Genomic characterization and physical mapping of two fucosyltransferase genes in<i>Medicago truncatula</i>
Bibliographic record
Abstract
Fucosyltransferases catalyse fucose transfer onto oligosaccharides. Two fucosylated structures have been identified in plants: the alpha1,4-fucosylated Lewis-a epitope and the alpha1,3-fucosylated core. Here we report the cloning, genomic characterization, and physical mapping of two genes encoding proteins similar to alpha1,4-fucosyltransferase (EC 2.4.1.65, MtFUT1) and alpha1,3-fucosyltransferase (EC 2.4.1.214, MtFUT2) in Medicago truncatula. Analysis of the genomic organization of the fucosyltransferase genes in M. truncatula, revealed the presence of two genomic variants of the MtFUT1 gene coding sequence, one containing a single intron and the other intronless, whereas in MtFUT2, the gene coding region is interrupted by four introns. Using for the first time fluorescence in situ hybridization (FISH) to physically map fucosyltransferase genes in plants, this study reveals a high genomic dispersion of these genes in Medicago. The MtFUT1 genes are mapped on chromosomes 4, 7, and 8, colocalizing on three of the five MtFUT2 loci. Chromosomes 1 and 5 carry the additional MtFUT2 loci. Moreover, the intensity of the FISH signals reveals marked differences in the number of gene copies per locus for both genes. Simultaneous mapping of rRNA genes on chromosome 5 shows that several MTFUT2 gene loci are inserted within the rDNA array. Insertions of coding DNA sequences into the rDNA repeats were never reported to date.
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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) | 0.000 | 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 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".