1. Large-Scale Copy Number Polymorphism in the Human Genome J. Sebat et al. Science, 305:525 Luana Ávila MedG 505 Feb. 24 th 2005 1/24

2. Outline Background Method Results Discussion Future applications 2/24

3. 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 3/24

4. 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 4/24 (CNP)

5. How do different copy numbers arise?  Gene duplication - gene conversion events - mRNA reverse transcript insertion  Genome duplication - cell cleavage error in mitosis - polyspermy - non-disjunction and non-reduction Background 5/24

6.  responsible for many of the genetic differences between humans and other primates Background 6/24 Rearrangements can drive evolution but can also alter cell function:  dosage dependent gene regulation  concentration imbalance of protein subunits  chromosome instability Large-scale rearrangements

7. 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 7/24

8. Large-scale rearrangements - test ‘normal to normal’ control comparisons Found: CNPs are present in normal samples (Sebat et al.) Background 8/24

9.  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 9/24

10. 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 10/24 Method

11.  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 11/24 Method Using ROMA

12. 12/24 CN Identify New Cancer Genes http://www.cshl.edu/public/releases/revealing.html Profiling Genetics of Cancer using ROMA

13. 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 13/24 Method

14. 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 14/24 Method

15. Probe ratio Genome Order Detection of germline CNP 15/24 Results

16. Detection of Somatic difference 16/24 Results

17. Verification of Results by FISH ROMAFISH 17/24

18. 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 14/25 Results

19.  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 19/24

20. What did they find? Results 20/24

21. 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? 21/24

22.  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 22/24

23. Genes content of CNPs 48COH1 Cohen syndrome 1 8q22 Autosomal recessive disorder 56PPYR1 Pancreatic polypep. recep. 10q11.2 Regulate food intake 15RAB6C RAS oncogene family 2q14 Leukemia + drug res. in Br. Cancer 70CHRFAM7A Cholinergic recep. 15q13 Genes involved in neuro- development 82NCAM2 Neural cell adhesion mol 2 21q21 22ATOH1 Atonal homolog (drosophila) 4q22 29GTF2H2 Transcription factor II 5q13 CNP Gene symbolGene nameLocationFunction Discussion

24. 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) 24/24