2008 Barcelona - European Society of Human Genetics

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Concurrent Sessions (a) 85% ascertained following normal karyotypes but with idiopathic mental retardation, dysmorphism and/or congenital abnormalities; (b) 15% for further characterisation of visible chromosome abnormalities including apparently balanced translocations (ABCR), complex rearrangements (CCR) and supernumerary marker chromosomes (SMC) . We have detected copy number changes (ranging in size from 88 Kb - 5 Mb) in 25% of ascertainment group (a), including a number of previously unreported de novo abnormalities . The majority of group (b) cases were found to have deletions or duplications not detected by light microscopy (ABCR and CCR), or arrays resolved their chromosomal origin and composition (SMC) . Interpretation of array-cgh results remains challenging and the increasing use and resolution of this technology suggests that it may soon replace karyotyping for some primary ascertainment groups . c04.3 the challenge of interpreting microduplications detected by arraycGH C. M. A. van Ravenswaaij-Arts, B. Leegte, T. Dijkhuizen, R. Hordijk, I. Stolte- Dijkstra, M. de Jong, M. Kerstjens-Frederikse, K. Kok, B. Sikkema-Raddatz; Department of Genetics, University Medical Center, Groningen, The Netherlands. The decision whether arrayCGH copy number alterations are causative for the phenotype comprises a number of steps: exclusion of known polymorphisms, confirmation by MLPA/FISH, analyzing parental samples, and a literature/database search to compare the phenotype with cases with similar genotypes . The interpretation of microduplications is difficult. FISH confirmation is technically not always possible and specific MLPA primers have to be constructed. The phenotype is usually variable and thus inheritance from a (near) normal parent does not always exclude a causal relationship . The scarcity of published cases is also a well known problem . We analysed 300 karyotypically normal MR/MCA patients with an in house 6500k BACarray . We detected, besides polymorphic CNV’s, 38 microduplications (0 .3-7 .3Mb) in 35 patients . In 28 cases FISH resulted in 18 confirmed (1.4-7.3Mb) and ten non-confirmed (0.3-3.4Mb) duplications. In eight of the ten non-confirmed cases the duplication was shown to be inherited by arrayCGH, demonstrating that FISH is not always suitable for confirming duplications. Three FISH non-confirmed duplications were tested and confirmed by MLPA. For 26 duplications the parents were tested: 19 were inherited (0 .5-4 .14Mb) and seven were de novo (0 .3-7 .3Mb) . Upon re-evaluation one mother appeared to have a similar phenotype as her affected son . Of the 38 microduplications six still need confirmation, seven need parental testing, 18 are inherited from a phenotypically normal parent and three could not be confirmed. So far four seem to be clinically relevant; the de novo duplications 9p24 .3, 17p13 .3, and 19q13 .31q13 .32, and a maternally inherited duplication 22q13 .3 . Clinical information will be presented . c04.4 Array-CGH analysis of MCA/MR patients: identification of 5 novel microdeletion syndromes F. T. Papa, E. Katzaki, M. A. Mencarelli, R. Caselli, V. Uliana, M. Pollazzon, K. Sampieri, I. Longo, F. Ariani, I. Meloni, F. Mari, A. Renieri; Medical Genetics, Siena, Italy. We have investigated 84 patients with mild to severe mental retardation associated to facial dysmorphisms and/or congenital anomalies . All patients had a normal karyotype and have been evaluated by clinical geneticists (AR and FM) who excluded a recognizable syndrome on a clinical ground . Using 105K oligo Array-CGH a mean of 5 CNVs/ patient were identified. These ranged in size from 62Kb to 1Mb and they are reported in the databases as benign polymorphisms . Private imbalances were detected in 24 out of 84 patients . In 10 cases (12%) a private rearrangement was inherited from one healthy parent . In 14 cases (16 .5%) the rearrangement was de novo: 5 were novel deletions (Tab .1, cases 1-5) and 9 were known syndromes in atypical cases (Tab .1, cases 6-14) . The last group included three cases of 22q11 deletions, the shortest 4p- known in the literature, and one case of Potocki-Lupski. The five novel de novo deletions ranged between 2.6 and 13 .9Mb and they overlapped with polymorphic regions for an extent of 5-48%. Only two (6q24.3-q25.1 and 7q36.1-q36.2) are flanked by LCRs . An accurate search of the literature allowed to identify additional patients with overlapping deletions . Comparative analysis of the phenotype of these patients with our patients suggested that a specific phenotype of these syndrome may be defined. These characteristics should be taken into account in order to identify additional patients . case molecular karyotype del(2)(q24 .3q31 .1){10 .6 Mb} Tab .1 de novo rearrangements Presence of LcR Overlap with polym. region Number of genes Disease genes References SCN2A; GALNT3; SCN1A; SCN9A; ABCB11; LRP2; BBS5; GAD1; Pescucci et al .; Eur J Med Genet . 1 NO 5% 50 2 del(2)(q31 .2q32 .3){13 .9 Mb} NO 33% 43 ITGA6; CHRNA1 2007;50(1):21-32 CERKL; NEUROD1; FRZB; COL3A1; Mencarelli et al .;Am COL5A2; SLC40A1; PMS1; J Med Genet A . HIBCH; STAT1 2007;143(8):858-65 Caselli et al .; Eur 3 del(6)(q24 .3q25 .1){2 .6 Mb} SI 10% 21 SUMO4 J Med Genet . 2007;50(4):315-21 4 del(7)(q36 .1q36 .2){5 .5 Mb} SI 35% 56 Caselli et al .; Am J Med CNTNAP2; KCNH2; NOS3; PRKAG2 Genet A . 2007 5 del(14)(q12q12){3 .0 Mb} NO 48% 5 COCH 6 del(1)(p36 .32p36 .33){3 .8 Mb} NO 70% 65 SKI; PEX1; TP73 7 del(4)(p16 .3p16 .3){2 .0 Mb} SI 60% 30 PDE6B; IDUA; FGFR3; WHSC1 8 9 10 11 12 13 14 del(15)(q11 .2q13 .1){5 .7 Mb} dup(17)(p11 .2p11 .2){3 .9 Mb} del(17)(p11 .2p11 .2){3 .4 Mb} del(22)(q11 .21q11 .21){3 .1 Mb} del(22)(q13 .31q13 .33){4 .7 Mb} SI SI SI SI NO 35% 63% 63% 42% 54% 14 41 41 37 39 NDN; SNRPN; UBE3A; GABRB3; OCA2 TNFRSF13B; FLCN; RAI1; ATPAF2; Greco et al . .; Clin Genet . MYO15A; ALDH3A2; AKAP10 2008;73(3):294-6 TNFRSF13B; FLCN; RAI1; ATPAF2; MYO15A; ALDH3A2; AKAP10 Uliana et al .; Clin PRODH; TBX1; COMT; RTN4R; Dysmorphol . SERPIND1; SNAP29; GGT2 2008;17(1):13-7 PPARA; TRMU;ALG12; MLC1; SCO2; ECGF1; ARSA; SHANK3; ACR c04.5 towards an improved genetic diagnosis of individuals with a congenital heart defects B. Thienpont 1 , L. Tranchevent 2 , P. Van Loo 1,2 , J. Breckpot 1 , M. Gewillig 3 , Y. Moureau 2 , K. Devriendt 1 ; 1 Center for Human Genetics, Leuven, Belgium, 2 Department of Electrical Engineering, ESAT-SCD, Leuven, Belgium, 3 Pediatric Cardiology Unit, Leuven, Belgium. Detection of submicroscopic chromosomal imbalances by array-CGH opens opportunities in diagnostics as well as in the identification of novel loci involved in the patients phenotype . We analysed 130 patients with idiopathic ‘syndromic’ congenital heart defects (CHDs) by array-CGH with a 1Mb resolution . Causal chromosomal abnormalities were detected in 22/130 patients (17%) . In some of the regions, genes known to cause CHDs upon mutation are found: TBX1, NKX2 .5, GATA4, NSD1, EHMT1, NOTCH1, ATRX and CBP . In the remaining regions no genes are known to cause CHDs, and they thus represent novel loci linked to CHDs . To identify the causal genes, the genes in imbalanced regions were first scored for their potential involvement in cardiogenesis using a tailored modular prioritisation algorithm based on ENDEAVOUR (Aerts et al, Nat Biotech 24 p 537). We first added expression microarray data of murine cardiogenesis to the ENDEAVOUR framework . We next constructed 6 different training sets related to different aspects of CHDs or cardiogenesis . Leave-one-out cross-validations determined which data sources contain relevant information for prioritization of genes related to that process . Next we fused these different prioritizations (of one candidate gene set, using different training sets) into one overall prioritization . We validated the prioritisation of ENDEAVOUR by expression analysis in zebrafish. 45 of the highest-ranking genes were analysed. As a positive control we analysed expression of some of the identified genes known to cause CHDs . Two strong candidate genes for CHDs emerge from these analyses: BMP4 and HAND2 . c04.6 information management for constitutional cytogenetics: tools for ArraycGH in a clinical diagnostic context S. W. L. A. Van Vooren1 , B. Coessens1 , J. R. Vermeesch2 , Y. Moreau1 ; 1 2 K.U.Leuven, ESAT/SCD (SISTA), Heverlee, Belgium, Center for Human Genetics, Leuven University Hospital, Leuven, Belgium. As Microarray-CGH is introduced into clinical practice for identification of submicroscopic genomic aberrations, tools to handle related data become essential for clinical geneticists and biomedical researchers alike . We have developed Bench, a web application that combines a constitutional cytogenetics database and tools for search, visualisation, genome annotation, automated genotype-phenotype linkage,

Concurrent Sessions reporting, and literature mining . Array-CGH technology is currently on its way to replace classical karyotyping as primary diagnostic tool in copy number screening . Its vast importance in clinical diagnosis and research are underlined by large number of genes in human development and disease still unknown. A data storage and mining tool aimed specifically at leveraging the power of Array-CGH in a clinical context will aid aetiology of rare and complex genetic diseases by characterising genomic rearrangements, annotating and analysing clinical features, and providing advanced data mining and integration . For example, through an automated analysis of PUBMED abstracts, Bench allows to prioritize candidate genes in genomic deletions and duplications by phenotype characteristics annotated to the patient . Also, known Copy Number Variations, genes and their functions, and other genome annotations, when integrated with patient related data, aid in diagnosis and aetiology of new submicroscopic chromosomal imbalance syndromes . Bench provides a collaborative Array-CGH LIMS system that allows to maintain records of phenotype and chromosome rearrangements in patients, augmented with data mining, reporting and visualisation facilitating research, diagnostics, research and genetic counseling by involving relevant information from a variety of sources . Bench can be used free of charge in a research collaboration . http://www .esat . kuleuven .be/cghgate/ . c05.1 Functional interactions of conserved non-coding (cNc) sequences with other cNc using circular chromosome conformation capture (4c) D. Robyr, G. Duriaux-Sail, S. E. Antonarakis; University of Geneva Medical School, Geneva, Switzerland. The comparison of human chromosome 21 (Hsa21) sequences with the mouse syntenic regions led to the identification of roughly 3500 regions displaying an identity of >70% over a length of a least 100 nucleotides of ungaped alignment . About 65% (~ 2300) of these are conserved non-coding sequences (CNCs) . Very little is known about the function of most CNCs . We speculated that a functional CNC may interact with its genomic target (i .e . an enhancer would bind to it’s cognate gene promoter). Thus, the identification of any part of the genome that interacts directly with a CNC could provide clues on the function of the latter . We have generated libraries of CNC-interacting DpnII fragments by chromosome conformation capture (4C) whose identity is determined by subsequent high-throughput sequencing . We are currently screening for the interactions of 18 CNCs located in the two ENCODE regions of HSA21 in different cell lines . Preliminary results for two CNCs in K562 cells indicate that these may interact near regions of the genome that show conservation among vertebrates . Indeed, the median distances from the sequenced DpnII fragments to the nearest conserved region are 381 .5 bp (P = 0 .0583) and 764bp (P = 0 .023) respectively for the 2 CNCs analysed . These results provide initial evidence that the function of CNCs is mediated by their interactions with other conserved regions . Interestingly, these CNCs are capable of interactions with loci not only in cis and over several Mb, but also in trans with loci located on other chromosomes . c05.2 A high-resolution structural variation map of a human genome by next-generation, high-throughput paired-end sequencing F. M. De La Vega 1 , H. E. Peckham 2 , S. S. Ranade 2 , S. F. McLaughlin 2 , C. C. Lee 2 , Y. Fu 2 , Z. Zhang 1 , F. C. L. Hyland 1 , C. L. Clouser 2 , A. A. Antipova 2 , J. M. Manning 2 , C. L. Hendrickson 2 , L. Zhang 2 , E. T. Dimalanta 2 , T. D. Sokolsky 2 , M. W. Laptewicz 2 , B. E. Coleman 2 , J. K. Ichikawa 2 , J. B. Warner 2 , B. Li 1 , J. M. Kidd 3 , J. A. Malek 4 , G. L. Costa 2 , E. E. Eichler 3 , K. J. McKernan 2 ; 1 Applied Biosystems, Foster City, CA, United States, 2 Applied Biosystems, Beverly, MA, United States, 3 HHMI, University of Washington, Seattle, WA, United States, 4 Weill Cornell Medical College in Qatar, Doha, Qatar. The human genome and HapMap projects have considerably increased our understanding of the role of sequence variation in evolution and disease . Hybridization microarrays and fosmid-end sequencing reveal that structural variants (SVs) including insertions, deletions, duplications, inversions and translocations are common and extensive . Microarray methods, however, lack resolution and are blind to unbalanced events, while clone-based end-sequencing is time consuming and expensive . Here, we present a high-resolution survey of SVs of a human genome, a HapMap Yoruba sample (NA18507), by ultra-high throughput sequencing of paired-end libraries with the AB SOLiD(TM) System . We sequenced a variety of 2x25-bp paired-end libraries (>15Gb) with insert sizes ranging from 600bp to 6kb (SD 10-23%) . Each library provides over 10x physical (clone) coverage, with a total combined physical coverage >60x for 90% of the genome . The high physical coverage and diverse insert sizes allowed detecting small indels within tags (1-10 bp), and approximately 70,000 indels of length 20 bp to >100 kb . Additionally, we sequenced 7Gb of 50-bp fragment libraries, which combined with the paired libraries provided over 12x sequence coverage, allowing us to discover millions of SNPs of which 75% are found in dbSNP . Inferred SVs were compared to a database of end-sequence pairs of 10x physical coverage obtained by di-deoxy sequencing of 40kb fosmid ends . A subset of novel SVs were validated by PCR and Sanger sequencing . Our results serves as a model for further high-resolution exploration of genetic variation in human populations and cancer with next-generation sequencing . c05.3 Expression analysis using deep solexa sequencing shows major advances in robustness, resolution and inter-lab portability over microarray platforms J. T. den Dunnen 1,2 , Y. Ariyurek 2 , H. H. Thygesen 1 , E. Vreugdenhil 3 , J. M. Boer 1 , G. B. van Ommen 1 , P. A. C. ‘t Hoen 1 ; 1 Human and Clinical Gentics, Leiden, The Netherlands, 2 Leiden Genome Technology Center, Leiden, The Netherlands, 3 Medical Pharmacology, Leiden / Amsterdam Center for Drug Research, Leiden, The Netherlands. The hippocampal transcriptomes of wild-type mice and mice transgenic for δC-doublecortin-like kinase were analyzed with the Solexa deep sequencing technology . We determined around 2 million sequence tags per sample and compared these data with results of the same samples analysed using five different microarray platforms. Seventy percent of the sequence tags were mapped to approximately 30,000 unique, high-confidence transcripts, their abundance spanning four orders of magnitude . Antisense transcription, undetectable by microarrays, was found in 51% of all genes, and alternative poly-adenylation in 47% . With a dedicated Bayesian model and false discovery rate of 8.5%, we measured statistically significant differential expression for 3179 transcripts; many more and with higher fold-changes than observed using microarrays . The deep sequencing technology demonstrates superb reproducibility, not only between biological replicates but even across laboratories . The described major advance in robustness, comparability and richness of sequence -based transcriptomics data is expected to boost in-depth collaborative, comparative and integrative genomics studies . c05.4 studying gene dosage imbalance in embryonic stem cells G. Cobellis 1,2 , A. Romito 1 , R. De Cegli 1 , S. Iacobacci 1 , A. Fedele 1 , D. di Bernardo 1 , A. Ballabio 1 ; 1 TIGEM, Napoli, Italy, 2 Second University of Naples, Naples, Italy. To gain insight into the alterations of the transcriptional pathways underlying the pathogenesis of Down syndrome, we decided to use an integrated strategy combining the systematic overexpression of chromosome 21 genes in ES cells, transcriptome analysis and systems biology approaches . We generated an ES cell clone bearing an inducible/exchangeable cassette in the ROSA26 locus to be used to insert, one by one, every murine orthologs of human chromosome 21 genes. Using this flexible system, we developed a library of ES cells over-expressing, in an inducible manner, murine orthologs of human transcription factors, kinases and miRNAs mapping on HSA21 in order to perturb the physiological genetic network at the cellular level . The biological pathways affected by the over-expression of each coding and non-coding gene and their regulators and regulated genes have been inferred using system biology approach . We already mapped the regulatory gene networks specifically altered by each transcription factors and kinases, opening new hypothesis toward the understanding of pathogenesis of Down syndrome . Finally, the above-described ES cell lines have been used to study the gene dosage imbalance effects on ES cell differentiation to cardiomyocytes, myeloid and neuronal lineages, tissues affected by the DS . This project represent the first to involve a systematic overexpression

Page 1 and 2: Volume 16 Supplement 2 May 2008 www

Page 3 and 4: Committees - Board - Organisation E

Page 5 and 6: Plenary Lectures ESHG PLENARY LECTU

Page 7 and 8: Plenary Lectures 6 Medical Genetics

Page 9 and 10: Concurrent Symposia ESHG CONCURRENT

Page 11 and 12: Concurrent Symposia s04.1 microRNA

Page 13 and 14: Concurrent Symposia 0 use of positi

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Page 27 and 28: Concurrent Sessions c06.3 clinical

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Page 33 and 34: Concurrent Sessions MYCN , E2F3 and

Page 35 and 36: Concurrent Sessions limb or thoraci

Page 37 and 38: Concurrent Sessions APC, BRCA1 and

Page 39 and 40: Concurrent Sessions identified 215

Page 41 and 42: Clinical genetics ESHG POSTERS P01.

Page 43 and 44: Clinical genetics In Cyprus, the mu

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Page 47 and 48: Clinical genetics are indeed more d

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Page 123 and 124: Cytogenetics P01.369 three novel mu

Page 125 and 126: Cytogenetics P02.008 Reconfirmation

Page 127 and 128: Cytogenetics mosomal rearrangement

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Page 135 and 136: Cytogenetics We herewith report two

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Page 195 and 196: Cancer genetics forms . The typical

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Page 471 and 472: Author Index Al-Owain, M.: P06.160

Page 473 and 474: Author Index 0 Baka, M.: P04.082 Ba

Page 475 and 476: Author Index Berwouts, S.: P09.20,

Page 477 and 478: Author Index P07.117 Buil, A.: P06.

Page 479 and 480: Author Index Cho, J.: P04.192, P08.

Page 481 and 482: Author Index Damy, T.: P01.057 Damy

Page 483 and 484: Author Index 0 Dror, A.: P05.074 Dr

Page 485 and 486: Author Index Fernandez-Real, J.: P0

Page 487 and 488: Author Index P06.310 Gavriliuc, A.

Page 489 and 490: Author Index Grinberg, Y. I.: P01.0

Page 491 and 492: Author Index Hood, L.: PL4.1 Hoogeb

Page 493 and 494: Author Index 0 P02.240, P09.63 Kala

Page 495 and 496: Author Index Kongstad, O.: P09.39 K

Page 497 and 498: Author Index Lee, C.: C13.3 Lee, D.

Page 499 and 500: Author Index Mahjoubi, F.: P02.045,

Page 501 and 502: Author Index P04.196 Meindl, A.: c0

Page 503 and 504: Author Index 00 Mottaghi, L.: P01.0

Page 505 and 506: Author Index 0 Oh, T. Y.: P01.084 O

Page 507 and 508: Author Index 0 Peñaloza, R.: P05.2

Page 509 and 510: Author Index 0 Proverbio, M.: P05.0

Page 511 and 512: Author Index 0 Rogers, M.: EP14.18

Page 513 and 514: Author Index 0 Scarcella, M.: P05.0

Page 515 and 516: Author Index P06.179 Sobrino, B.: P

Page 517 and 518: Author Index Taschner, P. E. M.: P0

Page 519 and 520: Author Index Urreizti, R.: P01.050,

Page 521 and 522: Author Index Voegele, C.: P04.121 V

Page 523 and 524: Author Index 0 P04.095, P04.106 Zem

Page 525 and 526: Keyword Index AMACR gene: P04.182 a

Page 527 and 528: Keyword Index cardiac: S04.1 Cardio

Page 529 and 530: Keyword Index Crohn: P07.022 Crohn

Page 531 and 532: Keyword Index evolution: P02.112, P

Page 533 and 534: Keyword Index 0 haemoglobinopathies

Page 535 and 536: Keyword Index KCNJ11: P05.026 KCNQ1

Page 537 and 538: Keyword Index MLH1: P04.010, P04.02

Page 539 and 540: Keyword Index osteochondrodysplasia

Page 541 and 542: Keyword Index PXE-like syndrome: P0

Page 543 and 544: Keyword Index 0 sperm: P02.205 sper

Page 545: Keyword Index venous thrombosis: P0

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