Genome-wide identification of Thellungiella salsuginea microRNAs with putative roles in the salt stress response
Bibliographic record
Abstract
BACKGROUND: MicroRNAs are key regulators of plant growth and development with important roles in environmental adaptation. The microRNAs from the halophyte species Thellungiella salsuginea (salt cress), which exhibits extreme salt stress tolerance, remain to be investigated. The sequenced genome of T. salsuginea and the availability of high-throughput sequencing technology enabled us to discover the conserved and novel miRNAs in this plant species. It is interesting to identify the microRNAs from T. salsuginea genome wide and study their roles in salt stress response. RESULTS: In this study, two T. salsuginea small RNA libraries were constructed and sequenced using Solexa technology. We identified 109 miRNAs that had previously been reported in other plant species. A total of 137 novel miRNA candidates were identified, among which the miR* sequence of 26 miRNAs was detected. In addition, 143 and 425 target mRNAs were predicted for the previously identified and Thellungiella-specific miRNAs, respectively. A quarter of these putative targets encode transcription factors. Furthermore, numerous signaling factor encoding genes, defense-related genes, and transporter encoding genes were amongst the identified targets, some of which were shown to be important for salt tolerance. Cleavage sites of seven target genes were validated by 5' RACE, and some of the miRNAs were confirmed by qRT-PCR analysis. The expression levels of 26 known miRNAs in the roots and leaves of plants subjected to NaCl treatment were determined by Affymetrix microarray analysis. The expression of most tested miRNA families was up- or down-regulated upon NaCl treatment. Differential response patterns between the leaves and roots were observed for these miRNAs. CONCLUSIONS: Our results indicated that diverse set of miRNAs of T. salsuginea were responsive to salt stress and could play an important role in the salt stress response.
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 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".