Genome comparisons indicate recent transfer of wRi-like Wolbachia between sister species Drosophila suzukii and D. subpulchrella.
William R ConnerMark L BlaxterGianfranco AnforaLino OmettoOmar Rota-StabelliMichael TurelliPublished in: Ecology and evolution (2017)
Wolbachia endosymbionts may be acquired by horizontal transfer, by introgression through hybridization between closely related species, or by cladogenic retention during speciation. All three modes of acquisition have been demonstrated, but their relative frequency is largely unknown. Drosophila suzukii and its sister species D. subpulchrella harbor Wolbachia, denoted wSuz and wSpc, very closely related to wRi, identified in California populations of D. simulans. However, these variants differ in their induced phenotypes: wRi causes significant cytoplasmic incompatibility (CI) in D. simulans, but CI has not been detected in D. suzukii or D. subpulchrella. Our draft genomes of wSuz and wSpc contain full-length copies of 703 of the 734 single-copy genes found in wRi. Over these coding sequences, wSuz and wSpc differ by only 0.004% (i.e., 28 of 704,883 bp); they are sisters relative to wRi, from which each differs by 0.014%-0.015%. Using published data from D. melanogaster, Nasonia wasps and Nomada bees to calibrate relative rates of Wolbachia versus host nuclear divergence, we conclude that wSuz and wSpc are too similar-by at least a factor of 100-to be plausible candidates for cladogenic transmission. These three wRi-like Wolbachia, which differ in CI phenotype in their native hosts, have different numbers of orthologs of genes postulated to contribute to CI; and the CI loci differ at several nucleotides that may account for the CI difference. We discuss the general problem of distinguishing alternative modes of Wolbachia acquisition, focusing on the difficulties posed by limited knowledge of variation in absolute and relative rates of molecular evolution for host nuclear genomes, mitochondria, and Wolbachia.
Keyphrases
- aedes aegypti
- dengue virus
- zika virus
- genome wide
- healthcare
- genetic diversity
- single molecule
- dna methylation
- machine learning
- reactive oxygen species
- cell death
- drug induced
- gene expression
- big data
- artificial intelligence
- diabetic rats
- transcription factor
- bioinformatics analysis
- endothelial cells
- deep learning
- endoplasmic reticulum