Genome-wide identification of soybean WRKY transcription factors in response to salt stress
Bibliographic record
Abstract
Members of the large family of WRKY transcription factors are involved in a wide range of developmental and physiological processes, most particularly in the plant response to biotic and abiotic stress. Here, an analysis of the soybean genome sequence allowed the identification of the full complement of 188 soybean WRKY genes. Phylogenetic analysis revealed that soybean WRKY genes were classified into three major groups (I, II, III), with the second group further categorized into five subgroups (IIa-IIe). The soybean WRKYs from each group shared similar gene structures and motif compositions. The location of the GmWRKYs was dispersed over all 20 soybean chromosomes. The whole genome duplication appeared to have contributed significantly to the expansion of the family. Expression analysis by RNA-seq indicated that in soybean root, 66 of the genes responded rapidly and transiently to the imposition of salt stress, all but one being up-regulated. While in aerial part, 49 GmWRKYs responded, all but two being down-regulated. RT-qPCR analysis showed that in the whole soybean plant, 66 GmWRKYs exhibited distinct expression patterns in response to salt stress, of which 12 showed no significant change, 35 were decreased, while 19 were induced. The data present here provide critical clues for further functional studies of WRKY gene in soybean salt tolerance.
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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".