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A novel association of campomelic dysplasia and hydrocephalus with an unbalanced chromosomal translocation upstream of SOX9

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      Abstract

      Campomelic dysplasia is a rare skeletal dysplasia characterized by Pierre Robin sequence, craniofacial dysmorphism, shortening and angulation of long bones, tracheobronchomalacia, and occasionally sex reversal. The disease is due to mutations in SOX9 or chromosomal rearrangements involving the long arm of Chromosome 17 harboring the SOX9 locus. SOX9, a transcription factor, is indispensible in establishing and maintaining neural stem cells in the central nervous system. We present a patient with angulation of long bones and external female genitalia on prenatal ultrasound who was subsequently found to harbor the chromosomal abnormality 46, XY, t(6;17) (p21.1;q24.3) on prenatal genetic testing. Comparative genomic hybridization revealed deletions at 6p21.1 and 17q24.3, the latter being 2.3 Mb upstream of SOX9. Whole-exome sequencing did not identify pathogenic variants in SOX9, suggesting that the 17q24.3 deletion represents a translocation breakpoint farther upstream of SOX9 than previously identified. At 2 mo of age the patient developed progressive communicating ventriculomegaly and thinning of the cortical mantle without clinical signs of increased intracranial pressure. This case suggests ventriculomegaly in some cases represents not a primary impairment of cerebrospinal fluid dynamics, but an epiphenomenon driven by a genetic dysregulation of neural progenitor cell fate.

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      The Genome Analysis Toolkit: a MapReduce framework for analyzing next-generation DNA sequencing data.

      Next-generation DNA sequencing (NGS) projects, such as the 1000 Genomes Project, are already revolutionizing our understanding of genetic variation among individuals. However, the massive data sets generated by NGS--the 1000 Genome pilot alone includes nearly five terabases--make writing feature-rich, efficient, and robust analysis tools difficult for even computationally sophisticated individuals. Indeed, many professionals are limited in the scope and the ease with which they can answer scientific questions by the complexity of accessing and manipulating the data produced by these machines. Here, we discuss our Genome Analysis Toolkit (GATK), a structured programming framework designed to ease the development of efficient and robust analysis tools for next-generation DNA sequencers using the functional programming philosophy of MapReduce. The GATK provides a small but rich set of data access patterns that encompass the majority of analysis tool needs. Separating specific analysis calculations from common data management infrastructure enables us to optimize the GATK framework for correctness, stability, and CPU and memory efficiency and to enable distributed and shared memory parallelization. We highlight the capabilities of the GATK by describing the implementation and application of robust, scale-tolerant tools like coverage calculators and single nucleotide polymorphism (SNP) calling. We conclude that the GATK programming framework enables developers and analysts to quickly and easily write efficient and robust NGS tools, many of which have already been incorporated into large-scale sequencing projects like the 1000 Genomes Project and The Cancer Genome Atlas.
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        ANNOVAR: functional annotation of genetic variants from high-throughput sequencing data

        High-throughput sequencing platforms are generating massive amounts of genetic variation data for diverse genomes, but it remains a challenge to pinpoint a small subset of functionally important variants. To fill these unmet needs, we developed the ANNOVAR tool to annotate single nucleotide variants (SNVs) and insertions/deletions, such as examining their functional consequence on genes, inferring cytogenetic bands, reporting functional importance scores, finding variants in conserved regions, or identifying variants reported in the 1000 Genomes Project and dbSNP. ANNOVAR can utilize annotation databases from the UCSC Genome Browser or any annotation data set conforming to Generic Feature Format version 3 (GFF3). We also illustrate a ‘variants reduction’ protocol on 4.7 million SNVs and indels from a human genome, including two causal mutations for Miller syndrome, a rare recessive disease. Through a stepwise procedure, we excluded variants that are unlikely to be causal, and identified 20 candidate genes including the causal gene. Using a desktop computer, ANNOVAR requires ∼4 min to perform gene-based annotation and ∼15 min to perform variants reduction on 4.7 million variants, making it practical to handle hundreds of human genomes in a day. ANNOVAR is freely available at http://www.openbioinformatics.org/annovar/ .
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          A global reference for human genetic variation

           Lachlan Coin (2016)
          The 1000 Genomes Project set out to provide a comprehensive description of common human genetic variation by applying whole-genome sequencing to a diverse set of individuals from multiple populations. Here we report completion of the project, having reconstructed the genomes of 2,504 individuals from 26 populations using a combination of low-coverage whole-genome sequencing, deep exome sequencing, and dense microarray genotyping. We characterized a broad spectrum of genetic variation, in total over 88 million variants (84.7 million single nucleotide polymorphisms (SNPs), 3.6 million short insertions/deletions (indels), and 60,000 structural variants), all phased onto high-quality haplotypes. This resource includes >99% of SNP variants with a frequency of >1% for a variety of ancestries. We describe the distribution of genetic variation across the global sample, and discuss the implications for common disease studies.
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            Author and article information

            Affiliations
            [1 ]Department of Neurosurgery, Yale University School of Medicine, New Haven, Connecticut 06520, USA;
            [2 ]Department of Genetics, Yale University School of Medicine, New Haven, Connecticut 06520, USA;
            [3 ]Department of Pediatrics, Yale School of Medicine, New Haven, Connecticut 06520, USA;
            [4 ]Department of Cellular & Molecular Physiology, Yale School of Medicine, New Haven, Connecticut 06520, USA
            Author notes
            Journal
            Cold Spring Harb Mol Case Stud
            Cold Spring Harb Mol Case Stud
            cshmcs
            cshmcs
            cshmcs
            Cold Spring Harbor Molecular Case Studies
            Cold Spring Harbor Laboratory Press
            2373-2873
            June 2018
            : 4
            : 3
            29695406
            5983176
            10.1101/mcs.a002766
            MCS002766Ant

            This article is distributed under the terms of the Creative Commons Attribution-NonCommercial License, which permits reuse and redistribution, except for commercial purposes, provided that the original author and source are credited.

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            Pages: 13
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            Funding
            Funded by: National Institutes of Health (NIH) , open-funder-registry 10.13039/100000002;
            Funded by: Clinical and Translational Science Award (CTSA)
            Award ID: TL1TR000141
            Funded by: Yale University School of Medicine
            Funded by: Hydrocephalus Foundation
            Categories
            Research Reports

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