Additive and mostly adaptive plastic responses of gene expression to multiple stress in Tribolium castaneum
Autoři:
Eva L. Koch aff001; Frédéric Guillaume aff001
Působiště autorů:
Department of Evolutionary Biology and Environmental Studies, University of Zürich, Zürich, Switzerland
aff001; Department of Animal and Plant Science, University of Sheffield, Western Bank, Sheffield, United Kingdom
aff002
Vyšlo v časopise:
Additive and mostly adaptive plastic responses of gene expression to multiple stress in Tribolium castaneum. PLoS Genet 16(5): e32767. doi:10.1371/journal.pgen.1008768
Kategorie:
Research Article
doi:
https://doi.org/10.1371/journal.pgen.1008768
Souhrn
Gene expression is known to be highly responsive to the environment and important for adjustment of metabolism but there is also growing evidence that differences in gene regulation contribute to species divergence and differences among locally adapted populations. However, most studies so far investigated populations when divergence had already occurred. Selection acting on expression levels at the onset of adaptation to an environmental change has not been characterized. Understanding the mechanisms is further complicated by the fact that environmental change is often multivariate, meaning that organisms are exposed to multiple stressors simultaneously with potentially interactive effects. Here we use a novel approach by combining fitness and whole-transcriptome data in a large-scale experiment to investigate responses to drought, heat and their combination in Tribolium castaneum. We found that fitness was reduced by both stressors and their combined effect was almost additive. Expression data showed that stressor responses were acting independently and did not interfere physiologically. Since we measured expression and fitness within the same individuals, we were able to estimate selection on gene expression levels. We found that variation in fitness can be attributed to gene expression variation and that selection pressures were environment dependent and opposite between control and stress conditions. We could further show that plastic responses of expression were largely adaptive, i.e. in the direction that should increase fitness.
Klíčová slova:
Beetles – Evolutionary adaptation – Evolutionary genetics – Gene expression – Humidity – Natural selection – Permutation – Transcriptome analysis
Zdroje
1. Prud ‘homme B, Gompel N, Carroll SB. Emerging principles of regulatory evolution. Proc Natl Acad Sci. 2007;104: 8605–8612. doi: 10.1073/pnas.0700488104 17494759
2. Romero IG, Ruvinsky I, Gilad Y. Comparative studies of gene expression and the evolution of gene regulation. Nat Rev Genet. 2012;13: 505–516. doi: 10.1038/nrg3229 22705669
3. Fay JC, Wittkopp PJ. Evaluating the role of natural selection in the evolution of gene regulation. Heredity. 2008;100: 191–199. doi: 10.1038/sj.hdy.6801000 17519966
4. Carroll SB. Evo-Devo and an Expanding Evolutionary Synthesis: A Genetic Theory of Morphological Evolution. Cell. 2008;134: 25–36. doi: 10.1016/j.cell.2008.06.030 18614008
5. Long Y, Li L, Li Q, He X, Cui Z. Transcriptomic characterization of temperature stress responses in larval zebrafish. PLoS One. 2012;7. doi: 10.1371/journal.pone.0037209 22666345
6. Cui X, Affourtit J, Shockley KR, Woo Y, Churchill GA. Inheritance patterns of transcript levels in F1 hybrid mice. Genetics. 2006;174: 627–637. doi: 10.1534/genetics.106.060251 16888332
7. Ayroles JF, Carbone MA, Stone EA, Jordan KW, Lyman RF, Magwire MM, et al. Systems genetics of complex traits in Drosophila melanogaster. Nat Genet. 2009;41: 299–307. doi: 10.1038/ng.332 19234471
8. Skelly DA, Ronald J, Akey JM. Inherited Variation in Gene Expression. Annu Rev Genomics Hum Genet. 2009;10: 313–332. doi: 10.1146/annurev-genom-082908-150121 19630563
9. Morris MRJ, Richard R, Leder EH, Barrett RDH, Aubin-Horth N, Rogers SM. Gene expression plasticity evolves in response to colonization of freshwater lakes in threespine stickleback. Mol Ecol. 2014;23: 3226–3240. doi: 10.1111/mec.12820 24889067
10. McCairns RJS, Smith S, Sasaki M, Bernatchez L, Beheregaray LB. The adaptive potential of subtropical rainbowfish in the face of climate change: Heritability and heritable plasticity for the expression of candidate genes. Evol Appl. 2016;9: 531–545. doi: 10.1111/eva.12363 27099620
11. Feder ME, Walser JC. The biological limitations of transcriptomics in elucidating stress and stress responses. J Evol Biol. 2005;18: 901–910. doi: 10.1111/j.1420-9101.2005.00921.x 16033562
12. Evans TG. Considerations for the use of transcriptomics in identifying the “genes that matter” for environmental adaptation. J Exp Biol. 2015;218: 1925–1935. doi: 10.1242/jeb.114306 26085669
13. Giaever G, Chu AM, Ni L, Connelly C, Riles L, Véronneau S, et al. Functional profiling of the Saccharomyces cerevisiae genome. Nature. 2002;418: 387–391. doi: 10.1038/nature00935 12140549
14. Keren L, Hausser J, Lotan-Pompan M, Vainberg Slutskin I, Alisar H, Kaminski S, et al. Massively Parallel Interrogation of the Effects of Gene Expression Levels on Fitness. Cell. 2016;166: 1282–1294.e18. doi: 10.1016/j.cell.2016.07.024 27545349
15. Sato MP, Makino T, Kawata M. Natural selection in a population of Drosophila melanogaster explained by changes in gene expression caused by sequence variation in core promoter regions. BMC Evol Biol. 2016;16: 1–12. doi: 10.1186/s12862-015-0575-y
16. Townsend JP, Cavalieri D, Hartl DL. Population genetic variation in genome-wide gene expression. Mol Biol Evol. 2003;20: 955–963. doi: 10.1093/molbev/msg106 12716989
17. Fraser HB. Gene expression drives local adaptation in humans Gene expression drives local adaptation in humans. Genome Res. 2013;23: 1089–1096. doi: 10.1101/gr.152710.112 23539138
18. Hutter S, Saminadin-Peter SS, Stephan W, Parsch J. Gene expression variation in African and European populations of Drosophila melanogaster. Genome Biol. 2008;9: R12. doi: 10.1186/gb-2008-9-1-r12 18208589
19. Dayan DI, Crawford DL, Oleksiak MF. Phenotypic plasticity in gene expression contributes to divergence of locally adapted populations of Fundulus heteroclitus. Mol Ecol. 2015;24: 3345–3359. doi: 10.1111/mec.13188 25847331
20. Ghalambor CK, Hoke KL, Ruell EW, Fischer EK, Reznick DN, Hughes KA. Non-adaptive plasticity potentiates rapid adaptive evolution of gene expression in nature. Nature. 2015;525: 372–375. doi: 10.1038/nature15256 26331546
21. McCairns RJSS, Bernatchez L. Adaptive divergence between freshwater and marine sticklebacks: insights into the role of phenotypic plasticity from an integrated analysis of candidate gene expression. Evolution. 2009;64: 1029–1047. doi: 10.1111/j.1558-5646.2009.00886.x 19895556
22. Zheng W, Gianoulis TA, Karczewski KJ, Zhao H, Snyder M. Regulatory Variation Within and Between Species. Annu Rev Genomics Hum Genet. 2011;12: 327–346. doi: 10.1146/annurev-genom-082908-150139 21721942
23. Riehle MM, Bennett AF, Lenski RE, Long AD. Evolutionary changes in heat-inducible gene expression in lines of Escherichia coli adapted to high temperature. Physiol Genomics. 2003;14: 47–58. doi: 10.1152/physiolgenomics.00034.2002 12672900
24. Telonis-Scott M, Hallas R, McKechnie SW, Wee CW, Hoffmann AA. Selection for cold resistance alters gene transcript levels in Drosophila melanogaster. J Insect Physiol. 2009;55: 549–555. doi: 10.1016/j.jinsphys.2009.01.010 19232407
25. Yampolsky LY, Glazko G V., Fry JD. Evolution of gene expression and expression plasticity in long-term experimental populations of Drosophila melanogaster maintained under constant and variable ethanol stress. Mol Ecol. 2012;21: 4287–4299. doi: 10.1111/j.1365-294X.2012.05697.x 22774776
26. Huang Y, Agrawal AF. Experimental Evolution of Gene Expression and Plasticity in Alternative Selective Regimes. PLoS Genet. 2016;12: 1–23. doi: 10.1371/journal.pgen.1006336 27661078
27. Ehrenreich IM, Pfennig DW. Genetic assimilation: A review of its potential proximate causes and evolutionary consequences. Ann Bot. 2016;117: 769–779. doi: 10.1093/aob/mcv130 26359425
28. Chevin LM, Lande R, Mace GM. Adaptation, plasticity, and extinction in a changing environment: Towards a predictive theory. PLoS Biol. 2010;8. doi: 10.1371/journal.pbio.1000357 20463950
29. Lande R. Adaptation to an extraordinary environment by evolution of phenotypic plasticity and genetic assimilation. J Evol Biol. 2009;22: 1435–1446. doi: 10.1111/j.1420-9101.2009.01754.x 19467134
30. Gasch AP, Spellman PT, Kao CM, Carmel-Harel O, Eisen MB, Storz G, et al. Genomic expression programs in the response of yeast cells to environmental changes. Mol Biol Cell. 2000;11: 4241–4257. doi: 10.1091/mbc.11.12.4241 11102521
31. Gibson G. The environmental contribution to gene expression profiles. Nat Rev Genet. 2008;9: 575. doi: 10.1038/nrg2383 18574472
32. López-Maury L, Marguerat S, Bähler J. Tuning gene expression to changing environments: From rapid responses to evolutionary adaptation. Nat Rev Genet. 2008;9: 583–593. doi: 10.1038/nrg2398 18591982
33. Des Marais DL, Hernandez KM, Juenger TE. Genotype-by-Environment Interaction and Plasticity: Exploring Genomic Responses of Plants to the Abiotic Environment. Annu Rev Ecol Evol Syst. 2013;44: 5–29. doi: 10.1146/annurev-ecolsys-110512-135806
34. Price TD, Qvarnström A, Irwin DE. The role of phenotypic plasticity in driving genetic evolution. Proc R Soc B Biol Sci. 2003;270: 1433–1440. doi: 10.1098/rspb.2003.2372 12965006
35. Fitzpatrick BM. Underappreciated consequences of phenotypic plasticity for ecological speciation. Int J Ecol. 2012;2012: 32–37. doi: 10.1155/2012/256017
36. Yeh PJ, Price TD. Adaptive Phenotypic Plasticity and the Successful Colonization of a Novel Environment. Am Nat. 2004;164: 531–542. doi: 10.1086/423825 15459883
37. Pavey SA, Collin H, Nosil P, Rogers SM. The role of gene expression in ecological speciation. Ann N Y Acad Sci. 2010;1206: 110–129. doi: 10.1111/j.1749-6632.2010.05765.x 20860685
38. Schneider RF, Meyer A. How plasticity, genetic assimilation and cryptic genetic variation may contribute to adaptive radiations. Mol Ecol. 2017;26: 330–350. doi: 10.1111/mec.13880 27747962
39. Sørensen JG, Dahlgaard J, Loeschcke V. Genetic variation in thermal tolerance among natural populations of Drosophila buzzatii: down regulation of Hsp70 expression and variation in heat stress resistance traits. Funct Ecol. 2001;15: 289–296. doi: 10.1046/j.1365-2435.2001.00525.x
40. Ghalambor CK, McKay JK, Carroll SP, Reznick DN. Adaptive versus non-adaptive phenotypic plasticity and the potential for contemporary adaptation in new environments. Funct Ecol. 2007;21: 394–407. doi: 10.1111/j.1365-2435.2007.01283.x
41. Whitehead A, Crawford DL. Neutral and adaptive variation in gene expression. Proc Natl Acad Sci United States Am. 2006;103: 5425–5430. doi: 10.1073/pnas.0507648103 16567645
42. Leder EH, McCairns RJS, Leinonen T, Cano JM, Viitaniemi HM, Nikinmaa M, et al. The evolution and adaptive potential of transcriptional variation in sticklebacks—Signatures of selection and widespread heritability. Mol Biol Evol. 2015;32: 674–689. doi: 10.1093/molbev/msu328 25429004
43. Moya A, Ganot P, Furla P, Sabourault C. The transcriptomic response to thermal stress is immediate, transient and potentiated by ultraviolet radiation in the sea anemone Anemonia viridis. Mol Ecol. 2012;21: 1158–1174. doi: 10.1111/j.1365-294X.2012.05458.x 22288383
44. Moya A, Huisman L, Forêt S, Gattuso JP, Hayward DC, Ball EE, et al. Rapid acclimation of juvenile corals to CO2-mediated acidification by upregulation of heat shock protein and Bcl-2 genes. Mol Ecol. 2015;24: 438–452. doi: 10.1111/mec.13021 25444080
45. Enzor LA, Place SP. Is warmer better? Decreased oxidative damage in notothenioid fish after long-term acclimation to multiple stressors. J Exp Biol. 2014;217: 3301–3310. doi: 10.1242/jeb.108431 25013114
46. Huth TJ, Place SP. Marine Genomics RNA-seq reveals a diminished acclimation response to the combined effects of ocean acidi fi cation and elevated seawater temperature in Pagothenia borchgrevinki. Mar Genomics. 2016;28: 87–97. doi: 10.1016/j.margen.2016.02.004 26969095
47. Schlichting CD, Smith H. Phenotypic plasticity: linking molecular mechanisms with evolutionary outcomes. Evol Ecol. 2002;16: 189–211. doi: 10.1023/A:1019624425971
48. Crain CM, Kroeker K, Halpern BS. Interactive and cumulative effects of multiple human stressors in marine systems. Ecol Lett. 2008;11: 1304–1315. doi: 10.1111/j.1461-0248.2008.01253.x 19046359
49. Byrne M, Przeslawski R. Multistressor impacts of warming and acidification of the ocean on marine invertebrates’ life histories. Integr Comp Biol. 2013;53: 582–596. doi: 10.1093/icb/ict049 23697893
50. Gunderson AR, Armstrong EJ, Stillman JH. Multiple Stressors in a Changing World: The Need for an Improved Perspective on Physiological Responses to the Dynamic Marine Environment. Ann Rev Mar Sci. 2016;8: 357–378. doi: 10.1146/annurev-marine-122414-033953 26359817
51. Kelly MW, DeBiasse MB, Villela VA, Roberts HL, Cecola CF. Adaptation to climate change: trade-offs among responses to multiple stressors in an intertidal crustacean. Evol Appl. 2016;9: 1147–1155. doi: 10.1111/eva.12394 27695522
52. DeBiasse MB, Kelly MW. Plastic and evolved responses to global change: What can we learn from comparative transcriptomics? J Hered. 2016;107: 71–81. doi: 10.1093/jhered/esv073 26519514
53. Pörtner HO, Bennett AF, Bozinovic F, Clarke A, Lardies MA, Lucassen M, et al. Trade‐Offs in Thermal Adaptation: The Need for a Molecular to Ecological Integration. Physiol Biochem Zool. 2006;79: 295–313. doi: 10.1086/499986 16555189
54. Crispo E. The Baldwin effect and genetic assimilation: Revisiting two mechanisms of evolutionary change mediated by phenotypic plasticity. Evolution. 2007;61: 2469–2479. doi: 10.1111/j.1558-5646.2007.00203.x 17714500
55. Healy TM, Schulte PM. Phenotypic plasticity and divergence in gene expression. Mol Ecol. 2015;24: 3220–3222. doi: 10.1111/mec.13246 26096949
56. Scoville AG, Pfrender ME. Phenotypic plasticity facilitates recurrent rapid adaptation to introduced predators. Proc Natl Acad Sci. 2010;107: 4260–4263. doi: 10.1073/pnas.0912748107 20160080
57. Mäkinen H, Papakostas S, Vøllestad LA, Leder EH, Primmer CR. Plastic and evolutionary gene expression responses are correlated in European grayling (Thymallus thymallus) subpopulations adapted to different thermal environments. Journal of Heredity. 2016. pp. 82–89. doi: 10.1093/jhered/esv069 26297731
58. Gibbons TC, Metzger DCH, Healy TM, Schulte PM. Gene expression plasticity in response to salinity acclimation in threespine stickleback ecotypes from different salinity habitats. Mol Ecol. 2017;26: 2711–2725. doi: 10.1111/mec.14065 28214359
59. Garland T, Kelly SA. Phenotypic plasticity and experimental evolution. J Exp Biol. 2008;211: 2725–2725. doi: 10.1242/jeb.022673
60. Conover DO, Duffy TA, Hice LA. The covariance between genetic and environmental influences across ecological gradients: Reassessing the evolutionary significance of countergradient and cogradient variation. Ann N Y Acad Sci. 2009;1168: 100–129. doi: 10.1111/j.1749-6632.2009.04575.x 19566705
61. Grether GF. Environmental Change, Phenotypic Plasticity, and Genetic Compensation. Am Nat. 2005;166: E115–E123. doi: 10.1086/432023 16224697
62. Sokoloff A. The biology of Tribolium with special emphasis on genetic aspects I. Clarendon Press and Oxford Univ. Press, Oxford. 1972. doi: 10.1086/407731
63. Park Y, Beeman RW. Postgenomics of Tribolium: Targeting the endocrine regulation of diuresis. Entomol Res. 2008;38: 93–100. doi: 10.1111/j.1748-5967.2008.00143.x
64. Milutinović B, Stolpe C, Peuß R, Armitage SAO, Kurtz J. The Red Flour Beetle as a Model for Bacterial Oral Infections. PLoS One. 2013;8. doi: 10.1371/journal.pone.0064638 23737991
65. Koch EL, Guillaume F. (2020) Data from: Fitness data of Tribolium castaneum in four different climate conditions. Dryad Digital Repository. https://doi.org/10.5061/dryad.gf1vhhmkn
66. Park Y, Aikins J, Wang LJ, Beeman RW, Oppert B, Lord JC, et al. Analysis of transcriptome data in the red flour beetle, Tribolium castaneum. Insect Biochem Molec Biol. 2008;38: 380–386. doi: 10.1016/10.1016/j.ibmb.2007.09.008
67. Hauser F, Cazzamali G, Williamson M, Park Y, Li B, Tanaka Y, et al. A genome-wide inventory of neurohormone GPCRs in the red flour beetle Tribolium castaneum. Front Neuroendocrinol. 2008;29: 142–165. doi: 10.1016/j.yfrne.2007.10.003 18054377
68. Li B, Predel R, Neupert S, Hauser F, Tanaka Y, Cazzamali G, et al. Genomics, transcriptomics, and peptidomics of neuropeptides and protein hormones in the red flour beetle Tribolium castaneum. Genome Res. 2008;18: 113–122. doi: 10.1101/gr.6714008 18025266
69. Aikins MJ, Schooley DA, Begum K, Detheux M, Beeman RW, Park Y. Vasopressin-like peptide and its receptor function in an indirect diuretic signaling pathway in the red flour beetle. Insect Biochem Mol Biol. 2008;38: 740–748. doi: 10.1016/j.ibmb.2008.04.006 18549960
70. Robinson MD, McCarthy DJ, Smyth GK. edgeR: a Bioconductor package for differential expression analysis of digital gene expression data. Bioinformatics. 2010;26: 139–140. doi: 10.1093/bioinformatics/btp616 19910308
71. Rasmussen S, Barah P, Suarez-Rodriguez MC, Bressendorff S, Friis P, Costantino P, et al. Transcriptome Responses to Combinations of Stresses in Arabidopsis. PLANT Physiol. 2013;161: 1783–1794. doi: 10.1104/pp.112.210773 23447525
72. Ihmels J, Friedlander G, Bergmann S, Sarig O, Ziv Y, Barkai N. Revealing modular organization in the yeast transcriptional network. Nat Genet. 2002;31: 370–377. doi: 10.1038/ng941 12134151
73. Barabási AL, Oltvai ZN. Network biology: Understanding the cell’s functional organization. Nat Rev Genet. 2004;5: 101–113. doi: 10.1038/nrg1272 14735121
74. Langfelder P, Horvath S. WGCNA: An R package for weighted correlation network analysis. BMC Bioinformatics. 2008;9. doi: 10.1186/1471-2105-9-9
75. Schwenke RA, Lazzaro BP, Wolfner MF. Reproduction–Immunity Trade-Offs in Insects. Annu Rev Entomol. 2016;61: 239–256. doi: 10.1146/annurev-ento-010715-023924 26667271
76. Parthasarathy R, Palli SR. Molecular analysis of nutritional and hormonal regulation of female reproduction in the red flour beetle, Tribolium castaneum. Insect Biochem Mol Biol. 2011;41: 294–305. doi: 10.1016/j.ibmb.2011.01.006 21288489
77. Parthasarathy R, Sheng Z, Sun Z, Palli SR. Ecdysteroid regulation of ovarian growth and oocyte maturation in the red flour beetle, Tribolium castaneum. Insect Biochem Mol Biol. 2010;40: 429–439. doi: 10.1016/j.ibmb.2010.04.002 20385235
78. Parthasarathy R, Sun Z, Bai H, Palli SR. Juvenile hormone regulation of vitellogenin synthesis in the red flour beetle, Tribolium castaneum. Insect Biochem Mol Biol. 2010;40: 405–414. doi: 10.1016/j.ibmb.2010.03.006 20381616
79. Xu J, Tan A, Palli SR. The function of nuclear receptors in regulation of female reproduction and embryogenesis in the red flour beetle, Tribolium castaneum. J Insect Physiol. 2010;56: 1471–1480. doi: 10.1016/j.jinsphys.2010.04.004 20416316
80. Lande R, Arnold SJ. The Measurement of Selection on Correlated Characters. Evolution. 1983;37: 1210. doi: 10.1111/j.1558-5646.1983.tb00236.x 28556011
81. Falconer DS, MacKay TFC. Introduction to Quantitative Genetics. 4th Editio. Essex: Longman Group; 1996.
82. Tufail M, Takeda M. Insect vitellogenin/lipophorin receptors: Molecular structures, role in oogenesis, and regulatory mechanisms. J Insect Physiol. 2009;55: 88–104. doi: 10.1016/j.jinsphys.2009.01.009
83. Kültz D. Molecular and Evolutionary Basis of the Cellular Stress Response. Annu Rev Physiol. 2005;67: 225–257. doi: 10.1146/annurev.physiol.67.040403.103635 15709958
84. Kassahn KS, Crozier RH, Pörtner HO, Caley MJ. Animal performance and stress: Responses and tolerance limits at different levels of biological organisation. Biol Rev. 2009;84: 277–292. doi: 10.1111/j.1469-185X.2008.00073.x 19344429
85. Flatt T, Tu M-P, Tatar M. Hormonal pleiotropy and the juvenile hormone regulation of Drosophila development and life history. BioEssays. 2005;27: 999–1010. doi: 10.1002/bies.20290 16163709
86. Gruntenko NE, Rauschenbach IY. The role of insulin signalling in the endocrine stress response in Drosophila melanogaster: A mini-review. Gen Comp Endocrinol. 2017;258: 134–139. doi: 10.1016/j.ygcen.2017.05.019 28554733
87. Feder ME, Hoffman GE. Heat-shock proteins, molecular chaperones, and the stress response: evolutionary and ecological physiology. Annu Rev Physiol. 1999;61: 243–282. doi: 10.1146/annurev.physiol.61.1.243 10099689
88. Silbermann R, Tatar M. Reproductive costs of heat shock protein in transgenic Drosophila melanogaster. Evolution. 2000;54: 2038–2045. doi: 10.1111/j.0014-3820.2000.tb01247.x 11209780
89. King B, Denholm B. Malpighian tubule development in the red flour beetle (Tribolium castaneum). Arthropod Struct Dev. 2014;43: 605–613. doi: 10.1016/j.asd.2014.08.002 25242057
90. Fischer EK, Ghalambor CK, Hoke KL. Can a Network Approach Resolve How Adaptive vs Nonadaptive Plasticity Impacts Evolutionary Trajectories? Integr Comp Biol. 2016;56: 877–888. doi: 10.1093/icb/icw087 27400976
91. Paaby AB, Rockman M V. Cryptic genetic variation: Evolution’s hidden substrate. Nat Rev Genet. 2014;15: 247–258. doi: 10.1038/nrg3688 24614309
92. Folt C, Chen C. Synergism and antagonism among multiple stressors. Limnol Oceanogr. 1999;44: 864–877. doi: 10.4319/lo.1999.44.3
93. Neven LG. Physiological responses of insects to heat. Postharvest Biol Technol. 2000;21: 103–111. doi: 10.1016/S0925-5214(00)00169-1
94. Nguyen TTA, Michaud D, Cloutier C. A proteomic analysis of the aphid Macrosiphum euphorbiae under heat and radiation stress. Insect Biochem Mol Biol. 2009;39: 20–30. doi: 10.1016/j.ibmb.2008.09.014 19000926
95. Levine MT, Eckert ML, Begun DJ. Whole-genome expression plasticity across tropical and temperate Drosophila melanogaster populations from eastern Australia. Mol Biol Evol. 2011;28: 249–256. doi: 10.1093/molbev/msq197 20671040
96. Chen X, Stillman JH. Multigenerational analysis of temperature and salinity variability affects on metabolic rate, generation time, and acute thermal and salinity tolerance in Daphnia pulex. J Therm Biol. 2012;37: 185–194. doi: 10.1016/j.jtherbio.2011.12.010
97. Sokolova IM. Energy-limited tolerance to stress as a conceptual framework to integrate the effects of multiple stressors. Integr Comp Biol. 2013;53: 597–608. doi: 10.1093/icb/ict028 23615362
98. Liess M, Foit K, Knillmann S, Schäfer RB, Liess HD. Predicting the synergy of multiple stress effects. Sci Rep. 2016;6: 1–8. doi: 10.1038/s41598-016-0001-8
99. Morris MRJ, Rogers SM. Overcoming maladaptive plasticity through plastic compensation. Curr Zool. 2013;59: 526–536. doi: 10.1093/czoolo/59.4.526
100. Ho W-C, Zhang J. Evolutionary adaptations to new environments generally reverse plastic phenotypic changes. Nat Commun. 2018;9: 1–11. doi: 10.1038/s41467-017-02088-w
101. Pigliucci M, Murren CJ, Schlichting CD. Phenotypic plasticity and evolution by genetic assimilation. J Exp Biol. 2006;209: 2362–2367. doi: 10.1242/jeb.02070 16731812
102. King AM, MacRae TH. Insect Heat Shock Proteins During Stress and Diapause. Annu Rev Entomol. 2015;60: 59–75. doi: 10.1146/annurev-ento-011613-162107 25341107
103. Walsh B, Blows MW. Abundant Genetic Variation + Strong Selection = Multivariate Genetic Constraints: A Geometric View of Adaptation. Annu Rev Ecol Evol Syst. 2009;40: 41–59. doi: 10.1146/annurev.ecolsys.110308.120232
104. Stinchcombe JR, Simonsen AK, Blows MW. Estimating uncertainty in multivariate responses to selection. Evolution. 2014;68: 1188–1196. doi: 10.1111/evo.12321 24274331
105. Robertson A. A mathematical model of the culling process in dairy cattle. Anim Sci. 1966;8: 95–108.
106. Morrissey MB, Kruuk LEB, Wilson AJ. The danger of applying the breeder’s equation in observational studies of natural populations. J Evol Biol. 2010;23: 2277–2288. doi: 10.1111/j.1420-9101.2010.02084.x 20831731
107. Rausher MD. The measurement of selection on quantitative traits—biases due to environmental covariances between traits and fitness. Evolution. 1992;46: 616–626. doi: 10.1111/j.1558-5646.1992.tb02070.x 28568666
108. Bates D, Mächler M, Bolker B, Walker S. Fitting Linear Mixed-Effects Models Using lme4. J Stat Softw. 2015;67: 1–48. doi: 10.18637/jss.v067.i01
109. R Core Team. R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing. 2015. doi: 10.1007/978-3-540-74686-7
110. Dobin A, Davis CA, Schlesinger F, Drenkow J, Zaleski C, Jha S, et al. STAR: ultrafast universal RNA-seq aligner. Bioinformatics. 2013;29: 15–21. doi: 10.1093/bioinformatics/bts635 23104886
111. Liao Y, Smyth GK, Shi W. FeatureCounts: An efficient general purpose program for assigning sequence reads to genomic features. Bioinformatics. 2014;30: 923–930. doi: 10.1093/bioinformatics/btt656 24227677
112. Hatakeyama M, Opitz L, Russo G, Qi W, Schlapbach R, Rehrauer H. SUSHI: An exquisite recipe for fully documented, reproducible and reusable NGS data analysis. BMC Bioinformatics. 2016;17: 1–9. doi: 10.1186/s12859-015-0844-1
113. Benjamini Y, Hochberg Y. Controlling the False Discovery Rate: A Practical and Powerful Approach to Multiple Testing Testing. J R Stat Soc Ser B. 1995;57: 289–300.
114. Love MI, Anders S, Huber W. Differential analysis of count data—the DESeq2 package. Genome Biology. 2014. doi: 110.1186/s13059-014-0550-8
115. Wu D, Lim E, Vaillant F, Asselin-Labat M-L, Visvader JE, Smyth GK. ROAST: rotation gene set tests for complex microarray experiments. Bioinformatics. 2010;26: 2176–82. doi: 10.1093/bioinformatics/btq401 20610611
116. Reimand J, Arak T, Vilo J. g:Profiler—A web server for functional interpretation of gene lists (2011 update). Nucleic Acids Res. 2011;39: W307–W315. doi: 10.1093/nar/gkr378 21646343
117. Szklarczyk D, Franceschini A, Wyder S, Forslund K, Heller D, Huerta-Cepas J, et al. STRING v10: Protein-protein interaction networks, integrated over the tree of life. Nucleic Acids Res. 2015;43: D447–D452. doi: 10.1093/nar/gku1003 25352553
118. Brodie ED III, Moore AJ, Janzen FJ. Visualizing and quantifying natural selection. Trends Ecol Evol. 1995;10: 313–318. </References> doi: 10.1016/s0169-5347(00)89117-x 21237054
Článek vyšel v časopise
PLOS Genetics
2020 Číslo 5
- Distribuce a lokalizace speciálně upravených exosomů může zefektivnit léčbu svalových dystrofií
- Prof. Jan Škrha: Metformin je bezpečný, ale je třeba jej bezpečně užívat a léčbu kontrolovat
- FDA varuje před selfmonitoringem cukru pomocí chytrých hodinek. Jak je to v Česku?
- Masturbační chování žen v ČR − dotazníková studie
- O krok blíže k pochopení efektu placeba při léčbě bolesti
Nejčtenější v tomto čísle
- The domesticated transposase ALP2 mediates formation of a novel Polycomb protein complex by direct interaction with MSI1, a core subunit of Polycomb Repressive Complex 2 (PRC2)
- Polyploidy breaks speciation barriers in Australian burrowing frogs Neobatrachus
- The phosphorelay BarA/SirA activates the non-cognate regulator RcsB in Salmonella enterica
- Congenital hearing impairment associated with peripheral cochlear nerve dysmyelination in glycosylation-deficient muscular dystrophy