Combining Congenic Coverage with Gene Profiling in Search of Candidates for Blood Pressure Quantitative Trait Loci in Dahl Rats
Why this work is in the frame
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Bibliographic record
Abstract
Chromosomes (Chr) 10 and 16 of the Dahl salt-sensitive (S) rat harbor quantitative trait loci (QTLs) for blood pressure (BP). To facilitate gene discovery of these QTLs, gene profiling based on microarrays was combined with fine QTL mapping to identify potential candidate genes that are differentially expressed. First, the region harboring the BP QTL on Chr 16 was narrowed by comparative congenic mapping. In this endeavor, a number of new chromosome markers were generated and used to physically define the chromosome interval in question. Second, in an effort to minimize the costs of gene profiling without sacrificing the chance of gene discovery, a combination congenic strain was produced by replacing one segment of Chr 10 along with one segment of Chr 16 of the hypertensive S rat by those of the normotensive Lewis (LEW) rat. Both of these regions are known to contain BP QTLs. Third, kidneys of this combination congenic strain and the S strain were employed for expression profiling studies. Finally, a comparison between the two strains yielded a number of potentially differentially expressed candidates. Six Established Sequence Tags (ESTs)/genes among them were located in Chr 10 regions and 1 was found in a Chr 16 region, and the genetic make-ups of all these regions were shown to be different between S and LEW. However, none of these ESTs/genes identified by gene profiling were located in an interval containing a QTL. Thus, the present study highlights the importance of correlating the results of gene expression profiling with fine congenic mapping.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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 it