Research in the Pfeifer Lab is focused on analysing high-throughput sequencing data to learn about genetic and evolutionary processes.
Sequencing has revolutionized biology by permitting the analysis of genomic variation at an unprecedented resolution. High-throughput sequencing is fast and inexpensive, making it accessible for a wide range of research topics ranging from comparative genomics to clinical diagnostics. However, to tap its full potential, a thorough understanding of the data produced as well as the available methodologies is required (Pfeifer, Heredity 2017). My group develops bioinformatic pipelines that overcome the statistical and computational challenges in the reliable detection of variants, thereby taking into account the subtle but complex types of errors, biases and uncertainties in the data (e.g., SCAMPI; Pfeifer & Helms, WASET 2010). We utilize these developments to study three particular topics within evolutionary genomics, also intersecting broadly with other related fields:
(i) Anthropological – mutation and recombination rate variation in primates
Interactions between mutation, recombination, natural selection, and population history shape the genetic differences among individuals, populations, and species. For anthropocentric reasons, a focal point of many studies addressing the processes of mutation, recombination, and selection has been characterizing the rate and patterns observed in humans as well as our closest extant evolutionary relative, chimpanzees (Auton*, Fledel-Alon*, Pfeifer*, Venn*, et al., Science 2012; Leffler*, Gao*, Pfeifer*, Ségurel*, et al., Science 2013). The gained knowledge from such studies is fundamentally important both to understand the causes of genetic diseases as well as to date events in human evolution. Until recently, the direct identification of mutation and recombination events was a technically difficult process, making experiments both complex and imprecise. However, advances in high throughput sequencing technologies have made it possible to detect mutations on a genome-wide scale, even in non-model organisms. This large-scale population genetic data can be used to estimate fine-scale historical, sex-averaged recombination maps, thus providing us with the necessary means to assess how much variation in mutation and recombination rates exist in natural populations. Specifically, I am interested in gaining a better understanding of fine-scale changes in rates of mutation and recombination through deeper evolutionary time within the primate clade (Pfeifer, MBE 2017) – research that will greatly illuminate current debates centred around the calibration of the molecular clock as well as the expected extent of linked selection in shaping genomic variation (Pfeifer & Jensen, GBE 2016).
(ii) Ecological – adaptation due to recent environmental change
Understanding the process of adaptation during rapid environmental change remains one of the central focal points of evolutionary biology. The recently formed White Sands system of southern New Mexico and the Sand Hills of Nebraska contain outstanding examples of rapid adaptation for crypsis, with a variety of species – from lizards to mice – having evolved blanched forms on the dunes that contrast with their close relatives in the surrounding dark soil habitats. In collaboration with the Rosenblum Lab at Berkeley, we are using model-based statistical inference methods to describe the demographic and adaptive history characterising the colonisation of different White Sands lizard species (Laurent*, Pfeifer* et al., Mol Ecol 2016; Ormond et al., Mol Ecol 2016). In collaboration with the Hoekstra Lab at Harvard, we focus on the evolution of cryptic colouration in Nebraska deer mouse populations, unravelling the interplay between demography and selection within and between populations as well as estimating selection on both phenotype and genotype (using clinal samples (Pfeifer*, Laurent*, Sousa*, Linnen* et al., In revision), as well as large-scale field experiments (In preparation)).
(iii) Clinical – virus evolution
Human cytomegalovirus (HCMV) is a large b-herpesvirus critically important to human health due to its ubiquitous occurrence – with adult infection rates ranging from 30–90% in industrialized countries to almost 100% in emerging countries. Although ‘primary’ infections are generally asymptomatic in healthy hosts, HCMV infections can lead to severe effects in immuno-suppressed or immuno-naïve hosts, including fetuses and newborns. HCMV infections affect ~0.5% of all live births in the United States – making it the most common source of infection-related congenital (i.e., before birth) infections. HCMV utilizes effective immune evasion techniques and, as a result, it is currently neither possible to prevent transmission from mother to fetus (due to an absence of an effective vaccine), nor to reduce severity of disease in the infant. As a consequence, a better understanding of the underlying biological and evolutionary processes at play during infection is indispensable to the future development of novel disease prevention and treatment strategies. In collaboration with the Jensen, Kowalik, and Trumble Labs, we work to characterize the evolutionary processes driving infection (e.g., Renzette et al., J. Virol. 2017; Pokalyuk et al., Mol. Ecol. 2017). This characterization will better illuminate the causes and consequences underlying this major threat to global health.
The Pfeifer Lab is in the School of Life Sciences at Arizona State University, and we are part of a large and collaborative group in evolutionary genomics at ASU – see ASUpopgen.org. We are also members of the Center for Evolution & Medicine, and the Center for Mechanisms of Evolution.