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Population Genomic Analysis of Diploid-Autopolyploid Species

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Polyploidy

Part of the book series: Methods in Molecular Biology ((MIMB,volume 2545))

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.

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References

  1. 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

    Article  Google Scholar 

  2. 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

    Article  CAS  Google Scholar 

  3. 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

    Article  Google Scholar 

  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

  5. 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

  6. 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

    Article  CAS  Google Scholar 

  7. 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

    Article  CAS  Google Scholar 

  8. 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

    Article  Google Scholar 

  9. 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

    Article  Google Scholar 

  10. 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

    Article  CAS  Google Scholar 

  11. 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

    Article  Google Scholar 

  12. 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

  13. 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

  14. 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

    Article  CAS  Google Scholar 

  15. 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

    Article  CAS  Google Scholar 

  16. 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

    Article  CAS  Google Scholar 

  17. 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

    Article  CAS  Google Scholar 

  18. 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

    Article  CAS  Google Scholar 

  19. 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

    Article  Google Scholar 

  20. 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

    Article  Google Scholar 

  21. 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

    Article  Google Scholar 

  22. 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

    Article  CAS  Google Scholar 

  23. Nei M, Li WH (1979) Mathematical model for studying genetic variation in terms of restriction endonucleases. PNAS 76:5269–5273

    Article  CAS  Google Scholar 

  24. 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

  25. Tajima F (1989) Statistical method for testing the neutral mutation hypothesis by DNA polymorphism. Genetics 123:585–595

    Article  CAS  Google Scholar 

  26. 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

  27. 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

    Article  CAS  Google Scholar 

  28. 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

  29. 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

  30. Hudson RR, Slatkin M, Maddison WP (1992) Estimation of levels of gene flow from DNA sequence data. Genetics 132:583–589

    Article  CAS  Google Scholar 

  31. Meirmans PG, Liu S (2018) Analysis of molecular variance (AMOVA) for autopolyploids. Front Ecol Evol 6. https://doi.org/10.3389/fevo.2018.00066

  32. 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

    Article  Google Scholar 

  33. 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

    Article  Google Scholar 

  34. Pritchard JK, Stephens M, Donnelly P (2000) Inference of population structure using multilocus genotype data. Genetics 155:945–959

    Article  CAS  Google Scholar 

  35. 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

    Article  CAS  Google Scholar 

  36. 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

    Article  Google Scholar 

  37. 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

    Article  CAS  Google Scholar 

  38. 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

    Article  CAS  Google Scholar 

  39. 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

    Article  Google Scholar 

  40. 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

    Article  CAS  Google Scholar 

  41. Arnold B, Bomblies K, Wakeley J (2012) Extending coalescent theory to autotetraploids. Genetics 192:195–204. https://doi.org/10.1534/genetics.112.140582

    Article  CAS  Google Scholar 

  42. 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

    Article  CAS  Google Scholar 

  43. Excoffier L, Dupanloup I, Huerta-Sánchez E et al (2013) Robust demographic inference from genomic and SNP data. PLoS Genet 9:e1003905

    Article  Google Scholar 

  44. 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

    Article  CAS  Google Scholar 

  45. 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

    Article  CAS  Google Scholar 

  46. Schmickl R, Yant L Adaptive introgression: how polyploidy reshapes gene flow landscapes. New Phytol. https://doi.org/10.1111/nph.17204

  47. 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

    Article  CAS  Google Scholar 

  48. Stephan W (2019) Selective sweeps. Genetics 211:5–13. https://doi.org/10.1534/genetics.118.301319

    Article  Google Scholar 

  49. 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

    Article  Google Scholar 

  50. 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

    Article  CAS  Google Scholar 

  51. 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

    Article  CAS  Google Scholar 

  52. 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

    Article  Google Scholar 

  53. 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

    Article  CAS  Google Scholar 

  54. 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

    Article  CAS  Google Scholar 

  55. 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

  56. 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

    Article  Google Scholar 

  57. 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

    Article  CAS  Google Scholar 

  58. 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

  59. 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

    Article  CAS  Google Scholar 

  60. McDonald JH, Kreitman M (1991) Adaptive protein evolution at the Adh locus in Drosophila. Nature 351:652–654. https://doi.org/10.1038/351652a0

    Article  CAS  Google Scholar 

  61. 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

    Article  CAS  Google Scholar 

  62. Fay JC, Wyckoff GJ, Wu CI (2001) Positive and negative selection on the human genome. Genetics 158:1227–1234

    Article  CAS  Google Scholar 

  63. 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

    Article  CAS  Google Scholar 

  64. 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

    Article  CAS  Google Scholar 

  65. 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

    Article  CAS  Google Scholar 

  66. 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

    Article  CAS  Google Scholar 

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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).

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Correspondence to Filip Kolář .

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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

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  • DOI: https://doi.org/10.1007/978-1-0716-2561-3_16

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  • Publisher Name: Humana, New York, NY

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