Pervasive Sex-Linked Effects on Transcription Regulation As Revealed by Expression Quantitative Trait Loci Mapping in Lake Whitefish Species Pairs (Coregonus sp., Salmonidae)
Bibliographic record
Abstract
Mapping of expression quantitative trait loci (eQTL) is a powerful means for elucidating the genetic architecture of gene regulation. Yet, eQTL mapping has not been applied toward investigating the regulation architecture of genes involved in the process of population divergence, ultimately leading to speciation events. Here, we conducted an eQTL mapping experiment to compare the genetic architecture of transcript regulation in adaptive traits, differentiating the recently evolved limnetic (dwarf) and benthic (normal) species pairs of lake whitefish. The eQTL were mapped in three data sets derived from an F(1) hybrid-dwarf backcrossed family: the entire set of 66 genotyped individuals and the two sexes treated separately. We identified strikingly more eQTL in the female data set (174), compared to both male (54) and combined (33) data sets. The majority of these genes were not differentially expressed between male and female progeny of the backcross family, thus providing evidence for a strong pleiotropic sex-linked effect in transcriptomic regulation. The subtelomeric region of a linkage group segregating in females encompassed >50% of all eQTL, which exhibited the most pronounced additive effects. We also conducted a direct comparison of transcriptomic profiles between pure dwarf and normal progeny reared in controlled conditions. We detected 34 differentially expressed transcripts associated with eQTL segregating only in sex-specific data sets and mostly belonging to functional groups that differentiate dwarf and normal whitefish in natural populations. Therefore, these eQTL are not related to interindividual variation, but instead to the adaptive and historical genetic divergence between dwarf and normal whitefish. This study exemplifies how the integration of genetic and transcriptomic data offers a strong means for dissecting the functional genomic response to selection by separating mapping family-specific effects from genetic factors under selection, potentially involved in the phenotypic divergence of natural populations.
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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 | 0.000 | 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 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".