Massively parallel sequencing and identification of genes for primary lymphoedema: a perfect fit

Authors

  • P Ostergaard,

    1. Medical Genetics Unit, Biomedical Sciences, St George's University of London, London, UK
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  • MA Simpson,

    1. Division of Genetics and Molecular Medicine, King's College London School of Medicine, Guy's Hospital, London, UK
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  • S Jeffery

    Corresponding author
    1. Medical Genetics Unit, Biomedical Sciences, St George's University of London, London, UK
      Steve Jeffery, Medical Genetics Unit, Biomedical Sciences, St George's University of London, London SW17 0RE, UK.
      Tel: +44 (0)208 725 5967;
      fax: +44 (0)208 725 1039;
      e-mail: sggt100@sgul.ac.uk
    Search for more papers by this author

Steve Jeffery, Medical Genetics Unit, Biomedical Sciences, St George's University of London, London SW17 0RE, UK.
Tel: +44 (0)208 725 5967;
fax: +44 (0)208 725 1039;
e-mail: sggt100@sgul.ac.uk

Abstract

Ostergaard P, Simpson MA, Jeffery S. Massively parallel sequencing and the identification of genes for primary lymphoedema: a perfect fit.

Primary lymphoedema is a clinically and genetically heterogeneous group of disorders characterized by disruption of the lymphatic system. To date, the majority of the causative genes in primary lymphoedema have been identified through linkage analysis in large families with multiple affected subjects. Studies aimed at isolating additional genes responsible for primary lymphoedema have been hampered by cohorts comprised primarily of sporadic cases and small affected kindreds. In the absence of genetic heterogeneity, recent development of massively parallel DNA sequencing technology, specifically exome sequencing, has provided novel paradigms for disease gene identification in such cohorts. In this review, we summarize the novel approaches to disease gene discovery with massively parallel sequencing also known as Next Generation Sequencing (NGS), and show how the selection of unrelated affected cases from clinically homogenous phenotypic subclassifications is proving to be a successful approach for disease gene discovery in primary lymphoedema.

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