Abstract
This chapter outlines an empirical analysis of genome-wide single-nucleotide polymorphism (SNP) variation and its underlying drivers among multiple natural populations within a diploid-autopolyploid species. The aim is to reconstruct the genetic structure among natural populations of varying ploidy and infer footprints of selection in these populations, framed around specific questions that are typically encountered when analyzing a mixed-ploidy data set,e.g., addressing the relevance of natural whole-genome duplication for speciation and adaptation. We briefly review the options for the analysis of polyploid population genomic data involving variant calling, population structure, demographic history inference, and selection scanning approaches. Further, we provide suggestions for methods and associated software, possible caveats, and examples of their application to mixed-ploidy and autopolyploid data sets.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Dufresne F, Stift M, Vergilino R, Mable BK (2014) Recent progress and challenges in population genetics of polyploid organisms: an overview of current state-of-the-art molecular and statistical tools. Mol Ecol 23:40–69. https://doi.org/10.1111/mec.12581
Meirmans PG, Liu S, van Tienderen PH (2018) The analysis of polyploid genetic data. J Hered 109:283–296. https://doi.org/10.1093/jhered/esy006
Monnahan P, Kolář F, Baduel P et al (2019) Pervasive population genomic consequences of genome duplication in Arabidopsis arenosa. Nat Ecol Evol 3:457. https://doi.org/10.1038/s41559-019-0807-4
Bohutínská M, Vlček J, Yair S et al (2021) Genomic basis of parallel adaptation varies with divergence in Arabidopsis and its relatives. PNAS 118. https://doi.org/10.1073/pnas.2022713118
Konečná V, Bray S, Vlček J et al (2021) Parallel adaptation in autopolyploid Arabidopsis arenosa is dominated by repeated recruitment of shared alleles. bioRxiv 2021.01.15.426785. https://doi.org/10.1101/2021.01.15.426785
Bohutínská M, Handrick V, Yant L et al (2021) De novo mutation and rapid protein (co-)evolution during meiotic adaptation in Arabidopsis arenosa. Mol Biol Evol 38:1980–1994. https://doi.org/10.1093/molbev/msab001
Yant L, Bomblies K (2017) Genomic studies of adaptive evolution in outcrossing Arabidopsis species. Curr Opin Plant Biol 36:9–14. https://doi.org/10.1016/j.pbi.2016.11.018
Kolář F, Lučanová M, Záveská E et al (2016) Ecological segregation does not drive the intricate parapatric distribution of diploid and tetraploid cytotypes of the Arabidopsis arenosa group (Brassicaceae). Biol J Linn Soc Lond 119:673–688. https://doi.org/10.1111/bij.12479
Morgan EJ, Čertner M, Lučanová M et al (2020) Niche similarity in diploid-autotetraploid contact zones of Arabidopsis arenosa across spatial scales. Am J Bot 107:1375–1388. https://doi.org/10.1002/ajb2.1534
Arnold B, Kim S-T, Bomblies K (2015) Single geographic origin of a widespread autotetraploid Arabidopsis arenosa lineage followed by interploidy admixture. Mol Biol Evol 32:1382–1395
Kolář F, Fuxová G, Záveská E et al (2016) Northern glacial refugia and altitudinal niche divergence shape genome-wide differentiation in the emerging plant model Arabidopsis arenosa. Mol Ecol 25:3929–3949. https://doi.org/10.1111/mec.13721
Knotek A, Konečná V, Wos G et al (2020) Parallel Alpine Differentiation in Arabidopsis arenosa. Front Plant Sci 11. https://doi.org/10.3389/fpls.2020.561526
Li H, Durbin R (2009) Fast and accurate short read alignment with Burrows–Wheeler transform. Bioinformatics 25:1754–1760. https://doi.org/10.1093/bioinformatics/btp324
McKenna A, Hanna M, Banks E et al (2010) The Genome Analysis Toolkit: a MapReduce framework for analyzing next-generation DNA sequencing data. Genome Res 20:1297–1303. https://doi.org/10.1101/gr.107524.110
Parisod C, Holderegger R, Brochmann C (2010) Evolutionary consequences of autopolyploidy. New Phytol 186:5–17. https://doi.org/10.1111/j.1469-8137.2009.03142.x
Butruille DV, Boiteux LS (2000) Selection–mutation balance in polysomic tetraploids: impact of double reduction and gametophytic selection on the frequency and subchromosomal localization of deleterious mutations. PNAS 97:6608–6613
Blischak PD, Kubatko LS, Wolfe AD (2018) SNP genotyping and parameter estimation in polyploids using low-coverage sequencing data. Bioinformatics 34:407–415. https://doi.org/10.1093/bioinformatics/btx587
Shastry V, Adams PE, Lindtke D et al (2021) Model-based genotype and ancestry estimation for potential hybrids with mixed-ploidy. Mol Ecol Resour 21:1434–1451. https://doi.org/10.1111/1755-0998.13330
Gerard D, Ferrão LFV, Garcia AAF, Stephens M (2018) Genotyping polyploids from messy sequencing data. Genetics 210:789–807. https://doi.org/10.1534/genetics.118.301468
Voorrips RE, Gort G, Vosman B (2011) Genotype calling in tetraploid species from bi-allelic marker data using mixture models. BMC Bioinform 12:172. https://doi.org/10.1186/1471-2105-12-172
Monnahan P, Brandvain Y (2020) The effect of autopolyploidy on population genetic signals of hard sweeps. Biol Lett 16:20190796. https://doi.org/10.1098/rsbl.2019.0796
Ronfort J, Jenczewski E, Bataillon T, Rousset F (1998) Analysis of population structure in autotetraploid species. Genetics 150:921–930. https://doi.org/10.1093/genetics/150.2.921
Nei M, Li WH (1979) Mathematical model for studying genetic variation in terms of restriction endonucleases. PNAS 76:5269–5273
Meirmans PG GenoDive version 3.0: easy-to-use software for the analysis of genetic data of diploids and polyploids. Mol Ecol Resour. https://doi.org/10.1111/1755-0998.13145
Tajima F (1989) Statistical method for testing the neutral mutation hypothesis by DNA polymorphism. Genetics 123:585–595
Ferretti L, Ribeca P, Ramos-Onsins SE (2018) The site frequency/dosage spectrum of autopolyploid populations. Front Genet 9. https://doi.org/10.3389/fgene.2018.00480
Schraiber JG, Akey JM (2015) Methods and models for unravelling human evolutionary history. Nat Rev Genet 16:727–740. https://doi.org/10.1038/nrg4005
Bohutínská M, Alston M, Monnahan P et al (2021) Novelty and convergence in adaptation to whole genome duplication. Mol Biol Evol. https://doi.org/10.1093/molbev/msab096
Bray SM, Wolf EM, Zhou M et al (2020) Convergence and novelty in adaptation to whole genome duplication in three independent polyploids. bioRxiv 2020.03.31.017939. https://doi.org/10.1101/2020.03.31.017939
Hudson RR, Slatkin M, Maddison WP (1992) Estimation of levels of gene flow from DNA sequence data. Genetics 132:583–589
Meirmans PG, Liu S (2018) Analysis of molecular variance (AMOVA) for autopolyploids. Front Ecol Evol 6. https://doi.org/10.3389/fevo.2018.00066
Huang K, Wang T, Dunn DW et al (2021) A generalized framework for AMOVA with multiple hierarchies and ploidies. Integr Zool 16:33–52. https://doi.org/10.1111/1749-4877.12460
Stift M, Kolář F, Meirmans PG (2019) Structure is more robust than other clustering methods in simulated mixed-ploidy populations. Heredity 123:429–441. https://doi.org/10.1038/s41437-019-0247-6
Pritchard JK, Stephens M, Donnelly P (2000) Inference of population structure using multilocus genotype data. Genetics 155:945–959
Alexander DH, Novembre J, Lange K (2009) Fast model-based estimation of ancestry in unrelated individuals. Genome Res 19:1655–1664. https://doi.org/10.1101/gr.094052.109
Raj A, Stephens M, Pritchard JK (2014) fastSTRUCTURE: Variational inference of population structure in large SNP data sets. Genetics 197:573–589. https://doi.org/10.1534/genetics.114.164350
Novikova PY, Hohmann N, Nizhynska V et al (2016) Sequencing of the genus Arabidopsis identifies a complex history of nonbifurcating speciation and abundant trans-specific polymorphism. Nat Genet 48:1077–1082. https://doi.org/10.1038/ng.3617
Pickrell JK, Pritchard JK (2012) Inference of population splits and mixtures from genome-wide allele frequency data. PLoS Genet 8:e1002967. https://doi.org/10.1371/journal.pgen.1002967
Wos G, Mořkovská J, Bohutínská M et al (2019) Role of ploidy in colonization of alpine habitats in natural populations of Arabidopsis arenosa. Ann Bot 124:255–268. https://doi.org/10.1093/aob/mcz070
Novikova PY, Brennan IG, Booker W et al (2020) Polyploidy breaks speciation barriers in Australian burrowing frogs Neobatrachus. PLoS Genet 16:e1008769. https://doi.org/10.1371/journal.pgen.1008769
Arnold B, Bomblies K, Wakeley J (2012) Extending coalescent theory to autotetraploids. Genetics 192:195–204. https://doi.org/10.1534/genetics.112.140582
Arnold BJ, Lahner B, DaCosta JM et al (2016) Borrowed alleles and convergence in serpentine adaptation. PNAS 113:8320–8325. https://doi.org/10.1073/pnas.1600405113
Excoffier L, Dupanloup I, Huerta-Sánchez E et al (2013) Robust demographic inference from genomic and SNP data. PLoS Genet 9:e1003905
Yant L, Hollister JD, Wright KM et al (2013) Meiotic adaptation to genome duplication in Arabidopsis arenosa. Curr Biol 23:2151–2156. https://doi.org/10.1016/j.cub.2013.08.059
Marburger S, Monnahan P, Seear PJ et al (2019) Interspecific introgression mediates adaptation to whole genome duplication. Nat Commun 10:1–11. https://doi.org/10.1038/s41467-019-13159-5
Schmickl R, Yant L Adaptive introgression: how polyploidy reshapes gene flow landscapes. New Phytol. https://doi.org/10.1111/nph.17204
Vitti JJ, Grossman SR, Sabeti PC (2013) Detecting natural selection in genomic data. Annu Rev Genet 47:97–120. https://doi.org/10.1146/annurev-genet-111212-133526
Stephan W (2019) Selective sweeps. Genetics 211:5–13. https://doi.org/10.1534/genetics.118.301319
Hoban S, Kelley JL, Lotterhos KE et al (2016) Finding the genomic basis of local adaptation: pitfalls, practical solutions, and future directions. Am Nat 188:379–397. https://doi.org/10.1086/688018
Oleksyk TK, Smith MW, O’Brien SJ (2010) Genome-wide scans for footprints of natural selection. Philos Trans R Soc B Biol Sci 365:185–205. https://doi.org/10.1098/rstb.2009.0219
Booker TR, Jackson BC, Keightley PD (2017) Detecting positive selection in the genome. BMC Biol 15:98. https://doi.org/10.1186/s12915-017-0434-y
Motazedi E, Finkers R, Maliepaard C, de Ridder D (2018) Exploiting next-generation sequencing to solve the haplotyping puzzle in polyploids: a simulation study. Brief Bioinform 19:387–403. https://doi.org/10.1093/bib/bbw126
Siragusa E, Haiminen N, Finkers R et al (2019) Haplotype assembly of autotetraploid potato using integer linear programing. Bioinformatics 35:3279–3286. https://doi.org/10.1093/bioinformatics/btz060
Hermisson J, Pennings PS (2005) Soft sweeps: molecular population genetics of adaptation from standing genetic variation. Genetics 169:2335–2352. https://doi.org/10.1534/genetics.104.036947
Morgan C, Zhang H, Henry CE et al (2020) Derived alleles of two axis proteins affect meiotic traits in autotetraploid Arabidopsis arenosa. PNAS. https://doi.org/10.1073/pnas.1919459117
Lee KM, Coop G (2017) Distinguishing among modes of convergent adaptation using population genomic data. Genetics 207:1591–1619. https://doi.org/10.1534/genetics.117.300417
Gautier M (2015) Genome-wide scan for adaptive divergence and association with population-specific covariates. Genetics 201:1555–1579. https://doi.org/10.1534/genetics.115.181453
Cheng JY, Racimo F, Nielsen R (2019) Ohana: detecting selection in multiple populations by modelling ancestral admixture components. bioRxiv 546408. https://doi.org/10.1101/546408
Szpak M, Mezzavilla M, Ayub Q et al (2018) FineMAV: prioritizing candidate genetic variants driving local adaptations in human populations. Genome Biol 19:5. https://doi.org/10.1186/s13059-017-1380-2
McDonald JH, Kreitman M (1991) Adaptive protein evolution at the Adh locus in Drosophila. Nature 351:652–654. https://doi.org/10.1038/351652a0
Charlesworth J, Eyre-Walker A (2008) The McDonald–Kreitman test and slightly deleterious mutations. Mol Biol Evol 25:1007–1015. https://doi.org/10.1093/molbev/msn005
Fay JC, Wyckoff GJ, Wu CI (2001) Positive and negative selection on the human genome. Genetics 158:1227–1234
Zhang L, Li W-H (2005) Human SNPs reveal no evidence of frequent positive selection. Mol Biol Evol 22:2504–2507. https://doi.org/10.1093/molbev/msi240
Frichot E, Schoville SD, Bouchard G, François O (2013) Testing for associations between loci and environmental gradients using latent factor mixed models. Mol Biol Evol 30:1687–1699. https://doi.org/10.1093/molbev/mst063
Meirmans PG, Van Tienderen PH (2013) The effects of inheritance in tetraploids on genetic diversity and population divergence. Heredity 110:131–137. https://doi.org/10.1038/hdy.2012.80
Cingolani P, Platts A, Wang LL et al (2012) A program for annotating and predicting the effects of single nucleotide polymorphisms, SnpEff. Fly 6:80–92. https://doi.org/10.4161/fly.19695
Acknowledgments
We are grateful to Arthur Zwaenepoel, Patrick Meirmans, Josselin Clo, Nélida Padilla García, and Polina Novikova for very useful comments on an earlier version of this chapter. We thank Veronika Konečná, Nélida Padilla García, and Gabriela Šrámková for help with running particular analyses of the example data set and Doubravka Požárová for photos of alpine plants. This work was supported by the Czech Science Foundation (project 20-22783S to FK) and the long-term research development project no. RVO 67985939 of the Czech Academy of Sciences. Access to computing and storage facilities has been provided by the National Grid Infrastructure MetaCentrum provided under the program “Projects of Large Research, Development, and Innovations Infrastructures” (CESNET LM2015042).
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2023 The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature
About this protocol
Cite this protocol
Bohutínská, M., Vlček, J., Monnahan, P., Kolář, F. (2023). Population Genomic Analysis of Diploid-Autopolyploid Species. In: Van de Peer, Y. (eds) Polyploidy. Methods in Molecular Biology, vol 2545. Humana, New York, NY. https://doi.org/10.1007/978-1-0716-2561-3_16
Download citation
DOI: https://doi.org/10.1007/978-1-0716-2561-3_16
Published:
Publisher Name: Humana, New York, NY
Print ISBN: 978-1-0716-2560-6
Online ISBN: 978-1-0716-2561-3
eBook Packages: Springer Protocols