<scp>3D</scp> Genome Constrains Breakpoints of Inversions That Can Act as Barriers to Gene Flow in the Stickleback
Bibliographic record
Abstract
DNA within the nucleus is organised into a well-regulated three-dimensional (3D) structure. However, how such 3D genome structures influence speciation processes remains largely elusive. Recent studies have shown that 3D genome structures influence mutation rates, including the occurrence of chromosomal rearrangement. For example, breakpoints of chromosomal rearrangements tend to be located at topologically associating domain (TAD) boundaries. Here, we hypothesised that TAD structures may constrain the location of chromosomal inversions and thereby shape the genomic landscape of divergence between species with ongoing gene flow, given that inversions can act as barriers to gene flow. To test this hypothesis, we used a pair of Japanese stickleback species, Gasterosteus nipponicus (Japan Sea stickleback) and G. aculeatus (three-spined stickleback). We first constructed chromosome-scale genome assemblies of both species using high fidelity long reads and high-resolution proximity ligation data and identified several chromosomal inversions. Second, via population genomic analyses, we revealed higher genetic differentiation in inverted regions than in colinear regions and no gene flow within inversions, which contrasts with the significant gene flow in colinear regions. Third, using Hi-C data, we revealed 3D genome structures of sticklebacks, delineated by A/B compartments and TADs. Finally, we found that inversion breakpoints tend to be located at TAD boundaries. Thus, our study demonstrates that the 3D genome constrains breakpoints of inversions that can act as barriers to gene flow in the stickleback. Further integration of 3D genome analyses with population genomics could provide novel insights into how the 3D genome influences speciation.
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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 | 0.000 | 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 | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 0.003 |
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".