Donor-Recipient Identification in Para- and Poly-phyletic Trees Under Alternative HIV-1 Transmission Hypotheses Using Approximate Bayesian Computation

• DOI: 10.1534/genetics.117.300284
• Publication Date: 2017-09-15T01:20:17Z
• Authors: Ethan O Romero-Se...; Ingo Bulla; Nick Hengartner; Inês Bártolo; Ana Abecasis; José M Azevedo-Pe...; Nuno Taveira; Thomas Leitner
• Keywords: Paraphyly

Abstract Diversity of the founding population Human Immunodeficiency Virus Type 1 (HIV-1) transmissions raises many important biological, clinical, and epidemiological issues. In up to 40% sexual infections, there is clear evidence for multiple variants, which can influence efficacy putative prevention methods, reconstruction epidemiologic histories. To infer who-infected-whom, compute probability alternative transmission scenarios while explicitly taking phylogenetic uncertainty into account, we created an approximate Bayesian computation (ABC) method based on a set statistics measuring topology, branch lengths, genetic diversity. We applied our suspected heterosexual case involving three individuals, showing complex monophyletic-paraphyletic-polyphyletic topology. detected that seven lineages had been transmitted between two individuals available samples, implying more unsampled also transmitted. Testing whether at one time or over some length suggested ongoing superinfection process several years was most likely. While individual found unlinked other two, surprisingly, when evaluating competing priors, donor did infect each not identified by host root-label, primary suspect in transmission. This highlights it take information account analyzing support hypothesis another, as results may be nonintuitive sensitive details about sampling dates relative possible infection dates. Our study provides formal inference framework include times, investigate ancestral node-label states, direction, diversity, frequency