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      Detection of Chromosomal Breakpoints in Patients with Developmental Delay and Speech Disorders

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          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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          Most cited references38

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          Paired-end mapping reveals extensive structural variation in the human genome.

          Structural variation of the genome involves kilobase- to megabase-sized deletions, duplications, insertions, inversions, and complex combinations of rearrangements. We introduce high-throughput and massive paired-end mapping (PEM), a large-scale genome-sequencing method to identify structural variants (SVs) approximately 3 kilobases (kb) or larger that combines the rescue and capture of paired ends of 3-kb fragments, massive 454 sequencing, and a computational approach to map DNA reads onto a reference genome. PEM was used to map SVs in an African and in a putatively European individual and identified shared and divergent SVs relative to the reference genome. Overall, we fine-mapped more than 1000 SVs and documented that the number of SVs among humans is much larger than initially hypothesized; many of the SVs potentially affect gene function. The breakpoint junction sequences of more than 200 SVs were determined with a novel pooling strategy and computational analysis. Our analysis provided insights into the mechanisms of SV formation in humans.
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            Mapping and sequencing of structural variation from eight human genomes.

            Genetic variation among individual humans occurs on many different scales, ranging from gross alterations in the human karyotype to single nucleotide changes. Here we explore variation on an intermediate scale--particularly insertions, deletions and inversions affecting from a few thousand to a few million base pairs. We employed a clone-based method to interrogate this intermediate structural variation in eight individuals of diverse geographic ancestry. Our analysis provides a comprehensive overview of the normal pattern of structural variation present in these genomes, refining the location of 1,695 structural variants. We find that 50% were seen in more than one individual and that nearly half lay outside regions of the genome previously described as structurally variant. We discover 525 new insertion sequences that are not present in the human reference genome and show that many of these are variable in copy number between individuals. Complete sequencing of 261 structural variants reveals considerable locus complexity and provides insights into the different mutational processes that have shaped the human genome. These data provide the first high-resolution sequence map of human structural variation--a standard for genotyping platforms and a prelude to future individual genome sequencing projects.
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              Sequencing chromosomal abnormalities reveals neurodevelopmental loci that confer risk across diagnostic boundaries.

              Balanced chromosomal abnormalities (BCAs) represent a relatively untapped reservoir of single-gene disruptions in neurodevelopmental disorders (NDDs). We sequenced BCAs in patients with autism or related NDDs, revealing disruption of 33 loci in four general categories: (1) genes previously associated with abnormal neurodevelopment (e.g., AUTS2, FOXP1, and CDKL5), (2) single-gene contributors to microdeletion syndromes (MBD5, SATB2, EHMT1, and SNURF-SNRPN), (3) novel risk loci (e.g., CHD8, KIRREL3, and ZNF507), and (4) genes associated with later-onset psychiatric disorders (e.g., TCF4, ZNF804A, PDE10A, GRIN2B, and ANK3). We also discovered among neurodevelopmental cases a profoundly increased burden of copy-number variants from these 33 loci and a significant enrichment of polygenic risk alleles from genome-wide association studies of autism and schizophrenia. Our findings suggest a polygenic risk model of autism and reveal that some neurodevelopmental genes are sensitive to perturbation by multiple mutational mechanisms, leading to variable phenotypic outcomes that manifest at different life stages. Copyright © 2012 Elsevier Inc. All rights reserved.
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                Author and article information

                Contributors
                Role: Editor
                Journal
                PLoS One
                PLoS ONE
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, USA )
                1932-6203
                2014
                6 March 2014
                : 9
                : 3
                : e90852
                Affiliations
                [1 ]Human Genetics, Genome Institute of Singapore, Singapore, Singapore
                [2 ]Cancer Therapeutics and Stratified Oncology, Genome Institute of Singapore, Singapore, Singapore
                [3 ]Stem Cells and Developmental Biology, Genome Institute of Singapore, Singapore, Singapore
                [4 ]Computational and Mathematical Biology, Genome Institute of Singapore, Singapore, Singapore
                [5 ]Scientific & Research Computing, Genome Institute of Singapore, Singapore, Singapore
                [6 ]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
                [7 ]Disciplines of Paediatrics and Child Health and Genetic Medicine, Sydney Medical School, University of Sydney, Sydney, New South Wales, Australia
                [8 ]Department of Cytogenetics, The Children’s Hospital at Westmead, Sydney, New South Wales, Australia
                [9 ]Department of Clinical Genetics, The Children’s Hospital at Westmead, Sydney, New South Wales, Australia
                [10 ]Department of Immunology, The Children’s Hospital at Westmead, Sydney, New South Wales, Australia
                [11 ]Unité de Génétique, Centre Hospitalier, Blois, France
                [12 ]Service de Genetique INEM UMR7355 CNRS-University, Centre Hospitalier Régional d’Orléans, Orléans, France
                [13 ]Department of Paediatrics, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
                [14 ]Genome Technology and Biology, Genome Institute of Singapore, Singapore, Singapore
                University of Bonn, Institut of experimental hematology and transfusion medicine, Germany
                Author notes

                Competing Interests: The authors have declared that no competing interests exist.

                Conceived and designed the experiments: AMH VC SD. Performed the experiments: KHU EGYC LSS ASMT ZZ LSS SY IP. Analyzed the data: KHU AMH CWHL PJC CCS PNA SLR. Wrote the paper: KHU AMH IA VC SD SKHT. Provided sequencing platform and facility: XR YR AMH ETL. Cpatient samples: GP FC MW AK GH AM OP SB RVJ. Provided analysis tools: KWKS.

                Article
                PONE-D-13-46794
                10.1371/journal.pone.0090852
                3946304
                24603971
                cbeee1b4-9de4-4f03-8bb3-3cb3572b8072
                Copyright @ 2014

                This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 7 November 2013
                : 4 February 2014
                Page count
                Pages: 10
                Funding
                This study is supported by grants from Biomedical Medical Research Council (BMRC) of the Agency for Science, Technology and Research (A*STAR), Singapore. Support is also acknowledged from the National Health and Medical Research Australia (NHMRC). KHU is funded by Singapore International Graduate Award (SINGA) fellowship. Additional support was also provided by the Genome Institute of Singapore internal research funds from the BMRC. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Categories
                Research Article
                Biology
                Genetics
                Cytogenetics
                Cytogenetic Techniques
                Heredity
                Phenotypes
                Human Genetics
                Chromosomal Disorders
                Translocations
                Genetic Association Studies
                X-Linked
                Genetics of Disease
                Genomics
                Genome Sequencing

                Uncategorized
                Uncategorized

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