Transcriptome analysis of a wild bird reveals physiological responses to the urban environment

Scientific Reports

Volumn 7, Issue , 2017, Pages

  Watson, Hannah ^a   Videvall, Elin ^a   Andersson, Martin N ^a   Isaksson, Caroline ^a  

^a LUND UNIVERSITY   (Sweden)

Author keywords

[No Author keywords available]

Indexed keywords

ADAPTATION; ANIMAL; BLOOD; FEMALE; GENE EXPRESSION PROFILING; GENE EXPRESSION REGULATION; GENETICS; LIVER; MALE; METABOLISM; PASSERIFORMES; PHYSIOLOGICAL STRESS; PHYSIOLOGY;

ADAPTATION, PHYSIOLOGICAL; ANIMALS; FEMALE; GENE EXPRESSION PROFILING; GENE EXPRESSION REGULATION; LIVER; MALE; PASSERIFORMES; STRESS, PHYSIOLOGICAL;

EID: 85015273011     PISSN: None     EISSN: 20452322     Source Type: Journal    
DOI: 10.1038/srep44180     Document Type: Article

References (81)

1. Seto K. C, Guneralp B, & Hutyra L. R. Global forecasts of urban expansion to 2030 and direct impacts on biodiversity and carbon pools. Proc. Natl. Acad. Sci. 109, 16083-16088 (2012).
2. McKinney M. L. Urbanization, biodiversity and conservation. Bioscience 52, 883-890 (2002).
3. Shochat E, Warren P. S, Faeth S. H, Mcintyre N. E, & Hope D. From patterns to emerging processes in mechanistic urban ecology. Trends Ecol. Evol. 21, 186-191 (2006).
4. Evans K. L, et al. Effects of urbanisation on disease prevalence and age structure in blackbird Turdus merula populations. Oikos 118, 774-782 (2009).
5. Giraudeau M, Mousel M, Earl S, & McGraw K. Parasites in the city: degree of urbanization predicts poxvirus and coccidian infections in house finches (Haemorhous mexicanus). PLoS One 9, e86747 (2014).
6. Slabbekoorn H, & Peet M. Birds sing at a higher pitch in urban noise. Nature 424, 267 (2003).
7. Isaksson C, Örnborg J, Stephensen E, & Andersson S. Plasma glutathione and carotenoid coloration as potential biomarkers of environmental stress in great tits. Ecohealth 2, 138-146 (2005).
8. Liker A, Papp Z, Bókony V, & Lendvai A. Z. Lean birds in the city: body size and condition of house sparrows along the urbanization gradient. J. Anim. Ecol. 77, 789-795 (2008).
9. Cheptou P.-O, Carrue O, Rouifed S, & Cantarel A. Rapid evolution of seed dispersal in an urban environment in the weed Crepis sancta. Proc. Natl. Acad. Sci. USA 105, 3796-3799 (2008).
10. Stone E. L, Jones G, & Harris S. Street Lighting Disturbs Commuting Bats. Curr. Biol. 19, 1123-1127 (2009).
11. Tennessen J. B, Parks S. E, & Langkilde T. Traffic noise causes physiological stress and impairs breeding migration behaviour in frogs. Conserv. Physiol. 2, 1-8 (2014).
12. Isaksson C. Urbanization, oxidative stress and inflammation: a question of evolving, acclimatizing or coping with urban environmental stress. Funct. Ecol. 29, 913-923 (2015).
13. Moya A, et al. Whole transcriptome analysis of the coral Acropora millepora reveals complex responses to CO2-driven acidification during the initiation of calcification. Mol. Ecol. 21, 2440-2454 (2012).
14. Whitehead A, Triant D. A, Champlin D, & Nacci D. Comparative transcriptomics implicates mechanisms of evolved pollution tolerance in a killifish population. Mol. Ecol. 19, 5186-5203 (2010).
15. Videvall E, Cornwallis C. K, Palinauskas V, Valkiunas G, & Hellgren O. The avian transcriptome response to malaria infection. Mol. Biol. Evol. 32, 1255-1267 (2015).
16. Cheviron Z. A, Whitehead A, & Brumfield R. T. Transcriptomic variation and plasticity in rufous-collared sparrows (Zonotrichia capensis) along an altitudinal gradient. Mol. Ecol. 17, 4556-4569 (2008).
17. Mesquita S. R, et al. Differential embryotoxicity of the organic pollutants in rural and urban air particles. Environ. Pollut. 206, 535-542 (2015).
18. van Leeuwen D. M, et al. Transcriptome analysis in peripheral blood of humans exposed to environmental carcinogens: a promising new biomarker in environmental health studies. Environ. Health Perspect. 116, 1519-1525 (2008).
19. Harris S. E, Munshi-South J, Obergfell C, & O?Neill R. Signatures of rapid evolution in urban and rural transcriptomes of whitefooted mice (Peromyscus leucopus) in the New York Metropolitan Area. PLoS One 8, e74938 (2013).
20. Harris S. E, O?Neill R. J, & Munshi-South J. Transcriptome resources for the white-footed mouse (Peromyscus leucopus): new genomic tools for investigating ecologically divergent urban and rural populations. Mol. Ecol. Resour. 15, 382-394 (2015).
21. Andersson M. N, Wang H.-L, Nord A, Salmón P, & Isaksson C. Composition of physiologically important fatty acids in great tits differs between urban and rural populations on a seasonal basis. Front. Ecol. Evol. 3, 93 (2015).
22. de Jong M, et al. Effects of nocturnal illumination on life-history decisions and fitness in two wild songbird species. Philos. Trans. R. Soc. Lond. B. Biol. Sci. 370, 1-8 (2015).
23. Moller A. P, Erritzoe J, & Karadas F. Levels of antioxidants in rural and urban birds and their consequences. Oecologia 163, 35-45 (2010).
24. Vanparys C, et al. Metallothioneins (MTs) and delta-Aminolevulinic acid dehydratase (ALAd) as biomarkers of metal pollution in great tits (Parus major) along a pollution gradient. Sci. Total Environ. 401, 184-193 (2008).
25. Koivula M. J, & Eeva T. Metal-related oxidative stress in birds. Environ. Pollut. 158, 2359-2370 (2010).
26. Jaenisch R, & Bird A. Epigenetic regulation of gene expression: how the genome integrates intrinsic and environmental signals. Nat. Genet. 33 Suppl, 245-254 (2003).
27. Fisher M. A, & Oleksiak M. F. Convergence and divergence in gene expression among natural populations exposed to pollution. BMC Genomics 8, 108 (2007).
28. Isaksson C. Pollution and its impact on wild animals: a meta-Analysis on oxidative stress. Ecohealth 7, 342-350 (2010).
29. Delgado-V, C. A, & French K. Parasite-bird interactions in urban areas: current evidence and emerging questions. Landsc. Urban Plan. 105, 5-14 (2012).
30. Mayfield A. B, Wang Y.-B, Chen C.-S, Chen S.-H, & Lin C.-Y. Dual-compartmental transcriptomic+ proteomic analysis of a marine endosymbiosis exposed to environmental change. Mol. Ecol. 2, 5944-5958 (2016).
31. Lu P, Vogel C, Wang R, Yao X, & Marcotte E. M. Absolute protein expression profiling estimates the relative contributions of transcriptional and translational regulation. Nat. Biotechnol. 25, 117-124 (2007).
32. Li J. J, Bickel P. J, & Biggin M. D. System wide analyses have underestimated protein abundances and the importance of transcription in mammals. PeerJ 2, e270 (2014).
33. Schat K. A, Kaspers B, & Kaiser P. Avian Immunology. (Elsevier Ltd 2013).
34. Bradley C. A, & Altizer S. Urbanization and the ecology of wildlife diseases. Trends Ecol. Evol. 22, 95-102 (2007).
35. Bradley C. A, Gibbs S. E. J, & Altizer S. Urban land use predicts West Nile virus exposure in songbirds. Ecol. Appl. 18, 1083-1092 (2008).
36. Moller A. P. Successful city dwellers: a comparative study of the ecological characteristics of urban birds in the Western Palearctic. Oecologia 159, 849-858 (2009).
37. Raberg L, Nilsson J.-A, Ilmonen P, Stjernman M, & Hasselquist D. The cost of an immune response: vaccination reduces parental effort. Ecol. Lett. 3, 382-386 (2000).
38. Libby P. Inflammatory mechanisms: the molecular basis of inflammation and disease. Nutr. Rev. 65, S140-S146 (2007).
39. Calder P. C. Polyunsaturated fatty acids, inflamation and immunity. Eur. J. Clin. Nutr. 56, S14-S19 (2002).
40. Wigley P, et al. Macrophages isolated from chickens genetically resistant or susceptible to systemic salmonellosis show magnitudinal and temporal differential expression of cytokines and chemokines following Salmonella enterica challenge. Infect. Immun. 74, 1425-1430 (2006).
41. Palmquist J. M, et al. In vivo activation of chicken macrophages by infectious bursal disease virus. Viral Immunol. 19, 305-315 (2006).
42. Dalloul R. A, et al. Unique responses of the avian macrophage to different species of Eimeria. Mol. Immunol. 44, 558-566 (2007).
43. Chamanza R, et al. Serum amyloid A and transferrin in chicken. A preliminary investigation of using acute-phase variables to assess diseases in chickens. Vet. Q. 21, 158-162 (1999).
44. Stohs S. J, & Bagchi D. Oxidative mechanisms in the toxicity of metal ions. Free Radic. Biol. Med. 18, 321-336 (1995).
45. Oberdörster G, Stone V, & Donaldson K. Toxicology of nanoparticles: a historical perspective. Nanotoxicology 1, 2-25 (2007).
46. Last J. A, Sun W. M, & Witschi H. Ozone, NO, and NO2: oxidant air pollutants and more. Environ. Health Perspect. 102, S179-S184 (1994).
47. Stroh E, Harrie L, & Gustafsson S. A study of spatial resolution in pollution exposure modelling. Int. J. Health Geogr. 6, 19 (2007).
48. Halliwell B, & Gutteridge J. M. C. Free Radicals in Biology and Medicine. (Oxford University Press, 2007).
49. Ercal N, Gurer-Orhan H, & Aykin-Burns N. Toxic metals and oxidative stress part I: mechanisms involved in metal induced oxidative damage. Curr. Top. Med. Chem. 1, 529-539 (2001).
50. Valavanidis A, Vlahogianni T, Dassenakis M, & Scoullos M. Molecular biomarkers of oxidative stress in aquatic organisms in relation to toxic environmental pollutants. Ecotoxicol. Environ. Saf. 64, 178-189 (2006).
51. Fossi M. C, Leonzio C, Focardi S, Lari L, & Renzoni A. Modulation of mixed-function oxidase activity in black-headed gulls living in anthropogenic environments: biochemical acclimatization or adaptation?. Environ. Toxicol. Chem. 10, 1179-1188 (1991).
52. Andrews G. K. Regulation of metallothionein gene expression by oxidative stress and metal ions. Biochem. Pharmacol. 59, 95-104 (2000).
53. Abel J, & de Ruiter N. Inhibition of hydroxyl-radical-generated DNA degradation by metallothionein. Toxicol. Lett. 47, 191-196 (1989).
54. Lushchak V. I. Environmentally induced oxidative stress in aquatic animals. Aquat. Toxicol. 101, 13-30 (2011).
55. Bauman J. W, Liu J, Liu Y. P, & Klaassen C. D. Increase in metallothionein produced by chemicals that induce oxidative stress. Toxicol. Appl. Pharmacol. 110, 347-354 (1991).
56. Matsuzaki Y, Adachi N, & Koyama H. Vertebrate cells lacking FEN-1 endonuclease are viable but hypersensitive to methylating agents and H2O2. Nucleic Acids Res. 30, 3273-3277 (2002).
57. Salmon P, Nilsson J. F, Nord A, Bensch S, & Isaksson C. Urban environment shortens telomere length in nestling great tits, Parus major. Biol. Lett. 12, 8-11 (2016).
58. Monaghan P, & Haussmann M. F. Do telomere dynamics link lifestyle and lifespan?. Trends Ecol. Evol. 21, 47-53 (2006).
59. Ben-Hamo M, McCue M. D, McWilliams S. R, & Pinshow B. Dietary fatty acid composition influences tissue lipid profiles and regulation of body temperature in Japanese quail. J. Comp. Physiol. B Biochem. Syst. Environ. Physiol. 181, 807-816 (2011).
60. Leonard A. E, et al. Identification and expression of mammalian long-chain PUFA elongation enzymes. Lipids 37, 733-740 (2002).
61. Inagaki K, et al. Identification and expression of a rat fatty acid elongase involved in the biosynthesis of C18 fatty acids. Biosci. Biotechnol. Biochem. 66, 613-621 (2002).
62. Larsson S. C, Kumlin M, Ingelman-Sundberg M, & Wolk A. Dietary long-chain n-3 fatty acids for the prevention of cancer: a review of potential mechanisms. Am. J. Clin. Nutr. 79, 935-945 (2004).
63. Goldberg A. D, Allis C. D, & Bernstein E. Epigenetics: a landscape takes shape. Cell 128, 635-638 (2007).
64. Head J. A. Patterns of DNA methylation in animals: an ecotoxicological perspective. Integr. Comp. Biol. 54, 77-86 (2014).
65. Laine V. N, et al. Evolutionary signals of selection on cognition from the great tit genome and methylome. Nat. Commun. 7, 10474 (2016).
66. Verhulst E. C, et al. Evidence from pyrosequencing indicates that natural variation in animal personality is associated with DRD4 DNA methylation. Mol. Ecol. 25, 1801-1811 (2016).
67. Baccarelli A, et al. Rapid DNA methylation changes after exposure to traffic particles. Am. J. Respir. Crit. Care Med. 179, 572-578 (2009).
68. Baccarelli A, & Bollati V. Epigenetics and environmental chemicals. Curr. Opin. Pediatr. 21, 243-251 (2009).
69. Laird P. W. Cancer epigenetics. Hum. Mol. Genet. 14, R65-R76 (2005).
70. Gluckman P. D, Hanson M. A, Buklijas T, Low F. M, & Beedle A. S. Epigenetic mechanisms that underpin metabolic and cardiovascular diseases. Nat. Rev. Endocrinol. 5, 401-408 (2009).
71. Dolinoy D. C, Weidman J. R, & Jirtle R. L. Epigenetic gene regulation: linking early developmental environment to adult disease. Reprod. Toxicol. 23, 297-307 (2007).
72. Lea A. J, Altmann J, Alberts S. C, & Tung J. Resource base influences genome-wide DNA methylation levels in wild baboons (Papio cynocephalus). Mol. Ecol. 25, 1681-1696 (2016).
73. Frésard L, et al. Epigenetics and phenotypic variability: some interesting insights from birds. Genet. Sel. Evol. 45, 16 (2013).
74. Kim D, et al. TopHat2: accurate alignment of transcriptomes in the presence of insertions, deletions and gene fusions. Genome Biol. 14, R36 (2013).
75. Ellegren H. Evolutionary stasis: the stable chromosomes of birds. Trends Ecol. Evol. 25, 283-91 (2010).
76. Anders S, Pyl P. T, & Huber W. HTSeq-A Python framework to work with high-Throughput sequencing data. Bioinformatics 31, 166-169 (2014).
77. Li H, et al. The Sequence Alignment/Map format and SAMtools. Bioinformatics 25, 2078-2079 (2009).
78. Love M. I, Huber W, & Anders S. Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol. 15, 550 (2014).
79. Benjamini Y, & Hochberg Y. Controlling the false discovery rate: a practical and powerful approach to multiple testing. J. R. Stat. Soc. Ser. B 57, 289-300 (1995).
80. Maere S, Heymans K, & Kuiper M. BiNGO: a Cytoscape plugin to assess overrepresentation of gene ontology categories in biological networks. Bioinformatics 21, 3448-3449 (2005).
81. Supek F, Bošnjak M, Škunca N, & Šmuc T. Revigo summarizes and visualizes long lists of gene ontology terms. PLoS One 6, e21800 (2011).