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A Genome Scan for Genes Underlying Microgeographic-Scale Local Adaptation in a Wild Species


Where does a local adaptation take place? In general, an adaptive divergence is predicted to occur between isolated populations because gene flow will erode and prevent the divergence. Therefore, previous genome-wide studies that aim to find the adaptive genes have compared populations that are usually tens of hundreds of kilometers apart. However, because nearby populations are likely to be genetically connected or connected until recently, most of the genome should be undifferentiated, leaving the genetic footprints of natural selections more pronounced. Thus, if an adaptive divergence is to be found within a small spatial scale, such case may favor the screening for the adaptive genes. Here, we took advantage of a unique small-scale local adaptation in Arabidopsis halleri subsp. gemmifera, where similar phenotypic differentiation is found across an altitudinal cline on two distinct mountains. By scanning the genome with a focus on the presence of unidirectional allele frequency shift along the altitudes, we successfully obtained genes with functions that were in line with the known phenotypic and environmental difference between altitudes. Our approach is applicable to any species that show microgeographic divergence and should help understand the genetic basis of small-scale evolution.


Vyšlo v časopise: A Genome Scan for Genes Underlying Microgeographic-Scale Local Adaptation in a Wild Species. PLoS Genet 11(7): e32767. doi:10.1371/journal.pgen.1005361
Kategorie: Research Article
prolekare.web.journal.doi_sk: https://doi.org/10.1371/journal.pgen.1005361

Souhrn

Where does a local adaptation take place? In general, an adaptive divergence is predicted to occur between isolated populations because gene flow will erode and prevent the divergence. Therefore, previous genome-wide studies that aim to find the adaptive genes have compared populations that are usually tens of hundreds of kilometers apart. However, because nearby populations are likely to be genetically connected or connected until recently, most of the genome should be undifferentiated, leaving the genetic footprints of natural selections more pronounced. Thus, if an adaptive divergence is to be found within a small spatial scale, such case may favor the screening for the adaptive genes. Here, we took advantage of a unique small-scale local adaptation in Arabidopsis halleri subsp. gemmifera, where similar phenotypic differentiation is found across an altitudinal cline on two distinct mountains. By scanning the genome with a focus on the presence of unidirectional allele frequency shift along the altitudes, we successfully obtained genes with functions that were in line with the known phenotypic and environmental difference between altitudes. Our approach is applicable to any species that show microgeographic divergence and should help understand the genetic basis of small-scale evolution.


Zdroje

1. Savolainen O, Lascoux M, Merilä J (2013) Ecological genomics of local adaptation. Nat Rev Genet 14: 807–820. doi: 10.1038/nrg3522 24136507

2. Lewontin RC, Krakauer J (1973) Distribution of gene frequency as a test of the theory of the selective neutrality of polymorphisms. Genetics 74: 175–195. 4711903

3. Endler JA (1986) Natural Selection in the Wild. Princeton: Princeton University Press. 354 p.

4. Thornton KR, Jensen JD, Becquet C, Andolfatto P (2007) Progress and prospects in mapping recent selection in the genome. Heredity 98: 340–348. 17473869

5. Narum SR, Hess JE (2011) Comparison of FST outlier tests for SNP loci under selection. Mol Ecol Res 11: 184–194.

6. De Mita S, Thuillet AC, Gay L, Ahmadi N, Manel S, et al. (2013) Detecting selection along environmental gradients: analysis of eight methods and their effectiveness for outbreeding and selfing populations. Mol Ecol 22: 1383–1399. doi: 10.1111/mec.12182 23294205

7. Barrett RDH, Hoekstra HE (2011) Molecular spandrels: tests of adaptation at the genetic level. Nat Rev Genet 12: 767–780. doi: 10.1038/nrg3015 22005986

8. Skelly DK (2004) Microgeographic countergradient variation in the wood frog, Rana sylvatica. Evolution 58: 160–165. 15058728

9. Antonovics J. (2006) Evolution in closely adjacent plant populations X: long-term persistence of prereproductive isolation at a mine boundary. Heredity 97: 33–37. 16639420

10. Kavanagh KD, Haugen TO, Gregersen F, Jernvall J, Vøllestad LA (2010) Contemporary temperature-driven divergence in a Nordic freshwater fish under conditions commonly thought to hinder adaptation. BMC Evol Biol 10: 350. doi: 10.1186/1471-2148-10-350 21070638

11. Richardson JL, Urban MC (2013) Strong selection barriers explain microgeographic adaptation in wild salamander populations. Evolution 67: 1729–1740. doi: 10.1111/evo.12052 23730765

12. Richardson JL, Urban MC, Bolnick DI, Skelly DK (2014) Microgeographic adaptation and the spatial scale of evolution. Trends Ecol Evol 29: 165–176. doi: 10.1016/j.tree.2014.01.002 24560373

13. Wright S (1969) Evolution and the Genetics of Populations, Volume 2: Theory of Gene Frequencies. Chicago: University of Chicago Press. 520 p.

14. Yeaman S, Whitlock MC (2011) The genetic architecture of adaptation under migration-selection balance. Evolution 65: 1897–1911. doi: 10.1111/j.1558-5646.2011.01269.x 21729046

15. Roda F, Ambrose L, Walter GM, Liu HL, Schaul A, Lowe A, et al. (2013) Genomic evidence for the parallel evolution of coastal forms in the Senecio lautus complex. Mol Ecol 22: 2941–2952. doi: 10.1111/mec.12311 23710896

16. Andrew RL, Rieseberg LH (2013) Divergence is focused on few genomic regions early in speciation: incipient speciation of sunflower ecotypes. Evolution 67–9: 2468–2482.

17. Hara H (1936) Arabis gemmifera var. alpicola. J Jap Bot 12: 900–901.

18. Ikeda H, Setoguchi H, Morinaga S-I (2010) Genomic structure of lowland and highland ecotypes of Arabidopsis halleri subsp. gemmifera (Brassicaceae) on Mt. Ibuki. Acta Phytotax Geobot 61: 21–26.

19. Nagano S (2011) Morphological and physiological adaptation in mountain plants to windy, ultraviolet radiation, and freezing stresses in high altitudes. Ph. D thesis, Tohoku University.

20. Levin DA (1973) The role of trichomes in plant defense. Q Rev Biol 48: 3–15.

21. Kawagoe T, Shimizu KK, Kakutani T, Kudoh H (2011) Coexistence of trichome variation in a natural plant population: A combined study using ecological and candidate gene approaches. PLoS ONE 6: e22184. doi: 10.1371/journal.pone.0022184 21811571

22. Küpper H, Lombi E, Zhao F-J, McGrath SP (2000) Cellular compartmentation of cadmium and zinc in relation to other elements in the hyperaccumulator Arabidopsis halleri. Planta 212: 75–84. 11219586

23. Rada F, Goldstein G, Azócar A, Meinzer F (1985) Freezing avoidance in Andean giant rosette plants. Plant Cell Environ 8: 501–507.

24. Woolley JT (1964) Water relations of soybean leaf hairs. Agron J 56: 569–571.

25. Karabourniotis G, Kotsabassidis D, Manetas Y (1995) Trichome density and its protective potential against ultraviolet-B radiation damage during leaf development. Can J Bot 73: 376–383.

26. Turner TL, Bourne EC, Von Wettberg EJ, Hu TT, Nuzhdin SV (2010) Population resequencing reveals local adaptation of Arabidopsis lyrata to serpentine soils. Nat Genet 42: 260–263. doi: 10.1038/ng.515 20101244

27. Hancock AM, Brachi B, Faure N, Horton MW, Jarymowycz LB, et al. (2011) Adaptation to climate across the Arabidopsis thaliana genome. Science 334: 83–86. doi: 10.1126/science.1209244 21980108

28. Fournier-Level A, Korte A, Cooper MD, Nordborg M, Schmitt J, et al. (2011) A map of local adaptation in Arabidopsis thaliana. Science 334: 86–89. doi: 10.1126/science.1209271 21980109

29. Fischer MC, Rellstab C, Tedder A, Zoller S, Gugerli F, et al. (2013) Population genomic footprints of selection and association with climate in natural populations of Arabidopsis halleri from the Alps. Mol Ecol 22: 5594–5607. doi: 10.1111/mec.12521 24102711

30. Barton NH (1999) Clines in polygenic traits. Genet Res 74: 223–236. 10689800

31. Bridle JR, Polechová J, Kawata M, Bultin RK (2010) Why is adaptation prevented at ecological margins? Ecol Lett 13: 485–494. doi: 10.1111/j.1461-0248.2010.01442.x 20455923

32. Johnston JS, Pepper AE, Hall AE, Chen ZJ, Hodnett G, et al. (2005). Evolution of genome size in Brassicaceae. Ann Bot 95: 229–235. 15596470

33. Hu TT, Pattyn P, Bakker EG, Cao J, Cheng J-F, et al. (2011). The Arabidopsis lyrata genome sequence and the basis of rapid genome size change. Nat Genet 43: 476–481. doi: 10.1038/ng.807 21478890

34. Pritchard JK, Stephens M, Donnelly P (2000) Inference of population structure using multilocus genotype data. Genetics 155: 945–959. 10835412

35. Falush D, Stephens M, Pritchard JK (2003) Inference of population structure: Extensions to linked loci and correlated allele frequencies. Genetics 164: 1567–1587. 12930761

36. Evanno G, Regnaut S, Goudet J (2005) Detecting the number of clusters of individuals using the software structure: a simulation study. Mol Ecol 14: 2611–2620. 15969739

37. Kimura M, Weiss GH (1964) The stepping stone model of population structure and the decrease of genetic correlation with distance. Genetics 49: 561–576. 17248204

38. Pickrell JK, Pritchard JK (2012) Inference of population splits and mixtures from genome-wide allele frequency data. PLoS Genet 8: e1002967. doi: 10.1371/journal.pgen.1002967 23166502

39. Hedrick PW (2005) A standardized genetic differentiation measure. Evolution 59: 1633–1638. 16329237

40. Storey JD, Tibshirani R (2003) Statistical significance for genomewide studies. Proc Natl Acad Sci USA 100: 9440–9445. 12883005

41. Kofler R, Schlötterer C (2012) Gowinda: unbiased analysis of gene set enrichment for genome-wide association studies. Bioinformatics 28: 2084–2085. doi: 10.1093/bioinformatics/bts315 22635606

42. Weng L, Macciardi F, Subramanian A, Guffanti G, Potkin SG, et al. (2011) SNP-based pathway enrichment analysis for genome-wide association studies. BMC Bioinformatics 12: 99. doi: 10.1186/1471-2105-12-99 21496265

43. Huang DW, Sherman BT, Lempicki RA (2009) Bioinformatics enrichment tools: paths toward the comprehensive functional analysis of large gene lists. Nucleic Acids Res. 37: 1–13. doi: 10.1093/nar/gkn923 19033363

44. Foll M, Gaggiotti O (2008) A genome scan method to identify selected loci appropriate for both dominant and codominant markers: a Bayesian perspective. Genetics 180: 977–993. doi: 10.1534/genetics.108.092221 18780740

45. Foll M, Fischer MC, Heckel G, Excoffier L (2010) Estimating population structure from AFLP amplification intensity. Mol Ecol 19: 4638–4647. doi: 10.1111/j.1365-294X.2010.04820.x 20874760

46. Fischer MC, Foll M, Excoffier L, Heckel G (2011) Enhanced AFLP genome scans detect local adaptation in high-altitude populations of a small rodent (Microtus arvalis). Mol Ecol 20: 1450–1462. doi: 10.1111/j.1365-294X.2011.05015.x 21352386

47. 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. doi: 10.1093/molbev/mst063 23543094

48. Maynard Smith J, Haigh J (1974) The hitch-hiking effect of a favorable gene. Genet Res 23: 23–25. 4407212

49. Yeaman S (2013) Genomic rearrangements and the evolution of clusters of locally adaptive loci. Proc Natl Acad Sci USA 110: E1743–E1751. doi: 10.1073/pnas.1219381110 23610436

50. Heyndrickx KS, Vandepoele K (2012) Systematic identification of functional plant modules through the integration of complementary data sources. Plant Physiol 159: 884–901. doi: 10.1104/pp.112.196725 22589469

51. Franzmann LH, Yoon ES, Meinke DW (1995) Saturating the genetic map of Arabidopsis thaliana with embryonic mutations. Plant J 7: 341–350.

52. Indorf M, Cordero J, Neuhaus G, Rodríguez-Franco M (2007) Salt tolerance (STO), a stress-related protein, has a major role in light signalling. Plant J 51: 563–574. 17605755

53. Gaxiola RA, Li J, Undurraga S, Dang LM, Allen GJ, et al. (2001) Drought- and salt-tolerant plants result from overexpression of the AVP1 H+-pump. Proc Natl Acad Sci USA 25: 11444–11449.

54. Li YF, Costello JC, Holloway AK, Hahn MW (2008) “Reverse ecology” and the power of population genomics. Evolution 62: 2984–2994. doi: 10.1111/j.1558-5646.2008.00486.x 18752601

55. Töller A, Brownfield L, Neu C, Twell D, Schulze-Lefert P (2008) Dual function of Arabidopsis glucan synthase-like genes GSL8 and GSL10 in male gametophyte development and plant growth. Plant J 54: 911–923. doi: 10.1111/j.1365-313X.2008.03462.x 18315544

56. Jiang Y, Yang B, Harris NS, Deyholos MK (2007) Comparative proteomic analysis of NaCl stress-responsive proteins in Arabidopsis roots. J Exp Bot 58: 3591–3607. 17916636

57. Fukao Y, Ferjani A, Fujiwara M, Nishimori Y, Ohtsu I (2009) Identification of Zinc-responsive proteins in the roots of Arabidopsis thaliana using highly improved method of two-dimensional electrophoresis. Plant Cell Physiol 50: 2234–2239. doi: 10.1093/pcp/pcp154 19880396

58. Chen I-P, Haehnel U, Altschmied L, Schubert I, Puchta H (2003) The transcriptional response of Arabidopsis to genotoxic stress–a high-density colony array study (HDCA). Plant J 35: 771–786. 12969430

59. Dixon DP, Skipsey M, Grundy NM, Edwards R (2005) Stress-induced protein S-Glutathionylation in Arabidopsis. Plant Physiol 138: 2233–2244. 16055689

60. Ascencio-Ibáñez JT, Sozzani R, Lee T-L, Chu T-M, Wolfinger RD, et al. (2008) Global analysis of Arabidopsis gene expression uncovers a complex array of changes impacting pathogen response and cell cycle during geminivirus infection. Plant Physiol 148: 436–454. doi: 10.1104/pp.108.121038 18650403

61. Hastugai N, Iwasaki S, Tamura K, Kondo M, Fuji K, et al. (2009) A novel membrane fusion-mediated plant immunity against bacterial pathogens. Genes Dev 23: 2496–2506. doi: 10.1101/gad.1825209 19833761

62. Kawecki TJ, Ebert D (2004) Conceptual issues in local adaptation. Ecol Lett 7: 1225–1241.

63. Hall MC, Lwory DB, Willis JH (2010) Is local adaptation in Mimulus guttatus caused by trade-offs at individual loci? Mol Ecol 19: 2739–2753. doi: 10.1111/j.1365-294X.2010.04680.x 20546131

64. Kirkpatrick M, Barton N (2006) Chromosome inversions, local adaptation and speciation. Genetics 173:419–434. 16204214

65. Alberto FJ, Derory J, Boury C, Frigerio J-M, Zimmermann NE, et al. (2013) Imprints of natural selection along environmental gradients in phenology-related genes of Quercus petraea. Genetics 195: 495–512. doi: 10.1534/genetics.113.153783 23934884

66. Al-Shehbaz IA, O’Kane SL Jr (2002) Taxonomy and phylogeny of Arabidopsis (Brassicaseae). In: Somerville CR, Meyerowitz EM, editors. The Arabidopsis Book. Rockville MD: American Society of Plant Biologists. http://www.aspb.org/publications/arabidopsis. Accessed 30 October 2014.

67. Rosenberg NA (2004) Distruct: a program for the graphical display of population structure. Mol Ecol Notes 4: 137–138.

68. Fisher RA (1922) On the interpretation of χ2 from contingency tables, and the calculation of P. J Royal Stat Soc 85: 87–94.

69. Fisher RA (1954) Statistical methods for research workers. London: Oliver and Boyd. 356 p.

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