Autozygosity Mapping with Exome Sequence Data

Ian M. Carr, Sanjeev Bhaskar, James O' Sullivan, Mohammed A. Aldahmesh, Hanan E. Shamseldin, Alexander F. Markham, David T. Bonthron, Graeme Black, Fowzan S. Alkuraya, James O'Sullivan

    Research output: Contribution to journalArticlepeer-review


    Autozygosity mapping is a powerful method for the identification of recessively inherited disease genes using small inbred families. Typically, microarray SNP genotype data are first used to identify autozygous regions as extended runs of homozygous genotypes. Next, candidate disease loci are found by defining regions that are autozygous in all affected patients. Finally, the disease gene is identified by sequencing the genes within the candidate disease loci. However, with the advent of massively parallel sequencing, it is now possible to sample or to completely sequence an individual's genome, or, more commonly, exome. This opens up the possibility of concurrently defining autozygous regions and identifying possibly deleterious sequence variants, using data from a single sequencing experiment. Consequently, we have developed a set of computer programs that identify autozygous regions using exome sequence data. These programs derive their genotyping data either by the ab initio detection of all sequence variants or by the assessment of 0.53 million known polymorphic positions within each exome dataset. Using genotype data derived solely from exome sequence data, it was possible to identify the majority of autozygous regions found by microarray SNP genotype data. © 2012 Wiley Periodicals, Inc.
    Original languageEnglish
    Pages (from-to)50-56
    Number of pages6
    JournalHuman Mutation
    Issue number1
    Publication statusPublished - Jan 2013


    • Autozygosity mapping
    • Bioinformatics
    • Exome sequencing
    • Software


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