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Genome assembly comparison identifies structural variants in the human genome

Nature Genetics volume 38, pages 1413–1418 (2006)Cite this article

Abstract

Numerous types of DNA variation exist, ranging from SNPs to larger structural alterations such as copy number variants (CNVs) and inversions. Alignment of DNA sequence from different sources has been used to identify SNPs1,2 and intermediate-sized variants (ISVs)3. However, only a small proportion of total heterogeneity is characterized, and little is known of the characteristics of most smaller-sized (<50 kb) variants. Here we show that genome assembly comparison is a robust approach for identification of all classes of genetic variation. Through comparison of two human assemblies (Celera's R27c compilation and the Build 35 reference sequence), we identified megabases of sequence (in the form of 13,534 putative non-SNP events) that were absent, inverted or polymorphic in one assembly. Database comparison and laboratory experimentation further demonstrated overlap or validation for 240 variable regions and confirmed >1.5 million SNPs. Some differences were simple insertions and deletions, but in regions containing CNVs, segmental duplication and repetitive DNA, they were more complex. Our results uncover substantial undescribed variation in humans, highlighting the need for comprehensive annotation strategies to fully interpret genome scanning and personalized sequencing projects.

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Figure 1: Overview of the different types of alignments and assembly differences extracted from the R27c and Build 35 genome assemblies.
Figure 2: Genome-wide overview of insertion points of unmatched and copy-unmatched sequences present in R27c with no corresponding match to Build 35.
Figure 3: Fosmid probes were used for FISH experiments to confirm the R27c mapping of unmatched sequences to Build 35 or to find a location for sequences with inconsistent or no mapping information.

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Acknowledgements

We thank T. Tang, L. Wong, J. Wittnam, C.-F. Chu and W. Hwang of The Centre for Applied Genomics for technical assistance. Computational analyses were supported by the Shared Hierarchical Academic Research Computing Network (SHARCNET) and the Centre for Computational Biology at the Hospital for Sick Children. The work was supported by Genome Canada/Ontario Genomics Institute, the Canadian Institutes of Health Research (CIHR), the Canada Foundation for Innovation and the McLaughlin Centre for Molecular Medicine (all to S.W.S). L.A. and X.E. are supported by Genoma España and Genome Canada joint R+D+I projects and by the Generalitat de Catalunya (Departament d'Universitats, 2005SGR00008, and Departament de Salut). L.F. is supported by CIHR. S.W.S. is an Investigator of CIHR and International Scholar of Howard Hughes Medical Institute.

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Authors and Affiliations

  1. The Hospital for Sick Children and Department of Molecular and Medical Genetics, Program in Genetics and Genomic Biology, University of Toronto and The Centre for Applied Genomics, MaRS Centre, Toronto, M5G 1L7, Ontario, Canada

    Razi Khaja, Junjun Zhang, Jeffrey R MacDonald, Yongshu He, Ann M Joseph-George, John Wei, Muhammad A Rafiq, Cheng Qian, Mary Shago, Stephen W Scherer & Lars Feuk

  2. Department of Biosciences, Commission on Science and Technology for Sustainable Development in the South Institute of Information Technology (CIIT), Islamabad, 44000, Pakistan

    Muhammad A Rafiq

  3. Genes and Disease Program, Center for Genomic Regulation, Charles Darwin s/n, Barcelona Biomedical Research Park, Barcelona, 08003, Catalonia, Spain

    Lorena Pantano, Lluis Armengol & Xavier Estivill

  4. Genome Science Laboratory, Research Center for Advanced Science and Technology, University of Tokyo, 4-6-1 Komaba, Meguro, 153-8904, Tokyo, Japan

    Hiroyuki Aburatani

  5. Affymetrix, Inc., Santa Clara, 95051, California, USA

    Keith Jones

  6. The Wellcome Trust Sanger Institute, The Wellcome Trust Genome Campus, Hinxton, CB10 1SA, Cambridge, UK

    Richard Redon & Matthew Hurles

  7. Pompeu Fabra University, Charles Darwin s/n, and National Genotyping Centre, Passeig Marítim 37-49, Barcelona Biomedical Research Park, Barcelona, Catalonia, Spain

    Xavier Estivill

  8. Windber Research Institute, 620 7th Street, Windber, 15963-1331, Pennsylvania, USA

    Richard J Mural

  9. Department of Pathology, Brigham and Women's Hospital and Harvard Medical School, 20 Shattuck St., Boston, 02115, Massachusetts, USA

    Charles Lee

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Contributions

The study was designed by R.K., S.W.S. and L.F. The GCA algorithm was created by R.K. Sequence alignment and computational analysis was performed by R.K., J.Z., J.R.M, J.W., C.Q., L.A. and R.J.M. FISH analysis was performed by Y.H., A.M.J.G., M.S. and C.L. PCR analysis was performed by M.A.R., L.P., L.A. and L.F. J.Z., J.R.M, J.W., C.Q., H.A., K.J., R.R., M.H., L.A., X.E., C.L., S.W.S. and L.F contributed to the analysis of overlap with genomic features, creation of data sets for such analysis and interpretation of the data. S.W.S. and L.F conceptualized, designed and coordinated the experiments. The paper was written by S.W.S and L.F.

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The authors declare no competing financial interests.

Supplementary information

Supplementary Table 1

Results for MegaBLAST and A2Amapper comparing R27c versus Build 35 and comparing Build 35 versus R27c. (PDF 18 kb)

Supplementary Table 2

List of copy-unmatched sequences identified by GCA; table also shows information on repeat content and re-BLAT versus Build 35, Build 36 and chimpanzee Build 1. (XLS 176 kb)

Supplementary Table 3

Intra- and interscaffold inversions identified by GCA between R27c and Build 35. (PDF 10 kb)

Supplementary Table 4

List of refined set of unmatched sequences used for analysis of overlap with genomic features; all entries in this list with an insertion point were used for genomic overlap analysis. (XLS 5127 kb)

Supplementary Table 5

Analysis of RefSeq genes and mRNAs. (XLS 377 kb)

Supplementary Table 6

Results and details for PCR-based assays. (XLS 34 kb)

Supplementary Table 7

Results and details for fluoresecence in situ hybridization experiments. (PDF 37 kb)

Supplementary Table 8

Results of comparisons of single-base mismatches detected by GCA with dbSNP_125 and with HapMap QC+/QC− SNPs. (PDF 59 kb)

Supplementary Table 9

Comparison between assembly differences and other genomic features. (XLS 82 kb)

Supplementary Methods (PDF 105 kb)

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Khaja, R., Zhang, J., MacDonald, J. et al. Genome assembly comparison identifies structural variants in the human genome. Nat Genet 38, 1413–1418 (2006). https://doi.org/10.1038/ng1921

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