Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

Strategies for mapping and cloning quantitative trait genes in rodents

Nature Reviews Genetics volume 6, pages 271–286 (2005)Cite this article

Key Points

  • Many quantitative phenotypes of biomedical interest can be modelled in rodents, and the chromosomal locations of the genetic variants that contribute to phenotypic variation can be identified by crosses between inbred strains. Unfortunately, it has proved extremely difficult to find the genes that underlie this variation. In the past few years, several novel methods and resources have become available that might make quantitative trait loci (QTL) cloning more tractable.

  • A number of problems must be overcome if QTL cloning is to become routine. First, the methods that are used must be able to tackle QTLs that contribute to only a small percentage of the variation of a phenotype. Second, it is unlikely that genes will be identified by the presence of unambiguous sequence features. Third, many QTLs that are detected in an inbred-strain cross are due to multiple, physically linked small effects.

  • New methods for QTL mapping include the use of chromosome substitution strains (CSSs), the proposed Collaborative Cross, probabilistic ancestral haplotype reconstruction in outbred mice, Yin–Yang crosses, in silico analysis of sequence variants in multiple inbred strains, gene-expression profiling and quantitative complementation tests.

  • CSSs consist of a set of animals in which one chromosome is derived from one strain and all the rest from another. QTL mapping in a CSS delivers researchers faster to same the point that classical strategies have led them, but no further. The main drawback of the method is that it makes no allowances for the fractionation of a large QTL effect into many loci with smaller effects.

  • The proposed Collaborative Cross will be a panel of 1,000 recombinant lines derived from 8 inbred strains. Its creation would make it possible to map multiple small-effect QTLs onto regions of 4 cM or less, and it would be able to detect many interacting loci. However, the resolution would still be insufficient to identify genes.

  • Recombination inbred segregation tests and Yin–Yang crosses, applied to a large number of recombinant inbreds such as the Collaborative Cross, will increase mapping resolution to the point where individual genes could be identified.

  • Probabilistic ancestral haplotype reconstruction of outbred animals makes it possible to map QTLs to a resolution that is sufficient to guarantee candidature of a single gene. The disadvantages of the method are the complexities of the analysis, and the need for large numbers of animals and high-density genotyping.

  • In silico mapping exploits the shared ancestry of laboratory mouse strains to identify regions of common descent containing QTLs. However, the method is compromised by low power and the complex structure of the genomes of laboratory strains.

  • Gene-expression profiling, combined with genetic mapping data, can help to identify candidate genes. However, differential gene expression is not always a marker of a QTL, expression differences might be restricted to certain tissues or developmental stages, and finding a gene-expression difference within a relevant tissue in a relevant biochemical pathway does not prove the gene's candidacy at the QTL.

  • Quantitative complementation tests for an interaction between the null allele of the candidate gene and the QTL, rather than for a main effect of either. A positive result indicates allelism or epistasis at the QTL. The current drawback of such tests is the lack of appropriate mutants.

  • None of the strategies described in this review provide a comprehensive solution to gene identification after QTL mapping, but together they provide a powerful armamentarium to aid QTL cloning in the twenty-first century.

Abstract

Over the past 15 years, more than 2,000 quantitative trait loci (QTLs) have been identified in crosses between inbred strains of mice and rats, but less than 1% have been characterized at a molecular level. However, new resources, such as chromosome substitution strains and the proposed Collaborative Cross, together with new analytical tools, including probabilistic ancestral haplotype reconstruction in outbred mice, Yin–Yang crosses and in silico analysis of sequence variants in many inbred strains, could make QTL cloning tractable. We review the potential of these strategies to identify genes that underlie QTLs in rodents.

This is a preview of subscription content, access via your institution

Relevant articles

Open Access articles citing this article.

Access options

Rent or buy this article

Get just this article for as long as you need it

$39.95

Learn more

Prices may be subject to local taxes which are calculated during checkout

Figure 1: The distribution of QTL effect sizes.
Figure 2: Effect size in F2 and BC relative to RI.
Figure 3: Haplotype complexity in inbred strains of mice.

References

  1. Hilbert, P. et al. Chromosomal mapping of two genetic loci associated with blood-pressure regulation in hereditary hypertensive rats. Nature 353, 521–529 (1991).

    Article  CAS  PubMed  Google Scholar 

  2. Jacob, H. et al. Genetic mapping of a gene causing hypertension in the stroke-prone spontaneously hypertensive rat. Cell 67, 213–224 (1991).

    Article  CAS  PubMed  Google Scholar 

  3. Lander, E. S. & Botstein, D. Mapping Mendelian factors underlying quantitative traits using RFLP linkage maps. Genetics 121, 185–199 (1989).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  4. Todd, J. A. et al. Genetic analysis of autoimmune type 1 diabetes mellitus in mice. Nature 351, 542–547 (1991).

    Article  CAS  PubMed  Google Scholar 

  5. Lynch, M. & Walsh, B. Genetics and Analysis of Quantitative Traits (Sinauer Associates, Sunderland, Massachusetts, 1998).

    Google Scholar 

  6. Turri, M. G., Henderson, N. D., DeFries, J. C. & Flint, J. Quantitative trait locus mapping in laboratory mice derived from a replicated selection experiment for open-field activity. Genetics 158, 1217–1226 (2001).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  7. Turri, M. G., Datta, S. R., DeFries, J., Henderson, N. D. & Flint, J. QTL analysis identifies multiple behavioral dimensions in ethological tests of anxiety in laboratory mice. Curr. Biol. 11, 725–734 (2001).

    Article  CAS  PubMed  Google Scholar 

  8. Henderson, N. D., Turri, M. G., DeFries, J. C. & Flint, J. QTL Analysis of multiple behavioral measures of anxiety in mice. Behav. Genet. 34, 267–293 (2004).

    Article  PubMed  Google Scholar 

  9. Belknap, J. K. & Atkins, A. L. The replicability of QTLs for murine alcohol preference drinking behavior across eight independent studies. Mamm. Genome 12, 893–899 (2001).

    Article  CAS  PubMed  Google Scholar 

  10. Nadeau, J. H. & Frankel, W. N. The roads from phenotypic variation to gene discovery: mutagenesis versus QTLs. Nature Genet. 25, 381–384 (2000). A discussion of the relative advantages of QTL mapping and mutagenesis for investigating the molecular basis of complex traits.

    Article  CAS  PubMed  Google Scholar 

  11. Korstanje, R. & Paigen, B. From QTL to gene: the harvest begins. Nature Genet. 31, 235–236 (2002).

    Article  CAS  PubMed  Google Scholar 

  12. Glazier, A. M., Nadeau, J. H. & Aitman, T. J. Finding genes that underlie complex traits. Science 298, 2345–2349 (2002).

    Article  CAS  PubMed  Google Scholar 

  13. Page, G. P., George, V., Go, R. C., Page, P. Z. & Allison, D. B. “Are we there yet?”: Deciding when one has demonstrated specific genetic causation in complex diseases and quantitative traits. Am. J. Hum. Genet. 73, 711–719 (2003).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  14. Abiola, O. et al. The nature and identification of quantitative trait loci: a community's view. Nature Rev. Genet. 4, 911–916 (2003).

    PubMed  Google Scholar 

  15. Ferraro, T. N. et al. Fine mapping of a seizure susceptibility locus on mouse chromosome 1: nomination of Kcnj10 as a causative gene. Mamm. Genome 15, 239–251 (2004).

    Article  CAS  PubMed  Google Scholar 

  16. Shirley, R. L., Walter, N. A., Reilly, M. T., Fehr, C. & Buck, K. J. Mpdz is a quantitative trait gene for drug withdrawal seizures. Nature Neurosci. 7, 699–700 (2004).

    Article  CAS  PubMed  Google Scholar 

  17. Beavis, W. D. in Molecular Analysis of Complex Traits (ed. Paterson, A. H.) 123–150 (CRC, Boca Raton, Florida, 1998).

    Google Scholar 

  18. Beavis, W. D. in 49th Annual Corn and Sorghum Research Conference 252–268 (American Seed Trade Association, Washington DC, 1994).

    Google Scholar 

  19. Legare, M. E., Bartlett, F. S. & Frankel, W. N. A major effect QTL determined by multiple genes in epileptic EL mice. Genome Res. 10, 42–48 (2000).

    CAS  PubMed  PubMed Central  Google Scholar 

  20. Stylianou, I. M. et al. Genetic complexity of an obesity QTL (Fob3) revealed by detailed genetic mapping. Mamm. Genome 15, 472–481 (2004).

    Article  CAS  PubMed  Google Scholar 

  21. Christians, J. K. & Keightley, P. D. Fine mapping of a murine growth locus to a 1.4-cM region and resolution of linked QTL. Mamm. Genome 15, 482–491 (2004).

    Article  CAS  PubMed  Google Scholar 

  22. Ariyarajah, A. et al. Dissecting quantitative trait loci into opposite blood pressure effects on Dahl rat chromosome 8 by congenic strains. J. Hypertens. 22, 1495–1502 (2004).

    Article  CAS  PubMed  Google Scholar 

  23. Alemayehu, A., Breen, L., Krenova, D. & Printz, M. P. Reciprocal rat chromosome 2 congenic strains reveal contrasting blood pressure and heart rate QTL. Physiol. Genomics 10, 199–210 (2002).

    Article  CAS  PubMed  Google Scholar 

  24. Garrett, M. R. & Rapp, J. P. Two closely linked interactive blood pressure QTL on rat chromosome 5 defined using congenic Dahl rats. Physiol. Genomics 8, 81–86 (2002).

    Article  CAS  PubMed  Google Scholar 

  25. Garrett, M. R. & Rapp, J. P. Multiple blood pressure QTL on rat chromosome 2 defined by congenic Dahl rats. Mamm. Genome 13, 41–44 (2002).

    Article  CAS  PubMed  Google Scholar 

  26. Frantz, S., Clemitson, J. R., Bihoreau, M. T., Gauguier, D. & Samani, N. J. Genetic dissection of region around the Sa gene on rat chromosome 1: evidence for multiple loci affecting blood pressure. Hypertension 38, 216–221 (2001).

    Article  CAS  PubMed  Google Scholar 

  27. Podolin, P. L. et al. Localization of two insulin-dependent diabetes (Idd) genes to the Idd10 region on mouse Chromosome 3. Mamm. Genome 9, 283–286 (1998).

    Article  CAS  PubMed  Google Scholar 

  28. Puel, A. et al. Identification of two quantitative trait loci involved in antibody production on mouse chromosome 8. Immunogenetics 47, 326–331 (1998).

    Article  CAS  PubMed  Google Scholar 

  29. Bihl, F., Brahic, M. & Bureau, J. F. Two loci, Tmevp2 and Tmevp3, located on the telomeric region of chromosome 10, control the persistence of Theiler's virus in the central nervous system of mice. Genetics 152, 385–392 (1999).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  30. Mackay, T. F. The genetic architecture of quantitative traits. Annu. Rev. Genet. 35, 303–339 (2001).

    Article  CAS  PubMed  Google Scholar 

  31. Yalcin, B. et al. Genetic dissection of a behavioral quantitative trait locus shows that Rgs2 modulates anxiety in mice. Nature Genet. 36, 1197–1202 (2004). The complexity of QTL architecture in mice becomes apparent in this paper, which used probabilistic ancestral haplotype reconstruction in outbred mice and a knockout interaction test to identify a candidate gene.

    Article  CAS  PubMed  Google Scholar 

  32. Mackay, T. F. The genetic architecture of quantitative traits: lessons from Drosophila. Curr. Opin. Genet. Dev. 14, 253–257 (2004). An excellent review of the genetic basis of complex traits, from the view point of Drosophila genetics.

    Article  CAS  PubMed  Google Scholar 

  33. Steinmetz, L. M. et al. Dissecting the architecture of a quantitative trait locus in yeast. Nature 416, 326–330 (2002). Even yeast have QTLs, and the formidable power of yeast genetics was used here to show that neither expression differences nor sequence variation are enough to identify their molecular basis. This paper introduced reciprocal hemizygosity for gene identification.

    Article  CAS  PubMed  Google Scholar 

  34. Aitman, T. J. et al. Quantitative trait loci for cellular defects in glucose and fatty acid metabolism in hypertensive rats. Nature Genet. 16, 197–201 (1997).

    Article  CAS  PubMed  Google Scholar 

  35. Vingsbo-Lundberg, C. et al. Genetic control of arthritis onset, severity and chronicity in a model for rheumatoid arthritis in rats. Nature Genet. 20, 401–404 (1998).

    Article  CAS  PubMed  Google Scholar 

  36. Thomas, P. D. & Kejariwal, A. Coding single-nucleotide polymorphisms associated with complex vs. Mendelian disease: evolutionary evidence for differences in molecular effects. Proc. Natl Acad. Sci. USA 101, 15398–15403 (2004). The molecular basis of complex traits in humans is shown to differ from the molecular basis of disorders owing to highly penetrant mutations.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  37. Yalcin, B. et al. Unexpected complexity in the haplotypes of commonly used inbred strains of laboratory mice. Proc. Natl Acad. Sci. USA 101, 9734–9739 (2004). The first of a series of papers that showed that the DNA-sequence relationship between inbred mouse strains is remarkably complex, a finding with important implications for in silico mapping strategies (see also references 102 and 103).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  38. Nobrega, M. A., Ovcharenko, I., Afzal, V. & Rubin, E. M. Scanning human gene deserts for long-range enhancers. Science 302, 413 (2003).

    Article  CAS  PubMed  Google Scholar 

  39. van Ooijen, J. W. Accuracy of mapping quantitative trait loci in autogamous species. Theor. Appl. Genet. 84, 803–811 (1992).

    Article  CAS  PubMed  Google Scholar 

  40. Darvasi, A., Weinreb, A., Minke, V., Weller, J. I. & Soller, M. Detecting marker-QTL linkage and estimating QTL gene effect and map location using a saturated genetic map. Genetics 134, 943–951 (1993).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  41. Darvasi, A. & Soller, M. A simple method to calculate resolving power and confidence interval of QTL map location. Behav. Genet. 27, 125–132 (1997).

    Article  CAS  PubMed  Google Scholar 

  42. Darvasi, A. Experimental strategies for the genetic dissection of complex traits in animal models. Nature Genet. 18, 19–24 (1998). An excellent review of QTL detection and fine-mapping methods in rodents, and the first description of the recombination inbred segregation test, which was then extended to Yin–Yang crosses in reference 58.

    Article  CAS  PubMed  Google Scholar 

  43. Darvasi, A. & Soller, M. Advanced intercross lines, an experimental population for fine genetic mapping. Genetics 141, 1199–1207 (1995). The first description of advanced intercross lines for QTL mapping in rodents.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  44. Matin, A., Collin, G. B., Asada, Y., Varnum, D. & Nadeau, J. H. Susceptibility to testicular germ-cell tumours in a 129.MOLF-Chr 19 chromosome substitution strain. Nature Genet. 23, 237–240 (1999). The first use of a chromosome-substitution strain for QTL mapping.

    Article  CAS  PubMed  Google Scholar 

  45. Nadeau, J. H., Singer, J. B., Matin, A. & Lander, E. S. Analysing complex genetic traits with chromosome substitution strains. Nature Genet. 24, 221–225 (2000).

    Article  CAS  PubMed  Google Scholar 

  46. Roman, R. J. et al. in Cold Spring Harbor Symposia on Quantitative Biology Vol. LXVII 309–315 (Cold Sping Harbor Laboratory, New York, 2002).

    Google Scholar 

  47. Cowley, A. W. Jr, Liang, M., Roman, R. J., Greene, A. S. & Jacob, H. J. Consomic rat model systems for physiological genomics. Acta Physiol. Scand. 181, 585–592 (2004).

    Article  CAS  PubMed  Google Scholar 

  48. Law, C. N. The location of genetic factors affecting a quantitative character in wheat. Genetics 53, 487–498 (1966).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  49. Caligari, P. D. & Mather, K. Genotype–environment interaction. III. Interactions in Drosophila melanogaster. Proc. R. Soc. Lond. B 191, 387–411 (1975).

    Article  CAS  PubMed  Google Scholar 

  50. Singer, J. B., Hill, A. E., Nadeau, J. H. & Lander, E. S. Mapping quantitative trait loci for anxiety in chromosome substitution strains of mice. Genetics 15 September 2004 (10.1534/genetics.104.031492).

  51. Singer, J. B. et al. Genetic dissection of complex traits with chromosome substitution strains of mice. Science 304, 445–448 (2004). This paper describes the construction of the first complete set of chromosome-substitution strains and their application in genome-wide QTL mapping.

    Article  CAS  PubMed  Google Scholar 

  52. Belknap, J. K. Chromosome substitution strains: some quantitative considerations for genome scans and fine mapping. Mamm. Genome 14, 723–732 (2003).

    Article  PubMed  Google Scholar 

  53. Churchill, G. A. et al. The Collaborative Cross, a community resource for the genetic analysis of complex traits. Nature Genet. 36, 1133–1137 (2004). This paper describes the Collaborative Cross and explains what the proposed resource would provide for complex trait analysis.

    Article  CAS  PubMed  Google Scholar 

  54. Belknap, J. K., Mitchell, S. R., O'Toole, L. A., Helms, M. L. & Crabbe, J. C. Type I and type II error rates for quantitative trait loci (QTL) mapping studies using recombinant inbred mouse strains. Behav. Genet. 26, 149–160 (1996).

    Article  CAS  PubMed  Google Scholar 

  55. Valdar, W., Flint, J. & Mott, R. Simulating the collaborative cross: power of QTL detection and mapping resolution afforded by a large set of recombinant inbred strains. Genetics (in the press).

  56. Williams, R. W. et al. Genetic structure of the LXS panel of recombinant inbred mouse strains: a powerful resource for complex trait analysis. Mamm. Genome 15, 637–647 (2004).

    Article  CAS  PubMed  Google Scholar 

  57. Peirce, J. L., Lu, L., Gu, J., Silver, L. M. & Williams, R. W. A new set of BXD recombinant inbred lines from advanced intercross populations in mice. BMC Genet. 5, 7 (2004).

    Article  PubMed  PubMed Central  Google Scholar 

  58. Shifman, S. & Darvasi, A. Mouse inbred strain sequence information and Yin–Yang crosses for QTL fine mapping. Genetics 1 November 2004 (10.1534/genetics.104.032474).

  59. Visscher, P. M. Speed congenics: accelerated genome recovery using genetic markers. Genet. Res. 74, 81–85 (1999).

    Article  CAS  PubMed  Google Scholar 

  60. Zhang, Y. et al. Positional cloning of a quantitative trait locus on chromosome 13q14 that influences immunoglobulin E levels and asthma. Nature Genet. 34, 181–186 (2003).

    Article  CAS  PubMed  Google Scholar 

  61. Lipkin, S. M. et al. The MLH1 D132H variant is associated with susceptibility to sporadic colorectal cancer. Nature Genet. 36, 694–699 (2004).

    Article  CAS  PubMed  Google Scholar 

  62. Guo, D. et al. A functional variant of SUMO4, a new IκBα modifier, is associated with type 1 diabetes. Nature Genet. 36, 837–841 (2004).

    Article  CAS  PubMed  Google Scholar 

  63. Stoll, M. et al. Genetic variation in DLG5 is associated with inflammatory bowel disease. Nature Genet. 36, 476–480 (2004).

    Article  CAS  PubMed  Google Scholar 

  64. Gretarsdottir, S. et al. The gene encoding phosphodiesterase 4D confers risk of ischemic stroke. Nature Genet. 35, 131–138 (2003).

    Article  CAS  PubMed  Google Scholar 

  65. Prokunina, L. et al. A regulatory polymorphism in PDCD1 is associated with susceptibility to systemic lupus erythematosus in humans. Nature Genet. 32, 666–669 (2002).

    Article  CAS  PubMed  Google Scholar 

  66. Rioux, J. D. et al. Genetic variation in the 5q31 cytokine gene cluster confers susceptibility to Crohn disease. Nature Genet. 29, 223–228 (2001).

    Article  CAS  PubMed  Google Scholar 

  67. Altshuler, D. et al. The common PPARγ Pro12Ala polymorphism is associated with decreased risk of type 2 diabetes. Nature Genet. 26, 76–80 (2000).

    Article  CAS  PubMed  Google Scholar 

  68. Hitzemann, R. et al. Multiple cross mapping (MCM) markedly improves the localization of a QTL for ethanol-induced activation. Genes Brain Behav. 1, 214–222 (2002).

    Article  CAS  PubMed  Google Scholar 

  69. Talbot, C. J. et al. Fine scale mapping of a genetic locus for conditioned fear. Mamm. Genome 14, 223–230 (2003).

    Article  PubMed  Google Scholar 

  70. Mott, R., Talbot, C. J., Turri, M. G., Collins, A. C. & Flint, J. A method for fine mapping quantitative trait loci in outbred animal stocks. Proc. Natl Acad. Sci. USA 97, 12649–12654 (2000). The introduction of probabilistic ancestral haplotype reconstruction for mapping QTL using heterogeneous stocks of mice.

    Article  PubMed  PubMed Central  Google Scholar 

  71. Talbot, C. J. et al. High-resolution mapping of quantitative trait loci in outbred mice. Nature Genet. 21, 305–308 (1999). The first use of heterogeneous stock mice for QTL mapping

    Article  CAS  PubMed  Google Scholar 

  72. Nagase, H. et al. Distinct genetic loci control development of benign and malignant skin tumours in mice. Nature Genet. 10, 424–429 (1995).

    Article  CAS  PubMed  Google Scholar 

  73. Nagase, H., Mao, J. H. & Balmain, A. A subset of skin tumor modifier loci determines survival time of tumor-bearing mice. Proc. Natl Acad. Sci. USA 96, 15032–15037 (1999).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  74. Ewart-Toland, A. et al. Identification of Stk6/STK15 as a candidate low-penetrance tumor-susceptibility gene in mouse and human. Nature Genet. 34, 403–412 (2003).

    Article  CAS  PubMed  Google Scholar 

  75. Manenti, G., Galbiati, F., Noci, S. & Dragani, T. A. Outbred CD-1 mice carry the susceptibility allele at the pulmonary adenoma susceptibility 1 (Pas1) locus. Carcinogenesis 24, 1143–1148 (2003).

    Article  CAS  PubMed  Google Scholar 

  76. Neale, B. M. & Sham, P. C. The future of association studies: gene-based analysis and replication. Am. J. Hum. Genet. 75, 353–362 (2004).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  77. Zondervan, K. T. & Cardon, L. R. The complex interplay among factors that influence allelic association. Nature Rev. Genet. 5, 89–100 (2004).

    Article  CAS  PubMed  Google Scholar 

  78. McKeigue, P. M. Prospects for admixture mapping of complex traits. Am. J. Hum. Genet. 76, 1–7 (2005).

    Article  CAS  PubMed  Google Scholar 

  79. Perez-Enciso, M. Fine mapping of complex trait genes combining pedigree and linkage disequilibrium information: a Bayesian unified framework. Genetics 163, 1497–1510 (2003).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  80. Meuwissen, T. H. & Goddard, M. E. Prediction of identity by descent probabilities from marker-haplotypes. Genet. Sel. Evol. 33, 605–634 (2001).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  81. Meuwissen, T. H. & Goddard, M. E. Fine mapping of quantitative trait loci using linkage disequilibria with closely linked marker loci. Genetics 155, 421–430 (2000).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  82. Farnir, F. et al. Simultaneous mining of linkage and linkage disequilibrium to fine map quantitative trait loci in outbred half-sib pedigrees: revisiting the location of a quantitative trait locus with major effect on milk production on bovine chromosome 14. Genetics 161, 275–287 (2002).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  83. McPeek, M. S. & Strahs, A. Assessment of linkage disequilibrium by the decay of haplotype sharing, with application to fine-scale genetic mapping. Am. J. Hum. Genet. 65, 858–875 (1999).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  84. Morris, A. P., Whittaker, J. C., Xu, C. F., Hosking, L. K. & Balding, D. J. Multipoint linkage-disequilibrium mapping narrows location interval and identifies mutation heterogeneity. Proc. Natl Acad. Sci. USA 100, 13442–13446 (2003).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  85. Meuwissen, T. H. & Goddard, M. E. Mapping multiple QTL using linkage disequilibrium and linkage analysis information and multitrait data. Genet. Sel. Evol. 36, 261–279 (2004).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  86. Churchill, G. A. & Doerge, R. W. Empirical threshold values for quantitative trait mapping. Genetics 138, 963–971 (1994).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  87. Mott, R. & Flint, J. Simultaneous detection and fine mapping of quantitative trait Loci in mice using heterogeneous stocks. Genetics 160, 1609–1618 (2002).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  88. Wang, X., Korstanje, R., Higgins, D. & Paigen, B. Haplotype analysis in multiple crosses to identify a QTL gene. Genome Res. 14, 1767–1772 (2004).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  89. Manenti, G. et al. Haplotype sharing suggests that a genomic segment containing six genes accounts for the pulmonary adenoma susceptibility 1 (Pas1) locus activity in mice. Oncogene 23, 4495–4504 (2004).

    Article  CAS  PubMed  Google Scholar 

  90. Park, Y. G., Clifford, R., Buetow, K. H. & Hunter, K. W. Multiple cross and inbred strain haplotype mapping of complex-trait candidate genes. Genome Res. 13, 118–121 (2003).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  91. Grubb, S. C., Churchill, G. A. & Bogue, M. A. A collaborative database of inbred mouse strain characteristics. Bioinformatics 20, 2857–2859 (2004).

    Article  CAS  PubMed  Google Scholar 

  92. Grupe, A. et al. In silico mapping of complex disease-related traits in mice. Science 292, 1915–1918 (2001). The paper that introduced in silico mapping to the world of mouse genetics.

    Article  CAS  PubMed  Google Scholar 

  93. Ferris, S. D., Sage, R. D. & Wilson, A. C. Evidence from mtDNA sequences that common laboratory strains of inbred mice are descended from a single female. Nature 295, 163–165 (1982).

    Article  CAS  PubMed  Google Scholar 

  94. Beck, J. A. et al. Genealogies of mouse inbred strains. Nature Genet. 24, 23–25 (2000).

    Article  CAS  PubMed  Google Scholar 

  95. Wade, C. M. et al. The mosaic structure of variation in the laboratory mouse genome. Nature 420, 574–578 (2002).

    Article  CAS  PubMed  Google Scholar 

  96. Lindblad-Toh, K. et al. Large-scale discovery and genotyping of single-nucleotide polymorphisms in the mouse. Nature Genet. 24, 381–386 (2000).

    Article  CAS  PubMed  Google Scholar 

  97. Wiltshire, T. et al. Genome-wide single-nucleotide polymorphism analysis defines haplotype patterns in mouse. Proc. Natl Acad. Sci. USA 100, 3380–3385 (2003). References 95, 96 and 97 presented the first description of genome-wide distribution of genetic variation in the mouse, and suggested that the observed mosaic structure was due to common descent from a relatively few progenitors strains.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  98. Liao, G. et al. In silico genetics: identification of a functional element regulating H2-Eα gene expression. Science 306, 690–695 (2004).

    Article  CAS  PubMed  Google Scholar 

  99. Pletcher, M. T. et al. Use of a dense single nucleotide polymorphism map for in silico mapping in the mouse. PLoS Biol. 2, e393 (2004).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  100. Usuka, J. et al. In silico mapping of mouse quantitative trait loci. Science 5551, 2423 (2001).

    Google Scholar 

  101. Turri, M. G., De Fries, J. C., Henderson, N. D. & Flint, J. Multivariate analysis of quantitative trait loci influencing variation in anxiety-related behavior in laboratory mice. Mamm. Genome 15, 69–76 (2004).

    Article  PubMed  Google Scholar 

  102. Frazer, K. A. et al. Segmental phylogenetic relationships of inbred mouse strains revealed by fine-scale analysis of sequence variation across 4.6 Mb of mouse genome. Genome Res. 14, 1493–1500 (2004).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  103. Ideraabdullah, F. Y. et al. Genetic and haplotype diversity among wild-derived mouse inbred strains. Genome Res. 14, 1880–1887 (2004).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  104. Sandberg, R. et al. Regional and strain-specific gene expression mapping in the adult mouse brain. Proc. Natl Acad. Sci. USA 97, 11038–11043 (2000).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  105. Eaves, I. A. et al. Combining mouse congenic strains and microarray gene expression analyses to study a complex trait: the NOD model of type 1 diabetes. Genome Res. 12, 232–243 (2002). An example of how gene-expression profiling might not be of help in gene identification, and a careful consideration of the limitations of this approach for gene location.

    Article  CAS  PubMed  Google Scholar 

  106. Karp, C. L. et al. Identification of complement factor 5 as a susceptibility locus for experimental allergic asthma. Nature Immunol. 1, 221–226 (2000).

    Article  CAS  Google Scholar 

  107. Klein, R. F. et al. Regulation of bone mass in mice by the lipoxygenase gene Alox15. Science 303, 229–232 (2004). In contrast to reference 105, references 106 and 107 are demonstrations of the power of gene-expression profiling for gene location.

    Article  CAS  PubMed  Google Scholar 

  108. Rozzo, S. J. et al. Evidence for an interferon-inducible gene, Ifi202, in the susceptibility to systemic lupus. Immunity 15, 435–443 (2001).

    Article  CAS  PubMed  Google Scholar 

  109. McBride, M. W. et al. Microarray analysis of rat chromosome 2 congenic strains. Hypertension 41, 847–853 (2003).

    Article  CAS  PubMed  Google Scholar 

  110. Gross, C. et al. Serotonin1A receptor acts during development to establish normal anxiety-like behaviour in the adult. Nature 416, 396–400 (2002). A salutary lesson in the use of gene-expression methods: this paper is an example of a mutation in which the phenotype depends on where and when the mutation occurs.

    Article  CAS  PubMed  Google Scholar 

  111. Mathis, D. J., Benoist, C., Williams, V. E. 2nd, Kanter, M. & McDevitt, H. O. Several mechanisms can account for defective E α gene expression in different mouse haplotypes. Proc. Natl Acad. Sci. USA 80, 273–277 (1983).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  112. Jones, P. P., Murphy, D. B. & McDevitt, H. O. Variable synthesis and expression of E α and Ae (E β) Ia polypeptide chains in mice of different H-2 haplotypes. Immunogenetics 12, 321–337 (1981).

    Article  CAS  PubMed  Google Scholar 

  113. Long, A. D., Mullaney, S. L., Mackay, T. F. C. & Langley, C. H. Genetic interactions between naturally occurring alleles at quantitative trait loci and mutant alleles at candidate loci affecting bristle number in Drosophila melanogaster. Genetics 144, 1497–1510 (1996). The first description of quantitative complementation testing for the investigation of candidate genes at QTL, carried out in Drosophila melanogaster.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  114. Darvasi, A. Dissecting complex traits: the geneticists' “around the world in 80 days”. Trends Genet. (in the press).

  115. Coghill, E. L. et al. A gene driven approach to the identification of ENU mutants in the mouse. Nature Genet. 30, 255–256 (1999).

    Article  Google Scholar 

  116. Flint, J. Analysis of quantitative trait loci that influence animal behavior. J. Neurobiol. 54, 46–77 (2003).

    Article  CAS  PubMed  Google Scholar 

  117. Min-Oo, G. et al. Pyruvate kinase deficiency in mice protects against malaria. Nature Genet. 35, 357–362 (2003).

    Article  CAS  PubMed  Google Scholar 

  118. Mitsos, L. M. et al. Susceptibility to tuberculosis: a locus on mouse chromosome 19 (Trl-4) regulates Mycobacterium tuberculosis replication in the lungs. Proc. Natl Acad. Sci. USA 100, 6610–6615 (2003).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  119. Diez, E. et al. Birc1e is the gene within the Lgn1 locus associated with resistance to Legionella pneumophila. Nature Genet. 33, 55–60 (2003).

    Article  CAS  PubMed  Google Scholar 

  120. Mitsos, L. M. et al. Genetic control of susceptibility to infection with Mycobacterium tuberculosis in mice. Genes Immunol. 1, 467–477 (2000).

    Article  CAS  Google Scholar 

  121. Vidal, S. M., Malo, D., Vogan, K., Skamene, E. & Gros, P. Natural resistance to infection with intracellular parasites: isolation of a candidate for Bcg. Cell 73, 469–485 (1993).

    Article  CAS  PubMed  Google Scholar 

  122. Poltorak, A. et al. Defective LPS signaling in C3H/HeJ and C57BL/10ScCr mice: mutations in Tlr4 gene. Science 282, 2085–2088 (1998).

    Article  CAS  PubMed  Google Scholar 

  123. Wanstrat, A. & Wakeland, E. The genetics of complex autoimmune diseases: non-MHC susceptibility genes. Nature Immunol. 2, 802–809 (2001).

    Article  Google Scholar 

  124. Leamy, L. J., Routman, E. J. & Cheverud, J. M. An epistatic genetic basis for fluctuating asymmetry of mandible size in mice. Evolution 56, 642–653 (2002).

    Article  PubMed  Google Scholar 

  125. van Wezel, T., Ruivenkamp, C. A., Stassen, A. P., Moen, C. J. & Demant, P. Four new colon cancer susceptibility loci, Scc6 to Scc9 in the mouse. Cancer Res. 59, 4216–4218 (1999).

    CAS  PubMed  Google Scholar 

  126. Fijneman, R. J., de Vries, S. S., Jansen, R. C. & Demant, P. Complex interactions of new quantitative trait loci, Sluc1, Sluc2, Sluc3, and Sluc4, that influence the susceptibility to lung cancer in the mouse. Nature Genet. 14, 465–467 (1996).

    Article  CAS  PubMed  Google Scholar 

  127. Flint, J., De Fries, J. C. & Henderson, N. D. Little epistasis for anxiety-related measures in the DeFries strains of laboratory mice. Mamm. Genome 15, 77–82 (2004).

    Article  PubMed  Google Scholar 

  128. Clark, R. M., Marker, P. C. & Kingsley, D. M. A novel candidate gene for mouse and human preaxial polydactyly with altered expression in limbs of Hemimelic extra-toes mutant mice. Genomics 67, 19–27 (2000).

    Article  CAS  PubMed  Google Scholar 

  129. Lettice, L. A. et al. A long-range Shh enhancer regulates expression in the developing limb and fin and is associated with preaxial polydactyly. Hum. Mol. Genet. 12, 1725–1735 (2003).

    Article  CAS  PubMed  Google Scholar 

  130. Lettice, L. A. et al. Disruption of a long-range cis-acting regulator for Shh causes preaxial polydactyly. Proc. Natl Acad. Sci. USA 99, 7548–7553 (2002).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  131. Austin, C. P. et al. The knockout mouse project. Nature Genet. 36, 921–924 (2004).

    Article  CAS  PubMed  Google Scholar 

  132. Belknap, J. K. Effect of within-strain sample size on QTL detection and mapping using recombinant inbred mouse strains. Behav. Genet. 28, 29–38 (1998).

    Article  CAS  PubMed  Google Scholar 

  133. Lander, E. & Kruglyak, L. Genetic dissection of complex traits: guidelines for interpreting and reporting linkage results. Nature Genet. 11, 241–247 (1995).

    Article  CAS  PubMed  Google Scholar 

  134. Belknap, J. K., Mitchell, S. R., Otoole, L. A., Helms, M. L. & Crabbe, J. C. Type-I and type-II error rates for quantitative trait loci (Qtl) mapping studies using recombinant inbred mouse strains. Behav. Genet. 26, 149–160 (1996).

    Article  CAS  PubMed  Google Scholar 

  135. Bolivar, V. J., Cook, M. N. & Flaherty, L. Mapping of quantitative trait loci with knockout/congenic strains. Genome Res. 11, 1549–1552 (2001).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  136. Moen, C. J. et al. The recombinant congenic strains — a novel genetic tool applied to the study of colon tumor development in the mouse. Mamm. Genome 1, 217–227 (1991).

    Article  CAS  PubMed  Google Scholar 

  137. Iakoubova, O. A. et al. Genome-tagged mice (GTM): two sets of genome-wide congenic strains. Genomics 74, 89–104 (2001).

    Article  CAS  PubMed  Google Scholar 

  138. McClearn, G. E., Wilson, J. R. & Meredith, W. in Contributions to Behavior-Genetic Analysis: the Mouse as a Prototype (eds Lindzey, G. & Thiessen, D.) 3–22 (Appleton Century Crofts, New York, 1970).

    Google Scholar 

  139. Demarest, K., Koyner, J., McCaughran, J. Jr, Cipp, L. & Hitzemann, R. Further characterization and high-resolution mapping of quantitative trait loci for ethanol-induced locomotor activity. Behav. Genet. 31, 79–91 (2001).

    Article  CAS  PubMed  Google Scholar 

  140. Rocha, J. L., Eisen, E. J., Van Vleck, L. D. & Pomp, D. A large-sample QTL study in mice: I. Growth. Mamm. Genome 15, 83–99 (2004).

    Article  CAS  PubMed  Google Scholar 

  141. Rocha, J. L., Eisen, E. J., Van Vleck, L. D. & Pomp, D. A large-sample QTL study in mice: II. Body composition. Mamm. Genome 15, 100–113 (2004).

    Article  CAS  PubMed  Google Scholar 

  142. Brockmann, G. A. et al. QTLs for pre- and postweaning body weight and body composition in selected mice. Mamm. Genome 15, 593–609 (2004).

    Article  PubMed  Google Scholar 

  143. Brockmann, G. A. et al. Single QTL effects, epistasis, and pleiotropy account for two-thirds of the phenotypic F2 variance of growth and obesity in DU6i x DBA/2 mice. Genome Res. 10, 1941–1957 (2000).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  144. Taylor, B. A., Wnek, C., Schroeder, D. & Phillips, S. J. Multiple obesity QTLs identified in an intercross between the NZO (New Zealand obese) and the SM (small) mouse strains. Mamm. Genome 12, 95–103 (2001).

    Article  CAS  PubMed  Google Scholar 

  145. Pitman, W. A. et al. Quantitative trait locus mapping of genes that regulate HDL cholesterol in SM/J and NZB/B1NJ inbred mice. Physiol. Genomics 9, 93–102 (2002).

    Article  CAS  PubMed  Google Scholar 

  146. Paigen, B. et al. Quantitative trait loci mapping for cholesterol gallstones in AKR/J and C57L/J strains of mice. Physiol. Genomics 4, 59–65 (2000).

    Article  CAS  PubMed  Google Scholar 

  147. Anunciado, R. V. et al. Quantitative trait locus analysis of serum insulin, triglyceride, total cholesterol and phospholipid levels in the (SM/J x A/J)F2 mice. Exp. Anim. 52, 37–42 (2003).

    Article  CAS  PubMed  Google Scholar 

  148. Colinayo, V. V. et al. Genetic loci for diet-induced atherosclerotic lesions and plasma lipids in mice. Mamm. Genome 14, 464–471 (2003).

    Article  PubMed  Google Scholar 

  149. Vaughn, T. T. et al. Mapping quantitative trait loci for murine growth: a closer look at genetic architecture. Genet. Res. 74, 313–322 (1999).

    Article  CAS  PubMed  Google Scholar 

  150. Cheverud, J. M. et al. Genetic architecture of adiposity in the cross of LG/J and SM/J inbred mice. Mamm. Genome 12, 3–12 (2001).

    Article  CAS  PubMed  Google Scholar 

  151. Workman, M. S., Leamy, L. J., Routman, E. J. & Cheverud, J. M. Analysis of quantitative trait locus effects on the size and shape of mandibular molars in mice. Genetics 160, 1573–1586 (2002).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  152. Reed, D. R. et al. Loci on chromosomes 2, 4, 9, and 16 for body weight, body length, and adiposity identified in a genome scan of an F2 intercross between the 129P3/J and C57BL/6ByJ mouse strains. Mamm. Genome 14, 302–313 (2003).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  153. Lammert, F., Carey, M. C. & Paigen, B. Chromosomal organization of candidate genes involved in cholesterol gallstone formation: a murine gallstone map. Gastroenterology 120, 221–238 (2001).

    Article  CAS  PubMed  Google Scholar 

  154. Cicila, G. T. et al. High-resolution mapping of the blood pressure QTL on chromosome 7 using Dahl rat congenic strains. Genomics 72, 51–60 (2001).

    Article  CAS  PubMed  Google Scholar 

  155. Farahani, P. et al. Reciprocal hemizygosity analysis of mouse hepatic lipase reveals influence on obesity. Obes. Res. 12, 292–305 (2004).

    Article  CAS  PubMed  Google Scholar 

  156. Crackower, M. A. et al. Angiotensin-converting enzyme 2 is an essential regulator of heart function. Nature 417, 822–828 (2002).

    Article  CAS  PubMed  Google Scholar 

  157. Olofsson, P. et al. Positional identification of Ncf1 as a gene that regulates arthritis severity in rats. Nature Genet. 33, 25–32 (2003).

    Article  CAS  PubMed  Google Scholar 

  158. Ruivenkamp, C. A. et al. Ptprj is a candidate for the mouse colon-cancer susceptibility locus Scc1 and is frequently deleted in human cancers. Nature Genet. 31, 295–300 (2002).

    Article  CAS  PubMed  Google Scholar 

  159. Bachmanov, A. A. et al. Positional cloning of the mouse saccharin preference (Sac) locus. Chem. Senses 26, 925–933 (2001).

    Article  CAS  PubMed  Google Scholar 

  160. Deschepper, C. F. et al. Functional alterations of the Nppa promoter are linked to cardiac ventricular hypertrophy in WKY/WKHA rat crosses. Circ. Res. 88, 223–228 (2001).

    Article  CAS  PubMed  Google Scholar 

  161. Aitman, T. J. et al. Identification of Cd36 (Fat) as an insulin-resistance gene causing defective fatty acid and glucose metabolism in hypertensive rats. Nature Genet. 21, 76–83 (1999). The first demonstration that gene-expression profiling could be used to find genes that underlie QTLs.

    Article  CAS  PubMed  Google Scholar 

  162. Cormier, R. T. et al. Secretory phospholipase Pla2g2a confers resistance to intestinal tumorigenesis. Nature Genet. 17, 88–91 (1997).

    Article  CAS  PubMed  Google Scholar 

  163. Ikeda, A. et al. Microtubule-associated protein 1A is a modifier of tubby hearing (moth1). Nature Genet. 30, 401–405 (2002).

    Article  CAS  PubMed  Google Scholar 

  164. Yokoi, N. et al. Cblb is a major susceptibility gene for rat type 1 diabetes mellitus. Nature Genet. 31, 391–394 (2002).

    Article  CAS  PubMed  Google Scholar 

  165. Ueda, H. et al. Association of the T-cell regulatory gene CTLA4 with susceptibility to autoimmune disease. Nature 423, 506–511 (2003).

    Article  CAS  PubMed  Google Scholar 

  166. Podolin, P. L. et al. Differential glycosylation of interleukin 2, the molecular basis for the NOD Idd3 type 1 diabetes gene? Cytokine 12, 477–482 (2000).

    Article  CAS  PubMed  Google Scholar 

  167. Zhang, S. L. et al. Efficiency alleles of the Pctr1 modifier locus for plasmacytoma susceptibility. Mol. Cell Biol. 21, 310–318 (2001).

    Article  PubMed  PubMed Central  Google Scholar 

  168. Hamilton-Williams, E. E. et al. Transgenic rescue implicates β2-microglobulin as a diabetes susceptibility gene in nonobese diabetic (NOD) mice. Proc. Natl Acad. Sci. USA 98, 11533–11538 (2001).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

Download references

Acknowledgements

The authors are supported by the Wellcome Trust. We would like to thank C. Benoist for comments on the manuscript.

Author information

Authors and Affiliations

  1. Wellcome Trust Centre for Human Genetics, Oxford University, Roosevelt Drive, Oxford, OX3 7BN, United Kingdom

    Jonathan Flint, William Valdar, Sagiv Shifman & Richard Mott

Authors
  1. Jonathan Flint
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. William Valdar
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Sagiv Shifman
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Richard Mott
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Jonathan Flint.

Ethics declarations

Competing interests

The authors declare no competing financial interests.

Related links

Related links

DATABASES

Entrez

Rgs2

Stk6

FURTHER INFORMATION

Entrez Gene

Gene Network

Mouse Genome Informatics

Mouse Phenome Database

US National Institute of Environmental Health Sciences Press Releases

Glossary

EFFECT SIZE

The percentage of the total phenotypic variation that is attributable to a QTL.

CONGENIC

A strain produced by a breeding strategy that delineates a genomic region containing a trait locus. Recombinants between two inbred strains are backcrossed to produce a strain that carries a single segment from one strain on the genetic background of the other.

INTROGRESSION

Introduction of a chromosomal segment from one strain into another by interbreeding.

HIDDEN MARKOV MODEL

A probabilistic description of a system in which the observed data depends on the hidden internal state of the system. The objective is usually to infer the likelihood that the system is in a particular hidden state, given the observed data.

DYNAMIC PROGRAMMING ALGORITHM

An algorithm that finds the optimum solution to a problem involving N objects in terms of the solutions to a series of smaller problems that involve subsets of the objects.

ANALYSIS OF VARIANCE

A statistical method to test the null hypothesis that the mean values of two or more groups are equal. The variance around the mean in groups is compared with the variance of the group mean. In genetic applications, the variance between families is compared with the variance within families. A significant F-ratio implies that variance between families is larger than within families.

ADMIXTURE MAPPING

Genetic mapping using individuals whose genomes are mosaics of fragments that are descended from genetically distinct populations. This method exploits differences in allele frequencies in the founders to determine ancestry at a locus in order to map traits, in a way that is broadly similar to an advanced intercross.

LINKAGE DISEQUILIBRIUM

The tendency for markers to have correlated genotypes when they are physically close together. Over several generations, recombination will break down linkage between markers and a QTL, so that linkage disequilibrium will only occur between markers that are close to a QTL. This explains why outbred animals can provide high-mapping resolution.

HAPLOTYPE SHARING

Sets of closely linked genetic variants in different individuals that are identical by descent around a locus.

Rights and permissions

Reprints and Permissions

About this article

Cite this article

Flint, J., Valdar, W., Shifman, S. et al. Strategies for mapping and cloning quantitative trait genes in rodents. Nat Rev Genet 6, 271–286 (2005). https://doi.org/10.1038/nrg1576

Download citation

  • Issue Date:

  • DOI: https://doi.org/10.1038/nrg1576

This article is cited by

Search

Advanced search

Quick links

Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing