Joel O. Wertheim

Detecting Individual Sites Subject to Episodic Diversifying Selection

The imprint of natural selection on protein coding genes is often difficult to identify because selection is frequently transient or episodic, i.e. it affects only a subset of lineages. Existing computational techniques, which are designed to identify sites subject to pervasive selection, may fail to recognize sites where selection is episodic: a large proportion of positively selected sites. We present a mixed effects model of evolution (MEME) that is capable of identifying instances of both episodic and pervasive positive selection at the level of an individual site. Using empirical and simulated data, we demonstrate the superior performance of MEME over older models under a broad range of scenarios. We find that episodic selection is widespread and conclude that the number of sites experiencing positive selection may have been vastly underestimated.

Dating the age of the SIV lineages that gave rise to HIV-1 and HIV-2.

Great strides have been made in understanding the evolutionary history of simian immunodeficiency virus (SIV) and the zoonoses that gave rise to HIV-1 and HIV-2. What remains unknown is how long these SIVs had been circulating in non-human primates before the transmissions to humans. Here, we use relaxed molecular clock dating techniques to estimate the time of most recent common ancestor for the SIVs infecting chimpanzees and sooty mangabeys, the reservoirs of HIV-1 and HIV-2, respectively. The date of the most recent common ancestor of SIV in chimpanzees is estimated to be 1492 (1266–1685), and the date in sooty mangabeys is estimated to be 1809 (1729–1875). Notably, we demonstrate that SIV sequences sampled from sooty mangabeys possess sufficient clock-like signal to calibrate a molecular clock; despite the differences in host biology and viral dynamics, the rate of evolution of SIV in sooty mangabeys is indistinguishable from that of its human counterpart, HIV-2. We also estimate the ages of the HIV-2 human-to-human transmissible lineages and provide the first age estimate for HIV-1 group N at 1963 (1948–1977). Comparisons between the SIV most recent common ancestor dates and those of the HIV lineages suggest a difference on the order of only hundreds of years. Our results suggest either that SIV is a surprisingly young lentiviral lineage or that SIV and, perhaps, HIV dating estimates are seriously compromised by unaccounted-for biases.

Purifying selection can obscure the ancient age of viral lineages

Abstract Statistical methods for molecular dating of viral origins have been used extensively to infer the time of most common recent ancestor for many rapidly evolving pathogens. However, there are a number of cases, in which epidemiological, historical, or genomic evidence suggests much older viral origins than those obtained via molecular dating. We demonstrate how pervasive purifying selection can mask the ancient origins of recently sampled pathogens, in part due to the inability of nucleotide-based substitution models to properly account for complex patterns of spatial and temporal variability in selective pressures. We use codon-based substitution models to infer the length of branches in viral phylogenies; these models produce estimates that are often considerably longer than those obtained with traditional nucleotide-based substitution models. Correcting the apparent underestimation of branch lengths suggests substantially older origins for measles, Ebola, and avian influenza viruses. This work helps to reconcile some of the inconsistencies between molecular dating and other types of evidence concerning the age of viral lineages.

The Global Transmission Network of HIV-1

Human immunodeficiency virus type 1 (HIV-1) is pandemic, but its contemporary global transmission network has not been characterized. A better understanding of the properties and dynamics of this network is essential for surveillance, prevention, and eventual eradication of HIV. Here, we apply a simple and computationally efficient network-based approach to all publicly available HIV polymerase sequences in the global database, revealing a contemporary picture of the spread of HIV-1 within and between countries. This approach automatically recovered well-characterized transmission clusters and extended other clusters thought to be contained within a single country across international borders. In addition, previously undescribed transmission clusters were discovered. Together, these clusters represent all known modes of HIV transmission. The extent of international linkage revealed by our comprehensive approach demonstrates the need to consider the global diversity of HIV, even when describing local epidemics. Finally, the speed of this method allows for near-real-time surveillance of the pandemics progression.

RELAX: Detecting Relaxed Selection in a Phylogenetic Framework

Relaxation of selective strength, manifested as a reduction in the efficiency or intensity of natural selection, can drive evolutionary innovation and presage lineage extinction or loss of function. Mechanisms through which selection can be relaxed range from the removal of an existing selective constraint to a reduction in effective population size. Standard methods for estimating the strength and extent of purifying or positive selection from molecular sequence data are not suitable for detecting relaxed selection, because they lack power and can mistake an increase in the intensity of positive selection for relaxation of both purifying and positive selection. Here, we present a general hypothesis testing framework (RELAX) for detecting relaxed selection in a codon-based phylogenetic framework. Given two subsets of branches in a phylogeny, RELAX can determine whether selective strength was relaxed or intensified in one of these subsets relative to the other. We establish the validity of our test via simulations and show that it can distinguish between increased positive selection and a relaxation of selective strength. We also demonstrate the power of RELAX in a variety of biological scenarios where relaxation of selection has been hypothesized or demonstrated previously. We find that obligate and facultative γ-proteobacteria endosymbionts of insects are under relaxed selection compared with their free-living relatives and obligate endosymbionts are under relaxed selection compared with facultative endosymbionts. Selective strength is also relaxed in asexual Daphnia pulex lineages, compared with sexual lineages. Endogenous, nonfunctional, bornavirus-like elements are found to be under relaxed selection compared with exogenous Borna viruses. Finally, selection on the short-wavelength sensitive, SWS1, opsin genes in echolocating and nonecholocating bats is relaxed only in lineages in which this gene underwent pseudogenization; however, selection on the functional medium/long-wavelength sensitive opsin, M/LWS1, is found to be relaxed in all echolocating bats compared with nonecholocating bats.

Relaxed Molecular Clocks, the Bias–Variance Trade-off, and the Quality of Phylogenetic Inference

Because a constant rate of DNA sequence evolution cannot be assumed to be ubiquitous, relaxed molecular clock inference models have proven useful when estimating rates and divergence dates. Furthermore, it has been recently suggested that using relaxed molecular clocks may provide superior accuracy and precision in phylogenetic inference compared with traditional time-free methods that do not incorporate a molecular clock. We perform a simulation study to determine if assuming a relaxed molecular clock does indeed improve the quality of phylogenetic inference. We analyze sequence data simulated under various rate distributions using relaxed-clocks, strict-clocks, and time-free Bayesian phylogenetic inference models. Our results indicate that no difference exists in the quality of phylogenetic inference between assuming a relaxed molecular clock and making no assumption about the clock-likeness of sequence evolution. This pattern is likely due to the bias-variance trade-off inherent in this type of phylogenetic inference. We also compared the quality of inference between Bayesian and maximum likelihood time-free inference models and found them to be qualitatively similar.

Using HIV Networks to Inform Real Time Prevention Interventions

Objective To reconstruct the local HIV-1 transmission network from 1996 to 2011 and use network data to evaluate and guide efforts to interrupt transmission. Design HIV-1 pol sequence data were analyzed to infer the local transmission network. Methods We analyzed HIV-1 pol sequence data to infer a partial local transmission network among 478 recently HIV-1 infected persons and 170 of their sexual and social contacts in San Diego, California. A transmission network score (TNS) was developed to estimate the risk of HIV transmission from a newly diagnosed individual to a new partner and target prevention interventions. Results HIV-1 pol sequences from 339 individuals (52.3%) were highly similar to sequences from at least one other participant (i.e., clustered). A high TNS (top 25%) was significantly correlated with baseline risk behaviors (number of unique sexual partners and insertive unprotected anal intercourse (p = 0.014 and p = 0.0455, respectively) and predicted risk of transmission (p<0.0001). Retrospective analysis of antiretroviral therapy (ART) use, and simulations of ART targeted to individuals with the highest TNS, showed significantly reduced network level HIV transmission (p<0.05). Conclusions Sequence data from an HIV-1 screening program focused on recently infected persons and their social and sexual contacts enabled the characterization of a highly connected transmission network. The network-based risk score (TNS) was highly correlated with transmission risk behaviors and outcomes, and can be used identify and target effective prevention interventions, like ART, to those at a greater risk for HIV-1 transmission.

A challenge to the ancient origin of SIVagm based on African green monkey mitochondrial genomes.

While the circumstances surrounding the origin and spread of HIV are becoming clearer, the particulars of the origin of simian immunodeficiency virus (SIV) are still unknown. Specifically, the age of SIV, whether it is an ancient or recent infection, has not been resolved. Although many instances of cross-species transmission of SIV have been documented, the similarity between the African green monkey (AGM) and SIVagm phylogenies has long been held as suggestive of ancient codivergence between SIVs and their primate hosts. Here, we present well-resolved phylogenies based on full-length AGM mitochondrial genomes and seven previously published SIVagm genomes; these allowed us to perform the first rigorous phylogenetic test to our knowledge of the hypothesis that SIVagm codiverged with the AGMs. Using the Shimodaira–Hasegawa test, we show that the AGM mitochondrial genomes and SIVagm did not evolve along the same topology. Furthermore, we demonstrate that the SIVagm topology can be explained by a pattern of west-to-east transmission of the virus across existing AGM geographic ranges. Using a relaxed molecular clock, we also provide a date for the most recent common ancestor of the AGMs at approximately 3 million years ago. This study substantially weakens the theory of ancient SIV infection followed by codivergence with its primate hosts.

Evolutionary Origins of Human Herpes Simplex Viruses 1 and 2

Abstract Herpesviruses have been infecting and codiverging with their vertebrate hosts for hundreds of millions of years. The primate simplex viruses exemplify this pattern of virus–host codivergence, at a minimum, as far back as the most recent common ancestor of New World monkeys, Old World monkeys, and apes. Humans are the only primate species known to be infected with two distinct herpes simplex viruses: HSV-1 and HSV-2. Human herpes simplex viruses are ubiquitous, with over two-thirds of the human population infected by at least one virus. Here, we investigated whether the additional human simplex virus is the result of ancient viral lineage duplication or cross-species transmission. We found that standard phylogenetic models of nucleotide substitution are inadequate for distinguishing among these competing hypotheses; the extent of synonymous substitutions causes a substantial underestimation of the lengths of some of the branches in the phylogeny, consistent with observations in other viruses (e.g., avian influenza, Ebola, and coronaviruses). To more accurately estimate ancient viral divergence times, we applied a branch-site random effects likelihood model of molecular evolution that allows the strength of natural selection to vary across both the viral phylogeny and the gene alignment. This selection-informed model favored a scenario in which HSV-1 is the result of ancient codivergence and HSV-2 arose from a cross-species transmission event from the ancestor of modern chimpanzees to an extinct Homo precursor of modern humans, around 1.6 Ma. These results provide a new framework for understanding human herpes simplex virus evolution and demonstrate the importance of using selection-informed models of sequence evolution when investigating viral origin hypotheses.

A case for the ancient origin of coronaviruses

ABSTRACT Coronaviruses are found in a diverse array of bat and bird species, which are believed to act as natural hosts. Molecular clock dating analyses of coronaviruses suggest that the most recent common ancestor of these viruses existed around 10,000 years ago. This relatively young age is in sharp contrast to the ancient evolutionary history of their putative natural hosts, which began diversifying tens of millions of years ago. Here, we attempted to resolve this discrepancy by applying more realistic evolutionary models that have previously revealed the ancient evolutionary history of other RNA viruses. By explicitly modeling variation in the strength of natural selection over time and thereby improving the modeling of substitution saturation, we found that the time to the most recent ancestor common for all coronaviruses is likely far greater (millions of years) than the previously inferred range.