Karen miga centromere sequence characterization and variant detection
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Centromeric regions contain significant human genetic variation that is not represented in current reference genomes. This document proposes a two-part approach to characterize sequence variation in centromeric regions: (1) construct chromosome-specific reference maps of centromeric DNA, and (2) expand the human variation reference map to include centromeric regions. Key aspects include using long reads to assemble higher-order repeats, short reads to estimate array sizes and variant frequencies, and graph representations to model structural variation while retaining haplotype information. This would provide new insights into centromeric biology and identify centromeric variants associated with disease.
Karen miga centromere sequence characterization and variant detection
- 1. Centromeric Regions: A source of new, unexplored human sequence variation Karen H. Miga University of California, Santa Cruz Jan 25, 2018 GIAB Workshop
- 2. Allele 1 Allele 2 LINE Mobile element insertion Allele 1 Allele 2 Copy Number Variation Inversion Polymorphism Allele 1 Allele 2 Single Nucleotide Polymorphisms Allele 1 Allele 2 …ATACGGATTTCATGACAGGTTA… …ATACGGATTTGATGACAGGTTA… CHR 9 Identifying Sequence Variants
- 3. ? Centromeres: Large Assembly Gaps p-arm q-arm Multi-Megabase Assembly Gaps ? CENTROMERIC REGIONS
- 4. ? Inability to track variation p-arm q-arm Multi-Megabase Assembly Gaps ?Mobile element insertion Copy Number Variation Inversion Polymorphism SNPs Unable to identify using standard genomic data: CENTROMERIC REGIONS
- 5. ? chr 9qh Allele2 Allele1 chr 9qh+ CHR 9 Cytogenetics: Identifying Sequence Variants CENTROMERIC REGIONS Mobile element insertion Copy Number Variation Inversion Polymorphism SNPs Unable to identify using standard genomic data: H. E. Wyandt, V. S. Tonk, Human Chromosome Variation: Heteromorphism and Polymorphism, 2011
- 6. ? chr 9qh Allele2 Allele1 chr 9qh+ CHR 9 Cytogenetics: Identifying Sequence Variants H. E. Wyandt, V. S. Tonk, Human Chromosome Variation: Heteromorphism and Polymorphism, 2011 Regulate Centromere Function Contribute to Chromosome Cohesion Centromeres Play a Role in Cell Division
- 7. ? chr 9qh Allele2 Allele1 chr 9qh+ CHR 9 Cytogenetics: Identifying Sequence Variants H. E. Wyandt, V. S. Tonk, Human Chromosome Variation: Heteromorphism and Polymorphism, 2011 • 9qh+ men had significantly increased frequencies of hyperdiploid cells. (Ford et al 1978) • 9qh+ women showed significant differences in rates of aneuploidy. (Ford et al 1978) • 9qh+ is associated with of an increased fraction of malformed spermatozoa (Eiben et al 1987) • Inversions spanning 9qh relate to recurrent miscarriages in Italian populations (Del Porto et al 1993)
- 8. Unchartered Functional Regions of the Human Genome Part I: Constructing a reference map of centromeric DNAs Part II: Expand the human “variation reference map” to include centromeric DNAs
- 9. p-arm q-arm ... ... multi-megabase array ALPHA SATELLITE ~171bp Tandem Repeat Wide Range of Percent ID: ~60-100% 1 2 3 4 Part I: Constructing a reference map of centromeric DNAs
- 10. Narrow Range of Percent ID: 94% - 100% “Higher Order Repeat” Multi-monomeric Repeat Unit Human Centromeric DNA: Higher Order Repeats p-arm q-arm ... ... 1 2 3 4 1 2 3 4 1 2 3 4 multi-megabase array
- 11. Human Centromeres: Chromosome-Specific Satellite Sequence Organization p-arm q-arm ... ... p-arm q-arm ... ... Array “A” Array “B” Array “C” chrX chr3
- 12. p-arm q-arm ... ... ... ...-A- -T- Human Centromeric DNA: Genome Model of Sequence Organization
- 13. INVERSION p-arm q-arm ... ... ... ...-A- -T- Human Centromeric DNA: Genome Model of Sequence Organization
- 14. INVERSION p-arm q-arm ... ... LINE SINE OTHER NON-ALPHA SATELLITE ... ...-A- -T- Human Centromeric DNA: Genome Model of Sequence Organization
- 15. INVERSION p-arm q-arm ... ... LINE SINE OTHER ... ...-A- -T- Non-satellite DNA GENES NON-ALPHA SATELLITE Human Centromeric DNA: Genome Model of Sequence Organization
- 16. INVERSION p-arm q-arm ... ... LINE SINE OTHER ... ...-A- -T- GENES NON-ALPHA SATELLITE Construct a new genomic reference for each centromeric region to broaden research in these areas Genome Informatics Non-satellite DNA
- 17. GM12878 B-lymphoblastoid (Female/CEPH) Datasets involved in Centromeric Reference Map
- 18. >200 ENCODE datasets A B C D E F Prediction of Higher Order Repeats PacBio ~10kb read
- 19. >200 ENCODE datasets α-Centauri (centromeric automated repeat identification) PacBio ~10kb read A B C D E F 5’… …3’ 10x 10 B C D EF A 10 10 10 10 10 5’ 3’ Prediction of Higher Order Repeats
- 21. Experimental Evidence: Chromosome-specific Satellite DNA tools to Screening Somatic Cell Hybrid Panel B C D EF A D7Z1 6-mer Waye et al (1987) 98% GenBank: M16101 Flow Sorted Chromosome Alignment/Enrichment Illumina sequencing of isolated human chromosomes Long Range Read Support “Anchor” to mapped to the assembled p-arm and/ or q-arm Chromosome specific assignment
- 22. Chromosome-assignment of Higher Order Repeats
- 23. Read Depth Estimates of Average Satellite Array Size 7q-arm D7Z1 (6-mer) 7p-arm D7Z2 (16-mer) R Wevrick and H F Willard. NAR ( 1991 )
- 24. Array size estimate: ~2.65 Mb Read Depth Estimates of Average Satellite Array Size 7q-arm D7Z1 (6-mer) D7Z2 (16-mer) B C D EF A 7p-arm Array estimate: ~0.42 Mb D7Z1 (Illumina Read Database) Hybrid approach Long reads inform sequence structure Short, high-quality reads generate frequency estimates
- 25. Array size estimate: ~2.65 Mb Read Depth Estimates of Average Satellite Array Size 7q-arm D7Z1 (6-mer) D7Z2 (16-mer) B C D EF A 7p-arm Array estimate: ~0.42 Mb D7Z1 (Illumina Read Database) 0 50 100 150 200 D7Z2 D7Z1 Individuals 0.0 5.00.5 1.0 1.5 2.0 3.0 4.0 4.53.52.5 Array Size (Mb)
- 26. 7q-arm 7p-arm Predicting HOR Repeat Variants α-Centauri (centromeric automated repeat identification) B C D EF A 5’… …3’ (6-mer) (4-mer)
- 27. 7q-arm B C D EF A 7p-arm Predicting HOR Repeat Variants 1.0 1.0 1.0 0.9 0.9 0.9 0.1 Hybrid approach Long reads inform sequence structure Short, high-quality reads generate frequency estimates
- 28. 7q-arm 7p-arm Map Single Nucleotide Variants -G--T- B C D EF A B’ 0.9 1.0 0.1 0.9 0.9 0.9 0.9 0.1 0.1 26 2565 Account for SNVs (frequency and position) within the array
- 29. 7q-arm 7p-arm Incorporate Interspersed Repeats -G--T- B C D EF A B’ LINE … L1/LINE L1Hs (2384 bp) LINE LINE
- 30. 7q-arm 7p-arm Detecting Array Inversions -G--T- … INVERSION Map shifts in orientation using long error corrected PacBio Reads 228 bp alpha satellite partial monomer at rearrangement
- 31. GENES INVERSION q-armp-arm Non-Satellite DNA Linking to chromosome arms and non-satellite DNA
- 32. CEN3: 300Kb Segmental Duplication from 6p11.2 Gene: DNA Primase Polypeptide 2 GENES INVERSION q-armp-arm Non-Satellite DNA Linking to chromosome arms and non-satellite DNA
- 33. INVERSION p-arm q-arm LINE SINE OTHER ... ...-A- -T- Construct a new graphical reference for each centromeric region to broaden research in these areas Genome Informatics CEN X
- 34. Key Advantages of Satellite DNA Graphs 1. Eliminates sequence redundancy
- 35. Key Advantages of Satellite DNA Graphs Improves Unambiguous Short Read Mapping REPEAT REPEAT REPEAT ? 5’ 3’REPEAT Benedict Paten Adam Novak Centromere Graphs Demonstrate unambiguous mapping the majority ( > 98%) of 1000 genome alpha satellite reads 1. Eliminates sequence redundancy
- 36. Key Advantages of Satellite DNA Graphs 1. Eliminates sequence redundancy 2. Information describing long-range haplotypes are retained as defined “paths” in the graph:
- 37. Key Advantages of Satellite DNA Graphs 1. Eliminates sequence redundancy 2. Information describing long-range haplotypes are retained as defined “paths” in the graph 3. Graph data structure and sequence analysis tools will be consistent with the rest of the human genome The major histocompatibility complex (Kiran Garimella & Gil McVean)
- 38. Part II: Variation Map The major histocompatibility complex (Kiran Garimella & Gil McVean) Expand the human “variation reference map” to include centromeric DNAs
- 39. p-arm q-arm ... ... 1 2 3 4 5 6 7 8 9 10 11 12 CENX DXZ1 ~ 2kb (12-mer) Study of Array Structural Variation
- 40. 1 2 3 4 5 6 7 8 9 10 11 12 DXZ1 ~ 2kb (12-mer) Study of Array Structural Variation cenX Ref Graph 1 2 3 4 5 67 8 9 10 11 12
- 41. Detection of Sequence Variants hg002 (son) hg003 (father) hg004 (mother) 45,43,53 Zook, Justin M., et al. 2016 Personal Genome Project trio: Ashkenazim Jewish ancestry
- 42. Detection of Sequence Variants hg002 (son) hg003 (father) hg004 (mother) 45,43,53 DEL ~0.3% >98% structural variant cononical repeat Zook, Justin M., et al. 2016
- 43. REARRANGEMENTS SHARED BY TRIO hg002 (son) hg003 (father) hg004 (mother) ????? ?? ?
- 44. Detection of Sequence Variants hg002 (son) hg003 (father) hg004 (mother) ?????? ??? ?
- 45. Detection of Sequence Variants AJ Trio Han Chinese (HG00512) Yoruba (NG19340) Puerto Rican (HG00733) Expand graph to include 4 reference populations Collaboration: Ali Bashir and Matthew Pendleton; Ichan Institute
- 46. Inversion Polymorphism NA24385 NA24149 Ashkenazi Jewish (AJ) Trio Mobile element insertion L1Hs/LINE HuRef Genome: GM12878 Genome: CHM1 Genome: CHM13 Genome: 16-mer 14-mer 99.6% 0.4% 16-mer 15-mer17-mer 14-mer 99.3% 0.5%0.1% 0.1% CEN17 (D17Z1) Allele 1 Allele 2 Allele 1 Allele 2 Copy Number Variation Allele 1 Allele 2 Single Nucleotide Polymorphisms Allele 1 Allele 2 …ATACGGATTTCATGACAGGTTA… …ATACGGATTTGATGACAGGTTA… Illumina: Determine Frequency
- 47. Miga et al (2014) p-arm q-arm ... ... Individual A 8.3 Mb p-arm q-arm ... ... 0.7 Mb Individual B Individuals Array Size (Mb) 0 5 10 15 20 98.587.576.565.554.543.532.521.510.5 Study of Array Size Variation
- 48. Sequence Variation Collection of 19 high coverage genomes (~30-60X) 9 Populations, 3 Trios Expand genome informatics to provide an assessment of common satVARs in population 1000 Genome Data (1,092) individuals from 26 distinct populations Identify a new source of human sequence variation
- 49. Satellite DNA Variants Associated with Cancer (Germline) ? Catalogue of all Common Human Satellite DNA Variants Novel Human Biomarkers: Use of genomics to greatly improve CEN variant detection Increase population based sampling to improve statistical tests Does of human sequence variation in centromeric regions contribute to disease?
- 50. David Haussler Benedict Paten Jim Kent (CGL, UCSC Browser, Haussler Wet Lab) Sofie Salama Adam Novak Maximilian Haeussler Brian Raney Ian Fiddes Yulia Newton (Josh Stuart) Jason Chin Volkan Sevim Creating (and mapping to) a Universal Reference Genome Benedict Paten, Adam Novak, David Haussler, UC Santa Cruz Acknowledgements Alex Hastie Denghong Zhang Ali Bashir Thomas Keane Mark Akeson Miten Jain Hugh Olsen