#PAGE_PARAMS# #ADS_HEAD_SCRIPTS# #MICRODATA#

Inference of past demography, dormancy and self-fertilization rates from whole genome sequence data


Autoři: Thibaut Paul Patrick Sellinger aff001;  Diala Abu Awad aff001;  Markus Moest aff002;  Aurélien Tellier aff001
Působiště autorů: Department of Population Genetics, Technische Universitaet Muenchen, Freising, Germany aff001;  Department of Population Genetics, Technische Universit at M unchen, Freising, Germany aff001;  Department of Ecology, University of Innsbruck, Innsbruck, Austria aff002
Vyšlo v časopise: Inference of past demography, dormancy and self-fertilization rates from whole genome sequence data. PLoS Genet 16(4): e32767. doi:10.1371/journal.pgen.1008698
Kategorie: Research Article
doi: https://doi.org/10.1371/journal.pgen.1008698

Souhrn

Several methods based on the Sequential Markovian coalescence (SMC) have been developed that make use of genome sequence data to uncover population demographic history, which is of interest in its own right and is a key requirement to generate a null model for selection tests. While these methods can be applied to all possible kind of species, the underlying assumptions are sexual reproduction in each generation and non-overlapping generations. However, in many plants, invertebrates, fungi and other taxa, those assumptions are often violated due to different ecological and life history traits, such as self-fertilization or long term dormant structures (seed or egg-banking). We develop a novel SMC-based method to infer 1) the rates/parameters of dormancy and of self-fertilization, and 2) the populations’ past demographic history. Using simulated data sets, we demonstrate the accuracy of our method for a wide range of demographic scenarios and for sequence lengths from one to 30 Mb using four sampled genomes. Finally, we apply our method to a Swedish and a German population of Arabidopsis thaliana demonstrating a selfing rate of ca. 0.87 and the absence of any detectable seed-bank. In contrast, we show that the water flea Daphnia pulex exhibits a long lived egg-bank of three to 18 generations. In conclusion, we here present a novel method to infer accurate demographies and life-history traits for species with selfing and/or seed/egg-banks. Finally, we provide recommendations for the use of SMC-based methods for non-model organisms, highlighting the importance of the per site and the effective ratios of recombination over mutation.

Klíčová slova:

Arabidopsis thaliana – Daphnia – Invertebrate genomics – Plant genomics – Seed germination – Seeds – Sequence analysis – Sexual reproduction


Zdroje

1. Ellegren H, Galtier N. Determinants of genetic diversity. Nature Reviews Genetics. 2016;17(7):422–433. doi: 10.1038/nrg.2016.58 27265362

2. The 1000 Genomes Project Consortium. An integrated map of genetic variation from 1,092 human genomes. Nature. 2012.

3. The 1001 Genomes Consortium. 1,135 Genomes Reveal the Global Pattern of Polymorphism in Arabidopsis thaliana. Cell. 2016.

4. Lynch M, Gutenkunst R, Ackerman M, Spitze K, Ye Z, Maruki T, et al. Population Genomics of Daphnia pulex. Molecular Biology and Evolution. 2017;206(1):315–332.

5. Palkopoulou E, Mallick S, Skoglund P, Enk J, Rohland N, Li H, et al. Complete Genomes Reveal Signatures of Demographic and Genetic Declines in the Woolly Mammoth. Current Biology. 2015;25(10):1395–1400. doi: 10.1016/j.cub.2015.04.007 25913407

6. Yew CW, Lu D, Deng L, Wong LP, Ong RTH, Lu Y, et al. Genomic structure of the native inhabitants of Peninsular Malaysia and North Borneo suggests complex human population history in Southeast Asia. Human Genetics. 2018;137(2):161–173. doi: 10.1007/s00439-018-1869-0 29383489

7. Mattle-Greminger MP, Sonay TB, Nater A, Pybus M, Desai T, de Valles G, et al. Genomes reveal marked differences in the adaptive evolution between orangutan species. Genome Biology. 2018;19. doi: 10.1186/s13059-018-1562-6 30428903

8. Pavlidis P, Jensen JD, Stephan W, Stamatakis A. A Critical Assessment of Storytelling: Gene Ontology Categories and the Importance of Validating Genomic Scans. Molecular Biology and Evolution. 2012;29(10):3237–3248. doi: 10.1093/molbev/mss136 22617950

9. Stephan W. Signatures of positive selection: from selective sweeps at individual loci to subtle allele frequency changes in polygenic adaptation. Molecular Ecology. 2016;25(1, SI):79–88. doi: 10.1111/mec.13288 26108992

10. Terhorst J, Kamm JA, Song YS. Robust and scalable inference of population history froth hundreds of unphased whole genomes. Nature Genetics. 2017;49(2):303–309. doi: 10.1038/ng.3748 28024154

11. Li H, Durbin R. Inference of human population history from individual whole-genome sequences. Nature. 2011;475(7357):493–U84. doi: 10.1038/nature10231 21753753

12. Schiffels S, Durbin R. Inferring human population size and separation history from multiple genome sequences. Nature Genetics. 2014;46(8):919–925. doi: 10.1038/ng.3015 24952747

13. Sheehan S, Harris K, Song YS. Estimating Variable Effective Population Sizes from Multiple Genomes: A Sequentially Markov Conditional Sampling Distribution Approach. Molecular Biology and Evolution. 2013;194(3):647+.

14. Mailund T, Halager AE, Westergaard M, Dutheil JY, Munch K, Andersen LN, et al. New A Isolation with Migration Model along Complete Genomes Infers Very Different Divergence Processes among Closely Related Great Ape Species. PLOS Genetics. 2012;8(12). doi: 10.1371/journal.pgen.1003125 23284294

15. McVean G, Cardin N. Approximating the coalescent with recombination. Philosophical Transactions of the Royal Society B-Biological Sciences. 2005;360(1459):1387–1393.

16. Marjoram P, Wall J. Fast “coalescent” simulation. BMC Genetics. 2006;7. doi: 10.1186/1471-2156-7-16 16539698

17. Wiuf C, Hein J. Recombination as a point process along sequences. Theoretical Population Biology. 1999;55(3):248–259. doi: 10.1006/tpbi.1998.1403 10366550

18. Wiuf C, Hein J. The ancestry of a sample of sequences subject to recombination. Molecular Biology and Evolution. 1999;151(3):1217–1228.

19. Fulgione A, Koornneef M, Roux F, Hermisson J, Hancock AM. Madeiran Arabidopsis thaliana Reveals Ancient Long-Range Colonization and Clarifies Demography in Eurasia. Molecular Biology and Evolution. 2018;35(3):564–574. doi: 10.1093/molbev/msx300 29216397

20. Durvasula A, Fulgione A, Gutaker RM, Alacakaptan SI, Flood PJ, Neto C, et al. African genomes illuminate the early history and transition to selfing in Arabidopsis thaliana. Proceedings of the National Academy of Sciences of the United States of America. 2017;114(20):5213–5218. doi: 10.1073/pnas.1616736114 28473417

21. Brendonck L, De Meester L. Egg banks in freshwater zooplankton: evolutionary and ecological archives in the sediment. Hydrobiologia. 2003;491(1-3):65–84.

22. Evans M, Dennehy J. Germ banking: Bet-hedging and varlable release from egg and seed dormancy. Quarterly Review of Biology. 2005;80(4):431–451. doi: 10.1086/498282 16519139

23. Baskin CC, Baskin JM. Germination Ecology of Seeds in the Persistent Seed Bank. In: Seeds: Ecology, Biogeography, and Evolution of Dormancy and Germination, 2ND EDITION; 2014. p. 187–276.

24. Jarne P, Auld JR. Animals mix it up too: The distribution of self-fertilization among hermaphroditic animals. Evolution. 2006;60(9):1816–1824. doi: 10.1554/06-246.1 17089966

25. Tellier A, Laurent SJY, Lainer H, Pavlidis P, Stephan W. Inference of seed bank parameters in two wild tomato species using ecological and genetic data. Proceedings of the National Academy of Sciences of the United States of America. 2011;108(41):17052–17057. doi: 10.1073/pnas.1111266108 21949404

26. Evans MEK, Ferriere R, Kane MJ, Venable DL. Bet hedging via seed banking in desert evening primroses (Oenothera, Onagraceae): Demographic evidence from natural populations. American Naturalist. 2007;169(2):184–194. doi: 10.1086/510599 17211803

27. Lennon JT, Jones SE. Microbial seed banks: the ecological and evolutionary implications of dormancy. Nature Reviews Microbiology. 2011;9(2):119–130. doi: 10.1038/nrmicro2504 21233850

28. Nunney L. The effective size of annual plant populations: The interaction of a seed bank with fluctuating population size in maintaining genetic variation. American Naturalist. 2002;160(2):195–204. doi: 10.1086/341017 18707486

29. Vitalis R, Glemin S, Olivieri I. When genes go to sleep: The population genetic consequences of seed dormancy and monocarpic perenniality. American Naturalist. 2004;163(2):295–311. doi: 10.1086/381041 14970929

30. Heinrich L, Mueller J, Tellier A, Zivkovic D. Effects of population- and seed bank size fluctuations on neutral evolution and efficacy of natural selection. Theoretical Population Biology. 2018;123:45–69. doi: 10.1016/j.tpb.2018.05.003 29959946

31. Tellier A. Persistent seed banking as eco-evolutionary determinant of plant nucleotide diversity: novel population genetics insights. New Phytologist. 2019;221(2):725–730. doi: 10.1111/nph.15424 30346030

32. Templeton A, Levin D. Evolutionary Consequences of Seed Pools. American Naturalist. 1979;114(2):232–249.

33. Zivkovic D, Tellier A. Germ banks affect the inference of past demographic events. Molecular Ecology. 2012;21(22):5434–5446. doi: 10.1111/mec.12039 23050602

34. Barrett SCH. The evolution of plant reproductive systems: how often are transitions irreversible? Proceedings of the Royal Society B-Biological Sciences. 2013;280 (1765).

35. Barrett Spencer C H and Arunkumar Ramesh and Wright Stephen I. The demography and population genomics of evolutionary transitions to self-fertilization in plants. Philosophical Transactions of the Royal Society B-Biological Sciences. 2014;369 (1648).

36. Abbot R, Gomes M. Population genetic-structure and outcrossing rate of Arabidopsis-thaliana (L) HEYNH. Heredity. 1989;62(3):411–418.

37. Kerdaffrec E, Filiault DL, Korte A, Sasaki E, Nizhynska V, Seren U, et al. Multiple alleles at a single locus control seed dormancy in Swedish Arabidopsis. ELife. 2016;5. doi: 10.7554/eLife.22502 27966430

38. Lundemo S, Falahati-Anbaran M, Stenoien HK. Seed banks cause elevated generation times and effective population sizes of Arabidopsis thaliana in northern Europe (vol 18, pg 2798, 2009). Molecular Ecology. 2010;19(8):1754.

39. Ebert D. Ecology, epidemiology, and evolution of parasitism in Daphnia. Bethesda (MD): National Library of Medicine (US), National Center for Biotechnology Information.; 2005.

40. Alekseev V, Lampert W. Maternal control of resting-egg production in Daphnia. Nature. 2001;414(6866):899–901. doi: 10.1038/414899a 11780060

41. Kaj I, Krone S, Lascoux M. Coalescent theory for seed bank models. Journal of Applied Probability. 2001;38(2):285–300.

42. Nordborg M. Linkage disequilibrium, gene trees and selfing: An ancestral recombination graph with partial self-fertilization. Molecular Biology and Evolution. 2000;154(2):923–929.

43. Mohle M. A convergence theorem for Markov chains arising in population genetics and the coalescent with selfing. Advances in Applied Probability. 1998;30(2):493–512.

44. Ke Wang JOSS Iain Mathieson. Tracking human population structure through time from whole genome sequences. bioRxiv. 2019; https://doi.org/10.1101/585265.

45. Salome PA, Bomblies K, Fitz J, Laitinen RAE, Warthmann N, Yant L, et al. The recombination landscape in Arabidopsis thaliana F-2 populations. Heredity. 2012;108(4):447–455. doi: 10.1038/hdy.2011.95 22072068

46. Tang C, Toomajian C, Sherman-Broyles S, Plagnol V, Guo YL, Hu TT, et al. The evolution of selfing in Arabidopsis thaliana. Science. 2007;317(5841):1070–1072. doi: 10.1126/science.1143153 17656687

47. Hiruta C, Nishida C, Tochinai S. Abortive meiosis in the oogenesis of parthenogenetic Daphnia pulex. Chromosome Research. 2010;18(7):833–840. doi: 10.1007/s10577-010-9159-2 20949314

48. Hiruta C, Tochinai S. Spindle Assembly and Spatial Distribution of gamma-tubulin During Abortive Meiosis and Cleavage Division in the Parthenogenetic Water Flea Daphnia pulex. Zoological Science. 2012;29(11):733–737. doi: 10.2108/zsj.29.733 23106557

49. Palacios JA, Wakeley J, Ramachandran S. Bayesian Nonparametric Inference of Population Size Changes from Sequential Genealogies. Genetics. 2015;201(1):281+. doi: 10.1534/genetics.115.177980 26224734

50. Wakeley J, King L, Wilton PR. Effects of the population pedigree on genetic signatures of historical demographic events. Proceedings of the National Academy of Sciences of the United States of America. 2016;113(29):7994–8001. doi: 10.1073/pnas.1601080113 27432946

51. Cao J, Schneeberger K, Ossowski S, Guenther T, Bender S, Fitz J, et al. Whole-genome sequencing of multiple Arabidopsis thaliana populations. Nature Genetics. 2011;43(10):956–U60. doi: 10.1038/ng.911 21874002

52. Rodriguez W, Mazet O, Grusea S, Arredondo A, Corujo JM, Boitard S, et al. The IICR and the non-stationary structured coalescent: towards demographic inference with arbitrary changes in population structure. Heredity. 2018;121(6):663–678. doi: 10.1038/s41437-018-0148-0 30293985

53. Parag KV, Pybus OG. Robust Design for Coalescent Model Inference. Systematic Biology. 2019;68(5):730–743. doi: 10.1093/sysbio/syz008 30726979

54. Whittle C. The influence of environmental factors, the pollen: ovule ratio and seed bank persistence on molecular evolutionary rates in plants. Journal of Evolutionary Biology. 2006;19(1):302–308. doi: 10.1111/j.1420-9101.2005.00977.x 16405600

55. Dann M SSSH Bellot S, A T. Mutation rates in seeds and seed-banking influence substitution rates across the angiosperm phylogeny. bioRxiv. 2017; https://doi.org/10.1101/156398.

56. Staab PR, Zhu S, Metzler D, Lunter G. scrm: efficiently simulating long sequences using the approximated coalescent with recombination. Bioinformatics. 2015;31(10):1680–1682. doi: 10.1093/bioinformatics/btu861 25596205

57. Ossowski S, Schneeberger K, Lucas-Lledo JI, Warthmann N, Clark RM, Shaw RG, et al. The Rate and Molecular Spectrum of Spontaneous Mutations in Arabidopsis thaliana. Science. 2010;327(5961):92–94. doi: 10.1126/science.1180677 20044577

58. Ye Z, Xu S, Spitze K, Asselman J, Jiang X, Ackerman MS, et al. A New Reference Genome Assembly for the Microcrustacean Daphnia pulex. G3-Genes Genomes Genetics. 2017;7(5):1405–1416.

59. Li H, Durbin R. Fast and accurate short read alignment with Burrows-Wheeler transform. Bioinformatics. 2009;25(14):1754–1760. doi: 10.1093/bioinformatics/btp324 19451168

60. Li H, Handsaker B, Wysoker A, Fennell T, Ruan J, Homer N, et al. The Sequence Alignment/Map format and SAMtools. Bioinformatics. 2009;25(16):2078–2079. doi: 10.1093/bioinformatics/btp352 19505943

61. McKenna A, Hanna M, Banks E, Sivachenko A, Cibulskis K, Kernytsky A, et al. The Genome Analysis Toolkit: A MapReduce framework for analyzing next-generation DNA sequencing data. Genome Research. 2010;20(9):1297–1303. doi: 10.1101/gr.107524.110 20644199

62. Flynn JM, Chain FJJ, Schoen DJ, Cristescu ME. Spontaneous Mutation Accumulation in Daphnia pulex in Selection-Free vs. Competitive Environments. Molecular Biology and Evolution. 2017;34(1):160–173. doi: 10.1093/molbev/msw234 27777284

63. Xu S, Ackerman MS, Long H, Bright L, Spitze K, Ramsdell JS, et al. A Male-Specific Genetic Map of the Microcrustacean Daphnia pulex Based on Single-Sperm Whole-Genome Sequencing. Molecular Biology and Evolution. 2015;201(1):31+.


Článek vyšel v časopise

PLOS Genetics


2020 Číslo 4
Nejčtenější tento týden
Nejčtenější v tomto čísle
Kurzy

Zvyšte si kvalifikaci online z pohodlí domova

Hypertenze a hypercholesterolémie – synergický efekt léčby
nový kurz
Autoři: prof. MUDr. Hana Rosolová, DrSc.

Multidisciplinární zkušenosti u pacientů s diabetem
Autoři: Prof. MUDr. Martin Haluzík, DrSc., prof. MUDr. Vojtěch Melenovský, CSc., prof. MUDr. Vladimír Tesař, DrSc.

Úloha kombinovaných preparátů v léčbě arteriální hypertenze
Autoři: prof. MUDr. Martin Haluzík, DrSc.

Halitóza
Autoři: MUDr. Ladislav Korábek, CSc., MBA

Terapie roztroušené sklerózy v kostce
Autoři: MUDr. Dominika Šťastná, Ph.D.

Všechny kurzy
Přihlášení
Zapomenuté heslo

Zadejte e-mailovou adresu, se kterou jste vytvářel(a) účet, budou Vám na ni zaslány informace k nastavení nového hesla.

Přihlášení

Nemáte účet?  Registrujte se

#ADS_BOTTOM_SCRIPTS#