FB2024_03 , released June 25, 2024
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Citation
Comeron, J.M., Reed, J., Christie, M., Jacobs, J.S., Dierdorff, J., Eberl, D.F., Manak, J.R. (2016). A Mismatch EndoNuclease Array-Based Methodology (MENA) for Identifying Known SNPs or Novel Point Mutations.  Microarrays (Basel) 5(2): E7.
FlyBase ID
FBrf0233394
Publication Type
Research paper
Abstract
Accurate and rapid identification or confirmation of single nucleotide polymorphisms (SNPs), point mutations and other human genomic variation facilitates understanding the genetic basis of disease. We have developed a new methodology (called MENA (Mismatch EndoNuclease Array)) pairing DNA mismatch endonuclease enzymology with tiling microarray hybridization in order to genotype both known point mutations (such as SNPs) as well as identify previously undiscovered point mutations and small indels. We show that our assay can rapidly genotype known SNPs in a human genomic DNA sample with 99% accuracy, in addition to identifying novel point mutations and small indels with a false discovery rate as low as 10%. Our technology provides a platform for a variety of applications, including: (1) genotyping known SNPs as well as confirming newly discovered SNPs from whole genome sequencing analyses; (2) identifying novel point mutations and indels in any genomic region from any organism for which genome sequence information is available; and (3) screening panels of genes associated with particular diseases and disorders in patient samples to identify causative mutations. As a proof of principle for using MENA to discover novel mutations, we report identification of a novel allele of the beethoven (btv) gene in Drosophila, which encodes a ciliary cytoplasmic dynein motor protein important for auditory mechanosensation.
PubMed ID
PubMed Central ID
PMC5003483 (PMC) (EuropePMC)
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Secondary IDs
    Language of Publication
    English
    Additional Languages of Abstract
    Parent Publication
    Publication Type
    Journal
    Abbreviation
    Microarrays (Basel)
    Title
    Microarrays
    ISBN/ISSN
    2076-3905
    Data From Reference
    Alleles (1)
    Genes (1)