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Array CGH for Constitutional Disorders: From Diagnosis to Gene Discovery

This article discusses the use of array comparative genomic hybridization (array CGH) in the diagnosis and gene discovery of patients with congenital and acquired disorders. It covers the process of data processing, prioritization of candidate genes, and experimental validation. The article also highlights the importance of array CGH in improving diagnosis and discovering new disease-causing genes.

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Array CGH for Constitutional Disorders: From Diagnosis to Gene Discovery

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  1. Array CGH for constitutional disorders: from diagnosis to disease gene discovery Computational Systems Biology

  2. CGH microarraysMolecular karyotyping Location of chromosomal imbalances Statistical analysis Databasing Validation Prioritized candidate genes • Map chromosomal abnormalities • Improved diagnosis Discover new disease causing genes and explain their function Array CGH: from diagnosis to gene discovery Patients with congenital & acquired disorders

  3. Part I: Array Comparative Genomic Hybridization (array CGH)

  4. Array CGH Child with e.g. heart defect and learning disabilities Sample is collected and sent to genetic center

  5. Cytogenetic diagnostic • 2-3% of live birth with major congenital anomaly • 15-25% recognized genetic causes • 8-12% environmental factors • 20-25% multifactorial • 40-60% unknown • 15-20% of those resolved by array CGH • Importance of diagnosis • Usually limited therapeutic impact BUT • Reduce family distress • End of “diagnostic odyssey” • Estimate risk of recurrence • De novo aberration vs. familial mutation • Knowledge of disorder evolution (life planning) • Prevent complications • Future therapies (e.g., fragile-X, Rett + gene therapy)

  6. Deletion del(22)(q12.2) • Patient • Pulmonary valve stenosis • Cleft uvula • Mild dysmorphism • Mild learning difficulties • High myopia

  7. Deletion del(22)(q12.2) • Deletion on Chromosome 22 • ~0.8Mb • Deletion contains NF2 • NF2  acoustic neurinomas • Benign tumor, BUT • Hard to diagnose • Severe complications

  8. The challenge: identifying recurrent imbalances and disease genes

  9. The imbalances are scattered across the genome

  10. Genotype-phenotype correlation

  11. Array CGH: from diagnosis to gene discovery • Processing of array CGH data • Databasing and mining of patient descriptions • Genotype-phenotype correlation • Candidate gene prioritization • Experimental validation of candidate genes

  12. Part II: Candidate gene prioritization

  13. Information sources • Identify key genes and their function • Integration of multiple types of information Candidate prioritization Validation Candidate gene prioritization High-throughputgenomics Data analysis Candidate genes ?

  14. Prioritization by text mining ENSG00000000001 ENSG00000000002 ... ENSG00000109685 ... ENSG00000024999 ENSG00000025000 Microcephaly overrepresented in document set for WHSC1 gene

  15. Prioritization by example • Several cardiac abnormalities mapped to 3p22-25 • Atrioventricular septal defect • Dilated cardiomyopathy • Brugada syndrome • Candidate genes (“test set”) • 3p22-25, 210 genes • Known genes (“training set”) • 10-15 genes: NKX2.5, GATA4, TBX5, TBX1, JAG1, THRAP, CFC1, ZFPM2, PTPN11, SEMA3E • Congenital heart defects (CHD) • High scoring genes • ACVR2, SHOX2 - linked to heterotaxy and Turner syndrome (often associated with CHD) • Plexin-A1 - reported as essential for chick cardiac morphogenesis • Wnt5A, Wnt7A – neural crest guidance

  16. Prioritization by virtual pulldown

  17. Endeavour http://www.esat.kuleuven.ac.be/endeavour Aerts et al. Nature Biotechnology. 2006.

  18. Prioritization by text mining in DECIPHER

  19. Novel DiGeorge candidate • D. Lambrechts, P. Carmeliet, KUL Cardiovascular Biol. • TBX1 critical gene in typical 3Mb aberration • Atypical 2Mb deletion (58 candidates)

  20. YPEL1 • YPEL1 is expressed in the pharyngeal arches during arch development • YPEL1KD zebrafish embryos exhibit typical DGS-like features

  21. Congenital heart disease genes • B. Thienpont, K. Devriendt, J. Vermeesch, KUL CME • 60 patients without diagnosis • Congenital heart defect • & Chromosomal phenotype • 2nd major congenital anomaly • Or mental retardation/special education • Or > 3 minor anomalies • Array Comparative Genomic Hybridization • 1 Mb resolution • 11 anomalies detected • 5 deletions • 2 duplications • 3 complex rearrangements • 1 mosaic monosomy 7

  22. Candidate regions • 4 regions with known critical genes, 6 new regions, 80 candidate genes

  23. Protein interactions Protein domains Cis-regulatory module BLAST KEGG pathways Expressiondata Gene prioritization Pubmed textmining BMP4

  24. Biological validation • Candidates currently being validated in zebrafish • Screen about 50 candidates for heart expression at different developmental stages • Morpholino knockdowns of candidates expressed in hearts • Screen for heart phenotypes

  25. CGH microarraysMolecular karyotyping Location of chromosomal imbalances Statistical analysis Databasing Validation Prioritized candidate genes • Map chromosomal abnormalities • Improved diagnosis Discover new disease causing genes and explain their function Array CGH: from diagnosis to gene discovery Patients with congenital & acquired disorders

  26. Some achievements • Publications • Aerts S et al. Gene prioritization through genomic data fusion. Nat Biotechnol. 2006 May;24(5):537-44. • Balikova I et al., Autosomal dominant microtia linked to five tandem copies of copy number variable region at Chromosome 4p16. Am J Hum Genet. 2007. in press. • Lage K et al. A human phenome-interactome network of protein complexes implicated in genetic disorders. Nat Biotechnol. 2007 Mar;25(3):309-16. • Guidelines for array CGH • Vermeesch J et al. Guidelines for molecular karyotyping in constitutional genetic diagnosis. Eur J Med Genet. 2007 Nov;15(11):1105-14. • Strategic Basic Research (SBO) project • Molecular karyotyping • K.U.Leuven, U.Gent, VUB • €2,800,000 (4 years) • Development of new applications of array CGH technology • FP7 proposal on bioinformatics for congenital heart defects • Visibility • European Cytogenetics association – molecular karyotyping workgroup • INSERM workshop array CGH (La Londe les Maures, FR, Sep 07) • Numerous keynote lectures • Contacts with all major array CGH companies

  27. Endocrinology Human genetics Modulediscovery Geneprioritization Probabilisticmodels Networkinference Salmonella sys. biology Partners involved • Yves Moreau • gene prioritization • Roland Barriot • knowledge mining • Francesca Martella • array CGH statistics • Sonia Leach • gene networks • Steven Van Vooren • text mining • Bert Coessens • - array CGH data mgt. • Leo Tranchevent • Endeavour • Yu Shi • prioritization algorithms • Daniela Nitsch • - prioritization algorithms • Peter Konings • statistical genetics CNVs • Joris Vermeesch • array CGH technology • Koen Devriendt • congenital heart defects • Hilde Van Esch • mental retardation • Thierry Voet • - array CGH technology • Femke Hannes • genotype-phenotypecorrelation • Bernard Thienpont • CHD disease genes • Jeroen Breckpot • congenital heart defects • Irina Balikova • eye defects • Liesbeth Backx • mental retardation genes • Boyan Dimitrov • skeletal disorders • An Crepel • microcephaly & autism • Caroline Robberechts • fertility • Evelyne Vanneste • - single cell array CGH CME-UZ ESAT-SCD BioStat Legendo ESAT-SCD

  28. Sangersequencing Next-gensequencing Challenges ahead • From genes to networks • The $1000 genome • Data big bang • Phenotypic genome annotation by data fusion

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