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ALPK3 gene mutation in a patient with congenital cardiomyopathy and dysmorphic features

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      Primary cardiomyopathy is one of the most common inherited cardiac diseases and harbors significant phenotypic and genetic heterogeneity. Because of this, genetic testing has become standard in treatment of this disease group. Indeed, in recent years, next-generation DNA sequencing has found broad applications in medicine, both as a routine diagnostic tool for genetic disorders and as a high-throughput discovery tool for identifying novel disease-causing genes. We describe a male infant with primary dilated cardiomyopathy who was diagnosed using intrauterine echocardiography and found to progress to hypertrophic cardiomyopathy after birth. This proband was born to a nonconsanguineous family with a past history of a male fetus that died because of cardiac abnormalities at 30 wk of gestation. Using whole-exome sequencing, a novel homozygous frameshift mutation (c.2018delC; p.Gln675SerfsX30) in ALPK3 was identified and confirmed with Sanger sequencing. Heterozygous family members were normal with echocardiographic examination. To date, only two studies have reported homozygous pathogenic variants of ALPK3, with a total of seven affected individuals with cardiomyopathy from four unrelated consanguineous families. We include a discussion of the patient's phenotypic features and a review of relevant literature findings.

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      Fast and accurate short read alignment with Burrows–Wheeler transform

      Motivation: The enormous amount of short reads generated by the new DNA sequencing technologies call for the development of fast and accurate read alignment programs. A first generation of hash table-based methods has been developed, including MAQ, which is accurate, feature rich and fast enough to align short reads from a single individual. However, MAQ does not support gapped alignment for single-end reads, which makes it unsuitable for alignment of longer reads where indels may occur frequently. The speed of MAQ is also a concern when the alignment is scaled up to the resequencing of hundreds of individuals. Results: We implemented Burrows-Wheeler Alignment tool (BWA), a new read alignment package that is based on backward search with Burrows–Wheeler Transform (BWT), to efficiently align short sequencing reads against a large reference sequence such as the human genome, allowing mismatches and gaps. BWA supports both base space reads, e.g. from Illumina sequencing machines, and color space reads from AB SOLiD machines. Evaluations on both simulated and real data suggest that BWA is ∼10–20× faster than MAQ, while achieving similar accuracy. In addition, BWA outputs alignment in the new standard SAM (Sequence Alignment/Map) format. Variant calling and other downstream analyses after the alignment can be achieved with the open source SAMtools software package. Availability: Contact:
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        A framework for variation discovery and genotyping using next-generation DNA sequencing data

        Recent advances in sequencing technology make it possible to comprehensively catalogue genetic variation in population samples, creating a foundation for understanding human disease, ancestry and evolution. The amounts of raw data produced are prodigious and many computational steps are required to translate this output into high-quality variant calls. We present a unified analytic framework to discover and genotype variation among multiple samples simultaneously that achieves sensitive and specific results across five sequencing technologies and three distinct, canonical experimental designs. Our process includes (1) initial read mapping; (2) local realignment around indels; (3) base quality score recalibration; (4) SNP discovery and genotyping to find all potential variants; and (5) machine learning to separate true segregating variation from machine artifacts common to next-generation sequencing technologies. We discuss the application of these tools, instantiated in the Genome Analysis Toolkit (GATK), to deep whole-genome, whole-exome capture, and multi-sample low-pass (~4×) 1000 Genomes Project datasets.
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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.

            Author and article information

            [1 ]Department of Medical Genetics, School of Medicine, Istanbul Bilim University, Istanbul 34394, Turkey;
            [2 ]Departments of Neurosurgery, Neurobiology and Genetics, Yale School of Medicine, New Haven, Connecticut 06510, USA;
            [3 ]Department of Pediatrics, University of Health Sciences, Zeynep Kamil Maternity and Childrens' Diseases Training and Research Hospital, Istanbul 34668, Turkey;
            [4 ]Department of Pediatrics, School of Medicine, Istanbul Bilim University, Istanbul 34394, Turkey;
            [5 ]Division of Pediatric Cardiology, Department of Pediatrics, Zeynep Kamil Maternity and Childrens’ Diseases Training and Research Hospital, Istanbul 34668, Turkey;
            [6 ]Division of Pediatric Cardiology, Department of Pediatrics, School of Medicine, Istanbul Bilim University, Istanbul 34394, Turkey;
            [7 ]Department of Genetics, Yale Center for Genome Analysis, Yale School of Medicine, New Haven, Connecticut 06510, USA
            Author notes
            Cold Spring Harb Mol Case Stud
            Cold Spring Harb Mol Case Stud
            Cold Spring Harbor Molecular Case Studies
            Cold Spring Harbor Laboratory Press
            September 2017
            : 3
            : 5

            This article is distributed under the terms of the Creative Commons Attribution License, which permits unrestricted reuse and redistribution provided that the original author and source are credited.

            Pages: 15
            Funded by: Yale Program on Neurogenetics and the Yale Center for Mendelian Disorders
            Award ID: U54HG006504
            Funded by: (NIH) Medical Scientist Training Program , open-funder-registry 10.13039/100000002;
            Award ID: T32GM007205
            Funded by: Gregory M. Kiez and Mehmet Kutman Foundation (M.G.)
            Research Report

            hypertrophic cardiomyopathy


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