Molecular Biology and EvolutionGenomicsPeer-reviewed journal article
Accelerated pseudogenization in ancient endosymbionts of giant scale insects
Jinyeong ChoiiD, Pradeep PalanichamyiD, Hirotaka TanakaiD, Takumasa KondoiD, Matthew E. GruwelliD, Filip HusníkiD
Abstract
Symbiotic microorganisms are subject to a complex interplay of environmental and population-genetic pressures that drive their gene loss. Despite the widely held perception that ancient symbionts have stable genomes, even tiny genomes experience ongoing pseudogenization. Whether these tiny genomes also experience bursts of rapid gene loss is, however, less understood. Giant scale insects (Monophlebidae) feed on plant sap and rely on the symbiotic bacterium Walczuchella which provides them with essential nutrients. When compared to other ancient symbionts with similar genome sizes such as Karelsulcia, Walczuchellas genome was previously reported as unusually pseudogene-rich (10 % of coding sequences). However, this result was based on only one genome assembly raising questions about the assembly quality or a recent ecological shift such as co-symbiont acquisition driving the gene loss. Here, we generated six complete genomes of Walczuchella from three genera of giant scales, each with distinct co-symbiotic partners. We show that all the genomes are highly degraded and particularly genes related to the cellular envelope and energy metabolism seem to be ongoing pseudogenization. Apart from general mechanisms driving genome reduction such as the long-term intracellular lifestyle with transmission bottlenecks, we hypothesize that a more profound loss of DNA replication and repair genes together with recent co-obligate symbiont acquisitions likely contribute to the accelerated degradation of Walczuchella genomes. Our results highlight that even ancient symbionts with small genomes can experience significant bursts of gene loss when stochastic processes erase a gene that accelerates gene loss or when the selection pressure changes such as after cosymbiont acquisition.
- organism: bacteria (other)
- assay: whole-genome sequencing
- research focus: gene regulatory network inference
- approach: statistical model
- Citations
- 10
- FWCI
- 7.48
- Field percentile
- top 2%
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