Recurrent DNA copy number variation in the laboratory mouse

Article metrics

Abstract

Different species, populations and individuals vary considerably in the copy number of discrete segments of their genomes. The manner and frequency with which these genetic differences arise over generational time is not well understood. Taking advantage of divergence among lineages sharing a recent common ancestry, we have conducted a genome-wide analysis of spontaneous copy number variation (CNV) in the laboratory mouse. We used high-resolution microarrays to identify 38 CNVs among 14 colonies of the C57BL/6 strain spanning 967 generations of inbreeding, and we examined these loci in 12 additional strains. It is clear from our results that many CNVs arise through a highly nonrandom process: 18 of 38 were the product of recurrent mutation, and rates of change varied roughly four orders of magnitude across different loci. Recurrent CNVs are found throughout the genome, affect 43 genes and fluctuate in copy number over mere hundreds of generations, observations that raise questions about their contribution to natural variation.

Access optionsAccess options

Rent or Buy article

Get time limited or full article access on ReadCube.

from$8.99

All prices are NET prices.

Figure 1: Examples of microarray data for three substrains at six loci, demonstrating representative data quality and experimental design.
Figure 2: Distribution of CNVs relative to the strain genealogy.

Accession codes

Accessions

Gene Expression Omnibus

References

  1. 1

    Bailey, J.A. & Eichler, E.E. Primate segmental duplications: crucibles of evolution, diversity and disease. Nat. Rev. Genet. 7, 552–564 (2006).

  2. 2

    Sebat, J. et al. Large-scale copy number polymorphism in the human genome. Science 305, 525–528 (2004).

  3. 3

    Iafrate, A.J. et al. Detection of large-scale variation in the human genome. Nat. Genet. 36, 949–951 (2004).

  4. 4

    Tuzun, E. et al. Fine-scale structural variation of the human genome. Nat. Genet. 37, 727–732 (2005).

  5. 5

    McCarroll, S.A. et al. Common deletion polymorphisms in the human genome. Nat. Genet. 38, 86–92 (2006).

  6. 6

    Hinds, D.A., Kloek, A.P., Jen, M., Chen, X.Y. & Frazer, K.A. Common deletions and SNPs are in linkage disequilibrium in the human genome. Nat. Genet. 38, 82–85 (2006).

  7. 7

    Conrad, D.F., Andrews, T.D., Carter, N.P., Hurles, M.E. & Pritchard, J.K. A high-resolution survey of deletion polymorphism in the human genome. Nat. Genet. 38, 75–81 (2006).

  8. 8

    Locke, D.P. et al. Linkage disequilibrium and heritability of copy-number polymorphisms within duplicated regions of the human genome. Am. J. Hum. Genet. 79, 275–290 (2006).

  9. 9

    Redon, R. et al. Global variation in copy number in the human genome. Nature 444, 444–454 (2006).

  10. 10

    Perry, G.H. et al. Hotspots for copy number variation in chimpanzees and humans. Proc. Natl. Acad. Sci. USA 103, 8006–8011 (2006).

  11. 11

    Li, J. et al. Genomic segmental polymorphisms in inbred mouse strains. Nat. Genet. 36, 952–954 (2004).

  12. 12

    Snijders, A.M. et al. Mapping segmental and sequence variations among laboratory mice using BAC array CGH. Genome Res. 15, 302–311 (2005).

  13. 13

    van Ommen, G.J. Frequency of new copy number variation in humans. Nat. Genet. 37, 333–334 (2005).

  14. 14

    Hollies, C.R., Monckton, D.G. & Jeffreys, A.J. Attempts to detect retrotransposition and de novo deletion of Alus and other dispersed repeats at specific loci in the human genome. Eur. J. Hum. Genet. 9, 143–146 (2001).

  15. 15

    Han, L.L., Keller, M.P., Navidi, W., Chance, P.F. & Arnheim, N. Unequal exchange at the Charcot-Marie-Tooth disease type 1A recombination hot-spot is not elevated above the genome average rate. Hum. Mol. Genet. 9, 1881–1889 (2000).

  16. 16

    Tusie-Luna, M.T. & White, P.C. Gene conversions and unequal crossovers between CYP21 (steroid 21-hydroxylase gene) and CYP21P involve different mechanisms. Proc. Natl. Acad. Sci. USA 92, 10796–10800 (1995).

  17. 17

    Inoue, K. & Lupski, J.R. Molecular mechanisms for genomic disorders. Annu. Rev. Genomics Hum. Genet. 3, 199–242 (2002).

  18. 18

    Repping, S. et al. High mutation rates have driven extensive structural polymorphism among human Y chromosomes. Nat. Genet. 38, 463–467 (2006).

  19. 19

    Sharp, A.J. et al. Segmental duplications and copy-number variation in the human genome. Am. J. Hum. Genet. 77, 78–88 (2005).

  20. 20

    Haldane, J.B.S. The amount of heterozygosity to be expected in an approximately pure line. J. Genet. 32, 375–391 (1936).

  21. 21

    Lucito, R. et al. Representational oligonucleotide microarray analysis: a high-resolution method to detect genome copy number variation. Genome Res. 13, 2291–2305 (2003).

  22. 22

    Lakshmi, B. et al. Mouse genomic representational oligonucleotide microarray analysis: detection of copy number variations in normal and tumor specimens. Proc. Natl. Acad. Sci. USA 103, 11234–11239 (2006).

  23. 23

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

  24. 24

    Drake, J.W., Charlesworth, B., Charlesworth, D. & Crow, J.F. Rates of spontaneous mutation. Genetics 148, 1667–1686 (1998).

  25. 25

    Kipling, D., Salido, E.C., Shapiro, L.J. & Cooke, H.J. High frequency de novo alterations in the long-range genomic structure of the mouse pseudoautosomal region. Nat. Genet. 13, 78–80 (1996).

  26. 26

    She, X. et al. A preliminary comparative analysis of primate segmental duplications shows elevated substitution rates and a great-ape expansion of intrachromosomal duplications. Genome Res. 16, 576–583 (2006).

  27. 27

    Selzer, R.R. et al. Analysis of chromosome breakpoints in neuroblastoma at sub-kilobase resolution using fine-tiling oligonucleotide array CGH. Genes Chromosom. Cancer 44, 305–319 (2005).

  28. 28

    Kent, W.J. BLAT—the BLAST-like alignment tool. Genome Res. 12, 656–664 (2002).

  29. 29

    Huang, Y. & Zhang, L. Rapid and sensitive dot-matrix methods for genome analysis. Bioinformatics 20, 460–466 (2004).

  30. 30

    Hsu, F. et al. The UCSC Known Genes. Bioinformatics 22, 1036–1046 (2006).

Download references

Acknowledgements

We thank J.C. Mell, L. Stein, B. Stillman and J.D. Watson for comments on the manuscript; L. Bianco for technical assistance; C. Ward for the B6N substrain and for advice; H. Hedrich and M. Dorsch for supplying the B6HanZtm substrain; A. Lerro for the B6Icr substrain; all strain suppliers for crucial genealogical details; N. Navin, V. Grubor, B. Lakshmi, A. Leotta and J. Kendall for computational contributions; and X. She and E.E. Eichler for sharing unpublished data. This work was supported by grants to I.M.H. from the Cold Spring Harbor President's Council and the Burroughs Wellcome Fund and to M.W. from The Simons Foundation. M.W. is an American Cancer Society Research Professor.

Author information

C.M.E. performed most of the microarray experiments, all of the PCR and DNA sequencing, and some of the data analysis. S.S. designed and implemented algorithms to identify CNVs and calculate mutation rates, and advised on all computational matters. M.W. contributed reagents and advice and helped calculate rates. I.M.H. conceived the study, obtained strains and genealogical information, performed many of the microarray experiments and most of the data analysis, and wrote the paper.

Correspondence to Ira M Hall.

Supplementary information

Supplementary Text and Figures

Supplementary Note, Supplementary Methods, Supplementary Figures 1–5, Supplementary Table 1 (PDF 22008 kb)

Rights and permissions

Reprints and Permissions

About this article

Further reading