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DNA copy number variation and cancer risk John F Pearson Canterbury Statistics Open Day University of Canterbury 2/10/2012
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2 Breast Cancer Foulkes WD. N Engl J Med 2008; 359:2143-2153
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3 Missing heritability TA Manolio et al. Nature 461, 747-753 (2009) doi:10.1038/nature08494
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4 Evan E. Eichler.
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5 Copy number variation Allele 1 Allele 2 Copy number loss Copy number gain Whole gene Partial gene Contiguous genes Regulatory effects
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6 Copy number variants (CNVs) 16,000 copy number variant loci cover >50% of the human genome CNVs are associated with cancer risk Rare CNVs detected in ~50% of familial cancer genes eg. BRCA1, BRCA2 Genome-wide association studies of cancer prostate cancer, hepatocarcinoma, nasopharyngeal carcinoma, and neuroblastoma Increased CNV load Li Fraumeni Syndome (cancer related genes?) breast cancer (TP53 pathway, ESR1 pathway)
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7 SNP arrays LRR = log 2 (R observed /R expected ) The B Allele Frequency (BAF) is a somewhat confusing term that actually refers to a normalized measure of relative signal intensity ratio of the B and A alleles Wang et al Genome Res. 2007 November; 17(11): 1665–1674.
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8 Genomic location
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9 Copy number AA AB B NormalCopy neutral LOH Copy number loss
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10 Copy number gain AAA AAB ABB BBB
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11 Illumina bead arrays. o CNVision (workflow software) o Gnosis o PennCNV o QuantiSNP o CNV Partition CNV calling CNV calling algorithms
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12 Hidden Markov Model Estimate copy number at each SNP from Log R ratio B allele frequency transition probability at previous SNP. PennCNV, QuantiSNP
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13 PennCNV
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14 PennCNV r i LRR b i BAF at SNP i. ( 1 ≤ i ≤ M ) z i copy number state The likelihood of the observed data is:
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15 PennCNV r i LRR b i BAF at SNP i. ( 1 ≤ i ≤ M ) z i copy number state The likelihood of the observed data is: LRR emission probability model includes a term for chemical fluctuations and misannotation/assembly BAF emission probability complicated mixture model
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16 PennCNV r i LRR b i BAF at SNP i. ( 1 ≤ i ≤ M ) z i copy number state Transmission probabilities between 2 adjacent SNPs i -1 and i. with copy numbers z i and z i-1 at distance d i. D = 100Mb for state 4, 100kb for other states. p are unknowns, estimated by the Baum-Welch algorithm.
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17 PennCNV r i LRR b i BAF at SNP i. ( 1 ≤ i ≤ M ) z i copy number state Baum-Welch used to train the model Viterbi algorithm used to infer most likely path CNV called whenever a stretch of states is different from normal ( usually state 3 or 4)
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18 Copy number gain AAA AAB ABB BBB
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19 Noisy data
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20 Breast cancer A characteristic of breast tumour cells is genomic instability BRCA1, BRCA2
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21 BRCA1: known large deletions Sample IDBRCA1 mutation EMB0001242del exons 2-24 EMB0001532del exons 3-19 EMB0001222del exons 1-23 EMB0001425del exons1-21 EMB0001439del exons 1-23 EMB0001458del exons 1-23 EMB0001477del exons1-21 GEM0002463del exons 16-23 PAD0005718del exons 9-19 EMB0001770del exons 1-17 EMB0001057del exons 1-17 KCO0003228 del exons 1-17 EMB0001082del exons 8-13 GEM0002430del exons 8-13 Sample IDBRCA1 mutation EMB0001530del exons 3-19 EMB0001689del exons 1-17 Detected Not detected CNV prediction summary: cnvPartition - 25% (4/16) GNOSIS- 19% (3/16) PennCNV- 88% (14/16) QuantiSNP- 81% (13/16)
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22 CNV calling by 4 algorithms QC(1) – GWAS criteria Endometrial cancer 1343 cases ANECS, SEARCH 1343 cases ANECS, SEARCH 655 female controls Hunter Community Study 655 female controls Hunter Community Study Case vs. control analyses 1279 cases 619 controls 1210 cases 612 controls Want to find: 1.CNVs overlapping known susceptibility genes 2.novel CNVs in the mismatch repair pathway 3.common or rare CNVs associations
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23 CNV frequency: all CaseControlDifferenceP 1,210612 Total CNVs26.726.50.2NS Deletions17.718.1-0.4NS Duplications8.98.40.5NS Exons7.16.90.2NS Mean CNV per sample
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24 CNV frequency: rare (< 1%) CaseControlDifferenceP 1,210612 Total CNVs63.32.74.0E-05 Deletions3.81.42.43.0E-06 Duplications2.21.90.3NS Exons63.32.72.0E-04 Mean rare CNV per sample
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25 CNV frequency: rare (< 1%) CaseControlDifferenceP 1,210612 Total CNVs63.32.74.0E-05 Deletions3.81.42.43.0E-06 Duplications2.21.90.3NS Exons63.32.72.0E-04 Mean rare CNV per sample
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26 Association study CaseControl P adjusted Chr01340134 X0100057000.000 X03070078000.000 X0200034000.000 X0000024000.000 691000435000.000 16012512700101900.000 X0000014000.001 681220343820477184276140.003 202200141600.006 70000012400.006 1103832001300.010 X0100001100.016 CNV Regions
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27 Association study CNV overlapping genes CaseControl P adjusted Chr01340134 X0200053000.000 10372000000.004 10352000000.004 70010013500.004 10362000000.004 10362000000.004 10342000000.005 10332000000.008 10311000000.011 10311000000.011 70432200000.011 X02260036000.021
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29 Acknowledgements University of Otago Gemma Moir-Meyer Logan Walker Mackenzie Cancer Research Group Queensland Institute of Medical Research Mandy Spurdle Felicity Lose Yen Tan Alex Metcalf Australian National Endometrial Cancer Study Bryony Thompson University of Cambridge Deborah Thompson Paul Pharoah Alison Dunning Douglas Easton Studies of Epidemiology and Risk Factors in Cancer Heredity (SEARCH) University of Newcastle Rodney Scott Mark McEvoy John Attia Elizabeth Holliday The Hunter Community Study CIMBA consortium MAYO clinic Fergus Couch
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