Inference of gene flow in the process of speciation: Efficient maximum-likelihood implementation of a generalised isolation-with-migration model

Abstract Gene flow between species may cause variations in branch length and topology of gene tree, which are beyond the expected variations from ancestral processes. These additional variations make it difficult to estimate parameters during speciation with gene flow, as the pattern of these additional variations differs with the relationship between isolation and migration. As far as we know, most methods rely on the assumption about the relationship between isolation and migration by a given model, such as the isolation-with-migration model, when estimating parameters during speciation with gene flow. In this article, we develop a multispecies coalescent approach which does not rely on any assumption about the relationship between isolation and migration when estimating parameters and is called mstree. mstree is available at https://github.com/liujunfengtop/MStree/ and uses some mathematical inequalities among several factors, which include the species divergence time, the ancestral population size, and the number of gene trees, to estimate parameters during speciation with gene flow. Using simulations, we show that the estimated values of ancestral population sizes and species divergence times are close to the true values when analyzing the simulation data sets, which are generated based on the isolation-with-initial-migration model, secondary contact model, and isolation-with-migration model. Therefore, our method is able to estimate ancestral population sizes and speciation times in the presence of different modes of gene flow and may be helpful to test different theories of speciation.

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Maximum Likelihood Implementation of an Isolation-with-Migration Model for Three Species

Systematic Biology ◽

10.1093/sysbio/syw063 ◽

2016 ◽

pp. syw063 ◽

Cited By ~ 3

Author(s):

Daniel A. Dalquen ◽

Tianqi Zhu ◽

Ziheng Yang

Keyword(s):

Maximum Likelihood ◽

Migration Model ◽

Isolation With Migration

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Efficient Maximum-Likelihood Inference For The Isolation-With-Initial-Migration Model With Potentially Asymmetric Gene Flow

10.1101/052894 ◽

2016 ◽

Author(s):

Rui J. Costa ◽

Hilde Wilkinson-Herbots

Keyword(s):

Gene Flow ◽

Maximum Likelihood ◽

Dna Sequences ◽

Computing Time ◽

Likelihood Method ◽

Ancestral Population ◽

Parameter Estimates ◽

Fast Method ◽

Data Set ◽

Im Model

AbstractThe isolation-with-migration (IM) model is commonly used to make inferences about gene flow during speciation, using polymorphism data. However, Becquet and Przeworski (2009) report that the parameter estimates obtained by fitting the IM model are very sensitive to the model's assumptions (including the assumption of constant gene flow until the present). This paper is concerned with the isolation-with-initial-migration (IIM) model of Wilkinson-Herbots (2012), which drops precisely this assumption. In the IIM model, one ancestral population divides into two descendant subpopulations, between which there is an initial period of gene flow and a subsequent period of isolation. We derive a very fast method of fitting an extended version of the IIM model, which also allows for asymmetric gene flow and unequal population sizes. This is a maximum-likelihood method, applicable to data on the number of segregating sites between pairs of DNA sequences from a large number of independent loci. In addition to obtaining parameter estimates, our method can also be used to distinguish between alternative models representing different evolutionary scenarios, by means of likelihood ratio tests. We illustrate the procedure on pairs of Drosophila sequences from approximately 30,000 loci. The computing time needed to fit the most complex version of the model to this data set is only a couple of minutes. The R code to fit the IIM model can be found in the supplementary files of this paper.

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Parallel Metropolis Coupled Markov Chain Monte Carlo for Isolation with Migration Model

Applied Mathematics & Information Sciences ◽

10.12785/amis/071l30 ◽

2013 ◽

Vol 7 (1L) ◽

pp. 219-224 ◽

Cited By ~ 2

Author(s):

Chunbao Zhou ◽

Xianyu Lang ◽

Yangang Wang ◽

Chaodong Zhu ◽

Zhonghua Lu ◽

...

Keyword(s):

Monte Carlo ◽

Markov Chain ◽

Markov Chain Monte Carlo ◽

Migration Model ◽

Isolation With Migration

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Genomic divergence in allopatric Northern Cardinals of the North American warm deserts is associated with behavioral differentiation

10.1101/347492 ◽

2018 ◽

Author(s):

Kaiya L. Provost ◽

William M. Mauck ◽

Brian Tilston Smith

Keyword(s):

Gene Flow ◽

Sonoran Desert ◽

Demographic History ◽

Isolation With Migration ◽

Song Recognition ◽

Behavioral Isolation ◽

The North ◽

Genome Wide ◽

Behavioral Differentiation ◽

Northern Cardinals

ABSTRACTBiogeographic barriers are thought to be important in initiating speciation through geographic isolation, but they rarely indiscriminately and completely reduce gene flow across the entire community. Understanding which species’ attributes regulate a barrier could help elucidate how speciation is initiated. Here, we investigated the association of behavioral isolation on population differentiation in Northern Cardinals (Cardinalis cardinalis) distributed across the Cochise Filter Barrier, a region of transitional habitat which separates the Sonoran and Chihuahuan deserts. Using genome-wide markers, we modeled demographic history by fitting the data to isolation and isolation-with-migration models. The best-fit model indicated that desert populations diverged in the mid-Pleistocene and there has been historically low, unidirectional gene flow into the Sonoran Desert. We then tested song recognition using reciprocal call-broadcast experiments to compare song recognition between deserts, controlling for song dialect changes within deserts. We found that male Northern Cardinals in both deserts were most aggressive to local songs and failed to recognize across-barrier songs. A correlation of genomic differentiation despite historic introgression and strong song discrimination is consistent with a model where speciation is initiated across a barrier and maintained by behavioral isolation.

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Reconstructing the demographic history of divergence between European river and brook lampreys using approximate Bayesian computations

PeerJ ◽

10.7717/peerj.1910 ◽

2016 ◽

Vol 4 ◽

pp. e1910 ◽

Cited By ~ 17

Author(s):

Quentin Rougemont ◽

Camille Roux ◽

Samuel Neuenschwander ◽

Jerome Goudet ◽

Sophie Launey ◽

...

Keyword(s):

Gene Flow ◽

Life Histories ◽

Evolutionary Biology ◽

Demographic History ◽

Secondary Contact ◽

Isolation With Migration ◽

Genome Wide Data ◽

History Of ◽

Parameterized Model ◽

Approximate Bayesian

Inferring the history of isolation and gene flow during species divergence is a central question in evolutionary biology. The European river lamprey (Lampetra fluviatilis) and brook lamprey(L. planeri)show a low reproductive isolation but have highly distinct life histories, the former being parasitic-anadromous and the latter non-parasitic and freshwater resident. Here we used microsatellite data from six replicated population pairs to reconstruct their history of divergence using an approximate Bayesian computation framework combined with a random forest model. In most population pairs, scenarios of divergence with recent isolation were outcompeted by scenarios proposing ongoing gene flow, namely the Secondary Contact (SC) and Isolation with Migration (IM) models. The estimation of demographic parameters under the SC model indicated a time of secondary contact close to the time of speciation, explaining why SC and IM models could not be discriminated. In case of an ancient secondary contact, the historical signal of divergence is lost and neutral markers converge to the same equilibrium as under the less parameterized model allowing ongoing gene flow. Our results imply that models of secondary contacts should be systematically compared to models of divergence with gene flow; given the difficulty to discriminate among these models, we suggest that genome-wide data are needed to adequately reconstruct divergence history.

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Faster-X adaptive differentiation under divergence-with-gene-flow in diploids and haplodiploids

10.1101/2021.04.09.439183 ◽

2021 ◽

Author(s):

Emily E. Bendall ◽

Robin Bagley ◽

Catherine R. Linnen ◽

Vitor C. Sousa

Keyword(s):

Gene Flow ◽

Meta Analysis ◽

Stochastic Simulations ◽

Adaptive Divergence ◽

Effective Population ◽

Isolation With Migration ◽

Demographic Modeling ◽

Novel Approach ◽

Divergence With Gene Flow ◽

Adaptive Differentiation

AbstractEmpirical data from diverse taxa indicate that the hemizygous portions of the genome (X/Z chromosomes) evolve more rapidly than their diploid counterparts. Faster-X theory predicts increased rates of adaptive substitutions between isolated species, yet little is known about species experiencing gene flow. Here we investigate how hemizygosity impacts genome-wide patterns of differentiation during adaptive divergence with gene flow, combining simulations under isolation-with-migration models, a meta-analysis of autosomes and sex-chromosomes from diverse taxa, and analysis of haplodiploid species. First, using deterministic and stochastic simulations, we show that elevated differentiation at hemizygous loci occurs when there is gene flow, irrespective of dominance. This faster-X adaptive differentiation stems from more efficient selection resulting in reduced probability of losing the beneficial allele, greater migration-selection threshold, greater allele frequency differences at equilibrium, and a faster time to equilibrium. Second, by simulating neutral variation linked to selected loci, we show that faster-X differentiation affects linked variation due to reduced opportunities for recombination between locally adaptive and maladaptive immigrant haplotypes. Third, after correcting for expected differences in effective population size, we find that most taxon pairs (24 out of 28) exhibit faster-X differentiation in the meta-analysis. Finally, using a novel approach combining demographic modeling and simulations, we found evidence for faster-X differentiation in haplodiploid pine-feeding hymenopteran species adapted to different host plants. Together, our results indicate that divergent selection with gene flow can lead to higher differentiation at selected and linked variation in hemizygous loci (i.e., faster-X adaptive differentiation), both in X/Z-chromosomes and haplodiploid species.

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Tracking human population structure through time from whole genome sequences

10.1101/585265 ◽

2019 ◽

Cited By ~ 4

Author(s):

Ke Wang ◽

Iain Mathieson ◽

Jared O’Connell ◽

Stephan Schiffels

Keyword(s):

Population Structure ◽

Gene Flow ◽

Demographic History ◽

Time Dependent ◽

Human Populations ◽

Whole Genome ◽

Genome Sequences ◽

Migration Model ◽

Novel Approach ◽

Different Populations

AbstractThe genetic diversity of humans, like many species, has been shaped by a complex pattern of population separations followed by isolation and subsequent admixture. This pattern, reaching at least as far back as the appearance of our species in the paleontological record, has left its traces in our genomes. Reconstructing a population’s history from these traces is a challenging problem. Here we present a novel approach based on the Multiple Sequentially Markovian Coalescent (MSMC) to analyse the population separation history. Our approach, called MSMC-IM, uses an improved implementation of the MSMC (MSMC2) to estimate coalescence rates within and across pairs of populations, and then fits a continuous Isolation-Migration model to these rates to obtain a time-dependent estimate of gene flow. We show, using simulations, that our method can identify complex demographic scenarios involving post-split admixture or archaic introgression. We apply MSMC-IM to whole genome sequences from 15 worldwide populations, tracking the process of human genetic diversification. We detect traces of extremely deep ancestry between some African populations, with around 1% of ancestry dating to divergences older than a million years ago.Author SummaryHuman demographic history is reflected in specific patterns of shared mutations between the genomes from different populations. Here we aim to unravel this pattern to infer population structure through time with a new approach, called MSMC-IM. Based on estimates of coalescence rates within and across populations, MSMC-IM fits a time-dependent migration model to the pairwise rate of coalescences. We implemented this approach as an extension to existing software (MSMC2), and tested it with simulations exhibiting different histories of admixture and gene flow. We then applied it to the genomes from 15 worldwide populations to reveal their pairwise separation history ranging from a few thousand up to several million years ago. Among other results, we find evidence for remarkably deep population structure in some African population pairs, suggesting that deep ancestry dating to one million years ago and older is still present in human populations in small amounts today.

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