New Human Genome Map Shows Extensive Copy Number Variation

When it comes to pathological variations in the human genome, single nucleotide polymorphisms have taken their fair share of the heat. After all, simple point mutations are responsible for a plethora of disorders, including Alzheimer disease—think amyloid precursor protein (APP) and presenilin (PS) mutations—and Parkinson disease (PD)—consider mutations in LRRK2 and α-synuclein, to name just two. But what about more profound changes or rearrangements of the human genome? If an extra copy of the APP gene can cause AD (see ARF related news story) or α-synuclein, PD (see ARF related news story), could copy number variation have as much, or even greater, impact on human health as SNPs?

Yes, suggests Matthew Hurles and colleagues in today’s Nature. Hurles, from the Wellcome Trust Sanger Institute in Cambridge, England, and an international collaborative of academic and industry researchers have compiled the first copy number variation (CNV) map of the human genome. They found a total of 1,447 copy number variable regions (CNVRs) covering 360 megabases of DNA (12 percent of the total genome), which means that CNVRs cover more nucleotide content per genome than SNPs. “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,” write Kevin Shianna and Huntington Willard, Duke University, Durham, North Carolina, in an accompanying Nature News & Views.

 

image

CNV Abundance
This color representation of CNVs in the International HapMap Project samples shows segments of DNA that are overrepresented (green) or underrepresented (red) in many individuals. Image credit: Matthew Hurles

First author Richard Redon and colleagues applied high-throughput detection and high-density DNA oligonucleotide arrays (described in two separate papers in today’s Genome Research—Komura et al., 2006, and Fiegler et al., 2006) to generate the CNVR map using the same DNA samples and cell lines used by the International HapMap Project. These samples cover four different ethnic populations: Nigerians, Europeans, Japanese, and Han Chinese (see ARF related news story). The researchers defined CNVs as segments of DNA 1 kb or larger in size that are present in variable copy number in comparison to a reference genome. Almost one-quarter of all CNVs were associated with segmental duplications, which is perhaps not surprising, given that natural selection tends to weed out deletions.

Though the vast majority of CNVs were found outside of coding sequences, thousands of putative functional segments of DNA fall within CNVs and 99 percent of them overlap with conserved non-coding sequences. The researchers also determined that at least 10 percent of disease-related genes in the OMIM database are associated with CNVs. Genes include CCL3L1, which has been linked to increased resistance to HIV-1, and DISC1, which undergoes a chromosomal translocation that might be causative for schizophrenia (see Schizophrenia Research Forum related news story).

“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,” write Shianna and Willard. To that end, the Wellcome Trust Sanger Institute has developed a CNV database called DECIPHER to share information on CNVs and rare, severe phenotypes.

In a related paper coauthored by many of the same researchers, Lars Feuk, University of Toronto, Canada, and colleagues describe a comparison of the two human genome assemblies: those produced by Celera Genomics and the Human Genome Sequencing Consortium. First author Razi Khaja and colleagues use the data to demonstrate that there are megabases of sequence information, specifically over 13,500 non-SNP events, that are absent, inverted, or polymorphic in one assembly compared to the other. The data indicate that there is substantial undescribed variation within the human genome and suggest that more comprehensive annotation will be needed as we enter the era of personalized, genomic-based medicine.—Tom Fagan

Comments

  1. This study is the first to systematically map large-scale copy number variation (CNV) across a large sample representing different populations. The investigators have significantly enhanced our knowledge of genomic diversity by identifying approximately 1,000 CNVs that had not been previously reported in the literature, thereby almost doubling the catalogue of published structural variants in healthy individuals. This data set will serve as the framework for a genomic resource on structural variation. It will continue to be refined through continued efforts of many groups and may soon be a very comprehensive map. It is currently just the tip of the iceberg.

    View all comments by Jonathan Sebat

Make a Comment

To make a comment you must login or register.

References

News Citations

  1. APP Double Dose Causes Early Onset AD
  2. Synuclein and Parkinson's—It's All in the Dose
  3. Charting Genetic Diversity—First Haplotype Map Appears

External Citations

  1. Schizophrenia Research Forum related news story
  2. DECIPHER

Further Reading

No Available Further Reading

Primary Papers

  1. Redon R, Ishikawa S, Fitch KR, Feuk L, Perry GH, Andrews TD, Fiegler H, Shapero MH, Carson AR, Chen W, Cho EK, Dallaire S, Freeman JL, González JR, Gratacòs M, Huang J, Kalaitzopoulos D, Komura D, MacDonald JR, Marshall CR, Mei R, Montgomery L, Nishimura K, Okamura K, Shen F, Somerville MJ, Tchinda J, Valsesia A, Woodwark C, Yang F, Zhang J, Zerjal T, Armengol L, Conrad DF, Estivill X, Tyler-Smith C, Carter NP, Aburatani H, Lee C, Jones KW, Scherer SW, Hurles ME. Global variation in copy number in the human genome. Nature. 2006 Nov 23;444(7118):444-54. PubMed.
  2. Komura D, Shen F, Ishikawa S, Fitch KR, Chen W, Zhang J, Liu G, Ihara S, Nakamura H, Hurles ME, Lee C, Scherer SW, Jones KW, Shapero MH, Huang J, Aburatani H. Genome-wide detection of human copy number variations using high-density DNA oligonucleotide arrays. Genome Res. 2006 Dec;16(12):1575-84. PubMed.
  3. Fiegler H, Redon R, Andrews D, Scott C, Andrews R, Carder C, Clark R, Dovey O, Ellis P, Feuk L, French L, Hunt P, Kalaitzopoulos D, Larkin J, Montgomery L, Perry GH, Plumb BW, Porter K, Rigby RE, Rigler D, Valsesia A, Langford C, Humphray SJ, Scherer SW, Lee C, Hurles ME, Carter NP. Accurate and reliable high-throughput detection of copy number variation in the human genome. Genome Res. 2006 Dec;16(12):1566-74. PubMed.
  4. Shianna KV, Willard HF. Human genomics: in search of normality. Nature. 2006 Nov 23;444(7118):428-9. PubMed.
  5. Khaja R, Zhang J, MacDonald JR, He Y, Joseph-George AM, Wei J, Rafiq MA, Qian C, Shago M, Pantano L, Aburatani H, Jones K, Redon R, Hurles M, Armengol L, Estivill X, Mural RJ, Lee C, Scherer SW, Feuk L. Genome assembly comparison identifies structural variants in the human genome. Nat Genet. 2006 Dec;38(12):1413-8. PubMed.

Annotate

To make an annotation you must Login or Register.