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1 Structural(varia+on! Programming)for)Biology)! CSH,!October!2012!!!! Tomas!Marques7Bonet! ICREA!Research!Professor! InsAtut!de!Biologia!EvoluAva! Nucleotide Forms!of!geneAc!variaAon.!! Single)base8pair)changes) Cytogenetics Con/nuum)of)Genomic)Varia/on)!!Point!mutaAons!(1!per!800!bp)!! Small)inser/ons/dele/ons)! FrameshiM,!microsatellite,!minisatellite!!! Mobile)elements)! Retroelement!inserAons!(300bp!710!kb)!! Large8scale)genomic)copy)) number)varia/on!(>10!kb)!! Large7scale!DeleAons!! Segmental!DuplicaAons!! Local)Rearangements)! Chromosomal)varia/on)! TranslocaAon,!inversion,!fusion!! Copy Number Variation Structural Variants (SV)
2 Genomic)Structural)Varia/on) Human!GeneAc!! VariaAon! Frequency! SNPs! structural!! variaaon! cytogeneac!!gene7altering,!e.g.!immune! response,!drug!metabolism!!abundant:!majority!of!human! heterozygosity!!numerous!plausible!funcaonal! consequences! 1!bp! Size! 1!chr! Types of Structural Variation) Hurles et al. 2008
3 Why)Study)Structural)Varia/on?) Common!in! normal!human!genomes77 major!cause!of!phenotypic!variaaon! Common!in!certain!diseases,!parAcularly! cancer! Now!showing!up!in!rare!disease;!auAsm,! schizophrenia! 17q21.31!deleAon!syndrome!! 16p12.1!deleAon!syndrome!! Zody)et(al.)Nature!GeneAcs!(2008)! Antonacci)et(al.)Nature!GeneAcs!(2010)! MR,!global!delay!and!! congenital!cardiac!defects!! childhood!intellectual!disability,!developmental!delay!
4 Challenges!of!CNV!studies! OMen!involves!repeated!regions! Rearrangements!are!complex! Can!involve!highly!repeAAve!elements! Methods)to!Find)SVs) Experimental!approach!! ArrayCGH (SNP based and genomic) Sequence!based! Local and de novo assembly Read pair analysis Read depth analysis Split read analysis
5 METHOD)1:)Copy)Number)Varia/on:) Array)Compara/ve)Genomic)Hybridiza/on) Modified:Feuk et al. Nat Rev Genet 2006 Genome)Tiling)Arrays! 800!bp! 25736mer!
6 Typical)Analysis)Procedure) For!each!probe,!calculate!a!log2!raAo!of!test/ reference! Log2!serves!to!center!values!around!0! Hemizygous!deleAon!in!test:!log2(test/ reference)=log2(1/2)=71! DuplicaAon!in!test:!!!!log2(test/reference)=log2(3/2)=0.59! Homozygous!duplicaAon:!!!log2(test/reference)=log2(4/2)=1! Copy Number Variations in the Human Genome Signal) Person)1) Signal) Person)2) Chromosome)Posi/on) Extra)DNA) Missing)DNA)
7 37State!HMM! log2! State!! Assignment! Gain! SegmentaAon!using!a!37state!HMM!(Viterbi!Algorithm)! Normal! Loss! METHOD)2:)Copy)Number)Varia/on:) SNP)genotyping)Array) Steemers!et)al.)
8 SNP)Fluorescence8Based)Dele/on)Discovery) A!B!B!A! B!A!B!B! B7Allele!Freq! 0.5! 0! 1! AB! BB! 0! 71! 1! LogR! CopyNum=2! A7! B7! A!B!B!A! B7Allele!Freq! 0.5! 0! 1! 0! 71! 1! LogR! CopyNum=1! A!B!B!A! B!A!B!B! 0! 71! 1! LogR! B7Allele!Freq! 0.5! 0! 1! AB! BB! CopyNum=2! A!B!B!A! B!A!B!B! A!B!B!A! B7Allele!Freq! 0.5! 0! 1! AAB! BBB! ABB! 0! 71! 1! LogR! CopyNum=3!
9 1! LogR!and!B7Allele!Frequency! 0.5! 0! 70.5! 71! ~90)kbp) Human!chromosome!2!posiAon! Sequencing)Methods) Going!Backwards!Sanger,!454,!Illumina..! CNV!and!SV!are!hotspots!of!research!but!reality!is:! LimitaAons!of!the!methods! Indirect!methods.!ALL!have!problems!!! What!do!we!want?! Clone!approached! Finish!sequence!!
10 De)novo)assemblies) Theory!vs.!Reality! Most!assemblies!(even!with!Sanger!technology!)!are!collapsed.! Examples.! DistribuAon!of!Total!duplicaAons! BONOBO CHIMP (pantro2) WGS! 454! HUMAN (hg18) Hg18 identity Distribution inter WGS! Sanger!sequence! intra Bases(bp) % 91.00% 92.00% 93.00% 94.00% 95.00% 96.00% 97.00% identity(%) 98.00% 99.00% 99.50% % BAC!hierarchical! Sanger!sequence!
11 LimitaAons!of!NGS!assemblies! Alkan et al. Nature Methods 2010 Method)2:)End8Sequence)Pair) (ESP))Analysis) End-Sequence Pairs Insert Size Distribution Human DNA Fosmid Vector Map to reference Number of Clones < 32 kb Putative Insertion >48 kb Putative Deletion Apparent Insert Size Genomic DNA Diploid Sample Tuzun et al. (2005)
12 Method)2:)End8Sequence)Pair) (ESP))Analysis) End-Sequence Pairs Insert Size Distribution Human DNA Fosmid Vector Map to reference Number of Clones < 32 kb Putative Insertion >48 kb Putative Deletion discordant by orientation (yellow/gold) discordant by size (red) reference sample Deletion Insertion Inversion Apparent Insert Size Tuzun et al. (2005) What!can!we!find?! Structural!variaAon!detecAon:! Alkan!et!al.!Nature!Review!GeneAcs!2011!
13 Map)of)Validated)Variants) ABC14 (CEPH) ABC13 (Yoruba) ABC12 (CEPH) ABC11 (China) ABC10 (Yoruba) ABC9 (Japan) ABC8 (Yoruba) ABC7 (Yoruba) G248 chr17 Genome wide map of variants Ability to resolve structure of individual haplotypes Insertion (Fosmid) Deletion Inversion Gaps Insertion (Fosmid) Deletion Inversion Gaps Novel Sequence ABC14 (CEPH) ABC13 (Yoruba) ABC12 (CEPH) ABC11 (China) ABC10 (Yoruba) ABC9 (Japan) ABC8 (Yoruba) ABC7 (Yoruba) G248
14 Frequency)of)Validated)Sites) Reference genome represents minor allele Number of sites Deletions Insertions Inversions Number of individuals (libraries) reporting variant site 261 (15%) sites where reference genome represents a minor allele Method)3:)Sequence!Read!Depth! Analysis) Individual sequence Reads Mapping Reference genome Counting mapped reads Read depth signal #!reads! 28 HMM!calls!
15 Method)3:)Sequence!Read!Depth! Analysis) Individual sequence Reads Mapping Reference genome Read depth signal Counting mapped reads #!reads! 29 HMM!calls! Sequence!coverage!and!detecAon!power!
16 ValidaAon!of!copy7number!esAmaAons! Alkan)et)al.,)Nature)Gene0cs,)2009) Defensin!gene!cluster!+!FAM90A7) Associated)with)psoriasis)and) Crohn s)disease) Alkan)et)al.,)Nature)Gene0cs,)2009)
17 Scaling!up:!1000!Genomes!and!more! Individuals)sequenced)in)Pilot)1) Histogram)of)Pilot)1)Illumina)effec/ve)coverage) 120) Yoruba)56) Number!of!genomes! 100) CEPH)48) Japanese)27) Han)29) 80) 60) 40) 20) 0) 1) 2) 3) 4) 5) 6) 7) 8) 9) 10) EffecAve!Coverage! Individuals)sequenced)in)Pilot)2) Other)Genomes) Sudmant,)Kitzman,)et)al.,)Science,)2010) Copy)number)varia/on)in)) human)popula/ons) Sudmant)et)al.)Science)2010)
18 DeleAons Split8read)Analysis) Dele/on)Event) Reference DeleAon! Read Breakpoint! Inser/on)Event) Reference Read InserAon!
19 Experimental)Valida/on) a A))CGH! c B) Fiber-FISH (For inversions) Without inversion With inversion CGH) PEM( b C))PCR! M A B C D A B C D A B C D A B C D A B C D A B C D A B C D A B C D M 3000 bp 1500 bp 500 bp Experimental!approach!! Methods)to!Find)SVs) ArrayCGH (SNP based and genomic) Based on ratios, Saturate quite fast, poor breakpoint resolution Sequence!based! Read pair analysis Deletions, small novel insertions, inversions, transposons Size and breakpoint resolution dependent to insert size Read depth analysis Deletions and duplications Relatively poor breakpoint resolution Split read analysis Small novel insertions/deletions, and mobile element insertions 1bp breakpoint resolution Local and de novo assembly SV in unique segments 1bp breakpoint resolution
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