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)

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

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

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

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

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

Pro

be r

atio

Genome Order

Detection of germline CNP 15/24

Results

Detection of Somatic difference 16/24

Results

Verification of Results by FISH

ROMA FISH17/24

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

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

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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