Comprehensive Sequence Analysis of IQD Gene Family and their Expression Profiling in Grapevine (Vitis vinifera)
Bibliographic record
Abstract
The plant-specific IQ67-domain (IQD) protein family members are downstream targets of calcium sensors, known to regulate plant growth and lateral organ polarity, and basal defense response against environmental cues. No systematic study of IQD gene family has been performed on grapevine. The public availability of grapevine genome enables us to perform identification, phylogeny, chromosomal orientation, and gene structure analysis of the IQD genes in grapevine. We identified 49 VvIQD genes (VvIQD1–VvIQD49) and further classified them into eight subgroups based on phylogenetic relationships. The 49 VvIQD genes were assigned to 19 different chromosomal positions. The collinear relationship between grapevine and Arabidopsis IQDs (VvIQD and AtIQD), and within grapevine VvIQDs, was highly conserved. In addition, most of duplicated gene pairs showed Ka/Ks ratio less than 1.00, indicating purifying selection within these gene pairs, implying functional discrepancy after duplication. Transcription profiling of VvIQD genes shed light on their specific role in grapevine tissue and organ development. The qRT-PCR validation of the 49 VvIQD genes in grape berry tissue from cultivars with distinct berry shape during developmental phases suggested candidate genes involved in the shape of grape berries. The subcellular prediction of VvIQD22, VvIQD23, VvIQD38, and VvIQD49 genes validated their localization in the nucleus and plasma membrane. The VvIQD49 protein interaction with VvCaM2 was also verified by bimolecular fluorescence complementation (BiFC) analysis in the plasma membrane. Our findings will be valuable for the functional genomic studies for desirable shape development of grape berries.
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 | 0.001 | 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) | 0.001 | 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".