Within-host Mycobacterium tuberculosis evolution: a population genetics perspective

Abstract

12The within-host evolutionary dynamics of TB remain unclear, and underlying biological 13 characteristics render standard population genetic approaches based upon the Wright-Fisher 14 model largely inappropriate. In addition, the compact genome combined with an absence of 15 recombination is expected to result in strong purifying selection effects. Thus, it is imperative to 16 establish a biologically-relevant evolutionary framework incorporating these factors in order to 17 enable an accurate study of this important human pathogen. Further, such a model is critical for 18 inferring fundamental evolutionary parameters related to patient treatment, including mutation 19 rates and the severity of infection bottlenecks. We here implement such a model and infer the 20 underlying evolutionary parameters governing within-patient evolutionary dynamics. Results 21 demonstrate that the progeny skew associated with the clonal nature of TB severely reduces 22 polymorphic sites per patient genome-wide. In addition, the observed site frequency spectrum 56 (SFS) is generally characterized by an abundance of rare variants (i.e., it is strongly left-skewed). 57These patterns have partly led to the suggestion that purifying selection effects may be wide-58 spread in the M.TB genome (Brown et al. 2016; Phelan et al. 2016; Mortimer et al. 2018). 59 60 Additional evolutionary factors likely contribute to these genomic patterns as well. For 61 example, population bottlenecks may reduce genetic variation and alter the shape of the SFS 62 (see review Thornton et al. 2007). Previous M.TB studies have investigated these effects 63 3 separately in both the deep-time view of the population bottleneck and subsequent growth 64 experienced by the host human population (Hershberg et al. 2008, Liu et al. 2018, as well as the 65 shallow-time view of the population bottleneck and subsequent growth characterizing each novel 66 transmission event and treatment (e.g., Trauner et al. 2017). Additionally, in fitting the left-67 skewed SFS, Pepperell et al. (2013) found that such a demographic history combined with a mix 68 of both deleterious and neutrally-evolving sites produced the nearest fit to the observed SFS. 69Finally, given the lack of recombination in M.TB, related linkage effects (i.e., background 70 selection (Charlesworth et al. 1993)) have similarly been discussed within these contexts 71 (Pepperell et al. 2010; Copin et al. 2016). 72 73 While these studies have provided many important insights, there remains a relatively 74 unexplored, though potentially highly significant, effect: clonality. Indeed, clonality and the 75 related progeny distribution represents an important violation of commonly used evolutionary 76 inference approaches based upon the Wright-Fisher (WF) model and the related Kingman 77 coalescent (Eldon et al. 2006; Dos Vultos et al. 2008; Huillet et al. 2011; Lapierre et al. 2016). 78 Specifically, progeny distributions under the WF model are Poisson distributed with a mean and 79 variance of 1. Therefore, when an ind...

Simultaneous Inference of Past Demography and Selection from the Ancestral Recombination Graph under the Beta Coalescent

“…As genome sequence data become available for many different species with as many different biological traits or life cycles, the applicability of the Kingman coalescent relying on the WF model can be questioned [78,2,59,39,56,81,53,27].…”