. A total of 280 miRNAs matched soybean miRNA sequences in miRBase, including mature miRNAs and pre-miRNAs. Of the 280 miRNAs, 30, 23, and 21 belonged to the miR166, miR156, and miR171 families, respectively. Moreover, 410 novel low-abundant miRNAs were identified in the JLCMS9A and JLCMS9B flower buds. Furthermore, 303 and 462 target genes unique to JLCMS9A and JLCMS9B, respectively, as well as 782 common targets were predicted based on the degradome analysis. Target genes differentially expressed between the CMS line and the maintainer line were revealed by an RNA-seq analysis. Moreover, all target genes were annotated with diverse functions related to biological processes, cellular components, and molecular functions, including transcriptional regulation, the nucleus, meristem maintenance, meristem initiation, cell differentiation, auxin-activated signaling, plant ovule development, and anther development. Finally, a network was built based on the interactions. Analyses of the miRNA, degradome, and transcriptome datasets generated in this study provided a comprehensive overview of the reproductive development of a CMS soybean line. The data presented herein represent useful information for soybean hybrid breeding. Furthermore, the study results indicate that miRNAs might contribute to the soybean CMS regulatory network by modulating the expression of CMS-related genes. These findings lay the foundation for future studies on the molecular mechanisms underlying soybean CMS.
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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 | 0.001 |
| 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".