Genomic fossils reveal adaptation of non-autonomous pararetroviruses driven by concerted evolution of noncoding regulatory sequences.
Sunlu ChenHuizhen ZhengYuji KishimaPublished in: PLoS pathogens (2017)
The interplay of different virus species in a host cell after infection can affect the adaptation of each virus. Endogenous viral elements, such as endogenous pararetroviruses (PRVs), have arisen from vertical inheritance of viral sequences integrated into host germline genomes. As viral genomic fossils, these sequences can thus serve as valuable paleogenomic data to study the long-term evolutionary dynamics of virus-virus interactions, but they have rarely been applied for this purpose. All extant PRVs have been considered autonomous species in their parasitic life cycle in host cells. Here, we provide evidence for multiple non-autonomous PRV species with structural defects in viral activity that have frequently infected ancient grass hosts and adapted through interplay between viruses. Our paleogenomic analyses using endogenous PRVs in grass genomes revealed that these non-autonomous PRV species have participated in interplay with autonomous PRVs in a possible commensal partnership, or, alternatively, with one another in a possible mutualistic partnership. These partnerships, which have been established by the sharing of noncoding regulatory sequences (NRSs) in intergenic regions between two partner viruses, have been further maintained and altered by the sequence homogenization of NRSs between partners. Strikingly, we found that frequent region-specific recombination, rather than mutation selection, is the main causative mechanism of NRS homogenization. Our results, obtained from ancient DNA records of viruses, suggest that adaptation of PRVs has occurred by concerted evolution of NRSs between different virus species in the same host. Our findings further imply that evaluation of within-host NRS interactions within and between populations of viral pathogens may be important.
Keyphrases
- genetic diversity
- sars cov
- single cell
- transcription factor
- dna repair
- genome wide
- stem cells
- induced apoptosis
- social media
- gene expression
- dna damage
- cell death
- electronic health record
- machine learning
- bone marrow
- cell free
- cell proliferation
- hiv infected
- deep learning
- dna methylation
- endoplasmic reticulum stress
- human immunodeficiency virus