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The complex landscape of structural divergence between the Drosophila pseudoobscura and D. persimilis genomes.

Javier Carpinteyro-PonceCarlos A Machado
Published in: Genome biology and evolution (2024)
Structural genomic variants are key drivers of phenotypic evolution. They can span hundreds to millions of base pairs and can thus affect large numbers of genetic elements. Although structural variation is quite common within and between species, its characterization depends upon the quality of genome assemblies and the proportion of repetitive elements. Using new high-quality genome assemblies, we report a complex and previously hidden landscape of structural divergence between the genomes of Drosophila persimilis and D. pseudoobscura, two classic species in speciation research, and study the relationships among structural variants (SVs), transposable elements (TEs), and gene expression divergence. The new assemblies confirm the already known fixed inversion differences between these species. Consistent with previous studies showing higher levels of nucleotide divergence between fixed inversions relative to collinear regions of the genome, we also find a significant overrepresentation of INDELs inside the inversions. We find that TEs accumulate in regions with low levels of recombination, and spatial correlation analyses reveal a strong association between TEs and SVs. We also report a strong association between differentially expressed genes and SVs, and an overrepresentation of differentially expressed genes inside the fixed chromosomal inversions that separate this species pair. Interestingly, species specific SVs are overrepresented in differentially expressed genes involved in neural development, spermatogenesis, and oocyte-to-embryo transition. Overall, our results highlight the association of TEs with SVs and their importance in driving evolutionary divergence.
Keyphrases
  • genome wide
  • copy number
  • gene expression
  • dna methylation
  • single cell
  • magnetic resonance
  • computed tomography
  • oxidative stress
  • quality improvement
  • contrast enhanced
  • bioinformatics analysis