bioRxivEvolutionary BiologyPreprint
Genome size changes by duplication, insertion and divergence in Caenorhabditis worms
J. D. Milwood, J. M. Sutton, P. E. Adams, J. Pienaar, J. L. Fierst
Abstract
Genome size has been measurable since the 1940s but we still do not understand the basis of genome size variation. Caenorhabditis nematodes show strong conservation of chromosome number but vary in genome size between closely related species. Androdioecy, where populations are composed of males and self-fertile hermaphrodites, has evolved from outcrossing, female-male dioecy, three times in this group. Androdioecious genomes are 10-30% smaller than dioecious species but large phylogenetic distances and rapid protein evolution have made it difficult to pinpoint the basis of these changes. Here, we analyze the genome sequences of Caenorhabditis and and test three hypotheses explaining genome evolution: 1) genomes evolve through deletions and genome shrinkage in androdioecious species; 2) genome size is determined by transposable element (TE) expansion and DNA loss through large deletions (the accordion model); and 3) TE dynamics differ in androdioecious and dioecious species. We find no evidence for these hypotheses in Caenorhabditis. Across both short and long evolutionary distances Caenorhabditis genomes evolve through small structural variant (SV) mutations including frequent duplications and insertions, predominantly in genic regions. Caenorhabditis have rapid rates of gene family expansion and contraction and we identify 71 protein families with significant, parallel decreases across self-fertile Caenorhabditis. These include genes involved in the sensory system, regulatory proteins and membrane-associated immune responses, reflecting the shifting selection pressures that result from self-fertility. Our results suggest that the rules governing genome evolution differ between organisms based on ecology, life style and reproductive system.
- organism: C. elegans
- assay: whole-genome sequencing
- research focus: chromatin & epigenetic regulation
- research focus: gene regulatory network inference
- approach: statistical model
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