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Quantitative Trait Loci (QTL) Mapping

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eQTL Analysis

Part of the book series: Methods in Molecular Biology ((MIMB,volume 2082))

Abstract

Quantitative trait loci (QTL) are genetic regions that influence phenotypic variation of a complex trait, often through genetic interactions with each other and the environment. These are commonly identified through a statistical genetic analysis known as QTL mapping. Here, I present a step-by-step, practical approach to QTL mapping along with a sample data file. I focus on methods commonly used and discoveries that have been made in fishes, and utilize a multiple QTL mapping (MQM) approach in the free software package R/qtl.

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References

  1. Alberch P (1991) From genes to phenotype: dynamical systems and evolvability. Genetica 84(1):5–11

    Article  CAS  PubMed  Google Scholar 

  2. Wagner GP, Altenberg L (1996) Perspective: complex adaptations and the evolution of evolvability. Evolution 50(3):967–976. https://doi.org/10.1111/j.1558-5646.1996.tb02339.x

    Article  PubMed  Google Scholar 

  3. Castle WE (1921) An improved method of estimating the number of genetic factors concerned in cases of blending inheritance. Science 54(1393):223. https://doi.org/10.1126/science.54.1393.223

    Article  CAS  PubMed  Google Scholar 

  4. Fisher RA (1918) The correlation between relatives on the supposition of Mendelian inheritance. Trans R Soc Edinburgh 52:399–433

    Article  Google Scholar 

  5. Haldane JBS (1932) The causes of evolution. Harper and Brothers, London

    Google Scholar 

  6. Wright S (1921) Systems of mating. I. the biometric relations between parent and offspring. Genetics 6(2):111–123

    CAS  PubMed  PubMed Central  Google Scholar 

  7. Wright S (1968) Evolution and genetics of populations, vol 1. University of Chicago Press, Chicago

    Google Scholar 

  8. Lynch M, Walsh B (1998) Genetics and analysis of quantitative traits. Sinauer, Sunderland, MA

    Google Scholar 

  9. Broman KW, Sen S (2009) A guide to QTL mapping with R/qtl. Springer, New York

    Book  Google Scholar 

  10. Falconer DS, Mackay TFC (2009) Introduction to quantitative genetics, 4th edn. Pearson, London

    Google Scholar 

  11. Arends D, Prins P, Jansen RC, Broman KW (2010) R/qtl: high-throughput multiple QTL mapping. Bioinformatics 26(23):2990–2992. https://doi.org/10.1093/bioinformatics/btq565

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  12. Rifkin SA (2012) Quantitative trait loci (QTL): methods and protocols. Methods in molecular biology. Humana Press, Totowa, NJ

    Book  Google Scholar 

  13. Doerge RW (2002) Mapping and analysis of quantitative trait loci in experimental populations. Nat Rev Genet 3(1):43–52. https://doi.org/10.1038/nrg703

    Article  CAS  PubMed  Google Scholar 

  14. Mackay TF, Stone EA, Ayroles JF (2009) The genetics of quantitative traits: challenges and prospects. Nat Rev Genet 10(8):565–577. https://doi.org/10.1038/nrg2612

    Article  CAS  PubMed  Google Scholar 

  15. Mackay TF, Fry JD (1996) Polygenic mutation in Drosophila melanogaster: genetic interactions between selection lines and candidate quantitative trait loci. Genetics 144(2):671–688

    CAS  PubMed  PubMed Central  Google Scholar 

  16. Mackay TF (1996) The nature of quantitative genetic variation revisited: lessons from Drosophila bristles. BioEssays 18(2):113–121. https://doi.org/10.1002/bies.950180207

    Article  CAS  PubMed  Google Scholar 

  17. Keightley PD, Hardge T, May L, Bulfield G (1996) A genetic map of quantitative trait loci for body weight in the mouse. Genetics 142(1):227–235

    CAS  PubMed  PubMed Central  Google Scholar 

  18. Johnson TE, DeFries JC, Markel PD (1992) Mapping quantitative trait loci for behavioral traits in the mouse. Behav Genet 22(6):635–653

    Article  CAS  PubMed  Google Scholar 

  19. Cheverud JM, Routman EJ, Duarte FA, van Swinderen B, Cothran K, Perel C (1996) Quantitative trait loci for murine growth. Genetics 142(4):1305–1319

    CAS  PubMed  PubMed Central  Google Scholar 

  20. Diers BW, Keim P, Fehr WR, Shoemaker RC (1992) RFLP analysis of soybean seed protein and oil content. Theor Appl Genet 83(5):608–612. https://doi.org/10.1007/BF00226905

    Article  CAS  PubMed  Google Scholar 

  21. Pe ME, Gianfranceschi L, Taramino G, Tarchini R, Angelini P, Dani M, Binelli G (1993) Mapping quantitative trait loci (QTLs) for resistance to Gibberella zeae infection in maize. Mol Gen Genet 241(1-2):11–16

    Google Scholar 

  22. Laurie DA, Pratchett N, Snape JW, Bezant JH (1995) RFLP mapping of five major genes and eight quantitative trait loci controlling flowering time in a winter x spring barley (Hordeum vulgare L.) cross. Genome 38(3):575–585

    Article  CAS  PubMed  Google Scholar 

  23. Veldboom LR, Lee M (1994) Molecular-marker-facilitated studies of morphological traits in maize. II: determination of QTLs for grain yield and yield components. Theor Appl Genet 89(4):451–458. https://doi.org/10.1007/BF00225380

    Article  CAS  PubMed  Google Scholar 

  24. Edwards MD, Stuber CW, Wendel JF (1987) Molecular-marker-facilitated investigations of quantitative-trait loci in maize. I. Numbers, genomic distribution and types of gene action. Genetics 116(1):113–125

    CAS  PubMed  PubMed Central  Google Scholar 

  25. Sucena E, Stern DL (2000) Divergence of larval morphology between Drosophila sechellia and its sibling species caused by cis-regulatory evolution of ovo/shaven-baby. Proc Natl Acad Sci U S A 97(9):4530–4534

    Article  CAS  Google Scholar 

  26. Liu J, Mercer JM, Stam LF, Gibson GC, Zeng ZB, Laurie CC (1996) Genetic analysis of a morphological shape difference in the male genitalia of Drosophila simulans and D. mauritiana. Genetics 142(4):1129–1145

    Google Scholar 

  27. True JR, Liu J, Stam LF, Zeng ZB, Laurie CC (1997) Quantitative genetic analysis of divergence in male secondary sexual traits between Drosophila simulans and Drosophila mauritiana. Evolution 51(3):816–832. https://doi.org/10.1111/j.1558-5646.1997.tb03664.x

    Article  PubMed  Google Scholar 

  28. Doebley J (2004) The genetics of maize evolution. Annu Rev Genet 38:37–59. https://doi.org/10.1146/annurev.genet.38.072902.092425

    Article  CAS  PubMed  Google Scholar 

  29. Kodama M, Hard JJ, Naish KA (2018) Mapping of quantitative trait loci for temporal growth and age at maturity in coho salmon: evidence for genotype-by-sex interactions. Mar Genomics 38:33–44. https://doi.org/10.1016/j.margen.2017.07.004

    Article  PubMed  Google Scholar 

  30. Fu B, Liu H, Yu X, Tong J (2016) A high-density genetic map and growth related QTL mapping in bighead carp (Hypophthalmichthys nobilis). Sci Rep 6:28679. https://doi.org/10.1038/srep28679

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  31. Wringe BF, Devlin RH, Ferguson MM, Moghadam HK, Sakhrani D, Danzmann RG (2010) Growth-related quantitative trait loci in domestic and wild rainbow trout (Oncorhynchus mykiss). BMC Genet 11:63. https://doi.org/10.1186/1471-2156-11-63

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  32. Liu H, Fu B, Pang M, Feng X, Yu X, Tong J (2017) A high-density genetic linkage map and QTL fine mapping for body weight in crucian carp (Carassius auratus) using 2b-RAD sequencing. G3 (Bethesda) 7(8):2473–2487. https://doi.org/10.1534/g3.117.041376

    Article  CAS  Google Scholar 

  33. Lin G, Chua E, Orban L, Yue GH (2016) Mapping QTL for sex and growth traits in salt-tolerant tilapia (Oreochromis spp. X O. mossambicus). PLoS One 11(11):e0166723. https://doi.org/10.1371/journal.pone.0166723

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  34. Wang L, Wan ZY, Bai B, Huang SQ, Chua E, Lee M, Pang HY, Wen YF, Liu P, Liu F, Sun F, Lin G, Ye BQ, Yue GH (2015) Construction of a high-density linkage map and fine mapping of QTL for growth in Asian seabass. Sci Rep 5:16358. https://doi.org/10.1038/srep16358

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  35. Miller CT, Glazer AM, Summers BR, Blackman BK, Norman AR, Shapiro MD, Cole BL, Peichel CL, Schluter D, Kingsley DM (2014) Modular skeletal evolution in sticklebacks is controlled by additive and clustered quantitative trait Loci. Genetics 197(1):405–420. https://doi.org/10.1534/genetics.114.162420

    Article  PubMed  PubMed Central  Google Scholar 

  36. Albertson RC, Streelman JT, Kocher TD, Yelick PC (2005) Integration and evolution of the cichlid mandible: the molecular basis of alternate feeding strategies. Proc Natl Acad Sci U S A 102(45):16287–16292. https://doi.org/10.1073/pnas.0506649102

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  37. Albertson RC, Streelman JT, Kocher TD (2003) Directional selection has shaped the oral jaws of Lake Malawi cichlid fishes. Proc Natl Acad Sci U S A 100(9):5252–5257. https://doi.org/10.1073/pnas.0930235100

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  38. Hulsey CD, Machado-Schiaffino G, Keicher L, Ellis-Soto D, Henning F, Meyer A (2017) The integrated genomic architecture and evolution of dental divergence in East African cichlid fishes (Haplochromis chilotes x H. nyererei). G3 (Bethesda) 7(9):3195–3202. https://doi.org/10.1534/g3.117.300083

    Article  CAS  Google Scholar 

  39. Streelman JT, Albertson RC (2006) Evolution of novelty in the cichlid dentition. J Exp Zool B Mol Dev Evol 306(3):216–226. https://doi.org/10.1002/jez.b.21101

    Article  CAS  PubMed  Google Scholar 

  40. Peichel CL, Nereng KS, Ohgi KA, Cole BL, Colosimo PF, Buerkle CA, Schluter D, Kingsley DM (2001) The genetic architecture of divergence between threespine stickleback species. Nature 414(6866):901–905. https://doi.org/10.1038/414901a

    Article  CAS  PubMed  Google Scholar 

  41. Albertson RC, Kawasaki KC, Tetrault ER, Powder KE (2018) Genetic analyses in Lake Malawi cichlids identify new roles for Fgf signaling in scale shape variation. Commun Biol 1:55. https://doi.org/10.1038/s42003-018-0060-4

    Article  PubMed  PubMed Central  Google Scholar 

  42. Navon D, Olearczyk N, Albertson RC (2017) Genetic and developmental basis for fin shape variation in African cichlid fishes. Mol Ecol 26(1):291–303. https://doi.org/10.1111/mec.13905

    Article  CAS  PubMed  Google Scholar 

  43. O’Quin KE, Yoshizawa M, Doshi P, Jeffery WR (2013) Quantitative genetic analysis of retinal degeneration in the blind cavefish Astyanax mexicanus. PLoS One 8(2):e57281. https://doi.org/10.1371/journal.pone.0057281

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  44. Liu J, Shikano T, Leinonen T, Cano JM, Li MH, Merila J (2014) Identification of major and minor QTL for ecologically important morphological traits in three-spined sticklebacks (Gasterosteus aculeatus). G3 (Bethesda) 4(4):595–604. https://doi.org/10.1534/g3.114.010389

    Article  Google Scholar 

  45. Cresko WA, Amores A, Wilson C, Murphy J, Currey M, Phillips P, Bell MA, Kimmel CB, Postlethwait JH (2004) Parallel genetic basis for repeated evolution of armor loss in Alaskan threespine stickleback populations. Proc Natl Acad Sci U S A 101(16):6050–6055. https://doi.org/10.1073/pnas.0308479101

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  46. Colosimo PF, Peichel CL, Nereng K, Blackman BK, Shapiro MD, Schluter D, Kingsley DM (2004) The genetic architecture of parallel armor plate reduction in threespine sticklebacks. PLoS Biol 2(5):E109. https://doi.org/10.1371/journal.pbio.0020109

    Article  PubMed  PubMed Central  Google Scholar 

  47. Shapiro MD, Marks ME, Peichel CL, Blackman BK, Nereng KS, Jonsson B, Schluter D, Kingsley DM (2004) Genetic and developmental basis of evolutionary pelvic reduction in threespine sticklebacks. Nature 428(6984):717–723. https://doi.org/10.1038/nature02415

    Article  CAS  PubMed  Google Scholar 

  48. Klingenberg CP (2010) Evolution and development of shape: integrating quantitative approaches. Nat Rev Genet 11(9):623–635. https://doi.org/10.1038/nrg2829

    Article  CAS  PubMed  Google Scholar 

  49. Mitteroecker P, Gunz P (2009) Advances in geometric morphometrics. Evol Biol 36:235–247

    Article  Google Scholar 

  50. Li Z, Guo B, Yang J, Herczeg G, Gonda A, Balazs G, Shikano T, Calboli FC, Merila J (2017) Deciphering the genomic architecture of the stickleback brain with a novel multilocus gene-mapping approach. Mol Ecol 26(6):1557–1575. https://doi.org/10.1111/mec.14005

    Article  CAS  PubMed  Google Scholar 

  51. Stewart TA, Albertson RC (2010) Evolution of a unique predatory feeding apparatus: functional anatomy, development and a genetic locus for jaw laterality in Lake Tanganyika scale-eating cichlids. BMC Biol 8:8. https://doi.org/10.1186/1741-7007-8-8

    Article  PubMed  PubMed Central  Google Scholar 

  52. Franchini P, Fruciano C, Spreitzer ML, Jones JC, Elmer KR, Henning F, Meyer A (2014) Genomic architecture of ecologically divergent body shape in a pair of sympatric crater lake cichlid fishes. Mol Ecol 23(7):1828–1845. https://doi.org/10.1111/mec.12590

    Article  PubMed  Google Scholar 

  53. Fruciano C, Franchini P, Kovacova V, Elmer KR, Henning F, Meyer A (2016) Genetic linkage of distinct adaptive traits in sympatrically speciating crater lake cichlid fish. Nat Commun 7:12736. https://doi.org/10.1038/ncomms12736

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  54. Parsons KJ, Wang J, Anderson G, Albertson RC (2015) Nested levels of adaptive divergence: the genetic basis of craniofacial divergence and ecological sexual dimorphism. G3 (Bethesda) 5(8):1613–1624. https://doi.org/10.1534/g3.115.018226

    Article  CAS  Google Scholar 

  55. Streelman JT, Albertson RC, Kocher TD (2003) Genome mapping of the orange blotch colour pattern in cichlid fishes. Mol Ecol 12(9):2465–2471

    Article  CAS  PubMed  Google Scholar 

  56. Albertson RC, Powder KE, Hu Y, Coyle KP, Roberts RB, Parsons KJ (2014) Genetic basis of continuous variation in the levels and modular inheritance of pigmentation in cichlid fishes. Mol Ecol 23(21):5135–5150. https://doi.org/10.1111/mec.12900

    Article  PubMed  PubMed Central  Google Scholar 

  57. Gross JB, Borowsky R, Tabin CJ (2009) A novel role for Mc1r in the parallel evolution of depigmentation in independent populations of the cavefish Astyanax mexicanus. PLoS Genet 5(1):e1000326. https://doi.org/10.1371/journal.pgen.1000326

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  58. Yong L, Peichel CL, McKinnon JS (2015) Genetic architecture of conspicuous red ornaments in female threespine stickleback. G3 (Bethesda) 6(3):579–588. https://doi.org/10.1534/g3.115.024505

    Article  Google Scholar 

  59. Tsuboko S, Kimura T, Shinya M, Suehiro Y, Okuyama T, Shimada A, Takeda H, Naruse K, Kubo T, Takeuchi H (2014) Genetic control of startle behavior in medaka fish. PLoS One 9(11):e112527. https://doi.org/10.1371/journal.pone.0112527

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  60. Greenwood AK, Ardekani R, McCann SR, Dubin ME, Sullivan A, Bensussen S, Tavare S, Peichel CL (2015) Genetic mapping of natural variation in schooling tendency in the threespine stickleback. G3 (Bethesda) 5(5):761–769. https://doi.org/10.1534/g3.114.016519

    Article  Google Scholar 

  61. Wright D, Butlin RK, Carlborg O (2006) Epistatic regulation of behavioural and morphological traits in the zebrafish (Danio rerio). Behav Genet 36(6):914–922. https://doi.org/10.1007/s10519-006-9080-9

    Article  PubMed  Google Scholar 

  62. Wright D, Nakamichi R, Krause J, Butlin RK (2006) QTL analysis of behavioral and morphological differentiation between wild and laboratory zebrafish (Danio rerio). Behav Genet 36(2):271–284. https://doi.org/10.1007/s10519-005-9029-4

    Article  PubMed  Google Scholar 

  63. Waits ER, Nebert DW (2011) Genetic architecture of susceptibility to PCB126-induced developmental cardiotoxicity in zebrafish. Toxicol Sci 122(2):466–475. https://doi.org/10.1093/toxsci/kfr136

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  64. Nacci D, Proestou D, Champlin D, Martinson J, Waits ER (2016) Genetic basis for rapidly evolved tolerance in the wild: adaptation to toxic pollutants by an estuarine fish species. Mol Ecol 25(21):5467–5482. https://doi.org/10.1111/mec.13848

    Article  CAS  PubMed  Google Scholar 

  65. Palaiokostas C, Cariou S, Bestin A, Bruant JS, Haffray P, Morin T, Cabon J, Allal F, Vandeputte M, Houston RD (2018) Genome-wide association and genomic prediction of resistance to viral nervous necrosis in European sea bass (Dicentrarchus labrax) using RAD sequencing. Genet Sel Evol 50(1):30. https://doi.org/10.1186/s12711-018-0401-2

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  66. Wang L, Liu P, Huang S, Ye B, Chua E, Wan ZY, Yue GH (2017) Genome-Wide Association Study identifies loci associated with resistance to viral nervous necrosis disease in Asian Seabass. Mar Biotechnol (NY) 19(3):255–265. https://doi.org/10.1007/s10126-017-9747-7

    Article  CAS  Google Scholar 

  67. Wang L, Bai B, Huang S, Liu P, Wan ZY, Ye B, Wu J, Yue GH (2017) QTL mapping for resistance to Iridovirus in Asian Seabass using genotyping-by-sequencing. Mar Biotechnol (NY) 19(5):517–527. https://doi.org/10.1007/s10126-017-9770-8

    Article  CAS  Google Scholar 

  68. Liu S, Vallejo RL, Gao G, Palti Y, Weber GM, Hernandez A, Rexroad CE 3rd (2015) Identification of single-nucleotide polymorphism markers associated with cortisol response to crowding in rainbow trout. Mar Biotechnol (NY) 17(3):328–337. https://doi.org/10.1007/s10126-015-9621-4

    Article  CAS  Google Scholar 

  69. Kusakabe M, Ishikawa A, Ravinet M, Yoshida K, Makino T, Toyoda A, Fujiyama A, Kitano J (2017) Genetic basis for variation in salinity tolerance between stickleback ecotypes. Mol Ecol 26(1):304–319. https://doi.org/10.1111/mec.13875

    Article  CAS  PubMed  Google Scholar 

  70. Haidle L, Janssen JE, Gharbi K, Moghadam HK, Ferguson MM, Danzmann RG (2008) Determination of quantitative trait loci (QTL) for early maturation in rainbow trout (Oncorhynchus mykiss). Mar Biotechnol (NY) 10(5):579–592. https://doi.org/10.1007/s10126-008-9098-5

    Article  CAS  Google Scholar 

  71. Wan SM, Liu H, Zhao BW, Nie CH, Wang WM, Gao ZX (2017) Construction of a high-density linkage map and fine mapping of QTLs for growth and gonad related traits in blunt snout bream. Sci Rep 7:46509. https://doi.org/10.1038/srep46509

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  72. Kliebenstein D (2009) Quantitative genomics: analyzing intraspecific variation using global gene expression polymorphisms or eQTLs. Annu Rev Plant Biol 60:93–114. https://doi.org/10.1146/annurev.arplant.043008.092114

    Article  CAS  PubMed  Google Scholar 

  73. Brown KH, Dobrinski KP, Lee AS, Gokcumen O, Mills RE, Shi X, Chong WW, Chen JY, Yoo P, David S, Peterson SM, Raj T, Choy KW, Stranger BE, Williamson RE, Zon LI, Freeman JL, Lee C (2012) Extensive genetic diversity and substructuring among zebrafish strains revealed through copy number variant analysis. Proc Natl Acad Sci U S A 109(2):529–534. https://doi.org/10.1073/pnas.1112163109

    Article  PubMed  Google Scholar 

  74. Uusi-Heikkila S, Savilammi T, Leder E, Arlinghaus R, Primmer CR (2017) Rapid, broad-scale gene expression evolution in experimentally harvested fish populations. Mol Ecol 26(15):3954–3967. https://doi.org/10.1111/mec.14179

    Article  CAS  PubMed  Google Scholar 

  75. Ishikawa A, Kusakabe M, Yoshida K, Ravinet M, Makino T, Toyoda A, Fujiyama A, Kitano J (2017) Different contributions of local- and distant-regulatory changes to transcriptome divergence between stickleback ecotypes. Evolution 71(3):565–581. https://doi.org/10.1111/evo.13175

    Article  CAS  PubMed  Google Scholar 

  76. Pritchard VL, Viitaniemi HM, McCairns RJ, Merila J, Nikinmaa M, Primmer CR, Leder EH (2017) Regulatory architecture of gene expression variation in the threespine stickleback Gasterosteus aculeatus. G3 (Bethesda) 7(1):165–178. https://doi.org/10.1534/g3.116.033241

    Article  CAS  Google Scholar 

  77. Pavlicev M, Cheverud JM, Wagner GP (2011) Evolution of adaptive phenotypic variation patterns by direct selection for evolvability. Proc Biol Sci 278(1713):1903–1912. https://doi.org/10.1098/rspb.2010.2113

    Article  PubMed  Google Scholar 

  78. Hu Y, Parsons KJ, Albertson RC (2014) Evolvability of the cichlid jaw: new tools provide insights into the genetic basis of phenotypic integration. Evol Biol 41(1):145–153

    Article  Google Scholar 

  79. Parsons KJ, Marquez E, Albertson RC (2012) Constraint and opportunity: the genetic basis and evolution of modularity in the cichlid mandible. Am Nat 179(1):64–78. https://doi.org/10.1086/663200

    Article  PubMed  Google Scholar 

  80. Jansen RC (1993) Interval mapping of multiple quantitative trait loci. Genetics 135(1):205–211

    CAS  PubMed  PubMed Central  Google Scholar 

  81. Jansen RC (1994) Controlling the type I and type II errors in mapping quantitative trait loci. Genetics 138(3):871–881

    CAS  PubMed  PubMed Central  Google Scholar 

  82. Zeng ZB (1994) Precision mapping of quantitative trait loci. Genetics 136(4):1457–1468

    CAS  PubMed  PubMed Central  Google Scholar 

  83. Visscher PM, Hill WG, Wray NR (2008) Heritability in the genomics era—concepts and misconceptions. Nat Rev Genet 9(4):255–266. https://doi.org/10.1038/nrg2322

    Article  CAS  PubMed  Google Scholar 

  84. Otto SP, Jones CD (2000) Detecting the undetected: estimating the total number of loci underlying a quantitative trait. Genetics 156(4):2093–2107

    CAS  PubMed  PubMed Central  Google Scholar 

  85. Sen S, Satagopan JM, Broman KW, Churchill GA (2007) R/qtlDesign: inbred line cross experimental design. Mamm Genome 18(2):87–93. https://doi.org/10.1007/s00335-006-0090-y

    Article  PubMed  PubMed Central  Google Scholar 

  86. Davey JW, Hohenlohe PA, Etter PD, Boone JQ, Catchen JM, Blaxter ML (2011) Genome-wide genetic marker discovery and genotyping using next-generation sequencing. Nat Rev Genet 12(7):499–510. https://doi.org/10.1038/nrg3012

    Article  CAS  PubMed  Google Scholar 

  87. Jamann TM, Balint-Kurti PJ, Holland JB (2015) QTL mapping using high-throughput sequencing. Methods Mol Biol 1284:257–285. https://doi.org/10.1007/978-1-4939-2444-8_13

    Article  CAS  PubMed  Google Scholar 

  88. Baird NA, Etter PD, Atwood TS, Currey MC, Shiver AL, Lewis ZA, Selker EU, Cresko WA, Johnson EA (2008) Rapid SNP discovery and genetic mapping using sequenced RAD markers. PLoS One 3(10):e3376. https://doi.org/10.1371/journal.pone.0003376

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  89. Chutimanitsakun Y, Nipper RW, Cuesta-Marcos A, Cistue L, Corey A, Filichkina T, Johnson EA, Hayes PM (2011) Construction and application for QTL analysis of a Restriction Site Associated DNA (RAD) linkage map in barley. BMC Genomics 12:4. https://doi.org/10.1186/1471-2164-12-4

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  90. Sonah H, Bastien M, Iquira E, Tardivel A, Legare G, Boyle B, Normandeau E, Laroche J, Larose S, Jean M, Belzile F (2013) An improved genotyping by sequencing (GBS) approach offering increased versatility and efficiency of SNP discovery and genotyping. PLoS One 8(1):e54603. https://doi.org/10.1371/journal.pone.0054603

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  91. Elshire RJ, Glaubitz JC, Sun Q, Poland JA, Kawamoto K, Buckler ES, Mitchell SE (2011) A robust, simple genotyping-by-sequencing (GBS) approach for high diversity species. PLoS One 6(5):e19379. https://doi.org/10.1371/journal.pone.0019379

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  92. Schlotterer C, Tobler R, Kofler R, Nolte V (2014) Sequencing pools of individuals—mining genome-wide polymorphism data without big funding. Nat Rev Genet 15(11):749–763. https://doi.org/10.1038/nrg3803

    Article  CAS  PubMed  Google Scholar 

  93. Van Ooijen J (2006) JoinMap 4. Software for the calculation of genetic linkage maps in experimental populations. Kayazama BV, Wageningen

    Google Scholar 

  94. Jansen RC, Stam P (1994) High resolution of quantitative traits into multiple loci via interval mapping. Genetics 136(4):1447–1455

    CAS  PubMed  PubMed Central  Google Scholar 

  95. Churchill GA, Doerge RW (1994) Empirical threshold values for quantitative trait mapping. Genetics 138(3):963–971

    CAS  PubMed  PubMed Central  Google Scholar 

  96. Papachristou C, Lin S (2006) A comparison of methods for intermediate fine mapping. Genet Epidemiol 30(8):677–689. https://doi.org/10.1002/gepi.20179

    Article  PubMed  Google Scholar 

  97. Mackay TF (2001) Quantitative trait loci in Drosophila. Nat Rev Genet 2(1):11–20. https://doi.org/10.1038/35047544

    Article  CAS  PubMed  Google Scholar 

  98. Carlborg O, Haley CS (2004) Epistasis: too often neglected in complex trait studies? Nat Rev Genet 5(8):618–625. https://doi.org/10.1038/nrg1407

    Article  CAS  PubMed  Google Scholar 

  99. Mackay TF (2014) Epistasis and quantitative traits: using model organisms to study gene-gene interactions. Nat Rev Genet 15(1):22–33. https://doi.org/10.1038/nrg3627

    Article  CAS  PubMed  Google Scholar 

  100. Phillips PC (2008) Epistasis—the essential role of gene interactions in the structure and evolution of genetic systems. Nat Rev Genet 9(11):855–867. https://doi.org/10.1038/nrg2452

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  101. Beavis WD (1998) QTL analysis: power, precision, and accuracy. In: Molecular dissection of complex traits. CRC Press, Boca Raton

    Google Scholar 

  102. Xu S (2003) Theoretical basis of the Beavis effect. Genetics 165(4):2259–2268

    PubMed  PubMed Central  Google Scholar 

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Correspondence to Kara E. Powder .

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Powder, K.E. (2020). Quantitative Trait Loci (QTL) Mapping. In: Shi, X. (eds) eQTL Analysis. Methods in Molecular Biology, vol 2082. Humana, New York, NY. https://doi.org/10.1007/978-1-0716-0026-9_15

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  • DOI: https://doi.org/10.1007/978-1-0716-0026-9_15

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