Genetic basis of transcriptome differences between the founder strains of the rat HXB/BXH recombinant inbred panel
Bibliographic record
Abstract
BACKGROUND: With the advent of next generation sequencing it has become possible to detect genomic variation on a large scale. However, predicting which genomic variants are damaging to gene function remains a challenge, as knowledge of the effects of genomic variation on gene expression is still limited. Recombinant inbred panels are powerful tools to study the cis and trans effects of genetic variation on molecular phenotypes such as gene expression. RESULTS: We generated a comprehensive inventory of genomic differences between the two founder strains of the rat HXB/BXH recombinant inbred panel: SHR/OlaIpcv and BN-Lx/Cub. We identified 3.2 million single nucleotide variants, 425,924 small insertions and deletions, 907 copy number changes and 1,094 large structural genetic variants. RNA-sequencing analyses on liver tissue of the two strains identified 532 differentially expressed genes and 40 alterations in transcript structure. We identified both coding and non-coding variants that correlate with differential expression and alternative splicing. Furthermore, structural variants, in particular gene duplications, show a strong correlation with transcriptome alterations. CONCLUSIONS: We show that the panel is a good model for assessing the genetic basis of phenotypic heterogeneity and for providing insights into possible underlying molecular mechanisms. Our results reveal a high diversity and complexity underlying quantitative and qualitative transcriptional differences.
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How this classification was reachedexpand
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 | 0.000 | 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 | 0.001 | 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 teacher head, 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".