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.

  • Review Article
  • Published:

Congenic mice: cutting tools for complex immune disorders

Key Points

  • In general, autoimmune diseases, which are an important source of disease affecting the adult human population, are under complex genetic control and subject to strong genetic interactions.

  • An improved knowledge of the underlying genetics will provide immunologists with a framework for studying the immune dysregulation that occurs in such diseases.

  • Ascertainment of the number of genes that are involved and their characterization has proven to be difficult in humans, in part because of the clinical and genetic heterogeneity of human populations, and in part because of the underlying intrinsic genetic complexity of autoimmune diseases.

  • Using mouse models of human diseases that are under complex genetic control, such as insulin-dependent diabetes mellitus or systemic lupus erythematosus, can alleviate these problems.

  • Improved methods of genetic analysis, the availability of a draft sequence of the complete mouse genome, annotated complementary DNA libraries and new tools for expression and functional analysis have markedly improved the outlook for such research and emphasized the advantages of mice as a model system.

  • In this review, we provide an overview of the genetic analysis of autoimmune diseases and the crucial role played by congenic and consomic mouse strains in such research, and of current strategies and ongoing efforts to understand autoimmune diseases.

Abstract

Autoimmune diseases are, in general, under complex genetic control and subject to strong interactions between genetics and the environment. Greater knowledge of the underlying genetics will provide immunologists with a framework for study of the immune dysregulation that occurs in such diseases. Ascertaining the number of genes that are involved and their characterization have, however, proven to be difficult. Improved methods of genetic analysis and the availability of a draft sequence of the complete mouse genome have markedly improved the outlook for such research, and they have emphasized the advantages of mice as a model system. In this review, we provide an overview of the genetic analysis of autoimmune diseases and of the crucial role of congenic and consomic mouse strains in such research.

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

Access options

Buy this article

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

Figure 1: Selected analytical tools in mouse genetics.
Figure 2: Comparison of classical-breeding and selected-breeding approaches to congenic-strain construction.
Figure 3: Haplotype mapping can help to reduce the size of a congenic candidate region.
Figure 4: The pivotal position occupied by congenic strains in the analysis of complex traits.

Similar content being viewed by others

References

  1. Vetrie, D. et al. The gene involved in X-linked agammaglobulinaemia is a member of the src family of protein-tyrosine kinases. Nature 361, 226–233 (1993).

    CAS  PubMed  Google Scholar 

  2. Becker, K. G. et al. Clustering of non-major histocompatibility complex susceptibility candidate loci in human autoimmune diseases. Proc. Natl Acad. Sci. USA 95, 9979–9984 (1998). This study describes the 'non-random clustering' hypothesis, which proposes that, in some cases, clinically distinct autoimmune diseases might be controlled by a common set of susceptibility genes.

    CAS  PubMed  PubMed Central  Google Scholar 

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

    CAS  PubMed  Google Scholar 

  4. Nolan, P. M. et al. A systematic, genome-wide, phenotype-driven mutagenesis programme for gene-function studies in the mouse. Nature Genet. 25, 440–443 (2000). This study describes genome-wide, phenotype-driven screens for dominant mutations in mice.

    CAS  PubMed  Google Scholar 

  5. Nelms, K. A. & Goodnow, C. C. Genome-wide ENU mutagenesis to reveal immune regulators. Immunity 15, 409–418 (2001). This paper describes the use of genome-wide chemical mutagenesis in mice as an extremely powerful methodology for the identification of genes that are required for complex immunological processes.

    CAS  PubMed  Google Scholar 

  6. Festing, M. F. W. Inbred Strains in Biomedical Research (Macmillian Press, London and Basingstoke, 1979).

    Google Scholar 

  7. Paigen, K. & Eppig, J. T. A mouse phenome project. Mamm. Genome 11, 715–717 (2000). A community-wide effort to establish baseline phenotypic data on commonly used and genetically diverse inbred mouse strains and to provide this information through a publicly accessible database.

    CAS  PubMed  Google Scholar 

  8. Nadeau, J. H. & Frankel, W. N. The roads from phenotypic variation to gene discovery: mutagenesis versus QTLs. Nature Genet. 25, 381–384 (2000).

    CAS  PubMed  Google Scholar 

  9. Nadeau, J. H. et al. Sequence interpretation. Functional annotation of mouse genome sequences. Science 291, 1251–1255 (2001).

    CAS  PubMed  Google Scholar 

  10. Avner, P. A toolbox for a small mammal. Mamm. Genome 13, 125–126 (2002).

    PubMed  Google Scholar 

  11. Fraser, A. G. et al. Functional genomic analysis of C. elegans chromosome I by systematic RNA interference. Nature 408, 325–330 (2000). RNA interference (RNAi) is used to target nearly 90% of predicted genes on Caenorhabditis elegans chromosome I by feeding worms with bacteria that express double-stranded RNA.

    CAS  PubMed  Google Scholar 

  12. Kamath, R. S. et al. Systematic functional analysis of the Caenorhabditis elegans genome using RNAi. Nature 421, 231–237 (2003). This study describes the use of RNAi to inhibit the function of 86% of the 19,427 predicted genes of C. elegans.

    CAS  PubMed  Google Scholar 

  13. Fortin, A. et al. Identification of a new malaria susceptibility locus (Char4) in recombinant congenic strains of mice. Proc. Natl Acad. Sci. USA 98, 10793–10798 (2001).

    CAS  PubMed  PubMed Central  Google Scholar 

  14. Bentley, D. R. The Human Genome Project — an overview. Med. Res. Rev. 20, 189–196 (2000).

    CAS  PubMed  Google Scholar 

  15. 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). This paper describes an approach in which a panel of chromosome-substitution strains (CSSs) were used for mapping of quantitative trait loci (QTL).

    CAS  PubMed  Google Scholar 

  16. Santos, J. et al. A new locus for resistance to γ-radiation-induced thymic lymphoma identified using inter-specific consomic and inter-specific recombinant congenic strains of mice. Oncogene 21, 6680–6683 (2002).

    CAS  PubMed  Google Scholar 

  17. Boyse, E. A. & Bentley, D. R. The increasing value of congenic mice in biomedical research. Lab. Anim. Sci. 27, 771–781 (1977).

    CAS  PubMed  Google Scholar 

  18. Wakeland, E., Morel, L., Achey, K., Yui, M. & Longmate, J. Speed congenics: a classic technique in the fast lane (relatively speaking). Immunol. Today 18, 472–477 (1997).

    CAS  PubMed  Google Scholar 

  19. Roths, J. B., Murphy, E. D. & Eicher, E. M. A new mutation, gld, that produces lymphoproliferation and autoimmunity in C3H/HeJ mice. J. Exp. Med. 159, 1–20 (1984).

    CAS  PubMed  Google Scholar 

  20. Castano, L. & Eisenbarth, G. S. Type-I diabetes: a chronic autoimmune disease of human, mouse and rat. Annu. Rev. Immunol. 8, 647–679 (1990).

    CAS  PubMed  Google Scholar 

  21. Delovitch, T. L. & Singh, B. The nonobese diabetic mouse as a model of autoimmune diabetes: immune dysregulation gets the NOD. Immunity 7, 727–738 (1997).

    CAS  PubMed  Google Scholar 

  22. Hattori, M. et al. The NOD mouse: recessive diabetogenic gene in the major histocompatibility complex. Science 231, 733–735 (1986).

    CAS  PubMed  Google Scholar 

  23. Adorini, L., Gregori, S. & Harrison, L. C. Understanding autoimmune diabetes: insights from mouse models. Trends Mol. Med. 8, 31–38 (2002).

    CAS  PubMed  Google Scholar 

  24. Bergman, M. L. et al. CTLA-4−/− mice display T-cell-apoptosis resistance resembling that ascribed to autoimmune-prone non-obese diabetic (NOD) mice. J. Autoimmun. 16, 105–113 (2001).

    CAS  PubMed  Google Scholar 

  25. Penha-Goncalves, C., Leijon, K., Persson, L. & Holmberg, D. Type 1 diabetes and the control of dexamethazone-induced apoptosis in mice maps to the same region on chromosome 6. Genomics 28, 398–404 (1995).

    CAS  PubMed  Google Scholar 

  26. Vyse, T. J. & Todd, J. A. Genetic analysis of autoimmune disease. Cell 85, 311–318 (1996).

    CAS  PubMed  Google Scholar 

  27. Doerge, R. W. Mapping and analysis of quantitative trait loci in experimental populations. Nature Rev. Genet. 3, 43–52 (2002).

    CAS  PubMed  Google Scholar 

  28. Prochazka, M., Serreze, D. V., Worthen, S. M. & Leiter, E. H. Genetic control of diabetogenesis in NOD/Lt mice. Development and analysis of congenic stocks. Diabetes 38, 1446–1455 (1989).

    CAS  PubMed  Google Scholar 

  29. Wicker, L. S. et al. Autoimmune syndromes in major histocompatibility complex (MHC) congenic strains of nonobese diabetic (NOD) mice. The NOD MHC is dominant for insulitis and cyclophosphamide-induced diabetes. J. Exp. Med. 176, 67–77 (1992).

    CAS  PubMed  Google Scholar 

  30. Prins, J. B. et al. Linkage on chromosome 3 of autoimmune diabetes and defective Fc receptor for IgG in NOD mice. Science 260, 695–698 (1993).

    CAS  PubMed  Google Scholar 

  31. Serreze, D. V., Prochazka, M., Reifsnyder, P. C., Bridgett, M. M. & Leiter, E. H. Use of recombinant congenic and congenic strains of NOD mice to identify a new insulin-dependent diabetes resistance gene. J. Exp. Med. 180, 1553–1558 (1994).

    CAS  PubMed  Google Scholar 

  32. McAleer, M. A. et al. Crosses of NOD mice with the related NON strain. A polygenic model for IDDM. Diabetes 44, 1186–1195 (1995).

    CAS  PubMed  Google Scholar 

  33. Grattan, M., Mi, Q. S., Meagher, C. & Delovitch, T. L. Congenic mapping of the diabetogenic locus Idd4 to a 5.2-cM region of chromosome 11 in NOD mice: identification of two potential candidate subloci. Diabetes 51, 215–223 (2002).

    CAS  PubMed  Google Scholar 

  34. Lamhamedi-Cherradi, S. E. et al. Further mapping of the Idd5.1 locus for autoimmune diabetes in NOD mice. Diabetes 50, 2874–2878 (2001).

    CAS  PubMed  Google Scholar 

  35. Hill, N. J. et al. NOD Idd5 locus controls insulitis and diabetes and overlaps the orthologous CTLA4/IDDM12 and NRAMP1 loci in humans. Diabetes 49, 1744–1747 (2000).

    CAS  PubMed  Google Scholar 

  36. Iakoubova, O. A. et al. Genome-tagged mice (GTM): two sets of genome-wide congenic strains. Genomics 74, 89–104 (2001). Marker-assisted breeding was used to construct two sets of overlapping congenic strains, known as genome-tagged mice (GTM), that span the entire mouse genome. C57BL/6J was used as a background strain for both GTM sets, with either DBA/2J mice or CAST/Ei mice as the donor strain.

    CAS  PubMed  Google Scholar 

  37. Markel, P. et al. Theoretical and empirical issues for marker-assisted breeding of congenic mouse strains. Nature Genet. 17, 280–284 (1997). This paper presents a theoretical evaluation of marker-assisted production of congenic mice and provides the empirical data to support it.

    CAS  PubMed  Google Scholar 

  38. Winer, S. et al. ICA69(null) nonobese diabetic mice develop diabetes, but resist disease acceleration by cyclophosphamide. J. Immunol. 168, 475–482 (2002).

    CAS  PubMed  Google Scholar 

  39. Serreze, D. V. et al. B lymphocytes are essential for the initiation of T-cell-mediated autoimmune diabetes: analysis of a new 'speed congenic' stock of NOD.Igμ null mice. J. Exp. Med. 184, 2049–2053 (1996).

    CAS  PubMed  Google Scholar 

  40. Lyon, M. F. et al. A personal history of the mouse genome. Annu. Rev. Genomics Hum. Genet. 3, 1–16 (2002). This article describes some personal reminiscences of various stages in the growth of knowledge of the mouse genome over the past 50 years.

    CAS  PubMed  Google Scholar 

  41. de Gouyon, B. et al. Genetic analysis of diabetes and insulitis in an interspecific cross of the nonobese diabetic mouse with Mus spretus. Proc. Natl Acad. Sci. USA 90, 1877–1881 (1993).

    CAS  PubMed  PubMed Central  Google Scholar 

  42. Wade, C. M. et al. The mosaic structure of variation in the laboratory mouse genome. Nature 420, 574–578 (2002). This study presents an analysis of the fine structure of variation in the mouse genome, using single-nucleotide polymorphisms (SNPs).

    CAS  PubMed  Google Scholar 

  43. Wicker, L. S. et al. Resistance alleles at two non-major histocompatibility complex-linked insulin-dependent diabetes loci on chromosome 3, Idd3 and Idd10, protect nonobese diabetic mice from diabetes. J. Exp. Med. 180, 1705–1713 (1994).

    CAS  PubMed  Google Scholar 

  44. 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).

    CAS  PubMed  Google Scholar 

  45. Podolin, P. L. et al. Congenic mapping of the insulin-dependent diabetes (Idd) gene, Idd10, localizes two genes mediating the Idd10 effect and eliminates the candidate Fcgr1. J. Immunol. 159, 1835–1843 (1997).

    CAS  PubMed  Google Scholar 

  46. Lyons, P. A. et al. The NOD Idd9 genetic interval influences the pathogenicity of insulitis and contains molecular variants of Cd30, Tnfr2 and Cd137. Immunity 13, 107–115 (2000).

    CAS  PubMed  Google Scholar 

  47. Rogner, U. C., Boitard, C., Morin, J., Melanitou, E. & Avner, P. Three loci on mouse chromosome 6 influence onset and final incidence of type I diabetes in NOD.C3H congenic strains. Genomics 74, 163–171 (2001).

    CAS  PubMed  Google Scholar 

  48. Steinmetz, L. M. et al. Dissecting the architecture of a quantitative trait locus in yeast. Nature 416, 326–330 (2002). The authors of this paper discovered a QTL architecture that was more complex than expected. Functional linkages both in cis and in trans were found between three tightly linked quantitative trait genes that are neither necessary nor sufficient for the phenotype in isolation.

    CAS  PubMed  Google Scholar 

  49. Silveira, P. A. & Baxter, A. G. The NOD mouse as a model of SLE. Autoimmunity 34, 53–64 (2001).

    CAS  PubMed  Google Scholar 

  50. Fortin, A. et al. Recombinant congenic strains derived from A/J and C57BL/6J: a tool for genetic dissection of complex traits. Genomics 74, 21–35 (2001).

    CAS  PubMed  Google Scholar 

  51. Threadgill, D. W., Hunter, K. W. & Williams, R. W. Genetic dissection of complex and quantitative traits: from fantasy to reality via a community effort. Mamm. Genome 13, 175–178 (2002).

    CAS  PubMed  Google Scholar 

  52. Lyons, P. A. et al. Congenic mapping of the type 1 diabetes locus, Idd3, to a 780-kb region of mouse chromosome 3: identification of a candidate segment of ancestral DNA by haplotype mapping. Genome Res. 10, 446–453 (2000).

    CAS  PubMed  PubMed Central  Google Scholar 

  53. Ikegami, H. et al. Identification of a new susceptibility locus for insulin-dependent diabetes mellitus by ancestral haplotype congenic mapping. J. Clin. Invest. 96, 1936–1942 (1995).

    CAS  PubMed  PubMed Central  Google Scholar 

  54. Lindblad-Toh, K. et al. Large-scale discovery and genotyping of single-nucleotide polymorphisms in the mouse. Nature Genet. 24, 381–386 (2000). This study characterized the rate of nucleotide polymorphism in eight mouse strains and identified a collection of 2,848 SNPs located at 1,755 sequence-tagged sites using high-density oligonucleotide arrays. The authors developed a multiplex-genotyping procedure by which a genome scan can be carried out with only six genotyping reactions per animal.

    CAS  PubMed  Google Scholar 

  55. Grupe, A. et al. In silico mapping of complex disease-related traits in mice. Science 292, 1915–1918 (2001). A computational method for predicting chromosomal regions that regulate phenotypic traits and a mouse database of SNPs were developed. After entry of phenotypic information obtained from inbred mouse strains, the phenotypic and genotypic information is analysed in silico to predict the chromosomal regions that regulate the phenotypic trait.

    CAS  PubMed  Google Scholar 

  56. Symula, D. J. et al. Functional screening of an asthma QTL in YAC-transgenic mice. Nature Genet. 23, 241–244 (1999).

    CAS  PubMed  Google Scholar 

  57. 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).

    CAS  PubMed  Google Scholar 

  58. Lock, C. et al. Gene-microarray analysis of multiple sclerosis lesions yields new targets validated in autoimmune encephalomyelitis. Nature Med. 8, 500–508 (2002).

    CAS  PubMed  Google Scholar 

  59. Scearce, L. M. et al. Functional genomics of the endocrine pancreas: the pancreas clone set and PancChip, new resources for diabetes research. Diabetes 51, 1997–2004 (2002).

    CAS  PubMed  Google Scholar 

  60. McHugh, R. S. et al. CD4+CD25+ immunoregulatory T cells: gene-expression analysis reveals a functional role for the glucocorticoid-induced TNF receptor. Immunity 16, 311–323 (2002).

    CAS  PubMed  Google Scholar 

  61. Granucci, F., Castagnoli, P. R., Rogge, L. & Sinigaglia, F. Gene-expression profiling in immune cells using microarray. Int. Arch. Allergy Immunol. 126, 257–266 (2001).

    CAS  PubMed  Google Scholar 

  62. Mikulowska-Mennis, A. et al. High-quality RNA from cells isolated by laser-capture microdissection. Biotechniques 33, 176–179 (2002).

    CAS  PubMed  Google Scholar 

  63. Rekhter, M. D. & Chen, J. Molecular analysis of complex tissues is facilitated by laser-capture microdissection: critical role of upstream tissue processing. Cell. Biochem. Biophys. 35, 103–113 (2001).

    CAS  PubMed  Google Scholar 

  64. Giraldo, P. & Montoliu, L. Size matters: use of YACs, BACs and PACs in transgenic animals. Transgenic Res. 10, 83–103 (2001). This article reviews the recent history of YAC/BAC/PAC-transgenic animals, indicating their benefits and the potential problems associated with their use.

    CAS  PubMed  Google Scholar 

  65. Waterston, R. H. et al. Initial sequencing and comparative analysis of the mouse genome. Nature 420, 520–562 (2002). This study reports the results of an international collaboration to produce a high-quality draft sequence of the mouse genome.

    CAS  PubMed  Google Scholar 

  66. Yu, Y. & Bradley, A. Engineering chromosomal rearrangements in mice. Nature Rev. Genet. 2, 780–790 (2001).

    CAS  PubMed  Google Scholar 

  67. Yoon, J. W. et al. Control of autoimmune diabetes in NOD mice by GAD expression or suppression in β-cells. Science 284, 1183–1187 (1999).

    CAS  PubMed  Google Scholar 

  68. Zhao, S. et al. Mouse BAC ends quality assessment and sequence analyses. Genome Res. 11, 1736–1745 (2001).

    PubMed  PubMed Central  Google Scholar 

  69. Wang, Z., Engler, P., Longacre, A. & Storb, U. An efficient method for high-fidelity BAC/PAC retrofitting with a selectable marker for mammalian-cell transfection. Genome Res. 11, 137–142 (2001).

    CAS  PubMed  PubMed Central  Google Scholar 

  70. Schuster-Gossler, K. et al. Use of coisogenic host blastocysts for efficient establishment of germline chimeras with C57BL/6J ES cell lines. Biotechniques 31, 1022–1024, 1026 (2001).

    CAS  PubMed  Google Scholar 

  71. Nagafuchi, S. et al. Establishment of an embryonic stem (ES)-cell line derived from a non-obese diabetic (NOD) mouse: in vivo differentiation into lymphocytes and potential for germ-line transmission. FEBS Lett. 455, 101–104 (1999).

    CAS  PubMed  Google Scholar 

  72. Brook, F. A. et al. The derivation of highly germline-competent embryonic stem cells containing NOD-derived genome. Diabetes 52, 205–208 (2003). This study reports the development of highly germline-competent embryonic stem-cell lines from the F 1 hybrid of non-obese diabetic (NOD) and 129 mice for use in NOD gene targeting.

    CAS  PubMed  Google Scholar 

  73. Cullen, B. R. RNA interference: antiviral defense and genetic tool. Nature Immunol. 3, 597–599 (2002).

    CAS  Google Scholar 

  74. McCaffrey, A. P. et al. RNA interference in adult mice. Nature 418, 38–39 (2002). These authors show that transgene expression can be suppressed in adult mice by synthetic small interfering RNAs and by small hairpin RNAs transcribed in vivo from DNA templates. They also show the therapeutic potential of this technique by demonstrating effective targeting of a sequence from hepatitis C virus by RNAi in vivo.

    CAS  PubMed  Google Scholar 

  75. Hannon, G. J. RNA interference. Nature 418, 244–251 (2002).

    CAS  PubMed  Google Scholar 

  76. Yu, J. Y., DeRuiter, S. L. & Turner, D. L. RNA interference by expression of short-interfering RNAs and hairpin RNAs in mammalian cells. Proc. Natl Acad. Sci. USA 99, 6047–6052 (2002).

    CAS  PubMed  PubMed Central  Google Scholar 

  77. Paddison, P. J., Caudy, A. A., Bernstein, E., Hannon, G. J. & Conklin, D. S. Short hairpin RNAs (shRNAs) induce sequence-specific silencing in mammalian cells. Genes Dev. 16, 948–958 (2002).

    CAS  PubMed  PubMed Central  Google Scholar 

  78. Sijen, T. et al. On the role of RNA amplification in dsRNA-triggered gene silencing. Cell 107, 465–476 (2001).

    CAS  PubMed  Google Scholar 

  79. Nishikura, K. A short primer on RNAi: RNA-directed RNA polymerase acts as a key catalyst. Cell 107, 415–418 (2001).

    CAS  PubMed  Google Scholar 

  80. Tsao, B. P. et al. Evidence for linkage of a candidate chromosome 1 region to human systemic lupus erythematosus. J. Clin. Invest. 99, 725–731 (1997).

    CAS  PubMed  PubMed Central  Google Scholar 

  81. Sobel, E. S., Satoh, M., Chen, Y., Wakeland, E. K. & Morel, L. The major murine systemic lupus erythematosus susceptibility locus Sle1 results in abnormal functions of both B and T cells. J. Immunol. 169, 2694–2700 (2002).

    CAS  PubMed  Google Scholar 

  82. Morel, L. et al. Functional dissection of systemic lupus erythematosus using congenic mouse strains. J. Immunol. 158, 6019–6028 (1997).

    CAS  PubMed  Google Scholar 

  83. Morel, L. et al. Genetic reconstitution of systemic lupus erythematosus immunopathology with polycongenic murine strains. Proc. Natl Acad. Sci. USA 97, 6670–6675 (2000).

    CAS  PubMed  PubMed Central  Google Scholar 

  84. Morel, L., Blenman, K. R., Croker, B. P. & Wakeland, E. K. The major murine systemic lupus erythematosus susceptibility locus, Sle1, is a cluster of functionally related genes. Proc. Natl Acad. Sci. USA 98, 1787–1792 (2001).

    CAS  PubMed  PubMed Central  Google Scholar 

  85. Kumar, R. K. & Foster, P. S. Modeling allergic asthma in mice: pitfalls and opportunities. Am. J. Respir. Cell. Mol. Biol. 27, 267–272 (2002).

    CAS  PubMed  Google Scholar 

  86. Gleich, G. J. et al. Bronchial asthma: lessons from murine models. Proc. Natl Acad. Sci. USA 94, 2101–2102 (1997).

    CAS  PubMed  PubMed Central  Google Scholar 

  87. Mehlhop, P. D. et al. Allergen-induced bronchial hyperreactivity and eosinophilic inflammation occur in the absence of IgE in a mouse model of asthma. Proc. Natl Acad. Sci. USA 94, 1344–1349 (1997).

    CAS  PubMed  PubMed Central  Google Scholar 

  88. Gavett, S. H., Chen, X., Finkelman, F. & Wills-Karp, M. Depletion of murine CD4+ T lymphocytes prevents antigen-induced airway hyperreactivity and pulmonary eosinophilia. Am. J. Respir. Cell. Mol. Biol. 10, 587–593 (1994).

    CAS  PubMed  Google Scholar 

  89. Foster, P. S., Hogan, S. P., Ramsay, A. J., Matthaei, K. I. & Young, I. G. Interleukin-5 deficiency abolishes eosinophilia, airways hyperreactivity and lung damage in a mouse asthma model. J. Exp. Med. 183, 195–201 (1996).

    CAS  PubMed  Google Scholar 

  90. McIntire, J. J. et al. Identification of Tapr (an airway hyperreactivity regulatory locus) and the linked Tim gene family. Nature Immunol. 2, 1109–1116 (2001).

    CAS  Google Scholar 

  91. Ji, H. et al. Genetic influences on the end-stage effector phase of arthritis. J. Exp. Med. 194, 321–330 (2001).

    CAS  PubMed  PubMed Central  Google Scholar 

  92. Nose, M., Nishihara, M., Kamogawa, J., Terada, M. & Nakatsuru, S. Genetic basis of autoimmune disease in MRL/lpr mice: dissection of the complex pathological manifestations and their susceptibility loci. Rev. Immunogenet. 2, 154–164 (2000).

    CAS  PubMed  Google Scholar 

  93. Smith, D. J. & Lusis, A. J. The allelic structure of common disease. Hum. Mol. Genet. 11, 2455–2461 (2002).

    CAS  PubMed  Google Scholar 

  94. Mendell, J. T., ap Rhys, C. M. & Dietz, H. C. Separable roles for rent1/hUpf1 in altered splicing and decay of nonsense transcripts. Science 298, 419–422 (2002).

    CAS  PubMed  Google Scholar 

  95. Okazaki, Y. et al. Analysis of the mouse transcriptome based on functional annotation of 60,770 full-length cDNAs. Nature 420, 563–573 (2002).

    PubMed  Google Scholar 

  96. Kono, D. H. & Theofilopoulos, A. N. Genetics of systemic autoimmunity in mouse models of lupus. Int. Rev. Immunol. 19, 367–387 (2000).

    CAS  PubMed  Google Scholar 

  97. Peirce, J. Looking at old tools in new ways: using knockouts as congenics to study QTLs. Genome Res. 11, 1469–1471 (2001).

    CAS  PubMed  Google Scholar 

Download references

Acknowledgements

We thank our colleagues F. Lepault, F. Colucci, J. Di Santo and C. Boitard for their critical comments on the manuscript.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Philip Avner.

Related links

Related links

DATABASES

LocusLink

GAD

Tim1

TIM1

OMIM

asthma

Bruton's autoimmune syndrome and X-linked agammaglobulinaemia

IDDM

multiple sclerosis

rheumatoid arthritis

SLE

Glossary

INBRED STRAIN

A strain that is essentially homozygous at all genetic loci. In mice, such strains are produced by brother–sister mating for at least 12 sequential generations, or more if other breeding systems are used.

RNA INTERFERENCE

(RNAi). A technique in which the expression of a gene is inhibited when a double-stranded complementary RNA is introduced into the organism.

PENETRANCE

The proportion of affected individuals among carriers of a particular genotype. If all individuals with a disease genotype show the disease phenotype, then the disease is said to be completely penetrant.

HAPLOTYPE

An alternative form of a group of genes, part of a chromosome or a gene complex. The term is applied to groups of genetic loci, whereas the term 'allele' refers to alternative forms of a single gene.

QUANTITATIVE TRAIT LOCI

(QTLs). Loci segregating alleles that have substantial input to the overall phenotype of a trait that is under complex genetic control.

YEAST ARTIFICIAL CHROMOSOME

(YAC). A large genomic fragment of up to 1 Mb in size, containing a centromere, an origin of replication and telomere sequences, that can be cloned into autonomously replicating yeast vectors. The genomic DNA fragments are maintained and propagated in the yeast Saccharomyces cerevisiae as linear chromosomes.

BACTERIAL ARTIFICIAL CHROMOSOME

(BAC). A cloning vector derived from a single-copy F-plasmid of Escherichia coli that carries the F replication and partitioning systems that ensure low copy number and faithful segregation of plasmid DNA to daughter cells. Large genomic fragments can be cloned into such vectors and they are faithfully replicated, which makes BACs useful for constructing genomic libraries.

EPISTASIS

When the phenotype caused by a mutation in one gene is masked or enhanced by a mutation in another gene.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Rogner, U., Avner, P. Congenic mice: cutting tools for complex immune disorders. Nat Rev Immunol 3, 243–252 (2003). https://doi.org/10.1038/nri1031

Download citation

  • Issue Date:

  • DOI: https://doi.org/10.1038/nri1031

This article is cited by

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