Natural populations exhibit a great deal of interindividual genetic variation in the response to toxins, exemplified by the variable clinical efficacy of pharmaceutical drugs in humans, and the evolution of pesticide resistant insects. Such variation can result from several phenomena, including variable metabolic detoxification of the xenobiotic, and differential sensitivity of the molecular target of the toxin. Our goal is to genetically dissect variation in the response to xenobiotics, and characterize naturally-segregating polymorphisms that modulate toxicity. Here, we use the Drosophila Synthetic Population Resource (DSPR), a multiparent advanced intercross panel of recombinant inbred lines, to identify QTL (Quantitative Trait Loci) underlying xenobiotic resistance, and employ caffeine as a model toxic compound. Phenotyping over 1,700 genotypes led to the identification of ten QTL, each explaining 4.5–14.4% of the broad-sense heritability for caffeine resistance. Four QTL harbor members of the cytochrome P450 family of detoxification enzymes, which represent strong a priori candidate genes. The case is especially strong for Cyp12d1, with multiple lines of evidence indicating the gene causally impacts caffeine resistance. Cyp12d1 is implicated by QTL mapped in both panels of DSPR RILs, is significantly upregulated in the presence of caffeine, and RNAi knockdown robustly decreases caffeine tolerance. Furthermore, copy number variation at Cyp12d1 is strongly associated with phenotype in the DSPR, with a trend in the same direction observed in the DGRP (Drosophila Genetic Reference Panel). No additional plausible causative polymorphisms were observed in a full genomewide association study in the DGRP, or in analyses restricted to QTL regions mapped in the DSPR. Just as in human populations, replicating modest-effect, naturally-segregating causative variants in an association study framework in flies will likely require very large sample sizes.
References
[1]
Glendinning JI. How do predators cope with chemically defended foods? Biol Bull. 2007;213(3):252–66. pmid:18083965 doi: 10.2307/25066643
[2]
Mithofer A, Boland W. Plant defense against herbivores: chemical aspects. Annu Rev Plant Biol. 2012;63:431–50. doi: 10.1146/annurev-arplant-042110-103854. pmid:22404468
[3]
Zhong W, Maradit-Kremers H, St Sauver JL, Yawn BP, Ebbert JO, Roger VL, et al. Age and sex patterns of drug prescribing in a defined American population. Mayo Clin Proc. 2013;88(7):697–707. doi: 10.1016/j.mayocp.2013.04.021. pmid:23790544
[4]
Holzinger F, Frick C, Wink M. Molecular basis for the insensitivity of the Monarch (Danaus plexippus) to cardiac glycosides. FEBS Lett. 1992;314(3):477–80. pmid:1334851 doi: 10.1016/0014-5793(92)81530-y
[5]
Zhen Y, Aardema ML, Medina EM, Schumer M, Andolfatto P. Parallel molecular evolution in an herbivore community. Science. 2012;337(6102):1634–7. pmid:23019645 doi: 10.1126/science.1226630
[6]
Li X, Schuler MA, Berenbaum MR. Molecular mechanisms of metabolic resistance to synthetic and natural xenobiotics. Annu Rev Entomol. 2007;52:231–53. pmid:16925478 doi: 10.1146/annurev.ento.51.110104.151104
[7]
Xu C, Li CY, Kong AN. Induction of phase I, II and III drug metabolism/transport by xenobiotics. Arch Pharm Res. 2005;28(3):249–68. pmid:15832810 doi: 10.1007/bf02977789
[8]
Snyder MJ, Glendinning JI. Causal connection between detoxification enzyme activity and consumption of a toxic plant compound. J Comp Physiol A. 1996;179(2):255–61. pmid:8765561 doi: 10.1007/bf00222792
[9]
Wink M, Theile V. Alkaloid tolerance in Manduca sexta and phylogenetically related sphingids (Lepidoptera: Sphingidae). Chemoecology. 2002;12:29–46. doi: 10.1007/s00049-002-8324-2
[10]
Chung H, Bogwitz MR, McCart C, Andrianopoulos A, Ffrench-Constant RH, Batterham P, et al. Cis-regulatory elements in the Accord retrotransposon result in tissue-specific expression of the Drosophila melanogaster insecticide resistance gene Cyp6g1. Genetics. 2007;175(3):1071–7. pmid:17179088 doi: 10.1534/genetics.106.066597
[11]
Daborn PJ, Yen JL, Bogwitz MR, Le Goff G, Feil E, Jeffers S, et al. A single p450 allele associated with insecticide resistance in Drosophila. Science. 2002;297(5590):2253–6. pmid:12351787 doi: 10.1126/science.1074170
[12]
Schmidt JM, Good RT, Appleton B, Sherrard J, Raymant GC, Bogwitz MR, et al. Copy number variation and transposable elements feature in recent, ongoing adaptation at the Cyp6g1 locus. PLoS Genet. 2010;6(6):e1000998. doi: 10.1371/journal.pgen.1000998. pmid:20585622
[13]
Carrillo R, Gibson G. Unusual genetic architecture of natural variation affecting drug resistance in Drosophila melanogaster. Genet Res. 2002;80(3):205–13. pmid:12688659 doi: 10.1017/s0016672302005888
[14]
King EG, Kislukhin G, Walters KN, Long AD. Using Drosophila melanogaster to identify chemotherapy toxicity genes. Genetics. 2014;198(1):31–43. doi: 10.1534/genetics.114.161968. pmid:25236447
[15]
Marriage TN, King EG, Long AD, Macdonald SJ. Fine-mapping nicotine resistance loci in Drosophila using a multiparent advanced generation inter-cross population. Genetics. 2014;198(1):45–57. doi: 10.1534/genetics.114.162107. pmid:25236448
[16]
Ge D, Fellay J, Thompson AJ, Simon JS, Shianna KV, Urban TJ, et al. Genetic variation in IL28B predicts hepatitis C treatment-induced viral clearance. Nature. 2009;461(7262):399–401. doi: 10.1038/nature08309. pmid:19684573
[17]
Shuldiner AR, O'Connell JR, Bliden KP, Gandhi A, Ryan K, Horenstein RB, et al. Association of cytochrome P450 2C19 genotype with the antiplatelet effect and clinical efficacy of clopidogrel therapy. JAMA. 2009;302(8):849–57. doi: 10.1001/jama.2009.1232. pmid:19706858
[18]
Takeuchi F, McGinnis R, Bourgeois S, Barnes C, Eriksson N, Soranzo N, et al. A genome-wide association study confirms VKORC1, CYP2C9, and CYP4F2 as principal genetic determinants of warfarin dose. PLoS Genet. 2009;5(3):e1000433. doi: 10.1371/journal.pgen.1000433. pmid:19300499
[19]
Bhaskara S, Dean ED, Lam V, Ganguly R. Induction of two cytochrome P450 genes, Cyp6a2 and Cyp6a8, of Drosophila melanogaster by caffeine in adult flies and in cell culture. Gene. 2006;377:56–64. pmid:16713132 doi: 10.1016/j.gene.2006.02.032
Morra R, Kuruganti S, Lam V, Lucchesi JC, Ganguly R. Functional analysis of the cis-acting elements responsible for the induction of the Cyp6a8 and Cyp6g1 genes of Drosophila melanogaster by DDT, phenobarbital and caffeine. Insect Mol Biol. 2010;19(1):121–30. doi: 10.1111/j.1365-2583.2009.00954.x. pmid:20002224
[22]
Willoughby L, Chung H, Lumb C, Robin C, Batterham P, Daborn PJ. A comparison of Drosophila melanogaster detoxification gene induction responses for six insecticides, caffeine and phenobarbital. Insect Biochem Mol Biol. 2006;36(12):934–42. pmid:17098168 doi: 10.1016/j.ibmb.2006.09.004
[23]
Churchill GA, Airey DC, Allayee H, Angel JM, Attie AD, Beatty J, et al. The Collaborative Cross, a community resource for the genetic analysis of complex traits. Nat Genet. 2004;36(11):1133–7. pmid:15514660 doi: 10.1038/ng1104-1133
[24]
Kover PX, Valdar W, Trakalo J, Scarcelli N, Ehrenreich IM, Purugganan MD, et al. A Multiparent Advanced Generation Inter-Cross to fine-map quantitative traits in Arabidopsis thaliana. PLoS Genet. 2009;5(7):e1000551. doi: 10.1371/journal.pgen.1000551. pmid:19593375
[25]
Macdonald SJ, Long AD. Joint estimates of quantitative trait locus effect and frequency using synthetic recombinant populations of Drosophila melanogaster. Genetics. 2007;176(2):1261–81. pmid:17435224 doi: 10.1534/genetics.106.069641
[26]
Rat Genome S, Mapping C, Baud A, Hermsen R, Guryev V, Stridh P, et al. Combined sequence-based and genetic mapping analysis of complex traits in outbred rats. Nat Genet. 2013;45(7):767–75. doi: 10.1038/ng.2644. pmid:23708188
[27]
Svenson KL, Gatti DM, Valdar W, Welsh CE, Cheng R, Chesler EJ, et al. High-resolution genetic mapping using the Mouse Diversity outbred population. Genetics. 2012;190(2):437–47. doi: 10.1534/genetics.111.132597. pmid:22345611
[28]
Threadgill DW, Churchill GA. Ten years of the collaborative cross. G3 (Bethesda). 2012;2(2):153–6. doi: 10.1534/g3.111.001891
[29]
Valdar W, Flint J, Mott R. Simulating the collaborative cross: power of quantitative trait loci detection and mapping resolution in large sets of recombinant inbred strains of mice. Genetics. 2006;172(3):1783–97. pmid:16361245 doi: 10.1534/genetics.104.039313
[30]
King EG, Macdonald SJ, Long AD. Properties and power of the Drosophila Synthetic Population Resource for the routine dissection of complex traits. Genetics. 2012;191(3):935–49. doi: 10.1534/genetics.112.138537. pmid:22505626
[31]
King EG, Merkes CM, McNeil CL, Hoofer SR, Sen S, Broman KW, et al. Genetic dissection of a model complex trait using the Drosophila Synthetic Population Resource. Genome Res. 2012;22(8):1558–66. doi: 10.1101/gr.134031.111. pmid:22496517
[32]
Kislukhin G, King EG, Walters KN, Macdonald SJ, Long AD. The genetic architecture of methotrexate toxicity is similar in Drosophila melanogaster and humans. G3 (Bethesda). 2013;3(8):1301–10. doi: 10.1534/g3.113.006619
[33]
Huang W, Massouras A, Inoue Y, Peiffer J, Ramia M, Tarone AM, et al. Natural variation in genome architecture among 205 Drosophila melanogaster Genetic Reference Panel lines. Genome Res. 2014;24(7):1193–208. doi: 10.1101/gr.171546.113. pmid:24714809
[34]
Mackay TF, Richards S, Stone EA, Barbadilla A, Ayroles JF, Zhu D, et al. The Drosophila melanogaster Genetic Reference Panel. Nature. 2012;482(7384):173–8. doi: 10.1038/nature10811. pmid:22318601
[35]
Ivanov DK, Escott-Price V, Ziehm M, Magwire MM, Mackay TF, Partridge L, et al. Longevity GWAS Using the Drosophila Genetic Reference Panel. J Gerontol A Biol Sci Med Sci. 2015. doi: 10.1093/gerona/glv047
[36]
King EG, Sanderson BJ, McNeil CL, Long AD, Macdonald SJ. Genetic dissection of the Drosophila melanogaster female head transcriptome reveals widespread allelic heterogeneity. PLoS Genet. 2014;10(5):e1004322. doi: 10.1371/journal.pgen.1004322. pmid:24810915
[37]
Giraud H, Lehermeier C, Bauer E, Falque M, Segura V, Bauland C, et al. Linkage disequilibrium with linkage analysis of multiline crosses reveals different multiallelic QTL for hybrid performance in the flint and dent heterotic groups of maize. Genetics. 2014;198(4):1717–34. doi: 10.1534/genetics.114.169367. pmid:25271305
[38]
Stankiewicz P, Lupski JR. Structural variation in the human genome and its role in disease. Annu Rev Med. 2010;61:437–55. doi: 10.1146/annurev-med-100708-204735. pmid:20059347
[39]
Weischenfeldt J, Symmons O, Spitz F, Korbel JO. Phenotypic impact of genomic structural variation: insights from and for human disease. Nat Rev Genet. 2013;14(2):125–38. doi: 10.1038/nrg3373. pmid:23329113
[40]
Zichner T, Garfield DA, Rausch T, Stutz AM, Cannavo E, Braun M, et al. Impact of genomic structural variation in Drosophila melanogaster based on population-scale sequencing. Genome Res. 2013;23(3):568–79. doi: 10.1101/gr.142646.112. pmid:23222910
[41]
Good RT, Gramzow L, Battlay P, Sztal T, Batterham P, Robin C. The molecular evolution of cytochrome P450 genes within and between Drosophila species. Genome Biol Evol. 2014;6(5):1118–34. doi: 10.1093/gbe/evu083. pmid:24751979
[42]
McDonnell CM, King D, Comeron JM, Li H, Sun W, Berenbaum MR, et al. Evolutionary toxicogenomics: diversification of the Cyp12d1 and Cyp12d3 genes in Drosophila species. J Mol Evol. 2012;74(5–6):281–96. doi: 10.1007/s00239-012-9506-3. pmid:22811321
[43]
Schrider DR, Begun DJ, Hahn MW. Detecting highly differentiated copy-number variants from pooled population sequencing. Pac Symp Biocomput. 2013:344–55. pmid:23424139 doi: 10.1142/9789814447973_0034
[44]
Adams MD, Celniker SE, Holt RA, Evans CA, Gocayne JD, Amanatides PG, et al. The genome sequence of Drosophila melanogaster. Science. 2000;287(5461):2185–95. pmid:10731132 doi: 10.1126/science.287.5461.2185
[45]
St Pierre SE, Ponting L, Stefancsik R, McQuilton P, FlyBase C. FlyBase 102—advanced approaches to interrogating FlyBase. Nucleic Acids Res. 2014;42(Database issue):D780–8. doi: 10.1093/nar/gkt1092. pmid:24234449
[46]
Mitchell CL, Saul MC, Lei L, Wei H, Werner T. The mechanisms underlying alpha-amanitin resistance in Drosophila melanogaster: a microarray analysis. PLoS One. 2014;9(4):e93489. doi: 10.1371/journal.pone.0093489. pmid:24695618
[47]
Coelho A, Fraichard S, Le Goff G, Faure P, Artur Y, Ferveur JF, et al. Cytochrome P450-dependent metabolism of caffeine in Drosophila melanogaster. PLoS One. 2015;10(2):e0117328. doi: 10.1371/journal.pone.0117328. pmid:25671424
[48]
Sztal T, Chung H, Berger S, Currie PD, Batterham P, Daborn PJ. A cytochrome p450 conserved in insects is involved in cuticle formation. PLoS One. 2012;7(5):e36544. doi: 10.1371/journal.pone.0036544. pmid:22574182
[49]
Osterwalder T, Yoon KS, White BH, Keshishian H. A conditional tissue-specific transgene expression system using inducible GAL4. Proc Natl Acad Sci U S A. 2001;98(22):12596–601. pmid:11675495 doi: 10.1073/pnas.221303298
[50]
Long AD, Macdonald SJ, King EG. Dissecting complex traits using the Drosophila Synthetic Population Resource. Trends Genet. 2014;30(11):488–95. doi: 10.1016/j.tig.2014.07.009. pmid:25175100
[51]
Turner TL, Miller PM, Cochrane VA. Combining genome-wide methods to investigate the genetic complexity of courtship song variation in Drosophila melanogaster. Mol Biol Evol. 2013;30(9):2113–20. doi: 10.1093/molbev/mst111. pmid:23777628
[52]
Beavis W. The power and deceit of QTL experiments: lessons from comparative QTL studies. Proceedings of the 49th Annual Corn and Sorghum Industry Research Conference. Washington, DC: American Seed Trade Association; 1994. p. 250–66.
[53]
Xu S. Theoretical basis of the Beavis effect. Genetics. 2003;165(4):2259–68. pmid:14704201
[54]
Parker CC, Carbonetto P, Sokoloff G, Park YJ, Abney M, Palmer AA. High-resolution genetic mapping of complex traits from a combined analysis of F2 and advanced intercross mice. Genetics. 2014;198(1):103–16. doi: 10.1534/genetics.114.167056. pmid:25236452
[55]
Chung H, Sztal T, Pasricha S, Sridhar M, Batterham P, Daborn PJ. Characterization of Drosophila melanogaster cytochrome P450 genes. Proc Natl Acad Sci U S A. 2009;106(14):5731–6. doi: 10.1073/pnas.0812141106. pmid:19289821
[56]
Harrop TW, Pearce SL, Daborn PJ, Batterham P. Whole-genome expression analysis in the third instar larval midgut of Drosophila melanogaster. G3 (Bethesda). 2014;4(11):2197–205. doi: 10.1534/g3.114.013870
[57]
Stranger BE, Forrest MS, Dunning M, Ingle CE, Beazley C, Thorne N, et al. Relative impact of nucleotide and copy number variation on gene expression phenotypes. Science. 2007;315(5813):848–53. pmid:17289997 doi: 10.1126/science.1136678
[58]
Li X, Zhuo R, Tiong S, Di Cara F, King-Jones K, Hughes SC, et al. The Smc5/Smc6/MAGE complex confers resistance to caffeine and genotoxic stress in Drosophila melanogaster. PLoS One. 2013;8(3):e59866. doi: 10.1371/journal.pone.0059866. pmid:23555814
Sun W, Valero MC, Seong KM, Steele LD, Huang IT, Lee CH, et al. A glycine insertion in the estrogen-related receptor (ERR) is associated with enhanced expression of three cytochrome P450 genes in transgenic Drosophila melanogaster. PLoS One. 2015;10(3):e0118779. doi: 10.1371/journal.pone.0118779. pmid:25761142
[61]
Lee Y, Moon SJ, Montell C. Multiple gustatory receptors required for the caffeine response in Drosophila. Proc Natl Acad Sci U S A. 2009;106(11):4495–500. doi: 10.1073/pnas.0811744106. pmid:19246397
[62]
Moon SJ, Kottgen M, Jiao Y, Xu H, Montell C. A taste receptor required for the caffeine response in vivo. Curr Biol. 2006;16(18):1812–7. pmid:16979558 doi: 10.1016/j.cub.2006.07.024
[63]
Lynch M, Walsh B. Genetics and Analysis of Quantitative Traits. Sunderland, Massachusetts: Sinauer Associates, Inc; 1998.
[64]
Pritchard JK. Are rare variants responsible for susceptibility to complex diseases? Am J Hum Genet. 2001;69(1):124–37. pmid:11404818
[65]
Thornton KR, Foran AJ, Long AD. Properties and modeling of GWAS when complex disease risk is due to non-complementing, deleterious mutations in genes of large effect. PLoS Genet. 2013;9(2):e1003258. doi: 10.1371/journal.pgen.1003258. pmid:23437004
[66]
DIAbetes Genetics Replication Meta-analysis, et al. Genome-wide trans-ancestry meta-analysis provides insight into the genetic architecture of type 2 diabetes susceptibility. Nat Genet. 2014;46(3):234–44. doi: 10.1038/ng.2897. pmid:24509480
[67]
Stone EA. Joint genotyping on the fly: identifying variation among a sequenced panel of inbred lines. Genome Res. 2012;22(5):966–74. doi: 10.1101/gr.129122.111. pmid:22367192
[68]
Pinheiro J, Bates D, DebRoy S, Sarkar D, Team RDC. nlme: linear and nonlinear mixed effects models. R package version 31–101. 2011.
Kim D, Pertea G, Trapnell C, Pimentel H, Kelley R, Salzberg SL. TopHat2: accurate alignment of transcriptomes in the presence of insertions, deletions and gene fusions. Genome Biol. 2013;14(4):R36. doi: 10.1186/gb-2013-14-4-r36. pmid:23618408
[71]
Trapnell C, Pachter L, Salzberg SL. TopHat: discovering splice junctions with RNA-Seq. Bioinformatics. 2009;25(9):1105–11. doi: 10.1093/bioinformatics/btp120. pmid:19289445
[72]
Trapnell C, Hendrickson DG, Sauvageau M, Goff L, Rinn JL, Pachter L. Differential analysis of gene regulation at transcript resolution with RNA-seq. Nat Biotechnol. 2013;31(1):46–53. doi: 10.1038/nbt.2450. pmid:23222703
[73]
Trapnell C, Williams BA, Pertea G, Mortazavi A, Kwan G, van Baren MJ, et al. Transcript assembly and quantification by RNA-Seq reveals unannotated transcripts and isoform switching during cell differentiation. Nat Biotechnol. 2010;28(5):511–5. doi: 10.1038/nbt.1621. pmid:20436464
[74]
Dietzl G, Chen D, Schnorrer F, Su KC, Barinova Y, Fellner M, et al. A genome-wide transgenic RNAi library for conditional gene inactivation in Drosophila. Nature. 2007;448(7150):151–6. pmid:17625558 doi: 10.1038/nature05954
[75]
Green EW, Fedele G, Giorgini F, Kyriacou CP. A Drosophila RNAi collection is subject to dominant phenotypic effects. Nat Methods. 2014;11(3):222–3. doi: 10.1038/nmeth.2856. pmid:24577271
[76]
Broman K, Sen S. A Guide to QTL Mapping with R/qtl. New York: Springer Dordrecht; 2009.