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Unique genetic signatures of local adaptation over space and time for diapause, an ecologically relevant complex trait, in Drosophila melanogaster


Autoři: Priscilla A. Erickson aff001;  Cory A. Weller aff001;  Daniel Y. Song aff001;  Alyssa S. Bangerter aff001;  Paul Schmidt aff002;  Alan O. Bergland aff001
Působiště autorů: Department of Biology, University of Virginia, Charlottesville, Virginia, United States of America aff001;  Department of Biology, University of Pennsylvania, Philadelphia, Pennsylvania, United States of America aff002
Vyšlo v časopise: Unique genetic signatures of local adaptation over space and time for diapause, an ecologically relevant complex trait, in Drosophila melanogaster. PLoS Genet 16(11): e1009110. doi:10.1371/journal.pgen.1009110
Kategorie: Research Article
doi: https://doi.org/10.1371/journal.pgen.1009110

Souhrn

Organisms living in seasonally variable environments utilize cues such as light and temperature to induce plastic responses, enabling them to exploit favorable seasons and avoid unfavorable ones. Local adapation can result in variation in seasonal responses, but the genetic basis and evolutionary history of this variation remains elusive. Many insects, including Drosophila melanogaster, are able to undergo an arrest of reproductive development (diapause) in response to unfavorable conditions. In D. melanogaster, the ability to diapause is more common in high latitude populations, where flies endure harsher winters, and in the spring, reflecting differential survivorship of overwintering populations. Using a novel hybrid swarm-based genome wide association study, we examined the genetic basis and evolutionary history of ovarian diapause. We exposed outbred females to different temperatures and day lengths, characterized ovarian development for over 2800 flies, and reconstructed their complete, phased genomes. We found that diapause, scored at two different developmental cutoffs, has modest heritability, and we identified hundreds of SNPs associated with each of the two phenotypes. Alleles associated with one of the diapause phenotypes tend to be more common at higher latitudes, but these alleles do not show predictable seasonal variation. The collective signal of many small-effect, clinally varying SNPs can plausibly explain latitudinal variation in diapause seen in North America. Alleles associated with diapause are segregating in Zambia, suggesting that variation in diapause relies on ancestral polymorphisms, and both pro- and anti-diapause alleles have experienced selection in North America. Finally, we utilized outdoor mesocosms to track diapause under natural conditions. We found that hybrid swarms reared outdoors evolved increased propensity for diapause in late fall, whereas indoor control populations experienced no such change. Our results indicate that diapause is a complex, quantitative trait with different evolutionary patterns across time and space.

Klíčová slova:

Diapause – Drosophila melanogaster – Gene mapping – Genome-wide association studies – Permutation – Population genetics – Seasons – Single nucleotide polymorphisms


Zdroje

1. Kawecki TJ, Ebert D. Conceptual issues in local adaptation. Ecol Lett. 2004;7:1225–1241. doi: 10.1111/j.1461-0248.2004.00684.x

2. Paul MJ, Zucker Irving, Schwartz William J. Tracking the seasons: the internal calendars of vertebrates. Philos Trans R Soc B Biol Sci. 2008;363:341–361. doi: 10.1098/rstb.2007.2143 17686736

3. Andrés F, Coupland G. The genetic basis of flowering responses to seasonal cues. Nat Rev Genet. 2012;13:627–639. doi: 10.1038/nrg3291 22898651

4. Denlinger DL, Hahn DA, Merlin C, Holzapfel CM, Bradshaw WE. Keeping time without a spine: what can the insect clock teach us about seasonal adaptation? Phil Trans R Soc B. 2017;372:20160257. doi: 10.1098/rstb.2016.0257 28993500

5. Moran NA. The Evolution of Aphid Life Cycles. Annu Rev Entomol. 1992;37:321–348. doi: 10.1146/annurev.en.37.010192.001541

6. Nijhout HF. Development and evolution of adaptive polyphenisms. Evol Dev. 2003;5:9–18. doi: 10.1046/j.1525-142x.2003.03003.x 12492404

7. Canard M. Seasonal adaptations of green lacewings (Neuroptera: Chrysopidae). Eur J Entomol Ceske Budejovice. 2005;102:317.

8. Urquhart FA, Urquhart NR. Autumnal migration routes of the eastern population of the monarch butterfly (Danaus p. plexippus L.; Danaidae; Lepidoptera) in North America to the overwintering site in the Neovolcanic Plateau of Mexico. Can J Zool. 1978;56:1759–1764. doi: 10.1139/z78-240

9. Tauber MJ, Tauber CA, Masaki S. Seasonal Adaptations of Insects. Oxford University Press; 1986.

10. Denlinger DL. Regulation of Diapause. Annu Rev Entomol. 2002;47:93–122. doi: 10.1146/annurev.ento.47.091201.145137 11729070

11. Koštál V. Eco-physiological phases of insect diapause. J Insect Physiol. 2006;52:113–127. doi: 10.1016/j.jinsphys.2005.09.008 16332347

12. Schmidt P. Evolution and mechanisms of insect reproductive diapause: a plastic and pleiotropic life history syndrome. Mechanisms of Life History Evolution: The Genetics and Physiology of Life History Traits and Trade-Offs. 2011. pp. 221–229.

13. Tougeron K. Diapause research in insects: historical review and recent work perspectives. Entomol Exp Appl. 2019;167:27–36. doi: 10.1111/eea.12753

14. Bradshaw WE, Armbruster PA, Holzapfel CM. Fitness Consequences of Hibernal Diapause in the Pitcher-Plant Mosquito, Wyeomyia Smithii. Ecology. 1998;79:1458–1462.

15. Schmidt PS, Paaby AB, Heschel MS. Genetic variance for diapause expression and associated life histories in Drosophila melanogaster. Evolution. 2005;59:2616–2625. 16526509

16. Chen C, Xia Q-W, Xiao H-J, Xiao L, Xue F-S. A comparison of the life-history traits between diapause and direct development individuals in the cotton bollworm, Helicoverpa armigera. J Insect Sci. 2014;14. doi: 10.1093/jis/14.1.19 25373166

17. Bradshaw WE, Lounibos LP. Evolution of Dormancy and Its Photoperiodic Control in Pitcher-Plant Mosquitoes. Evolution. 1977;31:546–567. 28563474

18. Schmidt PS, Matzkin L, Ippolito M, Eanes WF. Geographic Variation in Diapause Incidence, Life-History Traits, and Climatic Adaptation in Drosophila Melanogaster. Evolution. 2005;59:1721–1732. doi: 10.1111/j.0014-3820.2005.tb01821.x 16331839

19. Schmidt PS, Conde DR. Environmental Heterogeneity and the Maintenance of Genetic Variation for Reproductive Diapause in Drosophila Melanogaster. Evolution. 2006;60:1602–1611. doi: 10.1111/j.0014-3820.2006.tb00505.x 17017061

20. Paolucci S, van de Zande L, Beukeboom LW. Adaptive latitudinal cline of photoperiodic diapause induction in the parasitoid Nasonia vitripennis in Europe. J Evol Biol. 2013;26:705–718. doi: 10.1111/jeb.12113 23496837

21. Posledovich D, Toftegaard T, Wiklund C, Ehrlén J, Gotthard K. Latitudinal variation in diapause duration and post-winter development in two pierid butterflies in relation to phenological specialization. Oecologia. 2015;177:181–190. doi: 10.1007/s00442-014-3125-1 25362581

22. Lehmann P, Lyytinen A, Piiroinen S, Lindström L. Latitudinal differences in diapause related photoperiodic responses of European Colorado potato beetles (Leptinotarsa decemlineata). Evol Ecol. 2015;29:269–282. doi: 10.1007/s10682-015-9755-x

23. Klepsatel P, Gáliková M, Maio ND, Ricci S, Schlötterer C, Flatt T. Reproductive and post-reproductive life history of wild-caught Drosophila melanogaster under laboratory conditions. J Evol Biol. 2013;26:1508–1520. doi: 10.1111/jeb.12155 23675912

24. Saunders DS, Henrich VC, Gilbert LI. Induction of diapause in Drosophila melanogaster: photoperiodic regulation and the impact of arrhythmic clock mutations on time measurement. Proc Natl Acad Sci U S A. 1989;86:3748–3752. doi: 10.1073/pnas.86.10.3748 2498875

25. Saunders DS, Richard DS, Applebaum SW, Ma M, Gilbert LI. Photoperiodic diapause in Drosophila melanogaster involves a block to the juvenile hormone regulation of ovarian maturation. Gen Comp Endocrinol. 1990;79:174–184. doi: 10.1016/0016-6480(90)90102-r 2118114

26. Saunders DS. Insect Clocks, Third Edition. Elsevier; 2002.

27. Williams KD, Busto M, Suster ML, So AK-C, Ben-Shahar Y, Leevers SJ, et al. Natural variation in Drosophila melanogaster diapause due to the insulin-regulated PI3-kinase. Proc Natl Acad Sci. 2006;103:15911–15915. doi: 10.1073/pnas.0604592103 17043223

28. Liu Y, Liao S, Veenstra JA, Nässel DR. Drosophila insulin-like peptide 1 (DILP1) is transiently expressed during non-feeding stages and reproductive dormancy. Sci Rep. 2016;6:26620. doi: 10.1038/srep26620 27197757

29. Schiesari L, Andreatta G, Kyriacou CP, O’Connor MB, Costa R. The Insulin-Like Proteins dILPs-2/5 Determine Diapause Inducibility in Drosophila. PLOS ONE. 2016;11:e0163680. doi: 10.1371/journal.pone.0163680 27689881

30. Richard DS, Jones JM, Barbarito MR, Stacy Cerula, Detweiler JP, Fisher SJ, et al. Vitellogenesis in diapausing and mutant Drosophila melanogaster: further evidence for the relative roles of ecdysteroids and juvenile hormones. J Insect Physiol. 2001;47:905–913. doi: 10.1016/S0022-1910(01)00063-4

31. Richard DS, Rybczynski R, Wilson TG, Wang Y, Wayne ML, Zhou Y, et al. Insulin signaling is necessary for vitellogenesis in Drosophila melanogaster independent of the roles of juvenile hormone and ecdysteroids: female sterility of the chico1 insulin signaling mutation is autonomous to the ovary. J Insect Physiol. 2005;51:455–464. doi: 10.1016/j.jinsphys.2004.12.013 15890189

32. Gilbert LI, Serafin RB, Watkins NL, Richard DS. Ecdysteroids regulate yolk protein uptake by Drosophila melanogaster oocytes. J Insect Physiol. 1998;44:637–644. doi: 10.1016/s0022-1910(98)00020-1 12769946

33. Andreatta G, Kyriacou CP, Flatt T, Costa R. Aminergic Signaling Controls Ovarian Dormancy in Drosophila. Sci Rep. 2018;8:2030. doi: 10.1038/s41598-018-20407-z 29391447

34. Kubrak OI, Kučerová L, Theopold U, Nässel DR. The Sleeping Beauty: How Reproductive Diapause Affects Hormone Signaling, Metabolism, Immune Response and Somatic Maintenance in Drosophila melanogaster. PLOS ONE. 2014;9:e113051. doi: 10.1371/journal.pone.0113051 25393614

35. Lirakis M, Dolezal M, Schlötterer C. Redefining reproductive dormancy in Drosophila as a general stress response to cold temperatures. J Insect Physiol. 2018;107:175–185. doi: 10.1016/j.jinsphys.2018.04.006 29649483

36. Ojima N, Hara Y, Ito H, Yamamoto D. Genetic dissection of stress-induced reproductive arrest in Drosophila melanogaster females. PLOS Genet. 2018;14:e1007434. doi: 10.1371/journal.pgen.1007434 29889831

37. Zhao X, Bergland AO, Behrman EL, Gregory BD, Petrov DA, Schmidt PS. Global transcriptional profiling of diapause and climatic adaptation in Drosophila melanogaster. Mol Biol Evol. 2015;msv263. doi: 10.1093/molbev/msv263 26568616

38. Kučerová L, Kubrak OI, Bengtsson JM, Strnad H, Nylin S, Theopold U, et al. Slowed aging during reproductive dormancy is reflected in genome-wide transcriptome changes in Drosophila melanogaster. BMC Genomics. 2016;17:50. doi: 10.1186/s12864-016-2383-1 26758761

39. Ragland GJ, Keep E. Comparative transcriptomics support evolutionary convergence of diapause responses across Insecta. Physiol Entomol. 2017; n/a–n/a. doi: 10.1111/phen.12193

40. Parker DJ, Ritchie MG, Kankare M. Preparing for Winter: The Transcriptomic Response Associated with Different Day Lengths in Drosophila montana. G3 Genes Genomes Genet. 2016;6:1373–1381. doi: 10.1534/g3.116.027870 26976440

41. Kankare M, Parker DJ, Merisalo M, Salminen TS, Hoikkala A. Transcriptional Differences between Diapausing and Non-Diapausing D. montana Females Reared under the Same Photoperiod and Temperature. PLOS ONE. 2016;11:e0161852. doi: 10.1371/journal.pone.0161852 27571415

42. Zhai Y, Dong X, Gao H, Chen H, Yang P, Li P, et al. Quantitative Proteomic and Transcriptomic Analyses of Metabolic Regulation of Adult Reproductive Diapause in Drosophila suzukii (Diptera: Drosophilidae) Females. Front Physiol. 2019;10. doi: 10.3389/fphys.2019.00344 31019467

43. Kubrak OI, Kučerová L, Theopold U, Nylin S, Nässel DR. Characterization of Reproductive Dormancy in Male Drosophila melanogaster. Front Physiol. 2016;7. doi: 10.3389/fphys.2016.00572 27932997

44. Izquierdo JI. How does Drosophila melanogaster overwinter? Entomol Exp Appl. 1991;59:51–58. doi: 10.1111/j.1570-7458.1991.tb01485.x

45. Machado HE, Bergland AO, O’Brien KR, Behrman EL, Schmidt PS, Petrov DA. Comparative population genomics of latitudinal variation in Drosophila simulans and Drosophila melanogaster. Mol Ecol. 2016;25:723–740. doi: 10.1111/mec.13446 26523848

46. Ohtsu T, Kimura MT, Hori SH. Energy storage during reproductive diapause in the Drosophila melanogaster species group. J Comp Physiol B. 1992;162:203–208. doi: 10.1007/BF00357524 1613157

47. Higuchi C, Kimura MT. Influence of photoperiod on low temperature acclimation for cold-hardiness in Drosophila auraria. Physiol Entomol. 1985;10:303–308. doi: 10.1111/j.1365-3032.1985.tb00051.x

48. Lumme J, Oikarinen A. The genetic basis of the geographically variable photoperiodic diapause in Drosophila littoralis. Hereditas. 1977;86:129–141. doi: 10.1111/j.1601-5223.1977.tb01221.x

49. Lumme J. Phenology and Photoperiodic Diapause in Northern Populations of Drosophila. In: Dingle H, editor. Evolution of Insect Migration and Diapause. New York, NY: Springer US; 1978. pp. 145–170. doi: 10.1007/978-1-4615-6941-1_7

50. Reis M, Valer FB, Vieira CP, Vieira J. Drosophila americana Diapausing Females Show Features Typical of Young Flies. PLOS ONE. 2015;10:e0138758. doi: 10.1371/journal.pone.0138758 26398836

51. Tyukmaeva VI, Salminen TS, Kankare M, Knott KE, Hoikkala A. Adaptation to a seasonally varying environment: a strong latitudinal cline in reproductive diapause combined with high gene flow in Drosophila montana. Ecol Evol. 2011;1: 160–168. doi: 10.1002/ece3.14 22393492

52. Schmidt PS, Zhu C-T, Das J, Batavia M, Yang L, Eanes WF. An amino acid polymorphism in the couch potato gene forms the basis for climatic adaptation in Drosophila melanogaster. Proc Natl Acad Sci U S A. 2008;105:16207–16211. doi: 10.1073/pnas.0805485105 18852464

53. Bergland AO, Behrman EL, O’Brien KR, Schmidt PS, Petrov DA. Genomic Evidence of Rapid and Stable Adaptive Oscillations over Seasonal Time Scales in Drosophila. PLoS Genet. 2014;10:e1004775. doi: 10.1371/journal.pgen.1004775 25375361

54. Cogni R, Kuczynski C, Koury S, Lavington E, Behrman EL, O’Brien KR, et al. The intensity of selection acting on the couch potato gene—spatial-temporal variation in a diapause cline. Evol Int J Org Evol. 2014;68:538–548. doi: 10.1111/evo.12291 24303812

55. Pool JE. The Mosaic Ancestry of the Drosophila Genetic Reference Panel and the D. melanogaster Reference Genome Reveals a Network of Epistatic Fitness Interactions. Mol Biol Evol. 2015;32:3236–3251. doi: 10.1093/molbev/msv194 26354524

56. Hsu S-K, Jakšić AM, Nolte V, Lirakis M, Kofler R, Barghi N, et al. Rapid sex-specific adaptation to high temperature in Drosophila. Tautz D, Ebert D, Reisser C, editors. eLife. 2020;9:e53237. doi: 10.7554/eLife.53237 32083552

57. Lankinen P, Tyukmaeva VI, Hoikkala A. Northern Drosophila montana flies show variation both within and between cline populations in the critical day length evoking reproductive diapause. J Insect Physiol. 2013;59:745–751. doi: 10.1016/j.jinsphys.2013.05.006 23702203

58. Kimura MT. Quantitative response to photoperiod during reproductive diapause in the Drosophila auraria species-complex. J Insect Physiol. 1990;36:147–152. doi: 10.1016/0022-1910(90)90115-V

59. Tatar M, Chien SA, Priest NK. Negligible Senescence during Reproductive Dormancy in Drosophila melanogaster. Am Nat. 2001;158:248–258. doi: 10.1086/321320 18707322

60. Tauber E, Zordan M, Sandrelli F, Pegoraro M, Osterwalder N, Breda C, et al. Natural Selection Favors a Newly Derived timeless Allele in Drosophila melanogaster. Science. 2007;316:1895–1898. doi: 10.1126/science.1138412 17600215

61. Levins R. Evolution in Changing Environments: Some Theoretical Explorations. Princeton University Press; 1968.

62. Ragland GJ, Armbruster PA, Meuti ME. Evolutionary and functional genetics of insect diapause: a call for greater integration. Curr Opin Insect Sci. 2019;36:74–81. doi: 10.1016/j.cois.2019.08.003 31539788

63. Weller CA, Bergland AO. Accurate, ultra-low coverage genome reconstruction and association studies in Hybrid Swarm mapping populations. bioRxiv. 2019; 671925. doi: 10.1101/671925

64. Becker R, Wilks A, Brownrigg R, Minka T, Deckmyn A. maps: Draw Geographical Maps. 2018. https://CRAN.R-project.org/package=maps

65. Middleton CA, Nongthomba U, Parry K, Sweeney ST, Sparrow JC, Elliott CJ. Neuromuscular organization and aminergic modulation of contractions in the Drosophila ovary. BMC Biol. 2006;4:17. doi: 10.1186/1741-7007-4-17 16768790

66. King RC. Ovarian development in Drosophila melanogaster. Academic Press; 1970.

67. Lee SF, Sgrò CM, Shirriffs J, Wee CW, Rako L, van Heerwaarden B, et al. Polymorphism in the couch potato gene clines in eastern Australia but is not associated with ovarian dormancy in Drosophila melanogaster. Mol Ecol. 2011;20:2973–2984. doi: 10.1111/j.1365-294X.2011.05155.x 21689187

68. Soller M, Bownes M, Kubli E. Mating and sex peptide stimulate the accumulation of yolk in oocytes of Drosophila melanogaster. Eur J Biochem. 1997;243:732–738. doi: 10.1111/j.1432-1033.1997.00732.x 9057839

69. Soller M, Bownes M, Kubli E. Control of oocyte maturation in sexually mature Drosophila females. Dev Biol. 1999;208:337–351. doi: 10.1006/dbio.1999.9210 10191049

70. Mirth CK, Nogueira Alves A, Piper MD. Turning food into eggs: insights from nutritional biology and developmental physiology of Drosophila. Curr Opin Insect Sci. 2019;31:49–57. doi: 10.1016/j.cois.2018.08.006 31109673

71. Listgarten J, Lippert C, Kadie CM, Davidson RI, Eskin E, Heckerman D. Improved linear mixed models for genome-wide association studies. Nat Methods. 2012;9:525–526. doi: 10.1038/nmeth.2037 22669648

72. Widmer C, Lippert C, Weissbrod O, Fusi N, Kadie C, Davidson R, et al. Further Improvements to Linear Mixed Models for Genome-Wide Association Studies. Sci Rep. 2014;4:6874. doi: 10.1038/srep06874 25387525

73. Yang J, Lee SH, Goddard ME, Visscher PM. GCTA: a tool for genome-wide complex trait analysis. Am J Hum Genet. 2011;88:76–82. doi: 10.1016/j.ajhg.2010.11.011 21167468

74. Yang J, Benyamin B, McEvoy BP, Gordon S, Henders AK, Nyholt DR, et al. Common SNPs explain a large proportion of the heritability for human height. Nat Genet. 2010;42:565–569. doi: 10.1038/ng.608 20562875

75. Tibshirani R. Regression Shrinkage and Selection via the Lasso. J R Stat Soc Ser B Methodol. 1996;58:267–288.

76. Wu TT, Chen YF, Hastie T, Sobel E, Lange K. Genome-wide association analysis by lasso penalized logistic regression. Bioinformatics. 2009;25:714–721. doi: 10.1093/bioinformatics/btp041 19176549

77. Sing T, Sander O, Beerenwinkel N, Lengauer T. ROCR: visualizing classifier performance in R. Bioinformatics. 2005;21:3940–3941. doi: 10.1093/bioinformatics/bti623 16096348

78. Sandrelli F, Tauber E, Pegoraro M, Mazzotta G, Cisotto P, Landskron J, et al. A Molecular Basis for Natural Selection at the timeless Locus in Drosophila melanogaster. Science. 2007;316:1898–1900. doi: 10.1126/science.1138426 17600216

79. Mackay TFC, Richards S, Stone EA, Barbadilla A, Ayroles JF, Zhu D, et al. The Drosophila melanogaster Genetic Reference Panel. Nature. 2012;482:173–178. doi: 10.1038/nature10811 22318601

80. Machado HE, Bergland AO, Taylor R, Tilk S, Behrman E, Dyer K, et al. Broad geographic sampling reveals predictable and pervasive seasonal adaptation in Drosophila. bioRxiv. 2019;337543. doi: 10.1101/337543

81. Berg JJ, Coop G. A Population Genetic Signal of Polygenic Adaptation. PLOS Genet. 2014;10:e1004412. doi: 10.1371/journal.pgen.1004412 25102153

82. Beissinger T, Kruppa J, Cavero D, Ha N-T, Erbe M, Simianer H. A Simple Test Identifies Selection on Complex Traits. Genetics. 2018;209:321–333. doi: 10.1534/genetics.118.300857 29545467

83. Pais IS, Valente RS, Sporniak M, Teixeira L. Drosophila melanogaster establishes a species-specific mutualistic interaction with stable gut-colonizing bacteria. PLOS Biol. 2018;16:e2005710. doi: 10.1371/journal.pbio.2005710 29975680

84. Stone HM, Erickson PA, Bergland AO. Phenotypic plasticity, but not adaptive tracking, underlies seasonal variation in post-cold hardening freeze tolerance of Drosophila melanogaster. Ecol Evol. 2020;10:217–231. doi: 10.1002/ece3.5887 31988724

85. Drummond-Barbosa D, Spradling AC. Stem Cells and Their Progeny Respond to Nutritional Changes during Drosophila Oogenesis. Dev Biol. 2001;231:265–278. doi: 10.1006/dbio.2000.0135 11180967

86. Terashima J, Bownes M. Translating Available Food Into the Number of Eggs Laid by Drosophila melanogaster. Genetics. 2004;167:1711–1719. doi: 10.1534/genetics.103.024323 15342510

87. Terashima J, Takaki K, Sakurai S, Bownes M. Nutritional status affects 20-hydroxyecdysone concentration and progression of oogenesis in Drosophila melanogaster. J Endocrinol. 2005;187:69–79. doi: 10.1677/joe.1.06220 16214942

88. Lee KP, Simpson SJ, Clissold FJ, Brooks R, Ballard JWO, Taylor PW, et al. Lifespan and reproduction in Drosophila: New insights from nutritional geometry. Proc Natl Acad Sci. 2008;105:2498–2503. doi: 10.1073/pnas.0710787105 18268352

89. Fabian DK, Lack JB, Mathur V, Schlötterer C, Schmidt PS, Pool JE, et al. Spatially varying selection shapes life history clines among populations of Drosophila melanogaster from sub-Saharan Africa. J Evol Biol. 2015;28:826–840. doi: 10.1111/jeb.12607 25704153

90. Zonato V, Collins L, Pegoraro M, Tauber E, Kyriacou CP. Is diapause an ancient adaptation in Drosophila? J Insect Physiol. 2017;98:267–274. doi: 10.1016/j.jinsphys.2017.01.017 28161445

91. Lack JB, Cardeno CM, Crepeau MW, Taylor W, Corbett-Detig RB, Stevens KA, et al. The Drosophila Genome Nexus: A Population Genomic Resource of 623 Drosophila melanogaster Genomes, Including 197 from a Single Ancestral Range Population. Genetics. 2015;199:1229–1241. doi: 10.1534/genetics.115.174664 25631317

92. Lack JB, Lange JD, Tang AD, Corbett-Detig RB, Pool JE. A Thousand Fly Genomes: An Expanded Drosophila Genome Nexus. Mol Biol Evol. 2016;msw195. doi: 10.1093/molbev/msw195 27687565

93. Voight BF, Kudaravalli S, Wen X, Pritchard JK. A Map of Recent Positive Selection in the Human Genome. PLOS Biol. 2006;4:e72. doi: 10.1371/journal.pbio.0040072 16494531

94. Rockman MV. The QTN Program and the Alleles That Matter for Evolution: All That’s Gold Does Not Glitter. Evol Int J Org Evol. 2012;66:1–17. doi: 10.1111/j.1558-5646.2011.01486.x 22220860

95. Boyle EA, Li YI, Pritchard JK. An Expanded View of Complex Traits: From Polygenic to Omnigenic. Cell. 2017;169:1177–1186. doi: 10.1016/j.cell.2017.05.038 28622505

96. Emerson KJ, Uyemura AM, McDaniel KL, Schmidt PS, Bradshaw WE, Holzapfel CM. Environmental control of ovarian dormancy in natural populations of Drosophila melanogaster. J Comp Physiol A. 2009;195:825–829. doi: 10.1007/s00359-009-0460-5 19669646

97. Anduaga AM, Nagy D, Costa R, Kyriacou CP. Diapause in Drosophila melanogaster–Photoperiodicity, cold tolerance and metabolites. J Insect Physiol. 2018;105:46–53. doi: 10.1016/j.jinsphys.2018.01.003 29339232

98. Pegoraro M, Tauber E. Photoperiod-dependent expression of MicroRNA in Drosophila. bioRxiv. 2018;464180. doi: 10.1101/464180

99. Nagy D, Andreatta G, Bastianello S, Martín Anduaga A, Mazzotta G, Kyriacou CP, et al. A Semi-natural Approach for Studying Seasonal Diapause in Drosophila melanogaster Reveals Robust Photoperiodicity. J Biol Rhythms. 2018;33:117–125. doi: 10.1177/0748730417754116 29415605

100. McCall K. Eggs over easy: cell death in the Drosophila ovary. Dev Biol. 2004;274:3–14. doi: 10.1016/j.ydbio.2004.07.017 15355784

101. Pegoraro M, Zonato V, Tyler ER, Fedele G, Kyriacou CP, Tauber E. Geographical analysis of diapause inducibility in European Drosophila melanogaster populations. J Insect Physiol. 2017;98:238–244. doi: 10.1016/j.jinsphys.2017.01.015 28131702

102. Lloyd-Jones LR, Zeng J, Sidorenko J, Yengo L, Moser G, Kemper KE, et al. Improved polygenic prediction by Bayesian multiple regression on summary statistics. bioRxiv. 2019;522961. doi: 10.1038/s41467-019-12653-0 31704910

103. Rosenberg NA, Edge MD, Pritchard JK, Feldman MW. Interpreting polygenic scores, polygenic adaptation, and human phenotypic differences. Evol Med Public Health. 2019;2019:26–34. doi: 10.1093/emph/eoy036 30838127

104. Rajpurohit S, Hanus R, Vrkoslav V, Behrman EL, Bergland AO, Petrov D, et al. Adaptive dynamics of cuticular hydrocarbons in Drosophila. J Evol Biol. 2017;30:66–80. doi: 10.1111/jeb.12988 27718537

105. Friedline CJ, Faske TM, Lind BM, Hobson EM, Parry D, Dyer RJ, et al. Evolutionary genomics of gypsy moth populations sampled along a latitudinal gradient. Mol Ecol. 2019;0. doi: 10.1111/mec.15069 30834645

106. Bay RA, Palumbi SR. Multilocus Adaptation Associated with Heat Resistance in Reef-Building Corals. Curr Biol. 2014;24:2952–2956. doi: 10.1016/j.cub.2014.10.044 25454780

107. Exposito-Alonso M, Vasseur F, Ding W, Wang G, Burbano HA, Weigel D. Genomic basis and evolutionary potential for extreme drought adaptation in Arabidopsis thaliana. Nat Ecol Evol. 2018;2:352. doi: 10.1038/s41559-017-0423-0 29255303

108. Yeh T-H, Huang S-Y, Lan W-Y, Liaw G-J, Yu J-Y. Modulation of cell morphogenesis by tousled-like kinase in the Drosophila follicle cell. Dev Dyn. 2015;244:852–865. doi: 10.1002/dvdy.24292 25981356

109. Li H-H, Chiang C-S, Huang H-Y, Liaw G-J. mars and tousled-like kinase act in parallel to ensure chromosome fidelity in Drosophila. J Biomed Sci. 2009;16:51. doi: 10.1186/1423-0127-16-51 19486529

110. Croze M, Wollstein A, Božičević V, Živković D, Stephan W, Hutter S. A genome-wide scan for genes under balancing selection in Drosophila melanogaster. BMC Evol Biol. 2017;17. doi: 10.1186/s12862-016-0857-z 28086750

111. Mansourian S, Enjin A, Jirle EV, Ramesh V, Rehermann G, Becher PG, et al. Wild African Drosophila melanogaster Are Seasonal Specialists on Marula Fruit. Curr Biol. 2018 [cited 13 Dec 2018]. doi: 10.1016/j.cub.2018.10.033 30528579

112. Wilson TG. Determinants of oöcyte degeneration in Drosophila melanogaster. J Insect Physiol. 1985;31:109–117. doi: 10.1016/0022-1910(85)90015-0

113. Gruntenko NE, Rauschenbach IY. Interplay of JH, 20E and biogenic amines under normal and stress conditions and its effect on reproduction. J Insect Physiol. 2008;54:902–908. doi: 10.1016/j.jinsphys.2008.04.004 18511066

114. Nosil P, Villoutreix R, de Carvalho CF, Farkas TE, Soria-Carrasco V, Feder JL, et al. Natural selection and the predictability of evolution in Timema stick insects. Science. 2018;359:765–770. doi: 10.1126/science.aap9125 29449486

115. Barghi N, Tobler R, Nolte V, Jakšić AM, Mallard F, Otte KA, et al. Genetic redundancy fuels polygenic adaptation in Drosophila. PLOS Biol. 2019;17:e3000128. doi: 10.1371/journal.pbio.3000128 30716062

116. Pitchers W, Pool JE, Dworkin I. Altitudinal Clinal Variation in Wing Size & Shape in African Drosophila melanogaster: One Cline or Many? Evol Int J Org Evol. 2013;67:438–452. doi: 10.1111/j.1558-5646.2012.01774.x 23356616

117. Klepsatel P, Gáliková M, Huber CD, Flatt T. Similarities and Differences in Altitudinal Versus Latitudinal Variation for Morphological Traits in Drosophila Melanogaster. Evolution. 2014;68: 1385–1398. doi: 10.1111/evo.12351 24410363

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

119. Hoban S, Kelley JL, Lotterhos KE, Antolin MF, Bradburd G, Lowry DB, et al. Finding the Genomic Basis of Local Adaptation: Pitfalls, Practical Solutions, and Future Directions. Am Nat. 2016;188:379–397. doi: 10.1086/688018 27622873

120. Bale JS, Hayward S a L. Insect overwintering in a changing climate. J Exp Biol. 2010;213:980–994. doi: 10.1242/jeb.037911 20190123

121. Doležel D, Vaněčková H, Šauman I, Hodkova M. Is period gene causally involved in the photoperiodic regulation of reproductive diapause in the linden bug, Pyrrhocoris apterus? J Insect Physiol. 2005;51:655–659. doi: 10.1016/j.jinsphys.2005.01.009 15993130

122. Han B, Denlinger DL. Mendelian Inheritance of Pupal Diapause in the Flesh Fly, Sarcophaga bullata. J Hered. 2009;100:251–255. doi: 10.1093/jhered/esn082 18836144

123. Kozak GM, Wadsworth CB, Kahne SC, Bogdanowicz SM, Harrison RG, Coates BS, et al. Genomic Basis of Circannual Rhythm in the European Corn Borer Moth. Curr Biol. 2019;29:3501–3509.e5. doi: 10.1016/j.cub.2019.08.053 31607536

124. Mori A, Romero-Severson J, Severson DW. Genetic basis for reproductive diapause is correlated with life history traits within the Culex pipiens complex. Insect Mol Biol. 2007;16:515–524. doi: 10.1111/j.1365-2583.2007.00746.x 17635616

125. Pruisscher P, Nylin S, Gotthard K, Wheat CW. Genetic variation underlying local adaptation of diapause induction along a cline in a butterfly. Mol Ecol. 2018;27:3613–3626. doi: 10.1111/mec.14829 30105798

126. Ikten C, Skoda SR, Hunt TE, Molina-Ochoa J, Foster JE. Genetic Variation and Inheritance of Diapause Induction in Two Distinct Voltine Ecotypes of Ostrinia nubilalis (Lepidoptera: Crambidae). Ann Entomol Soc Am. 2011;104:567–575. doi: 10.1603/AN09149

127. Grenier JK, Arguello JR, Moreira MC, Gottipati S, Mohammed J, Hackett SR, et al. Global diversity lines—a five-continent reference panel of sequenced Drosophila melanogaster strains. G3 Bethesda Md. 2015;5:593–603. doi: 10.1534/g3.114.015883 25673134

128. Behrman E, Howick H, Kapun M, Staubach F, Bergland B, Petrov D, et al. Rapid seasonal evolution in innate immunity of wild Drosophila melanogaster. Proc R Soc B Biol Sci. 2018;285:20172599. doi: 10.1098/rspb.2017.2599 29321302

129. Kao JY, Zubair A, Salomon MP, Nuzhdin SV, Campo D. Population genomic analysis uncovers African and European admixture in Drosophila melanogaster populations from the south-eastern United States and Caribbean Islands. Mol Ecol. 2015;24:1499–1509. doi: 10.1111/mec.13137 25735402

130. Fox J, Weisberg S. An R Companion to Applied Regression, Third Edition. Thousand Oaks, CA: Sage; 2019. https://socialsciences.mcmaster.ca/jfox/Books/Companion/

131. Baym M, Kryazhimskiy S, Lieberman TD, Chung H, Desai MM, Kishony R. Inexpensive Multiplexed Library Preparation for Megabase-Sized Genomes. PLOS ONE. 2015;10:e0128036. doi: 10.1371/journal.pone.0128036 26000737

132. Zhang J, Kobert K, Flouri T, Stamatakis A. PEAR: a fast and accurate Illumina Paired-End reAd mergeR. Bioinforma Oxf Engl. 2014;30:614–620. doi: 10.1093/bioinformatics/btt593 24142950

133. Li H, Durbin R. Fast and accurate short read alignment with Burrows-Wheeler transform. Bioinforma Oxf Engl. 2009;25:1754–1760. doi: 10.1093/bioinformatics/btp324 19451168

134. 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 Res. 2010;20:1297–1303. doi: 10.1101/gr.107524.110 20644199

135. Kessner D, Turner TL, Novembre J. Maximum likelihood estimation of frequencies of known haplotypes from pooled sequence data. Mol Biol Evol. 2013;30:1145–1158. doi: 10.1093/molbev/mst016 23364324

136. Zheng C, Boer MP, van Eeuwijk FA. Reconstruction of Genome Ancestry Blocks in Multiparental Populations. Genetics. 2015;200:1073–1087. doi: 10.1534/genetics.115.177873 26048018

137. Comeron JM, Ratnappan R, Bailin S. The Many Landscapes of Recombination in Drosophila melanogaster. PLOS Genet. 2012;8:e1002905. doi: 10.1371/journal.pgen.1002905 23071443

138. Zheng X, Levine D, Shen J, Gogarten SM, Laurie C, Weir BS. A high-performance computing toolset for relatedness and principal component analysis of SNP data. Bioinforma Oxf Engl. 2012;28:3326–3328. doi: 10.1093/bioinformatics/bts606 23060615

139. Kapun M, Fabian DK, Goudet J, Flatt T. Genomic Evidence for Adaptive Inversion Clines in Drosophila melanogaster. Mol Biol Evol. 2016;33:1317–1336. doi: 10.1093/molbev/msw016 26796550

140. Conomos M, Gogarten SM, Brown L, Chen H, Rice K, Sofer T, et al. GENetic EStimation and Inference in Structured samples (GENESIS): Statistical methods for analyzing genetic data from samples with population structure and/or relatedness. 2019. https://github.com/UW-GAC/GENESIS

141. Conomos MP, Miller MB, Thornton TA. Robust Inference of Population Structure for Ancestry Prediction and Correction of Stratification in the Presence of Relatedness. Genet Epidemiol. 2015;39:276–293. doi: 10.1002/gepi.21896 25810074

142. Zeng Y, Breheny P. The biglasso Package: A Memory- and Computation-Efficient Solver for Lasso Model Fitting with Big Data in R. ArXiv170105936 Stat. 2018 [cited 24 Feb 2020]. http://arxiv.org/abs/1701.05936

143. Cingolani P, Platts A, Wang LL, Coon M, Nguyen T, Wang L, et al. A program for annotating and predicting the effects of single nucleotide polymorphisms, SnpEff: SNPs in the genome of Drosophila melanogaster strain w1118; iso-2; iso-3. Fly (Austin). 2012;6:80–92. doi: 10.4161/fly.19695 22728672

144. International Schizophrenia Consortium, Purcell SM, Wray NR, Stone JL, Visscher PM, O’Donovan MC, et al. Common polygenic variation contributes to risk of schizophrenia and bipolar disorder. Nature. 2009;460:748–752. doi: 10.1038/nature08185 19571811

145. Marees AT, de Kluiver H, Stringer S, Vorspan F, Curis E, Marie-Claire C, et al. A tutorial on conducting genome-wide association studies: Quality control and statistical analysis. Int J Methods Psychiatr Res. 2018;27:e1608. doi: 10.1002/mpr.1608 29484742

146. Gautier M, Vitalis R. rehh: an R package to detect footprints of selection in genome-wide SNP data from haplotype structure. Bioinforma Oxf Engl. 2012;28:1176–1177. doi: 10.1093/bioinformatics/bts115 22402612

147. Gautier M, Klassmann A, Vitalis R. rehh 2.0: a reimplementation of the R package rehh to detect positive selection from haplotype structure. Mol Ecol Resour. 2017;17:78–90. doi: 10.1111/1755-0998.12634 27863062

148. R Core Team. R: A language and environment for statistical computing. Vienna, Austria: R Foundation for Statistical Computing; http://www.R-project.org/

149. Wickham H. ggplot2: Elegant Graphics for Data Analysis. New York: Springer-Verlag; 2016.

150. Wilke CO. cowplot: Streamlined Plot Theme and Plot Annotations for “ggplot2.” 2019. https://CRAN.R-project.org/package=cowplot

151. Dowle M, Srinivasan A. data.table: Extension of `data.frame`. 2019. https://CRAN.R-project.org/package=data.table

152. Microsoft, Weston S. foreach: Provides Foreach Looping Construct for R. 2017. https://CRAN.R-project.org/package=foreach

153. Revolution Analytics, Weston S. doMC: Foreach Parallel Adaptor for “parallel.” 2017. Adaptor for ‘parallel’. R package version 1.3.5. https://CRAN.R-project.org/package=doMC

154. Clarke E, Sherrill-Mix S. ggbeeswarm: Categorical Scatter (Violin Point) Plots. 2017. https://CRAN.R-project.org/package=ggbeeswarm

155. Grolemund G, Wickham H. Dates and Times Made Easy with lubridate. J Stat Softw. 2011;40:1–25. doi: 10.18637/jss.v040.i03

156. Garnier S. viridis: Default Color Maps from “matplotlib.” 2018. https://CRAN.R-project.org/package=viridis


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