Detecting and Quantifying Natural Selection at Two Linked Loci from Time Series Data of Allele Frequencies with Forward-in-Time Simulations

Abstract

Recent advances in DNA sequencing techniques have made it possible to monitor genomes in great detail over time. This improvement provides an opportunity for us to study natural selection based on time serial samples of genomes while accounting for genetic recombination effect and local linkage information. Such time series genomic data allow for more accurate estimation of population genetic parameters and hypothesis testing on the recent action of natural selection. In this work, we develop a novel Bayesian statistical framework for inferring natural selection at a pair of linked loci by capitalising on the temporal aspect of DNA data with the additional flexibility of modelling the sampled chromosomes that contain unknown alleles. Our approach is built on a hidden Markov model where the underlying process is a two-locus Wright-Fisher diffusion with selection, which enables us to explicitly model genetic recombination and local linkage. The posterior probability distribution for selection coefficients is computed by applying the particle marginal Metropolis-Hastings algorithm, which allows us to efficiently calculate the likelihood. We evaluate the performance of our Bayesian inference procedure through extensive simulations, showing that our approach can deliver accurate estimates of selection coefficients, and the addition of genetic recombination and local linkage brings about significant improvement in the inference of natural selection. We also illustrate the utility of our method on real data with an application to ancient DNA data associated with white spotting patterns in horses.

Ecological Processes Shaping Microbiomes of Extremely Low Birthweight Infants

“…In order to better understand initial assembly and succession processes in the face of these chaotic dynamics, we applied a probabilistic approach and analyzed state transitions through Markov chain modeling on our time-course data. Markov processes are widely used in many fields of science, from thermodynamics to phylogenetic inference and genome evolution ( Erez et al, 2008 ; Kaehler et al, 2015 ; Sampid et al, 2018 ; Dhar et al, 2020 ; He et al, 2020 ), but have rarely been applied in microbial ecology ( DiGiulio et al, 2015 ) and have not yet been used to evaluate longitudinal transitions in microbiome composition in an individual. Despite the large influence of stochastic processes, this analysis revealed distinctive microbiome dynamics, as well as community stability, for each body site ( Figure 4 ).…”

Inferring the timing and strength of natural selection and gene migration in the evolution of chicken from ancient DNA data

“…For multiple (independent) loci, computational costs can be greatly reduced by updating the selection‐related parameters for different loci on different cores in parallel. Our approach can be readily extended to the case of two linked loci by incorporating the method of He, Dai, Beaumont, and Yu (2020), where modelling local linkage among loci has been illustrated to be capable of further improving the inference of selection, but such an extension will probably be computationally prohibitive in the case of multiple linked loci. As a tractable alternative for multiple linked loci, we can use our two‐locus method in a pairwise manner by adding additional blocks in blockwise sampling.…”

“…In their likelihood computation, the Wright–Fisher model was approximated through its standard diffusion limit, known as the Wright–Fisher diffusion, which was then discretized for numerical integration with a finite difference scheme. Their approach was applied to analyse the aDNA data associated with horse coat colouration in Ludwig et al (2009) and extended to more complex evolutionary scenarios (see, e.g., Ferrer‐Admetlla et al, 2016; He et al, 2020; He et al, 2020; Malaspinas et al, 2012; Schraiber et al, 2016; Steinrücken et al, 2014).…”

Inferring the timing and strength of natural selection and gene migration in the evolution of chicken from ancient DNA data

“…to the case of two linked loci by incorporating the method of He et al (2020b), where modelling local linkage among loci has been illustrated to be capable of further improving the inference of selection, but such an extension will probably be computationally prohibitive in the case of multiple linked loci. As a tractable alternative for multiple linked loci, we can use our two-locus method in a pairwise manner by adding additional blocks in blockwise sampling.…”