Section: Evolutionary Biology
Topic:
Ecology,
Evolution,
Genetics/genomics
Exploring the effects of ecological parameters on the spatial structure of genetic tree sequences
Corresponding author(s): Ianni-Ravn, Mariadaria K. (mianniravn@uchicago.edu)
10.24072/pcjournal.439 - Peer Community Journal, Volume 4 (2024), article no. e75.
Get full text PDF Peer reviewed and recommended by PCIGeographic space is a fundamental dimension of evolutionary change, determining how individuals disperse and interact with each other. Consequently, space has an important influence on the structure of genealogies and the distribution of genetic variants over time. Recently, the development of highly flexible simulation tools and computational methods for genealogical inference has greatly increased the potential for incorporating space into models of population genetic variation. It is now possible to explore how spatial ecological parameters can influence the distribution of genetic variation among individuals in unprecedented detail. In this study, we explore the effects of three specific parameters (the dispersal distance, competition distance and mate choice distance) on the spatial structure of genealogies. We carry out a series of in silico experiments using forwards-in-time simulations to determine how these parameters influence the distance between closely- and distantly-related individuals. We also assess the accuracy of the maximum likelihood estimation of the dispersal distance in a Gaussian model of dispersal from tree-sequence data, and highlight how it is affected by realistic factors such as finite habitat size and limited data. We find overall that the scale of mate choice in particular has marked patterns on short and long terms patterns of dispersal, as well as on the positions of individuals within a habitat. Our results showcase the potential for linking phylogeography, population genetics and ecology, in order to answer fundamental questions about the nature of spatial interactions across a landscape.
Type: Research article
Ianni-Ravn, Mariadaria K. 1, 2; Petr, Martin 1, 3; Racimo, Fernando 1, 3
@article{10_24072_pcjournal_439, author = {Ianni-Ravn, Mariadaria K. and Petr, Martin and Racimo, Fernando}, title = {Exploring the effects of ecological parameters on the spatial structure of genetic tree sequences}, journal = {Peer Community Journal}, eid = {e75}, publisher = {Peer Community In}, volume = {4}, year = {2024}, doi = {10.24072/pcjournal.439}, language = {en}, url = {https://peercommunityjournal.org/articles/10.24072/pcjournal.439/} }
TY - JOUR AU - Ianni-Ravn, Mariadaria K. AU - Petr, Martin AU - Racimo, Fernando TI - Exploring the effects of ecological parameters on the spatial structure of genetic tree sequences JO - Peer Community Journal PY - 2024 VL - 4 PB - Peer Community In UR - https://peercommunityjournal.org/articles/10.24072/pcjournal.439/ DO - 10.24072/pcjournal.439 LA - en ID - 10_24072_pcjournal_439 ER -
%0 Journal Article %A Ianni-Ravn, Mariadaria K. %A Petr, Martin %A Racimo, Fernando %T Exploring the effects of ecological parameters on the spatial structure of genetic tree sequences %J Peer Community Journal %D 2024 %V 4 %I Peer Community In %U https://peercommunityjournal.org/articles/10.24072/pcjournal.439/ %R 10.24072/pcjournal.439 %G en %F 10_24072_pcjournal_439
Ianni-Ravn, Mariadaria K.; Petr, Martin; Racimo, Fernando. Exploring the effects of ecological parameters on the spatial structure of genetic tree sequences. Peer Community Journal, Volume 4 (2024), article no. e75. doi : 10.24072/pcjournal.439. https://peercommunityjournal.org/articles/10.24072/pcjournal.439/
PCI peer reviews and recommendation, and links to data, scripts, code and supplementary information: 10.24072/pci.evolbiol.100655
Conflict of interest of the recommender and peer reviewers:
The recommender in charge of the evaluation of the article and the reviewers declared that they have no conflict of interest (as defined in the code of conduct of PCI) with the authors or with the content of the article.
[1] Deconstructing isolation-by-distance: The genomic consequences of limited dispersal, PLOS Genetics, Volume 13 (2017) no. 8 | DOI
[2] Space is the place: effects of continuous spatial structure on analysis of population genetic data, Genetics, Volume 215 (2020) no. 1, pp. 193-214 | DOI
[3] apTreeshape: statistical analysis of phylogenetic tree shape, Bioinformatics, Volume 22 (2006) no. 3, pp. 363-364 | DOI
[4] Spatial population genetics: it's about time, Annual Review of Ecology Evolution and Systematics, Volume 50 (2019), pp. 427-449 | DOI
[5] Evaluation of methods for estimating coalescence times using ancestral recombination graphs, Genetics, Volume 221 (2022) no. 1 | DOI
[6] Phylogeography and molecular epidemiology of Papaya ringspot virus, Virus research, Volume 159 (2011) no. 2, pp. 132-140 | DOI
[7] Demographic and genetic approaches to study dispersal in wild animal populations: A methodological review, Molecular ecology, Volume 27 (2018) no. 20, pp. 3976-4010 | DOI
[8] The effects of genetic and geographic structure on neutral variation, Annual Review of Ecology Evolution and Systematics, Volume 34 (2003) no. 1, pp. 99-125 | DOI
[9] Why trees migrate so fast: confronting theory with dispersal biology and the paleorecord, The American Naturalist, Volume 152 (1998) no. 2, pp. 204-224 | DOI
[10] Maximum-likelihood estimation of evolutionary trees from continuous characters, American journal of human genetics, Volume 25 (1973) no. 5, p. 471 | DOI
[11] A Pain in the Torus: Some Difficulties with Models of Isolation by Distance, The American Naturalist, Volume 109 (1975) no. 967, pp. 359-368 | DOI
[12] The wave of advance of advantageous genes, Annals of eugenics, Volume 7 (1937) no. 4, pp. 355-369 | DOI
[13] An ancestral recombination graph, Progress in population genetics and human evolution, Springer, 1997 (http://home.uchicago.edu/~rhudson1/popgen356/OxfordSurveysEvolBiol7_1-44.pdf)
[14] Ancestral Inference from Samples of DNA Sequences with Recombination, Journal of Computational Biology, Volume 3 (1996) no. 4, pp. 479-502 | DOI
[15] ggplot2-elegant graphics for data analysis, Journal of Statistical Software, Volume 77 (2017), pp. 1-3 | DOI
[16] Tree-sequence recording in SLiM opens new horizons for forward-time simulation of whole genomes, Molecular ecology resources, Volume 19 (2019) no. 2, pp. 552-566 | DOI
[17] SLiM 3: forward genetic simulations beyond the Wright–Fisher model, Molecular biology and evolution, Volume 36 (2019) no. 3, pp. 632-637 | DOI
[18] Isolation by distance in a continuous population: reconciliation between spatial autocorrelation analysis and population genetics models, Heredity, Volume 83 (1999) no. 2, pp. 145-154 | DOI
[19] Inference of ancestral recombination graphs using ARGweaver, Statistical Population Genomics, Humana, New York, NY, 2020, pp. 231-266 | DOI
[20] Gene genealogies and the coalescent process, Oxford surveys in evolutionary biology, Volume 7 (1990) no. 1, p. 44 (http://home.uchicago.edu/ rhudson1/popgen356/OxfordSurveysEvolBiol7_1-44.pdf)
[21] mkiravn/treesinspace: Code for Exploring the effects of ecological parameters on the spatial structure of genetic tree sequences (v0.1.0), Zenodo, 2023 | DOI
[22] A meta-analysis of isolation by distance: relic or reference standard for landscape genetics?, Ecography, Volume 33 (2010) no. 2, pp. 315-320 | DOI
[23] Efficient pedigree recording for fast population genetics simulation, PLOS Computational Biology, Volume 14 (2018) no. 11 | DOI
[24] Inferring whole-genome histories in large population datasets, Nature genetics, Volume 51 (2019) no. 9, pp. 1330-1338 | DOI
[25] Moments, cumulants, skewness, kurtosis and related tests, R package version, Volume 14 (2015) | DOI
[26] Dispersal data and the spread of invading organisms, Ecology, Volume 77 (1996) no. 7, pp. 2027-2042 | DOI
[27] Robust, universal tree balance indices, Systematic biology, Volume 71 (2022) no. 5, pp. 1210-1224 | DOI
[28] Sex-biased dispersal: A review of the theory, Biological Reviews, Volume 94 (2019) no. 2, pp. 721-736 | DOI
[29] Female philopatry and male-biased dispersal in a direct-developing salamander, Plethodon cinereus, Molecular Ecology, Volume 20 (2011) no. 2, pp. 249-257 | DOI
[30] Phylogeography and molecular epidemiology of hepatitis C virus genotype 2 in Africa, Journal of General Virology, Volume 90 (2009) no. 9, pp. 2086-2096 | DOI
[31] Population outbreaks in a discrete world, Theoretical Population Biology, Volume 57 (2000) no. 2, pp. 97-108 | DOI
[32] The molecular epidemiology and phylogeography of Trypanosoma cruzi and parallel research on Leishmania: looking back and to the future, Parasitology, Volume 136 (2009) no. 12, pp. 1509-1528 | DOI
[33] Package ‘VGAM’, 2022 | DOI
[34] Modeling the spatiotemporal spread of beneficial alleles using ancient genomes, eLife, Volume 11 (2022) | DOI
[35] Genes mirror geography within Europe, Nature, Volume 456 (2008) no. 7218, pp. 98-101 | DOI
[36] Human mtDNA and Y-chromosome variation is correlated with matrilocal versus patrilocal residence, Nature genetics, Volume 29 (2001) no. 1, pp. 20-21 | DOI
[37] Disentangling the impact of mating and competition on dispersal patterns, Peer Community in Evolutionary Biology (2024) | DOI
[38] Estimating dispersal rates and locating genetic ancestors with genome-wide genealogies, bioRxiv (2021) | DOI
[39] ape 5.0: an environment for modern phylogenetics and evolutionary analyses in R, Bioinformatics, Volume 35 (2019) no. 3, pp. 526-528 | DOI
[40] The impact of long-range dispersal on gene surfing, Proceedings of the National Academy of Sciences, Volume 117 (2020) no. 14, pp. 7584-7593 | DOI
[41] Simple Features for R: Standardized Support for Spatial Vector Data, The R Journal, Volume 10 (2018) no. 1 | DOI
[42] slendr: a framework for spatio-temporal population genomic simulations on geographic landscapes, Peer Community Journal, Volume 3 (2023) | DOI
[43] Genome-wide inference of ancestral recombination graphs, PLoS genetics, Volume 10 (2014) no. 5, p. e1004342 | DOI
[44] Inferring recent demography from isolation by distance of long shared sequence blocks, Genetics, Volume 205 (2017) no. 3, pp. 1335-1351 | DOI
[45] Isolation by distance in a continuous population under stochastic demographic fluctuations, Journal of evolutionary biology, Volume 23 (2010) no. 1, pp. 53-71 | DOI
[46] Inferences from spatial population genetics, Handbook of statistical genetics, Volume 4 (2001), p. 23 | DOI
[47] Genetic differentiation and estimation of gene flow from F-statistics under isolation by distance, Genetics, Volume 145 (1997) no. 4, pp. 1219-1228 | DOI
[48] Male-Mediated Gene Flow in Patrilocal Primates, PLoS ONE, Volume 6 (2011) no. 7 | DOI
[49] Genetic isolation by environment or distance: which pattern of gene flow is most common?, Evolution, Volume 68 (2014) no. 1, pp. 1-15 | DOI
[50] Dispersal inference from population genetic variation using a convolutional neural network, Genetics, Volume 224 (2023) no. 2 | DOI
[51] Isolation by Distance in Populations with Power-law Dispersal, bioRxiv, 2020 | DOI
[52] A method for genome-wide genealogy estimation for thousands of samples, Nature genetics, Volume 51 (2019) no. 9, pp. 1321-1329 | DOI
[53] Population genetic models for the spatial spread of adaptive variants: A review in light of SARS-CoV-2 evolution, PLOS Genetics, Volume 18 (2022) no. 9 | DOI
[54] Zusammensetzung von Populationen und Korrelationserscheinungen vom Standpunkt der Vererbungslehre aus betrachtet, Hereditas, Volume 11 (1928) no. 1, pp. 65-106 | DOI
[55] The coalescent in a continuous, finite, linear population, Genetics, Volume 161 (2002) no. 2, pp. 873-888 | DOI
[56] A unified genealogy of modern and ancient genomes, Science, Volume 375 (2022) no. 6583 | DOI
[57] Mathematica: a system for doing mathematics by computer, Addison Wesley Longman Publishing Co., Inc., 1991 | DOI
[58] Isolation by distance, Genetics, Volume 28 (1943) no. 2, p. 114 | DOI
Cited by Sources: