High resolution radiation hybrid maps of bovine chromosomes 19 and 29: comparison with the bovine genome sequence assembly
Bibliographic record
Abstract
BACKGROUND: High resolution radiation hybrid (RH) maps can facilitate genome sequence assembly by correctly ordering genes and genetic markers along chromosomes. The objective of the present study was to generate high resolution RH maps of bovine chromosomes 19 (BTA19) and 29 (BTA29), and compare them with the current 7.1X bovine genome sequence assembly (bovine build 3.1). We have chosen BTA19 and 29 as candidate chromosomes for mapping, since many Quantitative Trait Loci (QTL) for the traits of carcass merit and residual feed intake have been identified on these chromosomes. RESULTS: We have constructed high resolution maps of BTA19 and BTA29 consisting of 555 and 253 Single Nucleotide Polymorphism (SNP) markers respectively using a 12,000 rad whole genome RH panel. With these markers, the RH map of BTA19 and BTA29 extended to 4591.4 cR and 2884.1 cR in length respectively. When aligned with the current bovine build 3.1, the order of markers on the RH map for BTA19 and 29 showed inconsistencies with respect to the genome assembly. Maps of both the chromosomes show that there is a significant internal rearrangement of the markers involving displacement, inversion and flips within the scaffolds with some scaffolds being misplaced in the genome assembly. We also constructed cattle-human comparative maps of these chromosomes which showed an overall agreement with the comparative maps published previously. However, minor discrepancies in the orientation of few homologous synteny blocks were observed. CONCLUSION: The high resolution maps of BTA19 (average 1 locus/139 kb) and BTA29 (average 1 locus/208 kb) presented in this study suggest that by the incorporation of RH mapping information, the current bovine genome sequence assembly can be significantly improved. Furthermore, these maps can serve as a potential resource for fine mapping QTL and identification of causative mutations underlying QTL for economically important traits.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".