20181016 grc presentation-pa
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Long read structural variation analysis presentation by Peter Audano at GRC/GIAB workshop at ASHG 2018 meeting
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20181016 grc presentation-pa
- 1. Using long-read data to reveal variation and advance the human reference genome Peter Audano
- 2. Motivation • GRCh38 – 3.10 Gbp • 3.26 Gbp with patches/ALTs • Needs diversity: 70% RP11 • Structural variants (SVs) affect many bases • Indels ≥ 50 bp and inversions • 11 Mbp / genome (7x more than SNPs/indel) • More likely to be an eQTL • Illumina cannot capture all SVs • 53% DEL, 22% INS (Chaisson 2018) Alkan (2011)
- 3. Project goals 1. Sequence-resolve common structural variation 2. Correct errors and minor alleles in the reference 3. Build an alternate reference to support SV analysis with Illumina data
- 4. Constructing a diversity panel GRC Sequenced • CHM1 (Mole) • CHM13 (Mole) • HG00514 (CHB) • HG00733 (PUR) • NA19240 (YRI) • HG02818 (GWD) • NA19434 (LWK) • HG01352 (CLM) • HG02059 (KHV) • NA12878 (CEU) • HG04217 (ITU) • HG02106 (PEL) • HG00268 (FIN) Public • AK1 (Korean) • Seo, 2016 • HX1 (Chinese) • Shi 2016 • New PacBio data on 11 genomes. • 7 are new long-read biological samples. • Selected females to balance X
- 5. Building a non-redundant discovery set • 99,604 SVs • 21.3 Mbp INS • 18.5 Mbp DEL • 2,238 shared • 1.2 Mbp INS • 0.1 Mbp DEL • 5 coding • 160 regulatory
- 6. Discovery set growth slows
- 7. Merged set variant length distribution • 223 full-length L1 elements• 3,383 full-length AluY elements
- 8. Half the call set is novel, most is sequence- resolved for the first time
- 9. 90% of the genome is resolved • CEN / Peri-CEN • 254.5 Mbp • Low depth • 0.4 Mbp • Unresolved DUP • 19.9 Mbp • High-identity segmental duplications
- 10. Recovered 200 missing bases in FOXO6 and corrected its reading frame Credit: Max Dougherty
- 11. VNTRs distribution is non-random • VNTR enrichment in subtelomeres • 4.8-fold enrichment (Wilcoxon p = 2.9 × 10-9) • Correlates with male meiotic recombination and double-strand breaks Credit: Arvis Sulovari
- 12. Patching GRCh38 • Add SVs to reference on alternate contigs • Map reads with an ALT-aware aligner • Recovers 2.62% unmapped reads • Improves mapping quality for 25.68% of SV-insertion mapped reads • 2,228 SNPs and indels per sample within SV insertions (GQ 20+)
- 13. Genotyping SVs in Illumina samples GRCh38 primary contig SV contig • Extract features around SVs • Train a machine learning model to predict genotypes • 91-95% accuracy • 15% no-call
- 14. Genotyper is accurate over SV types and coverage
- 15. Genotyping enables eQTL and sQTL analysis • 376 samples (avg. 6-fold) • 379 SV eQTLs (411 genes) • 34 significant after accounting for SNP eQTLs • 244 SV sQTLs (197 genes) Credit: Yang Li and Ankeeta Shah
- 16. Resources available soon • Variant calls • VCF of SVs linked to contig breakpoints • BAM of contigs • SMRT-SV v2 genotyper • Contigs (PRJN481779) • Variants in dbVar (ntsd163) • Patched reference • ALTs for BWA-MEM • Graph for vg (Garrison 2018)
- 17. Future work • Sequence 50 additional genomes • Phase genomes • 10X and Strand-Seq • Phased-SV (Chaisson 2017, bioRxiv) • Genotype additional genomes • 2,500 high-coverage 1000 Genomes samples • 10,000 autism genomes • Improve the human reference • Patch GRCh38 • Build a human pan genome reference
- 18. Acknowledgments • Evan Eichler • Tonia Brown • Arvis Sulovari • David Gordon • Benson Hsieh • Zev Kronenberg • Tina Graves-Lindsay • Susan Dutcher • Wesley Warren • Vince Magrini • Sean McGrath • Richard Wilson • Yang Li • Ankeeta Shah
- 20. 15 long-read samples Sample Population Super- population Source New Data Accession Platform Mean Depth Longest Coverage Subread Coverage Longest N50 Subread N50 CHM1 Mole NA Reference No PRJNA246220 RS II 65x 63x 66x 19,728 19,226 CHM13 Mole NA Reference No PRJNA269593 RS II 67x 63x 72x 11,954 11,320 HG00514 CHB EA Reference Yes* PRJNA300843 RS II 76x 93x 104x 17,472 16,653 HG00733 PUR AMR Reference Yes* PRJNA300840 RS II 55x 63x 69x 16,195 15,461 NA19240 YRI AFR Reference Yes* PRJNA288807 RS II 59x 65x 71x 17,343 16,584 HG02818 GWD AFR Reference Yes PRJNA339722 RS II 79x 90x 98x 16,807 16,221 NA19434 LWK AFR Reference Yes PRJNA385272 RS II 59x 62x 71x 17,635 16,853 HG01352 CLM AMR Reference Yes PRJNA339719 RS II 56x 69x 75x 20,738 20,049 HG02059 KHV SA Reference Yes PRJNA339726 RS II 64x 71x 77x 18,533 17,890 NA12878 CEU EUR Reference Yes* PRJNA323611 RS II 50x 66x 75x 17,121 16,376 HG04217 ITU SA Reference Yes PRJNA481794 RS II 40x 46x 51x 18,149 16,871 HG02106 PEL AMR Reference Yes PRJNA480858 Sequel 73x 66x 69x 21,540 20,646 HG00268 FIN EUR Reference Yes PRJNA480712 Sequel 85x 76x 79x 25,245 24,487 AK1 Korean EA Public No PRJNA298944 RS II 77x 89x 102x 15,609 14,721 HX1 Chinese EA Public No PRJNA301527 RS II 98x 79x 103x 13,412 12,002
- 21. Methods •SMRT-SV •Align reads to GRCh38 •Assemble in windows (40 - 60 kbp) • Polish assemblies (quiver/arrow) •Align assemblies to GRCh38 •Call SVs • SV calls (VCF) with contig breakpoints • Contig BAM
- 22. SVs are resolved in 90% of the genome
- 24. Sensitivity increases over Illumina Published: • Illumina • 1000 Genomes 1 & 3 • Mills 2011 • Sudmant 2015 • GoNL
- 25. An augmented reference reveals hidden variation Type Count AC SVs DEL 3,582 8,835 206 INS 2,407 11,008 35 SNV 15,980 48,813 0 All 21,969 68,656 241
Notas do Editor
- 341,331 calls Mean 11,043,749 / sample 13,480 INS, 9,212 DEL, 64 INS Shared: 1.19 Mbp INS (n = 1,670) 0.33 Mbp DEL (n = 557)
- Add 1: Grow 2.1% Add 35 (50 total): Grow 39% Double: 327 total samples
- Add funding
- Chr15 chr15-34346634-INS-2159 2.1 kbp shared INS
- In 15 sample, we discovered 22% of the SVs in more than 3,000 samples.