Data from: Repeat variants for the SbMATE transporter protect sorghum roots from aluminum toxicity by transcriptional interplay in cis and trans
Bibliographic record
Abstract
Acidic soils, where aluminum (Al) toxicity is a major agricultural constraint, are globally widespread and are prevalent in developing countries. In sorghum, the root citrate transporter SbMATE confers Al tolerance by protecting root apices from toxic Al3+, but can exhibit reduced expression when introgressed into different lines. We show that allele-specific SbMATE transactivation occurs and is caused by factors located away from SbMATE. Using expression-QTL mapping and -GWAS, we establish that SbMATE transcription is controlled in a bipartite fashion, primarily in cis but also in trans. Multi-allelic promoter transactivation and ChIP analyses demonstrated that intermolecular effects on SbMATE expression arise from a WRKY and a zinc finger-DHHC transcription factor (TF) that bind to and trans-activate the SbMATE promoter. A haplotype analysis in sorghum RILs indicate that the TFs influence SbMATE expression and Al tolerance. Variation in SbMATE expression likely results from changes in tandemly repeated cis sequences flanking a transposable element (MITE) insertion in the SbMATE promoter, which are recognized by the Al3+-responsive TFs. According to our model, repeat expansion in Al-tolerant genotypes increases TF recruitment and, hence, SbMATE expression, which is, in turn, lower in Al-sensitive genetic backgrounds due to lower TF expression and fewer binding sites. We thus show that even dominant cis regulation of an agronomically-important gene can be subjected to precise intermolecular fine-tuning. These concerted cis/trans interactions, which allow the plant to sense and respond to environmental cues, such as Al3+ toxicity, can now be used to increase yields and food security on acidic soils.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.391 | 0.146 |
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".