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Genetic Mapping and Exome Sequencing Identify Variants Associated with Five Novel Diseases

Overview of attention for article published in PLOS ONE, January 2012
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Title
Genetic Mapping and Exome Sequencing Identify Variants Associated with Five Novel Diseases
Published in
PLOS ONE, January 2012
DOI 10.1371/journal.pone.0028936
Pubmed ID
Authors

Erik G. Puffenberger, Robert N. Jinks, Carrie Sougnez, Kristian Cibulskis, Rebecca A. Willert, Nathan P. Achilly, Ryan P. Cassidy, Christopher J. Fiorentini, Kory F. Heiken, Johnny J. Lawrence, Molly H. Mahoney, Christopher J. Miller, Devika T. Nair, Kristin A. Politi, Kimberly N. Worcester, Roni A. Setton, Rosa DiPiazza, Eric A. Sherman, James T. Eastman, Christopher Francklyn, Susan Robey-Bond, Nicholas L. Rider, Stacey Gabriel, D. Holmes Morton, Kevin A. Strauss

Abstract

The Clinic for Special Children (CSC) has integrated biochemical and molecular methods into a rural pediatric practice serving Old Order Amish and Mennonite (Plain) children. Among the Plain people, we have used single nucleotide polymorphism (SNP) microarrays to genetically map recessive disorders to large autozygous haplotype blocks (mean = 4.4 Mb) that contain many genes (mean = 79). For some, uninformative mapping or large gene lists preclude disease-gene identification by Sanger sequencing. Seven such conditions were selected for exome sequencing at the Broad Institute; all had been previously mapped at the CSC using low density SNP microarrays coupled with autozygosity and linkage analyses. Using between 1 and 5 patient samples per disorder, we identified sequence variants in the known disease-causing genes SLC6A3 and FLVCR1, and present evidence to strongly support the pathogenicity of variants identified in TUBGCP6, BRAT1, SNIP1, CRADD, and HARS. Our results reveal the power of coupling new genotyping technologies to population-specific genetic knowledge and robust clinical data.

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Geographical breakdown

Country Count As %
United States 2 <1%
Netherlands 1 <1%
Brazil 1 <1%
France 1 <1%
United Kingdom 1 <1%
South Africa 1 <1%
Unknown 235 97%

Demographic breakdown

Readers by professional status Count As %
Researcher 49 20%
Student > Ph. D. Student 38 16%
Student > Master 24 10%
Student > Bachelor 23 10%
Other 16 7%
Other 46 19%
Unknown 46 19%
Readers by discipline Count As %
Agricultural and Biological Sciences 71 29%
Medicine and Dentistry 47 19%
Biochemistry, Genetics and Molecular Biology 46 19%
Neuroscience 10 4%
Nursing and Health Professions 4 2%
Other 13 5%
Unknown 51 21%