Genealogies from Time-Stamped Sequence Data

The evolution of SARS-CoV-2

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has caused millions of deaths and substantial morbidity worldwide. Intense scientific effort to understand the biology of SARS-CoV-2 has resulted in daunting numbers of genomic sequences. We witnessed evolutionary events that could mostly be inferred indirectly before, such as the emergence of variants with distinct phenotypes, for example transmissibility, severity and immune evasion. This Review explores the mechanisms that generate genetic variation in SARS-CoV-2, underlying the within-host and population-level processes that underpin these events. We examine the selective forces that likely drove the evolution of higher transmissibility and, in some cases, higher severity during the first year of the pandemic and the role of antigenic evolution during the second and third years, together with the implications of immune escape and reinfections, and the increasing evidence for and potential relevance of recombination. In order to understand how major lineages, such as variants of concern (VOCs), are generated, we contrast the evidence for the chronic infection model underlying the emergence of VOCs with the possibility of an animal reservoir playing a role in SARS-CoV-2 evolution, and conclude that the former is more likely. We evaluate uncertainties and outline scenarios for the possible future evolutionary trajectories of SARS-CoV-2.

Screening ancient tuberculosis with qPCR: challenges and opportunities

The field of ancient DNA (aDNA) has rapidly accelerated in recent years as a result of new methods in next-generation sequencing, library preparation and targeted enrichment. Such research is restricted, however, by the highly variable DNA preservation within different tissues, especially when isolating ancient pathogens from human remains. Identifying positive candidate samples via quantitative PCR (qPCR) for downstream procedures can reduce reagent costs, increase capture efficiency and maximize the number of sequencing reads of the target. This study uses four qPCR assays designed to target regions within the Mycobacterium tuberculosis complex (MTBC) to examine 133 human skeletal samples from a wide geographical and temporal range, identified by the presence of skeletal lesions typical of chronic disseminated tuberculosis. Given the inherent challenges working with ancient mycobacteria, strict criteria must be used and primer/probe design continually re-evaluated as new data from bacteria become available. Seven samples tested positive for multiple MTBC loci, supporting them as strong candidates for downstream analyses. Using strict and conservative criteria, qPCR remains a fast and effective screening tool when compared with screening by more expensive sequencing and enrichment technologies.

Phylogenetic Estimation of Timescales Using Ancient DNA: The Effects of Temporal Sampling Scheme and Uncertainty in Sample Ages

In recent years, ancient DNA has increasingly been used for estimating molecular timescales, particularly in studies of substitution rates and demographic histories. Molecular clocks can be calibrated using temporal information from ancient DNA sequences. This information comes from the ages of the ancient samples, which can be estimated by radiocarbon dating the source material or by dating the layers in which the material was deposited. Both methods involve sources of uncertainty. The performance of Bayesian phylogenetic inference depends on the information content of the data set, which includes variation in the DNA sequences and the structure of the sample ages. Various sources of estimation error can reduce our ability to estimate rates and timescales accurately and precisely. We investigated the impact of sample-dating uncertainties on the estimation of evolutionary timescale parameters using the software BEAST. Our analyses involved 11 published data sets and focused on estimates of substitution rate and root age. We show that, provided that samples have been accurately dated and have a broad temporal span, it might be unnecessary to account for sample-dating uncertainty in Bayesian phylogenetic analyses of ancient DNA. We also investigated the sample size and temporal span of the ancient DNA sequences needed to estimate phylogenetic timescales reliably. Our results show that the range of sample ages plays a crucial role in determining the quality of the results but that accurate and precise phylogenetic estimates of timescales can be made even with only a few ancient sequences. These findings have important practical consequences for studies of molecular rates, timescales, and population dynamics.

Phylogenetic and epidemic modeling of rapidly evolving infectious diseases

Epidemic modeling of infectious diseases has a long history in both theoretical and empirical research. However the recent explosion of genetic data has revealed the rapid rate of evolution that many populations of infectious agents undergo and has underscored the need to consider both evolutionary and ecological processes on the same time scale. Mathematical epidemiology has applied dynamical models to study infectious epidemics, but these models have tended not to exploit--or take into account--evolutionary changes and their effect on the ecological processes and population dynamics of the infectious agent. On the other hand, statistical phylogenetics has increasingly been applied to the study of infectious agents. This approach is based on phylogenetics, molecular clocks, genealogy-based population genetics and phylogeography. Bayesian Markov chain Monte Carlo and related computational tools have been the primary source of advances in these statistical phylogenetic approaches. Recently the first tentative steps have been taken to reconcile these two theoretical approaches. We survey the Bayesian phylogenetic approach to epidemic modeling of infection diseases and describe the contrasts it provides to mathematical epidemiology as well as emphasize the significance of the future unification of these two fields.