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Human genomics

In search of normality

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The first map of copy-number variation in the human genome has been created. It is now feasible to examine the role of such genome variation in disease and to explore in depth the extent of 'normal' variability.

The human genome contains many forms of genetic variation. The most plentiful are the millions of single base-pair changes in the DNA code that were identified in the course of determining the human genome sequence, and then more systematically through the International HapMap Project1. These so-called single nucleotide polymorphisms (SNPs) distinguish any two unrelated copies of the genome. They account for the long-hypothesized, evolutionarily 'neutral' forms of widespread genetic variation that mark diversity within our species, as well as mutations, both rare and common, that account for or contribute to disease.

Less expected have been variations in the copy number of sequence elements — that is, variation in the number of deleted or duplicated versions of segments of the genome that result in a range of the number of copies (instead of the usual two) among apparently 'normal' members of the population2. Several studies have described the prevalence of common deletion polymorphisms in the human genome3,4. On page 444 of this issue, Redon et al.5 now present results of a global genome-wide screen looking for all types of copy-number variants (CNVs) using several hundred reference samples from four human populations. They document nearly 1,500 variable regions, covering a remarkable 12% of the human genome and including hundreds of genes and other functional elements whose copy number differs, sometimes dramatically, among us. The data suggest that the greatest source of genetic diversity in our species lies not in millions of SNPs, but rather in larger segments of the genome whose presence or absence calls into question what exactly is a 'normal' human genome.

To detect CNVs, Redon et al. used two complementary genome-wide technologies. The first was a genotyping approach in which some 500,000 SNPs were assayed, looking for stretches of adjacent SNPs that displayed atypical ratios of the expected two versions (called alleles) of a given SNP. The second involved comparing each sample with a reference standard, and looking for systematic differences in intensity among a set of more than 26,000 large-insert cloned segments that span nearly all of the currently sequenced portion of the genome.

Combining these approaches provided coverage adequate to detect most forms of CNVs. In total, 1,447 CNVs were identified across the 270 HapMap samples. The estimated average length of CNV regions per genome analysed was more than 20 million base pairs, representing some 5- to 10-fold more variation between any two randomly chosen genomes than suggested previously by studying SNPs alone. More than half of the CNVs that were identified overlap known annotated genes in the genome. So it is likely that CNVs play a role in so-called complex diseases, in which multiple genes and/or gene–environment interactions are involved.

Mechanistically, how might copy-number variation be involved with complex disease? When deletions or duplications are present within a gene or its regulatory region, there is a reasonable chance that there will be an imbalance in the appropriate level of RNA and thus protein production from that gene. For genes and pathways in which the amount of a functional product produced is critical, it seems likely that CNVs could underscore variation in susceptibility to disease. Classically, variation in the copy number of the globin genes was shown to be responsible for various disorders of haemoglobin, such as the α-thalassaemias6. More recently, variable copy number of the CCL3L1 gene was reported to be associated with increased resistance to infection by HIV7.

Many genome-wide studies are currently under way that aim to find SNPs associated with complex disease. These studies in effect look for disease- and population-specific changes in the frequencies of SNP alleles, using arrays containing 'tagging SNPs' that act as proxies for other closely associated SNPs that are inherited together as a block. The likely involvement of CNVs in complex disease, however, raises the question of whether the many CNVs reported by Redon et al.5 can also be detected by association with one of these tagging SNPs. The answer seems to be both yes and no. Some CNVs may be associated with their neighbouring SNPs over time, but others may be of newer origin and their presence or absence may not be accurately tagged. Thus, densely spaced SNPs will probably be a prerequisite for the most efficient use of CNVs in genome-wide SNP-based association studies.

Given the limited set of reference samples assayed, the 1,500 CNVs reported by Redon et al. are probably the tip of the iceberg. As the results and the raw data from the first wave of genome-wide association studies become available, it will be essential to catalogue the full range of human CNVs. A complete map of CNVs in global populations will be necessary before we can fully understand which of the variants have clinical or other consequences, and which are, in fact, within the extremes of what we consider 'normal'.

More than a hundred years ago — even before the rediscovery of Mendel's laws of inheritance, and well before an awareness of DNA and genomes — the physician Sir Archibald Garrod first shed light on what he termed “chemical individuality” to refer to biochemical variants that shape the intricacies of metabolism in different individuals8. As he observed9 so presciently, “the existence of chemical individuality follows of necessity from that of chemical specificity, but we should expect the differences between individuals to be still more subtle and difficult of detection.” Our current view of “genomic individuality” at the level of SNPs, CNVs and chromosomal variants indeed extends his view in ways “more subtle and difficult of detection”. The stage is set for global studies to explore anew, as Garrod once did, the clinical significance of human variation.

References

  1. 1

    International HapMap Consortium Nature 437, 1299–1320 (2005).

  2. 2

    Feuk, L. et al. Nature Rev. Genet. 7, 85–97 (2006).

  3. 3

    Hinds, D. A. et al. Nature Genet. 38, 82–85 (2005).

  4. 4

    McCarroll, S. A. et al. Nature Genet. 38, 86–92 (2005).

  5. 5

    Redon, R. et al. Nature 444, 444–454 (2006).

  6. 6

    Weatherall, D. J. Am. J. Hum. Genet. 74, 385–392 (2004).

  7. 7

    Gonzalez, E. et al. Science 307, 1434–1440 (2005).

  8. 8

    Garrod, A. E. Mol. Med. 2, 274–282 (1996; reprint of original 1902 paper).

  9. 9

    Garrod, A. Inborn Errors of Metabolism 2nd edn (Oxford Univ. Press, 1923).

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