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Cited by 916Genomic variations and chromosomal abnormalitiesGenomics and Phylogenetic StudiesGenome Rearrangement Algorithms

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Multi-platform discovery of haplotype-resolved structural variation in human genomes

Open access
Chaisson, Mark J. P., Sanders, Ashley D., Zhao, Xuefang, Malhotra, Ankit, Porubsky, David, Rausch, Tobias, Gardner, Eugene J., Rodriguez, Oscar L., Guo, Li, Collins, Ryan L., Fan, Xian, Wen, Jia, Handsaker, Robert E., Fairley, Susan, Kronenberg, Zev N., Kong, Xiangmeng, Hormozdiari, Fereydoun, Lee, Dillon, Wenger, Aaron M., Hastie, Alex R., Antaki, Danny, Anantharaman, Thomas, Audano, Peter A., Brand, Harrison, Cantsilieris, Stuart, Cao, Han, Cerveira, Eliza, Chen, Chong, Chen, Xintong, Chin, Chen-Shan, Chong, Zechen, Chuang, Nelson T., Lambert, Christine C., Church, Deanna M., Clarke, Laura, Farrell, Andrew, Flores, Joey, Galeev, Timur, Gorkin, David U., Gujral, Madhusudan, Guryev, Victor, Heaton, William Haynes, Korlach, Jonas, Kumar, Sushant, Kwon, Jee Young, Lam, Ernest T., Lee, Jong Eun, Lee, Joyce, Lee, Wan-Ping, Lee, Sau Peng, Li, Shantao, Marks, Patrick, Viaud-Martinez, Karine, Meiers, Sascha, Munson, Katherine M., Navarro, Fabio C. P., Nelson, Bradley J., Nodzak, Conor, Noor, Amina, Kyriazopoulou-Panagiotopoulou, Sofia, Pang, Andy W. C., Qiu, Yunjiang, Rosanio, Gabriel, Ryan, Mallory, Stütz, Adrian, Spierings, Diana C. J., Ward, Alistair, Welch, AnneMarie E., Xiao, Ming, Xu, Wei, Zhang, Chengsheng, Zhu, Qihui, Zheng-Bradley, Xiangqun, Lowy, Ernesto, Yakneen, Sergei, McCarroll, Steven, Jun, Goo, Ding, Li, Koh, Chong Lek, Ren, Bing, Flicek, Paul, Chen, Ken, Gerstein, Mark B., Kwok, Pui-Yan, Lansdorp, Peter M., Marth, Gabor T., Sebat, Jonathan, Shi, Xinghua, Bashir, Ali, Ye, Kai, Devine, Scott E., Talkowski, Michael E., Mills, Ryan E., Marschall, Tobias, Korbel, Jan O., Eichler, Evan E., Lee, Charles·2019·Nature Communications
DOI 10.1038/s41467-018-08148-zPMC PMC6467913

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Abstract

The incomplete identification of structural variants (SVs) from whole-genome sequencing data limits studies of human genetic diversity and disease association. Here, we apply a suite of long-read, short-read, strand-specific sequencing technologies, optical mapping, and variant discovery algorithms to comprehensively analyze three trios to define the full spectrum of human genetic variation in a haplotype-resolved manner. We identify 818,054 indel variants (<50 bp) and 27,622 SVs (≥50 bp) per genome. We also discover 156 inversions per genome and 58 of the inversions intersect with the critical regions of recurrent microdeletion and microduplication syndromes. Taken together, our SV callsets represent a three to sevenfold increase in SV detection compared to most standard high-throughput sequencing studies, including those from the 1000 Genomes Project. The methods and the dataset presented serve as a gold standard for the scientific community allowing us to make recommendations for maximizing structural variation sensitivity for future genome sequencing studies.

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Fig. 1 Characteristics of SNV-based haplotypes obtained from different data sources. a Distribution of phased block lengths for the YRI child NA19240. Note that Strand-seq haplotypes span whole chromosomes and therefore one block per chromosome is shown. Vertical bars highlight N50 haplotype length: the minimum length haplotype block at which at least half of the phased bases are contained. For Illumina (IL) paired-end data, phased blocks cover <50% of the genome and hence the N50 cannot be computed. b Fraction of phase connection, i.e., pairs of consecutive heterozygous variants provided by each technology (averaged over all proband samples). c Pairwise comparisons of different phasings; colors encode switch error rates (averaged over all proband samples). For each row, a green box indicates the phasing of an independent technology with best agreement, with corresponding switch error rates given in green. d Each phased block is shown in a different color. The largest block is shown in cyan, i.e., all cyan regions belong to one block, even though interspaced by white areas (genomic regions where no variants are phased) or disconnected small blocks (different colors). e Fraction of heterozygous SNVs in the largest block shown in d. f Mismatch error rate of largest block compared to trio-based phasing, averaged over all chromosomes of all proband genomes (i.e., the empirical probability that any two heterozygous variants on a chromosome are phased correctly with respect to each other, in contrast to the switch error rate, which relays the probability that any two adjacent heterozygous variants are phased correctly). (*) Not available because trio phasing is used as reference for comparisons. (**) Not shown as population-based phasing does not output block boundaries; refer to Supplementary Material for an illustration of errors in population-based phasing
Fig. 1 Characteristics of SNV-based haplotypes obtained from different data sources. a Distribution of phased block lengths for the YRI child NA19240. Note that Strand-seq haplotypes span whole chromosomes and therefore one block per chromosome is shown. Vertical bars highlight N50 haplotype length: the minimum length haplotype block at which at least half of the phased bases are contained. For Illumina (IL) paired-end data, phased blocks cover <50% of the genome and hence the N50 cannot be computed. b Fraction of phase connection, i.e., pairs of consecutive heterozygous variants provided by each technology (averaged over all proband samples). c Pairwise comparisons of different phasings; colors encode switch error rates (averaged over all proband samples). For each row, a green box indicates the phasing of an independent technology with best agreement, with corresponding switch error rates given in green. d Each phased block is shown in a different color. The largest block is shown in cyan, i.e., all cyan regions belong to one block, even though interspaced by white areas (genomic regions where no variants are phased) or disconnected small blocks (different colors). e Fraction of heterozygous SNVs in the largest block shown in d. f Mismatch error rate of largest block compared to trio-based phasing, averaged over all chromosomes of all proband genomes (i.e., the empirical probability that any two heterozygous variants on a chromosome are phased correctly with respect to each other, in contrast to the switch error rate, which relays the probability that any two adjacent heterozygous variants are phased correctly). (*) Not available because trio phasing is used as reference for comparisons. (**) Not shown as population-based phasing does not output block boundaries; refer to Supplementary Material for an illustration of errors in population-based phasingCC BY · PubMed Central
Fig. 2 Comparison and integration of indel and SV callsets on HG00733, HG00514, and NA12940. a Length distribution of deletions and insertions identified by PB (blue), IL (red) and BNG (brown), respectively, together with averaged length distribution of SVs discovered in the maternal genomes by the 1KG-P3 report (silver). b Number of SVs discovered by one or multiple genome platforms in the YRI child NA19240. c Overlap of IL indel discovery algorithms, with total number of indels found by each combination of IL algorithms (gray) and those that overlapped with a PB indel (blue) in the CHS child HG00514
Fig. 2 Comparison and integration of indel and SV callsets on HG00733, HG00514, and NA12940. a Length distribution of deletions and insertions identified by PB (blue), IL (red) and BNG (brown), respectively, together with averaged length distribution of SVs discovered in the maternal genomes by the 1KG-P3 report (silver). b Number of SVs discovered by one or multiple genome platforms in the YRI child NA19240. c Overlap of IL indel discovery algorithms, with total number of indels found by each combination of IL algorithms (gray) and those that overlapped with a PB indel (blue) in the CHS child HG00514CC BY · PubMed Central
Fig. 3 Characterization of simple and complex inversions. a Integration of inversions across platforms based on reciprocal overlap. Shown is an example of five orthogonal platforms intersecting at a homozygous inversion, with breakpoint ranges and supporting Strand-seq signature illustrated in bottom panels. b Size distribution of inversions included in the unified inversion list, subdivided by technology, with the total inversions (N) contributed by each listed. c Classification of Strand-seq inversions based on orthogonal phase support. Illustrative examples of simple (homozygous and heterozygous) and complex (inverted duplication) events are shown. Strand-seq inversions were identified based on read directionality (read count; reference reads in gray, inverted reads in purple), the relative ratio of reference to inverted reads within the locus (read ratio), and the haplotype structure of the inversion, with phased read data considered in terms of directionality (Ph; H1 alleles in red, H2 alleles in blue; alleles from reference reads are displayed above the ideogram and alleles from inverted reads are displayed below). ILL Illumina. liWGS long-insert whole-genome sequencing libraries. PB Pacific Biosciences. StS Strand-seq. BNG Bionano Genomics. SD segmental duplication. Ph phase data
Fig. 3 Characterization of simple and complex inversions. a Integration of inversions across platforms based on reciprocal overlap. Shown is an example of five orthogonal platforms intersecting at a homozygous inversion, with breakpoint ranges and supporting Strand-seq signature illustrated in bottom panels. b Size distribution of inversions included in the unified inversion list, subdivided by technology, with the total inversions (N) contributed by each listed. c Classification of Strand-seq inversions based on orthogonal phase support. Illustrative examples of simple (homozygous and heterozygous) and complex (inverted duplication) events are shown. Strand-seq inversions were identified based on read directionality (read count; reference reads in gray, inverted reads in purple), the relative ratio of reference to inverted reads within the locus (read ratio), and the haplotype structure of the inversion, with phased read data considered in terms of directionality (Ph; H1 alleles in red, H2 alleles in blue; alleles from reference reads are displayed above the ideogram and alleles from inverted reads are displayed below). ILL Illumina. liWGS long-insert whole-genome sequencing libraries. PB Pacific Biosciences. StS Strand-seq. BNG Bionano Genomics. SD segmental duplication. Ph phase dataCC BY · PubMed Central
Fig. 4 Concordance of IL methods compared against total IL callset and PB callset using orthogonal technologies. Results by algorithm shown for a the deletion concordance for individual methods, b the union of all pairs of methods, and c the requirement that more than one caller agree on any call. Individual callers are shown as red points for comparison. Pairs and triples of combinations are in black points. The solid and dashed lines represent the 5% and 10% non-concordance rates (NCR), respectively. The top five combinations of methods in each plot below the 10% NCR, along with the individual plots, are labeled. d Overlap of IL-SV discovery algorithms, with total number of SVs found by each combination of IL algorithms (gray) and those that overlapped with the PB-SV calls (blue) in the YRI child NA19240. e PCA of the genotypes of concordant calls of each method: PC 1 versus 2 (left), PC 2 versus 3 (right). VH VariationHunter
Fig. 4 Concordance of IL methods compared against total IL callset and PB callset using orthogonal technologies. Results by algorithm shown for a the deletion concordance for individual methods, b the union of all pairs of methods, and c the requirement that more than one caller agree on any call. Individual callers are shown as red points for comparison. Pairs and triples of combinations are in black points. The solid and dashed lines represent the 5% and 10% non-concordance rates (NCR), respectively. The top five combinations of methods in each plot below the 10% NCR, along with the individual plots, are labeled. d Overlap of IL-SV discovery algorithms, with total number of SVs found by each combination of IL algorithms (gray) and those that overlapped with the PB-SV calls (blue) in the YRI child NA19240. e PCA of the genotypes of concordant calls of each method: PC 1 versus 2 (left), PC 2 versus 3 (right). VH VariationHunterCC BY · PubMed Central

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Authors
Chaisson, M. J. P., Sanders, A. D., Zhao, X., Malhotra, A., Porubsky, D., Rausch, T., Gardner, E. J., Rodriguez, O. L., Guo, L., Collins, R. L., Fan, X., Wen, J., Handsaker, R. E., Fairley, S., Kronenberg, Z. N., Kong, X., Hormozdiari, F., Lee, D., Wenger, A. M., Hastie, A. R., Antaki, D., Anantharaman, T., Audano, P. A., Brand, H., Cantsilieris, S., Cao, H., Cerveira, E., Chen, C., Chen, X., Chin, C.-S., Chong, Z., Chuang, N. T., Lambert, C. C., Church, D. M., Clarke, L., Farrell, A., Flores, J., Galeev, T., Gorkin, D. U., Gujral, M., Guryev, V., Heaton, W. H., Korlach, J., Kumar, S., Kwon, J. Y., Lam, E. T., Lee, J. E., Lee, J., Lee, W.-P., Lee, S. P., Li, S., Marks, P., Viaud-Martinez, K., Meiers, S., Munson, K. M., Navarro, F. C. P., Nelson, B. J., Nodzak, C., Noor, A., Kyriazopoulou-Panagiotopoulou, S., Pang, A. W. C., Qiu, Y., Rosanio, G., Ryan, M., Stütz, A., Spierings, D. C. J., Ward, A., Welch, A. E., Xiao, M., Xu, W., Zhang, C., Zhu, Q., Zheng-Bradley, X., Lowy, E., Yakneen, S., McCarroll, S., Jun, G., Ding, L., Koh, C. L., Ren, B., Flicek, P., Chen, K., Gerstein, M. B., Kwok, P.-Y., Lansdorp, P. M., Marth, G. T., Sebat, J., Shi, X., Bashir, A., Ye, K., Devine, S. E., Talkowski, M. E., Mills, R. E., Marschall, T., Korbel, J. O., Eichler, E. E., & Lee, C.
Affiliations
  • University of Southern California (US)
  • European Molecular Biology Laboratory (DE)
  • Harvard University (US)
  • The Jackson Laboratory for Genomic Medicine (US)
  • University of Maryland, Baltimore (US)
  • Icahn School of Medicine at Mount Sinai (US)
  • Xi'an Jiaotong University (CN)
  • The University of Texas MD Anderson Cancer Center (US)
  • University of North Carolina at Charlotte (US)
  • Broad Institute (US)
  • European Bioinformatics Institute (GB)
  • University of Washington (US)
  • Yale University (US)
  • University of California, Davis (US)
  • University of Utah (US)
  • Pacific Biosciences (United States) (US)
  • BioNano Genomics (United States) (US)
  • University of California San Diego (US)
  • 10X Genomics (United States) (US)
  • Illumina (United States) (US)
  • University Medical Center Groningen (NL)
  • Ewha Womans University (KR)
  • Drexel University (US)
  • The University of Texas Health Science Center at Houston (US)
  • Washington University in St. Louis (US)
  • University of Malaya (MY)
  • University of California, San Francisco (US)
  • BC Cancer Agency (CA)
  • First Affiliated Hospital of Xi'an Jiaotong University (CN)
  • University of Michigan (US)
  • Max Planck Institute for Informatics (DE)
  • Howard Hughes Medical Institute (US)
Corresponding author
  • Korbel, Jan O.
  • Eichler, Evan E.
  • Lee, Charles
ORCID
Venue
Nature Communications
Publisher
Springer Science and Business Media LLC
Published
2019-04-16
Volume
10
Issue
1
Pages
1784-1784
ISSN
2041-1723 (ISSN-L)
DOI
10.1038/s41467-018-08148-z
PMC
PMC6467913
OpenAlex
W2949062400
Cited by
891
References
68
Citations by year
2026: 48 · 2025: 80 · 2024: 103 · 2023: 119 · 2022: 133 · 2021: 184 · 2020: 126 · 2019: 76
FWCI
80.48
Type
journal article
Language
en
Open access
Licence
Locations
  • Nature Communications (publishedVersion, cc-by)
  • Europe PMC (PubMed Central) (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • eScholarship (California Digital Library) (submittedVersion, cc-by)
  • Digital Commons@Becker (Washington University School of Medicine) (submittedVersion, cc-by)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion)
  • University of Groningen research database (University of Groningen / Centre for Information Technology) (submittedVersion, cc-by)
Funders
  • Wellcome Trust (WT104947, WT104947/Z/14/Z, WT085532)
  • European Molecular Biology Laboratory
  • National Natural Science Foundation of China (2018YFC0910400, 31701739, 2017YFC0907500, 31671372)
  • Ewha Womans University
  • Universiti Malaya
  • National Institutes of Health (1r15hg009565-01, HG005946, MH115957)
  • Medical Research Council
  • National Health and Medical Research Council (1073726)
  • National Institute of Mental Health (R56MH115957, R01MH115957)
  • National Human Genome Research Institute (R15 HG009565, U41HG007497, R01HG002898, U01HG006513, R01HG007068, F31HG009223, R01HG005946, R01HG008628, R01HG002385)
  • National Cancer Institute (R01CA166661)
  • National Institute of Allergy and Infectious Diseases (R21AI117407)
  • Eunice Kennedy Shriver National Institute of Child Health and Human Development (R01HD081256)
Topics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genomic variations and chromosomal abnormalities
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Genomics and Phylogenetic Studies
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genome Rearrangement Algorithms
Keywords
structural variants, indels, chromosomal inversions, microdeletion syndromes, microduplication syndromes, long-read sequencing, optical mapping, trios, human genetic variation
MeSH terms
Whole Genome Sequencing, Algorithms, Chromosome Mapping, Haplotypes, Humans, Genome, Human, Genomics, Databases, Genetic, INDEL Mutation, Genomic Structural Variation, High-Throughput Nucleotide Sequencing

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