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Old 09-10-2009, 07:19 PM   #21
Patrick
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Hi henry,
Glad to know you at this forum


Quote:
Originally Posted by henry View Post
Hi patrick,
you are welcome. Good luck to your research.

Best

Jing
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Old 09-11-2009, 12:39 AM   #22
Patrick
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Hi henry,
Do you have experience deal with Illumina/Solexa data?
Do you know what is the general control lane used by them among total eight lane produced by them?
Thanks a lot for your explanation.


Quote:
Originally Posted by henry View Post
Hi patrick,
you are welcome. Good luck to your research.

Best

Jing
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Old 09-11-2009, 04:05 AM   #23
henry
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Quote:
Originally Posted by Patrick View Post
Hi henry,
Do you have experience deal with Illumina/Solexa data?
Do you know what is the general control lane used by them among total eight lane produced by them?
Thanks a lot for your explanation.
Hi Patrick,
I only have some experiences (still limited ) in dealing with Illumina short reads data.
I got some information from paper named "improved base calling for the illumina genome analyzer using machine learning strategies" by Martin Kircher, et al. You can read it. It's as follows:
If there isn't high frequency / low frequency of GC in the DNA/RNA library, the first or second imaging cycle can be used to estimate the crosstalk matrix, which is used to separate AC/GT channels and normalize the individual intensities (because the intensity of A and C channels are highly correlated, similarly for G and T channels). In this case there is no need to use control lane .
If there exists high frequency or low frequency of GC, PhiX174 RF1 is used as control lane.
Maybe someone who have participated in the whole procedure of solexa sequencing experiments can give us more information on the details.
Hopefully, I will participate more in the genome sequencing project.

Best

Jing
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Old 09-11-2009, 03:38 PM   #24
Patrick
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Hi Henry,
You are right. I got read "improved base calling for the illumina genome analyzer using machine learning strategies" as well
It is quite useful for me to understand more about the Illumina read ^^
For your info, Illumina read also can divide into Single end and Pair end.
The detail about the single end and pair end reads, I not very sure about it lah.
Still do some research about it ^^
I believe sure you got the chance to deal with more genome sequencing project in future.
At the moment, hopefully we can discuss together for your trouble facing
At last, still thanks for your explanation again ^^

Quote:
Originally Posted by henry View Post
Hi Patrick,
I only have some experiences (still limited ) in dealing with Illumina short reads data.
I got some information from paper named "improved base calling for the illumina genome analyzer using machine learning strategies" by Martin Kircher, et al. You can read it. It's as follows:
If there isn't high frequency / low frequency of GC in the DNA/RNA library, the first or second imaging cycle can be used to estimate the crosstalk matrix, which is used to separate AC/GT channels and normalize the individual intensities (because the intensity of A and C channels are highly correlated, similarly for G and T channels). In this case there is no need to use control lane .
If there exists high frequency or low frequency of GC, PhiX174 RF1 is used as control lane.
Maybe someone who have participated in the whole procedure of solexa sequencing experiments can give us more information on the details.
Hopefully, I will participate more in the genome sequencing project.

Best

Jing
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Old 09-11-2009, 07:44 PM   #25
BENM
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I am sorry for a prompt reply, there is a list of tenology approach & reference for detecting SV here, hope it help to you.

(1)GTG-banded karyotype
The gold standard for clinical cytogenetic testing still remains the GTG-banded karyotype, where a genomewide analysis usually identifies chromosomal rearrangements or aberrations of 3–5 Mb and larger.


(2)Array-based approach (array CGH/ROMA, SNP oligonucleotide microarray)
*ROMA, representational oligonucleotide microarray analysis

2004 Two initail studies using CGH technology:
used a bacterial artificial chromosome (BAC)-based array, with clones chosen at 1-megabase (Mb) intervals throughout the human genome, together with a technique called array-based comparative genomic hybridization (array CGH);

Comparative genomic hybridization (CGH) is a molecular-cytogenetic method for the analysis of copy number changes (gains /losses) in the DNA content of tumor cells. The method is based on the hybridization of fluorescently labeled tumor DNA (frequently Fluorescein - FITC) and normal DNA (frequently Rhodamine or Texas Red) to normal human metaphase preparations. Using epifluorescence microscopy and quantitative image analysis, regional differences in the fluorescence ratio of tumor vs. control DNA can be detected and used for identifying abnormal regions in the tumor cell genome. CGH will detect only unbalanced chromosomes changes. Structural chromosome aberrations such as balanced reciprocal translocations or inversions can not be detected, as they do not change the copy number.

2004

1/.Iafrate AJ, Feuk L, Rivera MN, Listewnik ML, Donahoe PK, Qi Y, Scherer SW, Lee C. Detection of large-scale variation in the human genome. Nat Genet. 2004 Sep;36(9):949-51.
Iafrate BAC microarray analysis
All hybridizations were performed in duplicate incorporating a dye-reversal using proprietary 1 Mb GenomeChip V1.2 Human BAC Arrays consisting of 2,632 BAC clones (Spectral Genomics, Houston, TX). The false positive rate was estimated at ~1 clone per 5,264 tested.
Further information is available from the Database of Genomic Variants website.


2/.Sebat J, Lakshmi B, Troge J, Alexander J, Young J, Lundin P, Maner S, Massa H, Walker M, Chi M et al. Large-scale copy number polymorphism in the human genome. Science. 2004 July 23;305(5683):525-8.
Sebat ROMA
Following digestion with BglII or HindIII, genomic DNA was hybridized to a custom array consisting of 85,000 oligonucleotide probes. The probes were selected to be free of common repeats and have unique homology within the human genome. The average resolution of the array was ~35kb; however, only intervals in which three consecutive probes showed concordant signals were scored as CNPs. All hybridizations were performed in duplicate incorporating a dye-reversal, with the false positive rate estimated to be ~6%.

2005

1/.Sharp AJ, Locke DP, McGrath SD, Cheng Z, Bailey JA, et al. 2005. Segmental duplications and copy number variation in the human genome. Am. J. Hum. Genet. 77:78–88
Sharp BAC microarray analysis
All hybridizations were performed in duplicate incorporating a dye-reversal using a custom array consisting of 2,194 end-sequence or FISH-confirmed BACs, targeted to regions of the genome flanked by segmental duplications. The false positive rate was estimated at ~3 clones per 4,000 tested.
2/.deVries BB, Pfundt R, Leisink M, Koolen DA,Vissers LE, et al. 2005. Diagnostic genome profiling in mental retardation. Am. J. Hum. Genet. 77:606–16

3/.Bruce S, Leinonen R, Lindgren CM, Kivinen K, Dahlman-Wright K, et al. 2005. Global
analysis of uniparental disomy using high density genotyping arrays. J. Med. Genet.
42:847–51

2006
1/.Locke analysis of duplication-rich regions
DNA samples were obtained from Coriell Cell Repositories. The reference DNA used for all hybridizations was from a single male of Czechoslovakian descent, Coriell ID GM15724 (also used in the Sharp study).
A locus was considered a CNV (copy number variation) if the log ratio of fluroescence measurements for the individuals assayed exceeded twice the standard deviation of the autosomal clones in replicate dye-swapped experiments. A CNV was classified as a CNP if altered copy number was observed in more than 1% of the 269 individuals.
Locke DP, Sharp AJ, McCarroll SA, McGrath SD, Newman TL, Cheng Z, Schwartz S, Albertson DG, Pinkel D, Altshuler DM et al. Linkage disequilibrium and heritability of copy-number polymorphisms within duplicated regions of the human genome. Am J Hum Genet. 2006 Aug;79(2):275-90.
Locke duplication-rich regions
The authors performed validation using a custom oligonucleotide array, hybridized to 9 of the HapMap individuals. Their analysis of the validation experiments indicated a false-negative rate of 5% and a false-positive rate of less than 0.2%.

2./Redon R, Ishikawa S, Fitch KR, Feuk L, Perry GH, Andrews TD, Fiegler H, Shapero MH, Carson AR, Chen W et al. Global variation in copy number in the human genome. Nature. 2006 Nov 23;444(7118):444-454.
The authors utilized numerous quality meaures, including repeated experiments on the WGTP array for 82 individuals and on the 500K EA array for 15 individuals. The average false-positive rate per experiment was held beneath 5%. Aberrant chromosomes were removed from the analysis.
Redon analysis of HapMap data
Experiments were performed with the International HapMap DNA and cell-line collection using two technologies: comparative analysis of hybridization intensities on Affymetric GeneChip Human Mapping 500K early access arrays (500K EA) and comparative genomic hybridization with a Whole Genome TilePath (WGTP) array.
Sanger-Two platforms for CNV detection
WGTP
500k EA
1447 copy number variable regions in the HapMap populations covering ~12% of the human genome (~360 Mb)

(3) Sequence-based approaches(Paired-End Mapping, SNP genotype, comparative sequence analysis)

2005

1/.Tuzun E, Sharp AJ, Bailey JA, Kaul R, Morrison VA, Pertz LM, Haugen E, Hayden H, Albertson D, Pinkel D et al. Fine-scale structural variation of the human genome. Nat Genet. 2005 Jul;37(7):727-32.
Tuzun fosmid mapping
Paired-end sequences from a human fosmid DNA library were mapped to the assembly. The average resolution of this technique was ~8kb, and included 56 sites of inversion not detectable by the array-based approaches. However, because of the physical constraints of fosmid insert size, this technique was unable to detect insertions greater than 40 kb in size
The authors systematically compared the human genome reference sequence to a second genome (represented by fosmid paired-end sequences) to detect intermediate-sized structural variants (ISV) > 8 kb in length. They identified 297 sites of structural variation, corresponding to 139 insertions, 102 deletions and 56 inversion breakpoints. Based on our combined literature, sequence and experimental analyses we provide validation for 112 of the structural variants including several of biomedical relevance. These data provide the first fine-scale structural variation map of the human genome and provide the requisite sequence precision for subsequent population and association studies with human disease.

2/.Feuk L, MacDonald JR,Tang T, Carson AR, Li M, et al. 2005. Discovery of human inversionpolymorphisms by comparative analysis of human and chimpanzee DNA sequence assemblies. PLoS Genet. 1:e56


2006
1./Conrad genotype analysis
The authors first tested 12 predicted deletions using quantitative PCR. For all 12 deletions, DNA concentrations consistent with transmission of a deletion from parent to child were observed.
To provide more extensive validation by comparative genome hybridization (CGH), the authors designed a custom oligonucleotide microarray comprised of 380,000 probes that tile across all 134 candidate deletions identified in 9 HapMap offspring (8 YRI and 1 CEU). The results of this CGH analysis indicate that the majority (about 85%) of candidate deletions detected by the method are real.
Conrad DF, Andrews TD, Carter NP, Hurles ME, Pritchard JK.A high-resolution survey of deletion polymorphism in the human genome Nat Genet. 2006 Jan;38(1):75-81.
Conrad genotype analysis (deletion polymorphism)
SNPs in regions that are hemizygous for a deletion are generally miscalled as homozygous for the allele that is present. Hence, when a deletion is transmitted from parent to child, the genotypes at SNPs within the deletion region will often appear to violate the rules of Mendelian transmission. The authors developed a simple algorithm for scanning trio data for unusual runs of consecutive SNPs that, in a single family, have genotype configurations consistent with the presence of a deletion.

2/.McCarroll genotype analysis
McCarroll SA, Hadnott TN, Perry GH, Sabeti PC, Zody MC, Barrett JC, Dallaire S, Gabriel SB, Lee C, Daly MJ et al. Common deletion polymorphisms in the human genome. Nat Genet. 2006 Jan;38(1):86-92.
A segregating deletion can leave "footprints" in SNP genotype data, including apparent deviations from Mendelian inheritance, apparent deviations from Hardy-Weinberg equilibrium and null genotypes. Using these clues to discover true variants is challenging, however, because the vast majority of such observations represent technical artifacts and genotyping errors.
To determine whether a subset of "failed" SNP genotyping assays in the HapMap data might reflect structural variation, the authors examined whether such failures were physically clustered in a manner that is specific to individuals. Consistent with this hypothesis, the rate of Mendelian-inconsistent genotypes was elevated near other Mendelian-inconsistent genotypes in the same individual but was unrelated to Mendelian inconsistencies in other individuals.
The authors systematically looked for regions of the genome in which the same failure profile appeared repeatedly at nearby markers in a manner that was statistically unexpected based on chance. A set of statistical thresholds was tailored to each mode of failure, genotyping center and genotyping platform used in the project. The same procedure could readily apply to dense SNP data from any platform or study.
Four methods of validation were used: fluorescent in situ hybridization (FISH), two-color fluorescence intensity measurements, PCR amplification and quantitative PCR.
The authors performed fluorescent in situ hybridization for five candidate deletions large enough to span available FISH probes. In all five cases, FISH assays confirmed the deletions in the predicted individuals.
The authors examined two-color allele-specific fluorescence data from SNP genotyping assays from a data subset available at the Broad Institute, looking for a reduction in fluorescence intensity in individuals predicted to carry a deletion. At most SNPs in the genome, fluorescence intensity measurements clustered into two or three discrete groups corresponding to homozygous and hetrozygous genotypes. At 15 of 17 candidate deletion loci, fluorescence intensity data for one or more SNPs clustered into additional groups that corresponded to the predicted deletion genotypes.
The authors used PCR amplification to query 60 loci for which the pattern of genotypes suggested multiple individuals with homozygous deletions. Variants were considered confirmed if the pattern of amplification success and failure matched prediction across a set of 12-24 individuals. The authors confirmed 51 of 60 candidate variants by this criterion.
The authors performed quantitative PCR in all 269 HapMap DNA samples for 11 candidate deletions that overlapped the coding exons of genes and that were discovered in many individuals. At 10/11 loci, the authors observed three discrete clusters, identifying individuals with zero, one and two gene copies. All 60 trios displayed Mendelian inheritance for the ten deletions, as well as Hardy-Weinberg equilibrium in all four populations surveyed, and transmission rates close to 50%. This suggests that the deletions behave as a stable, heritable genetic polymorphism.

2007

High-throughput Paired-End Sequencing like 454, solexa, and SOLiD. Paired-End Mapping to the reference genome to find structural variation.
Korbel et al., Paired-End Mapping Reveals Extensive Structural Variation in the Human Genome Science, 27 September 2007 (10.1126/science.1149504).
Structural rearrangements were identified as significant differences between the fragments identified by the paired-end reads and the corresponding regions of the reference sequence.
Strategies:
Five different signatures(i-v)were used to predict SVs.
(i)Deletions relative to the reference genome were identified by paired-ends spanning a genomic region in the reference genome longer than a specified cutoff;
(ii)Simple insertions relative to the reference genome werepredicted with paired-ends that spanned a region shorter than a cutoff;
(iii)Mated insertions contained sequences connected to a distal locus on the basis of their paired-ends;
(iv)Inversions were detected through a relative orientation different from the reference genome;
(v)Unmated insertions contained sequences connected to a distal locus; one of the two expected breakpoints remained undetected. Unless stated otherwise, we treated insertions and deletions as ‘SV indels’ because a deletion in one individual is synonymous to an insertion in the other.

Illumina
Human1M DNA Analysis BeadChip.
CNV Regions
• Covers unstable portions of the genome such as segmental duplications, megasatellites, SNP deserts, and the MHC region
• 206,665 markers in CNV regions identified in the Database of Genomic Variants (DGV)
• 3,298 DGV regions covered with an average of 62.6 markers per region
• Targets numerous novel, non-overlapping CNV regions not found in the DGV
• Industry-leading SNP uniformity with the fewest large gaps
Illumina offers solutions for paired (matched) sample analysis, where a normal/tumor pair can be run side-by-side on the same array using the HumanHap300-Duo, HumanCNV370-Duo, Human450S-Duo, and HumanHap550-Duo. All of these BeadChips target a high percentage of commonly reported copy number variants while at the same time allowing the discovery of novel CNVs.
illumina's cnv analysis products
Human1M BeadChip
HumanHap650Y BeadChip
Human610 BeadChip
HumanHap550-Duo BeadChip
HumanHap550 BeadChip
Human450S-Duo BeadChip
HumanCNV370-Duo BeadChip
HumanHap300-Duo BeadChip

reference papers about CNV study[listed by Illumina]
Brunetti-Pierri N, Grange D, Ou Z, Peiffer D, Peacock S, et al. (2007) Characterization of de novo microdeletions involving 17q11.2q12 identified through chromosomal comparative genomic hybridization. 72(5): 411-419.

Wood LD, Parsons DW, Jones S, Lin J, Sjoblom T, et al. (2007) The Genomic Landscapes of Human Breast and Colorectal Cancers..

Wang K, Li M, Hadley D, Liu R, Glessner J, et al. (2007) PennCNV: An integrated hidden Markov model designed for high-resolution copy number variation detection in whole-genome SNP genotyping data..

Poot M, Eleveld MJ, van 't Slot R, van Genderen MM, Verrijn Stuart AA, et al. (2007) Proportional growth failure and oculocutaneous albinism in a girl with a 6.87 Mb deletion of region 15q26.2-->qter..

Jackson EM, Shaikh TH, Zhang F, Wainwright LM, Storm PB, et al. (2007) Atypical teratoid/rhabdoid tumor in a patient with Beckwith-Wiedemann syndrome. Am J Med Genet A 143(15): 1767-1770.

Ting JC, Roberson ED, Miller ND, Lysholm-Bernacchi A, Stephan DA, et al. (2007) Visualization of uniparental inheritance, Mendelian inconsistencies, deletions, and parent of origin effects in single nucleotide polymorphism trio data with SNPtrio. Hum Mutat Jul 27: [Epub ahead of print].

van de Leemput J, Chandran J, Knight MA, Holtzclaw LA, Scholz S, et al. (2007) Deletion at ITPR1 Underlies Ataxia in Mice and Spinocerebellar Ataxia 15 in Humans. 3(6): e108.

Lennon PA, Cooper ML, Peiffer DA, Gunderson KL, Patel A, et al. (2007) Deletion of 7q31.1 supports involvement of FOXP2 in language impairment: clinical report and review. Am J Med Genet A 143(8): 791-798.

Stark M, Hayward N (2007) Genome-wide loss of heterozygosity and copy number analysis in melanoma using high-density single-nucleotide polymorphism arrays. Cancer research 67(6): 2632-2642.

Oosting J, Lips EH, van Eijk R, Eilers PH, Szuhai K, et al. (2007) High-resolution copy number analysis of paraffin-embedded archival tissue using SNP BeadArrays. Genome research 17(3): 368-376.

Peiffer DA, Gunderson KL (2007) Analyzing copy number variation with Infinium whole-genome genotyping. Bio-IT March.

Simon-Sanchez J, Scholz S, Fung HC, Matarin M, Hernandez D, et al. (2007) Genome-wide SNP assay reveals structural genomic variation, extended homozygosity and cell-line induced alterations in normal individuals. Hum Mol Genet 16(1): 1-14.

Colella S, Yau C, Taylor JM, Mirza G, Butler H, et al. (2007) QuantiSNP: an Objective Bayes Hidden-Markov Model to detect and accurately map copy number variation using SNP genotyping data. Nucleic Acids Res 35(6): 2013-2025.

Peiffer DA, Gunderson KL (2006) LOH and DNA copy number changes. Genetic Engineering News Sept. 15.

Peiffer DA, Le JM, Steemers FJ, Chang W, Jenniges T, et al. (2006) High-resolution genomic profiling of chromosomal aberrations using Infinium whole-genome genotyping. Genome research 16(9): 1136-1148.

Gunderson KL, Peiffer DA (2006) SNP-CGH technologies for genomic profiling of LOH and copy number. Clinical Laboratory International May.

Comparison of different techniques for the genome-wide detection of structural rearrangements
-- Andrew J. Sharp, Ze Cheng, and Evan E. Eichler
“Structural Variation of the Human Genome”
Reference:
1.deVries BB, Pfundt R, Leisink M, Koolen DA,Vissers LE, et al. 2005. Diagnostic genome profiling in mental retardation. Am. J. Hum. Genet. 77:606–16

2.Iafrate AJ, Feuk L, Rivera MN, Listewnik ML, Donahoe PK, et al. 2004. Detection of large-scale variation in the human genome. Nat. Genet. 36:949–51

3.Pinkel D, Segraves R, Sudar D, Clark S, Poole I, et al. 1998. High resolution analysis of DNA copy number variation using comparative genomic hybridization to microarrays. Nat. Genet. 20:207–11

4.Sharp AJ, Locke DP, McGrath SD, Cheng Z, Bailey JA, et al. 2005. Segmental duplications and copy number variation in the human genome. Am. J. Hum. Genet. 77:78–88

5.Dhami P, Coffey AJ, Abbs S, Vermeesch JR, Dumanski JP, et al. 2005. Exon array CGH: detection of copy-number changes at the resolution of individual exons in the human genome. Am. J. Hum. Genet. 76:750–62

6.Lucito R, West J, Reiner A, Alexander J, Esposito D, et al. 2000. Detecting gene copy number fluctuations in tumor cells by microarray analysis of genomic representations. Genome Res. 10:1726–36

7.Mantripragada KK, Buckley PG, Jarbo C, Menzel U, Dumanski JP. 2003. Development of NF2 gene specific, strictly sequence defined diagnostic microarray for deletion detection. J. Mol. Med. 81:443–51

8.Sebat J, Lakshmi B, Troge J, Alexander J, Young J, et al. 2004. Large-scale copy number polymorphism in the human genome. Science 305:525–28

9.Bruce S, Leinonen R, Lindgren CM, Kivinen K, Dahlman-Wright K, et al. 2005. Global analysis of uniparental disomy using high density genotyping arrays. J. Med. Genet.
42:847–51

10.Hinds DA, Kloek AP, Jen M, Chen X, Frazer KA. 2006. Common deletions and SNPs are in linkage disequilibrium in the human genome. Nat. Genet. 38:82–85

11.Rauch A, Ruschendorf F, Huang J, Trautmann U, Becker C, et al. 2004. Molecular karyotyping using an SNP array for genomewide genotyping. J. Med. Genet. 41:916–22

12.Newman TL, Tuzun E, Morrison VA, Hayden KE, Ventura M, et al. 2005. A genomewide survey of structural variation between human and chimpanzee. Genome Res. 15:1344–
56

13.Tuzun E, Sharp AJ, Bailey JA, Kaul R, Morrison VA, et al. 2005. Fine-scale structural variation of the human genome. Nat. Genet. 37:727–32

14.Conrad DF, Andrews TD, Carter NP, Hurles ME, Pritchard JK. 2006. A high-resolution
survey of deletion polymorphism in the human genome. Nat. Genet. 38:75–78

15.McCarroll SA, Hadnott TN, Perry GH, Sabeti PC, Zody MC, et al. 2006. Common deletion polymorphisms in the human genome. Nat. Genet. 38:86–92

16.Feuk L, MacDonald JR,Tang T, Carson AR, Li M, et al. 2005. Discovery of human inversion
polymorphisms by comparative analysis of human and chimpanzee DNA sequence assemblies. PLoS Genet. 1:e56
BENM is offline   Reply With Quote
Old 09-13-2009, 05:23 PM   #26
Patrick
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Location: Malaysia

Join Date: Mar 2009
Posts: 27
Default

Hi BENM,

Thanks for your suggestion. The knowledge is very useful for my research in future.
Do you got read the YH project as well?
I just read it last week and found out it is quite interesting and fantastic research.
Pity that I not very understanding about some of its main findings
Do you know what is its main findings from this research?
Thanks again

Quote:
Originally Posted by BENM View Post
I am sorry for a prompt reply, there is a list of tenology approach & reference for detecting SV here, hope it help to you.

(1)GTG-banded karyotype
The gold standard for clinical cytogenetic testing still remains the GTG-banded karyotype, where a genomewide analysis usually identifies chromosomal rearrangements or aberrations of 3–5 Mb and larger.


(2)Array-based approach (array CGH/ROMA, SNP oligonucleotide microarray)
*ROMA, representational oligonucleotide microarray analysis

2004 Two initail studies using CGH technology:
used a bacterial artificial chromosome (BAC)-based array, with clones chosen at 1-megabase (Mb) intervals throughout the human genome, together with a technique called array-based comparative genomic hybridization (array CGH);

Comparative genomic hybridization (CGH) is a molecular-cytogenetic method for the analysis of copy number changes (gains /losses) in the DNA content of tumor cells. The method is based on the hybridization of fluorescently labeled tumor DNA (frequently Fluorescein - FITC) and normal DNA (frequently Rhodamine or Texas Red) to normal human metaphase preparations. Using epifluorescence microscopy and quantitative image analysis, regional differences in the fluorescence ratio of tumor vs. control DNA can be detected and used for identifying abnormal regions in the tumor cell genome. CGH will detect only unbalanced chromosomes changes. Structural chromosome aberrations such as balanced reciprocal translocations or inversions can not be detected, as they do not change the copy number.

2004

1/.Iafrate AJ, Feuk L, Rivera MN, Listewnik ML, Donahoe PK, Qi Y, Scherer SW, Lee C. Detection of large-scale variation in the human genome. Nat Genet. 2004 Sep;36(9):949-51.
Iafrate BAC microarray analysis
All hybridizations were performed in duplicate incorporating a dye-reversal using proprietary 1 Mb GenomeChip V1.2 Human BAC Arrays consisting of 2,632 BAC clones (Spectral Genomics, Houston, TX). The false positive rate was estimated at ~1 clone per 5,264 tested.
Further information is available from the Database of Genomic Variants website.


2/.Sebat J, Lakshmi B, Troge J, Alexander J, Young J, Lundin P, Maner S, Massa H, Walker M, Chi M et al. Large-scale copy number polymorphism in the human genome. Science. 2004 July 23;305(5683):525-8.
Sebat ROMA
Following digestion with BglII or HindIII, genomic DNA was hybridized to a custom array consisting of 85,000 oligonucleotide probes. The probes were selected to be free of common repeats and have unique homology within the human genome. The average resolution of the array was ~35kb; however, only intervals in which three consecutive probes showed concordant signals were scored as CNPs. All hybridizations were performed in duplicate incorporating a dye-reversal, with the false positive rate estimated to be ~6%.

2005

1/.Sharp AJ, Locke DP, McGrath SD, Cheng Z, Bailey JA, et al. 2005. Segmental duplications and copy number variation in the human genome. Am. J. Hum. Genet. 77:78–88
Sharp BAC microarray analysis
All hybridizations were performed in duplicate incorporating a dye-reversal using a custom array consisting of 2,194 end-sequence or FISH-confirmed BACs, targeted to regions of the genome flanked by segmental duplications. The false positive rate was estimated at ~3 clones per 4,000 tested.
2/.deVries BB, Pfundt R, Leisink M, Koolen DA,Vissers LE, et al. 2005. Diagnostic genome profiling in mental retardation. Am. J. Hum. Genet. 77:606–16

3/.Bruce S, Leinonen R, Lindgren CM, Kivinen K, Dahlman-Wright K, et al. 2005. Global
analysis of uniparental disomy using high density genotyping arrays. J. Med. Genet.
42:847–51

2006
1/.Locke analysis of duplication-rich regions
DNA samples were obtained from Coriell Cell Repositories. The reference DNA used for all hybridizations was from a single male of Czechoslovakian descent, Coriell ID GM15724 (also used in the Sharp study).
A locus was considered a CNV (copy number variation) if the log ratio of fluroescence measurements for the individuals assayed exceeded twice the standard deviation of the autosomal clones in replicate dye-swapped experiments. A CNV was classified as a CNP if altered copy number was observed in more than 1% of the 269 individuals.
Locke DP, Sharp AJ, McCarroll SA, McGrath SD, Newman TL, Cheng Z, Schwartz S, Albertson DG, Pinkel D, Altshuler DM et al. Linkage disequilibrium and heritability of copy-number polymorphisms within duplicated regions of the human genome. Am J Hum Genet. 2006 Aug;79(2):275-90.
Locke duplication-rich regions
The authors performed validation using a custom oligonucleotide array, hybridized to 9 of the HapMap individuals. Their analysis of the validation experiments indicated a false-negative rate of 5% and a false-positive rate of less than 0.2%.

2./Redon R, Ishikawa S, Fitch KR, Feuk L, Perry GH, Andrews TD, Fiegler H, Shapero MH, Carson AR, Chen W et al. Global variation in copy number in the human genome. Nature. 2006 Nov 23;444(7118):444-454.
The authors utilized numerous quality meaures, including repeated experiments on the WGTP array for 82 individuals and on the 500K EA array for 15 individuals. The average false-positive rate per experiment was held beneath 5%. Aberrant chromosomes were removed from the analysis.
Redon analysis of HapMap data
Experiments were performed with the International HapMap DNA and cell-line collection using two technologies: comparative analysis of hybridization intensities on Affymetric GeneChip Human Mapping 500K early access arrays (500K EA) and comparative genomic hybridization with a Whole Genome TilePath (WGTP) array.
Sanger-Two platforms for CNV detection
WGTP
500k EA
1447 copy number variable regions in the HapMap populations covering ~12% of the human genome (~360 Mb)

(3) Sequence-based approaches(Paired-End Mapping, SNP genotype, comparative sequence analysis)

2005

1/.Tuzun E, Sharp AJ, Bailey JA, Kaul R, Morrison VA, Pertz LM, Haugen E, Hayden H, Albertson D, Pinkel D et al. Fine-scale structural variation of the human genome. Nat Genet. 2005 Jul;37(7):727-32.
Tuzun fosmid mapping
Paired-end sequences from a human fosmid DNA library were mapped to the assembly. The average resolution of this technique was ~8kb, and included 56 sites of inversion not detectable by the array-based approaches. However, because of the physical constraints of fosmid insert size, this technique was unable to detect insertions greater than 40 kb in size
The authors systematically compared the human genome reference sequence to a second genome (represented by fosmid paired-end sequences) to detect intermediate-sized structural variants (ISV) > 8 kb in length. They identified 297 sites of structural variation, corresponding to 139 insertions, 102 deletions and 56 inversion breakpoints. Based on our combined literature, sequence and experimental analyses we provide validation for 112 of the structural variants including several of biomedical relevance. These data provide the first fine-scale structural variation map of the human genome and provide the requisite sequence precision for subsequent population and association studies with human disease.

2/.Feuk L, MacDonald JR,Tang T, Carson AR, Li M, et al. 2005. Discovery of human inversionpolymorphisms by comparative analysis of human and chimpanzee DNA sequence assemblies. PLoS Genet. 1:e56


2006
1./Conrad genotype analysis
The authors first tested 12 predicted deletions using quantitative PCR. For all 12 deletions, DNA concentrations consistent with transmission of a deletion from parent to child were observed.
To provide more extensive validation by comparative genome hybridization (CGH), the authors designed a custom oligonucleotide microarray comprised of 380,000 probes that tile across all 134 candidate deletions identified in 9 HapMap offspring (8 YRI and 1 CEU). The results of this CGH analysis indicate that the majority (about 85%) of candidate deletions detected by the method are real.
Conrad DF, Andrews TD, Carter NP, Hurles ME, Pritchard JK.A high-resolution survey of deletion polymorphism in the human genome Nat Genet. 2006 Jan;38(1):75-81.
Conrad genotype analysis (deletion polymorphism)
SNPs in regions that are hemizygous for a deletion are generally miscalled as homozygous for the allele that is present. Hence, when a deletion is transmitted from parent to child, the genotypes at SNPs within the deletion region will often appear to violate the rules of Mendelian transmission. The authors developed a simple algorithm for scanning trio data for unusual runs of consecutive SNPs that, in a single family, have genotype configurations consistent with the presence of a deletion.

2/.McCarroll genotype analysis
McCarroll SA, Hadnott TN, Perry GH, Sabeti PC, Zody MC, Barrett JC, Dallaire S, Gabriel SB, Lee C, Daly MJ et al. Common deletion polymorphisms in the human genome. Nat Genet. 2006 Jan;38(1):86-92.
A segregating deletion can leave "footprints" in SNP genotype data, including apparent deviations from Mendelian inheritance, apparent deviations from Hardy-Weinberg equilibrium and null genotypes. Using these clues to discover true variants is challenging, however, because the vast majority of such observations represent technical artifacts and genotyping errors.
To determine whether a subset of "failed" SNP genotyping assays in the HapMap data might reflect structural variation, the authors examined whether such failures were physically clustered in a manner that is specific to individuals. Consistent with this hypothesis, the rate of Mendelian-inconsistent genotypes was elevated near other Mendelian-inconsistent genotypes in the same individual but was unrelated to Mendelian inconsistencies in other individuals.
The authors systematically looked for regions of the genome in which the same failure profile appeared repeatedly at nearby markers in a manner that was statistically unexpected based on chance. A set of statistical thresholds was tailored to each mode of failure, genotyping center and genotyping platform used in the project. The same procedure could readily apply to dense SNP data from any platform or study.
Four methods of validation were used: fluorescent in situ hybridization (FISH), two-color fluorescence intensity measurements, PCR amplification and quantitative PCR.
The authors performed fluorescent in situ hybridization for five candidate deletions large enough to span available FISH probes. In all five cases, FISH assays confirmed the deletions in the predicted individuals.
The authors examined two-color allele-specific fluorescence data from SNP genotyping assays from a data subset available at the Broad Institute, looking for a reduction in fluorescence intensity in individuals predicted to carry a deletion. At most SNPs in the genome, fluorescence intensity measurements clustered into two or three discrete groups corresponding to homozygous and hetrozygous genotypes. At 15 of 17 candidate deletion loci, fluorescence intensity data for one or more SNPs clustered into additional groups that corresponded to the predicted deletion genotypes.
The authors used PCR amplification to query 60 loci for which the pattern of genotypes suggested multiple individuals with homozygous deletions. Variants were considered confirmed if the pattern of amplification success and failure matched prediction across a set of 12-24 individuals. The authors confirmed 51 of 60 candidate variants by this criterion.
The authors performed quantitative PCR in all 269 HapMap DNA samples for 11 candidate deletions that overlapped the coding exons of genes and that were discovered in many individuals. At 10/11 loci, the authors observed three discrete clusters, identifying individuals with zero, one and two gene copies. All 60 trios displayed Mendelian inheritance for the ten deletions, as well as Hardy-Weinberg equilibrium in all four populations surveyed, and transmission rates close to 50%. This suggests that the deletions behave as a stable, heritable genetic polymorphism.

2007

High-throughput Paired-End Sequencing like 454, solexa, and SOLiD. Paired-End Mapping to the reference genome to find structural variation.
Korbel et al., Paired-End Mapping Reveals Extensive Structural Variation in the Human Genome Science, 27 September 2007 (10.1126/science.1149504).
Structural rearrangements were identified as significant differences between the fragments identified by the paired-end reads and the corresponding regions of the reference sequence.
Strategies:
Five different signatures(i-v)were used to predict SVs.
(i)Deletions relative to the reference genome were identified by paired-ends spanning a genomic region in the reference genome longer than a specified cutoff;
(ii)Simple insertions relative to the reference genome werepredicted with paired-ends that spanned a region shorter than a cutoff;
(iii)Mated insertions contained sequences connected to a distal locus on the basis of their paired-ends;
(iv)Inversions were detected through a relative orientation different from the reference genome;
(v)Unmated insertions contained sequences connected to a distal locus; one of the two expected breakpoints remained undetected. Unless stated otherwise, we treated insertions and deletions as ‘SV indels’ because a deletion in one individual is synonymous to an insertion in the other.

Illumina
Human1M DNA Analysis BeadChip.
CNV Regions
• Covers unstable portions of the genome such as segmental duplications, megasatellites, SNP deserts, and the MHC region
• 206,665 markers in CNV regions identified in the Database of Genomic Variants (DGV)
• 3,298 DGV regions covered with an average of 62.6 markers per region
• Targets numerous novel, non-overlapping CNV regions not found in the DGV
• Industry-leading SNP uniformity with the fewest large gaps
Illumina offers solutions for paired (matched) sample analysis, where a normal/tumor pair can be run side-by-side on the same array using the HumanHap300-Duo, HumanCNV370-Duo, Human450S-Duo, and HumanHap550-Duo. All of these BeadChips target a high percentage of commonly reported copy number variants while at the same time allowing the discovery of novel CNVs.
illumina's cnv analysis products
Human1M BeadChip
HumanHap650Y BeadChip
Human610 BeadChip
HumanHap550-Duo BeadChip
HumanHap550 BeadChip
Human450S-Duo BeadChip
HumanCNV370-Duo BeadChip
HumanHap300-Duo BeadChip

reference papers about CNV study[listed by Illumina]
Brunetti-Pierri N, Grange D, Ou Z, Peiffer D, Peacock S, et al. (2007) Characterization of de novo microdeletions involving 17q11.2q12 identified through chromosomal comparative genomic hybridization. 72(5): 411-419.

Wood LD, Parsons DW, Jones S, Lin J, Sjoblom T, et al. (2007) The Genomic Landscapes of Human Breast and Colorectal Cancers..

Wang K, Li M, Hadley D, Liu R, Glessner J, et al. (2007) PennCNV: An integrated hidden Markov model designed for high-resolution copy number variation detection in whole-genome SNP genotyping data..

Poot M, Eleveld MJ, van 't Slot R, van Genderen MM, Verrijn Stuart AA, et al. (2007) Proportional growth failure and oculocutaneous albinism in a girl with a 6.87 Mb deletion of region 15q26.2-->qter..

Jackson EM, Shaikh TH, Zhang F, Wainwright LM, Storm PB, et al. (2007) Atypical teratoid/rhabdoid tumor in a patient with Beckwith-Wiedemann syndrome. Am J Med Genet A 143(15): 1767-1770.

Ting JC, Roberson ED, Miller ND, Lysholm-Bernacchi A, Stephan DA, et al. (2007) Visualization of uniparental inheritance, Mendelian inconsistencies, deletions, and parent of origin effects in single nucleotide polymorphism trio data with SNPtrio. Hum Mutat Jul 27: [Epub ahead of print].

van de Leemput J, Chandran J, Knight MA, Holtzclaw LA, Scholz S, et al. (2007) Deletion at ITPR1 Underlies Ataxia in Mice and Spinocerebellar Ataxia 15 in Humans. 3(6): e108.

Lennon PA, Cooper ML, Peiffer DA, Gunderson KL, Patel A, et al. (2007) Deletion of 7q31.1 supports involvement of FOXP2 in language impairment: clinical report and review. Am J Med Genet A 143(8): 791-798.

Stark M, Hayward N (2007) Genome-wide loss of heterozygosity and copy number analysis in melanoma using high-density single-nucleotide polymorphism arrays. Cancer research 67(6): 2632-2642.

Oosting J, Lips EH, van Eijk R, Eilers PH, Szuhai K, et al. (2007) High-resolution copy number analysis of paraffin-embedded archival tissue using SNP BeadArrays. Genome research 17(3): 368-376.

Peiffer DA, Gunderson KL (2007) Analyzing copy number variation with Infinium whole-genome genotyping. Bio-IT March.

Simon-Sanchez J, Scholz S, Fung HC, Matarin M, Hernandez D, et al. (2007) Genome-wide SNP assay reveals structural genomic variation, extended homozygosity and cell-line induced alterations in normal individuals. Hum Mol Genet 16(1): 1-14.

Colella S, Yau C, Taylor JM, Mirza G, Butler H, et al. (2007) QuantiSNP: an Objective Bayes Hidden-Markov Model to detect and accurately map copy number variation using SNP genotyping data. Nucleic Acids Res 35(6): 2013-2025.

Peiffer DA, Gunderson KL (2006) LOH and DNA copy number changes. Genetic Engineering News Sept. 15.

Peiffer DA, Le JM, Steemers FJ, Chang W, Jenniges T, et al. (2006) High-resolution genomic profiling of chromosomal aberrations using Infinium whole-genome genotyping. Genome research 16(9): 1136-1148.

Gunderson KL, Peiffer DA (2006) SNP-CGH technologies for genomic profiling of LOH and copy number. Clinical Laboratory International May.

Comparison of different techniques for the genome-wide detection of structural rearrangements
-- Andrew J. Sharp, Ze Cheng, and Evan E. Eichler
“Structural Variation of the Human Genome”
Reference:
1.deVries BB, Pfundt R, Leisink M, Koolen DA,Vissers LE, et al. 2005. Diagnostic genome profiling in mental retardation. Am. J. Hum. Genet. 77:606–16

2.Iafrate AJ, Feuk L, Rivera MN, Listewnik ML, Donahoe PK, et al. 2004. Detection of large-scale variation in the human genome. Nat. Genet. 36:949–51

3.Pinkel D, Segraves R, Sudar D, Clark S, Poole I, et al. 1998. High resolution analysis of DNA copy number variation using comparative genomic hybridization to microarrays. Nat. Genet. 20:207–11

4.Sharp AJ, Locke DP, McGrath SD, Cheng Z, Bailey JA, et al. 2005. Segmental duplications and copy number variation in the human genome. Am. J. Hum. Genet. 77:78–88

5.Dhami P, Coffey AJ, Abbs S, Vermeesch JR, Dumanski JP, et al. 2005. Exon array CGH: detection of copy-number changes at the resolution of individual exons in the human genome. Am. J. Hum. Genet. 76:750–62

6.Lucito R, West J, Reiner A, Alexander J, Esposito D, et al. 2000. Detecting gene copy number fluctuations in tumor cells by microarray analysis of genomic representations. Genome Res. 10:1726–36

7.Mantripragada KK, Buckley PG, Jarbo C, Menzel U, Dumanski JP. 2003. Development of NF2 gene specific, strictly sequence defined diagnostic microarray for deletion detection. J. Mol. Med. 81:443–51

8.Sebat J, Lakshmi B, Troge J, Alexander J, Young J, et al. 2004. Large-scale copy number polymorphism in the human genome. Science 305:525–28

9.Bruce S, Leinonen R, Lindgren CM, Kivinen K, Dahlman-Wright K, et al. 2005. Global analysis of uniparental disomy using high density genotyping arrays. J. Med. Genet.
42:847–51

10.Hinds DA, Kloek AP, Jen M, Chen X, Frazer KA. 2006. Common deletions and SNPs are in linkage disequilibrium in the human genome. Nat. Genet. 38:82–85

11.Rauch A, Ruschendorf F, Huang J, Trautmann U, Becker C, et al. 2004. Molecular karyotyping using an SNP array for genomewide genotyping. J. Med. Genet. 41:916–22

12.Newman TL, Tuzun E, Morrison VA, Hayden KE, Ventura M, et al. 2005. A genomewide survey of structural variation between human and chimpanzee. Genome Res. 15:1344–
56

13.Tuzun E, Sharp AJ, Bailey JA, Kaul R, Morrison VA, et al. 2005. Fine-scale structural variation of the human genome. Nat. Genet. 37:727–32

14.Conrad DF, Andrews TD, Carter NP, Hurles ME, Pritchard JK. 2006. A high-resolution
survey of deletion polymorphism in the human genome. Nat. Genet. 38:75–78

15.McCarroll SA, Hadnott TN, Perry GH, Sabeti PC, Zody MC, et al. 2006. Common deletion polymorphisms in the human genome. Nat. Genet. 38:86–92

16.Feuk L, MacDonald JR,Tang T, Carson AR, Li M, et al. 2005. Discovery of human inversion
polymorphisms by comparative analysis of human and chimpanzee DNA sequence assemblies. PLoS Genet. 1:e56
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Old 09-14-2009, 12:59 AM   #27
BENM
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Originally Posted by Patrick View Post
Hi BENM,

Thanks for your suggestion. The knowledge is very useful for my research in future.
Do you got read the YH project as well?
I just read it last week and found out it is quite interesting and fantastic research.
Pity that I not very understanding about some of its main findings
Do you know what is its main findings from this research?
Thanks again
Hi Patrick,

You're welcome.
In fact I am one of the co-authors of this paper, thereinto the SV detetion of this project is my main job. But I am not in BGI now.
About the main finding from the first of individual deploid genome of Asian, I don't know in which fields you be interested. But accoding to YH genome project SNPs detetion we proved that NCBI v36 had a lot of alleles that never presented in CEU populations. And I also found YH had a specific SV regions compared to NCBI v36, it turned up on each genome of YH-99 which had been sequenced and analyzed.
About YH projects, you can seek for more details from http://yh.genomics.org.cn/.

Last edited by BENM; 09-14-2009 at 01:03 AM.
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