large-scale copy number polymorphism in the human genome j. sebat et al. science, 305 :525
DESCRIPTION
Large-Scale Copy Number Polymorphism in the Human Genome J. Sebat et al. Science, 305 :525. Luana Á vila MedG 505 Feb. 24 th 2005. 1/2 4. Outline. Background Method Results Discussion Future applications. 2/ 24. Background. Common genetic variation. - PowerPoint PPT PresentationTRANSCRIPT
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Large-Scale Copy Number Polymorphism in the Human
GenomeJ. Sebat et al. Science, 305:525
Luana ÁvilaMedG 505
Feb. 24th 2005
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Outline
• Background• Method• Results• Discussion• Future applications
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Common genetic variation
Differences between people are given by genetic variations that can exist in a few forms:
1.Allelic differences
2.Single nucleotide differences – SNPs
3.Copy number differences - CNPs
Background
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Copy Number Polymorphism
“A normal variation in DNA due to variation in the number of copies of a sequence within the DNA. Large-scale copy number polymorphisms are common and widely distributed in the human genome.” http://www.medterms.com/script/main/art.asp?articlekey=34373
Background
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(CNP)
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How do different copy numbers arise?
Gene duplication- gene conversion events
- mRNA reverse transcript insertionGenome duplication
- cell cleavage error in mitosis
- polyspermy- non-disjunction and non-reduction
Background
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responsible for many of the genetic differences between humans and other primates
Background
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Rearrangements can drive evolution but can also alter cell function:
dosage dependent gene regulation concentration imbalance of protein
subunits chromosome instability
Large-scale rearrangements
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Large-scale rearrangements
Large-scale copy number differences are found in cancer due to genomic instability
Used ROMA to detect differences between normal and cancer tissues:- found CNPs in cancer cells
expected due to genomic instability (Lucito et al.)
Background
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Large-scale rearrangements
- test ‘normal to normal’ control comparisons
Found: CNPs are present in normal samples
(Sebat et al.)
Background
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Frequently detected large (100 kb to 1
Mb) chromosomal deletions and
duplications in normal DNA samples
Therefore, to correctly interpret data
need to to be able to distinguish normal
CNPs from abnormal genetic lesions
Used ROMA to find normal CNPs in
Human Genome
Large-scale rearrangements
Background
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Using ROMA
ROMA = Representational Oligonucleotide Microarray Analysis
It is an array-based comparative genomic hybridization
Genomic DNA is digested with restriction enzyme
Bgl II, Hind III
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Method
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Bgl II fragments (200–1200 bp) are ligated with PCR adapters – amplify genomic representational fragments
Probes are designed in silico from the Human genome project
Use microarray to compare hybridization from unrelated individuals
Further analysis with hidden Markov Model
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Method
Using ROMA
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C N
Identify New Cancer Genes
http://www.cshl.edu/public/releases/revealing.html
Profiling Genetics of Cancer using ROMA
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ROMA features:
Reduces complexity of the genome
Detect loss of a single allele
Resolution of 1 probe every 35kb of the genome
Lower signal to background ratio
Probes have fewer repetitive sequences in DNA sampled
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Method
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How did they do it?
Whole blood, lymphoblastoids and sperm samples from 20 people and extracted genomic DNA from each tissue sample
Germline CNP
Somatic CNP
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Method
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Pro
be r
atio
Genome Order
Detection of germline CNP 15/24
Results
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Detection of Somatic difference 16/24
Results
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Verification of Results by FISH
ROMA FISH17/24
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What did they find?Identified 221 germline CNPs in 20 people
76 non-overlapping CNPs (71 Bgl II + 5 Hind III)
Cover 44 Mb of genome
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Results
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Average CNP length = 465 kb
Average of 11 CNPs between 2 people
5 CNPs had been described before – Identified 71 novel CNPs
Some CNPs previously reported by McLean (1997) and Townson(2002) were not detected in this study
Estimate that any given experiment may miss up to 30% of CNPs (calculated false negative rate = 33%)
What did they find?Results
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What did they find?
Results
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Discussion
What is the relevance of it all? Large-scale CNPs were found
throughout the human genome – in all chromosomes but 18, 20, X and Y
- Some CNPs occur in clusters: Hotspots?
CNPs may reflect the genomic regions of instability.
Considerable genome structural variation among humans – responsible for genetic diversity? 21/2
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How many of such polymorphisms are commonly present in the population?
Can such variations or "copy number polymorphisms" among individuals underlie many human traits, including heritable predisposition or resistance to disease?
Questions:
Which genes/ chromosomal regions are more frequently affected?
Discussion
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Genes content of CNPs
48 COH1 Cohen syndrome 1 8q22 Autosomal recessive disorder
56 PPYR1 Pancreatic polypep. recep.
10q11.2 Regulate food intake
15 RAB6C RAS oncogene family
2q14 Leukemia + drug res. in Br. Cancer
70 CHRFAM7A Cholinergic recep. 15q13
Genes involved in neuro-
development
82 NCAM2 Neural cell adhesion mol 2
21q21
22 ATOH1 Atonal homolog (drosophila)
4q22
29 GTF2H2 Transcription factor II
5q13
CNP Gene symbol Gene name Location Function
Discussion
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Future Applications:
Further development of ROMA
Increase sample size and type – more subjects and different tissues
Investigate selective pressure on CNPs
- mechanism?
-compare rate of synonymous vs. non-synonymous substitutions
Use ROMA in cytogenetic diagnosis? (Jobanputra et al., Feb 2005)
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