Chromosomal rearrangements and transposable elements in locally adapted island Drosophila
Abstract
Chromosomal rearrangements, particularly those mediated by transposable elements (TEs), can drive adaptive evolution by creating chimeric genes, inducing de novo gene formation, or altering gene expression. Here, we investigate rearrangements evolutionary role during habitat shifts in two locally adapted populations, Drosphila santomea and Drosphila yakuba, who have inhabited the island São Tomé for 500,000 and 10,000 years respectively. Using the D. yakuba- D. santomea species complex, we identified 16,480 rearrangements in the two island populations and the ancestral mainland African population of D. yakuba. We find a disproportionate association with TEs, with 83.5% of rearrangements linked to TE insertions or TE-facilitated ectopic recombination. Using significance thresholds based on neutral expectations, we identify 383 and 468 significantly differentiated rearrangements in island D. yakuba and D. santomea, respectively, relative to the mainland population. Of these, 99 and 145 rearrangements also showed significant differential gene expression, highlighting the potential for adaptive solutions from rearrangements and TEs. Within and between island populations, we find significantly different proportions of rearrangements originating from new mutations versus standing variation depending on TE association, potentially suggesting adaptive genetic mechanisms differ based on the timing of habitat shifts. Functional analyses of rearrangements most likely driving local adaptation revealed enrichment for stress response pathways, including UV tolerance and DNA repair, in high-altitude D. santomea. These findings suggest that chromosomal rearrangements may act as a source of genetic innovation, and provides insight into evolutionary processes that SNP-based analyses might overlook.
- Publication:
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arXiv e-prints
- Pub Date:
- September 2021
- DOI:
- arXiv:
- arXiv:2109.09801
- Bibcode:
- 2021arXiv210909801T
- Keywords:
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- Quantitative Biology - Populations and Evolution;
- Quantitative Biology - Genomics
- E-Print:
- 49 pages