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eQTL Analysis pp 211-229 | Cite as

Quantitative Trait Loci (QTL) Mapping

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Part of the Methods in Molecular Biology book series (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.

Key words

Quantitative trait locus (QTL) Genetic basis Quantitative genetics Epistasis MQM 

References

  1. 1.
    Alberch P (1991) From genes to phenotype: dynamical systems and evolvability. Genetica 84(1):5–11PubMedCrossRefGoogle Scholar
  2. 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.xPubMedCrossRefGoogle Scholar
  3. 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.54.1393.223PubMedCrossRefGoogle Scholar
  4. 4.
    Fisher RA (1918) The correlation between relatives on the supposition of Mendelian inheritance. Trans R Soc Edinburgh 52:399–433CrossRefGoogle Scholar
  5. 5.
    Haldane JBS (1932) The causes of evolution. Harper and Brothers, LondonGoogle Scholar
  6. 6.
    Wright S (1921) Systems of mating. I. the biometric relations between parent and offspring. Genetics 6(2):111–123PubMedPubMedCentralGoogle Scholar
  7. 7.
    Wright S (1968) Evolution and genetics of populations, vol 1. University of Chicago Press, ChicagoGoogle Scholar
  8. 8.
    Lynch M, Walsh B (1998) Genetics and analysis of quantitative traits. Sinauer, Sunderland, MAGoogle Scholar
  9. 9.
    Broman KW, Sen S (2009) A guide to QTL mapping with R/qtl. Springer, New YorkCrossRefGoogle Scholar
  10. 10.
    Falconer DS, Mackay TFC (2009) Introduction to quantitative genetics, 4th edn. Pearson, LondonGoogle Scholar
  11. 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/btq565PubMedPubMedCentralCrossRefGoogle Scholar
  12. 12.
    Rifkin SA (2012) Quantitative trait loci (QTL): methods and protocols. Methods in molecular biology. Humana Press, Totowa, NJCrossRefGoogle Scholar
  13. 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/nrg703PubMedCrossRefGoogle Scholar
  14. 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/nrg2612PubMedCrossRefGoogle Scholar
  15. 15.
    Mackay TF, Fry JD (1996) Polygenic mutation in Drosophila melanogaster: genetic interactions between selection lines and candidate quantitative trait loci. Genetics 144(2):671–688PubMedPubMedCentralGoogle Scholar
  16. 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.950180207PubMedCrossRefGoogle Scholar
  17. 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):227–235PubMedPubMedCentralGoogle Scholar
  18. 18.
    Johnson TE, DeFries JC, Markel PD (1992) Mapping quantitative trait loci for behavioral traits in the mouse. Behav Genet 22(6):635–653PubMedCrossRefGoogle Scholar
  19. 19.
    Cheverud JM, Routman EJ, Duarte FA, van Swinderen B, Cothran K, Perel C (1996) Quantitative trait loci for murine growth. Genetics 142(4):1305–1319PubMedPubMedCentralGoogle Scholar
  20. 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/BF00226905PubMedCrossRefGoogle Scholar
  21. 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):11–16Google Scholar
  22. 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):575–585PubMedCrossRefGoogle Scholar
  23. 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/BF00225380PubMedCrossRefGoogle Scholar
  24. 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):113–125PubMedPubMedCentralGoogle Scholar
  25. 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):4530–4534CrossRefGoogle Scholar
  26. 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):1129–1145Google Scholar
  27. 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.xPubMedCrossRefGoogle Scholar
  28. 28.
    Doebley J (2004) The genetics of maize evolution. Annu Rev Genet 38:37–59.  https://doi.org/10.1146/annurev.genet.38.072902.092425PubMedCrossRefGoogle Scholar
  29. 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.2017.07.004PubMedCrossRefGoogle Scholar
  30. 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/srep28679PubMedPubMedCentralCrossRefGoogle Scholar
  31. 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/10.1186/1471-2156-11-63PubMedPubMedCentralCrossRefGoogle Scholar
  32. 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/g3.117.041376CrossRefGoogle Scholar
  33. 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.0166723PubMedPubMedCentralCrossRefGoogle Scholar
  34. 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/srep16358PubMedPubMedCentralCrossRefGoogle Scholar
  35. 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.114.162420PubMedPubMedCentralCrossRefGoogle Scholar
  36. 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.0506649102PubMedPubMedCentralCrossRefGoogle Scholar
  37. 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.0930235100PubMedPubMedCentralCrossRefGoogle Scholar
  38. 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/g3.117.300083CrossRefGoogle Scholar
  39. 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.21101PubMedCrossRefGoogle Scholar
  40. 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/10.1038/414901aPubMedCrossRefGoogle Scholar
  41. 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/s42003-018-0060-4PubMedPubMedCentralCrossRefGoogle Scholar
  42. 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.13905PubMedCrossRefGoogle Scholar
  43. 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.0057281PubMedPubMedCentralCrossRefGoogle Scholar
  44. 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/g3.114.010389CrossRefGoogle Scholar
  45. 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.0308479101PubMedPubMedCentralCrossRefGoogle Scholar
  46. 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.0020109PubMedPubMedCentralCrossRefGoogle Scholar
  47. 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/nature02415PubMedCrossRefGoogle Scholar
  48. 48.
    Klingenberg CP (2010) Evolution and development of shape: integrating quantitative approaches. Nat Rev Genet 11(9):623–635.  https://doi.org/10.1038/nrg2829PubMedCrossRefGoogle Scholar
  49. 49.
    Mitteroecker P, Gunz P (2009) Advances in geometric morphometrics. Evol Biol 36:235–247CrossRefGoogle Scholar
  50. 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.14005PubMedCrossRefGoogle Scholar
  51. 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/10.1186/1741-7007-8-8PubMedPubMedCentralCrossRefGoogle Scholar
  52. 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.12590PubMedCrossRefGoogle Scholar
  53. 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/ncomms12736PubMedPubMedCentralCrossRefGoogle Scholar
  54. 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/g3.115.018226CrossRefGoogle Scholar
  55. 55.
    Streelman JT, Albertson RC, Kocher TD (2003) Genome mapping of the orange blotch colour pattern in cichlid fishes. Mol Ecol 12(9):2465–2471PubMedCrossRefGoogle Scholar
  56. 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.12900PubMedPubMedCentralCrossRefGoogle Scholar
  57. 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.1000326PubMedPubMedCentralCrossRefGoogle Scholar
  58. 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/g3.115.024505CrossRefGoogle Scholar
  59. 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.0112527PubMedPubMedCentralCrossRefGoogle Scholar
  60. 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/g3.114.016519CrossRefGoogle Scholar
  61. 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/s10519-006-9080-9PubMedCrossRefGoogle Scholar
  62. 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/s10519-005-9029-4PubMedCrossRefGoogle Scholar
  63. 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/kfr136PubMedPubMedCentralCrossRefGoogle Scholar
  64. 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.13848PubMedCrossRefGoogle Scholar
  65. 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/s12711-018-0401-2PubMedPubMedCentralCrossRefGoogle Scholar
  66. 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/s10126-017-9747-7CrossRefGoogle Scholar
  67. 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/s10126-017-9770-8CrossRefGoogle Scholar
  68. 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/s10126-015-9621-4CrossRefGoogle Scholar
  69. 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.13875PubMedCrossRefGoogle Scholar
  70. 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/s10126-008-9098-5CrossRefGoogle Scholar
  71. 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/srep46509PubMedPubMedCentralCrossRefGoogle Scholar
  72. 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.043008.092114PubMedCrossRefGoogle Scholar
  73. 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.1112163109CrossRefPubMedGoogle Scholar
  74. 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.14179PubMedCrossRefGoogle Scholar
  75. 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.13175PubMedCrossRefGoogle Scholar
  76. 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/g3.116.033241CrossRefGoogle Scholar
  77. 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.2010.2113PubMedCrossRefGoogle Scholar
  78. 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):145–153CrossRefGoogle Scholar
  79. 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/10.1086/663200PubMedCrossRefGoogle Scholar
  80. 80.
    Jansen RC (1993) Interval mapping of multiple quantitative trait loci. Genetics 135(1):205–211PubMedPubMedCentralGoogle Scholar
  81. 81.
    Jansen RC (1994) Controlling the type I and type II errors in mapping quantitative trait loci. Genetics 138(3):871–881PubMedPubMedCentralGoogle Scholar
  82. 82.
    Zeng ZB (1994) Precision mapping of quantitative trait loci. Genetics 136(4):1457–1468PubMedPubMedCentralGoogle Scholar
  83. 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/nrg2322PubMedCrossRefGoogle Scholar
  84. 84.
    Otto SP, Jones CD (2000) Detecting the undetected: estimating the total number of loci underlying a quantitative trait. Genetics 156(4):2093–2107PubMedPubMedCentralGoogle Scholar
  85. 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-yPubMedPubMedCentralCrossRefGoogle Scholar
  86. 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/nrg3012PubMedCrossRefPubMedCentralGoogle Scholar
  87. 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_13PubMedCrossRefGoogle Scholar
  88. 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.0003376PubMedPubMedCentralCrossRefGoogle Scholar
  89. 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/10.1186/1471-2164-12-4PubMedPubMedCentralCrossRefGoogle Scholar
  90. 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.0054603PubMedPubMedCentralCrossRefGoogle Scholar
  91. 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.0019379PubMedPubMedCentralCrossRefGoogle Scholar
  92. 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/nrg3803PubMedCrossRefGoogle Scholar
  93. 93.
    Van Ooijen J (2006) JoinMap 4. Software for the calculation of genetic linkage maps in experimental populations. Kayazama BV, WageningenGoogle Scholar
  94. 94.
    Jansen RC, Stam P (1994) High resolution of quantitative traits into multiple loci via interval mapping. Genetics 136(4):1447–1455PubMedPubMedCentralGoogle Scholar
  95. 95.
    Churchill GA, Doerge RW (1994) Empirical threshold values for quantitative trait mapping. Genetics 138(3):963–971PubMedPubMedCentralGoogle Scholar
  96. 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.20179PubMedCrossRefGoogle Scholar
  97. 97.
    Mackay TF (2001) Quantitative trait loci in Drosophila. Nat Rev Genet 2(1):11–20.  https://doi.org/10.1038/35047544PubMedCrossRefGoogle Scholar
  98. 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/nrg1407PubMedCrossRefGoogle Scholar
  99. 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/nrg3627PubMedCrossRefGoogle Scholar
  100. 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/nrg2452PubMedPubMedCentralCrossRefGoogle Scholar
  101. 101.
    Beavis WD (1998) QTL analysis: power, precision, and accuracy. In: Molecular dissection of complex traits. CRC Press, Boca RatonGoogle Scholar
  102. 102.
    Xu S (2003) Theoretical basis of the Beavis effect. Genetics 165(4):2259–2268PubMedPubMedCentralGoogle Scholar

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© Springer Science+Business Media, LLC, part of Springer Nature 2020

Authors and Affiliations

  1. 1.Department of Biological SciencesClemson UniversityClemsonUSA

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