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  Deep sequencing to reveal new variants in pooled DNA samples

Out, A., van Minderhout, I., Goeman, J., Ariyurek, Y., Ossowski, S., Schneeberger, K., et al. (2009). Deep sequencing to reveal new variants in pooled DNA samples. Human Mutations, 30(12), 1703-1712. doi:10.1002/humu.21122.

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 Urheber:
Out, AA, Autor
van Minderhout, IJHM, Autor
Goeman, JJ, Autor
Ariyurek, Y, Autor
Ossowski, S1, Autor           
Schneeberger, K1, Autor           
Weigel, D1, Autor                 
van Galen, M, Autor
Taschner, PEM, Autor
Tops, CMJ, Autor
Breuning, MH, Autor
van Ommen, G-JB, Autor
den Dunnen, JT, Autor
Devilee, P, Autor
Hes, FJ, Autor
Affiliations:
1Department Molecular Biology, Max Planck Institute for Developmental Biology, Max Planck Society, ou_3375790              

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 Zusammenfassung: We evaluated massive parallel sequencing and long-range PCR (LRP) for rare variant detection and allele frequency estimation in pooled DNA samples. Exons 2 to 16 of the MUTYH gene were analyzed in breast cancer patients with Illumina's (Solexa) technology. From a pool of 287 genomic DNA samples we generated a single LRP product, while the same LRP was performed on 88 individual samples and the resulting products then pooled. Concentrations of constituent samples were measured with fluorimetry for genomic DNA and high-resolution melting curve analysis (HR-MCA) for LRP products. Illumina sequencing results were compared to Sanger sequencing data of individual samples. Correlation between allele frequencies detected by both methods was poor in the first pool, presumably because the genomic samples amplified unequally in the LRP, due to DNA quality variability. In contrast, allele frequencies correlated well in the second pool, in which all expected alleles at a frequency of 1% and higher were reliably detected, plus the majority of singletons (0.6% allele frequency). We describe custom bioinformatics and statistics to optimize detection of rare variants and to estimate required sequencing depth. Our results provide directions for designing high-throughput analyses of candidate genes.

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 Datum: 2009-12
 Publikationsstatus: Erschienen
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 Ort, Verlag, Ausgabe: -
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 Identifikatoren: DOI: 10.1002/humu.21122
PMID: 19842214
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Titel: Human Mutations
  Andere : Hum Mut
Genre der Quelle: Zeitschrift
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Ort, Verlag, Ausgabe: New York, N.Y. : Wiley-Liss
Seiten: - Band / Heft: 30 (12) Artikelnummer: - Start- / Endseite: 1703 - 1712 Identifikator: ISSN: 1059-7794
CoNE: https://pure.mpg.de/cone/journals/resource/954925597586