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Tecniche per l’analisi di mutazioni Vincenzo Nigro Dipartimento di Patologia Generale, Seconda Università degli Studi di Napoli Telethon Institute of Genetics.

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Presentation on theme: "Tecniche per l’analisi di mutazioni Vincenzo Nigro Dipartimento di Patologia Generale, Seconda Università degli Studi di Napoli Telethon Institute of Genetics."— Presentation transcript:

1 Tecniche per l’analisi di mutazioni Vincenzo Nigro Dipartimento di Patologia Generale, Seconda Università degli Studi di Napoli Telethon Institute of Genetics and Medicine (TIGEM)

2 What is a mutation? a variation of the DNA sequence…...that is only found in affected individuals..that is never found in non affected individuals..that accounts for the pathological process/status..that, when corrected in time, disease is rescued

3 ..that is only found in affected and that is never found in non affected incomplete penetrance that is more often found in affected than in non affected...

4 50.000 private variants = innocuous differences belonging to one family CCCCAGCCTCCTTGCCAACGCCCCCTTTCCCTCTCCCCCTCCCGCTCGGCGCTGACC CCCCATCCCCACCCCCGTGGGAACACTGGGAGCCTGCACTCCACAGACCCTCTCCTT GCCTCTTCCCTCACCTCAGCCTCCGCTCCCCGCCCTCTTCCCGGCCCAGGGCGCCG GCCCACCCTTCCCTCCGCCGCCCCCCGGCCGCGGGGAGGACATGGCCGCGCACAG GCCGGTGGAATGGGTCCAGGCCGTGGTCAGCCGCTTCGACGAGCAGCTTCCAATAA AAACAGGACAGCAGAACACACATACCAAAGTCAGTACTGAGCACAACAAGGAATGTC TAATCAATATTTCCAAATACAAGTTTTCTTTGGTTATAAGCGGCCTCACTACTATTTTAA AGAATGTTAACAATATGAGAATATTTGGAGAAGCTGCTGAAAAAAATTTATATCTCTCT CAGTTGATTATATTGGATACACTGGAAAAATGTCTTGCTGGGCAACCAAAGGACACAA TGAGATTAGATGAAACGATGCTGGTCAAACAGTTGCTGCCAGAAATCTGCCATTTTCT TCACACCTGTCGTGAAGGAAACCAGCATGCAGCTGAACTTCGGAATTCTGCCTCTGG GGTTTTATTTTCTCTCAGCTGCAACAACTTCAATGCAGTCTTTAGTCGCATTTCTACCA GGTTACAGGAATTAACTGTTTGTTCAGAAGACAATGTTGATGTTCATGATATAGAATTG TTACAGTATATCAATGTGGATTGTGCAAAATTAAAACGACTCCTGAAGGAAACAGCAT TTAAATTTAAAGCCCTAAAGAAGGTTGCGCAGTTAGCAGTTATAAATAGCCTGGAAAA GGCATTTTGGAACTGGGTAGAAAATTATCCAGATGAATTTACAAAACTGTACCAGATC CCACAGACTGATATGGCTGAATGTGCAGAAAAGCTATTTGACTTGGTGGATGGTTTTG CTGAAAGCACCAAACGTAAAGCAGCAGTTTGGCCACTACAAATCATTCTCCTTATCTT GTGTCCAGAAATAATCCAGGATATATCCAAAGACGTGGTTGATGAAAACAACATGAAT AAGAAGTTATTTCTGGACAGTCTACGAAAAGCTCTTGCTGGCCATGGAGGAAGTAGG CAGCTGACAGAAAGTGCTGCAATTGCCTGTGTCAAACTGTGTAAAGCAAGTACTTACA TCAATTGGGAAGATAACTCTGTCATTTTCCTACTTGTTCAGTCCATGGTGGTTGATCTT AAGAACCTGCTTTTTAATCCAAGTAAGCCATTCTCAAGAGGCAGTCAGCCTGCAGATG TGGATCTAATGATTGACTGCCTTGTTTCTTGCTTTCGTATAAGCCCTCACAACAACCAA CACTTTAAGATCTGCCTGGCTCAGAATTCACCTTCTACATTTCACTATGTGCTGGTAAA TTCACTCCATCGAATCATCACCAATTCCGCATTGGATTGGTGGCCTAAGATTGATGCT GTGTATTGTCACTCGGTTGAACTTCGAAATATGTTTGGTGAAACACTTCATAAAGCAG TGCAAGGTTGTGGAGCACACCCAGCAATACGAATGGCACCGAGTCTTACATTTAAAG AAAAAGTAACAAGCCTTAAATTTAAAGAAAAACCTACAGACCTGGAGACAAGAAGCTA TAAGTATCTTCTCTTGTCCATGGTGAAACTAATTCATGCAGATCCAAAGCTCTTGCTTT GTAATCCAAGAAAACAGGGGCCCGAAACCCAAGGCAGTACAGCAGAATTAATTACAG GGCTCGTCCAACTGGTCCCTCAGTCACACATGCCAGAGATTGCTCAGGAAGCAATGG AGGCTCTGCTGGTTCTTCATCAGTTAGATAGCATTGATTTGTGGAATCCTGATGCTCC TGTAGAAACATTTTGGGAGATTAGCTCACAAATGCTTTTTTACATCTGCAAGAAATTAA CTAGTCATCAAATGCTTAGTAGCACAGAAATTCTCAAGTGGTTGCGGGAAATATTGAT CTGCAGGAATAAATTTCTTCTTAAAAATAAGCAGGCAGATAGAAGTTCCTGTCACTTTC CCCCAGCCTCCTTGCCAACGCCCCCTTTCCCTCTCCCCCTCCCGCTCGGCGCTGACC CCCCATCCCCACCCCCGTGGGAACACTGGGAGCCTGCACTCCACAGACCCTCTCCTT GCCTCTTCCCTCACCTCAGCCTCCGCTCCCCGCCCTCTTCCCGGCCCAGGGCGCCG GCCCACCCTTCCCTCCGCCGCCCCCCGGCCGCGGGGAGGACATGGCCGCGCACAG GCCGGTGGAATGGGTCCAGGCCGTGGTCAGCCGCTTCGACGAGCAGCTTCCAATAA AAACAGGACAGCAGAACACACATACCAAAGTCAGTACTGAGCACAACAAGGAATGTC TAATCAATATTTCCAAATACAAGTTTTCTTTGGTTATAAGCGGCCTCACTACTATTTTAA AGAATGTTAACTATATGAGAATATTTGGAGAAGCTGCTGAAAAAAATTTATATCTCTCT CAGTTGATTATATTGGATACACTGGAAAAATGTCTTGCTGGGCAACCAAAGGACACAA TGAGATTAGATGAAACGATGCTGGTCAAACAGTTGCTGCCAGAAATCTGCCATTTTCT TCACACCTGTCGTGAAGGAAACCAGCATGCAGCTGAACTTCGGAATTCTGCCTCTGG GGTTTTATTTTCTCTCAGCTGCAACAACTTCAATGCAGTCTTTAGTCGCATTTCTACCA GGTTACAGGAATTAACTGTTTGTTCAGAAGACAATGTTGATGTTCATGATATAGAATTG TTACAGTATATCAATGTGGATTGTGCAAAATTAAAACGACTCCTGAAGGAAACAGCAT TTAAATTTAAAGCCCTAAAGAAGGTTGCGCAGTTAGCAGTTATAAATAGCCTGGAAAA GGCATTTTGGAACTGGGTAGAAAATTATCCAGATGAATTTACAAAACTGTACCAGATC CCACAGACTGATATGGCTGAATGTGCAGAAAAGCTATTTGACTTGGTGGATGGTTTTG CTGAAAGCACCAAACGTAAAGCAGCAGTTTGGCCACTACAAATCATTCTCCTTATCTT GTGTCCAGAAATAATCCAGGATATATCCAAAGACGTGGTTGATGAAAACAACATGAAT AAGAAGTTATTTCTGGACAGTCTACGAAAAGCTCTTGCTGGCCATGGAGGAAGTAGG CAGCTGACAGAAAGTGCTGCAATTGCCTGTGTCAAACTGTGTAAAGCAAGTACTTACA TCAATTGGGAAGATAACTCTGTCATTTTCCTACTTGTTCAGTCCATGGTGGTTGATCTT AAGAACCTGCTTTTTAATCCAAGTAAGCCATTCTCAAGAGGCAGTCAGCCTGCAGATG TGGATCTAATGATTGACTGCCTTGTTTCTTGCTTTCGTATAAGCCCTCACAACAACCAA CACTTTAAGATCTGCCTGGCTCAGAATTCACCTTCTACATTTCACTATGTGCTGGTAAA TTCACTCCATCGAATCATCACCAATTCCGCATTGGATTGGTGGCCTAAGATTGATGCT GTGTATTGTCACTCGGTTGAACTTCGAAATATGTTTGGTGAAACACTTCATAAAGCAG TGCAAGGTTGTGGAGCACACCCAGCAATACGAATGGCACCGAGTCTTACATTTAAAG AAAAAGTAACAAGCCTTAAATTTAAAGAAAAACCTACAGACCTGGAGACAAGAAGCTA TAAGTATCTTCTCTTGTCCATGGTGAAACTAATTCATGCAGCTCCAAAGCTCTTGCTTT GTAATCCAAGAAAACAGGGGCCCGAAACCCAAGGCAGTACAGCAGAATTAATTACAG GGCTCGTCCAACTGGTCCCTCAGTCACACATGCCAGAGATTGCTCAGGAAGCAATGG AGGCTCTGCTGGTTCTTCATCAGTTAGATAGCATTGATTTGTGGAATCCTGATGCTCC TGTAGAAACATTTTGGGAGATTAGCTCACAAATGCTTTTTTACATCTGCAAGAAATTAA CTAGTCATCAAATGCTTAGTAGCACAGAAATTCTCAAGTGGTTGCGGGAAATATTGAT CTGCAGGAATAAATTTCTTCTTAAAAATAAGCAGGCAGATAGAAGTTCCTGTCACTTTC

5 1-allele diseases monoallelic mutations may be responsible for dominant or X-linked disorders new random mutations are the rule with an unpredictable pattern of distribution

6 gender effect in mutations For mutations other than point mutations, sex biases in the mutation rate are very variable Small deletions are more frequent in females Germline base substitution mutations occur more frequently in males than in females, especially in older males Point mutations at some loci occur almost exclusively in males, whereas others occur ten times more than in females

7 relative frequency of de novo achondroplasia for different paternal ages

8 Relative frequency of de novo neurofibromatosis for different paternal ages

9 the number of male germ-cell divisions

10

11 2-allele diseases novel mutations are rare, usually mutations have a long history (100-1000 generations) mutations have an ethnical signature with a predictable pattern of distribution and frequency biallelic mutations may be responsible for autosomal recessive disorders polymorphisms and private variants are more easily discriminated vs true mutations

12 2-allele diseases consanguineity is a risk factor for homozygosity high carrier frequency is a risk factor for compound heterozygosity

13 The effect of an allele null or amorph = no product hypomorph = reduced amount / activity hypermorph = increased amount / activity neomorph = novel product / activity antimorph = antagonistic product / activity

14 Mutation detection mutation scanning or resequencing methods for identifying previously unknown mutations genotyping methods for scoring previously known mutations or single nucleotide polymorphisms (SNPs)

15 Key questions for mutation detection strategy expected mutations are monoallelic or biallelic? is the gene well recognized for that disease? is the mutation pattern known? (deletion, dup, small mutations, etc.) which is the complexity of the gene? how many patients must be examined? how many controls should be examined? how many mutations and how many variations have already been identified in this gene? are there more members of the same gene family (or pseudogenes) in the genome?

16 Gene size Number of patients X Number of controls Dimension of the mutation detection study

17 frequent mutations are known? mutation scanning SEQUENCING screening of recurrent mutations YES NO are identified? YES NO General strategy for mutation detection

18 DMD AB BMD C D Log-PCR = 4 multiplex-PCR (2x20+2x18) with uniform spacing and gel position according to chromosomal position 1 2 3 4 5 6 1: del ex 43 2: del ex 11, 17, 19, 21 3: del ex 17, 19, 21 4: del ex 50, 52 5: del ex 7, 11, 17, 19 6: del ex 61 1: no del 2: del ex 8, 12, 18, 20, 22 3: del ex 12, 18, 20, 22 4: del ex 46, 51 5: del ex 6, 8, 12, 18 6: del ex 62

19 MLPA ligation Probes are ligated by a thermostable ligase

20 PCR amplification A universal primer pair is used to amplify all ligated probes The PCR product of each probe has a unique length (130 480 bp)

21 Separation and quantification by capillary electrophoresis Each peak is the amplification product of a specific probe. Samples are compared to a control sample. A difference in relative peak height or peak area indicates a copy number change of the probe target sequence

22 MLPA can be used to detect known mutations MismatchPerfect match Ligation of the two probe oligonucleotides  Amplification product Mismatch at the probe ligation site  No ligation, no amplification product

23 MRC-Holland b.v. Unmethylated Target M M Methylated Target Denaturation and Multiplex probe hybridization M Only undigested (methylated) and ligated probes are exponentially amplified Ligation and Digestion with methylation sensitive endonucleases M MS-MLPA

24 Molecular inversion probe (MIP) genotyping MIP genotyping uses circularizable probes with 5′ and 3′ ends that anneal upstream and downstream of the SNP site leaving a 1 bp gap Polymerase extension with dNTPs and a non-strand- displacing polymerase is used to fill in the gap

25 Ligation seals the nick, and exonuclease I is used to remove excess unannealed and unligated circular probes The resultant product is PCR-amplified and the orientation of the primers ensures that only circularized probes will be amplified The resultant product is hybridized and read out on an array of universal-capture probes

26 GoldenGate uses extension ligation between annealed locus- specific oligos (LSOs) and allele-specific oligos (ASOs) An allele-specific primer extension step is used to preferentially extend the correctly matched ASO (at the 3′ end) up to the 5′ end of the LSO primer Ligation then closes the nick GoldenGate genotyping assay

27 A subsequent PCR amplification step is used to amplify the appropriate product using common primers to ‘built-in’ universal PCR sites in the ASO and LSO sequences The resultant PCR products are hybridized and read out on an array of universal-capture probes GoldenGate genotyping assay

28 PTT protein truncation test Sensitivity 1000-bp fragment > 85% Detects only nonsense mutations Post PCR time: 48-72 hours (translation/trascription, gel preparation, loading and run, analysis of results) Use of 35S radioactivity No special equipment required mRNA as starting template

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31 Applications of PTT (% of truncating mutations) Polycystic Kidney Disease PKD1 95% Familial Adenomatous Polyposis APC 95% Ataxia telangiectasia ATM 90% Hereditary breast and ovarian cancer BRCA1-290% Duchenne Muscular Dystrophy DMD 90% Fanconi anemia FAA80% Hereditary non-polyposis colorectal cancer hMSH1-2 70%-80% Neurofibromatosis type 2 NF2 65% Hunter Syndrome IDS50% Neurofibromatosis type 1 NF1 50% Cystic Fibrosis CFTR15%

32 SSCP

33 Mutation detection by heteroduplex analysis: the mutant DNA must first be hybridized with the wild-type DNA to form a mixture of two homoduplexes and two heteroduplexes

34 Heteroduplex analysis

35 DHPLC denaturing HPLC from Transgenomic

36 DHPLC analysis at different temperatures of the column

37 DHPLC analysis of the CAPN3 gene (exon 11) UV 02 FLUO 0 100 1:21:41:61:81:10

38 Sequencing artifacts FALSE POSITIVE (specificity) when searching for heterozygous DNA differences there are a number of potential mutations, together with sequence artifacts, compressions and differences in peak intensities that must be re-checked with additional primers and costs FALSE NEGATIVE (sensitivity) loss of information farther away or closer to the primer does not detect a minority of mutant molecules in a wild- type environment

39 Sanger DNA sequencing

40

41 Massive parallel DNA sequencing

42 454 technology: a water-in-oil emulsion is created: a single molecule of DNA with a single bead

43 454 technology: Beads with clones are selected and assembled onto a planar substrate

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45 454 technology: Sequencing by synthesis pyrosequencing Up to 100 Million bp in 8 hours can be read Ambiguities arise for homopolymeric tracts

46 Emulsion PCR or Bridge PCR?

47

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49 7.4 x coverage 234 runs 24.5 billions bp

50 NimbleGen sequence capture

51 11 genetic diseases !!


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