scholarly journals Parapatric speciation with recurrent gene flow of two sexual dichromatic pheasants

2021 ◽  
Author(s):  
Zheng Li ◽  
Jie Zhou ◽  
Minzhi Gao ◽  
Wei Liang ◽  
Lu Dong
Keyword(s):  
Sexual Selection ◽  
Gene Flow ◽  
Late Pleistocene ◽  
Approximate Bayesian Computation ◽  
De Novo ◽  
Demographic History ◽  
Population Expansion ◽  
Secondary Contact ◽  
Bayesian Computation ◽  
Approximate Bayesian

Background: Understanding speciation has long been a fundamental goal of evolutionary biology. It is widely accepted that speciation requires an interruption of gene flow to generate strong reproductive isolation between species, in which sexual selection may play an important role by generating and maintaining sexual dimorphism. The mechanism of how sexual selection operated in speciation with gene flow remains an open question and the subject of many research. Two species in genus Chrysolophus, Golden pheasant (C. pictus) and Lady Amherst's pheasant (C. amherstiae), which both exhibit significant plumage dichromatism, are currently parapatric in the southwest China with several hybrid recordings in field. Methods: In this research, we estimated the pattern of gene flow during the speciation of two pheasants using the Approximate Bayesian Computation (ABC) method based on the multiple genes data. With a new assembled de novo genome of Lady Amherst's pheasant and resequencing of widely distributed individuals, we reconstructed the demographic history of the two pheasants by pairwise sequentially Markovian coalescent (PSMC). Results: The results provide clear evidence that the gene flow between the two pheasants were consistent with the prediction of isolation with migration model for allopatric populations, indicating that there was long-term gene flow after the initially divergence (ca. 2.2 million years ago), and further support the secondary contact when included the parapatric populations since around 30 ka ongoing gene flow to now, which might be induced by the population expansion of the Golden pheasant in late Pleistocene. Conclusions: The results of the study support the scenario of speciation between Golden pheasant (C. pictus) and Lady Amherst's pheasant (C. amherstiae) with cycles of mixing-isolation-mixing due to the dynamics of natural selection and sexual selection in late Pleistocene that provide a good research system as evolutionary model to test reinforcement selection in speciation. Keywords: Golden pheasant (Chrysolophus pictus), Lady Amherst's pheasant (Chrysolophus amherstiae), speciation, gene flow, Approximate Bayesian Computation (ABC), Pairwise Sequentially Markovian coalescent (PSMC).

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

PeerJ ◽  
2016 ◽  
Vol 4 ◽  
pp. e1910 ◽  
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.

scholarly journals Exploring Approximate Bayesian Computation for inferring recent demographic history with genomic markers in non-model species

2018 ◽  
Author(s):  
Joane S. Elleouet ◽  
Sally N. Aitken
Keyword(s):  
Sample Size ◽  
Approximate Bayesian Computation ◽  
Demographic History ◽  
Initial Population ◽  
Bayesian Computation ◽  
Large Sample Size ◽  
Spatial Expansion ◽  
Model Species ◽  
Genomic Markers ◽  
Approximate Bayesian

AbstractApproximate Bayesian computation (ABC) is widely used to infer demographic history of populations and species using DNA markers. Genomic markers can now be developed for non-model species using reduced representation library (RRL) sequencing methods that select a fraction of the genome using targeted sequence capture or restriction enzymes (genotyping-by-sequencing, GBS). We explored the influence of marker number and length, knowledge of gametic phase, and tradeoffs between sample size and sequencing depth on the quality of demographic inferences performed with ABC. We focused on 2-population models of recent spatial expansion with varying numbers of unknown parameters. Performing ABC on simulated datasets with known parameter values, we found that the timing of a recent spatial expansion event could be precisely estimated in a 3-parameter model. Taking into account uncertainty in parameters such as initial population size and migration rate collectively decreased the precision of inferences dramatically. Phasing haplotypes did not improve results, regardless of sequence length. Numerous short sequences were as valuable as fewer, longer sequences, and performed best when a large sample size was sequenced at low individual depth, even when sequencing errors were added. ABC results were similar to results obtained with an alternative method based on the site frequency spectrum (SFS) when performed with unphased GBS-type markers. We conclude that unphased GBS-type datasets can be sufficient to precisely infer simple demographic models, and discuss possible improvements for the use of ABC with genomic data.

scholarly journals Approximate Bayesian computation untangles signatures of contemporary and historical hybridization between two endangered species

2021 ◽  
Author(s):  
Hannes Dittberner ◽  
Aurelien Tellier ◽  
Juliette de Meaux
Keyword(s):  
Gene Flow ◽  
Endangered Species ◽  
Approximate Bayesian Computation ◽  
Bayesian Computation ◽  
Sympatric Population ◽  
Genome Data ◽  
Contemporary Gene Flow ◽  
History Of ◽  
Low Levels ◽  
Approximate Bayesian

ABSTRACTContemporary gene flow, when resumed after a period of isolation, can have crucial consequences for endangered species, as it can both increase the supply of adaptive alleles and erode local adaptation. Determining the history of gene flow and thus the importance of contemporary hybridization, however, is notoriously difficult. Here, we focus on two endangered plant species, Arabis nemorensis and A. sagittata, which hybridize naturally in a sympatric population located on the banks of the Rhine. Using reduced genome sequencing, we determined the phylogeography of the two taxa but report only a unique sympatric population. Molecular variation in chloroplast DNA indicated that A. sagittata is the principal receiver of gene flow. Applying classical D-statistics and its derivatives to whole-genome data of 35 accessions, we detect gene flow not only in the sympatric population but also among allopatric populations. Using an Approximate Bayesian computation approach, we identify the model that best describes the history of gene flow between these taxa. This model shows that low levels of gene flow have persisted long after speciation. Around 10 000 years ago, gene flow stopped and a period of complete isolation began. Eventually, a hotspot of contemporary hybridization was formed in the unique sympatric population. Occasional sympatry may have helped protect these lineages from extinction in spite of their extremely low diversity.

scholarly journals Reconstructing the demographic history of orang-utans using Approximate Bayesian Computation

2015 ◽  
Vol 24 (2) ◽  
pp. 310-327 ◽  
Author(s):  
Alexander Nater ◽  
Maja P. Greminger ◽  
Natasha Arora ◽  
Carel P. van Schaik ◽  
Benoit Goossens ◽  
...  
Keyword(s):  
Approximate Bayesian Computation ◽  
Demographic History ◽  
Bayesian Computation ◽  
History Of ◽  
Approximate Bayesian

scholarly journals Investigating speciation in face of polyploidization: what can we learn from approximate Bayesian computation approach?

2014 ◽  
Author(s):  
Camille Roux ◽  
John Pannell
Keyword(s):  
Approximate Bayesian Computation ◽  
Sequence Data ◽  
Demographic History ◽  
Genomic Analysis ◽  
Bayesian Computation ◽  
Evolutionary Analysis ◽  
Polyploid Species ◽  
Model Species ◽  
Karyotypic Analysis ◽  
Approximate Bayesian

Despite its importance in the diversification of many eucaryote clades, particularly plants, detailed genomic analysis of polyploid species is still in its infancy, with published analysis of only a handful of model species to date. Fundamental questions concerning the origin of polyploid lineages (e.g., auto- vs. allopolyploidy) and the extent to which polyploid genomes display different modes of inheritance are poorly resolved for most polyploids, not least because they have hitherto required detailed karyotypic analysis or the analysis of allele segregation at multiple loci in pedigrees or artificial crosses, which are often not practical for non-model species. However, the increasing availability of sequence data for non-model species now presents an opportunity to apply established approaches for the evolutionary analysis of genomic data to polyploid species complexes. Here, we ask whether approximate Bayesian computation (ABC), applied to sequence data produced by next-generation sequencing technologies from polyploid taxa, allows correct inference of the evolutionary and demographic history of polyploid lineages and their close relatives. We use simulations to investigate how the number of sampled individuals, the number of surveyed loci and their length affect the accuracy and precision of evolutionary and demographic inferences by ABC, including the mode of polyploidisation, mode of inheritance of polyploid taxa, the relative timing of genome duplication and speciation, and effective populations sizes of contributing lineages. We also apply the ABC framework we develop to sequence data from diploid and polyploidy species of the plant genus Capsella, for which we infer an allopolyploid origin for tetra C. bursa-pastoris ≈ 90,000 years ago. In general, our results indicate that ABC is a promising and powerful method for uncovering the origin and subsequent evolution of polyploid species.

scholarly journals PipeMaster: inferring population divergence and demographic history with approximate Bayesian computation and supervised machine-learning in R

2020 ◽  
Author(s):  
Marcelo Gehara ◽  
Guilherme G. Mazzochinni ◽  
Frank Burbrink
Keyword(s):  
Machine Learning ◽  
Approximate Bayesian Computation ◽  
Demographic History ◽  
Divergence Time ◽  
R Package ◽  
Supervised Machine Learning ◽  
Population Divergence ◽  
Bayesian Computation ◽  
Approximate Bayesian ◽  
Recent Bottleneck

AbstractUnderstanding population divergence involves testing diversification scenarios and estimating historical parameters, such as divergence time, population size and migration rate. There is, however, an immense space of possible highly parameterized scenarios that are difsficult or impossible to solve analytically. To overcome this problem researchers have used alternative simulation-based approaches, such as approximate Bayesian computation (ABC) and supervised machine learning (SML), to approximate posterior probabilities of hypotheses. In this study we demonstrate the utility of our newly developed R-package to simulate summary statistics to perform ABC and SML inferences. We compare the power of both ABC and SML methods and the influence of the number of loci in the accuracy of inferences; and we show three empirical examples: (i) the Muller’s termite frog genomic data from Southamerica; (ii) the cottonmouth and (iii) and the copperhead snakes sanger data from Northamerica. We found that SML is more efficient than ABC. It is generally more accurate and needs fewer simulations to perform an inference. We found support for a divergence model without migration, with a recent bottleneck for one of the populations of the southamerican frog. For the cottonmouth we found support for divergence with migration and recent expansion and for the copperhead we found support for a model of divergence with migration and recent bottleneck. Interestingly, by using an SML method it was possible to achieve high accuracy in model selection even when several models were compared in a single inference. We also found a higher accuracy when inferring parameters with SML.

scholarly journals Phylogeny of beech in western Eurasia as inferred by approximate Bayesian computation

2018 ◽  
Vol 87 (2) ◽  
Author(s):  
Dušan Gömöry ◽  
Ladislav Paule ◽  
Vladimír Mačejovský
Keyword(s):  
Species Complex ◽  
Approximate Bayesian Computation ◽  
Demographic History ◽  
Sensu Stricto ◽  
Early Pleistocene ◽  
Hybrid Origin ◽  
Bayesian Computation ◽  
Western Asia ◽  
Approximate Bayesian ◽  
Western Eurasia

The <em>Fagus sylvatica</em> L. species complex in Europe and Western Asia comprises two commonly recognized subspecies, <em>F. sylvatica</em> subsp. <em>sylvatica</em> [= <em>F. sylvatica</em> sensu stricto (s. str.)] and <em>F. sylvatica</em> subsp. <em>orientalis</em> (= <em>F. orientalis</em>), and two putatively hybridogenous or intermediate taxa, “<em>F. moesiaca</em>” and “<em>F. taurica</em>”. The present study aimed to examine the demographic history of this species complex using 12 allelic loci of nine allozymes scored in 279 beech populations in western Eurasia. Three sets of phylogenetic scenarios were tested by approximate Bayesian computation: one dealing with the divergence of subspecies and/or regional populations within the whole taxonomical complex, and two others focusing on the potential hybrid origin of “<em>F. moesiaca</em>” and “<em>F. taurica</em>”. The best-supported scenario within the first set placed the time of divergence of regional populations of <em>F. orientalis</em> in the Early Pleistocene (1.18–1.87 My BP). According to this scenario, the Iranian population was the ancestral lineage, whereas <em>F. sylvatica</em> s. str. was the lineage that diverged most recently. “<em>Fagus taurica</em>” was found to have originated from hybridization between the Caucasian population of <em>F. orientalis</em> and <em>F. sylvatica</em> s. str. at 144 ky BP. In contrast, there was no evidence of a hybrid origin of “<em>F. moesiaca</em>”. The best-supported scenario suggested that the Balkan lineage is a part of <em>F. sylvatica</em> s. str., which diverged early from <em>F. orientalis</em> in Asia Minor (817 ky BP), while both the Italian and Central-European lineages diverged from the Balkan one later, at the beginning of the last (Weichselian) glacial period.

River capture or ancestral polymorphism: an empirical genetic test in a freshwater fish using approximate Bayesian computation

2020 ◽  
Vol 131 (3) ◽  
pp. 575-584
Author(s):  
Mateus S Souza ◽  
Andréa T Thomaz ◽  
Nelson J R Fagundes
Keyword(s):  
Mitochondrial Dna ◽  
Freshwater Fish ◽  
Approximate Bayesian Computation ◽  
Large Population ◽  
Secondary Contact ◽  
Bayesian Computation ◽  
Reciprocal Monophyly ◽  
Geological Evidence ◽  
River Capture ◽  
Approximate Bayesian

Abstract A headwater or river capture is a phenomenon commonly invoked to explain the absence of reciprocal monophyly of genetic lineages among isolated hydrographic basins in freshwater fish. Under the assumption of river capture, a secondary contact between populations previously isolated in different basins explains the observed genetic pattern. However, the absence of reciprocal monophyly could also arise under population isolation through the retention of ancestral of polymorphisms. Here, we applied an approximate Bayesian computation (ABC) framework for estimating the relative probability of scenarios with and without secondary contact. We used Cnesterodon decemmaculatus as a study model because of the multiple possible cases of river capture and the demographic parameters estimated in a previous mitochondrial DNA study that are useful for simulating scenarios to test both hypotheses using the ABC framework. Our results showed that, in general, mitochondrial DNA is useful for distinguishing between these alternative demographic scenarios with reasonable confidence, but in extreme cases (e.g. recent divergence or large population size) there is no power to discriminate between scenarios. Testing hypotheses of drainage rearrangement under a statistically rigorous framework is fundamental for understanding the evolution of freshwater fish fauna as a complement to, or in the absence of, geological evidence.

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