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Utami KH, Hillmer AM, Aksoy I, Chew EGY, Teo ASM, Zhang Z, Lee CWH, Chen PJ, Seng CC, Ariyaratne PN, Rouam SL, Soo LS, Yousoof S, Prokudin I, Peters G, Collins F, Wilson M, Kakakios A, Haddad G, Menuet A, Perche O, Tay SKH, Sung KWK, Ruan X, Ruan Y, Liu ET, Briault S, Jamieson RV, Davila S, Cacheux V. Detection of chromosomal breakpoints in patients with developmental delay and speech disorders. PLoS One 2014; 9:e90852. [PMID: 24603971 PMCID: PMC3946304 DOI: 10.1371/journal.pone.0090852] [Citation(s) in RCA: 34] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/07/2013] [Accepted: 02/04/2014] [Indexed: 01/25/2023] Open
Abstract
Delineating candidate genes at the chromosomal breakpoint regions in the apparently balanced chromosome rearrangements (ABCR) has been shown to be more effective with the emergence of next-generation sequencing (NGS) technologies. We employed a large-insert (7-11 kb) paired-end tag sequencing technology (DNA-PET) to systematically analyze genome of four patients harbouring cytogenetically defined ABCR with neurodevelopmental symptoms, including developmental delay (DD) and speech disorders. We characterized structural variants (SVs) specific to each individual, including those matching the chromosomal breakpoints. Refinement of these regions by Sanger sequencing resulted in the identification of five disrupted genes in three individuals: guanine nucleotide binding protein, q polypeptide (GNAQ), RNA-binding protein, fox-1 homolog (RBFOX3), unc-5 homolog D (C.elegans) (UNC5D), transmembrane protein 47 (TMEM47), and X-linked inhibitor of apoptosis (XIAP). Among them, XIAP is the causative gene for the immunodeficiency phenotype seen in the patient. The remaining genes displayed specific expression in the fetal brain and have known biologically relevant functions in brain development, suggesting putative candidate genes for neurodevelopmental phenotypes. This study demonstrates the application of NGS technologies in mapping individual gene disruptions in ABCR as a resource for deciphering candidate genes in human neurodevelopmental disorders (NDDs).
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Affiliation(s)
- Kagistia H. Utami
- Human Genetics, Genome Institute of Singapore, Singapore, Singapore
- Department of Paediatrics, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
| | - Axel M. Hillmer
- Cancer Therapeutics and Stratified Oncology, Genome Institute of Singapore, Singapore, Singapore
| | - Irene Aksoy
- Stem Cells and Developmental Biology, Genome Institute of Singapore, Singapore, Singapore
| | - Elaine G. Y. Chew
- Cancer Therapeutics and Stratified Oncology, Genome Institute of Singapore, Singapore, Singapore
| | - Audrey S. M. Teo
- Cancer Therapeutics and Stratified Oncology, Genome Institute of Singapore, Singapore, Singapore
| | - Zhenshui Zhang
- Cancer Therapeutics and Stratified Oncology, Genome Institute of Singapore, Singapore, Singapore
| | - Charlie W. H. Lee
- Computational and Mathematical Biology, Genome Institute of Singapore, Singapore, Singapore
| | - Pauline J. Chen
- Computational and Mathematical Biology, Genome Institute of Singapore, Singapore, Singapore
| | - Chan Chee Seng
- Scientific & Research Computing, Genome Institute of Singapore, Singapore, Singapore
| | - Pramila N. Ariyaratne
- Computational and Mathematical Biology, Genome Institute of Singapore, Singapore, Singapore
| | - Sigrid L. Rouam
- Computational and Mathematical Biology, Genome Institute of Singapore, Singapore, Singapore
| | - Lim Seong Soo
- Human Genetics, Genome Institute of Singapore, Singapore, Singapore
| | - Saira Yousoof
- Eye and Developmental Genetics Research, The Children’s Hospital at Westmead, Children’s Medical Research Institute and Save Sight Institute, Sydney, New South Wales, Australia
- Disciplines of Paediatrics and Child Health and Genetic Medicine, Sydney Medical School, University of Sydney, Sydney, New South Wales, Australia
| | - Ivan Prokudin
- Eye and Developmental Genetics Research, The Children’s Hospital at Westmead, Children’s Medical Research Institute and Save Sight Institute, Sydney, New South Wales, Australia
- Disciplines of Paediatrics and Child Health and Genetic Medicine, Sydney Medical School, University of Sydney, Sydney, New South Wales, Australia
| | - Gregory Peters
- Department of Cytogenetics, The Children’s Hospital at Westmead, Sydney, New South Wales, Australia
| | - Felicity Collins
- Department of Clinical Genetics, The Children’s Hospital at Westmead, Sydney, New South Wales, Australia
| | - Meredith Wilson
- Department of Clinical Genetics, The Children’s Hospital at Westmead, Sydney, New South Wales, Australia
| | - Alyson Kakakios
- Department of Immunology, The Children’s Hospital at Westmead, Sydney, New South Wales, Australia
| | | | - Arnaud Menuet
- Service de Genetique INEM UMR7355 CNRS-University, Centre Hospitalier Régional d’Orléans, Orléans, France
| | - Olivier Perche
- Service de Genetique INEM UMR7355 CNRS-University, Centre Hospitalier Régional d’Orléans, Orléans, France
| | - Stacey Kiat Hong Tay
- Department of Paediatrics, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
| | - Ken W. K. Sung
- Computational and Mathematical Biology, Genome Institute of Singapore, Singapore, Singapore
| | - Xiaoan Ruan
- Genome Technology and Biology, Genome Institute of Singapore, Singapore, Singapore
| | - Yijun Ruan
- Genome Technology and Biology, Genome Institute of Singapore, Singapore, Singapore
| | - Edison T. Liu
- Cancer Therapeutics and Stratified Oncology, Genome Institute of Singapore, Singapore, Singapore
| | - Sylvain Briault
- Service de Genetique INEM UMR7355 CNRS-University, Centre Hospitalier Régional d’Orléans, Orléans, France
| | - Robyn V. Jamieson
- Eye and Developmental Genetics Research, The Children’s Hospital at Westmead, Children’s Medical Research Institute and Save Sight Institute, Sydney, New South Wales, Australia
| | - Sonia Davila
- Human Genetics, Genome Institute of Singapore, Singapore, Singapore
| | - Valere Cacheux
- Human Genetics, Genome Institute of Singapore, Singapore, Singapore
- * E-mail:
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Leung HCM, Siu MH, Yiu SM, Chin FYL, Sung KWK. Finding linear motif pairs from protein interaction networks: a probabilistic approach. Comput Syst Bioinformatics Conf 2007; 6:111-119. [PMID: 17951817] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 05/25/2023]
Abstract
Finding motif pairs from a set of protein sequences based on the protein-protein interaction data is a challenging computational problem. Existing effective approaches usually rely on additional information such as some prior knowledge on protein groupings based on protein domains. In reality, this kind of knowledge is not always available. Novel approaches without using this knowledge is much desirable. Recently, Tan et al. proposed such an approach. However, there are two problems with their approach. The scoring function (using chi(2) testing) used in their approach is not adequate. Random motif pairs may have higher scores than the correct ones. Their approach is also not scalable. It may take days to process a set of 5000 protein sequences with about 20,000 interactions. In this paper, our contribution is two-fold. We first introduce a new scoring method, which is shown to be more accurate than the chi-score used in Tan et al. Then, we present two efficient algorithms, one exact algorithm and a heuristic version of it, to solve the problem of finding motif pairs. Based on experiments on real datasets, we show that our algorithms are efficient and can accurately locate the motif pairs. We have also evaluated the sensitivity and efficiency of our heuristics algorithm using simulated datasets, the results show that the algorithm is very efficient with reasonably high sensitivity.
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Affiliation(s)
- Henry C M Leung
- Department of Computer Science, The University of Hong Kong Pokfulam Road, Hong Kong.
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