Centromere Locations in<i>Brassica</i>A and C Genomes Revealed Through Half-Tetrad Analysis
Bibliographic record
Abstract
Locating centromeres on genome sequences can be challenging. The high density of repetitive elements in these regions makes sequence assembly problematic, especially when using short-read sequencing technologies. It can also be difficult to distinguish between active and recently extinct centromeres through sequence analysis. An effective solution is to identify genetically active centromeres (functional in meiosis) by half-tetrad analysis. This genetic approach involves detecting heterozygosity along chromosomes in segregating populations derived from gametes (half-tetrads). Unreduced gametes produced by first division restitution mechanisms comprise complete sets of nonsister chromatids. Along these chromatids, heterozygosity is maximal at the centromeres, and homologous recombination events result in homozygosity toward the telomeres. We genotyped populations of half-tetrad-derived individuals (from Brassica interspecific hybrids) using a high-density array of physically anchored SNP markers (Illumina Brassica 60K Infinium array). Mapping the distribution of heterozygosity in these half-tetrad individuals allowed the genetic mapping of all 19 centromeres of the Brassica A and C genomes to the reference Brassica napus genome. Gene and transposable element density across the B. napus genome were also assessed and corresponded well to previously reported genetic map positions. Known centromere-specific sequences were located in the reference genome, but mostly matched unanchored sequences, suggesting that the core centromeric regions may not yet be assembled into the pseudochromosomes of the reference genome. The increasing availability of genetic markers physically anchored to reference genomes greatly simplifies the genetic and physical mapping of centromeres using half-tetrad analysis. We discuss possible applications of this approach, including in species where half-tetrads are currently difficult to isolate.
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) | 0.002 | 0.001 |
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".