Efficient ancestry and mutation simulation with msprime 1.0

Baumdicker, Franz; Bisschop, Gertjan; Goldstein, Daniel; Gower, Graham; Ragsdale, Aaron P.; Tsambos, Georgia; Zhu, Sha; Eldon, Bjarki; Ellerman, E. Castedo; Galloway, Jared; Gladstein, Ariella L.; Gorjanc, Gregor; Guo, Bing; Jeffery, Ben; Kretzschmar, Warren W.; Lohse, Konrad; Matschiner, Michael; Nelson, Dominic; Pope, Nathaniel S.; Quinto-Cortés, Consuelo D.; Rodrigues, Murillo F.; Saunack, Kumar; Sellinger, Thibaut; Thornton, Kevin R.; Kemenade, Hugo van; Wohns, Anthony Wilder; Wong, Yan; Gravel, Simon; Kern, Andrew D.; Koskela, Jere; Ralph, Peter L.; Kelleher, Jerome

doi:10.1093/genetics/iyab229

Cited by 176 publications

(223 citation statements)

References 195 publications

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“…11 and SM Fig. 12) we generated population size change scenarios for simulating site frequency spectra using msprime (Kelleher et al, 2016;Baumdicker et al, 2021). The results (SM Fig.…”

Section: Historical Demography and Low Variance Reproductionmentioning

confidence: 99%

Sweepstakes reproductive success via pervasive and recurrent selective sweeps

Árnason

Koskela

Halldórsdóttir

et al. 2022

Preprint

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Highly fecund natural populations characterized by high early mortality abound, yet our knowledge of such population's recruitment dynamics is rudimentary at best. This knowledge gap has implications for our understanding of genetic variation, population connectivity, local adaptation, and resilience of highly fecund populations. The concept of sweepstakes reproductive success, which posits huge variance in individual reproductive output, is key to understanding recruitment dynamics, the distribution of individual reproductive and recruitment success. However, it is unknown whether highly fecund organisms reproduce by sweepstakes and if they do, the relative roles of neutral and selective sweepstakes. Here we use coalescent-based statistical analysis of genomic population data and show that selective sweepstakes are a strong candidate for explaining recruitment dynamics in the highly fecund Atlantic cod. The sweepstakes result from recurrent and pervasive selective sweeps of new variation generated by mutation. We show that the Kingman coalescent and the Xi-Beta coalescent (modelling random sweepstakes), including complex demography and background selection, are inadequate explanations. Our results show that sweepstakes reproduction processes and multiple-merger coalescent models are relevant and necessary for understanding genetic diversity in highly fecund natural populations. Our findings have fundamental implications for understanding the recruitment variation of fish stocks and general evolutionary genomics of high fecundity.

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“…11 and SM Fig. 12) we generated population size change scenarios for simulating site frequency spectra using msprime (Kelleher et al, 2016;Baumdicker et al, 2021). The results (SM Fig.…”

Section: Historical Demography and Low Variance Reproductionmentioning

confidence: 99%

Sweepstakes reproductive success via pervasive and recurrent selective sweeps

Árnason

Koskela

Halldórsdóttir

et al. 2022

Preprint

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“…I also benchmarked the evaluation time and accuracy ( Fig 3 right) against the simulation-based approach as described in [ 23 ]. Using [ 24 ], coalescent trees can be simulated under (almost) any demographic model. Without having to simulate mutations, we can calculate the probability of observing each mutation type.…”

Section: Resultsmentioning

confidence: 99%

Graph-based algorithms for Laplace transformed coalescence time distributions

Bisschop

2022

PLoS Comput Biol

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Extracting information on the selective and demographic past of populations that is contained in samples of genome sequences requires a description of the distribution of the underlying genealogies. Using the Laplace transform, this distribution can be generated with a simple recursive procedure, regardless of model complexity. Assuming an infinite-sites mutation model, the probability of observing specific configurations of linked variants within small haplotype blocks can be recovered from the Laplace transform of the joint distribution of branch lengths. However, the repeated differentiation required to compute these probabilities has proven to be a serious computational bottleneck in earlier implementations. Here, I show that the state space diagram can be turned into a computational graph, allowing efficient evaluation of the Laplace transform by means of a graph traversal algorithm. This general algorithm can, for example, be applied to tabulate the likelihoods of mutational configurations in non-recombining blocks. This work provides a crucial speed up for existing composite likelihood approaches that rely on the joint distribution of branch lengths to fit isolation with migration models and estimate the parameters of selective sweeps. The associated software is available as an open-source Python library, agemo.

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“…To quantify how accurately CO and GC rates can be estimated, we performed a power analyses and parametric bootstrap on data simulated under the full model in msprime 1.0 ( Baumdicker et al 2022 ): we simulated 100 replicates for each chromosome under the MCL estimates obtained from the house mouse data (see Results). Each replicate consisted of 10 diploid samples assuming

(the observed heterozygosity),

( Uchimura et al 2015 ), L = 108.4 for all chromosomes.…”

Section: Methodsmentioning

confidence: 99%

“…We quantify the precision and accuracy of our estimates for M. m. castaneus using 100 parametric bootstrap simulations in msprime 1.0 ( Baumdicker et al 2022 ), and we use further simulations to test for robustness to violations of the underlying model. First, we investigate the ability of heRho to obtain an average estimate when there is underlying fine-scale recombination rate variation, as complex recombination landscapes have been demonstrated to reduce the reliability of LD-based inference methods ( Raynaud et al 2022 ).…”

Section: Introductionmentioning

confidence: 99%

Estimating the rates of crossover and gene conversion from individual genomes

et al. 2022

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Recombination can occur either as a result of crossover or gene conversion events. Population genetic methods for inferring the rate of recombination from patterns of linkage disequilibrium generally assume a simple model of recombination that only involves crossover events and ignore gene conversion. However, distinguishing the two processes is not only necessary for a complete description of recombination, but also essential for understanding the evolutionary consequences of inversions and other genomic partitions in which crossover (but not gene conversion) is reduced. We present heRho, a simple composite likelihood scheme for co-estimating the rate of crossover and gene conversion from individual diploid genomes. The method is based on analytic results for the distance-dependent probability of heterozygous and homozygous states at two loci. We apply heRho to simulations and data from the house mouse Mus musculus castaneus, a well studied model. Our analyses show i) that the rates of crossover and gene conversion can be accurately co-estimated at the level of individual chromosomes and ii) that previous estimates of the population scaled rate of recombination ρ = 4 Ner under a pure crossover model are likely biased.

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Efficient ancestry and mutation simulation with msprime 1.0

Cited by 176 publications

References 195 publications

Sweepstakes reproductive success via pervasive and recurrent selective sweeps

Sweepstakes reproductive success via pervasive and recurrent selective sweeps

Graph-based algorithms for Laplace transformed coalescence time distributions

Estimating the rates of crossover and gene conversion from individual genomes

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