Discovery and genotyping of genome structural polymorphism by sequencing on a population scale


Accurate and complete analysis of genome variation in large populations will be required to understand the role of genome variation in complex disease. We present an analytical framework for characterizing genome deletion polymorphism in populations using sequence data that are distributed across hundreds or thousands of genomes. Our approach uses population-level concepts to reinterpret the technical features of sequence data that often reflect structural variation. In the 1000 Genomes Project pilot, this approach identified deletion polymorphism across 168 genomes (sequenced at 4× average coverage) with sensitivity and specificity unmatched by other algorithms. We also describe a way to determine the allelic state or genotype of each deletion polymorphism in each genome; the 1000 Genomes Project used this approach to type 13,826 deletion polymorphisms (48–995,664 bp) at high accuracy in populations. These methods offer a way to relate genome structural polymorphism to complex disease in populations.

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Figure 1: A population-aware analytical framework for analyzing Genome STRucture in Populations (Genome STRiP).
Figure 2: Identifying coherent sets of aberrantly mapping reads from a population of genomes.
Figure 3: Evaluating the population-heterogeneity and allele-substitution properties of population-scale sequence data.
Figure 4: Deletion polymorphisms identified by Genome STRiP in low-coverage sequence data from 168 genomes.
Figure 5: Determining the allelic state (genotype) of 13,826 deletions in 156 genomes.


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The authors wish to thank the 1000 Genomes Structural Variation Analysis Group for helpful conversations throughout this work and for collaborative work to evaluate the sensitivity and specificity of structural variation discovery algorithms. We would particularly like to acknowledge K. Chen for creation of a high-quality breakpoint library for the 1000 Genomes Project, on which Genome STRiP's genotyping algorithm drew, and R. Mills for managing the 1000 Genomes Project deletion discovery sets and validation data. We also thank C. Stewart, K. Walter, M. Hurles and N. Patterson for helpful conversations during the course of this work; D. Altshuler, M. DePristo and M. Daly for helpful comments on the manuscript and figures; and the anonymous reviewers of this manuscript, whose feedback improved it. This work was supported by the National Human Genome Research Institute (U01HG005208-01S1) and by startup funds from the Department of Genetics at Harvard Medical School.

Author information




R.E.H., J.M.K., J.N. and S.A.M. conceived the analytical approaches. R.E.H. implemented the algorithms and performed the data analysis. R.E.H. and S.A.M. wrote the manuscript.

Corresponding author

Correspondence to Steven A McCarroll.

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The authors declare no competing financial interests.

Supplementary information

Supplementary Text and Figures

Supplementary Figures 1–6, Supplementary Table 1 and Supplementary Note. (PDF 806 kb)

Supplementary Table 2

Evaluation of genotype likelihood calibration (XLSX 53 kb)

Supplementary Table 3

tagSNPs identified by Genome STRiP for deletions from the 1000 Genomes Project (XLSX 3631 kb)

Supplementary Table 4

Phenotype associated SNPs in linkage disequilibrium with 1000 Genomes pilot deletions (XLSX 92 kb)

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Handsaker, R., Korn, J., Nemesh, J. et al. Discovery and genotyping of genome structural polymorphism by sequencing on a population scale. Nat Genet 43, 269–276 (2011).

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